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Disparities in antipsychotic medication use Puyat, Joseph Hernandez 2011

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Disparities in Antipsychotic Medication Use by  Joseph Hernandez Puyat  A thesis submitted in partial fulfillment of the requirements for the degree of  Master of Science in The Faculty of Graduate Studies (Health Care and Epidemiology)  The University of British Columbia (Vancouver)  July 2011  © Joseph Hernandez Puyat, 2011  Abstract Objectives: To examine ethnic and income-related disparities in the use of antipsychotic medication by conducting a systematic review of the related literature and a secondary data analysis. Methods: The review was conducted using a protocol developed to systematically search, select and review peer-reviewed articles on ethnic disparities in antipsychotic use. Study selection and data abstraction were performed by two independent reviewers. The secondary data analysis was conducted to examine income-related disparities in antipsychotic use in three cohorts. The first cohort was comprised of 19 to 64-year olds who had a recorded schizophrenia diagnosis. Income-related differences in the essential use of antipsychotics were assessed in this cohort. The second cohort was comprised of seniors (65 years and older) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis. The third cohort was of children and youth (18 years and younger) who had no recorded schizophrenia or bipolar disorder diagnosis. Income-related differences in the potentially inappropriate use of antipsychotics were studied in these last two cohorts. Disparities in antipsychotic use were assessed using logistic regression, adjusting for factors that influence medicine use (i.e., age, sex, health status, relevant diagnoses and residence in urban areas). Results: The systematic review found no consistent evidence of ethnic disparities in the receipt of antipsychotic treatment. However, among those who were treated, ethnic minorities were found to be consistently less likely than non minorities to receive the newer type of antipsychotics. Results of the secondary data analyses indicate that the odds of essential antipsychotic use were lower in low-income individuals than those with higher incomes. Odds of exposure to potentially inappropriate antipsychotic use, on the other hand, were higher among low-income individuals and seniors in long-term care. Conclusion: There is evidence of persistent disparities in the use of antipsychotic medication. Periodic examination and studies that identify causal factors and effective interventions are needed to reduce disparities.  ii  Preface The research presented in this thesis was conceptualized, conducted and written by Joseph Puyat (JP) with the assistance, guidance and critical feedback from the members of his thesis committee – Drs. Steve Morgan, Michael Law, Sabrina Wong and Jason Sutherland. JP conducted and completed the systematic review with help from his thesis committee members and colleagues from the UBC Centre for Health Services Policy and Research (CHSPR). JP developed the protocol, performed independent reviews and data abstraction, and wrote the entire systematic review chapter. CHSPR information specialist, Devon Greyson, helped develop the literature search parameters and performed the actual electronic database searches. Drs. Steve Morgan and Mike Law and CHSPR research associates, Jamie Daw and Colleen Cunningham, acted as second reviewers, adjudicators and data abstractors. JP designed the study, performed the specified analyses and wrote the chapter on income-related disparities in antipsychotic medication use. The study was conducted as part of Dr. Steve Morgan’s research programme on equity in access to prescription drugs. Ethics approval was granted by the Behavioural Research Ethics Board at the University of British Columbia (certificate number: H10-01058). Data access permissions were provided by the BC Ministry of Health Services and the PharmaNet Stewardship Committee. The preparation and submission of data access request to Population Data BC (PopData BC) was facilitated by Gillian Hanley and PopData BC staff. CHSPR programmer, Lixiang Yan, performed the data extraction and de-identification in accordance with existing confidentiality and privacy regulations.  iii  Table of Contents Abstract ............................................................................................................................................... ii Preface ............................................................................................................................................... iii Table of Contents ........................................................................................................................... iv List of Tables .................................................................................................................................... vi List of Figures ................................................................................................................................ vii List of Abbreviations .................................................................................................................... ix Glossary .............................................................................................................................................. x Acknowledgements ...................................................................................................................... xi 1  Introduction ............................................................................................................................ 1 1.1 1.2 1.3  2  Racial and ethnic disparities in antipsychotic drug use: a systematic review of the literature............................................................................... 6 2.1 2.2  2.3  2.4 2.5  3  Research objectives............................................................................................................. 2 Thesis outline ........................................................................................................................ 3 Brief background on schizophrenia and antipsychotics...................................... 3 1.3.1 Schizophrenia ........................................................................................................ 3 1.3.2 Antipsychotics ....................................................................................................... 4  Introduction ........................................................................................................................... 6 Methods.................................................................................................................................... 8 2.2.1 Search strategy ...................................................................................................... 8 2.2.2 Inclusion criteria .................................................................................................. 8 2.2.3 Study selection process ..................................................................................... 9 2.2.4 Data collection ....................................................................................................... 9 2.2.5 Analysis ................................................................................................................. 10 Results ................................................................................................................................... 10 2.3.1 Racial or ethnic disparities in the use versus non use of antipsychotic drugs ..................................................................................... 12 2.3.2 Racial or ethnic disparities in the use of atypical versus typical antipsychotic medication ................................................. 14 Discussion ............................................................................................................................ 14 Conclusions.......................................................................................................................... 17  Income-related disparities in antipsychotic use: an analysis of linked administrative data ....................................................................................... 33 3.1 3.2  Introduction ........................................................................................................................ 33 Methods................................................................................................................................. 35 3.2.1 Study cohorts ...................................................................................................... 35 iv  3.3  3.4 3.5  4  3.2.2 Variables of interest ......................................................................................... 37 3.2.3 Analysis ................................................................................................................. 39 Results ................................................................................................................................... 40 3.3.1 Essential antipsychotic use ........................................................................... 40 3.3.2 Potentially inappropriate antipsychotic use in seniors with dementia..................................................................................... 41 3.3.3 Potentially inappropriate antipsychotic use in children and youth ............................................................................................ 42 Discussion ............................................................................................................................ 43 Conclusions.......................................................................................................................... 45  Conclusion ............................................................................................................................ 63 4.1 4.2  4.3  4.4  Summary of findings ........................................................................................................ 63 Strengths and limitations .............................................................................................. 65 4.2.1 Systematic review of ethnic disparities ................................................... 65 4.2.2 Analysis of income-related disparities ..................................................... 66 Recommendations ............................................................................................................ 68 4.3.1 Recommendations for future research .................................................... 68 4.3.2 Recommendations for initiatives that may reduce disparities ............................................................................................................. 69 Conclusions.......................................................................................................................... 71  References ...................................................................................................................................... 72 Appendices ..................................................................................................................................... 79 A. B. C. D.  Systematic review search strategy ............................................................................ 79 Systematic review data collection form................................................................... 82 List of typical and atypical antipsychotics found in PharmaNet in 2005 .......................................................................................................... 86 Public drug coverage in BC ........................................................................................... 87  v  List of Tables Table 2-1  Example search strategy ................................................................................ 18  Table 2-2  Inclusion/exclusion criteria ......................................................................... 19  Table 2-3  Design and sample/population characteristics of the studies included in the systematic review. ............................................ 20  Table 3-1  Descriptive characteristics of the cohort of adults (19 to 64 years) who had a recorded schizophrenia diagnosis in 2004 or 2005 ............................................................................. 47  Table 3-2  Essential antipsychotic use by income and other covariates among adults (19 to 64) who had a recorded schizophrenia diagnosis in 2004 or 2005 .......................... 48  Table 3-3  Descriptive characteristics of the cohort of seniors (≥65 years) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis ........................................ 49  Table 3-4  Potentially inappropriate antipsychotic use by income and other covariates among seniors (≥65 years) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis ........................................ 50  Table 3-5  Descriptive characteristics of the cohort of children and youth (≤18 years) who had no recorded schizophrenia or bipolar disorder diagnosis ........................................ 51  Table 3-6  Potentially inappropriate antipsychotic use by income and other covariates among children and youth (≤18 years) who had no recorded schizophrenia or bipolar disorder diagnosis ........................................ 52  vi  List of Figures Figure 2-1 Study selection and review process .......................................................... 27 Figure 2-2 Ethnic disparities in the use versus non use of any antipsychotics ..................................................................................................... 28 Figure 2-3 Ethnic disparities in the use versus non use of atypical antipsychotics ................................................................................... 29 Figure 2-4 Ethnic disparities in the use versus non use of typical antipsychotics ...................................................................................... 30 Figure 2-5 Ethnic disparities in the use versus non use of clozapine ............................................................................................................... 31 Figure 2-6 Ethnic disparities in the use of atypical versus typical antipsychotics ...................................................................................... 32 Figure 3-1 Selection process for the cohort of adult individuals (19 to 64 years) who had a recorded schizophrenia diagnosis ............................................................................................................... 53 Figure 3-2 Selection process for the cohort of seniors (≥65 years) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis ........................................ 54 Figure 3-3 Selection process for the cohort of children and youth (≤18 years) who had no recorded schizophrenia or bipolar disorder diagnosis ........................................ 55 Figure 3-4 Crude prevalence of essential antipsychotic use among individuals (19 to 64 years) who had a recorded schizophrenia diagnosis ............................................................. 56 Figure 3-5 Crude prevalence of potentially inappropriate antipsychotic use among seniors (≥65 years) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis ............................................................................ 57 Figure 3-6 Crude prevalence of potentially inappropriate antipsychotic use among children and youth (≤18 years) who had no recorded schizophrenia or bipolar disorder diagnosis ............................................................................ 58 Figure 3-7 Essential antipsychotic use by income among adults who had a recorded schizophrenia diagnosis ...................................... 59  vii  Figure 3-8 Potentially inappropriate antipsychotic use by income among community-dwelling seniors who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis ............................................................................ 60 Figure 3-9 Potentially inappropriate antipsychotic use by income among long-term care seniors who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis ............................................................................................ 61 Figure 3-10 Potentially inappropriate antipsychotic use by income among children and youth who had no recorded schizophrenia or bipolar disorder diagnosis ............................................................................................................... 62  viii  List of Abbreviations ATC  Anatomical Therapeutic Chemical  ACG  Adjusted Clinical Groups  ADG  Aggregated Diagnostic Groups  BC  British Columbia  CHSPR  Centre for Health services and Policy Research  CI  Confidence Interval  ICD  International Classification of Diseases  MSP  Medical Services Plan  NZ  New Zealand  NL  Netherlands  OR  Odds Ratio  UBC  University of British Columbia  UK  United Kingdom  US  United States  WHO  World Health Organization  ix  Glossary Antipsychotics – psychiatric drugs used primarily for the treatment of schizophrenia and psychotic disorders Atypical antipsychotics – newer (second-generation) type of antipsychotics identified by practice guidelines as first-line therapy for schizophrenia Bipolar disorder – severe mental disorder characterized by mania, with or without the presence of depressive episodes Disparities – differences in health status or care that are not attributable to differences in clinical need Ethnicity – a concept pertaining to perceived membership in groups by virtue of shared ancestry, language or culture Race – socially-constructed categories of people based on physical characteristics Schizophrenia – a severe mental disorder characterized by acute disturbances in thought, affect and behaviour Typical antipsychotics – older (first-generation) type of antipsychotics  x  Acknowledgements I am indebted to a number of people who all made it possible and a pleasure to complete this work. My deepest gratitude goes first to my supervisor, Steve Morgan, for his support, guidance and encouragement. I can never thank him enough for the rich and supportive training environment he provided over the past couple of years. I am also honoured to have Mike Law, Sabrina Wong and Jason Sutherland in my thesis committee. My work has greatly benefited from their invaluable critique and feedback. I am grateful for the opportunity to interact with and the assistance I received from the knowledgeable and passionate members of the CHSPR drug research team. I would like to especially thank Colleen Cunningham, Gillian Hanley and Lixiang Yan for their assistance in data access and analysis; Jamie Daw and Devon Greyson for their help in the systematic review; and Yuko Kawasumi, Karen Orr and Deborah Heard for providing helpful feedback on my pre-defence presentation. I would like to thank Sam Sheps and Isabella Lossinger from the Western Regional Training Centre for allowing me to participate in the training program and for the financial support. I also acknowledge the assistance provided by Ruth Lavergne, Beverley Biggs and Matthew Queree in proofreading and copy editing my final draft; however, all errors and omissions in the final work remain my responsibilty. Finally, I thank my parents, Joe and Libby, and my children, Matt and Rachel, for the unconditional love that sustained me through the most challenging times.  xi  1  Introduction Concerns about unequal access to a breakthrough drug for the treatment  of schizophrenia and other psychotic disorders have generated interest and several studies on ethnic disparities in antipsychotic treatment. Many of the earlier investigations have focused on racial or ethnic differences in the pharmacokinetic response to antipsychotics as well as in the search for biologically plausible mechanisms that could explain these variations.1 While the existing body of research on ethnic or race-based disparities in antipsychotic medicine use has increased steadily over the years, the growth in knowledge regarding income-based disparities has been sluggish, partly because of the overall lack of attention that has been paid to the examination of the effect of socioeconomic status on health.2 In the case of antipsychotic medication use, the lack of income-based analyses is regrettable since schizophrenia is strongly linked to socioeconomic status.3 This gap in knowledge seriously limits efforts to improve this patient group’s access to essential health services. The examination of these two determinants of disparities in access to an essential mental health treatment was the overarching theme that guided the research described in this thesis. As important factors that contribute to health disparities, ethnicity and socioeconomic status were given equal importance and were regarded as having independent effects on health and access to essential health care. This approach was taken in recognition of the presumption that both determinants need to be addressed to reduce health disparities since the reduction in or elimination of one source does not always bring about the same effect on the other.4  1  1.1  Research objectives In spite of the interest and the amount of research that have accumulated  over the past three decades on ethnic and racial disparities in antipsychotic treatment, studies that summarize the state of knowledge in the area have been scarce. Previous syntheses focused mostly in the area of ethnopsychopharmacology5-8 and no prior synthesis was found that specifically examined ethnic differences in antipsychotic drug use. To fill this research gap, and as the first objective of this thesis, a systematic review was conducted to: 1) Gather and synthesize the existing evidence from peer-reviewed scientific literature on racial and ethnic disparities in the use of antipsychotic medication. In contrast to the relatively extensive knowledge base developed around ethnicity and race-based disparities in antipsychotic use, there is a dearth of studies that focus on socioeconomic status. As a contribution to current efforts at examining income-based disparities in use and as its second objective, this thesis aimed to: 2) Examine differences in two facets of antipsychotic medicine use – essential and potentially inappropriate use – across different levels of a commonly used measure of socioeconomic status (income). The examination of income-related disparities was first conducted in light of antipsychotic medicine’s role as an essential treatment for schizophrenia. In this view, higher levels of antipsychotic use that are consistent across all income levels were viewed as desirable. A complementary analysis was conducted to examine income-related disparities in the potentially inappropriate use of antipsychotic medication. In this second facet of antipsychotic medicine use,  2  lower levels of use were regarded as desirable and disparities in use were seen as income-related inequalities in exposure to the drug’s potential adverse effects.  1.2  Thesis outline This thesis is comprised of four sections, including this introduction. The  second chapter is composed of the systematic review of the peer-reviewed scientific literature on racial and ethnic disparities in the use of antipsychotic medication. The third chapter is a presentation of the analyses on incomerelated disparities in the essential and potentially inappropriate use of antipsychotic medicine. The rationale, methods, discussions, and conclusions for these two independent studies are presented in their respective chapters. The last chapter concludes this thesis with a summary of key findings and a discussion of the study’s strengths and limitations and some recommendations.  1.3  Brief background on schizophrenia and antipsychotics  1.3.1 Schizophrenia Schizophrenia is a severe and persistent form of mental illness characterized by profound disturbances in thinking and feeling which severely impair social and occupational functioning. The wide range of symptoms used in diagnosing this condition include auditory and visual hallucinations, delusions, disorganized thinking and speech, grossly disorganized behaviour (e.g., extreme lack of hygiene, dressing inappropriately), catatonic behaviours, reduction in the range and intensity of emotional expression, lessening of speech fluency and productivity and reduction in goal-directed behaviour.9 Although advances in the understanding of the neurobiochemical processes associated with schizophrenia have been made in the past few decades, the aetiology of the  3  disorder remains largely unknown.10 At present, there is no cure for this illness, although the symptoms are usually treated and respond well to medications.11 In the US and Canada, around one percent of individuals, 18 years and older, are estimated to be living with schizophrenia.10,11 In British Columbia, the yearly proportion of individuals who received a diagnosis of schizophrenia while receiving ambulatory, hospital, or community mental health treatment ranged from 0.42% to 0.45% between the years 1996 and 1999.12 Treated prevalence varied across health service delivery areas with Vancouver (0.64%) registering the highest rate in 1996-97 and the relatively more affluent North Shore-Coast Garibaldi (0.23% in 1998-99) and Richmond (0.25% in 1998-99) registering the lowest rates in the period examined.12 The BC prevalence is likely to be a conservative estimate given that the study was based on administrative data which do not record cases who did not seek treatment in the years examined. Aside from the extreme human suffering schizophrenic disorders impose on individual patients and their families, the disorder also results in substantial economic burden. In 2004, schizophrenia was estimated to have resulted in direct healthcare and non-healthcare costs of CAN$2.02 billion, and, productivity, morbidity and mortality loss of CAN$4.83 billion, for a total cost of about CAN$6.85 billion.13 1.3.2 Antipsychotics Antipsychotics are prescription drugs (e.g., haloperidol, risperidone, olanzapine, etc.) used primarily to treat the clinical symptoms of schizophrenia and other psychotic disorders.14,15 Off-label, they are also used for conditions such as Tourette’s syndrome and the behavioural and psychological symptoms of dementia (BPSD).16 Antipsychotics were first discovered in the early part of the 1950s by drug developers experimenting with pharmaceutical adjuncts for postsurgical 4  shock treatment. In the 1990s, a newer class of antipsychotics, also known as the atypical antipsychotics, were introduced and later became widely used. Many clinicians believe these newer medications are better in producing cognitive and functional improvements and have lower risks of causing movement disorders.17 More recent studies suggest that atypical antipsychotics are likely to be just as effective as the older antipsychotics. In addition, atypical antipsychotics have been associated with increased risks of cerebrovascular events, metabolic side effects, upper respiratory infections and death.18-21 In BC, the use of antipsychotic drugs among individuals aged 20 years and older has increased dramatically from 13.5 per thousand in 1997-98 to 25 per thousand in 2005-06. 22 The increase in rates is driven by the higher use of the more expensive atypical antipsychotics. Older individuals (75 years and older) and women appear to have disproportionately higher rates of use.22 Among children below the age of 15, use has also increased over the past few years.23  5  2  Racial and ethnic disparities in antipsychotic drug use: a systematic review of the literature  2.1  Introduction The serendipitous discovery of the first antipsychotic drug,  chlorpromazine, in the early part of 1950s paved the way for a new era in psychiatric care. Since then the pharmacological treatment of mental disorders successfully displaced controversial procedures like prefrontal lobotomy and electroconvulsive shock therapy. With antipsychotic therapy, patients experienced dramatic reduction in symptoms and improvement in overall function and quality of life, consequently enabling them to be integrated back to the community. Unfortunately, treatment with chlorpromazine and similar first generation antipsychotics produced very unpleasant side effects (e.g. extrapyramidal symptoms, tardive dyskinesia and other related movement disorders) that discouraged many patients from continuing with their regimen. A few decades later, a new generation of antipsychotics, known as atypical antipsychotics, were developed and became widely used. These drugs were found to have comparable efficacy to earlier antipsychotics, but without the often irreversible movement disorders associated with typical antipsychotic use.17 The earliest of these atypical antipsychotics was clozapine, a medication that was found to be superior to chlorpromazine and haldol24 and which is now considered to be an effective medication for treatment-resistant schizophrenia.25 Clozapine use, however, requires enrolment in a registry of patients who must submit to regular blood work to detect the onset of the drug’s potentially fatal side effect – agranulocytosis (fatal lowering of white blood cells). Other atypicals (e.g., risperidone, olanzapine, and quetiapine) were later developed which do not have the risk profiles of the typical antipsychotics or clozapine, but  6  carry a host of other health risks such as cerebrovascular events, metabolic syndrome, upper respiratory infections, and increased mortality.18-21 Notwithstanding potential adverse effects, antipsychotic therapy is now regarded as an essential component of today’s treatment programs for schizophrenia and bipolar disorders. Clinical practice guidelines clearly identify pharmacotherapy, particularly atypical antipsychotics, as first-line treatment for acute and chronic schizophrenia.14,15,26-30 Because of these drugs’ demonstrated efficacy in reducing symptoms as well as in the prevention of relapse and re-hospitalization,31,32 it is imperative that patients with conditions that merit treatment with these drugs experience no barriers in obtaining them. Similar to disparities in access to other important health services, the presence of disparities in the use of antipsychotic medication could indicate poor care quality. Health systems need to be concerned about these disparities as their presence either point to underlying inequalities in the provision of care or to potential disparities in mental health outcomes.33 An Institute of Medicine report, which has documented persistent disparities across a wide range of medical conditions and health care services, defined disparities in health care as “... racial or ethnic differences in the quality of health care that are not due to access-related factors or clinical needs, preferences, and appropriateness of intervention.”34 Since the release of the report, other studies have been conducted to uncover evidence of disparities that have not been previously addressed. In line with these efforts, we conducted this review to systematically gather and synthesize the available evidence regarding racial and ethnic disparities in the use of antipsychotic medication.  7  2.2  Methods  2.2.1 Search strategy We searched the following electronic subscription databases to identify potentially relevant studies: CINAHL (Ebsco), EMBASE (OvidSP), International Pharmaceutical Abstracts (OvidSP), MEDLINE (OvidSP), PsycINFO (Ebsco), ScienceDirect, and Web of Science (Thompson Reuters). The electronic database search was implemented between November 29 and December 1, 2010 by a master’s-trained information specialist (DG). The search parameters used a combination of subject headings and keywords for ethnic or racial groups, and those for antipsychotic agents and specific antipsychotic medications (see Table 2-1 for an example of the search parameters). 2.2.2 Inclusion criteria We developed a review protocol detailing the inclusion criteria and the study selection process that guided this review. Specifically, we included studies that report measures of prevalence or disparity in the use of antipsychotic drugs in at least two clearly defined racial or ethnic groups drawn from the general population or from specific subpopulations (e.g., defined by disease category, demographics, socio-economic status or health insurance coverage) in any treatment setting (inpatient, outpatient, or both). In addition, we only included studies that had a primary focus on ethnic or racial disparities with adjustments for the effects of any factors known to influence medicine use such as age, sex, health status, income, insurance, and related diagnosis. Because of this, only studies that reported differences across ethnic groups in the likelihood of using antipsychotic medicine in terms of adjusted prevalence, odds ratios or probit coefficients were included. Studies that reported only ethnic differences in dose, adherence or compliance rates, initiation rates, route of administration (oral versus depot) and prevalence of polypharmacy were excluded. Also excluded 8  were clinical trials, case studies, literature reviews, articles from non-peer reviewed periodicals, commentaries and letters to the editor, books and book reviews, preliminary reports, meetings and conference proceedings, and studies from the grey literature. Literature searches were limited to peer-reviewed studies published in English between January 1, 1980 and December 30, 2010. The full inclusion criteria are detailed in Table 2-2. 2.2.3 Study selection process Study selection was done in three stages: title review, abstract review and full-text review. In the first two stages, JP and SM independently screened titles and reviewed all abstracts. Entries that were deemed relevant by at least one of these reviewers were included in the subsequent stages. In the final selection process (full-text review), JP and JD reviewed the full-texts of articles that were included in the abstract review. Only those studies that were considered potentially-relevant by both reviewers were included in the pool of studies for data abstraction and analysis. Although a third author (ML) was available to help resolve differences in inclusion assessment, consensus was achieved after discussion between the two full-text reviewers. Inter-rater reliability was assessed by calculating kappa coefficients between reviewers at each stage. 2.2.4 Data collection A data collection form (Appendix B) for extracting data from the included studies was piloted by five reviewers (JP, JD, CC, ML and SM) using two studies drawn at random from the pool of included studies. After revision, the form was used to extract data from each study by at least two reviewers based on the following allocation: JP – 100%; JD – 25%; CC – 25%, ML – 12.5% and SM – 12.5%. Any disagreements in data abstractions were resolved by consensus. The following data were extracted from each study: sample size, sampling frame, prescription data source, year(s) of data collection, covariates used for 9  adjustment, crude prevalence and measures of disparity, specifically, adjusted odds ratios. Study authors were contacted via email for clarification or when some of the data were not provided in the article. 2.2.5 Analysis Although adjusted odds ratios from most of the studies included in this review were available, important differences in sampling methodology, prescription data sources and time periods precluded us from performing a meta-analysis. Thus, data synthesis was performed by grouping the obtained odds ratios by type of comparison (use versus non use of antipsychotics or receipt of atypical versus typical antipsychotic among those that received the treatment), type of antipsychotics (any antipsychotic, atypical, typical and clozapine), racial or ethnic categories (white, African American, Latino, and others) and treatment setting (inpatient, outpatient, or both). Authors of published studies were not consistent in their use of ethnic or racial categories. To maintain parsimony, studies that reported results for “Blacks” were coded as African Americans while those that reported results for “Hispanics” were coded as Latinos. Also, the “non-Blacks” or “non-Hispanics” categories examined in some studies were coded as whites.  2.3  Results A total of 1,825 unique citations were obtained and subjected to the  three-stage review process. In the first stage of the study selection process, title reviewers read and identified 532 (29% of the unique citations) potentially relevant studies (Agreement: 85.8%; Kappa: 0.59, 95% CI=0.55-0.64). Abstracts of these studies were then reviewed in the next stage for inclusion in the full-text review which returned 121 studies (Agreement: 96.6%; Kappa: 0.91, 95% CI=0.86-0.95). In the final selection process (full-text review), 28 studies were  10  found to have met our inclusion criteria and subsequently constituted our final set of studies (Agreement: 96.7%; Kappa: 0.92, 95% CI=0.83-0.99). Differences in assessments were resolved after discussion between the two primary reviewers without involving the third reviewer. Key features of each study that met our inclusion criteria are presented in Table 2-3. Of the 28 studies, 25 were from the US and the rest were from the Netherlands,35 New Zealand36 and United Kingdom.37 Only one study38 was based on data collected before 1989 – the year the first atypical antipsychotic, clozapine, was introduced in the market; the rest of the studies were based on data collected from 1998 onwards. Sixty one percent (n=17) of the included studies used prescription drug data from administrative sources 35,37,39-53 while 32% (n=9) and seven percent (n=2) utilized medical chart reviews36,38,54-60 and survey/interviews,60,61 respectively. Only a small number of studies assessed the use of antipsychotic medication in inpatient or hospital settings38,48,58,59 (n=4, 14%); most of the studies examined use in either outpatient36,37,39,41,42,45,46,49,5254,56,61  (n=13, 47%) or all treatment settings35,40,43,44,47,50,51,55,57,60,62 (n=11, 40%).  Population-based studies comprised more than half (n=18, 64%) of the studies that satisfied our inclusion criteria; the rest used purposive46,55-57,60 (n=5, 18%), random49,54,62 (n=3, 11%) and convenience (n=2, 7%) samples. The majority (n=23, 82%) of the included studies examined antipsychotic medication use among patient groups diagnosed with severe mental disorders such as schizophrenia (n=20) and bipolar disorders (n=2). Most of the studies examined populations that included only the adult population (individuals between the ages of 19 and 60 years); there was only one that looked at the children and youth population,53 and two that examined medication use specifically among individuals aged 60 years and older.45,49  11  White, African American and Latino ethnicities were the groups most frequently examined in the 25 US-based studies included in this review. Ethnic groups such as Asian, Maori and Pacific Islanders were examined only in a study conducted in New Zealand (NZ).36 Similarly, Dutch, Moroccan and Turkish ethnicities were examined in the Netherlands (NL) study only.35 We found wide variation in the number and type of covariates used in adjustment for the odds ratio, but the most frequently examined covariates were psychiatric morbidity, age and sex. Only one study included in this review, the NL study, did not control for the effect of psychiatric morbidity either by restricting the analysis to those with mental disorders or including mental disorder diagnoses in the regression model. To maintain uniformity in the reporting of odds ratios in the following summary figures, all odds ratios (OR) were expressed using the majority ethnic group as the reference group. For example, in studies that reported African Americans as the reference group, the reciprocal of the reported odds ratio was calculated to obtain the odds ratio for whites as the reference group. Similarly, typical antipsychotics use was the reference group when reporting results of studies that compare odds of receiving typical versus atypical antipsychotics. Not all studies provided odds ratios and/or confidence intervals when reporting ethnic or racial disparities. When a study merely stated that no ethnic or racial disparities were observed, the study’s OR was plotted in the figures using a value of one with no confidence intervals. Odds ratios that have no confidence interval were plotted using just the point-estimate. 2.3.1 Racial or ethnic disparities in the use versus non use of antipsychotic drugs There were 10 (36%) studies that examined disparities in the use versus non use of any antipsychotics across all treatment settings (Figure 2-2). 12  Significant disparities were reported in four of these studies: two from the US and one each from NZ and NL. One of the US studies analyzed disparities among hospitalized patients diagnosed with schizophrenia and found African Americans marginally less likely than whites to have received any antipsychotic medication.52 The other US study assessed disparity among individuals with bipolar disorders receiving treatment in the community and found African Americans more likely than whites to have used an antipsychotic as adjunct medication.47 The NZ study reported that two ethnic minorities, Maori’s (in 2000 and 2004) and Pacific Islanders (in 2004) were less likely to have used an antipsychotic compared to the reference group (white Europeans).36 In the NL study, the Moroccan and Turkish ethnic groups were reported to have significantly higher odds of use than the Dutch reference group.35 The NL and NZ studies did not control for the presence of medical conditions usually treated with antipsychotic medications. There were six studies that examined ethnic disparities in the use of atypical antipsychotics compared to non use (Figure 2-3). Two US studies40,48 and the NZ study36 reported significant disparities in the likelihood of atypical antipsychotic use. In the two US studies, African Americans were less likely to have received atypical antipsychotic treatment compared to their white counterparts. In the NZ study, Maoris had lower odds of use compared to residents of European ethnicity in 2000, but the trend appears reversed in 2004. Similarly, Pacific Islanders had lower odds of use in 2000 only. There were five studies (n=3, US; n=1 NZ; n=1, UK) that examined ethnic disparities in the use of typical antipsychotics versus non use (Figure 2-4). Two of the three US studies found that African Americans were significantly more likely to receive typical antipsychotics than whites. 38,47 In the NZ study, Maoris were more likely, in 2000, but less likely in 2004, to be treated with typical  13  antipsychotics compared to the reference group (white Europeans). The Pacific Islander group in the NZ study was consistently less likely to receive typical antipsychotic treatment. The three studies that reported ethnic disparities in the use of clozapine versus non use indicate a consistent pattern of significantly low likelihood of clozapine use among ethnic minorities (Figure 2-5). African Americans in the US had about 40%40 to 60%48 less odds of receiving clozapine treatment than their white counterparts. In the NZ study, the Asian, Maori (in 2000 only) and Pacific Islander groups had lower odds of being treated with clozapine. 2.3.2 Racial or ethnic disparities in the use of atypical versus typical antipsychotic medication There were 15 studies, all US-based, that examined the likelihood of being treated with atypical versus typical antipsychotics among the subpopulation of individuals treated with antipsychotics (Figure 2-6). Of these, 12 studies reported odds ratios that were below one, indicating that minorities, such as African Americans and Latinos, were less likely than whites to be treated with atypical antipsychotics. The finding of lower likelihood for these groups was consistent across all treatment settings and types of patient populations. The other three studies also found lower likelihood of use for African Americans and Latinos, but the point-estimates were not statistically significant.39,42,49  2.4  Discussion Our review of studies published over the past few 30 years found neither  large nor consistent ethnic disparities in the receipt versus non-receipt of any antipsychotic treatment. However, among those who had been treated with antipsychotics, we found consistent evidence suggesting that ethnic minorities were less likely than non-minorities to receive atypical antipsychotics.  14  It is possible that the lack of a distinct pattern of disparity in the use versus non use of any antipsychotics reflects genuine absence of ethnic differences in the receipt of any antipsychotic treatment among people with schizophrenia. This interpretation seems consistent with the finding that only four studies reported statistically significant disparities in use. One of these studies reported a marginal difference while another reported a possibly important disparity but from a sample of individuals with bipolar disorders, not schizophrenia. The two other studies (NZ and NL) did not adjust for differences in psychiatric diagnosis; hence, the reported differences, though statistically significant, were likely to be confounded by differences in prevalence of schizophrenia diagnoses. The finding of consistent ethnic differences in the receipt of atypical versus typical antipsychotics merits further investigation. This finding seems to suggest that ethnic minorities received poor care quality when viewed in the context of existing practice guidelines that recommend the use of atypical antipsychotics as first-line treatment for psychotic disorders such as schizophrenia.14,15 Atypical antipsychotics have been regarded as better in improving cognitive functions (i.e., verbal fluency, attention, memory for facts and events) while at the same time have lower risks of causing irreversible movement disorders (i.e., extrapyramidal syndromes and tardive dyskinesia).17 It is also worth examining further if the lower prevalence of atypical use among ethnic minorities may have been motivated by concerns about adverse effects. Previous research has linked prolonged use of atypical antipsychotics with increased risks of cardiovascular events and metabolic syndrome.17 Since epidemiological studies have determined that the prevalence of hypertension and diabetes is higher among African Americans and Latinos,63,64 it is possible that the lower likelihood of atypical antipsychotic use among ethnic minorities  15  may have been inadvertently caused by efforts to minimize these risks. Some authors have hypothesized about this48 but none of the studies we reviewed offered conclusive evidence. The observed lower likelihood of clozapine use among African Americans is a cause for concern.40,48 The disparity has generally been attributed to clinicians’ hesitance to prescribe clozapine to African Americans because of the perception that members of this ethnic group are less likely to adhere to a clozapine regime and also are at greater risk of agranulocytosis.40,48,65 Others challenge this practice. Apparently, the limits established by existing guidelines for safe clozapine use failed to account for the typically normal low counts of white blood cells (benign leukopenia) among African Americans,66,67 thus, effectively limiting their access. The lower likelihood of clozapine use among Asians also deserves further investigation.36 It is possible that previous findings about Asians requiring lower doses of clozapine than whites68 may have prompted some clinicians to consider this particular antipsychotic as too potent for most Asians. This seems consistent with the finding that Asians in San Francisco were found to be less likely to be eligible for clozapine treatment even when the most lenient interpretation of the requirements for use were applied.69 Alternatively, cultural factors may have contributed to the observed disparities. It has been noted, for instance, that beliefs about the act of drawing out blood discouraged some Chinese patients from enrolling in clozapine registries. These patients have expressed concerns that the regular blood monitoring was detrimental to their overall health and vitality.70  16  2.5  Conclusions Our review found neither strong nor consistent ethnic disparities in the  use versus non use of any antipsychotics. However, among those who received antipsychotic treatment, ethnic minorities such as African Americans and Latinos were found to be consistently less likely than members of non minorities to be treated with atypical antipsychotics and more likely to have used typical antipsychotics. Prescribing practices influenced by guidelines regulating the use of antipsychotics and concerns about increased risk of potential adverse events may have contributed to this observed disparity.  17  Table 2-1  Example search strategy  MEDLINE (OvidSP) 1. exp neuroleptic agent/bd, ct, ad, cm, do, it, dt, ih, ia, ce, cv, dl, ig, im, na, ip, tl, iv, po, pa, pr, pe, pd, rc, sc, sb, li, tp, td 2. (Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Benperidol or Bromperidol or Butaperazine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clopenthixol or Clotiapine or Clozapine or Cyamemazine or Dixyrazine or DOGMATIL or Droperidol or Fluanisone or Flupentixol or Fluphenazine or Fluspirilene or Haloperidol or Levomepromazine or Levosulpiride or Loxapine or Melperone or Mesoridazine or Molindone or Moperone or Mosapramine or Olanzapine or Oxypertine or Paliperidone or Penfluridol or Perazine or Periciazine or Perphenazine or Pimozide or Pipamperone or Pipotiazine or Prochlorperazine or Promazine or Prothipendyl or Quetiapine or Remoxipride or Risperidone or Sertindole or Sulpiride or Sultopride or Thiopropazate or Thioproperazine or Thioridazine or Tiapride or Tiotixene or Trifluoperazine or Trifluperidol or Triflupromazine or Ziprasidon or Zotepine or Zuclopenthixol or Methotrimeprazine).mp. 3. 1 or 2 4. exp ethnic difference/ or exp ethnic group/ or exp "ethnic or racial aspects"/ or exp race/ or exp "ethnic, racial and religious groups"/ or exp ethnicity/ 5. 3 and 4 6. limit 5 to (human and english language and yr="1980 -Current")  18  Table 2-2  Inclusion/exclusion criteria  Included studies • Observational studies including: crosssectional, case-control, prospective and retrospective cohort studies • January 1, 1980 to October 31, 2010 • English language  Population  Intervention  • OECD countries  Use of:  • General population  • any antipsychotics • typical and antipsychotics • clozapine  Comparison  Outcome  • At least two clearly defined racial or ethnic groups compared with each other  • Odds ratios or prevalence rates describing ethnic disparities in use  • Ethnicity or race was analyzed as a primary variable with adjustments for factors such as age, sex, health status and income  19  Table 2-3  Design and sample/population characteristics of the studies included in the systematic review.  Study design  Study  Sample/Population characteristics  (Author, Year)  Sampling Frame  Sampling Method  Data collection years  Rx data source  Segal et al., 199638  Inpatients of psychiatric ERs in 4 urban general hospitals in California, US  Convenience  1981-1986  Chart review  Baillargeon & Contreras, 200139  Prisoners in the Texas Dept of Criminal Justice, US  Population  1998  Kuno & Rothbard, 200240  In/outpatient Medicaid recipients, US  Population  1995  Covell et al., 200254  Outpatients of the Connecticut public mental health system, US  Random  1996-1998  N  Sex (%) M/W  Age  60% with psychotic disorders; 9% had to be restrained  442  60/40  np  Administrative  Schizophrenia and other psychotic disorder  4,316  93/7  18+  Administrative  Schizophrenia  2,515  56/44  18-64  Chart review  Schizophrenia, schizoaffective, and psychotic disorders NOS  386  58/42  np  Diagnoses  Covariates  Psychotic disorders; severity of psychiatric disturbance; dangerousness; psychiatric history; physical restraints; hours spent in ER; treatment engagement; optimum time spent on evaluation Age, sex, violent offense, presence of schizophrenia diagnoses or other psychotic disorders Age, sex, insurance (all Medicaid), supplementary security income recipient, psych hospitalization; ER visit; use of intensive case management service; partial hospitalization; medical care; drug or alcohol treatment; depot use Age, sex, SES(education), marital status  20  Study design  Study (Author, Year)  Sampling Frame  Mark et al., 200255  In/outpatient participants of the Schizophrenia Care and Assessment Program (North Carolina site), US  Woods et al., 200361  Outpatients from a Connecticut community mental health centre, US Outpatient Veterans Affairs recipients, US Outpatient participants of the Schizophrenia Patient Outcomes Research Team in Maryland, US  Copeland et al., 200341 Kreyenbuhl et al., 200356  Sample/Population characteristics  Data collection years  Rx data source  Purposive  1997-1999  Chart review  Convenience  2000-2002  Population Purposive  Sampling Method  Covariates  N  Sex (%) M/W  Age  Schizophrenia, schizoaffective and schizophrenifor m  752  65/35  18+  Survey  participants from tardive dyskinesia study and receiving at least 1 AP  501  54/46  np  1998-1999  Administrative  Schizophrenia  69,787  95/5  18+  Age, sex, substance use, bipolar, other psychoses  1994-1996  Chart review  Schizophrenia or schizoaffective  344  36/64  18-64  Age, sex, SES (years of education), health status (medical comorbidity), psychiatric diagnoses (schizo vs. schizoaffective), marital status, state of residence, urban/rural, treatment facility type  Diagnoses  Age, age at onset, sex, insurance, SES (education), Clinical status (PANSS, MADRS and AIMS), schizophrenia (paranoid, undifferentiated and other), marital status, treatment site, physician char (i.e., sex, age, board certification etc.) Age, sex, SES (education), substance abuse or disorder  21  Study design  Study  Sample/Population characteristics  Data collection years  Rx data source  Purposive  1999-2001  Inpatients from New York(?), US  Population  2000  Bagchi et al., 200442  Outpatient Medicaid recipients identified in the New Jersey HIV/AIDS registry, US  Population  1992-1998  Administrative  McFarland et al., 200443  In/outpatient Medicaid recipients in Florida, Oregon and Pennsylvania, US  Population  1997-1998  Administrative  (Author, Year)  Sampling Frame  Mark et al., 200357  In/outpatient participants of the Schizophrenia Care and Assessment Program (North Carolina site), US  Valenti et al., 200358  Sampling Method  Diagnoses  N  Sex (%) M/W  Chart review  Schizophrenia or schizophrenifor m disorders  2,239  62/38  18+  Chart review  Schizophrenic, schizophrenifor m, schizoaffective, psychosis NOS Schizophrenia and HIV  276  54/46  np  350  54/46  18+  Psychotic disorders including schizophrenia and affective and substance use disorders with psychosis  894  39/61  np  Age  Covariates  Age, sex, insurance (Medicare, private, veteran), SES(education), psych dx (affective, undifferentiated, other schizo), veteran, marital status, depot use, adherence, PANSSGP, GAF, QLS,MADRS, CHAMPUS Age and substance abuse diagnosis Age at HIV diagnosis, sex, insurance (Medicare), health status (vital stat as of 1998) county of residence, mode of transmission; year of HIV diagnosis Age, sex, insurance (duration of Medicaid eligibility) and psychiatric diagnosis (affective only, psychosis only, substance only and combinations of all 3)  22  Study design  Study (Author, Year) Sohler et al., 200459  Herbeck et al., 200462  Opolka et al., 200444  Hudson et al., 200545  Sampling Frame  Sampling Method  Sample/Population characteristics  Data collection years  Rx data source  Diagnoses  N  Sex (%) M/W  Age  Covariates  Inpatient participants of the Suffolk County Mental Health Project, Massachusetts, US In/outpatients who received care from psychiatrist members of the American Psychiatric Institute for Research and Education's Practice Research Network, US In/outpatient Medicaid recipients in Texas, US  Population  1989-1995  Chart review  Schizophrenia and other psychosis  501  57/43  15-60  Age, sex, marital status, educational status, occupational status, and insurance status  Random  1997-1999  Survey  not specified, but everyone was treated by psychiatrists and received at least one AP  700  51/49  18 up  Age, sex, insurance, education, schizophrenia and substance use diagnoses, GAF score, previous hospitalization, treatment duration, marital status, region, treatment setting, type of health care plan  Population  1997-1998  Administrative  Schizophrenia  3,583  47/53  21-65  Nursing home residents with Medicaid coverage in Arkansas, US  Population  2001  Administrative  not specified, but everyone were nursing home residents; had at least one AP claim  2,717  26/74  65+  Age, sex, psychiatric diagnoses (bipolar disorder, other mental illness, substance use), region, medication and resource use in the previous 12 months Age, sex and location of nursing home  23  Study design  Study (Author, Year) Van Dorn et al., 200546  Chakos et al., 200660  Kilbourne & Pincus, 200647  Mallinger et al., 200648  Sampling Frame  Sampling Method  Data collection years  Sample/Population characteristics Rx data source  Diagnoses  N  Sex (%) M/W  Age  Outpatient participants of the Schizophrenia Care and Assessment Program (North Carolina site), US In/outpatient participants of the Clinical Antipsychotic Trials of Intervention Effectiveness study, US In/outpatient Veterans Affairs recipients in Pennsylvania, Delaware, West Virginia, Ohio, New Jersey & New York, US  Purposive  1997-1999  Administrative  Schizophrenia  224  64/36  18+  Purposive  2001-2003  Chart review & Interview  Schizophrenia, schizoaffective and depression with schizophrenic features  1,138  77/23  np  Population  2000-2001  Administrative  Bipolar disorders  2,958  89/11  np  Inpatients of the University of Rochester hospital in New York, US  Population  2003-2004  Administrative  Schizophrenia and schizoaffective disorder  456  65/35  18+  Covariates  Sex, insurance, GAF, psychiatric diagnosis (high psychotic symptoms, substance abuse), other (initial treatment setting, visits with a psychiatrist, compliance, arrest history) Lehman QOL interview, SCI DSM-IV Axis I depression, Abnormal Involuntary movement  Age, sex, income (copayment waiver eligibility status) health status (comorbid medical condition), psychiatric diagnoses (bipolar disorder subtype, inpatient/outpatient status), other (marital status) Age, insurance (Medicaid vs. nonMedicaid), SES (education), psychiatric diagnoses, other (living situation)  24  Study design  Study (Author, Year)  Sampling Frame  Sampling Method  Data collection years  Sample/Population characteristics Rx data source  Diagnoses  N  Sex (%) M/W  Age  Jano et al., 200849  Outpatient participants of the Medical Expenditure Panel Survey, US  Random  1996-2004  Administrative & Survey  Schizophrenia, bipolar disorder, anxiety and dementia  551  30/70  60+  Yang et al., 200850  In/outpatient Veterans Affairs recipients in Texas, US  Population  1997-2002  Administrative  Majority (83.4%) had at least one mental illness  8,096  93/7  18+  Wheeler et al., 200836  Outpatients of community health services in Auckland, New Zealand In/outpatient Medicaid recipients in Florida, US  Population  2000 & 2004  Chart review  Schizophrenia and schizoaffective disorder  4,821  np  np  Population  1997-2005  Administrative  Bipolar I disorder  13,497  29/71  Busch et al., 200951  18-64  Covariates  Age, sex, Insurance (private vs. not), SES (income), health status (perceived gen health and perceived mental health), psychiatric diagnosis (anxiety, schizophrenia, bipolar, dementia), other (region, time, metro stat area) Age, sex, health status (physical comorbidities including dyslipidemia and hypertension), psychiatric diagnosis (bipolar, depression, PTSD, schizophrenia, and substance abuse), treatment initiation years Age and sex  Age, sex, insurance (Medicaid eligibility), health status (comorbid conditions that discourage/encourage mood stabilizer prescribing, and encourage antipsychotic prescribing), substance use disorders  25  Study design  Study  Data collection years  Sample/Population characteristics Rx data source  N  Age  Schizophrenia  28,153  47/53  18-64  Administrative  Schizophrenia, bipolar disorders and any psychotic disorders not related to substance abuse  1,694  60/40  16-74  2000-2001  Administrative  Schizophrenia  11,241  62/38  <18  Age, sex, state of residence  2001-2006  Administrative  none  1,220,3 38  47/53  np  Age, sex, SES (income), urbanization  Sampling Frame  Busch et al., 200952  Outpatient nonHMO Medicaid recipients in Florida, US  Population  1996-2001  Administrative  Pinto et al., 201037  Outpatients from 29 out of 54 borough practices contributing data to Lambeth DataNet (primary care database) in London, UK Outpatient Medicaid recipients in North Carolina and Georgia, US In/outpatient Agis (major insurance provider) recipients, Netherlands  Population  2006  Population  Population  Sleath et al., 201053  Wittkampf et al., 201035  Sampling Method  Covariates  Sex (%) M/W  (Author, Year)  Diagnoses  Age, sex, comorbid substance abuse, fiscal year, region of residence, number of months of Medicaid enrolment Age, sex, SES (areabased social deprivation measure)  26  Figure 2-1  Study selection and review process  Unique titles screened for relevance (n= 1,824) Excluded non-relevant titles (n=645) Abstracts reviewed against inclusion criteria (n=532) Excluded abstracts not meeting inclusion criteria (n=411)  Excluded full-texts not meeting inclusion criteria (n=93): • 11 were not original or peer-reviewed studies • 1 was from non-OECD country • 2 had no explicitly identified ethnic groups • 58 had no adjusted disparity measures • 14 were single antipsychotic studies or did not look at antipsychotics • 7 did not examine individual level use of antipsychotics  Full-texts reviewed against inclusion criteria (n=121)  Relevant studies included in data abstraction (n=28)  27  Figure 2-2  Ethnic disparities in the use versus non use of any antipsychotics  Sohler et al. {US, 1989} Sohler et al. {US, 1989} Bagchi et al. {US, 1992} Busch et al. {US, 1996} Busch et al. {US, 1996}  African American  McFarland et al. {US, 1997} Busch et al. {US, 1997} Kilbourne & Pincus {US, 2000} Chakos et al. {US, 2001} Pinto et al. {UK, 2006} Bagchi et al. {US, 1992} Busch et al. {US, 1996}  Latino  Busch et al. {US, 1996} Busch et al. {US, 1997} Wheeler et al. {NZ, 2000}  Asian  Wheeler et al. {NZ, 2004} Wheeler et al. {NZ, 2000}  Maori  Wheeler et al. {NZ, 2004} Wheeler et al. {NZ, 2000}  Moroccan  Wheeler et al. {NZ, 2004} Wittkampf et al. {NL, 2001}  Turkish  Wittkampf et al. {NL, 2001}  Odds Ratio  0.00  0.50  Outpatient  1.00  1.50  2.00  Inpatient ‹Both  28  Figure 2-3  Ethnic disparities in the use versus non use of atypical antipsychotics  Kuno & Rothbard {US, 1995}  McFarland et al. {US, 1997-1998}  African American  Kilbourne & Pincus {US, 2000-2001}  Mallinger et al. {US, 2003-2004}  Pinto et al. {UK, 2006}  Wheeler et al. {NZ, 2000}  Latino Wheeler et al. {NZ, 2004}  Wheeler et al. {NZ, 2000}  Asian Wheeler et al. {NZ, 2004}  Wheeler et al. {NZ, 2000}  Maori Wheeler et al. {NZ, 2004}  Odds Ratio  0.00  0.50  Outpatient  1.00  1.50  2.00  Inpatient ‹Both  29  Figure 2-4  Ethnic disparities in the use versus non use of typical antipsychotics  Segal et al. {US, 1981-1986}  McFarland et al. {US, 1997-1998}  African American Kilbourne & Pincus {US, 2000-2001}  Pinto et al. {UK, 2006}  Wheeler et al. {NZ, 2000 & 2004}  Latino Wheeler et al. {NZ, 2000 & 2004}  Wheeler et al. {NZ, 2000 & 2004}  Asian Wheeler et al. {NZ, 2000 & 2004}  Wheeler et al. {NZ, 2000 & 2004}  Maori Wheeler et al. {NZ, 2000 & 2004}  Odds Ratio  0.00  0.50  Outpatient  1.00  1.50  2.00  Inpatient ‹Both  30  Figure 2-5  Ethnic disparities in the use versus non use of clozapine  Kuno & Rothbard {US, 1995}  African American Mallinger et al. {US, 2003}  Wheeler et al. {NZ, 2000}  Latino  Wheeler et al. {NZ, 2004}  Wheeler et al. {NZ, 2000}  Asian Wheeler et al. {NZ, 2004}  Wheeler et al. {NZ, 2000}  Maori Wheeler et al. {NZ, 2004}  Odds Ratio  0.00  0.50  Outpatient  1.00  1.50  2.00  Inpatient ‹Both  31  Figure 2-6  Ethnic disparities in the use of atypical versus typical antipsychotics Bagchi et al. {US/NJ, 1992}  Kreyenbuhl et al. {US/MD, 1994} Covell et al. {US/CT, 1996} Jano et al. {US/NTL, 1996} Opolka et al. {USA/TX, 1997} Van Dorn et al. {US/NC, 1997} Yang et al. {US/TX, 1997}  African American  Herbeck et al. {US/NTL, 1997} Mark et al. {US/NC, 1997} Baillargeon & Contreras {US/TX, 1998} Baillargeon & Contreras {US/TX, 1998} Copeland et al. {US/NTL, 1998} Mark et al. {US/NC, 1999} Valenti et al. {USA/NY?, 2000} Woods et al. {US/CT, 2000} Hudson et al. {US/AR, 2001} Bagchi et al. {US/NJ, 1992} Covell et al. {US/CT, 1996} Jano et al. {US/NTL, 1996} Opolka et al. {USA/TX, 1997}  Latino  Yang et al. {US/TX, 1997} Mark et al. {US/NC, 1997} Baillargeon & Contreras {US/TX, 1998} Baillargeon & Contreras {US/TX, 1998} Copeland et al. {US/NTL, 1998} Odds Ratio  0.00  0.50  Outpatient  1.00  1.50  2.00  Inpatient ‹Both  32  3  Income-related disparities in antipsychotic use: an analysis of linked administrative data  3.1  Introduction The discovery of the first antipsychotic, chlorpromazine, in the middle of  the twentieth century marks an important milestone in the treatment of severe mental disorders. Through the years, this class of medicines has helped thousands of individuals living with schizophrenia manage the disorder’s symptoms and improve their overall quality of life. Newer drugs have since been developed and are currently specified in many clinical practice guidelines as mainstay treatments for psychotic disorders.14,15 In recognition of the potential of antipsychotic medicines to meet the treatment needs of people with psychotic disorders, the World Health Organization has listed three older generation antipsychotic agents (chlorpromazine, fluphenazine and haloperidol) in its Model List of Essential Medicines, which is a prescriptive document for other countries and institutions.71 More antipsychotic agents are likely to be listed in the future as some of the newer agents are currently under review for inclusion.72 While antipsychotics are deemed essential for the treatment of psychotic disorders, the use of antipsychotic medicines has expanded beyond this indication. Their prescription for a host of other conditions 16 has been criticized on the grounds that such uses are not strongly supported by evidence. Worse, such uses may unnecessarily expose individuals to risks of adverse reactions (e.g., movement disorders, metabolic syndrome, cardiovascular events and death). One example of potentially inappropriate use is the antipsychotic treatment of behavioural and psychological symptoms associated with dementia among seniors. Evidence from systematic reviews of high quality studies 33  indicates that antipsychotic treatment in these patients has limited efficacy, and, results in higher risks of cardiovascular events, weight gain or death.18,73-75 A number of warnings from manufacturers and regulatory agencies were issued in 2005 to discourage such use, which, regrettably, continued to increase in 2007, albeit, at a significantly slower rate.76,77 Another instance of the potentially inappropriate use of antipsychotic medication is its use among children and youth. The rare prevalence78 and lack of consensus regarding the validity of schizophrenic disorder diagnoses among children and youth are among the reasons antipsychotic treatment in this population has been questioned. Another reason is the lack of high quality data supporting its use among children and youth diagnosed with schizophrenic disorders.79 Broadened use of this medication to treat behavioural symptoms associated with attention deficit disorder and hyperactivity is also not backed by strong evidence.16 Even if this medication could provide symptomatic relief from nonpsychotic symptoms, such off-label use still raises serious concerns about early exposure to the medication’s adverse effects (e.g., hormonal, metabolic and cardiovascular) and the potential for more severe and long-term health consequences.80,81 These two facets of antipsychotic use – essential and potentially inappropriate use – are important indicators of care quality that can be examined at the same time using linked health data. We sought to explore socioeconomic disparities in these indicators of quality of care linked to antipsychotic use. Specifically, this analysis addressed two objectives: 1) to examine income-related disparities in essential antipsychotic use among adults with a recorded diagnosis of schizophrenia; and 2) to examine income-related disparities in the potentially inappropriate use of antipsychotics among seniors,  34  children and youth who had no recorded schizophrenia or bipolar disorder diagnosis. At the time we conducted our analyses, we were not aware of studies that examined these aspects of antipsychotic use. This study used data obtained from the Canadian province of British Columbia (BC) where commonly prescribed antipsychotic medications are provided free or at reduced cost to individuals with a demonstrated clinical and financial need (see Appendix C for antipsychotics listed in the formulary). The list of BC residents with enhanced access to these medications include children with severe disabilities, registered mental health clients, recipients of income assistance and residents of long-term care facilities (see Appendix D for a list of the public drug coverage plans).  3.2  Methods We used de-identified linked administrative health care records for  calendar years 2004 and 2005 obtained from a population-based data repository in BC. Data access permissions were granted by the BC Ministry of Health Services and the PharmaNet Stewardship Committee. The Behavioural Research Ethics Board of the University of British Columbia reviewed and provided ethics approval for the project. 3.2.1 Study cohorts In order to assess three patterns of antipsychotic use (one essential and two potentially inappropriate uses) we constructed three mutually exclusive study cohorts from population-based data. In all study cohorts we excluded individuals whose health use data were unlikely to be fully reflected in the claims data we examined. These were individuals who were enrolled in the provincial health registry for less than nine months in a year and those who resided in health service delivery areas that had a high proportion of non-fee-  35  for-service claims. We preformed this to mitigate possible bias in case ascertainment and health status measurement – known issues in claims data analysis.82 We also excluded all individuals with missing data on income and sex to ensure comparability of data. 3.2.1.1 Essential antipsychotic use cohort  Our first cohort included only individuals, aged 19 to 60 years, who had a recorded diagnosis of schizophrenia (Figure 3-1). Age was restricted to the adult population to maximize the chances of selecting individuals who had the disorder (schizophrenia is rare in both the youth83 and senior populations84) and also to reduce the chances of confounding antipsychotic use for schizophrenia with use for other conditions (e.g., dementia, behavioural disorders in children). The cut-off age of 19 years was used as this is the actual threshold in BC for adult health services and insurance coverage. We searched for evidence of schizophrenia diagnoses from the physician and hospital diagnostic records using ICD-9 295 and ICD-10 F20 diagnostic codes. Although we examined antipsychotic use in 2005 only, we deemed it important to search for evidence of schizophrenia diagnoses both for 2005 and the preceding year. This allowed us to include patients who received the diagnoses and were on antipsychotics since 2004, and continued to adhere to their medication through 2005 without further physician or hospital visits. We applied a previously validated procedure for ascertaining schizophrenia cases using health administrative data. The method involves identifying individuals who received at least two physician visits or at least one hospital stay where schizophrenia was listed as the most responsible diagnosis.85 3.2.1.2 Potentially inappropriate antipsychotic use cohorts  The second cohort was comprised of seniors (65 years and older) who had a recorded dementia but not severe mental disorder diagnosis (Figure 3-2). 36  This cohort was restricted to seniors primarily because this is the population that would be expected to have the highest prevalence of dementia86 and at the same time lower prevalence of schizophrenic disorders. 84 Physician and hospital claims data were used to identify relevant diagnoses. We excluded patients who had at least one recorded schizophrenia diagnosis in either 2004 or 2005. We also excluded individuals with a recorded bipolar disorder diagnosis (ICD-9 296 but not 296.2, 296.3 and 296.9; and ICD10 F30 and F31) since antipsychotic medication is an approved adjunctive therapy for bipolar disorders with psychotic symptoms.87 Finally, we searched for and excluded all who did not have inpatient or outpatient dementia diagnoses (ICD-9 294, 298, 331, 348; and ICD-10 F00 to F03).88 The third cohort was composed of individuals who were 18 years old and younger (Figure 3-3). As with the second cohort, we used physician and hospital data to identify and exclude those who received at least one schizophrenia or bipolar disorder diagnoses in 2004 or 2005. 3.2.2 Variables of interest 3.2.2.1 Antipsychotic medication use  The primary outcome measure we analyzed is a dichotomous variable indicating whether or not individuals filled one or more prescriptions for antipsychotic drugs in 2005. Prescription data were obtained from PharmaNet, a centralized database that records every prescription filled in community pharmacies throughout BC, regardless of patient age or insurance status (except for about four percent of the population who are covered by federal drug plans, i.e., veterans, registered status Indians, federal penitentiary inmates, and members of the Royal Canadian Mounted Police). We identified all prescriptions filled for antipsychotics by using the third level of the WHO-Anatomical  37  Therapeutic Chemical (ATC) classification system (i.e., N05Axx; not including Lithium).89 Antipsychotics were further classified as typical or atypical (second generation antipsychotics). A list of all antipsychotics identified in our data is available in Appendix C. To examine long-term use, we constructed additional variables based on the accumulated number of days’ supply. In the analysis of essential antipsychotic use, a dichotomous measure indicating more than 180 days’ supply was constructed. For potentially inappropriate use, a variable based on a 90-day period was derived. 3.2.2.2 Income and other covariates  Our primary independent variable is an ordinal measure of income – quintiles – derived from a combination of household-specific (83% of the individuals in our cohorts) and neighbourhood-level income data for 2005.90 The household-specific income data were income percentiles assigned by the BC Ministry of Health Services (using Canada Revenue Agency data) for the purpose of administering the income-based public drug benefit program in BC. For the rest of the individuals in our cohort (17%), income percentiles were imputed using the average tax returns filed by households residing in the smallest census unit defined and used by Statistics Canada (Census Dissemination Area with a population of 400-700). To measure schizophrenia severity, we created a dichotomous variable indicating whether an individual was hospitalized with schizophrenia as the most responsible diagnosis in 2004 or 2005. We used this variable in our analysis of essential antipsychotic use to adjust for possible bias arising from the uneven distribution of severe schizophrenia cases across income strata. We controlled for overall health status in our analyses by including a variable based on the Johns Hopkins ACG Case-Mix system for deriving 38  Aggregated Diagnostic Groups (ADGs). ADGs are groupings of diagnosis codes that are similar in severity and chronicity. A higher count of ADGs is generally indicative of greater overall clinical complexity and increased likelihood of health service use (including the use of prescription medications).91 Other covariates used in the study include long-term care status (yes/no), sex (male/female), age (five-year bands) and residence in urban versus nonurban areas. Long-term care status is a dichotomous variable derived from a flag in the prescription drug database that identifies individuals in long-term care (see Appendix D for a list of the patient-specific drug plans in BC). Sex, age and place of residence were all determined from the provincial health plan registry. 3.2.3 Analysis In each study cohort, we performed logistic regression analyses to examine income-related disparities for two outcome variables: the use of one or more antipsychotics and long-term use of antipsychotics. These regression models adjusted for the effects of age, sex, health status, schizophrenia hospitalization (for essential use analysis only) and place of residence on antipsychotic medication use. The selection of predictors and covariates used in the model was informed by Anderson-Newman’s framework of health service use,92 which specifies three broad categories of factors that influence individual health service use: predisposing characteristics (sex and age), enabling resources (income and urban residence) and need characteristics (health status, psychiatric and dementia diagnoses). As the main objective of this study was to examine income-related differences in antipsychotic use that are not due to the other factors in the framework, all variables were simultaneously entered in the logistic regression model. The highest income quintile was used as the reference group in calculating the odds ratios for all the logistic regression models. Income quintile 39  groups with adjusted odds ratios that have associated confidence intervals not containing the value of one were interpreted as having statistically significantly different odds of antipsychotic use compared to the reference group. All statistical analyses were performed using Stata 10.1.93  3.3  Results  3.3.1 Essential antipsychotic use A total of 11,417 adults, aged 19-64 years with a recorded schizophrenia diagnosis in 2004 or 2005 met our criteria for inclusion to the essential antipsychotic use cohort (Figure 3-1). Members of this cohort were predominantly men (60%), lived in urban areas (84%) and had five chronic conditions on average. More than a quarter had been hospitalized (27%) with schizophrenia as the most responsible diagnosis (Table 3-1). The prevalence of essential (85%) and long-term (more than 180 days) antipsychotic use (71%) were high in this cohort. The majority of the individuals have used at least one atypical antipsychotic (75%) medication while only 10% appeared to have been exclusively treated with typical antipsychotics. Results of the bivariate analyses suggest that individuals in the third quintile group had the highest prevalence of essential use. This trend was observed both for essential (χ2 [4] =56.7, p<.001) and long-term antipsychotic use (χ2 [4] =114.9, p<.001). Logistic regression analyses that controlled for a number of covariates (Table 3-2) also indicated an inverted-U-shaped relationship between income and odds of essential antipsychotic use. Individuals in the lowest income group (OR=1.05, 95% CI=.90-1.23) had about the same odds of essential use as those in the highest income group. The other income groups had greater odds of essential  40  use, with those in the third quintile (OR=1.71, 95% CI=1.44-2.04) having the highest odds of essential use. The same pattern was observed for long-term use (Figure 3-7) except for the statistically-significant and slightly elevated odds ratios found in all the comparison income quintiles groups. 3.3.2 Potentially inappropriate antipsychotic use in seniors with dementia A total of 33,633 individuals, aged 65 years and older, who had a recorded diagnosis of possible dementia, but not schizophrenia or bipolar diagnosis in 2004 or 2005, met our criteria for inclusion in the cohort (Figure 3-2). Cohort members were predominantly women (60%), lived in urban areas (82%) and had seven chronic conditions on average. Those living in long-term care facilities comprised less than one quarter of seniors (23%), many of whom were concentrated in the lower income groups (Table 3-3). Close to one out of four seniors (23%) in this cohort had potentially inappropriately received antipsychotic treatment and about one out of seven were given the drug for more than 90 days (long-term use). There were more seniors who received at least one atypical antipsychotic (20%) than seniors who were exclusively on typical antipsychotics (2.5%). Bivariate analyses indicate the presence of an income gradient in the potentially inappropriate use of antipsychotics. The trend (Figure 3-5) suggests that seniors with lower income had higher levels and longer duration of potentially inappropriate antipsychotic use. In long-term care facilities, almost three out of every five seniors (56%) had been given potentially inappropriate antipsychotic treatment. In comparison, only 13% of community-dwelling seniors received similar treatment (data not shown). Even when differences in age, sex, health status and residence in urban areas had been accounted for, long-term care seniors were  41  still more likely than their community-dwelling counterparts to receive potentially inappropriate antipsychotic treatment (OR=9.31, 95% CI=8.75-9.91) . Because of the significant differences in the prevalence of use between long-term care and community-dwelling seniors, two separate logistic regression analyses were performed in each subgroup. Results of the stratified analysis (Table 3-4) indicate that among community-dwelling seniors, those from the lowest income quintile had higher odds of potentially inappropriate use compared to highest-income seniors (OR=1.24, 95% CI=1.10-1.39). Among longterm care seniors (who were more likely to receive antipsychotic treatment than community-dwelling seniors), no statistically significant differences in the odds of use were found. Similar trends were observed when long-term antipsychotic use was examined (Figure 3-8 and Figure 3-9). 3.3.3 Potentially inappropriate antipsychotic use in children and youth A total of 789,617 children and youth (aged 19 years and younger) met our criteria for inclusion in the cohort (Figure 3-3). These were all individuals who had no recorded schizophrenia or bipolar diagnosis in either 2004 or 2005. Many of these individuals lived in urban areas (83%) and had two chronic conditions on average (Table 3-5). About 40 per 10,000 (prevalence figures are presented in per 10,000 population due to rare prevalence) received potentially inappropriate antipsychotic treatment. Also, about 30 per 10,000 were on treatment for more than 90 days (long-term use). The use of atypical antipsychotics (37 per 10,000) was markedly greater than the use of typical antipsychotics (3 per 10,000). Bivariate analyses suggest a reversed-J-shaped relationship between income and the potentially inappropriate use of antipsychotics in this cohort (Figure 3-6). The trend suggests that children and youth from lowest income households had higher prevalence and longer duration of potentially 42  inappropriate antipsychotic use compared to those from highest-income households. Children and youth from the middle-income quintiles had the lowest prevalence and the smallest proportion of long-term recipients of potentially inappropriate antipsychotic treatment. Results of the logistic regression analysis that adjusted for a number of covariates (Table 3-6) confirm the presence of a reversed-J-shaped relationship (Figure 3-10) between income and potentially inappropriate antipsychotic use in this cohort. Children and youth from lowest income households had more than twice the odds of potentially inappropriate (OR=2.40, 95%CI=2.17-2.66) and long-term use (OR=2.63, 95%CI=2.34-2.96) of antipsychotics compared to those in the highest income quintile. Those from the third quintile group had the lowest odds of potentially inappropriate and long-term use. Older children (10 to 14 year olds OR=64.52, 95% CI=44.30-93.95; 15 to 18 year olds OR=58.83, 95% CI=40.39-85.69) and boys also had remarkably higher odds of use.  3.4  Discussion The results of this study show that the prevalence of essential  antipsychotic use among adults with a recorded schizophrenia diagnosis was high, though it varied across income groups. Study results also indicate that potentially inappropriate antipsychotic use differed across income levels, both for community-dwelling seniors and children and youth. Among seniors living in the community (who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis), 13% received potentially inappropriate antipsychotic treatment with higher odds of use evident among lowest income quintile individuals. Among seniors in long-term care, potentially inappropriate use was consistently high across income levels. Finally, among children and youth, potentially inappropriate antipsychotic use was rare, although those with the lowest incomes had the highest odds of use. 43  The high prevalence of essential antipsychotic treatment and its longterm use observed among people with a recorded schizophrenia diagnosis in this study is encouraging. This is because consistent use of this medication among individuals with schizophrenia improves overall functioning and reduces risk of hospitalization.94 The inverted-U-shaped relationship between income levels and antipsychotic use, however, points to the importance of factors, other than public drug coverage, in promoting essential antipsychotic use. Perhaps more aggressive forms of support are needed to assist individuals with schizophrenia fill their prescription and adhere to their treatment regimen. Among highest income group, the lower odds of use could be due to individuals’ relatively better ability to pay for alternative and complementary therapies, which could result in better outcomes and less need for antipsychotic medication. The continued use of antipsychotic treatment in seniors with dementia raises some concern given the increased risk of adverse events associated with antipsychotic use in this population.18,73-75 It should be noted that that regulatory warnings and definitive studies regarding antipsychotics’ limited efficacy and increased risk of adverse events for this population did not appear until the middle of 2005.18,73,76 Nevertheless, there were guidelines already in place before that time that urge care providers to use this medication as last-line treatment for extreme cases of agitation or psychotic behaviour.95 Another disconcerting finding is the higher odds of potentially inappropriate use found among low-income compared to high-income seniors living in the community. It is likely that these higher odds of use are caused partly by a greater proportion of income assistance recipients in low-income groups who received the treatment at reduced or no cost. A similar low-barrier to antipsychotic medication access in long-term care facilities could account for  44  the consistently high prevalence of potentially inappropriate use found across income groups. These findings, altogether, highlight the need to implement changes in dementia care to discourage potentially inappropriate antipsychotic use. Available evidence suggests that care models that emphasize psychosocial and person-centred approaches may help decrease antipsychotic use in this population.96 Finally, our finding of greater odds of antipsychotic use among children and youth from low-income families is similar to what others have previously reported. A recent US study, for example, reported that children and youth receiving benefits from Medicaid in the US had significantly higher levels of atypical antipsychotic treatment compared to those with private health insurance.97 This higher odds of use could simply be due to the higher concentration of prodromal severe mental disorders among children and youth from low-income families.98 Alternatively, this could again be due to the higher concentration of children and youth from low-income families who were eligible to receive antipsychotic treatment at reduced or no cost. Physicians in public treatment settings at times feel compelled to avoid further use of resources by administering antipsychotic treatment to children with challenging behaviours.99 In BC, nonpharmacological treatments such as behaviour therapies are not covered by the provincial health plan if administered by non-physicians.  3.5  Conclusions Where evidence indicates the use of medicine results in benefits that far  outweigh risk, higher levels of use that are consistent across income or other social categories are desirable and are indicative of good care quality. The results of our study on essential antipsychotic use suggest that the prevalence of this kind of use in BC is high, although, some income-related disparities persist and possibly impact the poorest segment of the population. Our study has also 45  provided some evidence for the potentially inappropriate use of this medication, which appeared to be more likely amongst the marginalized sectors of our society – seniors and children and youth from low income households and all seniors living in long-term care facilities.  46  Table 3-1  Descriptive characteristics of the cohort of adults (19 to 64 years) who had a recorded schizophrenia diagnosis in 2004 or 2005  Income Quintiles Statistics  Total  Lowest  Second  Third  Fourth  Highest  N  11,417  2,284  2,283  2,284  2,283  2,283  Income (median $)  14,375  3,999  5,313  14,375  27,500  46,667  H(4)=10531.6, p=.0001  Age (%) 19 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64  10.5 10.5 9.8 12.0 14.7 14.2 10.2 10.2 5.8  8.8 9.9 10.1 11.5 16.9 14.5 10.6 10.6 5.6  9.7 10.8 9.1 12.8 14.7 15.8 9.9 9.9 5.3  7.6 9.9 10.5 11.9 15.1 14.1 12.2 12.2 7.0  10.6 11.9 11.0 13.2 14.5 12.5 9.5 9.5 4.7  16.0 10.3 8.3 10.8 12.3 14.2 9.1 9.1 6.5  χ2(4)=102.9, p<.001 χ2(4)=6.9, p=.143 χ2(4)=11.6, p=.020 χ2(4)=8.0, p=.092 χ2(4)=19.3, p=.001 χ2(4)=10.3, p=.036 χ2(4)=14.5, p=.006 χ2(4)=14.5, p=.006 χ2(4)=14.8, p=.005  Women (%)  40.2  36.8  38.3  40.5  41.9  43.6  χ2(4)=28.1, p<.001  Urban dwellers (%)  83.8  82.6  84.4  85.1  83.9  83.0  χ2(4)=6.9, p=.140  5.2 3.2  5.2 3.3  5.1 3.2  5.3 3.3  5.1 3.1  5.1 3.1  F(4,11412)=2.94, p=.019  Hospitalization (%)†  26.79  27.93  28.43  27.10  28.25  22.25  χ2(4)=31.2, p<.001  Antipsychotic use (%) ≥ one antipsychotic > 180 days any atypical‡ typical only‖  85.09 71.26 75.04 10.06  84.02 69.48 72.59 11.43  84.28 72.89 73.89 10.38  89.58 78.42 79.07 10.51  85.55 71.05 76.65 8.89  82.04 64.48 72.97 9.07  χ2(4)=56.7, p<.001 χ2(4)=114.9, p<.001 χ2(4)=37.1, p<.000 χ2(4)=11.4, p=.022  Health status ADG count (mean)* SD  Source: Population Data BC and PharmaNet (2005). Although demographic and prescription use data were from 2005, schizophrenia case ascertainment were done for the years 2004 and 2005 Notes: *ADG – Aggregated Diagnostic Groups derived from physician and claims data using the ACG system. †any hospitalization in 2004 or 2005 with schizophrenia as the most responsible diagnosis. ‡includes everyone who filled atypical and typical antipsychotics in 2005. ‖includes only those who filled typical antipsychotics in 2005.  47  Table 3-2  Essential antipsychotic use by income and other covariates among adults (19 to 64) who had a recorded schizophrenia diagnosis in 2004 or 2005  ≥ one antipsychotic  > 180 days  OR  95% CI  95% CI  OR  95% CI  95% CI  Income quintiles Lowest Second Third Fourth Highest (ref)  1.05 1.08 1.71 1.22 1.00  0.90 0.92 1.44 1.04 -  1.23 1.26 2.04 1.44 -  1.18 1.40 1.87 1.31 1.00  1.04 1.23 1.64 1.15 -  1.34 1.59 2.14 1.48 -  Age 19 to 24 (ref) 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64  1.00 1.23 1.39 1.40 2.04 1.85 1.69 2.23 1.63  1.00 1.12 1.14 1.66 1.51 1.37 1.77 1.26  1.52 1.72 1.72 2.50 2.27 2.09 2.82 2.12  1.00 1.41 1.61 1.69 2.09 2.27 2.37 2.53 2.61  1.19 1.35 1.44 1.78 1.92 2.00 2.11 2.10  1.67 1.91 2.00 2.45 2.67 2.81 3.03 3.25  Women*  0.96  0.86  1.07  1.02  0.94  1.12  Health status†  1.03  1.02  1.05  0.98  0.97  1.00  Urban‡ Hospitalized‖  1.52 1.97  1.33 1.72  1.73 2.25  1.37 1.40  1.23 1.28  1.53 1.55  Notes: Numbers in bold were statistically significant at p<0.05. *compared to the reference group of men. †ADG counts derived from physician and claims data using the ACG system. ‡compared to non-urban reference group. ‖any hospitalization in 2004 or 2005 with schizophrenia as the most responsible diagnosis.  48  Table 3-3  Descriptive characteristics of the cohort of seniors (≥65 years) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis  Income Quintiles N  33,633  Total  Lowest  Second  Third  Fourth  Highest  Statistics  Income (median $)  6,727  6,727  6,726  6,727  6,726  31,500  16,000  24,000  31,500  45,000  70,000  H(4)=32267.2, p=.0001  Age (%) 65 to 69 70 to 74 75 to 79 80 to 84 85 to 89 90+  8.1 11.8 18.9 24.8 21.1 15.3  8.5 9.3 13.7 21.9 23.4 23.2  5.8 10.1 17.8 25.1 23.1 18.1  7.1 11.5 19.8 25.8 22.1 13.7  7.9 12.5 21.0 25.6 20.3 12.7  10.8 15.5 22.2 25.8 16.8 8.9  χ2(4)=124.7, p<.001 χ2(4)=155.1, p<.001 χ2(4)=193.8, p<.001 χ2(4)=40.3, p<.001 χ2(4)=119.6, p<.001 2 χ (4)=626.9, p<.001  Women (%)  60.3  76.5  64.4  58.6  54.4  47.8  χ2(4)=1300, p<.001  Urban dwellers (%)  81.7  81.8  81.0  77.2  81.6  86.9  χ2(4)=216.0, p<.001  In long-term care (%)  23.3  30.4  25.9  22.6  21.1  16.4  χ2(4)=413.6, p<.001  Health status ADG count (mean)* SD  7.2 3.6  7.0 3.8  7.3 3.7  7.2 3.7  7.2 3.6  7.3 3.5  F(4,33628)=9.40, p<.001  Antipsychotic use (%) ≥ one antipsychotic > 180 days any atypical† typical only‡  22.7 14.2 20.2 2.5  25.9 16.9 22.9 3.1  24.3 15.3 21.7 2.6  22.4 14.1 20.1 2.3  21.7 13.4 19.3 2.4  19.0 11.3 17.0 2.0  χ2(4)=106.6, p<.001 χ2(4)=94.9, p<.001 χ2(4)=84.1, p<.001 χ2(4)=18.2, p=.001  Source: Population Data BC and PharmaNet (2005) Although demographic and prescription use data were from 2005, schizophrenia and bipolar disorder case ascertainment were done for the years 2004 and 2005 Notes: *ADG – Aggregated Diagnostic Groups †includes everyone who filled atypical and typical antipsychotics in 2005. ‡includes only those who filled typical antipsychotics in 2005.  49  Table 3-4  Potentially inappropriate antipsychotic use by income and other covariates among seniors (≥65 years) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis  ≥ one antipsychotic OR  95% CI  > 180 days  95% CI  OR  95% CI  95% CI  Seniors living in the community (N=25,804) Income quintiles Lowest Second Third Fourth Highest (ref)  1.24 1.19 1.05 1.05 1.00  1.10 1.05 0.93 0.93 -  1.39 1.34 1.19 1.19 -  1.19 1.10 0.93 0.97 1.00  1.03 0.96 0.80 0.84 -  1.36 1.27 1.08 1.12 -  Age 65 to 69 70 to 74 75 to 79 80 to 84 85 to 89 90+  1.00 1.12 1.30 1.16 1.16 1.17  0.95 1.12 1.00 0.99 0.99  1.32 1.51 1.35 1.35 1.38  1.00 1.31 1.45 1.31 1.22 1.26  1.07 1.21 1.10 1.01 1.02  1.59 1.74 1.57 1.47 1.54  Women*  1.19  1.10  1.29  1.28  1.17  1.41  Health status†  1.07  1.06  1.08  1.02  1.00  1.03  Urban‡  0.92  0.84  1.01  0.94  0.84  1.05  Seniors in long-term care (N=7,829) Income quintiles Lowest Second Third Fourth Highest (ref)  0.90 0.88 0.94 1.02 1.00  0.78 0.76 0.81 0.89 -  1.04 1.02 1.08 1.18 -  0.96 0.95 1.05 1.05 1.00  0.83 0.82 0.91 0.91 -  1.10 1.09 1.21 1.21 -  Age 65 to 69 70 to 74 75 to 79 80 to 84 85 to 89 90+  0.87 0.99 0.75 0.67 0.54 0.87  0.61 0.71 0.54 0.48 0.39 0.61  1.26 1.39 1.04 0.92 0.74 1.26  0.95 1.04 0.75 0.68 0.53 0.95  0.67 0.75 0.54 0.50 0.38 0.67  1.35 1.44 1.02 0.93 0.72 1.35  0.93 1.00  0.84 0.99  1.03 1.02  0.98 0.96  0.88 0.95  1.08 0.98  0.93  0.82  1.05  0.93  0.82  1.06  Women* Health status† Urban‡  Notes: Numbers in bold were statistically significant at p<0.05. *compared to the reference group of men. †ADG counts derived from physician and claims data using the ACG system. ‡compared to non-urban reference group.  50  Table 3-5  Descriptive characteristics of the cohort of children and youth (≤18 years) who had no recorded schizophrenia or bipolar disorder diagnosis  Income Quintiles Statistics  Total  Lowest  Second  Third  Fourth  Highest  789,617  157,924  157,923  157,924  157,923  157,923  40,800  10,000  29,375  40,800  60,000  102,083  H(4)=75800, p=.0001  19.5 25.5 29.7 25.3  20.9 26.8 29.1 23.3  20.4 26.1 29.6 24.0  20.4 25.8 29.6 24.2  19.9 25.9 29.4 24.8  15.9 23.1 30.8 30.1  χ2(4)=1600, p<.001 χ2(4)=656.2, p<.001 χ2(4)=132.5, p<.001 χ2(4)=2500, p<.001  48.69  48.49  48.6  48.6  48.8  49.0  χ2(4)=9.1, p=.059  82.7  80.5  80.7  80.0  85.7  86.6  χ2(4)=4400, p<.001  Health status ADG count (mean)* SD  2.3 2.0  2.4 2.1  2.2 2.0  2.2 2.0  2.3 2.0  2.4 2.0  F(4,789612)=249.7,p<.001  Antipsychotic use (%) ≥ one antipsychotic > 180 days any atypical† typical only‡  .40 .30 .37 .03  .78 .62 .74 .04  .31 .22 .28 .02  .26 .18 .24 .02  .29 .21 .27 .03  .35 .25 .33 .02  χ2(4)=741.3, p<.001 χ2(4)=720.7, p<.001 χ2(4)=761, p<.001 χ2(4)=7.43, p=.115  N Income (median $) Age (%) 65 to 69 70 to 74 75 to 79 80 to 84 Girls (%) Urban dwellers (%)  Source: Population Data BC and PharmaNet (2005) Although demographic and prescription use data were from 2005, schizophrenia and bipolar disorder case ascertainment were done for the years 2004 and 2005 Notes: *ADG – Aggregated Diagnostic Groups †includes everyone who filled atypical and typical antipsychotics in 2005. ‡includes only those who filled typical antipsychotics in 2005.  51  Table 3-6  Potentially inappropriate antipsychotic use by income and other covariates among children and youth (≤18 years) who had no recorded schizophrenia or bipolar disorder diagnosis  ≥ one antipsychotic  Income quintiles Lowest Second Third Fourth Highest (ref) Age 0 to 4 5 to 9 10 to 14 15 to 18  > 180 days  OR  95% CI  95% CI  OR  95% CI  95% CI  2.40 1.02 0.87 0.95 1.00  2.17 0.90 0.77 0.82 -  2.66 1.15 0.99 1.05 -  2.63 1.01 0.81 0.90 1.00  2.34 0.87 0.70 0.78 -  2.96 1.16 0.95 1.04 -  1.00 24.57 64.52 58.83  16.79 44.30 40.39  35.95 93.95 85.69  1.00 33.95 89.16 66.15  20.60 54.35 40.27  55.96 146.27 108.66  Girls*  0.38  0.35  0.41  0.30  0.28  0.33  Health status† Urban‡  1.45 0.92  1.43 0.84  1.46 1.01  1.43 0.92  1.41 0.82  1.45 1.02  Notes: Numbers in bold were statistically significant at p<0.05. *compared to the reference group of men. †ADG counts derived from physician and claims data using the ACG system. ‡compared to non-urban reference group.  52  Figure 3-1  Selection process for the cohort of adult individuals (19 to 64 years) who had a recorded schizophrenia diagnosis  17,504 individuals who were either hospitalized with schizophrenia as the most responsible diagnosis or had at least two physician visits with schizophrenia as the recorded diagnosis in 2004 or 2005 Excluded 3,138 individuals who were younger than 19 (n=358) or older than 64 (n=2,138) years old  14,366 adults who had a recorded schizophrenia diagnosis in 2004 or 2005 Excluded 433 individuals who were in BC for less than 275 days 13,933 adult BC residents who had a recorded schizophrenia diagnosis in 2004 or 2005  Excluded 2,316 individuals from areas with high rates (20%) of non-feefor-service claims 11,617 adult BC residents who had a recorded schizophrenia diagnosis in 2004 or 2005 Excluded 260 individuals with missing data on: • income (n=198) • sex (n=2)  11,417 adult BC residents who had a recorded schizophrenia diagnosis in 2004 or 2005  53  Figure 3-2  Selection process for the cohort of seniors (≥65 years) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis  42,116 individuals 65 years and older who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis in 2004 or 2005 Excluded 4,884 individuals who were in BC for less than 275 days 37,232 BC seniors who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis Excluded 2,816 seniors from areas with high rates (20%) of non-feefor-service claims 34,416 BC seniors who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis Excluded 783 individuals with missing data on: • income (n=695) • sex (n=88)  33,633 BC seniors who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis  54  Figure 3-3  Selection process for the cohort of children and youth (≤18 years) who had no recorded schizophrenia or bipolar disorder diagnosis  930,794 individuals, ≤18 years old, who had no recorded schizophrenia or bipolar disorder diagnosis in 2004 or 2005 Excluded 77,206 individuals who were in BC for less than 275 days 853,588 BC residents, ≤18 years old, who had no recorded schizophrenia or bipolar disorder diagnosis in 2004 or 2005 Excluded 56,039 BC residents from areas with high rates (20%) of non-feefor-service claims 797,549 BC residents, ≤18 years old, who had no recorded schizophrenia or bipolar disorder diagnosis in 2004 or 2005 Excluded 7,932 individuals with missing data on: • income (n=7,901) • sex (n=31)  789,617 BC residents, ≤18 years old, who had no recorded schizophrenia or bipolar disorder diagnosis in 2004 or 2005  55  Figure 3-4  Crude prevalence of essential antipsychotic use among individuals (19 to 64 years) who had a recorded schizophrenia diagnosis 90  85  86  84  84  82 78  71  69  73  71  Prevalence (%)  64  one or more > 180 days of use  Total  Lowest  2nd  3rd  4th  Highest  Income quintiles Source: Population Data BC and PharmaNet (2005)  56  Figure 3-5  Crude prevalence of potentially inappropriate antipsychotic use among seniors (≥65 years) who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis 26 24  23  22  22  Prevalence (%)  19 17 15 14  14  13  one or more 11  Total  Lowest  2nd  3rd  4th  > 90 days of use  Highest  Income quintile Source: Population Data BC and PharmaNet (2005)  57  Figure 3-6  Crude prevalence of potentially inappropriate antipsychotic use among children and youth (≤18 years) who had no recorded schizophrenia or bipolar disorder diagnosis 78  Prevalence (per 10,000)  62  40  one or more 35 31  30  29  26  25  22 18  Total  Lowest  2nd  > 90 days of use  3rd  21  4th  Highest  Income quintiles Source: Population Data BC and PharmaNet (2005)  58  Figure 3-7  Essential antipsychotic use by income among adults who had a recorded schizophrenia diagnosis  2.0  1.5 Odds ratio 1.0  .5  •  one or more antipsychotic ♦ more than 180 days of use  •♦The highest income quintile with an odds ratio of 1.0 was the reference group  59  Figure 3-8  Potentially inappropriate antipsychotic use by income among community-dwelling seniors who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis  2.0  1.5  Odds ratio  1.0  Income quintiles .5  • one or more antipsychotic ♦ more than 90 days of use •♦The highest income quintile with an odds ratio of 1.0 was the reference group  60  Figure 3-9  Potentially inappropriate antipsychotic use by income among long-term care seniors who had a recorded dementia but not schizophrenia or bipolar disorder diagnosis  2.0  1.5  Odds ratio  1.0  Income quintiles .5  •  one or more antipsychotic ♦ more than 90 days of use  •♦The highest income quintile with an odds ratio of 1.0 was the reference group  61  Figure 3-10 Potentially inappropriate antipsychotic use by income among children and youth who had no recorded schizophrenia or bipolar disorder diagnosis  3.0  2.5  2.0  Odds ratio  1.5  1.0  .5  .0  Income quintiles  • one or more antipsychotic ♦ more than 90 days of use  •♦The highest income quintile with an odds ratio of 1.0 was the reference group  62  4  Conclusion  4.1  Summary of findings To examine disparities in the use of antipsychotic medication, we  conducted two studies: 1) a systematic review of the peer-reviewed literature to synthesize current findings on race or ethnic-based disparities, and, 2) a secondary analysis of linked administrative to examine income-related disparities in the use of antipsychotic medication. The systematic review was carried out in recognition of the need to synthesize the literature that has accumulated over the past three decades on ethnic disparities in antipsychotic use. The second study was an effort to contribute to an understudied area in disparities research. In our systematic review, we found 28 studies that examined racial or ethnic disparities in antipsychotic treatment after accounting for the effect of a wide range of factors (i.e., age, sex, comorbid mental, physical disorders, insurance) known to influence the use of antipsychotic medication. The majority of these studies were population-based studies using mostly samples of adults who were diagnosed with schizophrenia or other psychotic disorders. Many of the studies were conducted in the US (only three were from countries such as Netherlands, New Zealand, and the United Kingdom) with African Americans and Latinos as the most frequently studied ethnic groups. Our review did not find consistent ethnic disparities in the receipt of antipsychotics in general. However, among those who received antipsychotic treatment, our findings suggest racial or ethnic minorities such as African Americans and Latinos who were being treated for severe mental disorder diagnosis were less likely than whites to receive atypical antipsychotic treatment and more likely to have received the older, typical antipsychotics. In  63  addition, the studies we reviewed indicate that African Americans and Asians were less likely than whites to receive the antipsychotic medication specifically prescribed for individuals with treatment-resistant schizophrenia. These findings indicate that ethnic minorities have lower odds of using currently recommended antipsychotic treatment – atypical antipsychotics. Though it is not fully known what is driving this disparity, it has been suggested that this may have been caused by clinicians’ concerns about specific adverse effects (i.e., weight gain and cardiovascular events), which are putatively greater among ethnic minorities who already have a disproportionate burden of certain health conditions (e.g., diabetes and heart disease).48 Our secondary analysis of administrative data examined income-related disparities in the essential and potentially inappropriate use of antipsychotics. In our analysis of essential antipsychotic use within a cohort of adults who received outpatient or inpatient schizophrenia diagnosis in 2005 or the previous year, we found that up to 85% of the individuals were treated with antipsychotics and that the most frequently used antipsychotic was the atypical antipsychotics. We also found that middle quintile individuals had the highest prevalence of essential antipsychotic use. This disparity remained even after accounting for variables that influence medicine use. Our analyses of potentially inappropriate antipsychotic use were performed separately on a cohort of seniors and a cohort consisting of children and youth. The results of our analysis show that about one in every five seniors received potentially inappropriate antipsychotic treatment. Prevalence of use is higher among seniors in long-term care facilities than seniors living in the community. By type of antipsychotics, atypical antipsychotics appeared to be the most frequently used. By income, seniors in the lowest income quintile had higher odds of potentially inappropriate use compared to those in the highest  64  income quintile and the differences remained even after accounting for other factors that influence medicine use. In the cohort composed of children and youth who had no recorded schizophrenia or bipolar disorder diagnosis in 2005 or the previous year, our analysis indicate that the prevalence of potentially inappropriate use was low. However, we found children and youth from lowest income quintile households to have more than twice the odds of potentially inappropriate antipsychotic use compared to those from the highest income quintile. This greater odds of use persisted even after adjusting for other factors that influence medicine use. These findings regarding high prevalence of essential antipsychotic use and low prevalence of potentially inappropriate use are encouraging. Altogether, these imply that individuals who were most likely to benefit from antipsychotic therapy had received them while exposure was minimized for those who were likely to be affected mainly by its adverse effects. The observed income-related disparities in antipsychotic use have important implications regarding BC’s public coverage for this medication. Among individuals with schizophrenia, the disparities highlight the importance of considering factors other than public coverage when promoting essential use. Among those without severe mental illness, the disparities suggest that public drug coverage may have inadvertently increased the risk of exposure of certain individuals (low-income individuals and seniors in long-term care) to potentially inappropriate antipsychotic treatment.  4.2  Strengths and limitations  4.2.1 Systematic review of ethnic disparities To our knowledge, this systematic review is the first ever conducted to synthesize the extant literature on racial and ethnic disparities in the use of antipsychotic medication. We implemented the following to ensure that the 65  review was conducted in a rigorous manner: 1) a protocol for searching the literature, assessing studies for inclusion, data collection and synthesis was developed by the main investigator and revised after review and approval by coinvestigators; 2) a Master’s trained information specialist conducted the search across several bibliographic databases to ensure a reasonably comprehensive search; and, 3) two investigators assessed the studies in each stage of the review process to minimize subjectivity. Like any systematic review, our study comes with some limitations. First, the search was limited to literature published in academic journals. Any findings of disparity or the lack thereof that were reported in the grey literature or other types of reports and publications would therefore have been excluded. Second, the review was limited to studies that have a primary focus on ethnic or racial disparities in antipsychotic use. As a result, some studies examining determinants of antipsychotic use that have included ethnicity or race as a control variable may have been missed, particularly if the ethnicity relevant findings were not reported or discussed anywhere in the abstract. Finally, we were not able to perform statistical analyses on the odds ratios to determine the overall significance of the differences reported in the literature. Such analysis was not conducted due to the heterogeneity in the characteristics of the population studied and in the wide variation in the covariates used for calculating the adjusted odds ratios. 4.2.2 Analysis of income-related disparities Our analysis on income-related disparities in antipsychotic use is the only population-based study we know of that examined income disparities within the context of essential and potentially inappropriate medicine use. We have used income variables derived from previously validated data used in the actual implementation of the government’s drug benefit program. We adopted a  66  procedure for identifying probable schizophrenia cases from a study that found the method to be valid and reliable. More importantly, our source of data for antipsychotic medication use in outpatient settings covers virtually the entire population of BC. A number of limitations need to be mentioned when considering the results of this study. First, the outcome that was measured was based on prescriptions filled which is a variable that may overestimate the prevalence of medication use while at the same time underestimate the number of actual prescriptions issued by care providers. This is because not all individuals fill their prescriptions and those that do, may later not use them. Though the prevalence of use may have been biased by this, it is unlikely that the odds ratios were affected in a meaningful way as these biases do not seem to be systematically associated with income levels. Second, this study used administrative data to identify people with or without schizophrenia in 2004 and 2005. As a result, a small proportion of people who have schizophrenia may have been missed. Third, there is likely to be residual confounding in the analyses of essential antipsychotic use due to the over representation of severe schizophrenia cases in the lower income groups.100 We attempted to reduce some of this bias by deriving a measure of severity based on hospitalization, but we acknowledge that our analyses may still have underestimated the odds of essential use for the highest income group. Last, it is possible that some individuals may have been misclassified as not having schizophrenic disorders and were therefore included in the cohorts of individuals without schizophrenia or bipolar diagnosis. We tried to minimize this misclassification error by excluding everyone that had any schizophrenia or bipolar diagnoses in 2005 or the previous year, and also by dropping cases residing in areas that have high non fee-for-service claims.  67  4.3  Recommendations The use of antipsychotic medication as treatment for severe mental  disorders needs periodic examination and monitoring to determine if the disparities are changing in magnitude and also to ensure that the medication is equally accessible to individuals who would benefit from its use. At the same time, policies and interventions should be introduced to reduce potential misuse particularly among low-income individuals who have limited access to behavioural treatments for non-psychotic conditions. The following recommendations are therefore offered to guide future efforts along these lines. 4.3.1 Recommendations for future research 4.3.1.1 Examine understudied and homogeneous ethnic groups  Due to differences in historical background and socio-demographic characteristics, findings of disparities from one ethnicity may not generalize to other ethnic groups. There is therefore a need to conduct studies that examine other ethnic groups. This is particularly true for countries, such as Canada and the US, that are experiencing a surge in ethnic diversity coming especially from the recent wave of Asian migration.101,102 To our knowledge, there is only one study in Canada that has examined this issue.103 The contexts in which disparities are examined also vary from one country to another. It is not clear at present how much of the disparities reported in the literature could be accounted for by differences in the context within which health care is accessed. Replication studies in other countries would contribute to a better understanding of this issue. There is limited evidence that the disparity in antipsychotic use reported in the US between whites and non-whites does not exist in other countries with a different health care system. A recent study in the UK, for example, reported that no significant  68  differences were found in antipsychotic use between non-white and white inpatients.104 With the increase in the population of certain ethnic groups, it may also become possible to examine and compare single-ethnicity groups and avoid the common practice of aggregation. Aggregation (e.g., using Asians as the category for all non-African Americans, non-Latinos, non-whites and non-Arabs) limits the inference that can be made from disparity research to interpretations about ethnic relations (minority versus majority status) and socio-economic positions.105 Comparing single-ethnicity groups (e.g. white Europeans versus Chinese versus African Americans) will provide for a richer interpretation of disparity findings that encompasses differences in beliefs and cultural practices relevant to the use of medication. 4.3.1.2 Examine disparities in mental health outcomes  Three decades of research have consistently demonstrated the existence of disparities in the use of antipsychotic medication. The next logical step would be to determine the impact this disparity has had on mental health outcomes, particularly for members of ethnic minorities. Differences in outcomes that are causally linked to disparities in use will more strongly emphasize the importance of eliminating disparities in the use and access of medications. 4.3.2 Recommendations for initiatives that may reduce disparities There have been many recommendations put forward to reduce disparities in health care. Many of these general recommendations10,34,106 address various aspects of the issue (e.g., legal, regulatory, financing and policy) and can be applied to eliminate disparities in access to antipsychotic medications. Generally, interventions that have been found successful were the ones that are multi-faceted in addressing causes of disparities, culturally appropriate, and, patient-centered.106 69  Recommendations that apply specifically to disparities in the use of antipsychotic medication would include the systematic collection of ethnicity and income data from people who are on antipsychotic regimen and reporting these data in aggregate form as quality indicators. These would be useful for performance monitoring and also for evaluating the effectiveness of interventions and innovations implemented to reduce disparities.34 Another specific recommendation is to design programs that take into account differences in language and culture.107,108 Variations in cultural beliefs about mental disorders influence individual behaviour towards seeking and receiving mental health care. Initiatives that are delivered in the patients’ native language and that are respectful of their culture should result in better uptake of and promote adherence to antipsychotic medications.109 The inappropriate use of antipsychotics is best addressed by initiatives that are designed to minimize misuse and increase the capacity of the health system to manage behavioural disorders. A government inquiry in the UK that looked at antipsychotic medication use among people with dementia living in care homes has provided the following recommendations to curtail indiscriminate antipsychotic use: 1) provide specialist dementia training for all care home staff; 2) provide enhanced support from general practitioners and other psychiatric care providers; 3) ensure involvement of family members or caregivers in all decisions regarding medication use; 4) require patient-reviews every 3 months; and 5) institute compulsory regulation and audit of antipsychotic drugs for people with dementia.110 With regards to the higher odds of potentially inappropriate antipsychotic treatment in lowest income individuals, policies and initiatives that enhance access to a wider range of treatment options may be beneficial. At present, inadequate access to nonpharmacological treatments leave low-income  70  households and physicians little choice in the management of behavioural symptoms that sometimes accompany nonpsychotic conditions.  4.4  Conclusions Disparities in the use of antipsychotic medication continue to exist. The  patterns of disparities observed in this study point to the marginalized sectors of our society as the group most likely to be affected – ethnic minorities and lowincome individuals. These findings have important implications about the quality of care provided to people with mental disorders and behavioural problems. Future studies should help unravel how disparities in use impact mental health outcomes and what actions can be done to reduce or eliminate them.  71  References 1.  Chen, C.-H., Chen, C.-Y. & Lin, K.-M. Ethnopsychopharmacology. Int Rev Psychiatry 20, 452-459 (2008).  2.  Isaacs, S.L. & Schroeder, S.A. Class - the ignored determinant of the nation’s health. 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(Free Press ; Collier Macmillan Canada ; Maxwell Macmillan International: New York : Toronto : New York :, New York : Free Press ; Toronto : Collier Macmillan Canada ; New York : Maxwell Macmillan International, c1991.).  85.  Lurie, N., Popkin, M., Dysken, M., Moscovice, I. & Finch, M. Accuracy of Diagnoses of Schizophrenia in Medicaid Claims. Hosp Community Psychiatry 43, 69-71 (1992).  86.  Berthelot, J.M., Forbes, W., Hill, G., Lindsay, J. & McDowell, I. Dementia among seniors. (1996).at <http://www.statcan.gc.ca/bsolc/olc-cel/olc-cel?catno=82-003X19960022826&lang=eng>  87.  Yatham, L.N. et al. Canadian Network for Mood and Anxiety Treatments (CANMAT) guidelines for the management of patients with bipolar disorder: consensus and controversies. Bipolar Disord 7 Suppl 3, 5-69 (2005).  88.  Pippenger, M., Holloway, R.G. & Vickrey, B.G. Neurologists’ use of ICD-9CM codes for dementia. Neurology 56, 1206 (2001).  89.  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Antipsychotic drug use in older adults. Am J Hosp Pharm 51, 2917-2943; Quiz 2959-2961 (1994).  96.  Fossey, J. et al. Effect of enhanced psychosocial care on antipsychotic use in nursing home residents with severe dementia: cluster randomised trial. BMJ 332, 756-761 (2006).  97.  Crystal, S., Olfson, M., Huang, C., Pincus, H. & Gerhard, T. Broadened Use Of Atypical Antipsychotics: Safety, Effectiveness, And Policy Challenges. Health Aff 28, w770-781 (2009).  98.  Johnson, J.G., Cohen, P., Dohrenwend, B.P., Link, B.G. & Brook, J.S. A longitudinal investigation of social causation and social selection processes involved in the 77  association between socioeconomic status and psychiatric disorders. J Abnorm Psychol 108, 490-499 (1999). 99.  Pappadopulos, E. et al. “Real world” atypical antipsychotic prescribing practices in public child and adolescent inpatient settings. Schizophr Bull 28, 111-121 (2002).  100.  Dohrenwend, B. et al. Socioeconomic status and psychiatric disorders: the causationselection issue. Science 255, 946 -952 (1992).  101.  Statistics Canada Ethnic diversity and immigration. (2009).at <http://www.statcan.gc.ca/>  102.  U.S. Census Bureau Selected Population Profile in the United States (Asian alone or in combination with one or more other races). (2007).at <http://factfinder.census.gov/>  103.  Puyat, J.H. et al. Ethnic disparities in antipsychotic drug use in British Columbia: a crosssectional retrospective study of linked survey and administrative data. Psychiatric Services (Washington, D.C.) (in press).  104.  Connolly, A., Taylor, D., Sparshatt, A. & Cornelius, V. Antipsychotic prescribing in Black and White hospitalised patients. Journal of Psychopharmacology 25, 704 -709 (2011).  105.  Sue, S. & Dhindsa, M.K. Ethnic and Racial Health Disparities Research: Issues and Problems. Health Education & Behavior 33, 459 -469 (2006).  106.  Chin, M.H., Walters, A.E., Cook, S.C. & Huang, E.S. Interventions to Reduce Racial and Ethnic Disparities in Health Care. Med Care Res Rev 64, 7S-28S (2007).  107.  Brach, C. & Fraser, I. Can Cultural Competency Reduce Racial And Ethnic Health Disparities? A Review And Conceptual Model. Med Care Res Rev 57, 181-217 (2000).  108.  Brach, C. & Fraser, I. Reducing disparities through culturally competent health care: an analysis of the business case. Qual Manag Health Care 10, 15-28 (2002).  109.  Barksdale, D.J. Provider factors affecting adherence: cultural competency and sensitivity. Ethn Dis 19, S5-3-7 (2009).  110.  GREAT BRITAIN. Parliament. All-Party Parliamentary Group on Dementia Always a last resort: inquiry into the prescription of antipsychotic drugs to people with dementia in care homes. (2008).  78  Appendices A.  Systematic review search strategy  Source: CINAHL (EbscoHost CINAHL with full text) Searched on: 29 November, 2010 Saved as: n/a Results: 96 Search: (MH "Ethnic Groups+") OR (MH "Race Factors") OR (MH "Minority Groups") AND (MH "Antipsychotic Agents+") OR (Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Benperidol or Bromperidol or Butaperazine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clopenthixol or Clotiapine or Clozapine or Cyamemazine or Dixyrazine or DOGMATIL or Droperidol or Fluanisone or Flupentixol or Fluphenazine or Fluspirilene or Haloperidol or Levomepromazine or Levosulpiride or Loxapine or Melperone or Mesoridazine or Molindone or Moperone or Mosapramine or Olanzapine or Oxypertine or Paliperidone or Penfluridol or Perazine or Periciazine or Perphenazine or Pimozide or Pipamperone or Pipotiazine or Prochlorperazine or Promazine or Prothipendyl or Quetiapine or Remoxipride or Risperidone or Sertindole or Sulpiride or Sultopride or Thiopropazate or Thioproperazine or Thioridazine or Tiapride or Tiotixene or Trifluoperazine or Trifluperidol or Triflupromazine or Ziprasidon or Zotepine or Zuclopenthixol or Methotrimeprazine) Limit to: Scholarly (Peer Reviewed) Journals Source: EMBASE (OvidSP; 1980 to 2010 Week 47) Searched on: 1 December, 2010 Saved as: ethnicity antipsychotics Joseph SR EMBASE Results: 1310 Search: 1. exp neuroleptic agent/bd, ct, ad, cm, do, it, dt, ih, ia, ce, cv, dl, ig, im, na, ip, tl, iv, po, pa, pr, pe, pd, rc, sc, sb, li, tp, td 2. (Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Benperidol or Bromperidol or Butaperazine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clopenthixol or Clotiapine or Clozapine or Cyamemazine or Dixyrazine or DOGMATIL or Droperidol or Fluanisone or Flupentixol or Fluphenazine or Fluspirilene or Haloperidol or Levomepromazine or Levosulpiride or Loxapine or Melperone or Mesoridazine or Molindone or Moperone or Mosapramine or Olanzapine or Oxypertine or Paliperidone or Penfluridol or Perazine or Periciazine or Perphenazine or Pimozide or Pipamperone or Pipotiazine or Prochlorperazine or Promazine or Prothipendyl or Quetiapine or Remoxipride or Risperidone or Sertindole or Sulpiride or Sultopride or Thiopropazate or Thioproperazine or Thioridazine or Tiapride or Tiotixene or Trifluoperazine or Trifluperidol or Triflupromazine or Ziprasidon or Zotepine or Zuclopenthixol or Methotrimeprazine).mp. 3. 1 or 2 4. exp ethnic difference/ or exp ethnic group/ or exp "ethnic or racial aspects"/ or exp race/ or exp "ethnic, racial and religious groups"/ or exp ethnicity/ 5. 3 and 4 6. limit 5 to (human and english language and yr="1980 -Current") 7. limit 6 to (article or journal or letter or report or "review")  79  Source: International Pharmaceutical Abstracts (OvidSP; 1970 to November 2010) Searched on: 29 November, 2010 Saved as: ethnicity antipsychotics Joseph SR IPA Results: 84 Search: 1. ethnic.mp. [mp=title, subject heading word, registry word, abstract, trade name/generic name] 2. (ethnic or ethnicity).hw. 3. race.hw. 4. 1 or 2 or 3 5. Antipsychotic agents.hw. 6. (Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Benperidol or Bromperidol or Butaperazine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clopenthixol or Clotiapine or Clozapine or Cyamemazine or Dixyrazine or DOGMATIL or Droperidol or Fluanisone or Flupentixol or Fluphenazine or Fluspirilene or Haloperidol or Levomepromazine or Levosulpiride or Loxapine or Melperone or Mesoridazine or Molindone or Moperone or Mosapramine or Olanzapine or Oxypertine or Paliperidone or Penfluridol or Perazine or Periciazine or Perphenazine or Pimozide or Pipamperone or Pipotiazine or Prochlorperazine or Promazine or Prothipendyl or Quetiapine or Remoxipride or Risperidone or Sertindole or Sulpiride or Sultopride or Thiopropazate or Thioproperazine or Thioridazine or Tiapride or Tiotixene or Trifluoperazine or Trifluperidol or Triflupromazine or Ziprasidon or Zotepine or Zuclopenthixol or Methotrimeprazine).ti,ab,hw,tn,rw. 7. 5 or 6 8. 4 and 7 9. limit 8 to (english language and human and yr="1980 -Current") Source: MEDLINE (1950 to Present with Daily Update) (OvidSP) Searched on: 29 November 2010 Saved as: ethnicity antipsychotics Joseph SR Results: 597 Search: 1. ethnicity.mp. 2. exp ethnic groups/ or exp african americans/ or exp arabs/ or exp asian americans/ or exp gypsies/ or exp hispanic americans/ or exp mexican americans/ or exp jews/ 3. exp continental population groups/ or exp african continental ancestry group/ or exp african americans/ or exp indians, central american/ or exp indians, south american/ or exp asian continental ancestry group/ or exp asian americans/ or exp european continental ancestry group/ or exp oceanic ancestry group/ 4. cross-cultural comparison/ or exp cultural characteristics/ or exp cultural diversity/ or exp ethnology/ 5. 1 or 2 or 3 or 4 6. Antipsychotic Agents/ 7. Psychotic Disorders/dt [Drug Therapy] 8. (Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Benperidol or Bromperidol or Butaperazine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clopenthixol or Clotiapine or Clozapine or Cyamemazine or Dixyrazine or DOGMATIL or Droperidol or Fluanisone or Flupentixol or Fluphenazine or Fluspirilene or Haloperidol or Levomepromazine or Levosulpiride or Loxapine or Melperone or Mesoridazine or Molindone or Moperone or Mosapramine or Olanzapine or Oxypertine or Paliperidone or Penfluridol or Perazine or Periciazine or Perphenazine or Pimozide or Pipamperone or Pipotiazine or Prochlorperazine or Promazine or Prothipendyl or Quetiapine or Remoxipride or Risperidone or Sertindole or Sulpiride or Sultopride or Thiopropazate or Thioproperazine or Thioridazine or Tiapride or Tiotixene or Trifluoperazine or Trifluperidol or Triflupromazine or Ziprasidon or Zotepine or Zuclopenthixol or Methotrimeprazine).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier] 9. 6 or 7 or 8 10. 5 and 9 11. limit 10 to (english language and yr="1980 -Current") 12. limit 11 to (classical article or clinical trial, all or comparative study or controlled clinical trial or evaluation studies or journal article or letter or meta analysis or multicenter study or randomized controlled trial or "review" or technical report or validation studies) 80  Source: PsycINFO (Ebsco) Searched on: 29 November, 2010 Saved as: n/a Results: 76 Search: S1 DE "Racial and Ethnic Groups" OR DE "African Cultural Groups" OR DE "Arabs" OR DE "Asians" OR DE "Blacks" OR DE "Indigenous Populations" OR DE "Latinos/Latinas" OR DE "Romanies" OR DE "Whites" OR DE "Cross Cultural Differences" OR DE "Racial and Ethnic Differences" S2 DE "Neuroleptic Drugs" OR DE "Aripiprazole" OR DE "Clozapine" OR DE "Molindone" OR DE "Nialamide" OR DE "Olanzapine" OR DE "Quetiapine" OR DE "Reserpine" OR DE "Risperidone" OR DE "Spiroperidol" OR DE "Sulpiride" OR DE "Tetrabenazine" S3 (Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Benperidol or Bromperidol or Butaperazine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clopenthixol or Clotiapine or Clozapine or Cyamemazine or Dixyrazine or DOGMATIL or Droperidol or Fluanisone or Flupentixol or Fluphenazine or Fluspirilene or Haloperidol or Levomepromazine or Levosulpiride or Loxapine or Melperone or Mesoridazine or Molindone or Moperone or Mosapramine or Olanzapine or Oxypertine or Paliperidone or Penfluridol or Perazine or Periciazine or Perphenazine or Pimozide or Pipamperone or Pipotiazine or Prochlorperazine or Promazine or Prothipendyl or Quetiapine or Remoxipride or Risperidone or Sertindole or Sulpiride or Sultopride or Thiopropazate or Thioproperazine or Thioridazine or Tiapride or Tiotixene or Trifluoperazine or Trifluperidol or Triflupromazine or Ziprasidon or Zotepine or Zuclopenthixol or Methotrimeprazine) S4 S2 OR S3 S5 S1 AND S4 Limiters - Scholarly (Peer Reviewed) Journals, 1980-Current Source: Web of Science (Thompson Reuters ISI Web of Knowledge) Searched on: 29 November, 2010 Saved as: n/a Results: 307 Search: #1 Topic=(antipsychotic*) #2 Topic=(ethnic* OR racial OR race) #3 #2 AND #1 Refined by: Document Type=( ARTICLE OR LETTER OR REVIEW ) AND Languages=( ENGLISH ) Timespan=All Years. Databases=SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH.  81  B.  Systematic review data collection form  Full-text #: Authors: Year: Location: (country only) Year(s) of data collection: Sampling frame (X):  Geographic Institutional Insurance status Other Details  Sampling method (X):  Random Convenience Population-based Other  Age range: Sex (X):  Male only Female only Both  Treatment Setting (X):  Inpatient only Outpatient only Both  Population group(s) studied (X): e.g. Patients with schizophrenia only  Schizophrenia Bipolar disorders Depression Dementia HIV Autism Spectrum Disorder Other  Specify here  82  Prescription data source (X):  Administrative data Chart review Survey Other  Specify here  Not specified Ethnic Groups  Ref  Note: please write actual ethnic/racial categories used  EG1 EG2 EG3 EG4 EG5 EG6  Type of antipsychotic studied  any antipsychotic  note: single AP studies (e.g. Risperidone) are excluded, except for Clozapine studies  any typical any atypical Clozapine  Measure of AP use  use versus non use atypical versus typical Other  Specify here  Not specified Count(s) of AP use  at least one 2 or more Other  Specify here  Not specified AP form investigated  Oral Depot Both Not specified  83  Covariates used for adjustment  Age Sex Insurance SES Health status Psychiatric diagnoses Other  Distribution by Covariates Used Sample Size (n) % Age  Agecat1  Note: write the actual age categories used  Agecat2 Agecat3 Agecat4 Agecat5  Sex  Men Women  Any Antipsychotic  Crude Prev  Adjusted Odds Ratio Pt est  -CI  +CI  Other Disparity Measure Pt est  -CI  +CI  Ref EG1 EG2 EG3 EG4 EG5 EG6  84  Any Atypical  Crude Prev  Adjusted Odds Ratio Pt est  -CI  +CI  Other Disparity Measure Pt est  -CI  +CI  Ref EG1 EG2 EG3 EG4 EG5 EG6  Any Typical  Crude Prev  Adjusted Odds Ratio Pt est  -CI  +CI  Other Disparity Measure Pt est  -CI  +CI  Ref EG1 EG2 EG3 EG4 EG5 EG6  Clozapine  Crude Prev  Adjusted Odds Ratio Pt est  -CI  +CI  Other Disparity Measure Pt est  -CI  +CI  Ref EG1 EG2 EG3 EG4 EG5 EG6  Other important sources of bias not related to sampling, data source or covariates included in the model:  1. 2.  85  C.  List of typical and atypical antipsychotics found in PharmaNet in 2005  Typical agents  Atypical agents  Chlorpromazine  Clozapine  Flupentixol  Olanzapine†  Fluphenazine  Quetiapine  Fluspirilene  Risperidone  Haloperidol Levomepromazine Loxapine Mesoridazine Periciazine Perphenazine Pimozide Pipotiazine Thioproperazine Thioridazine Thiotixene Trifluoperazine Zuclopenthixol † requires special authorization from PharmaCare as of March 2011  86  D.  Public drug coverage in BC  Plan B: Permanent residents of licensed residential care facilities • Full coverage for eligible prescription.  Plan C: Recipients of BC income assistance • Full coverage for eligible prescription.  Plan D: Cystic fibrosis • Coverage contingent on the patient’s primary plan (e.g., Plan C). • Full coverage for digestive enzymes and other products listed in the Cystic Fibrosis Formulary.  Plan F: Children in the ‘At Home’ Program • Full coverage of eligible prescription. • The ‘At Home’ program of the Ministry of Children and Family Development provides community-based, family-style care for severely handicapped children who would otherwise become reliant on institutional care.  Plan G: No-charge psychiatric medication plan • Full coverage of psychiatric medications included in the formulary. Certain drugs (e.g. Olanzapine) require prior authorization from PharmaCare. • Registration in the plan is required and eligibility is determined by physicians and community mental health centers.  Plan I: Fair PharmaCare Plan • Coverage is based on income.  87  

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