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Effects of prescription adaptation by pharmacists Law, Michael R; Morgan, Steven G; Majumdar, Sumit R; Lynd, Larry D; Marra, Carlo A Nov 17, 2010

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STUDY PROTOCOL Open AccessEffects of prescription adaptation by pharmacistsMichael R Law1*, Steven G Morgan2, Sumit R Majumdar3, Larry D Lynd4, Carlo A Marra4AbstractBackground: Granting dispensing pharmacists the authority to prescribe has significant implications forpharmaceutical and health human resources policy, and quality of care. Despite the growing number ofjurisdictions that have given pharmacists such privileges, there are few rigorous evaluations of these policychanges. This study will examine a January 2009 policy change in British Columbia (BC), Canada that allowedpharmacists to independently adapt and renew prescriptions. We hypothesize this policy increased drug utilizationand drug costs, increased patient adherence to medication, and reduced total healthcare resource use.Methods/Design: We will study a population-based cohort of approximately 4 million BC residents from 2004through 2010. We will use data from BC PharmaNet on all of the prescriptions obtained by this cohort during thestudy period, and link it to administrative billings from physicians and hospital discharges. Using interrupted timeseries analysis, we will study longitudinal changes in drug utilization and costs, medication adherence, and short-term health care use. Further, using hierarchical modelling, we will examine the factors at the regional, pharmacy,patient, and prescription levels that are associated with prescription adaptations and renewals.Discussion: In a recent survey of Canadian policymakers, many respondents ranked the issue of prescribingprivileges as one of their most pressing policy questions. No matter the results of our study, they will be importantfor policymakers, as our data will make policy decisions surrounding pharmacist prescribing more evidence-based.BackgroundContextAccess to primary care is an important concern forpatients in almost every jurisdiction examined. InCanada, nearly 4 million individuals report not having aregular physician and over 2 million report difficulties inaccessing routine or ongoing care [1]. For at least someof these individuals, and for certain components of pri-mary health care, non-physician health professionalsmay represent high-quality alternatives. There is someresearch evidence on the potential of deploying pharma-cists in primary care [2]; that literature, and practicalexperience in other jurisdictions points to a considerableamount of untapped pharmacist human resources [3-7].Expanding the scope of pharmacy practice may be acost-effective way to enhance patient access and adher-ence to medicines, and to reduce the clinical burden onprimary care physicians.Around 53% of Canadians fill one or more prescrip-tions each year, and at least half of these representchronic medications used to manage cardiovascular riskfactors [8,9]. However, rates of continuous use of medi-cines for chronic conditions are often sub-optimal [10].But with prescription lengths limited to approximately 3months in most provinces (with up to 4 refills if theyare provided), access to primary care doctors for thepurpose of prescription renewal may be a barrier tocontinuous adherence to long-term drug therapies.Thus, granting pharmacists prescribing authority mayincrease Canadians’ access to medications. Thoughpharmacists are highly trained in matters related to theeffects, interactions, and appropriate use of medicines,their expertise is seldom called upon as a first-line pri-mary health care provider in community settings.Recently, numerous Canadian provinces have imple-mented programs designed to expand the scope of phar-macy practice. The first province to move in thisdirection was Alberta, which implemented a program in2007 that allows pharmacists to prescribe medicationsand adapt existing prescriptions [3]. One year later,three-quarters of pharmacists in the province reported* Correspondence: mlaw@chspr.ubc.ca1Centre for Health Services and Policy Research, School of Population andPublic Health, The University of British Columbia. 201-2206 East Mall,Vancouver, BC, V6T 1Z3, CanadaFull list of author information is available at the end of the articleLaw et al. BMC Health Services Research 2010, 10:313http://www.biomedcentral.com/1472-6963/10/313© 2010 Law et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.that they regularly renewed or adapted prescriptions[11]. Several other provinces allow pharmacists similarprescribing privileges, and the remaining provinces havepassed the enabling legislation to allow pharmacist pre-scribing in the future. The trend towards pharmacistprescribing is present internationally as well. The UnitedKingdom has introduced “independent prescribing”,which gives pharmacists the ability to prescribe all med-ications after completing a training program. Likewise,in the United States, collaborative drug therapy manage-ment by pharmacists is permitted by the federal govern-ment and by at least 40 individual states [3]. All of thesechanges granting pharmacists prescribing authority mayhave significant implications for quality of care.Policy Change: A Natural ExperimentA January 2009 policy change in the Canadian provinceof British Columbia (BC) provides an opportunity togenerate valuable information about the impacts ofchanges in pharmacists’ prescribing authority. This pol-icy allowed pharmacists to adapt existing prescriptionswithout the consent of the original prescriber [12]. Thepolicy was adopted based on the potential benefit ofincreased patient adherence to medicines and anexpected reduction in the visit burden on primary carephysicians [13]. Prescription adaptations include chan-ging the dose, regimen, or formulation of a prescription,renewing an existing prescription and making therapeu-tic substitutions to an alternative drug from the sameclass. Therapeutic substitutions are only permitted in alimited number of drug classes: histamine 2 receptorblockers, non-steroidal anti-inflammatory drugs, nitrates,angiotensin converting enzyme inhibitors, dihydropyri-dine calcium channel blockers and proton pump inhibi-tors. Further, pharmacists cannot modify the dose orregimen for prescriptions treating cancer, cardiovasculardisease, asthma, seizures or psychiatric conditions.Pharmacist-initiated renewal of a prescription involvestheir dispensing of medicines beyond the term specifiedin the original prescription. BC pharmacists are onlypermitted to make renewals under certain circum-stances. Renewals can only be made for patients withlong-term chronic conditions who have been on thesame therapy for more than six months. Further, phar-macist-initiated renewals may only occur within the firstsix months after an original prescription is filled. Phar-macists cannot renew prescriptions for narcotics andpsychiatric medications. Finally, pharmacists arerequired to notify the original prescriber of a renewal oradaptation within 24 hours, and, although under noobligation to participate, pharmacists who do so mustadhere to guidelines and possess two million dollars ofpersonal liability coverage.Despite the fact that a growing number of jurisdic-tions are giving pharmacists various forms of prescrip-tive privileges, there are conspicuously few rigorousevaluations of these policy changes. Allowing pharma-cists to modify or renew prescriptions may or may notimprove treatment quality and continuity of care byimproving drug selection, dosing, and use [14] - this is atestable hypothesis that has as yet not been convincinglyinvestigated. Therefore, we undertook a study to evalu-ate pharmacist prescribing in BC. We hypothesized thatprescription adaptation by pharmacists increased drugutilization and drug costs, increased patient adherenceto medication, reduced the use of ambulatory physicianservices, and had no effect on hospitalization rates.Methods/DesignStudy Setting and PopulationBritish Columbia (BC) is Canada’s westernmost andthird most populous province, with nearly 4.5 millionresidents in 2009 [15]. Approximately half of the popu-lation lived in the greater Vancouver area [16]. Ourstudy will focus on a population-based open cohort ofBC residents. In 2006, 14.7% of the population wereover 65 and 50.3% were female [17]. The population isethnically diverse, with significant numbers of peopleidentifying as Europeans, Aboriginals, East Asians, andSouth Asians [18]. Thus, the overall population is typicalof that seen in the larger provinces of Canada and isreasonably generalizable to many North American juris-dictions. For all individuals, we will extract data on theirdrug utilization as well as a range of control variables.Based on prior work with the BC databases, we antici-pate an overall cohort of over 4 million individuals,which includes the majority of BC residents, with theexception of First Nations and veterans who receivedrug benefits through the Federal Government.Health care is provided to all residents through theBC Medical Services Plan, which covers medically neces-sary physician and hospital services. Unlike hospitalsand physicians, prescription drug coverage is a mix ofpublic and private programs. Public coverage is availableto all residents through the Fair PharmaCare program,which covers prescription drugs after households havemet an income-based deductible. The public programuses several cost containment mechanisms, including aformulary of reimbursable medications and reference-based pricing for several drug classes. Estimated provin-cial health expenditure in 2009 was $23.4 billion, about$2.6 billion of which paid for prescription drugs [19,20].In sum, this public expenditure represented about 42%of total drug costs [20]. Alongside this public coverage,many BC residents hold private drug coverage, largelypaid for through their employer.Law et al. BMC Health Services Research 2010, 10:313http://www.biomedcentral.com/1472-6963/10/313Page 2 of 7To ensure maximum policy relevance, the team willmaintain regular communication with local and nationaldecision makers. This research project was developed incollaboration with the BC Ministry of Health Servicesand upon consultation with the BC Pharmacy Associa-tion, so we expect the results will affect future policydevelopment or the refinement of existing policies. Thisstudy was reviewed and approved by the University ofBritish Columbia Behavioural Research Ethics Board.Data SourcesData Access and LinkageThree population-based, administrative data sources willbe used in this analysis: (1) the BC PharmaNet prescrip-tion drug claims database, and (2) health services utiliza-tion databases held at Population Data BC. We plan tostudy data for a period of 5 years prior to the policy and2 years after (January 1, 2004 through December 31,2010).The DatabasesBC PharmaNetPharmaceutical dispensing data come from the prescrip-tion monitoring system-BC PharmaNet-that was estab-lished in 1995 to track progress toward deductiblesunder the BC PharmaCare program, and to monitor forcontraindicated combinations of prescribed drugs. Itcontains a comprehensive record of ambulatory pre-scriptions received by all residents of the province. ThePharmaNet database will be used to capture data onindividual prescriptions, including drug type, total cost,whether the prescription is a physician-initiated refill,and whether the prescription was adapted or renewedby a pharmacist. The design of the PharmaNet databasemakes it possible to ‘nest’ all prescriptions according tothe originating pharmacy; this information will be usedto determine the characteristics of the originating phar-macy such as the volume of prescriptions. These data-bases have been used extensively in pharmaceuticalpolicy and pharmacoepidemiology research, and areconsidered to be among the most valid and highestquality available in Canada [21-23].Health Services Data from Population Data BCHealth services data holdings of Population Data BCinclude administrative data files containing informationfrom medical service claims submitted by physicians,hospital separations, and vital statistics (births/deaths).Specific information to be drawn from these datasources for the purposes of this project will include thefollowing: from the Medical Services Plan registrationfiles, descriptive information about individuals in thestudy population (age, sex, Local Health Area, durationof residency); from the Medical Services Plan paymentfile, medical services used and data for the constructionof profiles of patient morbidity ICD-9 codes); from theHospital Separations files, data for the construction ofmeasures of patient morbidity and clinical complexity(discharge data and up to 25 primary and secondaryICD-10 diagnosis codes); and from the Vital statistics,date of death.Income DataFor each individual, we will assign income percentilesusing existing custom tabulations of Statistics Canada’sTaxfiler Database at the Census Dissemination Arealevel [24]. In previous studies, these data have shownreasonable agreement with individual-level verifiedincomes [25].General Work PlanFor various components of the analysis, we will use spe-cific subsets of prescription drug claims. First, we willuse data on all prescriptions to analyse the prevalenceand characteristics of pharmacist adaptations andrenewals and their overall impact on drug utilizationand costs. Second, we will study all prescriptions fromdrug classes in which adaptation was permitted. Third,we will determine prescriptions that were ‘potentiallyrenewable’. The guidelines for pharmacist renewal statethat a prescription may be renewed for a medicationused for a chronic condition that the patient has usedfor more than 6 months with no changes. Thus, we willdefine a ‘potentially renewable’ prescription-one that apharmacist could have hypothetically renewed-using thefollowing criteria (see Figure 1):1. At least one prescription for the same drug duringthe period from 2 years prior to six months prior, toestablish long-term “consistent use” (prescription J-2)2. One or more prescriptions for the same drug dur-ing the 6 months prior to the current prescription(prescription J-1)3. The potentially renewable prescription, prescrip-tion J, is for the same drug at the same dose as pre-scription J-1.Subgroup AnalysesTo study the impact of prescription renewal on adherenceto therapy and short-term health care use, we will con-struct cohorts of patients established on specific medica-tions. We will study users of medication classes that aretypically used continuously, such as anti-hypertensives,and are amongst the top 20 classes of drugs in terms ofthe number of users in BC [26]. We will exclude medica-tion classes that pharmacists are restricted from renewingor where pharmacist renewal is unnecessary given existingdispensing rules. Based on data from the BC Rx Atlas, 2ndEdition, Table 1 shows the approximate numbers ofunique users of specific drug classes to be studied [26].Law et al. BMC Health Services Research 2010, 10:313http://www.biomedcentral.com/1472-6963/10/313Page 3 of 7Variables of InterestPrescription RateOur analysis of drug utilization will focus on both thenumber of Defined Daily Doses (DDDs) of particular med-ications and the number of days supplied. Days supply is afield that must be entered by pharmacists in the Pharma-Net database for the prescription dispensation to be adju-dicated under the universal, income-based drug benefitprogram. DDDs are a WHO-developed measure that stan-dardizes drug therapy and provides a consistent measureof drug use over time between therapies with differenttypical dosing levels [27]. Using DDDs will allow us toassess the validity of the days supplied field.CostsWe will examine the cost of pharmacist adaptations andrenewals by studying the drug cost per eligible patient,along with the professional fees paid to pharmacists forperforming adaptations and renewals. For adaptations,we will analyze any changes in the cost per day of treat-ment within specific therapeutic classes. Of particularinterest will be any shifts toward use of less expensivealternative drugs under BC PharmaCare’s Reference Pri-cing Program [28-30]. For renewals, we will examine theimpact on drug costs due to increased drug adherence.Medication AdherenceWe will analyse prescription adherence using two com-monly used measures [10]. The first measure is the pro-portion of days covered, which is the number of dayssupply of medication divided by the number of days ineach study month. Second, we will construct measuresof persistence, defined as the number of days of therapywithout a gap of 90 or more days.Ambulatory physician visitsTo assess the impact of the policy changes in the visitburden on primary care physicians, we will analyse thenumber of ambulatory physician care visits per patientper month, for patients prescribed each renewal oradaptation-eligible class of drug. While it would be idealto study visits that were only intended to renew a pre-scription, billing data do not contain sufficient detail.Hospital AdmissionsTo assess any changes in hospitalization rates, we willanalyse the number of hospital admissions for relevantdiagnoses (i.e. myocardial infarction for antihypertensiveusers).Other VariablesDemographic characteristicsFor modelling the determinants of prescription adaptationand renewal, we will include indicators for patient age,sex, urban/rural, and socioeconomic status (income level).To define urban and rural areas, we will divide BC LocalHealth Areas (LHAs) based on population density usingexisting publically available data [31]. Income level will bederived from Statistics Canada data, as described above.Case-mix AdjustmentWe will adjust for case-mix in resource consumption atthe individual level in our models using the John’s Hop-kins ACG Case-Mix System [32].Pharmacy and Pharmacist prescribing volumeFor each pharmacy and pharmacist in our sample, wewill calculate average prescribing volumes over thestudy period by dividing the total number of prescrip-tions by the number of months.Proposed Statistical AnalysisDescriptive Characteristics of AdaptationsWe will use the complete population-based cohort ofprescriptions to detail the following descriptive charac-teristics of adaptations for the first year of the program:1. Number and types of adaptations performed;Figure 1 Definition of a “Potentially Renewable Prescription” (J). The solid circles are examples of prescriptions that must have been filled:one prior to six months before the potentially renewable one (J-1) and one in the 18 months prior to that (J-2). The outlines representexamples of other possible prescriptions during the same time periods.Table 1 Number of unique users in potential drug classesfor analysis in 2006Drug Class Unique users in 2006Cardiovascular: Antihypertensives 587,814Psychiatric: Antidepressants 382,813Acid reducing drugs 316,738Cardiovascular: Statins 284,364Hormonal contraceptives 204,629Diabetes: Oral drugs (non-insulins) 128,408Bisphosphonates 100,944Cardiovascular: Antithrombotics 82,136Law et al. BMC Health Services Research 2010, 10:313http://www.biomedcentral.com/1472-6963/10/313Page 4 of 72. Which drug classes and particular agents were mostregularly adapted;3. The concentration of adaptations amongst particu-lar pharmacists, particular pharmacies and particulargeographic regions;4. The cost of professional services fees for the adapta-tion program.Impact of Pharmacist AdaptationUsing Interrupted Time Series Analysis, we will studylongitudinal changes in drug utilization and costs, medica-tion adherence, and ambulatory care visits and hospitaliza-tions during each study month [33]. Our models will takethe following form to model each measure in month i:outcome time policy policy timei i i i i= + + + +    0 1 1 2 3· · · ·Where time represents the month in study time (i.e. 1,2, 3...) and policy is an indicator variable indicating if thepolicy is in effect at that observation point. The two para-meters of interest are b2, which indicates any immediatechange in the level of the outcome and b3, which indi-cates any change in the trend of the outcome followinginitiation of the policy. As the monthly observations maybe correlated over time, we will control for autocorrela-tion using appropriate adjustments in a generalised leastsquares model, or a similar model for correlated data[33]. We will use the resulting model estimates to calcu-late both absolute and percentage changes in the out-comes to make the results easily interpretable [34].As the policy may have had differential uptake ratesamongst particular pharmacists, we will also exploreconstructing a “control” cohort for this analysis in sev-eral ways. For example, we will explore the utility ofstratifying our sample into two groups: patients that vis-ited a pharmacy that adapts prescriptions, and patientsthat did not. This would allow us to more specificallyidentify an effect by having a control series in all ourtime series regressions and perhaps to determine if“early adoptors” are representative of the pharmacistpopulation in general. Alternately, we may explore usingpropensity score matching to pair individuals who had aprescription adapted with otherwise similar individualswho did not [35] or instrumental variables analysis.Determinants of Pharmacist Adaptations and RenewalsWe will use multi-level modelling techniques to deter-mine what factors at the region, pharmacy, patient andprescription levels are associated with prescription adap-tations and renewals. In particular, we will investigatesystematic differences in how the policy has affectedpatients of different age, sex and socioeconomic status.For example, we know that drug use varies by sex; forinstance, there are higher rates of antidepressant useamongst women in Canada [36]. Thus, it may be thatthis policy has differential effects on men and women.Further, one identified goal of the policy was to increaseaccess to medicines in rural communities. Thus, we willinvestigate rural region as a key factor.By using a hierarchical model to model the probabilityof an adaptation or renewal, we can estimate the effectof different region, pharmacy, and patient characteristicswhile controlling for the clustering of observationswithin these different levels. For the determinants asso-ciated with adaptation, we will use the dataset contain-ing all prescriptions for drugs potentially subject toadaptation. For renewals, we will use the dataset ofpotentially renewable prescriptions described above.Our model will contain a hierarchical structure of 4levels and include the following variables:• Regional characteristics (of ~79 regions with suffi-cient population size): urban/rural; primary carephysician supply (per 10,000 population); averageincome• Pharmacy characteristics: chain/independent; num-ber of pharmacists; volume of prescriptions, patients,and prescribers• Patient characteristics: patient age, sex, health sta-tus, income• Prescription characteristics: drug class; length ofprescription; calendar month (to control forseasonality)When modelling, we will test intra-cluster correlationcoefficients to determine which levels of the hierarchicalstructure are important.In both analyses, we will control for clustering at eachlevel by appropriately including random effects terms inthe model. As the primary goal of our modelling strat-egy is to test for differences between types of LHAs (i.e.urban/rural) and not for differences between individualLHAs, we have chosen to use random effects ratherthan fixed effects models. Our models will thus have thefollowing general structure to model the probability ofadaptation or renewal:Pr adaptation yes X X X b b bijk i j k i j k=( ) = + + + + + + +    0 1 2 3    ijkwhere Xi, Xj, Xk and Xl are vectors of variables asso-ciated with LHA i, pharmacy j, patient k and prescrip-tion l, respectively, and bi, bj, and bk are random effectsterms to account for multiple prescriptions from thesame LHA i, pharmacy j and patient k.DiscussionUsing a prospective population-based cohort studyand interrupted time series analyses, we plan to takeLaw et al. BMC Health Services Research 2010, 10:313http://www.biomedcentral.com/1472-6963/10/313Page 5 of 7advantage of a natural experiment in policy change withrespect to pharmacist adaptation and renewal. Short ofa randomized trial, our proposed approach has perhapsthe highest level of internal validity that could bebrought to bear to answer such an important policyquestion. Our analysis will benefit from having compre-hensive population-based data on every prescription forthe majority of the BC population, something that is notpossible in other Canadian jurisdictions with similarpolicies in place. Despite its novelty and strengths, werecognize several limitations.Study LimitationsFirst, while our study methodology is based on astrong quasi-experimental research design, individualpatients could not feasibly be randomized to treatment(as in a controlled trial). While it might have been pos-sible to randomize the pharmacists themselves to whenthey could begin using their advance prescribing privi-leges, this was not part of the policy implementation.Second, our study will be limited to administrativehealth data, and as such will not contain detailed clini-cal data that might be obtained through medicalrecords. Third, we will have limited measures regard-ing the appropriateness of prescribing and patient orphysician or pharmacist satisfaction. Finally, we willnot have access to data on over-the-counter medica-tions use. This will only be a potential issue for thefew drug classes where there are over-the-counterequivalents, such as acid-suppressing drugs. However,as many individuals have low deductibles under BC’sFair PharmaCare program, the prescription alternativewill be less costly for many individuals with regulardrug use.ConclusionIn a recent survey of Canadian policymakers, manyrespondents from across the country ranked the issue ofprescribing privileges as one of their most pressing pol-icy questions [37]. No matter the results of our study,they will be important for policymakers. If we find thepolicy is safe and effective and cost-neutral, it will pro-vide justification for widespread adoption elsewhere andprovide justification for it’s continuation in BC. If itleads to substantially increased drug costs or health careuse, it may need to be significantly altered or aban-doned. However, our study findings will make suchdecisions evidence-based, and help inform other health-care jurisdictions.AcknowledgementsThis study was supported by an operating grant from the CanadianInstitutes of Health Research (MOP-102719, “Effects of PrescriptionAdaptation and Renewal by Pharmacists”, P.I. Michael Law). Dr. Lawreceives salary support through a New Investigator Award from theCanadian Institutes of Health Research and an Early Career Scholar Awardfrom the Peter Wall Institute for Advanced Studies. Dr. Majumdar receivessalary support (Health Scholar) from the Alberta Heritage Foundation forMedical Research. Dr. Lynd is a Michael Smith Foundation for HealthResearch Scholar and Canadian Institutes for Health Research NewInvestigator for which he receives salary support. The authors thankTracey Ma for her assistance with preparing this manuscript. The fundershad no role in the collection, analysis and interpretation of data; in thewriting of the protocol; and in the decision to submit the protocol forpublication.Author details1Centre for Health Services and Policy Research, School of Population andPublic Health, The University of British Columbia. 201-2206 East Mall,Vancouver, BC, V6T 1Z3, Canada. 2Centre for Health Services and PolicyResearch, School of Population and Public Health, The University of BritishColumbia. 201-2206 East Mall, Vancouver, British Columbia, V6T 1Z3, Canada.3Division of General Internal Medicine, Department of Medicine, University ofAlberta. 2E3.07 Walter Mackenzie Centre, Edmonton, AB, T6G 2B7, Canada.4Collaboration for Outcomes Research and Evaluation (CORE), Faculty ofPharmaceutical Sciences, The University of British Columbia and Centre forHealth Evaluation and Outcome Sciences, Providence Health Care ResearchInstitute. 2146 East Mall, Vancouver, British Columbia, V6T 1Z3, Canada.Authors’ contributionsAll authors contributed to the conception and design of the study. MLdrafted the manuscript and all authors participated in revisions forintellectual content. All authors read and approved the final manuscript.Competing InterestsDrs. Law, Morgan and Majumdar declare that they have no competinginterests. Both Drs. Lynd and Marra have received research funding from theBC Pharmacists Association to investigate pharmacy adaptation services inBC.Received: 27 September 2010 Accepted: 17 November 2010Published: 17 November 2010References1. Glazier RH, Klein-Geltink J, Kopp A, Sibley LM: Capitation and enhancedfee-for-service models for primary care reform: a population-basedevaluation. CMAJ 2009, 180:E72-81.2. Nkansah N, Mostovetsky O, Yu C, Chheng T, Beney J, Bond CM, Bero L:Effect of outpatient pharmacists’ non-dispensing roles on patientoutcomes and prescribing patterns. Cochrane Database of SystematicReviews The Cochrane Collaboration, Bero L Chichester, UK: John Wiley &Sons, Ltd; 2010.3. 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Morgan S, Cunningham C: Needs, Gaps and Opportunities Assessment -Emerging Themes. Presentation at the Pharmaceutical Policy ResearchCollaboration meeting. Vancouver, BC; 2009.Pre-publication historyThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6963/10/313/prepubdoi:10.1186/1472-6963-10-313Cite this article as: Law et al.: Effects of prescription adaptation bypharmacists. BMC Health Services Research 2010 10:313.Submit your next manuscript to BioMed Centraland take full advantage of: • Convenient online submission• Thorough peer review• No space constraints or color figure charges• Immediate publication on acceptance• Inclusion in PubMed, CAS, Scopus and Google Scholar• Research which is freely available for redistributionSubmit your manuscript at www.biomedcentral.com/submitLaw et al. BMC Health Services Research 2010, 10:313http://www.biomedcentral.com/1472-6963/10/313Page 7 of 7

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