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Predictors of inappropriate and excessive use of reliever medications in asthma: a 16-year population-based… Tavakoli, Hamid; Mark FitzGerald, J.; Lynd, Larry D; Sadatsafavi, Mohsen Feb 12, 2018

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RESEARCH ARTICLE Open AccessPredictors of inappropriate and excessiveuse of reliever medications in asthma:a 16-year population-based studyHamid Tavakoli1,2,3* , J. Mark FitzGerald1,2, Larry D. Lynd1 and Mohsen Sadatsafavi1,2,3AbstractBackground: Understanding factors associated with the inappropriate or excessive use of short-acting beta agonists(SABA) can help develop better policies.Methods: We used British Columbian (BC)‘s administrative health data (1997–2014) to create a retrospective cohort ofasthma patients aged between 14 and 55 years. The primary and secondary outcomes were, respectively, inappropriateand excessive use of SABA based on a previously validated definition. Exposures were categorised into groups comprisingsocio-demographic variables, indicators of type and quality of asthma care, and burden of comorbid conditions.Results: 343,520 individuals (56.3% female, average age 30.5) satisfied the asthma case definition, contributing 2.6 millionperson-years. 7.3% of person-years were categorised as inappropriate SABA use and 0.9% as excessive use. Several factorswere associated with lower likelihood of inappropriate use, including female sex, higher socio-economic status, highercontinuity of care, having received pulmonary function test in the previous year, visited a specialist in the previous year,and the use of inhaled corticosteroids in the previous year. An asthma-related outpatient visit to a general practitioner inthe previous year was associated with a higher likelihood of inappropriate SABA use. Similar associations were found forexcessive SABA use with the exception that visit to respirologist and the use of systemic corticosteroids were associatedwith increased likelihood of excessive use.Conclusions: Despite proven safety issues, inappropriate SABA use is still prevalent. Several factors belonging to patients’characteristics and type/quality of care were associated with inappropriate use of SABAs and can be used to risk-stratifypatients for targeted attempts to reduce this preventable cause of adverse asthma outcomes.BackgroundThe anti-inflammatory properties of inhaled corticosteroids(ICS) and other asthma controller medications result insustained improvement in lung function and a reduction inthe risk of exacerbations [1]. On the other hand, relievermedications such as short-acting beta agonists (SABAs) areassociated with the rapid resolution of symptoms but donot affect the underlying inflammatory process [1]. One ofthe most important concerns in the treatment of asthma ishe adverse effects of the reliever medications, which occursmostly when the proper balance between the controllerand the reliever medication use is not preserved [2]. Theevidence strongly suggests that exposure to relievermedications, in the absence of adequate controller therapy,increases airway hyper-responsiveness, which can eventuallyresult in life threatening exacerbations [3–8].Despite the widespread availability and promotion ofguidelines and evidence-based action plans, SABAscontinue to be used inappropriately in a large number ofindividuals [2, 9, 10]. While the outcomes associatedwith the inappropriate use of SABAs have been studiedby many investigators [4, 5, 11, 12], the reasons behindsuch inappropriate use are unclear.In a previous study, we have documented a steadydecline (5.3% annually) in inappropriate SABA use overa 12-year period in British Columbia (BC), Canada [13].Such a trend implies that the composition of patientsexposed to inappropriate doses of SABAs is rapidly* Correspondence: hamid.tavakoli@ubc.ca1Faculty of Pharmaceutical Sciences, University of British Columbia, 2405Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada2Department of Medicine, Institute for Heart and Lung Health, University ofBritish Columbia, Vancouver, CanadaFull list of author information is available at the end of the article© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Tavakoli et al. BMC Pulmonary Medicine  (2018) 18:33 https://doi.org/10.1186/s12890-018-0598-4changing over time. In this context, identifying factorsassociated with inappropriate exposure to SABAs incontemporary patient populations can help narrow theevidence gap and design targeted strategies towardsreducing this source of preventable burden. Theobjective of this study was to evaluate a relativelycomprehensive range of factors that could potentiallyaffect the inappropriate or excessive use of SABAs in apopulation based asthma cohort.MethodsWe used population-based administrative health data ofBC. BC has a universal health-care system covering itsentire 4.7 Million (as of 2015 [14]) residents. The adminis-trative needs of such a system have resulted in thecreation of centralised databases capturing health-careutilisation records for all of its legal residents. The follow-ing databases were available to us: 1-Discharge AbstractsDatabase (DAD) containing hospitalisation informationincluding admission date and up to 25 discharge diagnosescoded using international classification of diseases, 9th(ICD-9) or 10th (ICD-10) revisions [15], 2-Medical ServicesPlan (MSP) which contains all outpatient services dates,diagnosis, and costs [16], 3-PharmaNET, which containsdispensation information such as unique drug identifier,service date, dispensed quantities and days of supply, andmedication and services costs [17], 4-Vital Statisticsdatabase, which contains information on deaths [18],5-Demographics and Census databases, which containbasic demographic information such as date of birth,sex [19], and census database containing socioeconomicstatus (income quintiles determined from the geographicneighbourhood) [20]. All data were linkable at theindividual level and have shown excellent reliability withvery low rate of missing or incorrect data [21].Data were obtained for the period of January 1st, 1997through March 31th, 2014. We did not use the first yearof data, to allow for sufficient time evaluate thecovariates (e.g., comorbidity indices). Hence, the studyperiod was January 1st, 1998 through March 31th, 2014.The Clinical Research Ethics Board at the University ofBritish Columbia approved this study (H15–00062). Allinferences, opinions, and conclusions drawn in thisresearch are those of the authors and do not reflect theopinions or policies of the data steward(s).Asthma cohortWe created a cohort of individuals with asthma, aged 14to 55, using a validated and previously applied casedefinition [22]. According to this definition, asthma wasidentified if the individual had at least one hospitalisationor used two outpatient services at different dates within a24-month rolling window. We used the internationalclassification of disease (ICD, 9th revision) codes 493.xxor J45/J46 (ICD, 10th revision) for identifying asthma-specific inpatient and outpatient records.Within this cohort, we applied a ‘look-back’ algorithmto determine the first time the patient used any asthma-related health services. This date was referred to as theindex date, marking the beginning of follow-up. Asthmamedications were identified using a pre-specified list(Additional file 1). Follow-up continued to the earliest ofthe following: time of death, end of study period (March,31, 2014), or the last date of resource use of any type.Follow-up time was divided into adjacent 1 year periods.Figure 1 provides the details of the study design.Outcomes and exposuresThe primary outcome was inappropriate use of SABAs, asdefined previously [23]. Each patient-year of data waslabelled as ‘inappropriate use’ if either of the followingconditions was satisfied: 1-no use of ICS with 2 or morepuffs of SABA per week, or 2-use of more than 9 canistersof SABA during the year and no more than 100 μg/day ofICS [2]. Usage was inferred from the dispensation records.The secondary outcome was excessive use of SABA,defined as filling prescriptions for more than 12 canistersof SABA during the year [24]. The decision to evaluate ex-cessive use independent of inappropriate use was made apriori, as we believe that excessive use can be an independ-ent phenomenon likely to occur in patients with difficult-to-control asthma, despite proper controller therapy.Fig. 1 Cohort generation schemaTavakoli et al. BMC Pulmonary Medicine  (2018) 18:33 Page 2 of 8The exposures were measured during the 12-monthperiod preceding the period in which inappropriate orexcessive use was measured (Figure 1). This wasconducted to avoid overlapping exposure and outcomesassessment windows, which can cause time-dependentbiases. Both controller and reliever medications wereadjusted for the defined daily doses (controller medica-tions were adjusted to the beclomethasone equivalentand SABAs to the albuterol equivalent) [4].Factors associated with inappropriate or excessive SABAuseWe considered three groups of variables for theirassociation with the outcomes: socio-demographicvariables, variables pertaining to quality of asthma care,and variables quantifying burden of comorbid condi-tions. The socio-demographic variables included sex,age, and socio economic status (SES). The latter wasdefined as income quintiles inferred from geographicneighbourhoods. Age and SES were measured at thebeginning of each person-year. Variables pertaining tothe quality of asthma care comprised of the receipt ofcare for asthma by general practitioners, specialistconsultations, continuity of care (COC), and whetherpulmonary function tests (PFT) was performed. ForCOC, we calculated the Bice-Boxeman index for eachpatient-year [25]. This index varies between 0 and 1,with zero meaning that an individual’s physician visitswere all to different physicians during the year, and 1meaning that the individual only consulted with thesame physician during the year. The other factors in thecategory of quality of asthma care were the number ofasthma-related hospitalisations, use of any systemiccorticosteroids, and appropriate controller medicationuse. The latter was defined as the ratio of a ICS (eitherin a single inhaler or a combination inhaler with long-acting beta-agonists) to all inhaled medications (bothmeasured in number of canisters), as defined andvalidated previously [26], with a cut-off point of 0.5.Finally, comorbidity-related variables were the numberof non-asthma-related hospitalisations, number of non-asthma-related outpatient visits, and the modifiedCharlson comorbidity score [27] (removing all respira-tory related conditions).Statistical analysisSAS Enterprise Guide (Version 6.1, Cary, NC, USA) wasused for all analyses. The unit of observation was eachpatient-year of follow up. Generalised linear models withgeneralised estimating equations (with a binomial distri-bution and logit link function, given the binary out-comes) were used to account for the clustered nature ofthe data (multiple observation units within the samepatient). The binary dependent variable indicatedinappropriate (primary outcome) or excessive (secondaryoutcome) SABA use. The aforementioned covariatesentered the model as independent variables. All afore-mentioned variables were simultaneously included in theregression model and adjusted for. We excluded theperiods in which individuals had no record of anyasthma-related resource use (hospitalisation, outpatientvisits, or medication dispensation) from the regressionanalysis, as these periods likely represent dormantasthma. However, in a sensitivity analysis we includedsuch periods and repeated all analyses.ResultsA total of 343,520 individuals were included in the study.The mean age on the index date was 30.5 (SD = 13.3);193,992 (56.5%) were female. In total, patients contributed2,623,065 person-years of data. Of these, 24.3% includedperiods without asthma-related resource use and wereremoved from the main analysis. Table 1 provides thebaseline characteristics of the study sample and overalldistribution of outcome variables. Table 2 illustrates thedistribution of the exposure variables.Inappropriate use of SABAIn 190,364 (7.3%) patient-years, SABAs were usedinappropriately. Table 3 provides the results of theregression analyses on the inappropriate and excessiveuse of SABAs.Among the sociodemographic variables, female sex(odds ratio [OR] = 0.67, 95%CI 0.65–0.68, P < 0.001),younger age at baseline (OR = 0.95 per 10-year decrease,95%CI 0.95–0.96, P < 0.001), and higher SES (OR = 0.97per one unit increase in quantile, 95%CI 0.96–0.97,P < 0.001) were associated with a lower likelihood ofinappropriate SABA use. Among type and quality of caremetrics, appropriate use of ICS (ratio of ICS of totalasthma-related medications being above 0.5) was stronglyassociated with a lower risk of inappropriate SABA use inthe next year (OR = 0.10 95%CI 0.10–0.11, P < 0.001).Table 1 Demographic characteristics of the final sampleVariable ValueTotal sample size 343,520Total person years 2,623,065Person years with no asthma resource use a 638,075 (24.3%)Average follow up years (SD) 7.64 (5.3)Inappropriate use of SABA 190,364 (7.3%)Excessive use of SABAs 24,017 (0.9%)Asthma related death 122 (< 0.1%)SD standard deviationaThese periods were removed from the main analysis but were investigated ina sensitivity analysisTavakoli et al. BMC Pulmonary Medicine  (2018) 18:33 Page 3 of 8In a majority (95.1%) of patient-years, general practitioners(GPs) were the sole provider of outpatient care. Receiving atleast one asthma-related consultation with a respirologist(OR= 0.70, 95%CI 0.66–0.75, P < .0001), internal medicinespecialist (OR = 0.69, 95%CI 0.65–0.74, P < .0001), orallergist (OR = 0.48, 95%CI 0.45–0.51, P < .0001), comparedwith no such consultation, was significantly associated witha lower risk of inappropriate use in the next year. On theother hand, an asthma-related GP visit in a given year wasassociated with higher risk of inappropriate SABA use inthe next patient-year compared with periods with one GPvisit. Further, there was an increasing trend betweenthe number of asthma-related GP visits and risk ofinappropriate SABA use with the strongest associationfor patient-years with more than 2 GP visits (OR =1.73,95%CI 1.69–1.77, P < .0001). All levels of continuity ofcare (COC) were associated with lower risk of inappropri-ate use compare to person-years in which COC was zero(OR for the highest level of COC [versus COC= 0] = 0.82,95%CI 0.79–0.85, P < .0001).In the comorbidity indicators category, Charlson scoreand number of non-asthma-related hospitalisationsTable 2 Rates and frequencies of exposure during the follow-up timeVariable Group Variable ValueSocio-demographic variables Female; N (%) 193,992 (56.5%)Age at index date; mean (SD) 30.5 (13.3)Socioeconomic status; N (%)quintile 1 38,501 (11.2%)quintile 2 52,581 (15.3%)quintile 3 65,695 (19.1%)quintile 4 81,610 (23.8%)quintile 5 102,534 (29.8%)Unknown/missing 2599 (0.8%)Type and quality of carefor asthma(measured in the previous year)*Having received pulmonary function test 82,765 (3.2%)Respirologist consultation 47,957 (1.8%)Internal medicine consultation 28,501 (1.1%)Allergist consultation 35,405 (1.3%)General Practitioner visitsNo visit 1,803,958 (68.8%)1 visit 452,950 (17.3%)2 visits 199,816 (7.6%)More than 2 visits 166,341 (6.3%)Continuity of care (COC)COC = 0 275,396 (10.5%)COC > 0 and COC < 50% 2,065,128 (78.7%)COC > =50% and COC < 100% 205,991 (7.9%)COC = 100% 76,550 (2.9%)History of asthma hospitalisation 9936 (0.4%)Ratio of ICS to total asthma medicationsbeing more than 50%776,182 (29.6%)Use of systemic corticosteroids 330,381 (12.6%)Comorbidity(measured in the previous year)Modified Charlson score (SD) 0.1 (2.0)None asthma related outpatient resource use< 5 times outpatient service use 543,505 (20.7%)<=5 and > 10 times outpatient service use 615,599 (23.5%)<=10 and > 20 times outpatient service use 750,000 (28.6%)> 20 times outpatient service use 713,961 (27.2%)Non-asthma related hospitalisation 417,864 (15.9%)*All exposure variables are ascertained in the preceding follow-up periodTavakoli et al. BMC Pulmonary Medicine  (2018) 18:33 Page 4 of 8showed no statistically significant association withinappropriate use of SABA. On the other hand, there wasa strong association between the number of non-asthma-related outpatient encounters and lower likelihood ofinappropriate use of SABA (OR for person-years withmore than 20 visits a year [compared with person-yearswith less than five visits] = 0.63, 95%CI 0.61–0.65,P < .0001). Beside the socio-demographic factors, effect ofthe rest of exposures belong to preceding year.Excessive use of SABAIn 24,017 (0.9%) person-years, SABAs were used exces-sively (more than 12 canisters per year). Among these,6840 (28.5%) were also categorised as inappropriate use.In general, the direction of associations includedcovariates and excessive SABA use was similar to that ofinappropriate use (Table 3). The exceptions were thevisit of a respirologist (OR =1.18, 95%CI 1.07–1.31,P < .0001) and the use of systemic corticosteroids(OR =1.80, 95%CI 1.72–1.90, P < .0001) that wereassociated with an increased likelihood of excessive use.Sensitivity analysisAdditional file 2 illustrates the results for the sensitivityanalysis after repeating the analyses based on all person-years including those with no history of asthma-relatedTable 3 Factors associated with inappropriate and excessive use of SABAInappropriate use Excessive useGroup Variable Odds Ratio 95% CI P value Odds Ratio 95% CI P value(Lower, Upper) (Lower, Upper)Socio-demographic Sex (female = 1) 0.67 0.65–0.68 <.0001 0.50 0.47–0.54 <.0001Higher SES 0.97 0.96–0.97 <.0001 0.92 0.91–0.94 <.0001Year 0.98 0.98–0.98 <.0001 0.99 0.98–0.99 <.0001Age (per 10 years increase) 1.05 1.05–1.06 <.0001 1.36 1.33–1.39 <.0001Type & quality of care for asthma Having received pulmonaryfunction test0.86 0.82–0.89 <.0001 0.90 0.83–0.98 0.0006Respirologist consultation 0.70 0.66–0.75 <.0001 1.18 1.07–1.31 <.0001Internal medicine consultation 0.69 0.65–0.74 <.0001 1.06 0.95–1.18 0.317Allergist consultation 0.48 0.45–0.51 <.0001 0.34 0.28–0.41 <.0001General Practitioner visitsNo visit – – – – – –1 visit PY 1.24 1.22–1.26 <.0001 1.58 1.51–1.66 <.00012 visits PY 1.29 1.27–1.32 <.0001 2.46 2.33–2.61 <.0001More than 2 visits 1.73 1.69–1.77 <.0001 7.24 6.8–7.71 <.0001Continuity of care (COC)COC = 0 – – – – – –COC > 0 and COC < 50% 0.73 0.71–0.75 <.0001 0.92 0.85–0.99 0.0275COC > =50% and COC < 100% 0.77 0.75–0.8 <.0001 0.94 0.85–1.03 0.1953COC = 100% 0.82 0.79–0.85 <.0001 0.96 0.84–1.08 0.4703Asthma-related hospitalisation 1.46 1.34–1.58 <.0001 1.48 1.33–1.65 <.0001Appropriate use of ICS 0.10 0.10–0.11 <.0001 0.09 0.09–0.10 <.0001Systemic corticosteroid 0.61 0.60–0.63 <.0001 1.80 1.72–1.90 <.0001Comorbidity-related variables Modified Charlson score (SD) 0.99 0.97–1.00 0.1371 0.95 0.91–1.00 0.0201None asthma related outpatientresource utilisations< 5 times – – – – – –<=5 and > 10 times 0.77 0.76–0.79 <.0001 0.84 0.79–0.89 <.0001<=10 and > 20 times 0.68 0.67–0.7 <.0001 0.79 0.74–0.85 <.0001> 20 times 0.63 0.61–0.65 <.0001 0.81 0.75–0.88 <.0001None asthma related hospitalisation 1.09 1.07–1.11 <.0001 1.33 1.27–1.39 <.0001Entire covariates have been simultaneously included in the regression modelTavakoli et al. BMC Pulmonary Medicine  (2018) 18:33 Page 5 of 8resource use. The direction and magnitude of the associ-ations for all exposures were similar with those of themain analysis.DiscussionWe evaluated the association between several patient-and care-related factors and inappropriate/excessive useof SABAs. We found that patients who received appro-priate amount of ICS, visited a specialist, or had bettercontinuity of care were less likely to use SABAs inappro-priately in the following year. In addition, we found thatindividuals with a higher SES had a lower likelihood ofinappropriate use of SABAs. On the other hand, patientswho had more frequent general practitioner visits forasthma had a higher likelihood of inappropriate SABAuse in the following year. Overall, many modifiablefactors representing type and quality of care (e.g., GPvisits, specialist visits, continuity of care, history of PFT)were associated with inappropriate use of SABAs,indicating that inappropriate SABA use is at leastpartially preventable. An important finding was thestrong negative association with previous appropriateICS use and future excessive SABA use. These resultsindicate that excessive SABA use, even in severe asthma,can be prevented with adequate controller therapy.While excessive SABA use was less prevalent thaninappropriate use, factors associated with both outcomeswere generally similar, with two exceptions: the use ofsystemic corticosteroids and the visit to a respirologistwere associated with a lower likelihood of inappropriateuse but a higher likelihood of excessive use. Bothfindings can be attributable to the residual confoundingeffect of asthma severity not captured in the othercovariates. For example, it is likely that specialists tendto better adhere to respiratory guidelines, as comparedwith generalists, thus leading to lower levels of inappro-priate reliever use. However, patients with very severe ordifficult-to-treat asthma, who require high dose relievertherapy, are more likely to be referred to a respirologist,resulting in a higher proportion of excessive SABA use.Some of the reported associations in the present studyhave been previously reported. Blanchette et al. demon-strated that patients are more likely to be prescribed anICS if they have a respirologist or allergy consultation(thus reducing the risk of inappropriate reliever use)[28]. Other investigators have shown that women tendto be more adherent to prescribed asthma therapies thanmen, which is compatible with their observed the lowerrisk of inappropriate reliever use in our study [29]. Con-sultation with a specialist has previously been associatedwith more appropriate use of asthma medications [30].To the best of our knowledge, other associations namelythe SES and continuity of care have not been previosulyevaluated. There may be many reasons for the low SESbeing associated with higher rate of inappropriateasthma medication use. In addition to potential differ-ences in environmental risk factors, access to high qual-ity care might be difficult for patients who are socio-economically challenged. In addition, while the publichealthcare system in Canada provides free inpatient andoutpatient care, medication is generally not covered.Hence lower-income individuals might have difficultiesaffording the controller medications (e.g., combinationinhalers of ICS and LABA). A previous study has illus-trated a strong socio-economic gradient in the burden ofasthma even in a public health-care system such as thatof BC [31].The major strength of this study was its large,population-based sample with a long follow-up time,which provided estimates of association with a low levelof uncertainty. The universal coverage of the health-caresystem means there was no self-selection through enrol-ment. Thus our findings can have high external validityin the jurisdictions with similar health-care settings.However, the limitations of the study should also beacknowledged. Filling prescriptions does not equateusage. As such, the associations reported in this studyare diluted by the extent medication dispensation deviatesfrom the actual intake. In addition, we could not evaluateseveral important variables that could moderate the effectof, or interact with, the studied variables (e.g., smokingstatus, education, levels of airflow obstruction, asthma se-verity, and patient adherence to medication). Evaluatingsuch associations requires databases with richer clinicalcontent but this will likely come at the cost of generalis-ability and external validity of the results given theinevitable self-selection of patients into clinical cohorts.ConclusionsConsidering the high prevalence of asthma, the observedlevel of inappropriate use of reliever medications resultsin thousands of patients being at risk of preventableadverse outcomes every year. In a separate work base onthe same data, it has been shown that inappropriateSABA use continues to be associated with adverseasthma-related outcomes, specifically a 45% increase inrisk of asthma-related hospitalization, 25% increase inasthma-related ED visits, and 6.5% increase in asthma-related medication cost [32]. Our study shows thatseveral factors associated with inappropriate use arepotentially modifiable, specifically factors pertaining tothe type and quality of care. Indeed, previous researchhas demonstrated that simple advice to physiciansprescribing relievers can result in significant decreases inthe total reliever use [33]. Given that the majority ofasthma patients in our sample received general practicecare, interventions aimed at improving general practi-tioner’s adherence to evidence-based guidelines have theTavakoli et al. BMC Pulmonary Medicine  (2018) 18:33 Page 6 of 8potential to improve asthma medication use. Futurestudies need to evaluate the behavioural factors and therole of patient education as potential determinants ofappropriate asthma treatment.Additional filesAdditional file 1: List of asthma-related medications. (DOCX 14 kb)Additional file 2: Sensitivity analysis after including all patient-years withno history of asthma related healthcare use. (DOCX 18 kb)AbbreviationsBC: British Columbia; COC: Continuity of care; DAD: Discharge AbstractsDatabase; GP: General practitioners; ICD: International classification ofdiseases; ICS: Inhaled corticosteroids; MSP: Medical Services Plan; OR: Oddsratio; PFT: Pulmonary function test; SABA: Short-acting beta agonists;SES:: Socio economic statusAcknowledgementsNot applicable.FundingThis study was funded by an arm’s length research contract withAstraZeneca Canada, mediated through and approved by the University-Industry Liaison Office at the University of British Columbia.Availability of data and materials1-Discharge Abstracts Database (DAD [15].2-Medical Services Plan (MSP) [16].3-PharmaNET [17].4-Vital Statistics database [18].5-Demographics and Census databases [19].Authors’ contributionsMS, JMF, and LL formulated the idea. MS and HT designed the study andcreated the data analysis plan. JMF and LL provided feedback on the design.HT performed all the statistical analyses. HT wrote the first draft of themanuscript. All authors critically commented on the manuscript andapproved the final version. MS and HT are guarantors of the manuscript.Ethics approval and consent to participateThe Clinical Research Ethics Board at the University of British Columbiaapproved this study (H15–00062). The anonymized data were provided to usthrough the Freedom of Information and Protection of Privacy Act (FIPPA).Consent for publicationNot applicable.Competing interestsJMF has served on advisory boards for, AstraZeneca, Novartis, Pfizer, Novartis,Boehringer-Ingelheim. He has also been a member of speakers’ bureaus for,AstraZeneca, Boehringer-Ingelheim, Pfizer, and Merck. He has received re-search funding paid directly to the University of British Columbia from theCanadian Institutes of Health Research, AstraZeneca, Glaxo-SmithKline,Boehringer-Ingelheim, Merck, Amgen, and Genentech. JMF is a member ofthe Global Initiative for Asthma (GINA) Executive and Science Committee. LLhas served on advisory boards from AstraZeneca, Novartis, Boehringer-Ingelheim, Teva, and Pfizer.Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.Author details1Faculty of Pharmaceutical Sciences, University of British Columbia, 2405Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada. 2Department of Medicine,Institute for Heart and Lung Health, University of British Columbia,Vancouver, Canada. 3Centre for Clinical Epidemiology and Evaluation,University of British Columbia, Vancouver, Canada.Received: 23 January 2018 Accepted: 29 January 2018References1. Lougheed MD, Lemiere C, Ducharme FM, Licskai C, Dell SD, Rowe BH, et al.Canadian thoracic society 2012 guideline update: diagnosis andmanagement of asthma in preschoolers, children and adults. Can Respir J JCan Thorac Soc. 2012;19:127–64.2. Anis AH, Lynd LD, Wang XH, King G, Spinelli JJ, FitzGerald M, et al. 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