The influence of physicians on medication adherence

Background: Medication adherence is defined as the extent to which patients take medications according to agreed recommendations from a health care provider. Correspondingly, medication non-adherence is the failure to take medications according to a prescribed medication regimen. Considered one of the greatest challenges to the successful management of people with chronic conditions in the community setting, patients who are non-adherent to medications have higher risks for hospitalization and even death compared to patients who take medications as prescribed. According to a report in 2008, the costs due to non-adherence in the United States (US) was estimated to be between US$100 billion to US$310 billion per year; however, these numbers are based on general assumptions and rigorous estimates are not available in the US or Canada. Despite years of research, major gaps remain in our understanding of the causes of non-adherence. Studies often focus on patient characteristics and patient behaviour. Although some of these factors are influential, they typically only explain a small fraction of the variance in models predicting non-adherence. Prescribing physicians have been identified as having a strong influence on their patient’s adherence to medications; however, their impact has never been comprehensively incorporated into population-based models to help explain the residual variance. Purpose and research approach: The purpose of this research was to examine the impact of physicians on population-based models of medication adherence. Three retrospective cohort studies were conducted using population-based, administrative databases from Saskatchewan, Canada. The study population consisted of new statin users (no statin claims in the previous five year) between 2012 and 2017. Statin medication was the focus in these studies because they are prescribed for chronic treatment only, they had no therapeutic equivalent during the period of study, they are prescribed to a large percentage of the population, and they are associated with reduced morbidity and mortality from atherosclerotic cardiovascular disease. Each study focused on different aspects of the physician’s potential impact on the outcome of optimal medication adherence to statins defined as proportion of days covered (PDC) of at least 80%. Study 1 measured the impact of continuity of care (COC) provided by physician prescribers on optimal adherence; study 2 focused on the impact of demographic characteristics of physicians on optimal adherence; and study 3 measured the overall effect of physicians on the outcome of optimal adherence. Study 1 – The impact of physician continuity of care on medication adherence The first study investigated continuity of care (COC), a factor related to physician practice that is associated with medication adherence and is commonly used as a baseline explanatory variable in population-based studies. COC is typically represented by the usual provider continuity index (UPCI), which is calculated exclusively from the number of outpatient physician visits. However, the number of outpatient visits only represents one aspect of COC. Our aim was to improve the measurement of COC by integrating information on physician services and pharmacy claims (i.e., medication dispensing) data. Our new “integrated COC” definition required patients to have one physician who satisfied all three criteria: a) the most frequently visited general practitioner physician (i.e., usual care provider); b) the statin prescriber; and c) provider of a complete medical examination within the past year. Logistic regression models were constructed with each measure of COC (high UPCI index or integrated COC) on the outcome of optimal statin adherence (PDC ≥80%). Predictive performance of the two models was compared using the DeLong test. In a cohort of 55,144 new statin users, the integrated COC measure had a stronger association with optimal adherence [adjusted odds ratio (aOR) =1.56, 95% confidence interval (CI) 1.50 to 1.63] than UPCI (aOR = 1.23, 95% CI 1.19 to 1.28), and produced greater prediction accuracy of the multivariable model (DeLong test, p<0.0001). The results suggest that physician service and pharmacy claim data should be adopted in COC measures for population-based adherence models because of greater predictive performance in models predicting optimal adherence to statin. Study 2 – Physician demographic factors and medication adherence The second study examined the impact of age or sex concordance (i.e., same age range or same sex) between physicians and patients on optimal adherence to statin medications. We hypothesized that age or sex concordance between physicians and patients would result in higher medication adherence through improved communication and trust compared to non-concordant pairs. Multivariable logistic regression models by generalized estimating equations were applied to examine odds of optimal adherence associated with age and/or sex concordance. Among 51,874 pairs of new statin users and 1,562 prescribers, no influence of age concordance on the odds of optimal adherence could be detected (aOR = 1.02, 95%CI 0.97 to 1.07). The association between sex concordance and optimal statin adherence was stronger but failed to reach statistical significance by a very small margin (aOR=1.05, 95%CI 1.00 to 1.11). It suggested that the potential for an important influence of sex concordance remains and should be investigated in other health care settings. Study 3 – The overall impact of physicians on medication non-adherence The third study aimed to quantify the overall impact of physicians on optimal statin adherence. We identified the prescriber for each new statin user and measured each patient’s adherence one-year after the initial dispensation. The overall physician impact on optimal medication adherence (i.e., PDC >= 80%) was estimated from the intraclass correlation coefficient (ICC) derived from a random intercept model controlled by numerous patient-level variables (e.g., sex, residence, income, etc.). We also examined the impact of unmeasured physician factors or latent effects based on the ICC of a random intercept model controlled by both patient variables and physician-level factors (e.g., country of medical training, remuneration type, statin patient count, etc.). Finally, we estimated the impact of specific physician-level factors [sex, country of medical training, years in practice, remuneration type, number of patients, and number of patients taking a statin (statin patient count)]. Unadjusted odds ratios (uOR) for each factor were generated from logistic regression models; adjusted odds ratios (aORs) were obtained from non-linear mixed-effects logistic regression models adjusted by patient-level variables. Our results were derived from 51,874 new statin users. Addition of the physician effect to a model consisting of multiple patient-level factors only explained an additional 6.4% of the observed variance in adherence between patients, of which physician-level factors had a minimal contribution. The vast majority of the overall physician impact (5.2% out of a possible 6.4%) was attributed to a “latent effect” of the prescriber. The results suggest that the overall impact of prescribers on optimal statin adherence appears to be very limited. Future research Research on the influence of physicians should continue with different types of medications and conditions. Also, specific factors such as COC, type of physician remuneration, sex concordance, and country of medical education require further study to help understand the complex role of physicians and potential new targets for improving medication adherence

Impact of the Saskatchewan seniors’ drug plan (SDP) to medication utilization and adherence among Saskatchewan residents

Background: In 2007, Saskatchewan’s Ministry of Health launched the Seniors’ Drug Plan (SDP), whereby provincial beneficiaries at or above the age of 65 receive medications at a maximum self-payment of $15. The purpose of this study was to document the impact of the SDP using provincial health-administrative databases. Methods: Aggregate medication utilization and costs were described using the prescription drug database starting two years before the implementation of the SDP and continuing for two years after. Interrupted time series analysis using segmented regression models were developed to test the impact of the SDP. Also, the probability of achieving optimal medication adherence was examined among cohorts receiving medications after SDP implementation versus similar patients receiving medications before the SDP and also a group of patients <65 years who were not eligible for the SDP at all. The impact of the SDP on the outcome of optimal adherence was estimated using logistic regression models with generalized estimating equations (GEE). Results: Monthly government spending on medications increased by 47.5% following implementation of the SDP, while total medication dispensations only increased by 5.8%. The SDP was associated with more dispensations per month among prevalent users (+5.4%, 95% CI: 1.3% to 9.5%) but not incident users who did not receive the study medication in the previous 365 days (+1.3%, 95% CI: -8.0% to 10.7%). Similarly, the SDP did not appear to impact the use of blood-glucose-lowering agents, (-0.5%, 95% CI: -6.2% to 5.2%). A small but significant increase in the odds of optimal medication adherence was observed after the SDP compared with before (OR=1.08, 95% CI 1.04 to 1.11). However, the impact was only observed in prevalent users (OR=1.08, 95% CI 1.04 to 1.12), but not incident users (OR=1.05, 95% CI 0.98 to 1.13). Also, the impact of the SDP on medication adherence was not consistent for all medication classes examined. Discussion: In summary, the SDP resulted in substantially higher government investment into drug costs without a major effect on medication utilization and adherence. However, cost reduction for seniors must have provided substantial relief independent of the impact on adherence and utilization

Disease-Modifying Drugs for Multiple Sclerosis and Association With Survival

BACKGROUND AND OBJECTIVES: We examined the association between the disease-modifying drugs (DMDs) for multiple sclerosis (MS) and survival in a multiregion population-based study. METHODS: We accessed multiple administrative health databases from 4 Canadian provinces. Persons with MS were identified and followed from the most recent of the first MS or demyelinating event or January 1, 1996 (index date), until death, emigration, or December 31, 2017. Association between the first-generation and second-generation DMDs and all-cause mortality was examined using stratified Cox proportional hazard models, reported as adjusted hazard ratios (aHRs). Timing of DMD initiation was explored, with findings reported at 2, 5, or 10 years postindex date, representing very early, early, or late initiation. RESULTS: We identified 35,894 persons with MS; 72% were female. The mean age at index date was 44.5 years (SD = 13.6). The total person-years of follow-up while DMD-exposed was 89,180, and total person-years while unexposed was 342,217. Compared with no exposure, exposure to any DMD or to any first-generation DMD was associated with a 26% lower hazard of mortality (both aHRs 0.74; 95% CI 0.56-0.98), while any second-generation DMD exposure was associated with a 33% lower hazard (aHR 0.67; 95% CI 0.46-0.98). Earlier DMD initiation (beta-interferon or glatiramer acetate vs no exposure) was associated with a significant mortality effect (p < 0.05), while later initiation was not (95% CIs included 1). However, the survival advantage with earlier initiation diminished over time, no longer reaching statistical significance at 15 years postindex date. DISCUSSION: Our study demonstrates an association between the DMDs for MS and improved survival in the real-world setting

Disease-modifying drugs for multiple sclerosis and subsequent health service use

OBJECTIVE: We assessed the relationship between the multiple sclerosis (MS) disease-modifying drugs (DMDs) and healthcare use. METHODS: Persons with MS (aged ⩾18 years) were identified using linked population-based health administrative data in four Canadian provinces and were followed from the most recent of their first MS/demyelinating event or 1 January 1996 until the earliest of death, emigration, or study end (31 December 2017 or 31 March 2018). Prescription records captured DMD exposure, examined as any DMD, then by generation (first-generation (the injectables) or second-generation (orals/infusions)) and individual DMD. The associations with subsequent all-cause hospitalizations and physician visits were examined using proportional means model and negative binomial regression. RESULTS: Of 35,894 MS cases (72% female), mean follow-up was 12.0 years, with person-years of DMD exposure for any, or any first- or second-generation DMD being 63,290, 54,605 and 8685, respectively. Any DMD or any first-generation DMD exposure (versus non-exposure) was associated with a 24% lower hazard of hospitalization (adjusted hazard ratio, aHR: 0.76; 95% confidence intervals (CIs): 0.71–0.82), rising to 29% for the second-generation DMDs (aHR: 0.71; 95% CI: 0.58–0.88). This ranged from 18% for teriflunomide (aHR: 0.82; 95% CI: 0.67–1.00) to 44% for fingolimod (aHR: 0.56; 95% CI: 0.36–0.87). In contrast, DMD exposure was generally not associated with substantial differences in physician visits. CONCLUSION: Findings provide real-world evidence of a beneficial relationship between DMD exposure and hospitalizations

Medication adherence in multiple sclerosis as a potential model for other chronic diseases: a population-based cohort study

Objective To determine whether better medication adherence in multiple sclerosis (MS) might be due to specialised disease-modifying drug (DMD) support programmes by: (1) establishing higher adherence in MS than in other chronic diseases and (2) determining if higher adherence is associated with patient-specific or treatment-specific factors.Design Retrospective cohort study with data from 1 January 1996 to 31 December 2015.Setting Population-based health administrative data from three Canadian provinces.Participants Individual cohorts were created using validated case definitions for MS, epilepsy, Parkinson’s disease (PD) and rheumatoid arthritis (RA). Subjects were included if they received ≥1 dispensation for a disease-related drug between 1 January 1997 and 31 December 2014.Main outcome measure(s) Proportion of subjects with optimal adherence (≥80%) measured by the medication possession ratio 1 year after the index date (first dispensation of disease-related drug).Results 126 478 subjects were included in the primary analysis (MS, n=6271; epilepsy, n=55 739; PD, n=21 304; RA, n=43 164). Subjects with epilepsy (adjusted OR, aOR 0.29; 95% CI 0.19 to 0.45), PD (aOR 0.42; 95% CI 0.29 to 0.63) or RA (aOR 0.26; 95% CI 0.19 to 0.35) were less likely to have optimal 1-year adherence compared with subjects with MS. Within the MS cohort, adherence was higher for DMD than for chronic-use non-MS medications, and no consistent patient-related predictors of adherence were observed across all four non-MS medication classes, including having optimal adherence to DMD.Conclusions Subjects with MS were significantly more likely to have optimal 1-year adherence than subjects with epilepsy, RA and PD, and optimal adherence appears related to treatment-specific factors rather than patient-related factors. This supports the hypothesis that higher adherence to the MS DMDs could be due to the specialised support programmes; these programmes may serve as a model for use in other chronic conditions

Reduced Out-of-Pocket Costs and Medication Adherence - A Population-Based Study

Background: In 2007, a drug benefit plan for Seniors (SDP) was launched in Saskatchewan, Canada. SDP capped out-of-pocket costs at $15 per prescription for individuals aged 65 and older. Objectives: To quantify the impact of the SDP on chronic medication adherence. Methods: A retrospective cohort study was conducted for participants aged 65 or older who were eligible to the SPD, controlled by a younger group aged 40 to 64 who were ineligible. Adherence was measured over 365 days using medication possession ratio (MPR). MPRs were compared between age groups, and between pre and post SDP-launch periods. The odds ratio of optimal adherence (i.e., MPR≥80%) was estimated using logistic regression models with generalized estimating equations (GEE). Results: Between 2005 and 2009, 353,568 adherence observations were observed from 188,109 unique patients. Comparing the post-SDP period vs before, the increase in the odds of optimal medication adherence was significant (OR=1.08, 95% CI: 1.04 to 1.11) and was stronger after excluding patients already receiving medication benefits from other government programs (OR= 1.21, 95% CI: 1.16 to 1.26). The SDP was associated with improved adherence among the subgroup of prevalent medication users (OR=1.08, 95% CI: 1.04 to 1.12), but not incident users (OR=1.05, 95% CI: 0.98 to 1.13). Conclusion: Reducing out-of-pocket medication costs for seniors was associated with small improvements in medication adherence across the population

Recent life stress predicts blunted acute stress response and the role of executive control

The present study examined the associations between recent life stress and responses to acute psychological stress, and how these associations varied with executive control. Heart rate (HR), heart rate variability (HRV), salivary cortisol, and affective states were measured before, during and after the Trier Social Stress Test (TSST), an effective laboratory stressor, in 54 healthy participants, and executive control function was tested with a Go/No-Go task in a neutral context on a different day. The hierarchical multiple regression analysis showed that high frequency of life stress during the last twelve months predicted blunted cardiovascular acute stress response, i.e., smaller HR and HRV reactivity. Moreover, the low executive control group showed a significant association between higher recent life stress and blunted acute stress response, which was not apparent in the high executive control group. The results suggested that greater executive control may benefit us with adaptive acute stress response under recent life stress.HighlightsThe Trier Social Stress Test induces cardiovascular and cortisol responses.Higher life event frequency (LEF) predicts smaller cardiovascular stress response.Executive control plays a role in the link of LEF to stress response. The Trier Social Stress Test induces cardiovascular and cortisol responses. Higher life event frequency (LEF) predicts smaller cardiovascular stress response. Executive control plays a role in the link of LEF to stress response