Factors associated with first-fill adherence rates for diabetic medications: a cohort study

Exploring patient medication adherence and data mining methods in clinical big data: A contemporary review

BACKGROUND

Increasingly, patient medication adherence data are being consolidated from claims databases and electronic health records (EHRs). Such databases offer an indirect avenue to gauge medication adherence in our data-rich healthcare milieu. The surge in data accessibility, coupled with the pressing need for its conversion to actionable insights, has spotlighted data mining, with machine learning (ML) emerging as a pivotal technique. Nonadherence poses heightened health risks and escalates medical costs. This paper elucidates the synergistic interaction between medical database mining for medication adherence and the role of ML in fostering knowledge discovery.

METHODS

We conducted a comprehensive review of EHR applications in the realm of medication adherence, leveraging ML techniques. We expounded on the evolution and structure of medical databases pertinent to medication adherence and harnessed both supervised and unsupervised ML paradigms to delve into adherence and its ramifications.

RESULTS

Our study underscores the applications of medical databases and ML, encompassing both supervised and unsupervised learning, for medication adherence in clinical big data. Databases like SEER and NHANES, often underutilized due to their intricacies, have gained prominence. Employing ML to excavate patient medication logs from these databases facilitates adherence analysis. Such findings are pivotal for clinical decision-making, risk stratification, and scholarly pursuits, aiming to elevate healthcare quality.

CONCLUSION

Advanced data mining in the era of big data has revolutionized medication adherence research, thereby enhancing patient care. Emphasizing bespoke interventions and research could herald transformative shifts in therapeutic modalities.

Prevalence and predictors of primary nonadherence to medications prescribed in primary care

BACKGROUND

Most research on medication adherence has focused on secondary nonadherence and persistence to therapy. Medication prescriptions that are never filled by patients (primary nonadherence) remain understudied in the general population.

METHODS

We linked prescribing data from primary care electronic medical records to comprehensive pharmacy dispensing claims between January 2013 and April 2019 in British Columbia (BC) to estimate primary nonadherence, defined as failure to dispense a new medication or its equivalent within 6 months of the prescription date. We used hierarchical multivariable logistic regression to determine prescriber, patient and medication factors associated with primary nonadherence among community-dwelling patients in primary care.

RESULTS

Among 150 565 new prescriptions to 34 243 patients, 17% of prescriptions were never filled. Primary nonadherence was highest for drugs prescribed mostly on an as-needed basis, including topical corticosteroids (35.1%) and antihistamines (23.4%). In multivariable analysis, primary nonadherence was lower for prescriptions issued by male prescribers (odds ratio [OR] 0.66, 95% confidence interval [CI] 0.50-0.88). Primary nonadherence decreased with patient age (OR 0.91, 95% CI 0.90-0.92 for each additional 10 years) but increased with polypharmacy among patients aged 65 years or older. Patients filled more than 82% of their medication prescriptions within 2 weeks after their primary care provider visit.

INTERPRETATION

The prevalence of primary nonadherence to new prescriptions was 17%. Interventions to address primary nonadherence could target older patients with multiple medication use and within the first 2 weeks of the prescription issue date.

Not obtaining a medication the first time it is prescribed: primary non-adherence to cardiovascular pharmacotherapy

Primary medication non-adherence describes the situation when a first prescription for a new medication is never filled. Primary non-adherence is an important, yet understudied aspect of reduced effectiveness of pharmacotherapy. This review summarizes the frequency, impact, reasons, predictors, and interventions regarding primary non-adherence to cardiovascular/cardiometabolic drugs. The current literature reveals a high prevalence of primary non-adherence. The individual risk of primary non-adherence is determined on multiple factors, e.g., primary non-adherence of lipid-lowering drugs is higher compared to antihypertensive medications. However, the overall rate of primary non-adherence is > 10%. Additionally, this review identifies specific areas for research to better understand why patients forgo evidence-based beneficial pharmacotherapy and to explore targeted interventions. At the same time, measures to reduce primary non-adherence-once proven to be effective-may represent an important new opportunity to reduce cardiovascular diseases.

Automated versus manual prior authorization for diabetes mellitus drugs: A retrospective study from Israel

Introduction

Drug prior authorization (PA) imposes a bureaucratic and economic burden on healthcare service providers and payers. A novel automated PA system may improve these drawbacks.

Methods

An historical cohort study from a large health maintenance organization in Israel, comparing manual versus automated PA mechanisms for diabetes mellitus (DM) drugs: sodium-glucose co-transporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 analogs (GLP1-A). We compared patients with DM, whose first drug applications were approved using the automated system, with similar patients whose first drug applications were approved by manual PA. The primary endpoint was the time elapsed from application approval to prescription filling (accessibility time). Secondary endpoints included the prescription filling rate at 7 and 30 days.

Results

In total, 1371 automated approved prescriptions and 1240 manually approved prescriptions were included in the analysis. Median accessibility time was one day (interquartile range (IQR) 0-5) with automated PA for both GLP1-A and SGLT2i, compared with four days (IQR 1-9) and three days (IQR 1-8), respectively, with the manual PA (p < 0.001). Eighty-four percent of GLP1-A automated PA approvals were filled within seven days compared with 70% with manual PA (p < 0.001). Similar results were seen with SGLT2i (80% vs. 72%, p < 0.008). No differences were observed at 30 days post-approval. Using logistic regression, odds for GLP1-A and SGLT2i prescription filling within seven days were 2.36 and 1.53 folds higher (respectively) with automated PA (p < 0.01).

Conclusions

Automated PA system improved access time to SGLT2i/GLP1-A seven days post-approval compared to manual PA.

Pediatric Medication Noninitiation in Spain

OBJECTIVES

To estimate medication noninitiation prevalence in the pediatric population and identify the explanatory factors underlying this behavior.

METHODS

Observational study of patients (<18 years old) receiving at least 1 new prescription (28 pharmaceutical subgroups; July 2017 to June 2018) in Catalonia, Spain. A prescription was considered new when there was no prescription for the same pharmaceutical subgroup in the previous 6 months. Noninitiation occurred when a prescription was not filled within 1 month or 6 months (sensitivity analysis). Prevalence was estimated as the proportion of total prescriptions not initiated. To identify explanatory factors, a multivariable multilevel logistic regression model was used, and adjusted odds ratios were reported.

RESULTS

Overall, 1 539 003 new prescriptions were issued to 715 895 children. The overall prevalence of 1-month noninitiation was 9.0% (ranging from 2.6% [oral antibiotics] to 21.5% [proton pump inhibitors]), and the prevalence of 6-month noninitiation was 8.5%. Noninitiation was higher in the youngest and oldest population groups, in children from families with a 0% copayment rate (vulnerable populations) and those with conditions from external causes. Out-of-pocket costs of drugs increased the odds of noninitiation. The odds of noninitiation were lower when the prescription was issued by a pediatrician (compared with a primary or secondary care clinician).

CONCLUSIONS

The prevalence of noninitiation of medical treatments in pediatrics is high and varies according to patients' ages and medical groups. Results suggest that there are inequities in access to pharmacologic treatments in this population that must be taken into account by health care planners and providers.

Non-initiation of prescribed medication from a Spanish health professionals' perspective: A qualitative exploration based on Grounded Theory

We explore, from the perspective of primary care health professionals, the motivations that lead patients to not initiate prescribed treatments, by developing a qualitative study in Spanish primary care. Six focus groups (N = 46) were conducted with general practitioners, nurse practitioners, social workers and community pharmacists and carried out in primary care (PC) of Barcelona Province, from April to July of 2018. The 46 participants were identified by three general practitioners and two pharmacists. In the interviews, the reasons for non-initiation of PC patients' medication were explored. Triangulated content analysis was performed. Patients' perspective, analysed in a previous study, and professionals' perspective agree on most of the factors that affect non-initiation. New factors were categorized into existent categories, confirming, and supplementing the model developed with patients. Health professionals identified some new factors which were not present in the patients' discourse, such as stigma related to the drug, hidden reasons for consultation, the role of nurses in prescription and support, the role of the pharmacy technician, illiteracy and lack of social support. The professionals confirm and expand on the Theoretical Model of Medication Non-Initiation. Primary care professionals should consider the factors described when prescribing a new medication. Knowledge contributed by the model should guide the design of interventions to improve initiation.

Combining patient reported outcomes and EHR data to understand population level treatment needs: correcting for selection bias in the migraine signature study

BACKGROUND

Electronic health records (EHR) data can be used to understand population level quality of care especially when supplemented with patient reported data. However, survey non-response can result in biased population estimates. As a case study, we demonstrate that EHR and survey data can be combined to estimate primary care population prescription treatment status for migraine stratified by migraine disability, without and with adjustment for survey non-response bias. We selected disability as it is associated with survey participation and patterns of prescribing for migraine.

METHODS

A stratified random sample of Sutter Health adult primary care (PC) patients completed a digital survey about headache, migraine, and migraine related disability. The survey data from respondents with migraine were combined with their EHR data to estimate the proportion who had prescription orders for acute or preventive migraine treatments. Separate proportions were also estimated for those with mild disability (denoted "mild migraine") versus moderate to severe disability (denoted mod-severe migraine) without and with correction, using the inverse propensity weighting method, for non-response bias. We hypothesized that correction for non-response bias would result in smaller differences in proportions who had a treatment order by migraine disability status.

RESULTS

The response rate among 28,268 patients was 8.2%. Among survey respondents, 37.2% had an acute treatment order and 16.8% had a preventive treatment order. The response bias corrected proportions were 26.2% and 11.6%, respectively, and these estimates did not differ from the total source population estimates (i.e., 26.4% for acute treatments, 12.0% for preventive treatments), validating the correction method. Acute treatment orders proportions were 32.3% for mild migraine versus 37.3% for mod-severe migraine and preventive treatment order proportions were 12.0% for mild migraine and 17.7% for mod-severe migraine. The response bias corrected proportions for acute treatments were 24.8% for mild migraine and 26.6% for mod-severe migraine and the proportions for preventive treatment were 8.1% for mild migraine and 12.0% for mod-severe migraine.

CONCLUSIONS

In this study, we combined survey data with EHR data to better understand treatment needs among patients diagnosed with migraine. Migraine-related disability is directly related to preventive treatment orders but less so for acute treatments. Estimates of treatment status by self-reported disability status were substantially over-estimated among those with moderate to severe migraine-related disability without correction for non-response bias.

Applying the Social-Ecological Approach to Evaluate Diabetes Medication Management in Older People

Glucagonlike peptide-1 receptor agonist is a common antidiabetic medication class to lower HbA1c, weight, and cardiovascular risk. This case study describes the challenges a patient with uncontrolled diabetes faced after receiving a prescription for liraglutide because of multiple levels of influence, including individual, family, institutional, and policy level barriers. The case highlights the importance of utilizing a person-centered care approach by evaluating patient's preferences, visual and motor coordination, cognitive function, psychological stress, and medication cost before prescribing injectable products for elderly patients.

Factors associated with primary nonadherence to newly initiated direct oral anticoagulants in patients with nonvalvular atrial fibrillation

BACKGROUND: Direct oral anticoagulants (DOACs) are widely used for the prevention of stroke in nonvalvular atrial fibrillation (NVAF); however, real-world primary nonadherence (failing to collect the first prescription) has been measured in very few studies. OBJECTIVE: To report primary nonadherence in NVAF patients who are newly prescribed DOACs and identify associated factors. METHODS: This observational retrospective cohort study used a large primary care database in Catalonia. Patients with NVAF who were newly prescribed a DOAC between January 2009 and December 2015 were identified, and primary nonadherence was measured by comparing prescribing records to pharmacy claims data. Multivariable logistic regression was used to determine associated factors. RESULTS: A total of 12,257 patients met the inclusion and exclusion criteria; of these, 1,276 (10.4%) were primary nonadherent. Primary nonadherence was found to be 12.8% for apixaban, 8.6% for dabigatran, and 10.8% for rivaroxaban. Multivariable logistic regression indicated higher odds of primary nonadherence with apixaban and rivaroxaban compared to dabigatran (apixaban: OR = 1.61, 95% CI = 1.39-1.87; rivaroxaban: OR = 1.28, 95% CI = 1.11-1.47). Patients aged at least 80 years showed lower odds of primary nonadherence compared to those aged less than 65 years (OR = 0.78, 95% CI = 0.66-0.93). A diagnosis of chronic kidney disease was associated with primary nonadherence (OR = 1.27, 95% CI = 1.08-1.50). Whereas, diabetes (OR = 0.85, 95% CI = 0.74-0.97), hypertension (OR = 0.79, 95% CI = 0.70-0.91), and stroke/transient ischemic attack (OR = 0.70, 95% C I =0.59-0.82) were inversely associated with primary nonadherence. CONCLUSIONS: Overall, 10.4% of patients prescribed DOACs were primary nonadherent, failing to collect the first prescription. The percentage could have serious implications for patient outcomes and the real-world cost-effectiveness of prescribing DOACs in NVAF. Rates of primary nonadherence and associated factors may provide useful information for the design and evaluation of adherence interventions. DISCLOSURES: No outside funding was received for this study. The data for this study came from the European Medicines Agency PE-PV project (Grant/Award Number EMA/2015/27/PH). The authors have nothing to disclose. A preliminary version of this work was presented at the European Drug Utilisation Research Group (EuroDURG) Conference, Szeged, Hungary, March 5, 2020.

Diabetes medication regimens and patient clinical characteristics in the national patient-centered clinical research network, PCORnet

We used electronic medical record (EMR) data in the National Patient-Centered Clinical Research Network (PCORnet) to characterize "real-world" prescription patterns of Type 2 diabetes (T2D) medications. We identified a retrospective cohort of 613,203 adult patients with T2D from 33 datamarts (median patient number: 12,711) from 2012 through 2017 using a validated computable phenotype. We characterized outpatient T2D prescriptions for each patient in the 90 days before and after cohort entry, as well as demographics, comorbidities, non-T2D prescriptions, and clinical and laboratory variables in the 730 days prior to cohort entry. Approximately half of the individuals in the cohort were females and 20% Black. Hypertension (60.3%) and hyperlipidemia (50.5%) were highly prevalent. Most patients were prescribed either a single T2D drug class (42.2%) or had no evidence of a T2D prescription in the EMR (42.4%). A smaller percentage was prescribed multiple T2D drug types (15.4%). Among patients prescribed a single T2D drug type, metformin was the most common (42.6%), followed by insulin (18.2%) and sulfonylureas (13.9%). Newer classes represented approximately 13% of single T2D drug type prescriptions (dipeptidyl peptidase-4 inhibitors [6.6%], glucagon-like peptide-1 receptor agonists [2.5%], thiazolidinediones [2.0%], and sodium-glucose cotransporter-2 inhibitors [1.6%]). Among patients prescribed multiple T2D drug types, the most common combination was metformin and sulfonylureas (63.5%). Metformin-based regimens were highly prevalent in PCORnet's T2D population, whereas newer agents were prescribed less frequently. PCORnet is a novel source for the potential conduct of observational studies among patients with T2D.

Assessment of diabetic patients' adherence to insulin injections on basal-bolus regimen in diabetic care center in Saudi Arabia 2018: Cross sectional survey

Background:

Since insulin became a focal point of diabetes management, several studies have been carried out to monitor and improve patient outcomes. Adherence insulin therapy is an important part of diabetes management.

Aim:

This study reviews the responses of patients being managed in a diabetic care setting in monitoring their adherence to basal bolus insulin therapy.

Method:

A pre-validated questionnaire containing 18 questions was administered to patients in the diabetic care unit of the Security Forces Hospital, Riyadh, Saudi Arabia.

Results:

The levels of adherence with basal bolus insulin therapy was 61.9%. There is no considerable difference in adherence levels of male and female respondents with 31.62% and 31.58% respectively. The younger age groups (14-29) had the highest adherence levels at 65.75%. Higher levels of patient literacy and the location also have a positive relationship with adherence.

Conclusion:

To improve adherence levels, dosing should be made with consideration for patient convenience, and patients should be encouraged to build positive psychological relationships. Further studies should look to studying outcomes of therapy, and markers should be developed to monitor patient progress on therapy regimen regularly. The aspect of short clinic visits is another major consideration that needs to be look into properly to understand and monitor patients’ proper adherence toward the basal bolus insulin.

Prevalence of and factors associated with primary medication non-adherence in chronic disease: A systematic review and meta-analysis

BACKGROUND

Primary medication non-adherence (PMN), defined as failure to obtain newly prescribed medications, results in adverse clinical and economic outcomes. We aimed to (a) assess the prevalence of PMN in six common chronic diseases: asthma and/ or chronic obstructive pulmonary disease, depression, diabetes mellitus, hyperlipidaemia, hypertension and osteoporosis; (b) identify and categorise factors associated with PMN; (c) explore characteristics that contributed to heterogeneity between studies.

METHODS

We performed a systematic search in MEDLINE, Embase, Cochrane Library, CINAHL and PsycINFO. Studies published in English between January 2008 and August 2018 assessing PMN in subjects aged ≥18 years were included. We used the Cochrane risk of bias tool, Newcastle-Ottawa Scale and National Heart, Lung and Blood Institute Quality Assessment Tool to assess the quality of randomised controlled trials, cohort and cross-sectional studies, respectively. Findings were reported using the PRISMA checklist. PMN rates were pooled using a random effects model. We summarised factors associated with PMN descriptively. Subgroup analysis was performed to explore sources of heterogeneity.

RESULTS

We screened 3083 articles and included 33 (5 randomised controlled trials, 26 cohort and 2 cross-sectional studies, n = 539 156), of which 31 (n = 519 971) were used in meta-analysis. The pooled PMN rate was 17% (95% CI: 15%-20%). Pooled PMN rates were highest in osteoporosis (25%, 95% CI: 7%-44%) and hyperlipidaemia (25%, 95% CI: 18%-32%) and lowest in diabetes mellitus (10%, 95% CI: 7%-12%). Factors commonly associated with PMN include younger age, number of concurrent medications, practitioner specialty and higher co-payment. Type of chronic disease, age, study setting and PMN definition contributed to heterogeneity between studies (all P < 0.001).

CONCLUSION

Primary medication non-adherence is common among patients with chronic diseases and more needs to be done to address this issue in order to improve patient outcomes. Future PMN studies could benefit from greater standardisation to enhance comparability.

Primary nonadherence to chronic disease medications: a meta-analysis

BACKGROUND

Medication nonadherence is a global problem that requires urgent attention. Primary nonadherence occurs when a patient consults with a medical doctor, receives a referral for medical therapy but never fills the first dispensation for the prescription medication. Nonadherence to chronic disease medications costs the USA ~$290 billion (USD) every year in avoidable health care costs. In Canada, it is estimated that 5.4% of all hospitalizations are due to medication nonadherence.

OBJECTIVES

The objective of this study was to quantify the extent of primary nonadherence for four of the most common chronic disease medications. The second objective was to identify factors associated with primary nonadherence to chronic disease medications.

MATERIALS AND METHODS

We conducted an extensive systematic literature review of eight databases with a wide range of keywords. We identified relevant articles for primary nonadherence to antihypertensives, lipid-lowering agents, hypoglycemics, and antidepressants. After further screening and assessment of methodologic quality, relevant data were extracted and analyzed using a random-effects model.

RESULTS

Twenty-four articles were included for our meta-analysis after full review and assessment for risk of bias. The pooled primary nonadherence rate for the four chronic disease medications was 14.6% (95% CI: 13.1%-16.2%). Primary medication nonadherence was higher for lipid-lowering medications among the four chronic disease medications assessed (20.8%; 95% CI: 16.0%-25.6%). The rates in North America (17.0%; 95% CI: 14.4%-19.5%) were twice those from Europe (8.5%; 95% CI: 7.1%-9.9%). The absence of social support (20%; 95% CI: 14.4%-26.6%) was the most common sociodemographic variable associated with chronic disease medication primary nonadherence.

CONCLUSION

Evidence suggests that a considerable percentage of patients do not initially fill their medications for treatable chronic diseases or conditions. This represents a major health care problem that can be successfully addressed. Efforts should be directed toward proper medication counseling, patient social support, and clinical follow-up, especially when the indications for the prescribed medication aim to provide primary prevention.

Evaluating the Impact of Prescription Fill Rates on Risk Stratification Model Performance

BACKGROUND

Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates-extracted by comparing electronic health record prescriptions and pharmacy claims fills-represent a novel measure of medication adherence and may improve the performance of risk adjustment models.

OBJECTIVE

We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prospective costs and utilization.

METHODS

We conducted a retrospective cohort study of 43,097 primary care patients from HealthPartners network between 2011 and 2012. Diagnosis and/or pharmacy claims of 2011 were used to build 3 base models using the Johns Hopkins ACG system, in addition to demographics. Model performances were compared before and after adding 3 types of prescription fill rates: primary 0-7 days, primary 0-30 days, and overall. Overall fill rates utilized all ordered prescriptions from electronic health record while primary fill rates excluded refill orders.

RESULTS

The overall, primary 0-7, and 0-30 days fill rates were 72.30%, 59.82%, and 67.33%. The fill rates were similar between sexes but varied across different medication classifications, whereas the youngest had the highest rate. Adding fill rates modestly improved the performance of all models in explaining medical costs (improving concurrent R by 1.15% to 2.07%), followed by total costs (0.58% to 1.43%), and pharmacy costs (0.07% to 0.65%). The impact was greater for concurrent costs compared with prospective costs. Base models without diagnosis information showed the highest improvement using prescription fill rates.

CONCLUSIONS

Prescription fill rates can modestly enhance claims-based risk prediction models; however, population-level improvements in predicting utilization are limited.

Factors predicting self-reported medication low adherence in a large sample of adults in the US general population: a cross-sectional study

OBJECTIVES

The study objective was to determine the level and correlates of self-reported medication low adherence in the US general population.

SETTING

A 30 min cross-sectional online survey was conducted with a national sample of adults.

PARTICIPANTS

9202 adults (aged 18+) who had filled at least three or more prescriptions at a community pharmacy in the past 12 months.

PRIMARY AND SECONDARY OUTCOME MEASURES

Self-reported medication adherence was measured with the 8-item Morisky Medication Adherence Scale.

RESULTS

Low adherence was reported by 42.0%, 29.4% had medium adherence and 28.6% had high adherence. Low adherence was significantly associated with: lower age, being of Hispanic origin or African-American, having difficulty with healthcare, medication or transportation costs, needing the support of others to access primary care, health limiting activity, using multiple providers, infrequent visits to primary care providers and visiting an emergency department >3 times in last 12 months.

CONCLUSIONS

A very high level of low medication adherence is seen in the general population, particularly for ethnic minorities, those who use multiple healthcare providers and those who experience barriers to access for regular primary care. As clinical, patient education and counselling, and healthcare policy initiatives are directed to tracking the problem of low medication adherence, these should be priority populations for research and interventions.

[Evaluation of primary adherence to medications in patients with chronic conditions: A retrospective cohort study]

OBJECTIVES

To assess the proportion of members of a private health insurance at the Hospital Italiano de Buenos Aires with primary adherence to, 1) bisphosphonates for secondary prevention of osteoporotic fractures, 2) insulin and metformin in type 2 diabetes, and 3) tamoxifen in the context of treatment of breast cancer.

DESIGN

Retrospective cohort study to determine the proportion of primary treatment adherence during 2012 and 2013. SITE: Hospital Italiano de Buenos Aires, Argentina.

PARTICIPANTS

Members of the Hospital Italiano de Buenos Aires private health insurance, who had received a new electronic prescription (alendronate or ibandronate for secondary prevention of fractures following an osteoporotic fracture; insulin and/or metformin for type 2 diabetes; or tamoxifen as a treatment for breast cancer) during the years 2012 and 2013. An analysis was performed on 1,403 new electronic prescriptions, of which 673 were excluded for not meeting the inclusion criteria.

MAIN MEASUREMENTS

Primary adherence has been defined as the execution of a first-time treatment after it was agreed with the health care provider. The primary analysis assessed the proportion of primary adherence for the three medications. A bivariate analysis was performed to compare the characteristics and potential predictors of primary adherence.

RESULTS

Primary adherence for each drug group was, 93% Bisphosphonates, 88% Metformin, 96% Insulin, and 92% Tamoxifen.

CONCLUSIONS

To the best of our knowledge, this is the first study that has evaluated primary adherence in Argentina, and the first for Tamoxifen world wide. The primary adherence documented in our study was somewhat higher than that reported in the literature.

Medication Adherence: Truth and Consequences

Improving medication adherence may have a greater influence on the health of our population than in the discovery of any new therapy. Patients are nonadherent to their medicine 50% of the time. Although most physicians believe nonadherence is primarily due to lack of access or forgetfulness, nonadherence can often be an intentional choice made by the patient. Patient concealment of their medication-taking behavior is often motivated by emotions on the part of both provider and patient, leading to potentially dire consequences. A review of the literature highlights critical predictors of adherence including trust, communication and empathy, which are not easily measured by current administrative databases. Multifactorial solutions to improve medication adherence include efforts to improve patients' understanding of medication benefits, access and trust in their provider and health system. Improving providers' recognition and understanding of patients' beliefs, fears and values, as well as their own biases is also necessary to achieve increased medication adherence and population health.

Initial Medication Adherence in the Elderly Using PACE Claim Reversals: A Pilot Study

BACKGROUND

The Medicare Modernization Act, with its requirements for Medicare Part D to comply with electronic prescribing (e-prescribing), bolstered the adoption of e-prescribing, which increased to 73% in 2013. Therefore, understanding whether electronic prescriptions are less likely to be picked up is important as e-prescribing continues to be emphasized.

OBJECTIVE

To assess whether prescription origin is among the factors associated with initial medication adherence, using claim reversals as a proxy measure.

METHODS

A cross-sectional study was completed using a sample of reversed claims from the Pharmaceutical Assistance Contract for the Elderly (PACE) program for September 2014. The total number of reversed claims for new prescriptions (15,966) was categorized by prescription origin (written, telephone, electronic, fax, and pharmacy). Using a chi-square analysis, the reversed claims were compared among prescription origin to determine if there is a difference in the proportion of electronic prescriptions reversed compared with those from other origins.

RESULTS

When compared with all other prescription origins, electronic prescriptions (E) were more likely to be reversed at day 0 (E = 50%, any other [AO] = 49%, P < 0.05) and after day 0 (E = 58%, AO = 42%, P < 0.05).

CONCLUSIONS

Electronic prescriptions are associated with a higher rate of claim reversals and may reflect poorer initial adherence. Electronic prescriptions may more likely be forgotten or not picked up because they were not presented to the pharmacy by the patient. The growing adoption of electronic prescriptions merits particular attention, since it may be a factor in initial medication adherence in the elderly.

DISCLOSURES

This study was not supported by any funding. Peterson reports advisory board and consultancy fees from IMS Health and Pfizer and employment by Genentech. Klaiman is currently employed by AccessMatters. No other financial or other conflicts of interests were reported. Study concept and design were primarily contributed by Forestal, along with Klaiman and Peterson. Heller took the lead in data collection, along with Forestal, and data interpretation was performed by Forestal, Klaiman, and Peterson. Forestal, Klaiman, and Heller were responsible for manuscript preparation.

Initial Medication Adherence in the Elderly Using PACE Claim Reversals: A Pilot Study

BACKGROUND

The Medicare Modernization Act, with its requirements for Medicare Part D to comply with electronic prescribing (e-prescribing), bolstered the adoption of e-prescribing, which increased to 73% in 2013. Therefore, understanding whether electronic prescriptions are less likely to be picked up is important as e-prescribing continues to be emphasized.

OBJECTIVE

To assess whether prescription origin is among the factors associated with initial medication adherence, using claim reversals as a proxy measure.

METHODS

A cross-sectional study was completed using a sample of reversed claims from the Pharmaceutical Assistance Contract for the Elderly (PACE) program for September 2014. The total number of reversed claims for new prescriptions (15,966) was categorized by prescription origin (written, telephone, electronic, fax, and pharmacy). Using a chi-square analysis, the reversed claims were compared among prescription origin to determine if there is a difference in the proportion of electronic prescriptions reversed compared with those from other origins.

RESULTS

When compared with all other prescription origins, electronic prescriptions (E) were more likely to be reversed at day 0 (E = 50%, any other [AO] = 49%, P < 0.05) and after day 0 (E = 58%, AO = 42%, P < 0.05).

CONCLUSIONS

Electronic prescriptions are associated with a higher rate of claim reversals and may reflect poorer initial adherence. Electronic prescriptions may more likely be forgotten or not picked up because they were not presented to the pharmacy by the patient. The growing adoption of electronic prescriptions merits particular attention, since it may be a factor in initial medication adherence in the elderly.

DISCLOSURES

This study was not supported by any funding. Peterson reports advisory board and consultancy fees from IMS Health and Pfizer and employment by Genentech. Klaiman is currently employed by AccessMatters. No other financial or other conflicts of interests were reported. Study concept and design were primarily contributed by Forestal, along with Klaiman and Peterson. Heller took the lead in data collection, along with Forestal, and data interpretation was performed by Forestal, Klaiman, and Peterson. Forestal, Klaiman, and Heller were responsible for manuscript preparation.

Persistence with medication and overactive bladder: an ongoing challenge

INTRODUCTION

For optimum results from pharmacological management of overactive bladder, adherence to prescribed medication is required. Overactive bladder treatment has been compromised by low adherence and persistence to medications, losing many people who might benefit from treatment and exposing them to unnecessary consequences of their disease.

AREAS COVERED

This narrative review examines what is known about adherence and persistence with treatment and, drawing evidence from other disease areas suggests factors which might be modifiable to improve the situation. A structured search of PubMed using the terms persistence, adherence, overactive bladder, urgency incontinence, and chronic conditions, was performed and added to as themes from exiting data emerged. Expert commentary: Adherence has traditionally been poor in this disease area with limited understanding of the modifiable factors underlying the observation. Increased understanding of the nature of the underlying disease should allow adoption of strategies tested in other disease areas.

Defining and Measuring Primary Medication Nonadherence: Development of a Quality Measure

Poor medication adherence has been increasingly recognized as a major public health issue and a priority for health care reform. Primary medication nonadherence (PMN) is a subset of this broader subject and occurs when a new medication is prescribed for a patient, but the patient does not obtain the medication, or an appropriate alternative, within an acceptable period of time after it was prescribed. It is increasingly evident that the public health problem of PMN is widespread. However, the lack of standardized definitions and measures inhibits the ability to establish the true incidence of this problem or to track changes in PMN rates over time. Given the limitations of current measures, the Pharmacy Quality Alliance (PQA) convened an expert working group to set parameters for a new industry measure. That new measure, which links electronic prescribing and pharmacy dispensing databases and was developed and approved by the PQA, is described here. PMN literature from 1990 to June 2015 is also reviewed, and existing PMN measures are summarized.

DISCLOSURES

No funding was received for this article, and the authors declare no conflicts of interest. The views expressed in this article are those of the authors alone and do not necessarily reflect those of their respective employers. Adams has received grant support from Pfizer for adherence research. Adams and Stolpe were equally involved in all aspects of study design, data collection and interpretation, and manuscript preparation.

A Pilot Study Using a Web Survey to Identify Characteristics That Influence Hypogonadal Men to Initiate Testosterone Replacement Therapy

Men with hypogonadism (HG) who choose testosterone replacement therapy (TRT) may have distinct characteristics that provide insight as to why they may/may not initiate therapy. The aim of the current study was to identify trends in patient characteristics and attitudes in men diagnosed with HG who initiated TRT (TRT+) compared with men who were diagnosed with HG but did not initiate TRT (TRT-). The market research-based online survey conducted between 2012 and 2013 included patients from a Federated Sample, a commercially available panel of patients with diverse medical conditions. The current analysis was composed of two groups: TRT+ ( n = 155) and TRT- ( n = 157). Patient demographics, clinical characteristics, and attitudes toward HG and TRT were examined as potential predictors of primary adherence in men with HG; cohorts were compared by using Fisher's exact test. Significant associations among sexual orientation, relationship status, educational level, presence of comorbid erectile dysfunction, area of residence, and TRT initiation were present ( p ≤ .05). College-educated, heterosexual, married men with comorbid erectile dysfunction living in suburban and urban areas were more likely to initiate treatment. The most bothersome symptoms reported were lack of energy (90% vs. 81%, p = .075), decreased strength and endurance (86% vs. 76%, p = .077), and deterioration in work performance (52% vs. 31%, p = .004); lack of energy prompted men to seek help. Patients (48%) in the TRT+ group were more knowledgeable regarding HG as compared with TRT- respondents (14%, p < .001), and most men obtained their information from a health care professional (89% vs. 82%, p = .074). The current analysis identified distinct demographic and clinical characteristics and attitudes among TRT users compared with men who were diagnosed with HG yet remained untreated.

Understanding adherence to medications in type 2 diabetes care and clinical trials to overcome barriers: a narrative review

AIM

To identify factors affecting adherence to medications in type 2 diabetes (T2D) care and clinical trials.

BACKGROUND

Adherence to medication is associated with better patient outcomes, lower healthcare costs, and improved quality and robustness of trial data. In T2D, non-adherence to regimens may compromise glycemic, blood pressure and lipid control, which can, in turn, increase morbidity and mortality rates.

DESIGN

A literature search was performed to identify studies reporting adherence to medications and highlighting specific adherence challenges/approaches in T2D. The search was limited to clinical trials, comparative studies or meta-analyses, reported in English with a freely available abstract.

DATA SOURCE

MEDLINE (31 December 2008 to 31 December 2013).

REVIEW METHODS

Studies not reporting adherence to medications or highlighting adherence challenges/approaches in T2D, presenting only self-reported adherence or including fewer than 100 patients were excluded. Eligible reports are discussed narratively.

RESULTS

Factors identified as having a detrimental impact on adherence were smoking, depression and polypharmacy. Conversely, increased convenience (e.g. pen compared with vial and syringe; medication supplied by mail order vs. retail pharmacy) was associated with better patient adherence, as were interventions that increased patient motivation (e.g. individualized, nurse-led consultation) and education.

CONCLUSIONS

Medication adherence is influenced by complex and multifactorial issues, which can include smoking, depression, polypharmacy, convenience of obtaining and administering the medication, patient motivation and education. We recommend simplifying treatment regimens, where possible, improving provider-patient communication, and providing support and education to increase medication adherence, with a view to improving patient outcomes and clinical trial data quality.

Medication Adherence With Diabetes Medication: A Systematic Review of the Literature

PURPOSE

The primary purpose of this systematic review is to synthesize the evidence regarding risk factors associated with nonadherence to prescribed glucose-lowering agents, the impact of nonadherence on glycemic control and the economics of diabetes care, and the interventions designed to improve adherence.

METHODS

Medline, EMBASE, the Cochrane Collaborative, BIOSIS, and the Health and Psychosocial Instruments databases were searched for studies of medication adherence for the period from May 2007 to December 2014. Inclusion criteria were study design and primary outcome measuring or characterizing adherence. Published evidence was graded according to the American Association of Clinical Endocrinologists protocol for standardized production of clinical practice guidelines.

RESULTS

One hundred ninety-six published articles were reviewed; 98 met inclusion criteria. Factors including age, race, health beliefs, medication cost, co-pays, Medicare Part D coverage gap, insulin use, health literacy, primary nonadherence, and early nonpersistence significantly affect adherence. Higher adherence was associated with improved glycemic control, fewer emergency department visits, decreased hospitalizations, and lower medical costs. Adherence was lower when medications were not tolerated or were taken more than twice daily, with concomitant depression, and with skepticism about the importance of medication. Intervention trials show the use of phone interventions, integrative health coaching, case managers, pharmacists, education, and point-of-care testing improve adherence.

CONCLUSION

Medication adherence remains an important consideration in diabetes care. Health professionals working with individuals with diabetes (eg, diabetes educators) are in a key position to assess risks for nonadherence, to develop strategies to facilitate medication taking, and to provide ongoing support and assessment of adherence at each visit.

Improving Patient's Primary Medication Adherence: The Value of Pharmaceutical Counseling

Quality of transitions of care is one of the first concerns in patient safety. Redesigning the discharge process to incorporate clinical pharmacy activities could reduce the incidence of postdischarge adverse events by improving medication adherence. The present study investigated the value of pharmacist counseling sessions on primary medication adherence after hospital discharge.This study was conducted in a 1844-bed hospital in France. It was divided in an observational period and an interventional period of 3 months each. In both periods, ward-based clinical pharmacists performed medication reconciliation and inpatient follow-up. In interventional period, initial counseling and discharge counseling sessions were added to pharmaceutical care. The primary medication adherence was assessed by calling community pharmacists 7 days after patient discharge.We compared the measure of adherence between the patients from the observational period (n = 201) and the interventional period (n = 193). The rate of patients who were adherent increased from 51.0% to 66.7% between both periods (P < 0.01). When discharge counseling was performed (n = 78), this rate rose to 79.7% (P < 0.001). The multivariate regression performed on data from both periods showed that age of at least 78 years old, and 3 or less new medications on discharge order were predictive factors of adherence. New medications ordered at discharge represented 42.0% (n = 1018/2426) of all medications on discharge order. The rate of unfilled new medications decreased from 50.2% in the observational period to 32.5% in the interventional period (P < 10). However, patients included in the observational period were not significantly more often readmitted or visited the emergency department than the patients who experienced discharge counseling during the interventional period (45.3% vs. 46.2%; P = 0.89).This study highlights that discharge counseling sessions are essential to improve outpatients' primary medication adherence. We identified predictive factors of primary nonadherence in order to target the most eligible patients for discharge counseling sessions. Moreover, implementation of discharge counseling could be facilitated by using Health Information Technology to adapt human resources and select patients at risk of nonadherence.

Initial Medication Adherence-Review and Recommendations for Good Practices in Outcomes Research: An ISPOR Medication Adherence and Persistence Special Interest Group Report

BACKGROUND

Positive associations between medication adherence and beneficial outcomes primarily come from studying filling/consumption behaviors after therapy initiation. Few studies have focused on what happens before initiation, the point from prescribing to dispensing of an initial prescription.

OBJECTIVE

Our objective was to provide guidance and encourage high-quality research on the relationship between beneficial outcomes and initial medication adherence (IMA), the rate initially prescribed medication is dispensed.

METHODS

Using generic adherence terms, an international research panel identified IMA publications from 1966 to 2014. Their data sources were classified as to whether the primary source reflected the perspective of a prescriber, patient, or pharmacist or a combined perspective. Terminology and methodological differences were documented among core (essential elements of presented and unpresented prescribing events and claimed and unclaimed dispensing events regardless of setting), supplemental (refined for accuracy), and contextual (setting-specific) design parameters. Recommendations were made to encourage and guide future research.

RESULTS

The 45 IMA studies identified used multiple terms for IMA and operationalized measurements differently. Primary data sources reflecting a prescriber's and pharmacist's perspective potentially misclassified core parameters more often with shorter/nonexistent pre- and postperiods (1-14 days) than did a combined perspective. Only a few studies addressed supplemental issues, and minimal contextual information was provided.

CONCLUSIONS

General recommendations are to use IMA as the standard nomenclature, rigorously identify all data sources, and delineate all design parameters. Specific methodological recommendations include providing convincing evidence that initial prescribing and dispensing events are identified, supplemental parameters incorporating perspective and substitution biases are addressed, and contextual parameters are included.

Do patients initiate therapy? Primary non-adherence to statins and antidepressants in Iceland

BACKGROUND

Primary non-adherence occurs when a drug has been prescribed but the patient fails to have it dispensed at the pharmacy.

AIMS

To assess primary non-adherence to statins and antidepressants in Iceland, the association of demographic factors with primary non-adherence, and the time from when a prescription is issued until it is dispensed.

METHODS

Data on patients receiving a new prescription for a statin or an antidepressant from the Primary Health Care database were linked with dispensing histories from The Icelandic Prescription Database. The proportion of patients who did not have their prescription dispensed within a year from issuing (primary non-adherent) was assessed, as well as the time from issue until dispensing. Associations between demographic factors and primary non-adherence were estimated using logistic regression.

RESULTS

The overall primary non-adherence was 6.3% and 8.0% for statins and antidepressants, respectively. The majority of patients had their prescription dispensed within 7 days (85% for statins, 87% for antidepressants). Being disabled and receiving a prescription for an expensive drug was associated with higher rates of primary non-adherence.

CONCLUSION

The rate of primary non-adherence to statins and antidepressants in Iceland is low. Vulnerable groups such as the disabled should be given special attention when new drugs are prescribed.

Primary non-adherence in Portugal: findings and implications

BACKGROUND

Portugal is currently facing a serious economic and financial crisis, which is dictating some important changes in the health care sector. Some of these measures may potentially influence patients' access to medication and consequently adherence, which will ultimately impact on health status, especially in chronic patients.

AIMS

This study aimed at providing a snapshot of adherence in patients with chronic conditions in Portugal between March and April 2012.

SETTING

Community pharmacy in Portugal.

METHOD

A cross-sectional pilot study was undertaken, where patients were recruited via community pharmacies to a questionnaire study evaluating the number of prescribed and purchased drugs and, when these figures were inconsistent, the reasons for this.

MAIN OUTCOME MEASURES

Primary and secondary adherence measures. Failing to purchase prescription items was categorized as primary nonadherence. Secondary nonadherence was attributed to purchasing prescription items, but not taking medicines as prescribed.

RESULTS

Data were collected from 375 patients. Primary nonadherence was identified in 22.8 % of patients. Regardless of the underlying condition, the most commonly reported reason for primary non-adherence was having spare medicines at home ("leftovers"), followed by financial problems. The latter appeared to be related to the class of medicines prescribed. Primary non-adherence was associated with low income (<475 <euro>/month; p = 0.026). Secondary non-adherence, assessed by the 7-MMAS was detected in over 50 % of all patients, where unintentional nonadherence was higher than intentional nonadherence across all disease conditions.

CONCLUSION

This study revealed that more than one fifth of chronic medication users report primary nonadherence (22.8 %) and more than 50 % report secondary nonadherence. Data indicates that the existence of spare medicines and financial constraints occurred were the two most frequent reasons cited for nonadherence (47, 6-64, 8 and 19-45.5 %, depending on the major underlying condition, respectively).

Pharmacy-based interventions to reduce primary medication nonadherence to cardiovascular medications

BACKGROUND

Primary medication nonadherence (PMN) occurs when patients do not fill new prescriptions. Interventions to reduce PMN have not been well described.

OBJECTIVES

To determine whether 2 pharmacy-based interventions could decrease PMN.

DESIGN

Two sequential interventions with a control group were evaluated after completion. The automated intervention began in 2007 and consisted of phone calls to patients on the third and seventh days after a prescription was processed but remained unpurchased. The live intervention began in 2009 and used calls from a pharmacist or technician to patients who still had not picked up their prescriptions after 8 days.

SUBJECTS

Patients with newly prescribed cardiovascular medications received at CVS community pharmacies. Patients with randomly selected birthdays served as the control population.

MEASURES

Patient abandonment of new prescription, defined as not picking up medications within 30 days of initial processing at the pharmacy.

RESULTS

The automated intervention included 852,612 patients and 1.2 million prescriptions, with a control group of 9282 patients and 13,178 prescriptions. The live intervention included 121,155 patients and 139,502 prescriptions with a control group of 2976 patients and 3407 prescriptions. The groups were balanced by age, sex, and patterns of prior prescription use. For the automated intervention, 4.2% of prescriptions were abandoned in the intervention group and 4.5% in the control group (P>0.1), with no significant differences for any individual classes of medications. The live intervention was used in a group that had not purchased prescriptions after 8 days and thus had much higher PMN. In this setting 36.9% of prescriptions were abandoned in the intervention group and 41.7% in the control group, a difference of 4.8% (P<0.0001). The difference in abandoned prescriptions for antihypertensives was 6.9% (P<0.0001) but for antihyperlipidemics was only 1.4% (P>0.1).

CONCLUSIONS

Automated reminder calls had no effect on PMN. Live calls from pharmacists decreased antihypertensive PMN significantly, although many patients still abandoned their prescriptions.

A randomized telephone intervention trial to reduce primary medication nonadherence

BACKGROUND

Primary medication nonadherence (PMN), defined as patients not picking up an initial prescription, can limit the effectiveness of therapy for chronic conditions. Effective interventions to reduce PMN have not been widely studied or implemented.

OBJECTIVE

To evaluate the ability of an additional nurse-directed telephone intervention to reduce PMN in a cohort of patients with persistent nonadherence after repeated pharmacy-based outreach.

METHODS

Patients in the Geisinger Health System receiving new (i.e., initially prescribed) prescriptions sent to CVS pharmacies for medications treating asthma, hypertension, diabetes, or hyperlipidemia were identified. As part of existing programs, all patients received 2 automated and 1 live call from CVS pharmacies encouraging them to pick up their prescriptions; those who had canceled their prescriptions or had not picked them up after the 3 pharmacy interventions were eligible for this study. Patients were then randomized, and the intervention group received telephone outreach from a nursing call center to assess reasons for PMN and encourage pickup of prescriptions, with up to 3 attempts to reach each patient. Medication pickup rates were compared across the intervention and control groups.

RESULTS

Initial PMN rates in the overall population were 6%, lower than previously observed in other studies. A total of 290 patients had not picked up their prescriptions after 3 calls from the pharmacy and were enrolled in the study: 142 in the intervention group and 148 controls. The intervention did not change the rate at which patients picked up their prescriptions: 25% of intervention patients did so compared with 24% of control patients. Multivariate models adjusting for patient characteristics and medication classes did not change the results.

CONCLUSIONS

In a population of patients who had not picked up new prescriptions after 3 calls from the pharmacy, additional nurse-directed outreach did not improve primary medication adherence. Re-engagement with the prescribing clinician may be needed to improve adherence in this patient population. The low rate of PMN in the overall population differed from prior studies in this setting and others and should be assessed in future research.

Why do we observe a limited impact of primary care access measures on clinical quality indicators?

The study assessed the effects of enhanced primary care access and continuity on clinical quality in a large, multipayer, multispecialty ambulatory care organization with fee-for-service provider incentives. The difference-in-differences estimates indicate that access to own primary care physician is a statistically significant predictor of improved clinical quality, although the effect size is small such that clinical significance may be negligible. Reduced time for own primary care physician appointment and increased enrollment in electronic personal health record are positive predictors of chronic disease management processes and preventive screening but are inconsistently associated with clinical outcomes. Challenges in identifying relationships between access and quality outcomes in a real-world setting are also discussed.

Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases

OBJECTIVE

To propose a unifying set of definitions for prescription adherence research utilizing electronic health record prescribing databases, prescription dispensing databases, and pharmacy claims databases and to provide a conceptual framework to operationalize these definitions consistently across studies.

METHODS

We reviewed recent literature to identify definitions in electronic database studies of prescription-filling patterns for chronic oral medications. We then develop a conceptual model and propose standardized terminology and definitions to describe prescription-filling behavior from electronic databases.

RESULTS

The conceptual model we propose defines 2 separate constructs: medication adherence and persistence. We define primary and secondary adherence as distinct subtypes of adherence. Metrics for estimating secondary adherence are discussed and critiqued, including a newer metric (New Prescription Medication Gap measure) that enables estimation of both primary and secondary adherence.

DISCUSSION

Terminology currently used in prescription adherence research employing electronic databases lacks consistency. We propose a clear, consistent, broadly applicable conceptual model and terminology for such studies. The model and definitions facilitate research utilizing electronic medication prescribing, dispensing, and/or claims databases and encompasses the entire continuum of prescription-filling behavior.

CONCLUSION

Employing conceptually clear and consistent terminology to define medication adherence and persistence will facilitate future comparative effectiveness research and meta-analytic studies that utilize electronic prescription and dispensing records.

Measuring Diabetes Care Performance Using Electronic Health Record Data: The Impact of Diabetes Definitions on Performance Measure Outcomes

The objective was to examine the use of electronic health record (EHR) data for diabetes performance measurement. Data were extracted from the EHR of a health system to identify patients with diabetes using 8 different EHR data-based methods of identification. These EHR-based methods were compared to the gold standard of a manual medical record review. The study team then assessed whether the method of identifying patients with diabetes could affect performance measurement scores. The sensitivity of the 8 EHR-based methods of identifying patients with diabetes ranged from moderate to high. The use of certain data elements in the EHR to identify patients with diabetes selectively identified those who had better performance measures. Diabetes performance measures are influenced by the data elements used to identify patients. As EHR data are used increasingly to measure performance, continuing to improve our understanding of how EHR data are collected and used will be critical.

Feasibility and effectiveness in clinical practice of a multifactorial intervention for the reduction of cardiovascular risk in patients with type 2 diabetes: the 2-year interim analysis of the MIND.IT study: a cluster randomized trial

OBJECTIVE

To evaluate the feasibility and effectiveness of an intensive, multifactorial cardiovascular risk reduction intervention in a clinic-based setting.

RESEARCH DESIGN AND METHODS

The study was a pragmatic, cluster randomized trial, with the diabetes clinic as the unit of randomization. Clinics were randomly assigned to either continue their usual care (n = 5) or to apply an intensive intervention aimed at the optimal control of cardiovascular disease (CVD) risk factors and hyperglycemia (n = 4). To account for clustering, mixed model regression techniques were used to compare differences in CVD risk factors and HbA1c. Analyses were performed both by intent to treat and as treated per protocol.

RESULTS

Nine clinics completed the study; 1,461 patients with type 2 diabetes and no previous cardiovascular events were enrolled. After 2 years, participants in the interventional group had significantly lower BMI, HbA1c, LDL cholesterol, and triglyceride levels and significantly higher HDL cholesterol level than did the usual care group. The proportion of patients reaching the treatment goals was systematically higher in the interventional clinics (35% vs. 24% for LDL cholesterol, P = 0.1299; 93% vs. 82% for HDL cholesterol, P = 0.0005; 80% vs. 64% for triglycerides, P = 0.0002; 39% vs. 22% for HbA1c, P = 0.0259; 13% vs. 5% for blood pressure, P = 0.1638). The analysis as treated per protocol confirmed these findings, showing larger and always significant differences between the study arms for all targets.

CONCLUSIONS

A multifactorial intensive intervention in type 2 diabetes is feasible and effective in clinical practice and it is associated with significant and durable improvement in HbA1c and CVD risk profile.

Primary non-adherence to bisphosphonates in an integrated healthcare setting

We estimated primary non-adherence to oral bisphosphonate medication and examined the factors associated with primary non-adherence. Nearly 30% of women did not pick up their new bisphosphonate within 60 days. Identifying barriers and developing interventions that address patients' needs and concerns at the time a new medication is prescribed are warranted.

INTRODUCTION

To estimate primary non-adherence to oral bisphosphonate medications using electronic medical record data in a large, integrated healthcare delivery system and to describe patient and prescribing provider factors associated with primary non-adherence.

METHODS

Women aged 55 years and older enrolled in Kaiser Permanente Southern California (KPSC) with a new prescription for oral bisphosphonates between December 1, 2009 and March 31, 2011 were identified. Primary non-adherence was defined as failure to pick up the new prescription within 60 days of the order date. Multivariable logistic regression models were used to investigate patient factors (demographics, healthcare utilization, and health conditions) and prescribing provider characteristics (demographics, years in practice, and specialty) associated with primary non-adherence.

RESULTS

We identified 8,454 eligible women with a new bisphosphonate order. Among these women, 2,497 (29.5%) did not pick up their bisphosphonate prescription within 60 days of the order date. In multivariable analyses, older age and emergency department utilization were associated with increased odds of primary non-adherence while prescription medication use and hospitalizations were associated with lower odds of primary non-adherence. Prescribing providers practicing 10 or more years had lower odds of primary non-adherent patients compared with providers practicing less than 10 years. Internal medicine and rheumatology providers had lower odds of primary non-adherent patients than primary care providers.

CONCLUSION

This study found that nearly one in three women failed to pick up their new bisphosphonate prescription within 60 days. Identifying barriers and developing interventions aimed at reducing the number of primary non-adherent patients to bisphosphonate prescriptions are warranted.

A systematic literature review of psychosocial and behavioral factors associated with initial medication adherence: a report of the ISPOR medication adherence & persistence special interest group

OBJECTIVES

Numerous factors influencing medication adherence in chronically ill patients are well documented, but the paucity of studies concerning initial treatment course experiences represents a significant knowledge gap. As interventions targeting this crucial first phase can affect long-term adherence and outcomes, an international panel conducted a systematic literature review targeting behavioral or psychosocial risk factors.

METHODS

Eligible published articles presenting primary data from 1966 to 2011 were abstracted by independent reviewers through a validated quality instrument, documenting terminology, methodological approaches, and factors associated with initial adherence problems.

RESULTS

We identified 865 potentially relevant publications; on full review, 24 met eligibility criteria. The mean Nichol quality score was 47.2 (range 19-74), with excellent reviewer concordance (0.966, P < 0.01). The most prevalent pharmacotherapy terminology was initial, primary, or first-fill adherence. Articles described the following factors commonly associated with initial nonadherence: patient characteristics (n = 16), medication class (n = 12), physical comorbidities (n = 12), pharmacy co-payments or medication costs (n = 12), health beliefs and provider communication (n = 5), and other issues. Few studies reported health system factors, such as pharmacy information, prescribing provider licensure, or nonpatient dynamics.

CONCLUSIONS

Several methodological challenges synthesizing the findings were observed. Despite implications for continued medication adherence and clinical outcomes, relatively few articles directly examined issues associated with initial adherence. Notwithstanding this lack of information, many observed factors associated with nonadherence are amenable to potential interventions, establishing a solid foundation for appropriate ongoing behaviors. Besides clarifying definitions and methodology, future research should continue investigating initial prescriptions, treatment barriers, and organizational efforts to promote better long-term adherence.

Completeness of prescription information in US commercial claims databases

PURPOSE

Pharmacy commercial claims databases are widely used for pharmacoepidemiologic research. However, concerns have been raised that these databases may not fully capture claims for generic medications as a result of patients filling outside the context of their insurance. This has implications for many research activities and quality improvement programs. We sought to estimate the percentage of missing prescriptions in US commercial claims data using a novel design.

METHODS

Using a large US commercial insurance database, we examined the completeness of warfarin prescription claims among patients with atrial fibrillation receiving regular medical follow-up and testing to manage warfarin dosing. We examined 14 different 6-month cross sections. Each cross section was treated independently to identify patients with at least two outpatient diagnoses of atrial fibrillation, two international normalized ratio tests, and one pharmacy claim. Trends in the percentage of patients with prescription claims for generic and branded warfarin were compared by year and 6-month periods using chi-square tests and generalized linear models adjusting for patient characteristics.

RESULTS

Out of 111 170 patients, the percentage of patients with any warfarin drug decreased slightly from 91.7% (95% CI: 91.0, 92.4) in early 2003 to 87.1% (95% CI: 86.7-87.6) in late 2009 (χ(2)  = 93.8, p < 0.0001). Over the same interval, the proportion of patients with generic warfarin exposure appearing increased significantly, whereas the proportion of patients with branded warfarin exposure decreased significantly.

CONCLUSIONS

Our study supports the possibility that some prescriptions may not be captured in US commercial insurance databases.

Adherence with medications used to treat osteoporosis: behavioral insights

Non-persistence (never starting or stopping medication prematurely) and non-compliance (taking medication inappropriately) with fracture prevention medication among those at high risk of fracture remain significant barriers to optimal reduction of osteoporotic fractures. Current research suggest that for patients to persist and comply with prescriptions for fracture prevention medication, they need to believe that they are at significant risk of fracture, that the prescribed medication can safely reduce their risk of fracture without exposing them to long-term harm, that equally effective non-medicinal therapies are not available, and that they can successfully execute medication use in the context of their daily task demands. Further research is needed to understand; a) the mental models of osteoporosis, fractures, and medications used to treat osteoporosis that patients employ when making decisions as to whether or not to take fracture prevention medication; and b) how patients arbitrage information from various sources (health care providers, family, friends, and other sources) to formulate their beliefs about osteoporosis and medications used to treat it.

Characteristics of patients with primary non-adherence to medications for hypertension, diabetes, and lipid disorders

BACKGROUND

Information comparing characteristics of patients who do and do not pick up their prescriptions is sparse, in part because adherence measured using pharmacy claims databases does not include information on patients who never pick up their first prescription, that is, patients with primary non-adherence. Electronic health record medication order entry enhances the potential to identify patients with primary non-adherence, and in organizations with medication order entry and pharmacy information systems, orders can be linked to dispensings to identify primarily non-adherent patients.

OBJECTIVE

This study aims to use database information from an integrated system to compare patient, prescriber, and payment characteristics of patients with primary non-adherence and patients with ongoing dispensings of newly initiated medications for hypertension, diabetes, and/or hyperlipidemia.

DESIGN

This is a retrospective observational cohort study. PARTICIPANTS (OR PATIENTS OR SUBJECTS): Participants of this study include patients with a newly initiated order for an antihypertensive, antidiabetic, and/or antihyperlipidemic within an 18-month period.

MAIN MEASURES

Proportion of patients with primary non-adherence overall and by therapeutic class subgroup. Multivariable logistic regression modeling was used to investigate characteristics associated with primary non-adherence relative to ongoing dispensings.

KEY RESULTS

The proportion of primarily non-adherent patients varied by therapeutic class, including 7% of patients ordered an antihypertensive, 11% ordered an antidiabetic, 13% ordered an antihyperlipidemic, and 5% ordered medications from more than one of these therapeutic classes within the study period. Characteristics of patients with primary non-adherence varied across therapeutic classes, but these characteristics had poor ability to explain or predict primary non-adherence (models c-statistics = 0.61-0.63).

CONCLUSIONS

Primary non-adherence varies by therapeutic class. Healthcare delivery systems should pursue linking medication orders with dispensings to identify primarily non-adherent patients. We encourage conduct of research to determine interventions successful at decreasing primary non-adherence, as characteristics available from databases provide little assistance in predicting primary non-adherence.

Trouble getting started: predictors of primary medication nonadherence

BACKGROUND

Patient nonadherence to prescribed medication is common and limits the effectiveness of treatment for many conditions. Most adherence studies evaluate behavior only among patients who have filled a first prescription. The advent of electronic prescribing (e-prescribing) systems provides the opportunity to track initial prescriptions and identify nonadherence that may have previously been undetected.

METHODS

We analyzed e-prescribing data and filled claims for all patients with CVS Caremark (Woonsocket, RI) drug coverage who received e-prescriptions from the iScribe e-prescribing system in calendar 2008. We matched e-prescriptions with filled claims by using data on the drug name, date of e-prescription, and date of filled claims, allowing up to 180 days for patients to fill e-prescriptions. We evaluated the rate of primary nonadherence to newly prescribed medications across multiple characteristics of patients, prescribers, and prescriptions and developed multivariable models to identify predictors of nonadherence.

RESULTS

We identified 423,616 e-prescriptions for new medications, with 3634 prescribers and 280,081 patients. The primary nonadherence rate was 24.0%. Several factors were associated with nonadherence to e-prescriptions, including nonformulary status of medications (odds ratio [OR] 1.31 compared with preferred medications; 95% confidence interval [CI], 1.26-1.36; P<.001) and residence in a low-income ZIP code (OR 1.23 compared with high-income ZIP code; 95% CI, 1.17-1.30; P<.001) Nonadherence occurred less often when e-prescriptions were transmitted directly to the pharmacy rather than printed to give to patients (OR 0.54; 95% CI, 0.52-0.57; P<.001).

CONCLUSION

24% of e-prescriptions for new medications were not filled. Our results suggest that interventions to address economic barriers and increase electronic integration in the healthcare system may be promising approaches to improve medication adherence.

Importance of including early nonadherence in estimations of medication adherence

BACKGROUND

Many medication adherence metrics are based on refill rates determined from pharmacy claims databases. However, these methods do not incorporate assessment of nonadherence to new prescriptions when those prescriptions are never dispensed (primary nonadherence), or dispensed only once (early nonpersistence). As a result, published studies may overestimate adherence, but the extent of overestimation posed by not considering patients with primary nonadherence and early nonpersistence has not been assessed.

OBJECTIVE

To estimate the magnitude of misestimation in adherence estimates that results from not including patients with primary nonadherence and early nonpersistence.

METHODS

We conducted a retrospective cohort study of 15,417 patients enrolled in an integrated health care delivery system who were newly prescribed an antihypertensive, antidiabetic, or antihyperlipidemic medication. We linked prescription orders to medication dispensings. Based on dispensing and refill rates, we stratified patients into primary nonadherent, early nonpersistent, and ongoing dispensings groups. Adherence was estimated using the proportion of days covered (PDC). Standardized observation periods were applied across all groups.

RESULTS

A total of 1142 (7.4%) patients were primarily nonadherent, 3356 (21.8%) demonstrated early nonpersistence, and 10,919 (70.8%) patients received ongoing dispensings, with a mean PDC of 84%. Not including primarily nonadherent and early nonpersistent patients in calculations resulted in adherence estimates overestimated by 9-18%.

CONCLUSIONS

When medication adherence is estimated from pharmacy claims databases, adherence estimates are substantially inflated because primarily nonadherent and early nonpersistent patients are not included in the estimations. An implication of this incorrect estimation is potential distortion of the true relationship between medication adherence and clinical outcomes.

Reconceptualizing medication adherence: six phases of dynamic adherence

Nonadherence is the Achilles' heel of effective psychiatric treatment. It affects the resolution of mental health symptoms and interferes with the assessment of treatment response. The meaning of the term adherence has evolved over time and is now associated with a variety of definitions and measurement methods. The result has been a poorly operationalized and nonstandardized term that is often interpreted differently by providers and patients. Drawing extensively from the literature, this article aims to (1) describe changes in the concept of adherence, drawing from the mental health treatment literature, (2) present a more comprehensive definition of adherence that recognizes the role of patient-provider transactions, (3) introduce dynamic adherence, a six-phase model, which incorporates the role of transactional processes and other factors that influence patients' adherence decisions, and (4) provide recommendations for providers to improve adherence as well as their relationships with patients.