Importance of including early nonadherence in estimations of medication adherence

Initial non-adherence to lipid-lowering medication: a systematic literature review

BACKGROUND

The impact on cardiovascular health is lost when a patient does not obtain a newly prescribed lipid-lowering medication, a situation termed "initial medication nonadherence" (IMN). This research summarizes the published evidence on the prevalence, associated factors, consequences, and solutions for IMN to prescribed lipid-lowering medication in the United States.

METHODS

A systematic literature search using PubMed and Google Scholar, along with screening citations of systematic reviews, identified articles published from 2010 to 2021. Studies reporting results of IMN to lipid-lowering medications were included. Studies that evaluated non-adult or non-US populations, used weaker study designs (e.g., case series), or were not written in English were excluded.

RESULTS

There were 19 articles/18 studies that met inclusion and exclusion criteria. Estimates of the prevalence of IMN to newly prescribed lipid-lowering medications ranged from 10 to 18.2% of patients and 1.4-43.8% of prescriptions (n = 9 studies). Three studies reported prescriber and patient characteristics associated with IMN. Hispanic ethnicity, Black race, lower Charlson Comorbidity Index score and no ED visits or hospitalization were associated with IMN. Lipid lowering prescriptions from primary care providers were also associated with IMN. Four studies described patient-reported reasons for IMN, including preference for lifestyle modifications, lack of perceived need, and side effect concerns. Four intervention studies reported mixed results with automated calls, live calls, or letters. One study reported worse clinical outcomes in patients with IMN: higher levels of low-density lipoprotein and greater risk of emergency department visits.

CONCLUSIONS

Up to one-fifth of patients fail to obtain a newly prescribed lipid-lowering medication but there is limited information about the clinical consequences. Future research should assess outcomes and determine cost-effective approaches to address IMN to lipid-lowering therapy.

Linkage between electronic prescribing data and pharmacy claims records to determine primary adherence: the case of antihypertensive therapy in the Lisbon and Tagus Valley Region, Portugal

BACKGROUND

Hypertension (HT) is highly prevalent and a major risk factor for cardiovascular disease. Over 42% of Portuguese adults have HT. Even though the benefits of antihypertensive (AHT) drugs have been demonstrated, HT control remains inadequate. One major reason is that patients often fail to take their medications as prescribed. This paper aims to determine primary adherence to AHT therapy in newly diagnosed and treated hypertensive patients in Primary Health Care (PHC) units of Lisbon and Tagus Valley Health Region.

METHODS

This study reports data from a population-based, retrospective, cohort study from patients diagnosed with HT in PHC units of Lisbon and Tagus Valley Region from 1 January to 31 March 2011, with no prior use of AHT drugs. Primary adherence rate was expressed as number of claims records/total number of prescriptions records. Data were collected from SIARS for each patient during a 2-year period.

RESULTS

Overall primary adherence rate was 58.5%, increasing with age. Rates were higher for men, living in the Lisbon Metropolitan Area and diagnosed with uncomplicated HT. Drugs acting on the renin-angiotensin system had the highest rates, increasing for fixed-dose combinations and diminishing with the increase of cost for the patient.

CONCLUSIONS

Overall, almost 1 out of 2 prescribed AHT drugs were not dispensed. Until this study, little was known in Portugal about primary adherence. Our findings imply that the potential benefits of AHT therapy cannot be fully realized in this population.

Initial non-adherence to antihypertensive medications in the United States: a systematic literature review

An important component of hypertension management is the initiation and continuation of antihypertensive medications. Non-adherence during the long-term use of antihypertensive medications is well studied. However, there is a paucity of research about the frequency and clinical consequences of failing to take the first dose of an antihypertensive, a treatment challenge known as initial medication non-adherence (IMN). This systematic literature review summarizes the published evidence from 2010 to 2019 on the prevalence, associated factors, consequences, and solutions for IMN to antihypertensive medications in the United States. Of the fifteen studies identified, nine studies reported the prevalence of IMN, two studies examined patient-reported reasons for IMN, and four studies evaluated interventions aimed to lower IMN. It is estimated that 5-34% of patients do not obtain their new antihypertensive medications. Factors and reasons cited include patient demographics, patient beliefs or perceptions about medications, cost or financial barriers, and clinical characteristics, such as a new hypertension diagnosis or higher co-morbid disease burden. The clinical, economic, and patient-reported outcomes of IMN are not well researched. In addition, interventions to address IMN have yielded inconsistent results. Significant opportunities exist for further research into this dimension of patient behavior to better understand and address IMN to new antihypertensive medications.

Primary Non-adherence to Treatment with New Oral Anticoagulants: The Results of a Prospective Observational Study «ANTEY»

Aim:

To assess the main characteristics of patients with non-valvular Atrial Fibrillation (AF) who are initially non-adherent to New Oral Anticoagulants (NOAC), and to identify factors associated with this version of non-adherence.

Materials and Methods:

The ANTEY study included 201 patients with non-valvular AF, who had indications and without contraindications for NOAC treatment. The patients had previously been advised to take oral anticoagulants but they did not comply with all medical recommendations. The observation period was 1 year, during which 2 in-person visits were performed: an inclusion visit (V0) and a visit (V1), as well as 1 telephone contact/follow up (FU); the interval between contacts was 6 months. All patients were recommended to take the NOAC by decision of the physician. During the V0, V1 and FU visits, the “National Society for Evidence-Based Pharmacotherapy (NSEPh) Adherence Scale” questionnaire was used to assess overall adherence and associated factors. 15 (7.5%) patients had not started NOAC therapy by the end of the study (primary non-adherent patients). Their characteristics are analysed in this work.

Results:

The main reasons for primary non-adherence to NOAC were high cost (33.3%), fears of adverse effects (AE) (33.3%), doubts about the need for treatment (13.3%) and the complex therapy regimen (13.3%). In the group of primary non-adherent patients in comparison with the rest of the patients there were significantly more patients with 1 point according to CHADS2VASc (20% and 2.2%, respectively, p = 0.029) and patients with 3 points according to HAS-BLED (33.3% and 9.1%, respectively, p = 0.006); they took antiplatelet drugs more often 73.3% versus 21.5%, respectively (p = 0.001). Full employment at work (OR = 5.2; CI95% [1.5; 18.1], p = 0.009), history of quitting smoking (OR = 5.1; CI95% [1.5; 17.0], p = 0,008), the presence of any pharmacotherapy AE (OR = 4.0; CI95% [1.01; 16.0], p = 0.048) increased the chance of primary non-adherence to NOAC by 4-5 times.

Conclusion:

The most vulnerable in relation to initiation of NOAC therapy for the prevention of thromboembolic complications in AF are those patients who continue to work or have any pharmacotherapy AE. The leading factors preventing the initiation of NOAC administration are their high cost, fear of the development of AE from the therapy, and patients’ doubts about the need for treatment with these drugs. The clinical trial registration number is NCT 03790917.

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.

Primary medication nonadherence calculation method specifications impact resulting rates

BACKGROUND

Previous literature has illustrated a wide range of primary medication nonadherence (PMN) rates due to inconsistent calculation methods and parameters, but the impact of parameter specifications on PMN rates has not been assessed.

OBJECTIVES

The objective of this study was to evaluate the impact of lookback window (LBW), duplicate window (DW), and fill window (FW) specifications on PMN rates in patients prescribed specialty self-administered oncology medications.

METHODS

This was a single-center, retrospective cohort analysis. Patients receiving a new electronic specialty oncology prescription January-December 2018 were included; excluded if re-routed to an external pharmacy within 2 days, fell within a DW, or cancelled within a FW. Twenty-four methods were used to calculate PMN based on combinations of the following parameters: (i) absence of prior specialty self-administered oncology medication fill within LBW (90, 180 days); (ii) absence of a duplicate prescription within DW (2, 7, 30 days); and (iii) sold status within FW (14, 30, 60, 90 days). For each method, PMN was calculated as the number of unsold prescriptions within the FW divided by all eligible prescriptions.

RESULTS

We evaluated 4,482 prescriptions, resulting in PMN ranging from 16% to 23%. Patients were commonly male (53%) and white (83%), with a median age of 64 years (interquartile range, IQR, 54, 72). Increasing the LBW from 90 to 180 days resulted in exclusion of 72 (2%) prescriptions and minimally impacted PMN rates. Most duplicate prescriptions (87%) occurred within two days of original prescription and PMN rates were minimally affected by DW. Most fulfilled prescriptions were filled within FW 30 days, 98% with a method of LBW 180, DW 2, and FW 30. Adjusting the FW consistently impacted PMN rates.

CONCLUSIONS

Because various PMN definitions can significantly impact results, a thorough explanation of all parameter specifications should be reported in research using PMN.

Initiation and Single Dispensing in Cardiovascular and Insulin Medications: Prevalence and Explanatory Factors

BACKGROUND

Adherence problems have negative effects on health, but there is little information on the magnitude of non-initiation and single dispensing.

OBJECTIVE

The aim of this study was to estimate the prevalence of non-initiation and single dispensation and identify associated predictive factors for the main treatments prescribed in Primary Care (PC) for cardiovascular disease (CVD) and diabetes.

METHODS

Cohort study with real-world data. Patients who received a first prescription (2013-2014) for insulins, platelet aggregation inhibitors, angiotensin-converting enzyme inhibitors (ACEI) or statins in Catalan PC were included. The prevalence of non-initiation and single dispensation was calculated. Factors that explained these behaviours were explored.

RESULTS

At three months, between 5.7% (ACEI) and 9.1% (antiplatelets) of patients did not initiate their treatment and between 10.6% (statins) and 18.4% (ACEI) filled a single prescription. Body mass index, previous CVD, place of origin and having a substitute prescriber, among others, influenced the risk of non-initiation and single dispensation.

CONCLUSIONS

The prevalence of non-initiation and single dispensation of CVD medications and insulin prescribed in PC in is high. Patient and health-system factors, such as place of origin and type of prescriber, should be taken into consideration when prescribing new medications for CVD and diabetes.

Methods for Measuring Multiple Medication Adherence: A Systematic Review-Report of the ISPOR Medication Adherence and Persistence Special Interest Group

BACKGROUND

A broad literature base exists for measuring medication adherence to monotherapeutic regimens, but publications are less extensive for measuring adherence to multiple medications.

OBJECTIVES

To identify and characterize the multiple medication adherence (MMA) methods used in the literature.

METHODS

A literature search was conducted using PubMed, PsycINFO, the International Pharmaceutical Abstracts, the Cumulative Index to Nursing and Allied Health Literature and the Cochrane Library databases on methods used to measure MMA published between January 1973 and May 2015. A two-step screening process was used; all abstracts were screened by pairs of researchers independently, followed by a full-text review identifying the method for calculating MMA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed to conduct this systematic review. For studies that met the eligibility criteria, general study and adherence-specific characteristics and the number and type of MMA measurement methods were summarized.

RESULTS

The 147 studies that were included originated from 32 countries, in 13 disease states. Of these studies, 26 used proportion of days covered, 23 used medication possession ratio, and 72 used self-reported questionnaires (e.g., the Morisky Scale) to assess MMA. About 50% of the studies included more than one method for measuring MMA, and different variations of medication possession ratio and proportion of days covered were used for measuring MMA.

CONCLUSIONS

There appears to be no standardized method to measure MMA. With an increasing prevalence of polypharmacy, more efforts should be directed toward constructing robust measures suitable to evaluate adherence to complex regimens. Future research to understand the validity and reliability of MMA measures and their effects on objective clinical outcomes is also needed.

Primary Nonadherence to Oral Anticoagulants in Patients with Atrial Fibrillation: Real-World Data from a Population-Based Cohort

BACKGROUND

Primary nonadherence (not filling a first prescription) is an important yet unstudied aspect of adherence to oral anticoagulant (OAC) therapy.

OBJECTIVE

To estimate the rates of primary nonadherence to OACs and determine associated factors in real-world practice.

METHODS

This population-based retrospective cohort study set in the Valencia region of Spain (about 5 million inhabitants) included all patients with atrial fibrillation who were newly prescribed OACs during 2011-2014 (N = 18,715). Primary nonadherence was obtained by linking electronic prescription and dispensing data and assessed by type of OAC-vitamin K antagonists (VKAs) or non-VKA oral anticoagulants (NOACs). Covariates were obtained from diverse databases, including electronic medical records. Multivariate logistic regression models were used to assess characteristics associated with primary nonadherence, adjusting for a propensity score to minimize confounding by indication.

RESULTS

Primary nonadherence to OACs was 5.62% (VKA 4.29% vs. NOAC 10.81%; P < 0.001), with varying rates among specific drugs (acenocoumarol 4.2%, warfarin 10.9%, apixaban 5.0%, dabigatran 7.9%, and rivaroxaban 15.5%). After adjusting for potential confounders, the likelihood of not filling the first prescription was higher for NOAC patients than for VKA patients (OR = 2.76, 95% CI = 2.41-3.15). High coinsurance in the older groups (OR = 2.63, 95% CI = 1.47-4.69 for patients aged 66-75 years and OR = 3.02, 95% CI = 1.58-5.76 for patients aged > 75 years); being a non-Spanish European (OR = 1.49, 95% CI = 1.12-1.99); and having dementia (OR = 1.72, 95% CI = 1.37-2.16) were positively associated with primary nonadherence. Electronic transmission of prescriptions (OR = 0.85, 95% CI = 0.74-0.96); liver disease (OR = 0.73, 95% CI = 0.54-0.99); and polypharmacy (OR = 0.59, 95% CI = 0.50-0.70) were inversely associated with primary nonadherence.

CONCLUSIONS

Overall, primary nonadherence to OACs was relatively low (5%). However, important differences were found between VKAs and NOACs. After adjustment, patients prescribed NOACs nearly tripled the likelihood of nonadherence compared with patients prescribed VKAs, which could negatively affect their effectiveness in clinical practice. Identified correlates were similar to those shown in the limited evidence for other medications.

DISCLOSURES

This work was partially supported by the 2013 Collaboration Agreement between the Fundación para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO) from the Valencia Ministry of Health and Boehringer Ingelheim, a nonconditioned program to conduct independent research in chronic health care, pharmacoepidemiology, and medical practice variation. Rodriguez-Bernal was funded by the Instituto de Salud Carlos III, Spanish Ministry of Health, and cofinanced by the European Regional Development Fund (grant number RD12/0001/0005). The views presented here are those of the authors and not necessarily those of the FISABIO Foundation, the Valencia Ministry of Health, or the study sponsors. The funding sources had no access to study data and did not participate in any way in the design or conduct of the study, data analysis, decisions regarding the dissemination of findings, the development of the manuscript, or its publication. Peiró has received fees for participation in scientific meetings and courses sponsored by Novartis and Ferrer International. In 2014, Sanfélix-Gimeno participated in an advisory meeting of Boehringer Ingelheim. García-Sempere is a former employee of Boehringer Ingelheim. Rodriguez-Bernal and Hurtado have no relationships relevant to the contents of this article to disclose. This work was previously submitted as an abstract (podium presentation) at the 31st International Society of Pharmacoepidemiology (ISPE) Annual Conference; August 22-26, 2015; Boston, Massachusetts.

A systematic literature review comparing methods for the measurement of patient persistence and adherence

OBJECTIVES

A systematic literature review was conducted comparing different approaches estimating persistence and adherence in chronic diseases with polypharmacy of oral and subcutaneous treatments.

METHODS

This work followed published guidance on performing systematic reviews. Twelve electronic databases and grey literature sources were used to identify studies and guidelines for persistence and adherence of oral and subcutaneous therapies in hypercholesterolemia, type 2 diabetes, hypertension, osteoporosis and rheumatoid arthritis. Outcomes of interest of each persistence and adherence data collection and calculation method included pros: accurate, easy to use, inexpensive; and cons: inaccurate, difficult to use, expensive.

RESULTS

A total of 4158 records were retrieved up to March 2017. We included 16 observational studies, 5 systematic reviews and 7 guidelines, in patients with hypercholesterolemia (n = 8), type 2 diabetes (n = 4), hypertension (n = 2), rheumatoid arthritis (n = 1) and mixed patient populations (n = 13). Pharmacy and medical records offer an accurate, easy and inexpensive data collection method. Pill count, medication event monitoring systems (MEMs), self-report questionnaires and observer report are easy to use. MEMS and biochemical monitoring tests can be expensive. Proportion of days covered (PDC) was recommended as a gold standard calculation method for long-term treatments. PDC avoids use of days' supply in calculation, hence is more accurate compared to medication possession ratio (MPR) to assess adherence to treatments in chronic diseases.

CONCLUSIONS

Decisions on what method to use should be based on considerations of the route of medication administration, the resources available, setting and aim of the assessment. Combining different methods may provide wider insights into adherence and persistence, including patient behavior.

Reasons for Primary Medication Nonadherence: A Systematic Review and Metric Analysis

BACKGROUND

The behavior of medication nonadherence is distinguished into primary and secondary nonadherence. Primary nonadherence (PNA) is not as thoroughly studied as secondary nonadherence.

OBJECTIVE

To explore and synthesize contributing factors to PNA based on the existing body of literature.

METHODS

A search was performed on the PubMed, PsycINFO, CINAHL, and ScienceDirect databases to identify previously published scholarly articles that described the "factors," "reasons," "determinants" or "facilitators" of PNA. The alternate spelling of "nonadherence" was used as well. The effect that the articles had in the research community, as well as across social media, was also explored.

RESULTS

22 studies met the inclusion criteria for this review. The PNA factors that the studies identified were diverse, spanning economic, social, and medical dimensions. A multilevel classification method was applied to categorize the factors into 5 broad groups-patient, medication, health care provider, health care system, and socioeconomic factors. Patient factors were reported the most. Some groups overlapped and shared a dynamic causal relationship where one group influenced the outcome of the other.

CONCLUSIONS

Like all nonadherence behaviors, PNA is multifaceted with highly varied contributing factors that are closely associated with one another. Given the multidimensional nature of PNA, future intervention studies should focus on the dynamic relationship between these factor groups for more efficient outcomes.

DISCLOSURES

This research was supported by the National Research Foundation Singapore under its National Innovation Challenge on Active and Confident Ageing (Award No. MOH/NIC/CAHIG03/2016) and administered by the Singapore Ministry of Health's National Medical Research Council. This research was also supported by the National Research Foundation within the Prime Minister's Office of Singapore, under its Science of Research, Innovation and Enterprise Programme (SRIE Award No. NRF2014-NRF-SRIE001-019). The authors have no relevant conflicts of interest to disclose.

Predicting Adherence and Persistence with Oral Bisphosphonate Therapy in an Integrated Health Care Delivery System

BACKGROUND

Examining drug exposure is essential to pharmacovigilance, especially for bisphosphonate (BP) therapy.

OBJECTIVE

To examine differences in 4 measures of oral BP exposure: treatment discontinuation, adherence, persistence, and nonpersistence.

METHODS

Among women aged ≥ 50 years who initiated oral BP therapy during 2002-2007 with at least 3 years of health plan membership follow-up, discontinuation was defined by evidence of no further treatment during the study observation period. Among those with at least 2 filled BP prescriptions during the study period, adherence was calculated for each year of follow-up using the (modified) proportion of days covered (mPDC) metric that allows for stockpiling of prescription/refills overlap ≤ 30 days supply. Persistence was quantified by treatment duration, allowing a gap of up to 60 days between prescription/refill days covered. Nonpersistence was quantified by the periods without drugs outside this allowable gap. Multivariable logistic regression was used to compare age and race groups and the relationships of early adherence (adherence during the first year) with subsequent adherence.

RESULTS

Among 48,390 women initiating oral BP therapy and followed for 3 years, 26.7% discontinued in year 1, and 14.7% of the remaining 35,456 women discontinued in year 2. Discontinuation rates were slightly higher (29.4%, P < 0.001) for women aged ≥ 75 years and somewhat lower (21.1%, P < 0.001) for Asian women. During the first year, 60.4% of the women achieved an mPDC of ≥ 75%, with demographic differences in adherence similar to that seen for treatment discontinuation. Over the 3 years, the median mPDC levels for BP therapy were 86%, 84%, and 85% in years 1, 2, and 3, respectively, for those receiving treatment. Cumulative persistence was 2.3 years (median, IQR = 1.0-3.0) overall and slightly greater for Asian versus white women and lower for older women. There were 18,174 (42.9%) women with at least 1 period of nonpersistence during 3 years follow-up in excess of the 60-day allowable gap between prescription/refills (median cumulative nonpersistence = 0.65, IQR = 0.30-1.25 years). Women with mPDC ≥ 75% during the first year had a 12-fold and 6-fold increased odds of mPDC ≥ 75% during year 2 and year 3, respectively.

CONCLUSIONS

BP discontinuation rates are highest for women during the first year. Among those continuing treatment in subsequent years, adherence rates were relatively stable. Persistence and adherence varied slightly by age and was somewhat higher in Asians, contributing to differences in cumulative BP exposure. We also found evidence that optimal adherence in the first year was highly predictive of optimal adherence in the subsequent 1-2 years. Hence, subgroups of patients receiving oral BP drugs may require different levels of support and monitoring to maximize treatment benefit, especially based on early patterns of use.

DISCLOSURES

This study was supported by grants from the Kaiser Permanente Northern California Community Benefit Program and the National Institutes of Health, 1R01AG047230-01A1. The opinions expressed in this publication are solely the responsibility of the authors and do not represent the official views of Kaiser Permanente or the National Institutes of Health. Hui, Yi, and Chandra have received past research funding from Amgen not related to the current study. Adams has received research funding from Amgen, Merck, and Otsuka not related to the current study. Niu has received research funding from Bristol-Myers Squibb not related to the current study. Ettinger has received past legal fees in litigation involving Fosamax. Lo has received past research funding from Amgen and current research funding from Sanofi not related to the current study. The data from this study were presented at the Academy of Managed Care Pharmacy Annual Meeting; April 19-22, 2016; San Francisco, California. Study concept and design were contributed primarily by Hui and Lo, along with Adams, Niu, Yi, and Ettinger. Hui took the lead in data collection, along with Chandra, and data interpretation was performed by Niu, Yi, and Lo, along with the other authors. The manuscript was written by Hui, Adams, and Lo, along with Niu, Yi, and Ettinger, and revised by Ettinger, Hui, Lo, and Niu, along with the other authors.

Long-term patterns of adherence to medication therapy among patients with type 2 diabetes mellitus in Denmark: The importance of initiation

AIMS

Poor adherence to medication therapy among type 2 diabetes patients is a clinical challenge. We aimed to determine which factors are associated with the three phases of long-term adherence to medication: initiation, implementation and discontinuation in a register-based study.

METHODS

Adherence to six medicine groups (metformin, sulfonylureas, acetylsalicylic acid, thiazide diuretics, renin angiotensin system inhibitors, and statins) were analysed among 5,232 patients with type 2 diabetes at a tertiary referral hospital during 1998-2009. Rate-ratios of initiation of treatment, recurrent gaps in supply of medication, and discontinuation of treatment were analysed using Poisson regression.

RESULTS

Poor initiation rather than poor implementation or discontinuation was the main contributor to medication nonadherence. Polypharmacy was a risk factor for slower initiation of treatment for all six medicine groups (rate ratio ranging 0.79 95%CI [0.72-0.87] to 0.89 95%CI [0.82-0.96] per already prescribed medicine), but once patients were in treatment, polypharmacy was not associated with recurrence of gaps in supply of medication, and polypharmacy was associated with lower risk of discontinuation (rate ratio ranging 0.93 95%CI [0.86-1.00] to 0.96 95%CI [0.93-0.99] per prescribed medicine). Other identified risk factors for slow initiation, poor implementation, and discontinuation were diabetes duration, younger age, and Turkish/Pakistani origin.

DISCUSSION

This study showed that a risk factor does not necessarily have the same association with all three elements of adherence (initiation, implementation and discontinuation), and that efforts supporting patients introduced to more complex drug combinations should be prioritized.

Primary Nonadherence, Associated Clinical Outcomes, and Health Care Resource Use Among Patients with Rheumatoid Arthritis Prescribed Treatment with Injectable Biologic Disease-Modifying Antirheumatic Drugs

BACKGROUND

Adherence to biologic disease-modifying antirheumatic drugs (bDMARDs) among patients with rheumatoid arthritis (RA) is often suboptimal in routine clinical practice. Low or nonadherence can reduce the effectiveness of bDMARD therapies.

OBJECTIVE

To evaluate filling of newly prescribed initial bDMARDs for the treatment of RA and evaluate potential for characterizing treatment decisions and patient outcomes.

METHODS

In this retrospective cohort analysis, patients aged ≥ 18 years with an RA diagnosis (ICD-9-CM code 714.xx) were selected from a de-identified database of clinical information from the Electronic Health Record (EHR; Humedica) database linked to health care claims (Optum) from commercial and Medicare Advantage health plans (2007-2013). The first biologic prescription date in EHR was the index date. Patients were categorized as filling the prescription within 30 days (early fillers), 31-180 days (late fillers), or not at all within 180 days (nonfillers) of index date.

RESULTS

Of 373 patients meeting inclusion criteria, 170 (45.6%), 59 (15.8%), and 144 (38.6%) were categorized as early fillers, late fillers, and nonfillers, respectively. Most prescriptions were written or ordered for tumor necrosis factor inhibitors (88.7%). Compared with late and nonfillers, early fillers were younger and more likely to be female, with higher pain scores (among those reporting pain scores) and RA severity scores pre-index, and filled more prescriptions for any reason pre-index. More nonfillers (66.0%) were Medicare patients than early (17.7%) and late (35.6%) fillers. During days 0-30 post-index, conventional synthetic DMARD use was greatest for early fillers (45.9%) and lowest among nonfillers (24.3%); however, during days 31-180 post-index, the proportion was highest for late fillers (61.0%) and lowest for nonfillers (35.4%). Of early fillers, 12.9% did not fill/receive a bDMARD after 30 days. Only 23 patients had pre/post-index pain scores, and 47 patients had a rationale for stopping or not filling a bDMARD. In patients with pharmacy and medical coverage for 180 days post-index, early fillers had greater RA-related pharmacy and medical resource use and costs than late and nonfillers combined.

CONCLUSIONS

These findings confirm a high rate of primary nonadherence to bDMARDs among patients with RA.

Medication Adherence Does Not Explain Black-White Differences in Cardiometabolic Risk Factor Control among Insured Patients with Diabetes

BACKGROUND

Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes.

METHODS

We identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (n = 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (n = 27,954), and systolic blood pressure (SBP) >130 mm Hg (n = 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator.

RESULTS

We observed poorer medication adherence among black patients than white patients (p < 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (p < 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics.

CONCLUSIONS

Medication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes.

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.

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.

Medication adherence part one: understanding and assessing the problem

PURPOSE

This is the first of a three-part series on medication adherence in which the authors describe the continuum of adherence to nonadherence of medication usage.

DATA SOURCES

Research articles through MEDLINE and PubMed.

CONCLUSIONS

Understanding the magnitude and scope of the problem of medication nonadherence is the first step in reaching better adherence rates. The second step is to evaluate the risk factors for each patient for medication adherence/nonadherence. The third step is to assess for adherence. The process will continue with a consistent systematic process to evaluate continual adherence.

IMPLICATIONS FOR PRACTICE

The implications for nurse practitioners include using time with patients to assist them in adherence, building a trusting relationship with patients, and developing protocols for assessing and preventing nonadherence.

Adherence to therapy and adverse drug reactions: is there a link?

INTRODUCTION

Advances in biomedical technology and access to effective medications have resulted in significant improvements in patient survival and quality of life. Patient adherence is crucial to quality healthcare outcomes; however, achievement of consistent adherence remains difficult. Patient non-adherence represents an important health problem, from a clinical/economic viewpoint, being associated with reduced treatment benefits and significant financial burden. Non-adherence potentially leads to adverse drug events (ADEs), which are generally responsible for poorer health outcomes and avoidable resource misuse. Further, adverse drug reactions (ADRs) exemplify one of the most significant barriers to patients' medication-taking behavior with further detrimental clinical/economic outcomes.

AREAS COVERED

The authors review adherence definitions and its measurement, emphasizing the consequences of the New European Pharmacovigilance Legislation on ADR definition. They analyzed the causes and the clinical/economic consequences of non-adherence and ADEs/ADRs in order to highlight a possible causal link.

EXPERT OPINION

Careful assessment of this harmful relationship is crucial in planning for the interventions needed to improve effectiveness of pharmacological care and to safeguard the sustainability of healthcare systems. Finally, through the 'deactivation' of this link, there will be more chance that advances in healthcare technologies will realize their potential to reduce the burden of chronic illness.

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.

Medicare Star excludes diabetes patients with poor CVD risk factor control

OBJECTIVES

CMS recently added medication adherence to antihypertensives, antihyperlipidemics, and oral antihyperglycemics to its Medicare Star quality measures. These CMS metrics exclude patients with <2 medication fills (ie, "early nonadherence") and patients concurrently taking insulin. This study examined the proportion of patients with diabetes prescribed cardiovascular disease (CVD) medications excluded from Star adherence metrics and assessed the relationship of both Star-defined adherence and exclusion from Star metrics with CVD risk factor control.

STUDY DESIGN

Cross-sectional, population-based analysis of 129,040 patients with diabetes aged ≥65 years in 2010 from 3 Kaiser Permanente regions.

METHODS

We estimated adjusted risk ratios to assess the relationship between achieving Star adherence and being excluded from Star adherence metrics, with CVD risk factor control (glycated hemoglobin [A1C]<8.0%, low-density lipoprotein cholesterol [LDL-C]<100 mg/dL, and systolic blood pressure [SBP]<130 mm Hg) in patients with diabetes.

RESULTS

Star metrics excluded 27% of patients with diabetes prescribed oral medications. Star-defined nonadherence was negatively associated with CVD risk factor control (risk ratio [RR], 0.95, 0.84, 0.96 for A1C, LDL-C, and SBP control, respectively; P<.001). Exclusion from Star metrics due to early nonadherence was also strongly associated with poor control (RR, 0.83, 0.56, 0.87 for A1C, LDL-C, and SBP control, respectively; P<.001). Exclusion for insulin use was negatively associated with A1C control (RR, 0.78; P<.0001).

CONCLUSIONS

Medicare Star adherence measures underestimate the prevalence of medication nonadherence in diabetes and exclude patients at high risk for poor CVD outcomes. Up to 3 million elderly patients with diabetes may be excluded from these measures nationally. Quality measures designed to encourage effective medication use should focus on all patients treated for CVD risk.

Primary non-adherence in general practice: a Danish register study

PURPOSE

The aim of this study was to describe primary non-adherence (PNA) in a Danish general practitioner (GP) setting, i.e. the extent to which patients fail to fill the first prescription for a new drug. We also assessed the length of time between the issuing of a prescription by the GP and the dispensing of the drug by the pharmacist. Lastly, we sought to identify associations between PNA and the characteristics of the patient, the drug and the GP.

METHODS

By linking data on issued prescriptions compiled in the Danish General Practice Database with data on redeemed prescriptions contained in the Danish National Prescription Registry, we calculated the rate of PNA among Danish patients from January 2011 through to August 2012. Characteristics associated with PNA were analysed using a mixed effects logistic regression model.

RESULTS

A total of 146,959 unique patients were started on 307,678 new treatments during the study period. The overall rate of PNA was 9.3 %, but it varied according to the major groups of the Anatomical Therapeutic Chemical (ATC) Classification System, ranging from 16.9 % for "Blood and bloodforming organs" (ATC group B) to 4.7 % for "Cardiovascular system" (ATC group C). Most of the patients redeemed their prescriptions within the first week. Older age, high income and a diagnosis of chronic obstructive pulmonary disease were found to be significantly associated with lower rates of PNA, while polypharmacy and a diagnosis of ischaemic heart disease were associated with higher rates of PNA.

CONCLUSIONS

The overall rate of PNA among Danish residents in a GP setting was 9.3 %. Certain drug classes and patient characteristics were associated with PNA.

A multistate model and an algorithm for measuring long-term adherence to medication: a case of diabetes mellitus type 2

OBJECTIVES

To develop a multistate model and an algorithm for calculating long-term adherence to medication among patients with a chronic disease.

METHODS

We propose definitions of the different states of waiting, persistence, with sufficient supply to implement the prescribed dosing regimen, gaps, nonpersistence, and nonacceptance and an algorithm for transitions between states to describe long-term adherence to medication treatment. The model and algorithm are operationalized for use in a case with a retrospective cohort of patients with type 2 diabetes mellitus, with access to records of prescribed drugs from a Danish diabetes research hospital and records of filled prescriptions at Danish pharmacies from the Danish Health and Medicines Authority.

RESULTS

Calculations of long-term adherence to medication are shown for patients with type 2 diabetes mellitus on metformin and/or simvastatin. The study shows how the prevalence of patients waiting to initiate treatment, patients with supply to implement the prescribed dosing regimen, patients not accepting treatment, and patients discontinuing treatment varies over time.

CONCLUSIONS

The proposed multistate model and algorithm can easily be translated and used for the calculation of adherence to medication in any chronic disease. The model and algorithm take time into account, and thus, changes in incidence rates and prevalence of the different states over time can be estimated on several time scales (calendar time, age of the patient, and time since indication for medication).

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.

Providing patients with pharmacogenetic test results affects adherence to statin therapy: results of the Additional KIF6 Risk Offers Better Adherence to Statins (AKROBATS) trial

Despite the clinical benefit of statin therapy and the numerous strategies used to improve adherence, no strategy has used direct communication of genetic test results to the patient as an adherence and persistence motivator. We investigated in a real-world setting the effect of a process of providing KIF6 test results and risk information directly to 647 tested patients on 6-month statin adherence (proportion of days covered (PDC)) and persistence compared with concurrent non-tested matched controls. Adjusted 6-month statin PDC was significantly greater in tested patients: 0.77 (95% confidence interval (CI) 0.72-0.82) vs controls 0.68 (95% CI 0.63-0.73), P<0.0001. Significantly more tested patients were adherent (PDC⩾0.80) (63.4% (59.6-67.1%) vs 45.0% (41.1-48.8%), P<0.0001) and persisted on therapy (69.1% (65.4-72.5%) vs 53.3% (49.4-57.1%), P<0.0001). Similar results were observed in a secondary comparison with 779 unmatched patients who declined testing. The Additional KIF6 Risk Offers Better Adherence to Statins trial provides the first evidence that pharmacogenetic testing may modify patient adherence.

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.

Primary medication non-adherence after discharge from a general internal medicine service

Background

Medication non-adherence frequently leads to suboptimal patient outcomes. Primary non-adherence, which occurs when a patient does not fill an initial prescription, is particularly important at the time of hospital discharge because new medications are often being prescribed to treat an illness rather than for prevention.

Methods

We studied older adults consecutively discharged from a general internal medicine service at a large urban teaching hospital to determine the prevalence of primary non-adherence and identify characteristics associated with primary non-adherence. We reviewed electronic prescriptions, electronic discharge summaries and pharmacy dispensing data from April to August 2010 for drugs listed on the public formulary. Primary non-adherence was defined as failure to fill one or more new prescriptions after hospital discharge. In addition to descriptive analyses, we developed a logistical regression model to identify patient characteristics associated with primary non-adherence.

Results

There were 493 patients eligible for inclusion in our study, 232 of whom were prescribed new medications. In total, 66 (28%) exhibited primary non-adherence at 7 days after discharge and 55 (24%) at 30 days after discharge. Examples of medications to which patients were non-adherent included antibiotics, drugs for the management of coronary artery disease (e.g. beta-blockers, statins), heart failure (e.g. beta-blockers, angiotensin converting enzyme inhibitors, furosemide), stroke (e.g. statins, clopidogrel), diabetes (e.g. insulin), and chronic obstructive pulmonary disease (e.g. long-acting bronchodilators, prednisone). Discharge to a nursing home was associated with an increased risk of primary non-adherence (OR 2.25, 95% CI 1.01–4.95).

Conclusions

Primary non-adherence after medications are newly prescribed during a hospitalization is common, and was more likely to occur in patients discharged to a nursing home.

Medication adherence to multidrug regimens

Despite the fact that medication adherence has been extensively described in the literature over the last several decades, a quote by Becker and Maiman from over 35 years ago best captures the current state of our understanding: “Patient compliance[sic adherence] has become the best documented, but least understood, health behavior.” Future research is greatly needed to identify and translate safe and effective interventions into routine clinical practice to improve adherence. Only then can we begin to make significant improvements to the medication use process and, in turn, the health of older adults.

Non-adherence to drug therapy and drug acquisition costs in a national population--a patient-based register study

Background

Patients' non-adherence to drug therapy is a major problem for society as it is associated with reduced health outcomes. Generally, approximately only 50% of patients with chronic disease in developed countries adhere to prescribed therapy, and the most common non-adherence refers to chronic under-use, i.e. patients use less medication than prescribed or prematurely stop the therapy. Patients' non-adherence leads to high additional costs for society in terms of poor health. Non-adherence is also related to the unnecessary sale of drugs. The aim of the present study was to estimate the drug acquisition cost related to non-adherence to drug therapy in a national population.

Methods

We constructed a model of the drug acquisition cost related to non-adherence to drug therapy based on patient register data of dispensed out-patient prescriptions in the entire Swedish population during a 12-month period. In the model, the total drug acquisition cost was successively adjusted for the assumed different rates of primary non-adherence (prescriptions not being filled by the patient), and secondary non-adherence (medication not being taken as prescribed) according to the patient's age, therapies, and the number of dispensed drugs per patient.

Results

With an assumption of a general primary non-adherence rate of 3%, and a general secondary non-adherence rate of 50%, for all types of drugs, the acquisition cost related to non-adherence totalled SEK 11.2 billion (€ 1.2 billion), or 48.5% of total drug acquisition costs in Sweden 2006.

With the assumption of varying primary non-adherence rates for different age groups and different secondary non-adherence rates for varying types of drug therapies, the acquisition cost related to non-adherence totalled SEK 9.3 billion (€ 1.0 billion), or 40.2% of the total drug acquisition costs.

When the assumption of varying primary and secondary non-adherence rates for a different number of dispensed drugs per patient was added to the model, the acquisition cost related to non-adherence totalled SEK 9.9 billion (€ 1.1 billion), or 42.6% of the total drug acquisition costs.

Conclusions

Our estimate indicates that drug acquisition costs related to non-adherence represent a substantial proportion of the economic resources in the health care sector. A low rate of primary non-adherence, combined with a high rate of secondary non-adherence, contributes to a large degree of unnecessary medical spending. Thus, efforts of different types of interventions are needed to improve secondary adherence.