Operationalization and validation of a novel method to calculate adherence to polypharmacy with refill data from the Australian pharmaceutical benefits scheme (PBS) database

Abstract

BackgroundElectronic health care data contain rich information on medicine use from which adherence can be estimated. Various measures developed with medication claims data called for transparency of the equations used, predominantly because they may overestimate adherence, and even more when used with multiple medications. We aimed to operationalize a novel calculation of adherence with polypharmacy, the daily polypharmacy possession ratio (DPPR), and validate it against the common measure of adherence, the medication possession ratio (MPR) and a modified version (MPRm).MethodsWe used linked health data from the Australian Pharmaceutical Benefits Scheme and Western Australian hospital morbidity dataset and mortality register. We identified a strict study cohort from 16,185 patients aged ≥65 years hospitalized for myocardial infarction in 2003–2008 in Western Australia as an illustrative example. We applied iterative exclusion criteria to standardize the dispensing histories according to previous literature. A SAS program was developed to calculate the adherence measures accounting for various drug parameters.ResultsThe study cohort was 348 incident patients (mean age 74.6±6.8 years; 69% male) with an admission for myocardial infarction who had cardiovascular medications over a median of 727 days (range 74 to 3,798 days) prior to readmission. There were statins (96.8%), angiotensin converting enzyme inhibitors (88.8%), beta-blockers (85.6%), and angiotensin receptor blockers (13.2%) dispensed. As expected, observed adherence values were higher with mean MPR (median 89.2%; Q1: 73.3%; Q3: 104.6%) than mean MPRm (median 82.8%; Q1: 68.5%; Q3: 95.9%). DPPR values were the most narrow (median 83.8%; Q1: 70.9%; Q3: 96.4%). Mean MPR and DPPR yielded very close possession values for 37.9% of the patients. Values were similar in patients with longer observation windows. When the traditional threshold of 80% was applied to mean MPR and DPPR values to signify the threshold for good adherence, 11.6% of patients were classified as good adherers with the mean MPR relative to the DPPR.ConclusionIn the absence of transparent and standardized equations to calculate adherence to polypharmacy from refill databases, the novel DPPR algorithm represents a valid and robust method to estimate medication possession for multi-medication regimens.

Comparison of Different Strategies to Measure Medication Adherence via Claims Data in Patients With Chronic Heart Failure

“…Methods and related parameters to assess medication adherence via claims data differ widely in the literature . To the best of our knowledge, this is the first analysis comparing the influence of different strategies for the parameters assumed PDD, stockpiling, and truncations because of hospitalizations in patients with CHF.…”

“…If this dose is unknown, no gold standard exists for the assumption of the daily doses prescribed. Authors referred to the doses of major clinical trials, the DDD, the doses recommended in each agent's product monograph, or the assumption of one or one or two tablets per day . As for many studies analyzing claims data, the prescribed doses were not available in our study.…”

“…However, irregular and inconsistent intake of medications is common . A frequently used method to determine medication adherence is the analysis of claims data . Claims data are based on billing data with additional information.…”

“…There are different measures and related parameters for the calculation of medication adherence via claims data . Even though there is no gold standard, the medication possession ratio (MPR) and the proportion of days covered (PDC) are most commonly used . However, different definitions and related parameters within these methods are used in the literature, e.g., consideration of the duration of hospital stays and stockpiling (for an overview, see Andrade et al ., Hess et al ., and Vollmer et al …”

“…We identified the following parameters to be considered for adherence measures via claims data: measurement method, observation period, substances, dosing information, switches, stockpiling, truncations, statistical analysis, and cutoff for adherence. A crucial point for the adherence measure is the daily dosage a patient is advised to take—information not available in many claims data …”