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.
Adherence to medications is directly associated with improved clinical outcomes in chronic diseases such as diabetes, heart failure, hyperlipidemia, coronary artery disease, and hypertension. High adherence is also associated with lower health care costs. If adherence is inaccurately estimated, results of comparative effectiveness research may not be correctly interpreted, as the relationship between medication exposure and clinical outcome is likely to be distorted.
Adherence is often calculated using claims-based electronic pharmacy databases. Pharmacy databases enable adherence monitoring in large populations and assess medication dispensing, the critical first step in the adherence process. Pharmacy databases have also been used to trigger interventions intended to increase medication effectiveness and safety. Claims databases are extensively used to estimate adherence because they are relatively inexpensive, efficient, and an accessible source of information about the frequency and timeliness of medication refills in large populations. A key limitation to pharmacy databases is that they can be used only to estimate medication possession, not medication consumption. Other tools to measure adherence, such as electronic devices, patient self-report, and pill counts, have advantages and disadvantages; no method is considered the gold standard.
Published adherence literature using pharmacy databases is based on data from patients who have 1 or more dispensings of the drug(s) of interest. By definition, pharmacy claims databases do not contain information about medications ordered but never dispensed (ie, primary nonadherence). Furthermore, medications dispensedonly once but never refilled (ie, early nonpersistence) do not meet the minimum criterion of 2 dispensings required to calculate indices such as the continuous multiple-interval measure of gaps (CMG, the total number of days for which a drug is unavailable within a period) or the continuous multiple-interval measure of medication availability (CMA, the days' supply of medication obtained throughout the period divided by the number of days of participation). As a result, many adherence studies systematically exclude patients with primary nonadherence or early nonpersistence, the 2 subcategories that together compose early nonadherence.
In addition, medication ordering and dispensing are generally recorded in separate, unlinked computer systems, thus limiting access to information required to calculate early nonadherence. Prescription orders have seldom been linked to medication dispensings, and reconciliation of orders and dispensings has been even less frequent. We must better understand the importance of excluding calculations of early nonadherence and the implications this has on interpreting comparative effectiveness data if we are to achieve the full benefits of adherence and comparative effectiveness initiatives.
We hypothesized that population medication adherence estimates calculated from pharmacy databases are inflated as a result of excluding data from patients who fail to obtain initial prescriptions for chronic medications and patients who obtain only a single dispensing of chronic medications. Our specific objective was to estimate the magnitude of misestimation in adherence estimates that resulted from excluding assessment of patients with early nonadherence. To achieve this objective, we linked prescription orders in an ambulatory electronic health record (EHR) to medication dispensings in a pharmacy information system for 3 categories of commonly used oral medication where adherence is directly associated with improved clinical outcomes: antihypertensives, antidiabetics, and/or antihyperlipidemics. We then determined the misestimation of adherence that resulted from not including the early nonadherent patients.
Abstract and Introduction
Abstract
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.
Introduction
Adherence to medications is directly associated with improved clinical outcomes in chronic diseases such as diabetes, heart failure, hyperlipidemia, coronary artery disease, and hypertension. High adherence is also associated with lower health care costs. If adherence is inaccurately estimated, results of comparative effectiveness research may not be correctly interpreted, as the relationship between medication exposure and clinical outcome is likely to be distorted.
Adherence is often calculated using claims-based electronic pharmacy databases. Pharmacy databases enable adherence monitoring in large populations and assess medication dispensing, the critical first step in the adherence process. Pharmacy databases have also been used to trigger interventions intended to increase medication effectiveness and safety. Claims databases are extensively used to estimate adherence because they are relatively inexpensive, efficient, and an accessible source of information about the frequency and timeliness of medication refills in large populations. A key limitation to pharmacy databases is that they can be used only to estimate medication possession, not medication consumption. Other tools to measure adherence, such as electronic devices, patient self-report, and pill counts, have advantages and disadvantages; no method is considered the gold standard.
Published adherence literature using pharmacy databases is based on data from patients who have 1 or more dispensings of the drug(s) of interest. By definition, pharmacy claims databases do not contain information about medications ordered but never dispensed (ie, primary nonadherence). Furthermore, medications dispensedonly once but never refilled (ie, early nonpersistence) do not meet the minimum criterion of 2 dispensings required to calculate indices such as the continuous multiple-interval measure of gaps (CMG, the total number of days for which a drug is unavailable within a period) or the continuous multiple-interval measure of medication availability (CMA, the days' supply of medication obtained throughout the period divided by the number of days of participation). As a result, many adherence studies systematically exclude patients with primary nonadherence or early nonpersistence, the 2 subcategories that together compose early nonadherence.
In addition, medication ordering and dispensing are generally recorded in separate, unlinked computer systems, thus limiting access to information required to calculate early nonadherence. Prescription orders have seldom been linked to medication dispensings, and reconciliation of orders and dispensings has been even less frequent. We must better understand the importance of excluding calculations of early nonadherence and the implications this has on interpreting comparative effectiveness data if we are to achieve the full benefits of adherence and comparative effectiveness initiatives.
We hypothesized that population medication adherence estimates calculated from pharmacy databases are inflated as a result of excluding data from patients who fail to obtain initial prescriptions for chronic medications and patients who obtain only a single dispensing of chronic medications. Our specific objective was to estimate the magnitude of misestimation in adherence estimates that resulted from excluding assessment of patients with early nonadherence. To achieve this objective, we linked prescription orders in an ambulatory electronic health record (EHR) to medication dispensings in a pharmacy information system for 3 categories of commonly used oral medication where adherence is directly associated with improved clinical outcomes: antihypertensives, antidiabetics, and/or antihyperlipidemics. We then determined the misestimation of adherence that resulted from not including the early nonadherent patients.
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