David P. Nau

The concordance of self-report with other measures of medication adherence: A summary of the literature

Objective:The objective of this study was to evaluate the concordance of self-report measures of medication adherence (interview, diary, or questionnaire) with nonself-report measures of adherence (administrative claims, pill count or canister weight, plasma drug concentration, electronic monitors, or clinical opinion). Methods:A literature search was conducted to identify published reports in which self-report and nonself-report measures of adherence were used within the same study. The concordance of measures within each study was categorized as high, moderate, or low based on a comparison of the adherence estimates. Results:Eight-six comparisons of self-report to nonself-report measures of adherence were identified. Thirty-seven of the 86 comparisons (43%) were categorized as highly concordant. However, concordance varied substantially by type of self-report measure and nonself-report measure. Self-report measures, in general, were highly concordant with electronic measures in only 17% of comparisons, whereas they were highly concordant with other types of nonself-report measures in 58% of comparisons (chi-square = 14.30, P <0.01). When comparing self-report measures, interviews had significantly lower concordance with nonself-report measures as compared with questionnaires or diaries (chi-square = 8.47, P = 0.01). In 15 comparisons of interviews with electronic measures, none of the comparisons were highly concordant, whereas questionnaires and diaries had moderate-to-high concordance with electronic measures in 12 of 16 comparisons (75%). Conclusions:The concordance of self-report and other measures of medication adherence varies widely based on the type of measures used. Questionnaires and diaries tend to have moderate-to-high concordance with other measures of medication adherence. However, interview-based self-reports are not concordant with electronic measures. Questionnaire and diary methods could be preferable to interviews for self-reported medication adherence.

Adherence to Maintenance-Phase Antidepressant Medication as a Function of Patient Beliefs About Medication

PURPOSE This study aimed to identify the demographic, psychiatric, and attitudinal predictors of treatment adherence during the maintenance phase of antidepressant treatment, ie, after symptoms and regimen are stabilized. METHODS We surveyed 81 primary care patients given maintenance antidepressant medications regarding general adherence, recent missed doses, depression and treatment features, medication beliefs (necessity, concerns, harmfulness, and overprescription), and other variables. Additional data were collected from medical and payer records. RESULTS Median treatment duration was 75 weeks. Adherence and beliefs were broadly dispersed and unrelated to treatment duration and type, physical functioning, and demographics. Multivariate analysis adjusting for social desirability, depression severity, and treatment duration indicated that an antidepressant-specific “necessity-minus-concerns” composite was strongly associated with both adherence outcomes. Specifically, adherence was highest when necessity exceeded concerns and lowest when concerns exceeded necessity. We crossed these 2 dimensions to characterize 4 patient attitudes toward antidepressants: skepticism, indifference, ambivalence, and acceptance. CONCLUSIONS Patients given maintenance antidepressants vary widely in adherence. This variation is primarily explained by the balance between their perceptions of need and harmfulness of antidepressant medication, in that adherence is lowest when perceived harm exceeds perceived need, and highest when perceived need exceeds perceived harm. We speculate on ways to tailor adherence strategies to patient beliefs. Subsequent research should determine whether patients’ perceptions about medication predict depression outcomes, can be used to improve clinical management, and respond to behavioral intervention.

Adherence Analysis Using Visual Analog Scale Versus Claims-Based Estimation

Background: Although visual analog scales (VAS) have been used frequently in outcomes research, there is little evidence regarding the validity of this scale for measuring medication adherence. Objective: To determine whether a VAS self-report measure of medication adherence is concordant with claims-based measurement of adherence. Methods: A mail survey was conducted in 2005 of persons with diabetes. Prescription claims were obtained for the 1985 survey respondents who used oral diabetes medications and lipid-modifying drugs. The self-reported measure of adherence was a VAS scored 0–100%, and the claims-based measure was the continuous measure of medication gaps (CMG), reverse-coded to yield a score of 0–100%. Dichotomous measures (highly adherent vs poorly adherent) were also created from the VAS and CMG using a cutoff value of 80%. For diabetes and lipid-modifying drugs, the scores on the VAS and CMG (continuous versions) were compared using a Pearson correlation coefficient, while the concordance of the dichotomous versions of the measures was compared using the kappa coefficient. Results: The mean ± SD for the VAS and CMG for oral diabetes drugs were 95.9 ± 9.2 and 84.1 ± 19.2, respectively, and for lipid-modifying drugs, 95.2 ± 11.2 and 85.3 ± 20.0, respectively. The VAS-diabetes and CMG-diabetes scales were moderately correlated (r = 0.22), as were the VAS-lipid and CMG-lipid (r = 0.26). The majority (69.0%) of subjects had consistent adherence classifications across the dichotomous versions of VAS-diabetes and CMG-diabetes (kappa = 0.13), while 73.1% of subjects had consistent classifications for the dichotomous VAS-lipid and CMG-lipid (kappa = 0.19). Conclusions: The VAS self-reports of adherence to medications had moderate concordance with estimates derived from drug benefit claims. Although the majority of subjects were consistently classified by the VAS and claims, the concordance may not be sufficient for direct comparisons of studies using VAS data with studies using claims-based estimates

Measuring pharmacy quality

OBJECTIVE To describe methods for measuring health care quality and how these methods can be applied to the measurement of pharmacy quality and to describe ways of stimulating the use of quality improvement methods in pharmacy. SUMMARY The health care system is moving toward value-based purchasing of professional services, which is also known as value-driven health care. Value is often described as the balance between quality and costs, and thus, we can enhance value by improving quality while controlling costs. Although community pharmacies have not experienced the demand for evidence of quality and value, this is likely to change in the near future as the federal government and private purchasers expand their search for quality-related evidence to all sectors of health care. PQA, a pharmacy quality alliance, has been created to coordinate the efforts of numerous pharmacy stakeholders in developing measures of pharmacy quality and in educating pharmacists about quality improvement methods. In addition to educational strategies for stimulating quality improvement, the pharmacy sector is likely to experience regulatory changes that mandate quality improvement, public reports on the quality of individual pharmacies, and pay-for-performance systems that reward pharmacies for achieving higher levels of quality. CONCLUSION All stakeholders in pharmacy (i.e., pharmacists, owners, managers, technicians, benefits managers) must become more aware of the movement toward value-driven health care and the ramifications for pharmacy practice. Community pharmacists will soon see an increased demand for evidence of quality and value as this sector is integrated within the broader framework for value-driven health care.

Pharmacy Quality Alliance: Five Phase I demonstration projects: Descriptions and lessons learned

OBJECTIVES To describe the five Phase I Pharmacy Quality Alliance (PQA) demonstration projects and discuss lessons learned across the projects. DESIGN Descriptive nonexperimental study. SETTING United States from July 2008 to November 2009. PARTICIPANTS Community pharmacies from five states. INTERVENTION Pharmacies viewed their performance scores on a reporting website and provided feedback. MAIN OUTCOMES MEASURES Pharmacy performance scores and pharmacist feedback about the scores and reporting websites. RESULTS Considerable variation was found in the pharmacy performance scores. Some pharmacies did not have enough patients taking medications that were included in specific performance measures. Use of a website to report pharmacy performance was feasible across several different approaches. PQA has developed measures of pharmacy performance that can be used in programs intended to report pharmacy performance. CONCLUSION It is feasible to calculate pharmacy performance scores and create Web-based pharmacy performance reports to provide feedback to community pharmacists. Further development of pharmacy performance reporting should occur.

Evaluating Medication Use for Continuous Quality Improvement in Diabetes Care

Copyright© 2002, Academy of Managed Care Pharmacy. All rights reserved. Author ontinuous quality improvement (CQI) is the structured organizational process for involving personnel in planning and executing a continuous flow of improvements to provide services that meet or exceed expectations. It is integral to the long-term success of managed care organizations (MCOs). Many purchasers of health care, along with accrediting bodies, have encouraged the adoption of the CQI philosophy and its tools. The hope is that CQI will lead to more efficient care as well as better health for members enrolled in health plans. The value of CQI is generally accepted, and consistent with the philosophy of CQI, the methods for measuring quality are undergoing constant evolution. The most common method for evaluating the quality of MCOs is the Health Plan Employer Data and Information Set (HEDIS) from the National Committee for Quality Assurance (NCQA). HEDIS includes performance indicators related to health promotion and the effectiveness of care for selected diseases. These performance indicators offer insight to the quality of care provided by MCOs. The number of performance indicators within HEDIS has expanded over the past several years, and the technical specifications for the indicators have been refined. Reported results and trends in the performance indicators over the past several years suggest that NCQA has been successful in stimulating quality improvement in MCOs Nonetheless, HEDIS does have limitations. Kerr and colleagues have pointed out several pitfalls in the use of HEDIS for quality improvement. These pitfalls include the lack of a strong link between many process-oriented measures and outcomes, intermediate outcomes-oriented measures that are not linked to actionable processes, measures that do not target those at highest-risk, the lack of severity adjustment for outcomes measures, and the inability of the measurement system to allow for patient exceptions. These pitfalls in the measurement system limit the utility of HEDIS for quality improvement efforts. Ideally, the current indicators in HEDIS would be supplemented by additional measures of quality that help to pinpoint specific health care processes that need improvement. Evaluating Medication Use for Continuous Quality Improvement in Diabetes Care

Development of the Consumer Assessment of Pharmacy Services survey

OBJECTIVES To develop and test a tool for obtaining patient evaluations of the quality of pharmacy services provided in ambulatory settings. DESIGN Descriptive, exploratory, nonexperimental study. SETTING United States from June 1, 2006, through May 31, 2007. PARTICIPANTS 895 individuals who obtained prescription medications from participating pharmacies. INTERVENTION Items were evaluated for inclusion in composite scales based on factor analysis and frequency of missing data. Standard psychometric methods were used to assess the reliability and construct validity of the resulting three composite and three global-item measures. MAIN OUTCOME MEASURE Patient assessment of the quality of ambulatory care pharmacy services. RESULTS Confirmatory factor analysis indicated that a subset of 15 items measuring three aspects of pharmacy services (General Staff Communication, Health- and Medication-Focused Communication, and Clarity of Written Information about Medications) provided excellent fit to the data. Cronbachs alphas for these scales were greater than 0.80. The three scales and corresponding three global ratings of quality reliably described differences among providers of pharmacy services. CONCLUSION These data provide support for the reliability and validity of the Consumer Assessment of Pharmacy Services survey. Although preliminary results regarding reliability and validity are promising, further study of the survey is warranted.

Impact of Environmental Factors on Differences in Quality of Medication Use: An Insight for the Medicare Star Rating System.

BACKGROUND The Medicare star ratings system incentivizes health plan sponsors based on their performance across a measurement system that contains quality measures related to medication use. As health plan sponsors seek to further engage their network providers, specifically network pharmacies, to improve performance on these measures, it is important to consider the effect of environmental factors on the performance of network pharmacies. OBJECTIVE To determine the effect of environmental factors on pharmacy quality as measured by (a) medication adherence for noninsulin diabetes medications, (b) medication adherence for renin angiotensin receptor antagonists (RASA), (c) medication adherence for cholesterol medications (statins), and (d) use of high-risk medications (HRM) in the elderly. METHODS The EQuIPP database, which contains performance information for pharmacies for a nationwide sample of Medicare beneficiaries, was used for this analysis. Environmental factors included regions or characteristics of a community or county. County-level data was obtained from the Area Health Resource Files, a resource product available from the Health Resources & Service Administration. A logistic regression model was developed with performance as the dependent variable and regions and environmental factors as independent variables. Performance and county characteristics, such as proportion of patients in an age group, race, income, or number of outpatient visits, were classified as high and low based on a median cutoff of nationwide performance scores. RESULTS A total of 28,950 pharmacies were included in this analysis. For most measures, the proportion of low-performing pharmacies was significantly higher in the East South Central, Mid-Atlantic, Mountain, Pacific, and West South Central regions. Pharmacies in counties with high median income, high proportion of elderly population (aged > 84 years), high proportion of elderly patients who were white or Hispanic, high proportion of elderly males, and high proportion of elderly urban patients were less likely to have low performance, whereas those with high proportion of elderly African Americans and high density of independent pharmacies were more likely to have low performance (P < 0.05-0.0001). CONCLUSIONS This study found that environmental characteristics of a region, including pharmacy and sociodemographic characteristics, explained regional variation in quality measures related to medication use for patient populations served by pharmacies. This evaluation serves to further inform the discussion regarding case-mix adjustment of quality measures and provides information that may be important to further refine intervention strategies for pharmacies and pharmacists who serve certain regional populations. Additionally, pharmacies in greatest need of support for quality improvement may be those who serve populations that are predominantly low income and elderly African American. DISCLOSURES Desais postdoctoral fellowship was funded by Pharmacy Quality Solutions for conducting this study and writing the manuscript. Nau and Conklin are employed by Pharmacy Quality Solutions. An earlier version of this research was presented as a poster at the Annual Meeting of the Academy of Managed Care Pharmacy; San Diego, CA; April 7-10, 2015. Study concept and design were contributed by Conklin, Nau, Desai, and Heaton. Desai and Conklin took the lead in data collection, assisted by Nau and Heaton. The manuscript was primarily written by Desai and Heaton, with assistance from Conklin and Nau. All authors contributed to data interpretation and manuscript revision.

The Relationship of Diabetes Mellitus Performance Indicators with Self-Reported Health and Patient Satisfaction

AbstractIntroduction: Disease management programs often strive to enhance patient outcomes through improvements in the process of care. The purpose of this study was to determine the relationship of diabetes care process measures with self-rated health and patient satisfaction among managed care patients with diabetes mellitus, while controlling for the influence of demographics, co-morbidities and severity of illness. Study design and methods: This study was an integrated analysis of cross-sectional survey and retrospective claims data. The sample included 300 adult patients with diabetes mellitus enrolled in an Independent Practice Association—model health maintenance organization. Analyses consisted of two multiple regression models with self-rated health (100-point scale, higher score = better health) and patient satisfaction (9-point scale, higher score = greater satisfaction) being the dependent variables, respectively. Predictor variables in both models included: demographics (age, gender, education, income), severity of illness (insulin use, duration of diabetes mellitus), number of co-morbidities, receipt of foot and eye exams, diabetes mellitus education, lipid tests, microalbumin tests, frequency of self-monitoring of blood glucose and the frequency of tests for glycosylated hemoglobin (HbA1c) and blood glucose. Results: Mean (SD) for self-rated health and patient satisfaction scores were 49.8 (25.0) and 7.8 (1.8), respectively. The squared multiple regression coefficients (R2) for model 1 (self-rated health) and model 2 (patient satisfaction) were 0.20 and 0.10, respectively. Significant predictors of self-rated health included co-morbidities (standardized regression coefficient [β] = −0.12), income (β = 0.27), and HbA1c tests (β = 0.19). Significant predictors of patient satisfaction included co-morbidities (β = −0.16), foot exams (β = 0.16), and diabetes mellitus education (β = 0.16). Conclusion: When controlling for demographics, co-morbidities and severity of illness, those patients who received more frequent HbA1c monitoring reported better health, and patients who received foot exams and diabetes education were more satisfied with the care they received for diabetes mellitus. Thus, disease management initiatives that optimize the education and monitoring of patients with diabetes mellitus are likely to produce better patient-reported outcomes.

PDB26 CAN PATIENTS ACCURATELY RATE THEIR ADHERENCE TO MEDICATIONS

was performed. Cronbach’s alpha coefficients and Pearson’s product moment correlations were calculated to estimate reliability. To establish construct validity, correlation coefficients were calculated between the subscales and vitality, well-being, treatment satisfaction, and/or baseline glycosylated hemoglobin (HbA1c). Standard errors of measurement (SEMs) were calculated to estimate minimal important difference. RESULTS: In both studies: 1) factor analysis confirmed the factor structure of the four subscales with the exception that the “sleepiness or drowsiness” item loaded with the Fatigue subscale items rather than the Cognitive Distress items; 2) test-retest reliability (all >0.68) and Cronbach’s alpha coefficients (all >0.79) were acceptable; 3) associations between subscales and other patientreported outcomes measures and/or HbA1c were significant (p < 0.05) and in the hypothesized directions; and 4) SEMs were approximately 0.5 on a 1 to 5 scale. CONCLUSION: Preliminary validation indicates that the Cognitive Distress, Fatigue, Hyperglycemia, and Hypoglycemia subscales are potentially reliable and valid individual measures for use in clinical trials evaluating antihyperglycemic medications in patients with type 1 or type 2 diabetes.