Can one or two simple questions predict poor medication adherence?

RATIONALE, AIMS, AND OBJECTIVES: Poor adherence to evidence-based medications is a major problem in conventional clinical practise. Better prognostic tools are needed to identify those with the highest likelihood of being non-adherent. The objective of this study is to determine if a 2-item patient activation status (PAS) measure identifies Medicare beneficiaries at risk of poor adherence to drugs typically recommended in treating type 2 diabetes. METHODS: PAS and medication adherence were assessed for respondents to the 2009 Medicare Current Beneficiary Survey and then compared using bivariate and multivariate tests. Participants' PAS was classified as "active," "high effort," "complacent," or "passive" based on how confident they were in identifying needed medical care and whether they brought medication lists to their doctors' visits. Adherence with oral antidiabetic drugs, angiotensin-converting enzyme-inhibitors/angiotensin receptor blockers, and statins was assessed using proportion of days covered (PDC). RESULTS: A total of 940 Medicare beneficiaries with diabetes enrolled in Part D plans in 2009. The overall effect of PAS on medication adherence was small (3% lower PDC for complacent/passive vs active/high effort beneficiaries, P < 0.10). However, interactions of complacent/passive PAS with other characteristics associated with poor adherence identified certain subgroups as especially prone to problematic adherence: age < 65 (PDC -11%, P < 0.05), non-Hispanic black (PDC -13%, P < 0.05), and morbidly obese (-9%, P < 0.10). CONCLUSION: A single question relating to taking medication lists to doctor visits may help identify patient subgroups prone to poor adherence in conventional practise, but larger samples are necessary to validate and extend these findings.

Does good medication adherence really save payers money?

BACKGROUND: Despite a growing consensus that better adherence with evidence-based medications can save payers money, assertions of cost offsets may be incomplete if they fail to consider additional drug costs and/or are biased by healthy adherer behaviors unobserved in typical medical claims-based analyses. OBJECTIVES: The objective of this study was to determine whether controlling for healthy adherer bias (HAB) materially affected estimated medical cost offsets and additional drug spending associated with higher adherence. SUBJECTS: A total of 1273 Medicare beneficiaries with diabetes enrolled in Part D plans between 2006 and 2009. RESEARCH DESIGN: Using survey and claims data from the Medicare Current Beneficiary Survey, we measured medical and drug costs associated with good and poor adherence (proportion of days covered ≥ 80% and <80%, respectively) to oral antidiabetic drugs, ACE inhibitors/ARBs, and statins over 2 years. To test for HAB, we estimated pairs of regression models, one set containing variables typically controlled for in conventional claims analysis and a second set with survey-based variables selected to capture HAB effects. RESULTS: We found consistent evidence that controlling for HAB reduces estimated savings in medical costs from better adherence, and likewise, reduces estimates of additional adherence-related drug spending. For ACE inhibitors/ARBs we estimate that controlling for HAB reduced adherence-related medical cost offsets from $6389 to $4920 per person (P<0.05). Estimates of additional adherence-related drug costs were 26% and 14% lower in HAB-controlled models (P < 0.05). CONCLUSIONS: These results buttress the economic case for action by health care payers to improve medication adherence among insured persons with chronic disease. However, given the limitations of our research design, further research on larger samples with other disease states is clearly warranted.