Accepting Medication Therapy Management Recommendations to Add ACEIs or ARBs in Diabetes Care

BACKGROUND: National guidelines and initiatives have promoted the use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) for patients with diabetes. The University of Arizona Medication Management Center (UA-MMC) is contracted by Medicare health plans, pharmacy benefit managers (PBMs), and multiple commercial health insurance plans to provide medication therapy management (MTM) services for plan members. As part of the MTM program, recommendations have been made for those patients who may benefit from the addition of an ACEI/ARB. Although the intervention benefits and guidelines for using ACEIs/ARBs are clear, real-world evidence is needed to understand and potentially increase uptake of guideline interventions among eligible patients. OBJECTIVES: To (a) identify patient characteristics that predict acceptance of guideline recommendations to add ACEI/ARB medications to diabetic treatment via MTM services and (b) examine how well different case characteristics (i.e., patient age and sex, type and number of recommendation attempts, type of health care plan) predict the odds of adding ACEI/ARB medications to diabetic regimens when recommended through an MTM call center. METHODS: This was a retrospective analysis of secondary data provided by the UA-MMC. The de-identified national data included adult plan members with diabetes who the UA-MMC recommended adding an ACEI/ARB prescription based on 2012 national guidelines. The UA-MMC made recommendations by either patient letters, patient phone calls, physician faxes, or any combination thereof. We conducted a binary logistic regression analysis to assess the impact of case characteristics on the likelihood of accepting recommendations to add ACEI/ARB medications. The outcome variable was recommendation acceptance (yes/no), defined as new prescription claims for an ACEI/ARB within 120 days following the recommendation. Five predictor variables were assessed: (1) patient’s age quartile; (2) method of communicating recommendations (letter, phone call, fax, or some combination thereof); (3) whether recommendations were made once or twice on separate dates; (4) patient’s sex; and (5) type of health care plan. RESULTS: Recommendations were made for 31,495 members of health plans or PBMs that contracted with the UA-MMC. Patients’ ages ranged from 19-90 (Mean =72.01; SD =10.21), with females comprising 56% of the sample. The recommendation to add ACEI/ARB medications was accepted for 14.5% (4,559) of patients. In most cases (73%), recommendations occurred via a letter to patients together with a fax to their providers. The fitted model, containing 3 predictor variables (age quartile, type of contact to communicate the recommendations, and whether recommendation contacts were made twice), was statistically significant, χ(2) (10; N = 31,495) = 112.82 (P < 0.001), indicating that the model was able to distinguish between those who did and did not accept UA-MMC’s recommendations to add ACEI/ARB medications. The likelihood of recommendation acceptance decreased as patient age increased compared with patients in the first age quartile (ages 19-67; P ≤ 0.005 at all levels). Compared with sending only a provider fax, patients who received all 3 types of contact (provider fax with patient phone call and letter) were estimated to be 1.34 times more likely (34% increase) to have recommendation acceptance ( P = 0.004; 95% CI = 1.10-1.63). Similarly, patients who received only letters were also 1.32 times more likely (32% increase) than provider faxes alone to result in recommendation acceptance ( P = 0.003; 95% CI = 1.10-1.59). Patients for whom recommendations were made twice were less likely to have recommendation acceptance than for those contacted once, controlling for all other predictor variables in the model ( P < 0.001; OR = 0.77; 95% CI = 0.69-0.86). CONCLUSIONS: Recommendations to add an ACEI/ARB to diabetic regimens are more likely to be accepted for younger patients and those who receive recommendations through all 3 communication types (provider fax combined with patient phone call and letter) or just letters than provider faxes alone. Further research is needed to understand why prescribers are not accepting MTM recommendations.