A Motivational Interviewing Intervention to Improve Adherence to ACEIs/ARBs among Nonadherent Older Adults with Comorbid Hypertension and Diabetes.

BACKGROUND: Hypertension and diabetes mellitus are independent risk factors for cardiovascular diseases. Due to the cardioprotective nature of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs), they are recommended for patients with comorbid hypertension and diabetes. However, poor adherence to ACEIs/ARBs among older adults is a major public health concern. This study aimed to assess the effectiveness of a telephonic motivational interviewing (MI) intervention conducted by pharmacy students among a nonadherent older population (≥ 65 years old) with diabetes and hypertension. METHODS: Patients continuously enrolled in a Medicare Advantage Plan who received an ACEI/ARB prescription between July 2017 and December 2017 were identified. Group-based trajectory modeling (GBTM) was used to identify distinct patterns of ACEI/ARB adherence during the 1-year baseline period: adherent, gaps in adherence, gradual decline, and rapid decline in adherence. Patients from the three nonadherent trajectories were randomized into MI intervention or control group. The intervention consisted of an initial call and five follow-up calls administered by MI-trained pharmacy students and tailored to the baseline ACEI/ARB adherence trajectories. The primary outcome was adherence to ACEI/ARB during the 6- and 12-month periods post-MI implementation. The secondary outcome was discontinuation, defined as no refills for ACEI/ARB during the 6- and 12-month periods post-MI implementation. Multivariable regression analyses examined the impact of MI intervention on ACEI/ARB adherence and discontinuation while adjusting for baseline covariates. RESULTS: A total of 240 patients in the intervention group and 480 patients as randomly selected controls were included in this study. At 6 months, patients receiving the MI intervention had significantly better adherence (ß = 0.06; p = 0.03) compared with the controls. Linear and logistic regression models also showed patients in the intervention group were more likely to be adherent than controls within 12 months of intervention implementation (ß = 0.06; p = 0.02 and OR: 1.46; 95% CI 1.05-2.04, respectively). MI intervention did not have any significant impact on the ACEI/ARB discontinuation. CONCLUSION: Patients who received the MI intervention were more likely to be adherent at 6 and 12 months following the intervention initiation, despite gaps in the follow-up calls due to COVID-19. Pharmacist-led MI intervention is an effective behavioral strategy to improve medication adherence among older adults and tailoring the intervention to past adherence patterns may enhance the intervention effectiveness. This study was registered with the United States National Institutes of Health (ClinicalTrials.gov identifier NCT03985098).

[Assessment of pain in patients with rheumatic disease under biological therapy treatment].

BACKGROUND: To assess pain in patients with rheumatic disease under biological therapy treatment. METHODS: Observational retrospective study of patients with rheumatic disease under biological therapy treatment who visited the health care center as outpatients in February/August 2020. We collected demographic (sex and age), clinical (diagnosis, pain presence, intensity, and location), and pharmacological (biological therapy, concomitant treatment with traditional DMARDs, and analgesic treatment) variables from the electronic medical records and Farmatools Dominion®. RESULTS: We included 138 patients; mean age was 56 years and 71% were female. The most frequent diagnosis (47%) was ankylosing spondylitis. Anti-TNF-a was the most prescribed biological drug (64%); 60.1% of study patients received traditional drugs, particularly methotrexate and leflunomide (51.8 and 28.9%, respectively). Pain was reported in 81% of the cases, particularly in hands (73.2%) and knees (69.6%); mean pain intensity was 6.5 (VAS). Although 83.3% of the patients had been prescribed analgesics, pain persisted in 84.8% of the cases (VAS >4), being severe or very severe in 67.9%. Over half of the patients (52.2%) used more than one analgesic. The most frequently prescribed medications were non-steroidal anti-inflammatory drugs (NSAIDs) (60%), paracetamol (52.2%), and opioids (56.5%). NSAIDs controlled pain (14.5%) better than opioids (8.3%); there was no post-treatment improvement of pain in 29.6% of the patients. The number of prescribed drugs increased with pain intensity (rho= 0.264; p= 0.006). CONCLUSION: Almost 70% of study patients had uncontrolled severe rheumatic-related pain. This implies a challenge for esta­blishing effective treatments for this type of pain.

Evaluating trajectories of statin adherence after a motivational interviewing intervention.

OBJECTIVE: The objective of the current study was to compare postintervention adherence trajectories with preintervention trajectories for those receiving a telephonic motivational interviewing (MoI) intervention to determine predictors associated with each distinct postintervention trajectory and any association between pre- and postintervention trajectories. DESIGN: Retrospective study design using group-based trajectory modeling. SETTINGS AND PARTICIPANTS: A telephonic MoI intervention was conducted by trained student pharmacists to improve statin adherence in a Medicare Advantage plan. Four preintervention adherence trajectories were previously identified: rapid decline (RD), gradual decline (GD), gaps in adherence (GA), and adherent and were used to customize the MoI intervention. Patients from the 3 nonadherent preintervention trajectories were randomized to control or intervention groups and were followed for 6 months from the date of MoI intervention. OUTCOME MEASURES: Group-based trajectory modeling was performed to identify 3 relevant postintervention trajectories. Descriptive statistics were used to assess differences in pre- and postintervention adherence trajectories. Multinomial logistic regression was conducted to determine predictors associated with each identified postintervention trajectory. RESULTS: There were 152 intervention patients and 304 randomly selected controls. The prominent postintervention trajectories that were identified differed from the preintervention trajectories and were (1) GD (17.2%), (2) adherent (61.9%), and (3) discontinuation (20.9%). Among the intervention group, more patients in the GA preintervention trajectory (58.65%) moved to the adherent trajectory postintervention than those in the RD and GD preintervention trajectories. Furthermore, the predictors associated with the postintervention trajectories included MoI intervention, prescriber specialty, presence of diabetes, presence of congestive heart failure, Centers for Medicare & Medicaid Services risk score, and preintervention trajectories. CONCLUSION: The postintervention adherence trajectory patterns differed from the preintervention trajectory patterns with many patients moving into an adherent trajectory especially among those receiving the intervention.

Evaluating Success Factors of a Medication Adherence Tracker Pilot Program in Improving Part D Medication Adherence Metrics in a Medicare Advantage Plan: Importance of Provider Engagement.

BACKGROUND: Health plans and providers can increase quality by improving adherence to chronic disease medications included in star ratings among Medicare Advantage Part D (MAPD) plan enrollees. Research is needed to evaluate effective means of collaboration between health plans and providers. The Medication Adherence Tracker (MAT) is a health plan initiative to help primary care providers use outreach to improve their patients' adherence. OBJECTIVE: To quantify the contribution of structural and process factors on the success of a health plan-initiated tracking system in improving chronic disease medication adherence over 6 months. METHODS: The MAT quality improvement initiative was carried out in South Texas from June to December 2016. Health plan pharmacists used claims data to identify MAPD enrollees at risk of nonadherence to triple-weighted star medications: renin-angiotensin system antagonists, oral diabetes medications, and statins. Actionable reports were delivered biweekly to each provider, either by fax or in person, by embedded health plan nurses. Multivariable regression was used to evaluate sociodemographic and clinical factors as well as the role of provider outreach in increasing paid pharmacy claims and medication adherence as measured by proportion of days covered (PDC) > 0.8. RESULTS: Of 3,542 patients in 5 Texas physician-organized delivery system groups whose 67 providers received tracking reports from June through December 2016, 1,901 (54%) patients had more than 1 related prescription, and 3,064 (87%) received provider outreach on at least 1 prescription. 2,493 (70%) had at least 1 paid pharmacy claim. Provider outreach was associated with greater likelihood of paid prescription claims (relative risk [RR] = 4.59, 95% CI = 3.74-5.62) and greater year-end adherence (PDC > 0.8, RR = 1.86, 95% CI = 1.63-2.12) in multivariable predictive models. 95% CIs for age, gender, low-income subsidy eligibility, and number of prescriptions did not exclude the null value. CONCLUSIONS: Provider engagement is critical to effective health plan-provider partnerships to overcome barriers, change behavior, and improve chronic disease care quality and population outcomes. DISCLOSURES: This study was funded by Cigna. The manuscript was prepared as a work for hire. Hong, Esse, Gallardo, Serna, Fosshat, and Mamvou are employees of CareAllies, a Cigna company. Bruce was employed by Cigna at the time of the study. Vadhariya reports a past internship at Regeneron Pharmaceuticals, unrelated to this work. Abughosh reports grants from Regeneron Pharmaceuticals, Valeant Pharmaceuticals, Sanofi, and BMS/Pfizer, unrelated to this work.

Enhancing Statin Adherence Using a Motivational Interviewing Intervention and Past Adherence Trajectories in Patients with Suboptimal Adherence.

BACKGROUND: Statins have been shown to be effective in reducing the occurrence of cardiovascular (CV) events and are widely prescribed for the risk reduction of CV diseases and recurrent CV events. However, poor adherence prevents some patients from receiving the maximum benefit of the therapy. Motivational interviewing (MoI) is a patient-centered collaborative approach that can be used to improve medication adherence. Group-based trajectory modeling depicts patterns of adherence over time and may help tailor the MoI intervention to further enhance adherence. OBJECTIVE: To assess the effect of a phone-based MoI intervention tailored by patients' past adherence trajectory in improving adherence to statins among patients in a Medicare Advantage prescription drug plan (MAPD). METHODS: Patients continuously enrolled in an MAPD from 2013 to 2017 with a statin prescription between January and June 2015 to allow 2 years of pre-index period and 1 year of follow-up were included in the study. Adherence to statins was measured monthly during the 1-year follow-up as proportion of days covered (PDC) and incorporated into a group-based trajectory model to provide 4 distinct patterns of adherence: adherent, rapid decline, gradual decline, and gaps in adherence. Patients in the 3 nonadherent groups were randomized to either control or intervention. The intervention was an initial counseling call and up to 2 monthly follow-up calls by pharmacy students trained in MoI, providing education consistent with a previously identified pattern of use. Refill data at 6 months post-intervention were evaluated to examine the intervention's effect on PDC, as continuous and dichotomized as PDC ≥ 0.8, as well as discontinuation. Multivariable regression adjusted for baseline demographics, clinical characteristics, and past adherence trajectory. RESULTS: There were 152 patients included in the analysis who received MoI phone calls and 304 randomly selected controls. Mean PDC for the intervention group (0.67 ± 0.3) was significantly higher than the control (0.55 ± 0.4; P < 0.001). The intervention group was also less likely to discontinue (OR = 0.38; 95% CI = 0.19-0.76) and more likely to be adherent in the linear regression model (ß = 12.4; P < 0.001) as well as in the logistic regression model (OR = 1.87; 95% CI = 1.18-2.95). Previous adherence trajectories were significantly associated with adherence in the follow-up. CONCLUSIONS: Patients who received the MoI intervention were more likely to be adherent and less likely to discontinue the statin in the 6 months follow-up compared with controls. Future research can identify other approaches to tailor interventions and expand the intervention to other languages. This intervention may also prove valuable to improve adherence to other medications for chronic and asymptomatic diseases. DISCLOSURES: This study was funded by Regeneron Pharmaceuticals, which provided critical input during study design, implementation, and manuscript preparation. Abughosh reports grants from Sanofi, BMS/Pfizer, and Valeant Pharmaceuticals, unrelated to this study. Vadhariya reports a past internship at Regeneron Pharmaceuticals, unrelated to this study. Esse, Serna, and Gallardo are employees of CareAllies, a Cigna subsidiary. Boklage is an employee of Regeneron Pharmaceuticals. Choi was an employee of Sanofi during this study. Johnson, Essien, Fleming, and Holstad have nothing to disclose. A poster based on this study was presented at AMCP Nexus 2018; October 22-25, 2018; Orlando, FL.