Patient-reported barriers to statin adherence: Excerpts from a motivational interviewing intervention in older adults.

OBJECTIVE: Despite a known benefit in the reduction of cardiovascular risk, adherence to statins remains suboptimal. A qualitative analysis was conducted within an intervention that identified trajectories of statin adherence in patients and used motivational interviewing (MoI) to improve adherence. The objective of this qualitative study was to evaluate transcripts of an MoI telephonic intervention to identify potential, past, and current barriers to statin adherence and barriers specific to distinct adherence trajectories. METHODS: The MoI intervention was customized by past 1-year adherence trajectories (rapid discontinuation, gradual decline, and gaps in adherence). Two authors independently extracted and documented barriers from phone transcripts. Themes were derived from literature a priori and by cataloging recurring themes from the transcripts. RESULTS: The transcripts of calls made to 157 patients were reviewed of which 25.2% did not communicate a specific adherence barrier despite falling into a low-adherence trajectory when examining refill data. The most commonly reported barriers to statin adherence included adverse effects (40.1%), forgetfulness (30.0%), and lack of skills or knowledge pertaining to statins (25%). More patients in the rapid discontinuation group perceived medication as unnecessary, whereas more patients in the gaps in adherence group reported a communication barrier with their health care provider. Several barriers among patients who fell into low-adherence trajectories were reported. Some patients did not report any barriers, which may have indicated denial. MoI phone calls were useful in providing knowledge, clarifying medication regimens, and reinforcing the need to take statins. CONCLUSION: This study identified patient-reported barriers to statin adherence elicited during an MoI telephonic intervention conducted by student pharmacists. There were differences in barriers reported by patients from each trajectory, which emphasize the need for additional tailored interventions to improve patient adherence.

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.

Impact of a motivational interviewing intervention targeting statins on adherence to concurrent hypertension or diabetes medications.

OBJECTIVE: This study explored if a motivational interviewing intervention customized for statins impacted adherence to concomitantly used antidiabetic/antihypertensive medications. METHODS: The intervention was conducted among patients with a history of suboptimal adherence to statins and included 152 patients in intervention and 304 controls. This retrospective study design identified patients with claims for statins and either antidiabetic/antihypertensive medications. The outcome variable was adherence, measured as proportion of days covered ≥ 0.80, to antidiabetic/antihypertensive medications. Multivariable linear and logistic regression evaluated the effect of intervention on adherence to antidiabetic/antihypertensive medications during the 6 months post-intervention. RESULTS: The antidiabetic group had 53 intervention patients and 102 controls. The antihypertensive group had 80 intervention patients and 159 controls. There was no significant improvement in adherence for antidiabetic/antihypertensive medications following the intervention. Adherence at baseline was a significant predictor of adherence post-intervention in the antidiabetic (OR = 6.5;P < 0.0001) and antihypertensive (OR = 4.1; P = 0.0001 & ß = 0.09; P = 0.008) users. Physician specialty (OR = 3.902; P = 0.01& ß = 0.09; P = 0.015) among antidiabetic users and age >70 years (OR = 2.148; P = 0.025) among antihypertensive users were predictors of adherence. CONCLUSION: The intervention targeting statin did not significantly improve antihypertensive/antidiabetic adherence. PRACTICE IMPLICATIONS: Targeted interventions tailored to patient past adherence and specific medications should be explored.

Evaluating perceptions of social determinants of health and Part D star performance of Medicare Advantage-contracted primary care providers serving a South Texas market.

BACKGROUND: Socioeconomic factors can have a significant impact on a patient's health status and could be responsible for as much as 70%-80% of a patient's overall health. These factors, called the social determinants of health (SDoH), define a patient's day-to-day experiences. While the influence of such factors is well recognized, who ultimately is responsible for addressing SDoH in health care remains unclear. Physicians and other clinicians are suitably placed to assess SDoH factors that can impact clinical decision making. Understanding Medicare Advantage (MA)-contracted primary care provider (PCP) SDoH perceptions has yet to be fully explored. OBJECTIVES: To (a) understand MA-contracted PCP perceptions of SDoH and (b) investigate correlations between PCP perceptions and their CMS Part D star performances, as well as their hospital admissions and emergency room admissions. METHODS: Survey data were collected from MA-contracted PCPs serving a South Texas market during 2019. An 8-item survey consisting of short answer, ranking, and multiple-choice questions was deployed at attendance-mandatory provider meetings from August to October. Analyses were conducted to understand the providers' SDoH perceptions. PCP responses were first summarized as frequencies and percentages. Baseline descriptive characteristics of the providers were compared by Medicare star ratings using chi-square tests (for categorical variables) and t-tests (for continuous variables). Group differences in physician beliefs on how SDoH affects patients' overall health (question 1), as well as provider beliefs regarding how SDoH affects patients' medication adherence practices (question 2), were assessed using chi-square and t-tests. Associations of provider SDoH perceptions with hospital admissions and emergency room admissions were also assessed. A Fischer's chi-square test was used to examine associations between how PCPs answered the question regarding lack of consistent transportation (question 3) and emergency room admissions. The relationships between PCP perceptions of whose job it is to address SDoH (question 7) and hospital admissions were also evaluated. RESULTS: The response rate for returned surveys was 89%. Analysis revealed that the top 3 barriers were financial insecurity (24.87%), low health literacy (18.65%), and social isolation (15.03%). However, about 36% of PCPs felt they should be the primary addressor of SDoH. There was a significant association between years of practice and CMS Part D star ratings (P = 0.005). A significant association between responses in belief towards patients' overall health and CMS Part D star ratings was examined (P = 0.047). There was a statistically significant difference in mean hospital admissions with PCP perception of who should address SDOH (P = 0.03). Emergency room admissions was significantly associated with perceptions regarding lack of consistent transportation (P = 0.04). No differences with star ratings were observed. CONCLUSIONS: Previous literature recognize safety and food insecurity as key SDoH barriers. However, they were not among the top SDoH barriers in our survey. Future research should examine patient perceptions of SDoH in this population to identify ways providers can better serve their patients. DISCLOSURES: Funding for this study was provided by CareAllies, a Cigna business. Statistical analysis was completed in partnership with the University of Houston. Payne, Esse, Qian, Serna, Villarreal, and Becho-Dominguez are employees of CareAllies. Mohan and Abughosh are employed by the University of Houston College of Pharmacy. Abughosh reports grants from Valeant and Regeneron/Sanofi, unrelated to this work. Vadhariya has nothing to disclose. This research was presented virtually at the AMCP Pharmacist Virtual Learning Days event, April 2020, as well as the American College of Clinical Pharmacy Virtual Poster Symposium, May 26-27, 2020.

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.

Examination of physicians' adherence to the 2013 ACC/AHA statin/cholesterol guidelines using a framework of awareness to adherence: A cross-sectional study.

BACKGROUND: Currently, limited data exists regarding primary care physicians' awareness and implementation of the 2013 cholesterol guidelines. OBJECTIVES: To evaluate primary care physicians' adherence to the 2013 ACC/AHA cholesterol management guidelines using the framework of the awareness-to-adherence model. METHODS: The study was a cross-sectional pre-post survey design based on the constructs of the awareness-to-adherence model to capture physicians' awareness of, agreement with, adoption of, and adherence to the 2013 ACC/AHA guidelines for cholesterol treatment and statin and cholesterol management software applications. Physicians with a Medicare Advantage organization in Texas were surveyed before and after educational interventions. RESULTS: A total of 170 responses were considered usable (post-survey). A significant difference was observed when physicians were divided into 2 groups (any intervention vs no intervention) (P = .027). Physicians with a higher level of agreement were 4.8 times more likely to be adherent to the guidelines (P = .011), compared with those with a lower level of agreement. Also, physicians practicing in the Rio Grande Valley area were 4.7 times more likely to be adherent to the guidelines (P = .001) compared with those from the Greater Houston area. CONCLUSION: A high level of awareness, but a lower level of adherence to the guidelines was reported among responding physicians. The awareness-to-adherence model was useful in examining physicians' level of adherence to the cholesterol guidelines and the utilization of statin and cholesterol management cellular apps and online websites. Future studies are required to examine physicians' adoption and adherence of new guidelines.

Effectiveness of mailed letters to improve medication adherence among Medicare Advantage Plan participants with chronic conditions.

BACKGROUND: Medication adherence is associated with improved health outcomes in multiple chronic diseases. Information is needed on the effectiveness of specific adherence interventions. This study's objectives were to quantify effects of a targeted mailing intervention on adherence among older adults at risk for nonadherence, and to examine associations of individual and plan characteristics with adherence. MATERIALS AND METHODS: Among adults enrolled in a Medicare Advantage Plan with prescription drug coverage from May 2014 to June 2015, those identified as eligible for the mailing intervention had a late refill for oral antidiabetic medication, statin, angiotensin-converting enzyme inhibitor, or angiotensin receptor blocker medication and were previously unreachable by telephone. Pharmacy claims data were analyzed with the outcome of 6-month proportion of days covered (PDC) before and after the mailing. The t-test and chi-square analyses were used to evaluate univariate associations. Multivariable linear and logistic regression models were conducted to assess relative covariate effects. A sub-analysis of those with at least one medication fill post-mailing was also performed. RESULTS: A total of 460 non-adherent individuals aged 70±10.5 years, with 50.2% female and 66.7% white individuals, were included. Of those who were mailed a letter, 24.1% became adherent to the specified maintenance medication. Those who received >30-day supplies were more than twice as likely to become adherent after the mailed letter than those who received 30-day supplies or less (P<0.05). Baseline higher PDC was also associated with greater adherence post-mailing (P<0.01). A total of 284 (61.7%) individuals filled their medication at least once after the mailed letter; of those, 39.1% became adherent (mean [SD] change in PDC =0.15 [±0.28]). CONCLUSION: Our findings suggest that a single mailed letter improved medication adherence by 24.1% in adults with chronic conditions. As a health plan seeking to improve its customers' well-being and outcomes, Cigna continues to utilize targeted mail interventions to improve medication adherence.

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.

Group-Based Trajectory Models to Identify Sociodemographic and Clinical Predictors of Adherence Patterns to Statin Therapy Among Older Adults.

BACKGROUND: The benefits of statins in the prevention of primary and secondary atherosclerotic cardiovascular (CV) disease events have been well documented. Suboptimal adherence is a persistent problem associated with increased CV events and increased healthcare utilization. Proportion of days covered (PDC) is widely used to measure medication adherence, and provides a single value that does not adequately depict different adherence behavior patterns. Group-based trajectory modeling has been used to identify adherence patterns (or trajectories) over time. The identification of characteristics unique to each pattern can help in the early identification of patients who are likely to be poor adherents and can inform the development of interventions. OBJECTIVES: To identify distinct trajectories of statin adherence in patients enrolled in a Medicare Advantage plan and the sociodemographic and clinical predictors associated with each trajectory. METHODS: Patients were included in the study if they were continuously enrolled in a Medicare Advantage plan between 2013 and 2016 and had a statin prescription between January 2015 and June 2015. We observed each patient for 360 days and computed the monthly PDC. The monthly PDC was incorporated into a group-based trajectory model to provide distinct patterns of adherence. Using group-based trajectory modeling, the patients were categorized into groups based on their adherence patterns. Multinomial logistic regression was performed to identify the sociodemographic and clinical factors associated with each group. RESULTS: A total of 7850 patients were included in the analysis and were categorized into 4 distinct groups based on statin adherence-rapid discontinuation (7.8%), gradual decline (16.8%), gaps in adherence (17.2%), and high or nearly perfect adherence (58.2%). Significant predictors of being placed into one or more of the low-adherence trajectories compared with the high-adherence trajectory included sex, age, low-income subsidy, language, Charlson Comorbidity Index score, statin intensity, and 90-day refills. CONCLUSIONS: The predictors identified in this study provide valuable insight into patient characteristics that increase the risk for statin nonadherence, which has the potential to inform targeted interventions. Identifying patient trajectories can inform the future development of protocols to individualize appropriate interventions for these patients.

A Motivational Interviewing Intervention by Pharmacy Students to Improve Medication Adherence.

BACKGROUND: Diabetes mellitus (DM) patients with comorbid hypertension (HTN) are at a higher risk of developing microvascular and macrovascular DM complications. Through guideline-driven recommendations, angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) are highly recommended for these patients. Unfortunately, medication adherence to these products, though crucial to achieving therapeutic benefit, is frequently suboptimal. Motivational interviewing (MI) is a patient-centered collaborative communication style that is used to strengthen internal motivation for change that may prove effective in enhancing adherence. OBJECTIVE: To examine the effect of an MI telephone intervention conducted by pharmacy students in improving adherence to ACEIs/ARBs among Medicare Advantage Plan (MAP) patients with both DM and HTN. METHODS: A prospective study was conducted among patients enrolled in a Texas MAP. Medical claims data were used to identify patients with DM and HTN, and pharmacy claims were observed to recognize those who filled either an ACEI or an ARB during June 2014. Patients with a 6-month proportion of days covered (PDC) < 0.80 in the previous 6 months were determined nonadherent, and 75% of those were randomly selected to serve as potential subjects for the intervention, while 25% were randomly selected to serve as potential subjects for the control group. The intervention was a telephone call by a pharmacy student on rotation at the health plan, and 5 monthly follow-up calls. Before implementing calls, participating students attended a 3-day MI training course, where their proficiency for MI skills was evaluated. Refill data during the 6-month postintervention were evaluated to examine the intervention effect measured on 3 outcomes: PDC; PDC ≥ 0.80 versus < 0.80; and discontinuation versus continuation. Multivariate linear and logistic regression models were constructed to adjust for any imbalances in baseline characteristics, including age, gender, number of other medications, regimen complexity, health low-income subsidy status, prescriber specialty, comorbidities, 6-month previous hospitalization, baseline 6-month PDC, and Centers for Medicare & Medicaid Services risk score. RESULTS: A total of 11 students participated in the intervention implementation. Patients receiving calls were randomly selected from those potential subjects for the intervention arm until a target of 250 was reached; 500 controls were randomly selected from the potential subjects for the control arm. The final cohort included in multivariate models consisted of 743 patients. Patients completing the initial call and at least 2 follow-ups were less likely to discontinue (OR = 0.29; 95% CI = 0.15-0.54; P < 0.001) and more likely to be adherent in the linear regression model (ß = 0.0604, P < 0.001) and the logistic regression model (OR = 1.53; 95% CI = 1.02-2.28; P = 0.009). Other factors significantly associated with better adherence included higher baseline PDC and number of medications. Depression status was significantly associated with lower adherence. CONCLUSIONS: Patients receiving 2 or more calls had significantly better adherence and less discontinuation during the 6 months following initial calls compared with those who did not receive calls. This finding indicates that an MI-based telephone intervention by pharmacy students may be a promising intervention to improve adherence. Future research should examine the sustainability of the intervention effect for longer time periods and its influence on associated clinical outcomes. DISCLOSURES: This project was supported by the Pharmaceutical Research and Manufacturers of America Foundation (PhRMA). The content is solely the responsibility of the authors and does not necessarily represent the official views of PhRMA. The funding agency was not involved in research design, analysis, or reporting results. Funding was obtained by Abughosh. Holstad provided a consultation regarding the MI guide and provided the MI training. Study concept and design were contributed by Abughosh and Fleming, along with Serna, Esse, and Holstad. Serna, Esse, Mann, Holstad, and Masilamani collected the data, and data interpretation was performed by Abughosh, Wong, and Esse. The manuscript was written by Abughosh, Wong, and Esse and revised by Masilamani and Holstad, along with the other authors.

Evaluating Pharmacist-Written Recommendations to Providers in a Medicare Advantage Plan: Factors Associated with Provider Acceptance.

BACKGROUND: Pharmacist-written recommendation letters to physicians, through mail or fax, are common practice in managed care settings. While rates of physician acceptance of pharmacist recommendations have been reported to average around 50%, the factors affecting the provider's acceptance of recommendations have not been adequately explored. Identifying these factors may help to improve pharmacist-physician communication and help identify areas where physician education may benefit patient care. OBJECTIVES: To (a) determine the percentage of pharmacist-written recommendations for members enrolled in a Medicare Advantage Plan with prescription drug coverage that was accepted by providers and (b) examine member and provider factors associated with provider acceptance. METHODS: A retrospective cohort study was conducted among members enrolled in a Medicare Advantage Plan in Texas. Members were included if their medication profiles were reviewed by a health plan resident pharmacist and resulted in a recommendation letter sent directly to the member's provider between July 1, 2012, and March 15, 2014. Pharmacist-written recommendation letters were retrieved from the archived files and were assessed for factors such as type of recommendation made, the member's disease state affected by the recommendation, and the letter format. Other factors assessed included member and provider characteristics such as demographics, participation in the health plan pay-for-performance program, physician specialty, and region of practice. Acceptance was defined as a change in pharmacy claims that reflected the change suggested in the letter within 6 months of the recommendation. The percentage of recommendations accepted by providers was calculated. Chi-square tests were used to examine group differences in recommendation acceptances with recommendation type as well as member and prescriber characteristics. Logistic regression was used to identify significant predictors of an accepted change. RESULTS: From 158 pharmacist-written recommendation letters, 228 recommendations were identified, of which 115 (50.4%) were accepted. Ninety-five (41.7%) recommendations were to add a drug; 80 (35.1%) recommendations were to discontinue a drug; and 53 (23.2%) recommendations were to change a drug. The member population affected by these recommendations had a mean [SD] age of 69 [± 11] years. Recommendations to discontinue or change a drug were more likely to be accepted than to add a drug (P = 0.007), but recommendation type was not determined as a significant predictor in the multivariate model. Recommendations for heart failure were less likely to be followed compared with recommendations for diabetes (OR = 0.31; 95% CI = 0.10-0.96; P = 0.043). A regional trend was identified in which recommendations in Southeast Texas were more likely to be implemented than those in West Texas, but it did not reach a level of significance (OR = 0.51; 95% CI = 0.24-1.07; P = 0.074), possibly because of the relatively limited sample size. CONCLUSIONS: Overall, pharmacist-written recommendations were commonly accepted by physicians. Recommendations for heart failure were less likely followed versus those for diabetes. Since most recommendations for heart failure concerned changing drugs within the beta-blocker class, physicians may not have seen the value in modifying current therapy. This finding points to a potential need for physician education. Further research with larger samples is warranted to increase the power to identify significant differences in other variables that may need to be addressed in order to increase the rates of recommendation acceptance and improve patient care.

Physician Perception of Patient Medication Adherence in a Cohort of Medicare Advantage Plans in Texas.

BACKGROUND: Prescription medication adherence is a known health-related barrier for elderly patients, leading to insufficient disease control and negative health outcomes. The Centers for Medicare & Medicaid Services (CMS) have placed significant emphasis on medication adherence, through the Part D star measures, revolving around treatment for chronic disease states such as hypertension, diabetes, and hyperlipidemia. However, it is unclear if physicians fully grasp the extent of nonadherence within their patient populations with regard to these medications, specifically those patients enrolled in Medicare Advantage Prescription Drug (MA-PD) plans. OBJECTIVES: To (a) determine physicians' perceptions of medication adherence among their patients enrolled in MA-PD plans and (b) compare those perceptions with actual adherence rates obtained from claims data. METHODS: A survey was developed and administered to primary care physicians (PCPs) contracted within a Texas MA-PD plan. The previously validated questionnaire was distributed during an all-PCP quarterly meeting and was collected prior to the meeting's conclusion to increase completion and return rates. PCPs were requested to indicate what percentage of their patients they believed to be adherent to each of the CMS Part D star medication classes, which includes statins, oral antidiabetic drugs (OADs), and reninangiotensin system (RAS) antagonists; what financial category they believe the majority of their patients fall under; and what percentage of their patients receive samples. The PCPs' perceived percentage of adherent patients were compared with the calculated percentage of patients, using a chi-square test at an a priori alpha level of 0.05. The calculated adherence was obtained from pharmacy claims data, meeting the CMS targeted adherence threshold (≥ 80%). This adherence rate was calculated using proportion of days covered (PDC) for all 3 medication categories in each PCP's patient population. RESULTS: To compare PCP perception of patient adherence and actual adherence, 226 PCPs were used. The sample population shared similar sex and age distribution with the national physician average; however, there was more racial diversity represented. PCP perception of patient adherence, as well as the actual percentage of adherent patients, were significantly (P < 0.05) different across statins, OADs, and RAS antagonists; lowest perceived percentage, as well as actual percentage, were reported for statins. PCP perception of patient adherence and actual percentage of adherent patients were significantly different in the 3 medication categories. PCPs' correct estimations were significantly (P < 0.0001) lower than expected values, while over- and underestimations were significantly (P < 0.0001) higher than the expected values. CONCLUSIONS: PCPs were almost equally likely to over- or underestimate percentage of adherent patients in their patient pools.

Quality compensation programs: are they worth all the hype? A comparison of outcomes within a Medicare advantage heart failure population.

BACKGROUND: Quality compensation programs (QCPs), also known as pay-for-performance programs, are becoming more common within managed care entities. QCPs are believed to yield better patient outcomes, yet the programs lack the evidence needed to support these claims. We evaluated a QCP offered to network primary care physicians (PCPs) within a Medicare managed care plan to determine if a positive correlation between outcomes and the program exists. OBJECTIVE: To compare outcomes of heart failure members under the care of PCPs enrolled in a Medicare Advantage Prescription Drug (MAPD) Plan QCP with those who are not affiliated with a QCP. METHODS: Retrospective analysis was conducted on the heart failure population of a MAPD in Texas. Heart failure members were identified using ICD-9-CM codes from inpatient and outpatient claims for 2010. These members must have been continuously eligible all 12 months of the year to be included in the analysis. The primary intervention was enrollment by the member's PCP into the QCP. Measurable outcomes included acute (hospital) admits, emergency room (ER) visits, appropriate laboratory tests, and prescriptions of medications that are evidence based and guideline driven. Centers for Medicare and Medicaid Services (CMS) risk scores and comorbidities were used to risk-adjust outcomes. RESULTS: A total of 4,240 members was included in the analysis. From that population, 1,225 members (28.8%) were followed by PCPs enrolled in a QCP; 3,015 members (71.1%) were followed by PCPs not enrolled in a QCP. The adjusted analysis showed that none of the drug comparisons statistically differed between the QCP and non-QCP groups, whereas all of the lab tests, including low-density lipoprotein cholesterol (LDL-C), hemoglobin A1c, creatinine, and microalbumin, as well as the acquisition of the flu vaccine, occurred more frequently in the QCP group. Acute admits and ER visits in the QCP and non-QCP groups were similar before and after adjustment. The QCP group was significantly older with a statistically significant higher prevalence of renal failure and higher CMS risk scores. CONCLUSIONS: After evaluation of our QCP's impact on the quality of care provided to our Medicare beneficiaries, we have concluded that there is potential for health care improvement through pay-for-performance programs. We have observed in our MAPD heart failure population, enrolled in a QCP during the year of 2010, an increase in age and CMS risk scores, a decline in renal function, and noted the group to have a more female presence. Yet, the outcomes of this group (hospitalizations, ER visits, acquisition of lab tests, etc.) were similar when compared with younger, healthier members not enrolled in a QCP. We feel the clinical relevance of the data indicates that, overall, the quality of care is somewhat improved for QCP-enrolled providers when compared with non-QCP providers in regards to achieving certain quality metrics. (i.e., immunizations, HgA1c, LDL-C, etc.) Further research is definitely needed to determine if health care costs and clinical outcomes, in the long term, are improved for members enrolled in these QCP programs, as well as their impact upon a health plan's Medicare Star rating.