Persistence to Basal Insulin: Association With Health Outcomes in a Population With Type 2 Diabetes.

This study examined the association between persistence to basal insulin and clinical and economic health outcomes. The question of whether a persistence measure for basal insulin could be leveraged in quality measurement was also explored. Using the IBM-Truven MarketScan Commercial and Medicare Supplemental Databases from 1 January 2011 to 31 December 2015, a total of 14,126 subjects were included in the analyses, wherein 9,898 (70.1%) were categorized as persistent with basal insulin therapy. Basal insulin persistence was associated with lower A1C, fewer hospitalizations and emergency department visits, and lower health care expenditures. Quality measures based on prescription drug claims for basal insulin are feasible and should be considered for guiding quality improvement efforts.

Factors associated with medication nonadherence among Medicare low-income subsidy beneficiaries with diabetes, hypertension, and/or heart failure.

BACKGROUND: Previous studies have documented factors influencing medication nonadherence among the Medicare population, but few studies have examined medication nonadherence among the Medicare low-income subsidy (LIS) population. Furthermore, little is known about the factors associated with nonadherence among this population, especially those with prevalent chronic conditions such as type 2 diabetes, hypertension, or heart failure. OBJECTIVE: To examine factors associated with the likelihood of medication nonadherence among Medicare LIS recipients with type 2 diabetes, hypertension, or heart failure. METHODS: This was a retrospective analysis of 2012-2013 Medicare Parts A, B, and D claims (most recent available for this research) linked to the Area Health Resources Files. Beneficiaries aged 65 years or older with continuous Medicare coverage and receiving any LIS were included. Individuals were categorized into full LIS or partial LIS groups. Nonadherence was determined by the proportion of days covered less than 80% for specified oral type 2 diabetes, hypertension, and heart failure medications, as defined by the Pharmacy Quality Alliance. A multivariate logistic regression was used to determine and compare individual-level and community-level characteristics associated with nonadherence among the entire study sample, the full LIS group, and the partial LIS group. RESULTS: The study sample included 505,771 Medicare beneficiaries, with 448,509 (88.7%) receiving full LIS and 57,262 (11.3%) receiving partial LIS. The proportion of individuals nonadherent was higher among the full LIS population (33.2%) than that of the partial LIS population (30.8%). Among the entire population, younger age was associated with nonadherence (OR = 0.98; 95% CI = 0.98-0.99). Men were more likely to be nonadherent than women (OR = 1.12; 95% CI = 1.11-1.14). Compared with non-Hispanic Whites, racial/ethnic minorities had higher nonadherence. Compared with beneficiaries who were non-Hispanic White, the ORs for those who were Black, Hispanic, Asian, and other were 1.41 (95% CI = 1.38-1.43), 1.58 (95% CI = 1.55-1.61), 1.08 (95% CI = 1.05-1.11), and 1.63 (95% CI = 1.56-1.70), respectively. There were higher nonadherence rates among patients living in communities with lower socioeconomic characteristics, such as a metropolitan statistical area (MSA vs non-MSA; OR = 1.05, 95% CI = 1.04-1.07). A higher risk adjustment summary score, indicating worse health status, was associated with an increased likelihood of medication nonadherence (OR = 1.21; 95% CI = 1.20-1.22). These patterns were similar among the full and partial LIS groups. CONCLUSIONS: Individual- and community-level characteristics were associated with the likelihood of medication nonadherence among Medicare LIS recipients with type 2 diabetes, hypertension, or heart failure. These characteristics included younger age, male sex, racial/ethnic minorities, living in lower socioeconomic communities, and a higher risk adjustment summary score. This study provided insight into medication nonadherence within the Medicare LIS population and identified the need to consider these factors when developing future policies to improve medication adherence. DISCLOSURES: This study was funded by the Pharmaceutical Research & Manufacturers of America (PhRMA), which was involved in the preparation and revision of the manuscript. Dougherty is employed by PhRMA. Todor was a PQA-CVS Health Foundation Scholar who was funded to work on this study. Hines is employed by Pharmacy Quality Alliance. Wang reports grants from AbbVie, Curo, Bristol Myers Squibb, and Pfizer, during the time of this study, and fees from the PhRMA Foundation for work on its Heath Outcomes Research Advisor Committee. The other authors have nothing to disclose. This study was presented as a poster at the online 2020 PQA Annual Meeting, May 7, 2020.

Effects of the Medicare Part D comprehensive medication review on medication adherence among patients with Alzheimer's disease.

OBJECTIVE: Older patients with Alzheimer's disease (AD) are challenged with adhering to complex medication regimens. We examined effects of Comprehensive Medication Review (CMR), a required Medicare Part D Medication Therapy Management (MTM) program component, on medication adherence among AD patients. METHODS: This retrospective study analyzed 100% of 2016-2017 Medicare claims covering the entire United States, linked to Area Health Resources Files. Medicare beneficiaries aged ≥65 years were included. Propensity score matching identified comparable intervention and comparison groups with the intervention defined as receiving a CMR in 2017. A difference-in-differences analysis included in multivariate logistic regressions an interaction term between CMR receipt and year 2017. The outcome measured was nonadherence to diabetes, hypertension and hyperlipidemia medications, with nonadherence defined as proportion of days covered <80% for study medications. RESULTS: Unadjusted comparisons indicated the proportion of nonadherence for intervention group members decreased from 2016 to 2017 but increased for the comparison group. In adjusted analyses, reduction in medication nonadherence among the intervention group remained higher: odds ratios for the interaction term were 0.62 (95% confidence interval [CI] = 0.54-0.71), 0.54 (95% CI = 0.50-0.58) and 0.50 (95% CI = 0.47-0.53) respectively for diabetes, hypertension and hyperlipidemia medications. This suggests that the likelihood of nonadherence in the intervention group was respectively reduced by 38%, 46% and 50% more than the comparison group. CONCLUSIONS: CMR was found to reduce nonadherence to diabetes, hypertension and hyperlipidemia medications among older Medicare beneficiaries with AD. This provides evidence that the MTM program is effective for a population with unique medication compliance challenges.

Exploring Racial and Ethnic Disparities in Medication Adherence Among Medicare Comprehensive Medication Review Recipients.

Background: There has been a lack of evidence on whether there are racial and ethnic disparities in medication nonadherence among individuals receiving comprehensive medication review (CMR), a required component of the Medicare Part D medication therapy management (MTM) services. Objectives: To explore racial/ethnic disparities in medication nonadherence among older MTM enrollees who received a CMR and to determine how much the identified disparities can be explained by observed characteristics. Methods: The retrospective study used 100% of the 2017 Medicare claims, including MTM data. Linked Area Health Resources Files provided community characteristics. Nonadherence was defined as proportion of days covered <80%, and was measured for diabetes, hypertension, and hyperlipidemia medications. Racial/ethnic disparities were examined by logistic regressions that included racial/ethnic minority dummy variables. A nonlinear Blinder-Oaxaca decomposition method was applied to decompose the identified disparities. Results: Compared with non-Hispanic Whites (Whites), Blacks were respectively 39% (odds ratio [OR] = 1.39, 95% confidence interval [CI] = 1.33-1.45), 27% (OR = 1.27, 95% CI = 1.22-1.32), and 43% (OR = 1.43, 95% CI = 1.39-1.47) more likely to be nonadherent to diabetes, hypertension, and hyperlipidemia medications; Hispanics were 20% (OR = 1.20, 95% CI = 1.14-1.27) more likely to be nonadherent to hyperlipidemia medications. The total portion of disparity explained was 13.42%, 7.66%, 14.87%, and 10.69% respectively for disparities in Black-White (B-W) diabetes, B-W hypertension, B-W hyperlipidemia, and Hispanic-White hyperlipidemia. The top three contributors were the proportion of married-couple families, census region, and male gender. Conclusions: A lower level of community affluence and social support, regional variations, and a lower proportion of males in Blacks and Hispanics may contribute to the disparities in medication nonadherence. The large unexplained portion of the disparity attests that nonadherence is a complex issue. The Medicare MTM program needs to implement measures to reduce disparities in medication adherence.

Effects of the Medicare Part D Comprehensive Medication Review on Racial and Ethnic Disparities in Medication Adherence.

Background: Substantial research has documented inequalities between US minorities and whites in meeting the eligibility criteria for the Medicare Part D medication therapy management (MTM) program. Even though the Centers for Medicare & Medicaid Services attempted to relax the eligibility criteria, a critical barrier to effective MTM reform is a lack of stronger evidence about the effects of MTM on minorities' health outcomes. Objective: To examine the effects of comprehensive medication review (CMR), an MTM core component, on racial and ethnic disparities in adherence to diabetes, hypertension, and hyperlipidemia medications among Medicare beneficiaries aged ≥65 years. Methods: This study used full-year 2017 Medicare Parts A, B, and D claims data, including MTM data, linked to the Area Health Resources Files. Racial and ethnic disparities in nonadherence to diabetes, hypertension, and hyperlipidemia medications were compared between CMR recipients and nonrecipients matched by their propensity scores. To determine the changes in racial and ethnic disparities after receiving CMR, a difference-in-differences framework was applied, by including in logistic regression analyses interaction terms between dummy variables for CMR receipt and each racial or ethnic minority group. Results: Compared with CMR nonrecipients, CMR recipients had significantly lower racial and ethnic disparities across the 3 outcome measures, with the exception of the difference between whites and blacks in nonadherence to diabetes medications. For example, compared with CMR nonrecipients, among CMR recipients the differences in the odds of nonadherence to hypertension medications were reduced, respectively, by 8% (95% confidence interval [CI], 0.88-0.96) between whites and blacks; by 18% (95% CI, 0.78-0.86) between whites and Hispanics; by 16% (95% CI, 0.77-0.91) between whites and Asians; and by 9% (95% CI, 0.85-0.98) between whites and other racial and ethnic groups. Conclusion: Receiving a CMR reduced the racial and ethnic disparities in adherence to diabetes, hypertension, and hyperlipidemia medications among Medicare beneficiaries aged ≥65 years. These findings provide critical empirical evidence that may inform the future design of the Medicare Part D MTM program, which is valuable for improving pharmacotherapy outcomes and could further realize its potential when additional people from racial and ethnic minorities are enrolled.

Racial/ethnic disparities in measure calculations for Part D Star Ratings among Medicare beneficiaries with diabetes, hypertension, and/or hyperlipidemia.

BACKGROUND: Previous literature reported racial/ethnic disparities in the measure assessment of diabetes medication adherence in the Medicare Part D Star Ratings program. OBJECTIVE: This study examined the likelihood of inclusion in measure calculation across racial/ethnic groups for adherence metrics in Part D Star Ratings among individuals with diabetes, hypertension, and/or hyperlipidemia. METHODS: This was a retrospective cross sectional analysis of a 10% random sample of 2017 Medicare claims linked to Area Health Resources Files. Inclusion in measure calculation was determined based on inclusion/exclusion criteria in adherence metrics for adherence medications for diabetes, hypertension, and hyperlipidemia in Part D Star Ratings developed by the Pharmacy Quality Alliance. Logistic regression and multinomial logistic regression were used to adjust for patient/community characteristics. RESULTS: The study sample size was 2 707 216. Compared to Non-Hispanic White (White) beneficiaries, minorities were more likely to be excluded from measure calculation among individuals with 1 condition. For example, among individuals with hypertension, compared to White individuals, the adjusted odds ratios for exclusion for Black, Hispanic, Asian/Pacific Islander and other individuals were 1.46 (95% confidence interval, or CI = 1.42-1.50), 1.38 (95% CI = 1.33-1.43), 1.28 (95% CI = 1.21-1.35), and 1.08 (95% CI = 1.02-1.15), respectively. Among individuals with more than 1 chronic condition, minorities were more likely to be included in fewer calculations for medication adherence measures. For example, among individuals with all 3 conditions, the adjusted relative risk ratios for Black, compared to White, beneficiaries for being included in 0, 1, and 2 measures, versus all 3 measures, were 2.14 (95% CI = 1.99-2.30), 1.49 (95% CI = 1.41-1.56), 1.20 (95% CI = 1.18-1.23), respectively. CONCLUSIONS: Compared to White beneficiaries, racial/ethnic minorities are more likely to be excluded from the calculation for adherence measures among individuals with diabetes, hypertension, and/or hyperlipidemia. Future studies should examine whether such disparities exacerbate existing racial/ethnic disparities in health outcomes and devise solutions for these disparities.

Testing the face validity and inter-rater agreement of a simple approach to drug-drug interaction evidence assessment.

Low concordance between drug-drug interaction (DDI) knowledge bases is a well-documented concern. One potential cause of inconsistency is variability between drug experts in approach to assessing evidence about potential DDIs. In this study, we examined the face validity and inter-rater reliability of a novel DDI evidence evaluation instrument designed to be simple and easy to use. METHODS: A convenience sample of participants with professional experience evaluating DDI evidence was recruited. Participants independently evaluated pre-selected evidence items for 5 drug pairs using the new instrument. For each drug pair, participants labeled each evidence item as sufficient or insufficient to establish the existence of a DDI based on the evidence categories provided by the instrument. Participants also decided if the overall body of evidence supported a DDI involving the drug pair. Agreement was computed both at the evidence item and drug pair levels. A cut-off of ≥ 70% was chosen as the agreement threshold for percent agreement, while a coefficient > 0.6 was used as the cut-off for chance-corrected agreement. Open ended comments were collected and coded to identify themes related to the participants' experience using the novel approach. RESULTS: The face validity of the new instrument was established by two rounds of evaluation involving a total of 6 experts. Fifteen experts agreed to participate in the reliability assessment, and 14 completed the study. Participant agreement on the sufficiency of 22 of the 34 evidence items (65%) did not exceed the a priori agreement threshold. Similarly, agreement on the sufficiency of evidence for 3 of the 5 drug pairs (60%) was poor. Chance-corrected agreement at the drug pair level further confirmed the poor interrater reliability of the instrument (Gwet's AC1 = 0.24, Conger's Kappa = 0.24). Participant comments suggested several possible reasons for the disagreements including unaddressed subjectivity in assessing an evidence item's type and study design, an infeasible separation of evidence evaluation from the consideration of clinical relevance, and potential issues related to the evaluation of DDI case reports. CONCLUSIONS: Even though the key findings were negative, the study's results shed light on how experts approach DDI evidence assessment, including the importance situating evidence assessment within the context of consideration of clinical relevance. Analysis of participant comments within the context of the negative findings identified several promising future research directions including: novel computer-based support for evidence assessment; formal evaluation of a more comprehensive evidence assessment approach that requires consideration of specific, explicitly stated, clinical consequences; and more formal investigation of DDI case report assessment instruments.

Comparative Effectiveness of Medication Therapy Management Eligibility Criteria Across Racial/Ethnic Groups.

BACKGROUND/OBJECTIVES: Previous research indicates that eligibility criteria for medication therapy management (MTM) services in Medicare prescription drug (Part D) plans, defined under the Medicare Modernization Act (MMA), are associated with racial/ethnic disparities and ineffective in identifying individuals with medication utilization issues. Our study's objective was to determine the comparative effectiveness of MTM eligibility criteria under MMA and in the Affordable Care Act (ACA) in identifying patients with medication utilization issues across racial/ethnic groups. DESIGN: ACA and MMA MTM eligibility criteria were compared on proportions of eligible individuals among patients with medication utilization issues. Multinomial logistic regression was conducted to control for patient/community characteristics. Need-based and demand-based analyses were used to determine disparities due to need and demand for healthcare. Main/sensitivity analyses were conducted for the range of eligibility thresholds. SETTING: Medicare data (2012-2013) linked to Area Health Resources Files. PARTICIPANTS: A total of 964 610 patients 65 years or older. MEASUREMENTS: Medication safety/adherence measures, developed primarily by the Pharmacy Quality Alliance, were used to determine medication utilization issues. RESULTS: Higher proportions of patients were eligible based on ACA than MMA MTM eligibility criteria. For example, in 2013, proportions based on ACA and MMA MTM eligibility criteria would be 99.7% and 26.2%, respectively, in the main analysis (p < .001); in the demand-based main analysis, ACA criteria were associated with 13.6% and 9.8%, respectively, higher effectiveness than MMA criteria among non-Hispanic blacks and Hispanics than non-Hispanic whites. CONCLUSION: ACA MTM eligibility criteria are more effective than MMA criteria in identifying older patients needing MTM, particularly among minorities. J Am Geriatr Soc 67:581-587, 2019.

Ability and Use of Comparative Effectiveness Research by P&T Committee Members and Support Staff: A 1-Year Follow-up.

BACKGROUND: In recent years, comparative effectiveness tools and methods have evolved to assist health care decision makers in identifying optimal therapies. In-person training programs on comparative effectiveness research may be helpful in understanding and applying this information. OBJECTIVE: To provide a follow-up assessment of the use of comparative effectiveness research (CER) in the pharmacy and therapeutics (P&T) committee decision-making process, using information collected from participants 1 year after attending a live continuing education program, in which participants were taught about CER designs and how to access available CER resources through the Agency for Healthcare Research and Quality (AHRQ) Effective Health Care (EHC) Program. METHODS: A retrospective, cross-sectional questionnaire was developed and mailed to 2 groups of individuals: CER workshop attendees and interested nonattendees (expressing an interest in attending a workshop but did not attend for unknown reasons). The questionnaire asked respondents to indicate personal and organizational use of CER in the decision-making process. Participants were asked to indicate whether their knowledge, ability, and use of CER studies increased since participating in the program. Data were analyzed using nonparametric tests to compare the responses of attendees and nonattendees, as well as overall reliability of the instrument. RESULTS: A total of 164 respondents completed the questionnaire (63 attendees and 101 nonattendees; overall response rate = 44%). The majority of respondents were pharmacists (n = 157, 95.7%) and were affiliated with a hospital (n = 106, 64.6%). Proportions of attendees and nonattendees differed significantly in the use of EHC research reviews/reports (45% and 28%, respectively; P = 0.02) and EHC executive summaries of research reviews/reports (48% and 29%, respectively; P = 0.01). At 1-year follow-up, the majority of attendees reported an increase ("somewhat" or "very much") in knowledge of CER (91.5%), ability to use CER (83.0%), and use of CER studies (58.7%). CONCLUSIONS: Health professionals attending a continuing education CER program reported higher use of EHC CER materials compared with nonattendees. Additionally, attendees reported increased use of CER in clinical decision making. A continuing education program such as this may provide an effective avenue for introducing CER methods and resources to the P&T committee and clinical decision-making processes. DISCLOSURES: This project was supported by grant number R18HS019220 from the Agency of Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency of Healthcare Research and Quality. Augustine has stock in Pfizer. The authors declared no other potential conflicts of interest associated with this study. Study concept and design were primarily contributed by Malone, along with Warholak, Hines, Brown, Hurwitz, and Taylor. Warholak, Hines, Brown, Hurwitz, and Taylor collected the data, assisted by Malone, Brixner, Cobaugh, and Schlaifer. Data interpretation was performed by Malone and Augustine, with assistance from the other authors. The manuscript was written primarily by Augustine, with assistance from Malone, Sun, Warholak, Hines, Brown, Hurwitz, and Taylor. Malone revised the manuscript, assisted by Warholak, Hines, Brown, Hurwitz, Taylor, Brixner, Cobaugh, and Schlaifer.

Recommendations for selecting drug-drug interactions for clinical decision support.

PURPOSE: Recommendations for including drug-drug interactions (DDIs) in clinical decision support (CDS) are presented. SUMMARY: A conference series was conducted to improve CDS for DDIs. A work group consisting of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information vendors, and healthcare organizations was convened to address (1) the process to use for developing and maintaining a standard set of DDIs, (2) the information that should be included in a knowledge base of standard DDIs, (3) whether a list of contraindicated drug pairs can or should be established, and (4) how to more intelligently filter DDI alerts. We recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated and more research to identify methods to safely reduce repetitive and less-relevant alerts. CONCLUSION: An expert panel with a centralized organizer or convener should be established to develop and maintain a standard set of DDIs for CDS in the United States. The process should be evidence driven, transparent, and systematic, with feedback from multiple stakeholders for continuous improvement. The scope of the expert panel's work should be carefully managed to ensure that the process is sustainable. Support for research to improve DDI alerting in the future is also needed. Adoption of these steps may lead to consistent and clinically relevant content for interruptive DDIs, thus reducing alert fatigue and improving patient safety.

Recommendations to improve the usability of drug-drug interaction clinical decision support alerts.

OBJECTIVE: To establish preferred strategies for presenting drug-drug interaction (DDI) clinical decision support alerts. MATERIALS AND METHODS: A DDI Clinical Decision Support Conference Series included a workgroup consisting of 24 clinical, usability, and informatics experts representing academia, health information technology (IT) vendors, healthcare organizations, and the Office of the National Coordinator for Health IT. Workgroup members met via web-based meetings 12 times from January 2013 to February 2014, and two in-person meetings to reach consensus on recommendations to improve decision support for DDIs. We addressed three key questions: (1) what, how, where, and when do we display DDI decision support? (2) should presentation of DDI decision support vary by clinicians? and (3) how should effectiveness of DDI decision support be measured? RESULTS: Our recommendations include the consistent use of terminology, visual cues, minimal text, formatting, content, and reporting standards to facilitate usability. All clinicians involved in the medication use process should be able to view DDI alerts and actions by other clinicians. Override rates are common but may not be a good measure of effectiveness. DISCUSSION: Seven core elements should be included with DDI decision support. DDI information should be presented to all clinicians. Finally, in their current form, override rates have limited capability to evaluate alert effectiveness. CONCLUSION: DDI clinical decision support alerts need major improvements. We provide recommendations for healthcare organizations and IT vendors to improve the clinician interface of DDI alerts, with the aim of reducing alert fatigue and improving patient safety.

Consensus recommendations for systematic evaluation of drug-drug interaction evidence for clinical decision support.

BACKGROUND: Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. OBJECTIVE: The aim of this study was to provide recommendations for systematic evaluation of evidence for DDIs from the scientific literature, drug product labeling, and regulatory documents. METHODS: A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 18 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar 12 times from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. RESULTS: We developed expert consensus answers to the following three key questions. (i) What is the best approach to evaluate DDI evidence? (ii) What evidence is required for a DDI to be applicable to an entire class of drugs? (iii) How should a structured evaluation process be vetted and validated? CONCLUSION: Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug compendia and clinical decision support systems in which these recommendations are implemented should be able to provide higher-quality information about DDIs.

The good, the bad, and the different: a primer on aspects of heterogeneity of treatment effects.

The concept of heterogeneity is concerned with understanding differences within and across patients and studies. Heterogeneity of treatment effects is nonrandom variability in response to treatment and includes both benefits and harms. Because not all patients respond the same way, treatment decisions applied in a "one size fits all" fashion based on the average response observed in clinical trials may lead to suboptimal outcomes for some patients. Variation in outcomes among patients may be caused by observable and nonobservable factors. Changes in patients' health status over time can contribute to variability among patients. Assuming that the results from clinical trials are homogeneous across patients may fail to take into account clinically significant variability where some patients may receive benefit and others harm. Subgroup analyses and prediction models are 2 tools to explain variability observed within a study. Evidence synthesis with meta-analysis can provide useful information on the overall effectiveness and response among groups of patients undersampled in individual studies. Yet caution is warranted if the meta-analysis is missing studies or the individual studies comprising the meta-analysis are inherently different.For those making clinical, coverage, and reimbursement decisions at a population level, such as clinicians and pharmacy and therapeutics committee members, understanding the variation among patients, among subpopulations or populations of patients, among clinical studies, or within a meta-analysis is important to ensuring optimal patient outcomes. This article presents a variety of tools and resources to aid decision makers as they evaluate the literature to determine when clinically relevant differences exist.

Evaluation of an educational program on deciphering heterogeneity for medical coverage decisions.

BACKGROUND: It is increasingly important for decision makers, such as medical and pharmacy managers (or pharmacy therapeutics committee members and staff), to understand the variation and diversity in treatment response as decisions shift from an individual patient perspective to optimizing care for populations of patients. OBJECTIVE: To assess the effectiveness of an instructional program on heterogeneity designed for medical and pharmacy managers. METHODS: A live educational program was offered to members of the Academy of Managed Care Pharmacy at the fall 2012 educational meeting and also to medical directors and managers attending a national payer roundtable meeting in October 2012. Participants completed a retrospective pretest-posttest assessment of their knowledge, attitudes, and self-efficacy immediately following the program. Participants were offered the opportunity to participate in a follow-up assessment 6 months later. Willing participants for the follow-up assessment were contacted via e-mail and telephone. Rasch rating scale models were used to compare pre- and postscores measuring participants' knowledge about and attitude towards heterogeneity. RESULTS: A total of 49 individuals completed the retrospective pretest-posttest assessment and agreed to be a part of the program evaluation. Fifty percent (n = 25) of participants had heard of the phrase "heterogeneity of treatment effect," and 36 (72%) were familiar with the phrase "individualized treatment effect" prior to the live program. Participants reported a significant improvement in knowledge of heterogeneity (P less than 0.01) and attitudes about heterogeneity (P less than 0.01) immediately after attending the program. At the time of the educational program, participants had either never considered heterogeneity (26%) or reported not knowing (28%) whether their organizations considered it when determining basic coverage. Participants were more likely to report "sometimes" considering heterogeneity for determining necessity for individual appeals, prior authorization, tier placement for pharmaceutical therapies, and other types of medical management. At the 6-month follow-up, 21 of the 49 willing participants (43% response rate) completed the evaluation; participants continued to have a good understanding of heterogeneity, but there was no significant difference in attitudes towards heterogeneity between pre- and 6-month follow-up. CONCLUSION: A live educational program was effective in improving participants' immediate knowledge and attitudes regarding the topic of heterogeneity. Participating managed care pharmacists and medical managers indicated that heterogeneity of treatment effect was likely to be used in determining prior authorizations and determining necessity.

Prescriber perceptions of a near real-time fax alert program for potential drug-drug interactions.

BACKGROUND: Health systems have developed interventions to reduce harm associated with drug-drug interactions. Pharmacy benefit managers are in an important position to identify the coprescribing of medications known to interact, since they process data on a large portion of prescription claims in the United States. Electronic health records and electronic prescribing also include alerts through their systems' clinical decision support. However, limited data are available that assess prescribers' perceptions of processes that screen for potential drug-drug interactions (PDDIs). OBJECTIVE: To determine prescribers' perceptions of near real-time fax alerts for PDDIs. METHODS: This was a 6-month prospective study where a pharmacy benefit manager distributed evidence-based summaries of 18 different PDDIs that included references and suggested management strategies. Fax alerts were individualized letters sent to the prescriber of the second drug of a PDDI pair for an individual patient. A 16-item questionnaire to assess prescribers' perceptions of the intervention accompanied each individualized PDDI evidence-based summary. RESULTS: A total of 8,075 fax alerts were distributed with 977 returning questionnaires, yielding a 12.1% response rate. There were 848 (86.8%) responses completed by physicians, and 71 (7.3%) completed by nurse practitioners. The most common PDDI fax alerts sent were for warfarin-statin (3,511, 43.5%) and warfarin-thyroid (2,111, 26.1%) interactions. 42.6% of respondents agreed or strongly agreed that fax alerts were a good way to communicate with them. However, 37.5% of respondents either agreed or strongly agreed that the fax alert was a "waste of my time." In contrast, respondents thought notification of carbamazepine-macrolide (mean 1.5 ± 0.71), ciprofloxacin-tizanidine (mean 2.3 ± 1.0), and statin-macrolide (mean 2.3 ± 1.1) was not a waste of time. Also, 59.1% of respondents either disagreed or strongly disagreed that they would prefer to receive a telephone call when interactions like this occur. Half (50.5%) of the respondents indicated their computer systems provided drug interaction alerts. Prescribers who had previously received alerts and specialists were less likely to respond to the questionnaire (OR = 0.685, P ≤ 0.0001 and OR = 0.851, P = 0.0205, respectively). CONCLUSIONS: The positive response to fax alerts by physicians varies by the component drugs of the PDDI alerts.

Health care decision makers' use of comparative effectiveness research: report from a series of focus groups.

BACKGROUND: Comparative effectiveness research (CER) is a helpful approach to improve health outcomes by developing and disseminating evidence-based information to patients, clinicians, and other decision makers about the most effective interventions. OBJECTIVES: To (a) identify the factors necessary to increase the use of the Agency for Healthcare Research and Quality's (AHRQ) CER reviews in hospitals and managed care organizations; (b) assess current awareness and implementation of CER materials in these facilities and organizations; and (c) inform development of content for a workshop on CER. METHODS: Pharmacy and therapeutics (PT) committee members and supportive personnel were recruited to participate in focus groups conducted at national health professional meetings. Prior to the sessions, each participant completed a prefocus group questionnaire evaluating the organization and process of the respondent's PT committee, as well as the respondent's role in the PT committee and awareness of AHRQ CER reports. Each session consisted of a focused discussion about CER and sources of evidence for PT monographs, and each participant completed a ballot to rank topics of importance for inclusion in a CER workshop for health care professionals involved in the PT process. Overarching themes were later identified using qualitative analysis of the transcripts of the focus group sessions. RESULTS: Thirty-nine (68%) pharmacists and 18 (32%) physicians involved in the PT process participated in 1 of 7 focus groups. Almost half of the participants had 6-15 years experience with the PT process. Participants represented health plans, hospitals, and health care systems. Two-thirds indicated they were aware of AHRQ's Effective Health Care Program's CER reviews, yet only 26% reported using the reviews in their organizations. The overarching themes reflected the need for timely and conclusive CER information; the role of the pharmacist as central to evidence synthesis for the PT process; and the need for educational programs in online formats that are designed primarily for pharmacists. CONCLUSION: Health care decision makers identified timeliness as a key factor for facilitating the use of AHRQ CER reviews and guides in hospitals and managed care organizations. To facilitate integration of CER into the decision-making process, it is imperative that key stakeholders have access to comprehensive and timely information. While the majority of participants indicated that they were aware of AHRQ CER reviews, few had used them in the PT process.

Assessing patients' information needs regarding drug-drug interactions.

OBJECTIVE: To assess patients' information needs regarding drug-drug interactions (DDIs) to inform patient DDI education resources. DESIGN: Cross-sectional study. SETTING: Online (United States in May 2011). PARTICIPANTS: Registered users of an online medication monitoring service (MediGuard). INTERVENTION: Online questionnaire. MAIN OUTCOME MEASURE: Participants' information needs regarding DDIs and perceived importance of questions related to detecting and preventing harm from DDIs. RESULTS: Characteristics of the 100 surveyed participants were as follows: 57% women, 88% white, 96% non-Hispanic, 71% retired, mean (±SD) age 65.2 ± 9.7 years (range 35-86). The number of prescription medications ranged from 2 to 22 (median 7) and the number of over-the-counter (OTC) medications from 1 to 10 (4). The most common concerns cited by participants were identification of interacting medications, seriousness of DDIs, interactions with OTC medications, interactions with foods, exacerbating comorbidities, short- and long-term adverse effects, signs and frequency of DDIs, and how to minimize adverse effects. Statistically significant differences based on gender, number of prescriptions, and number of OTC medications were observed in rankings of the importance of some DDI questions ( P < 0.05). CONCLUSION: Patient-centered DDI education programs should consider addressing the seriousness of DDIs, the effect of DDIs on comorbidities, and interactions with OTC medications and foods and determining methods for identifying, minimizing, and managing DDIs.

Evaluation of a drug-drug interaction: fax alert intervention program.

BACKGROUND: Clinicians often encounter information about drug-drug interactions (DDIs) during clinical practice. This information is found within product information (hardcopy and electronic) and various electronic systems. Prescribers may receive medication-related communications in practice that are distributed by facsimile (fax), mail, or telephone from pharmacies and pharmacy benefit managers (PBMs). The purpose of this study was to determine if near-real time fax alerts for potential drug-drug interactions (PDDIs) would influence prescribing. METHODS: A prospective study, in cooperation with a pharmacy benefit manager (PBM), was conducted targeting 18 clinically important PDDIs. Fax alerts included an individualized letter to the prescriber with a list of the interacting drugs, PDDI evidence summaries with citations, and recommended clinical management strategies. Among the 18 PDDIs, 13 PDDIs could be assessed for prescription therapy changes using pharmacy claims data. A prospective cohort design was used to evaluate changes in prescription dispensing 90-days following a PDDI fax alert. RESULTS: A total of 8,075 fax alerts were sent to prescribers and there were 4,712 alerts for the 13 PDDIs that could be assessed for change using pharmacy claims data. There were 2,019 patients (interventions) for which fax alerts were sent to their prescribers who were matched with a control group consisting of patients with the same PDDIs but for whom no fax alert was sent. Overall, this study found 154 (7.6%) of patients in the fax alert group compared to 132 (6.5%) in the control group had changes in therapy (p = 0.177). CONCLUSIONS: This fax alert intervention program observed no statistically significant differences in prescribing with a fax alert compared to the control group. If PBMs chose to send individualized, evidence-based information to clinicians regarding drug-drug interactions, this study suggests it may not be an effective intervention to mitigate harm.

Recommendations for generating, evaluating, and implementing drug-drug interaction evidence.

In October 2009, a 2-day, multistakeholder, national conference was held in Rockville, Maryland, to discuss and propose methods to improve the drug-drug interaction (DDI) evidence base and its evaluation and integration into clinical decision support (CDS) systems. The conference featured participants representing consumers, health care providers, those responsible for relevant policies and guidelines, and developers and vendors of DDI compendia, databases, and CDS systems. One desired outcome of the conference was to prepare recommendations on critical issues surrounding DDI evidence. A set of recommendations was developed to improve the generation, evaluation, and translation of DDI evidence into CDS systems based on presentations by experts and the supporting literature. These recommendations were reviewed initially by conference moderators, speakers, and Scientific Steering and Planning Committee members, and subsequently by all attendees. The following recommendations were developed to increase patient safety by improving the relevance and assessment of DDI evidence: conduct well-designed studies to determine the incidence, outcomes, and patient-level risk factors for DDIs; use a systematic and transparent process for evaluating the DDI evidence in order to estimate the severity and risks of DDIs; and improve the integration of DDI evidence into electronic CDS. Opportunities exist to improve the DDI evidence base, develop and promote a systematic approach for evaluating the evidence, and integrate this evidence into meaningful CDS.

Impact of a drug-drug interaction intervention on pharmacy and medical students' knowledge and attitudes: a 1-year follow-up.

BACKGROUND: There have been many interventions aimed at improving retention of drug-drug interaction (DDI) knowledge of health care professionals. Much less is known about their retention of such knowledge for extended periods of time after an educational intervention. OBJECTIVES: To evaluate pharmacy and medical students' knowledge retention and attitudes 1 year after participating in an educational session on DDIs. METHODS: This study used a pre-post design with an assessment of DDI knowledge and attitude by pharmacy and medical students before and after the final didactic year of their professional education. The intervention was a 1-hour program. RESULTS: A total of 74 of 193 students (38%) completed the pre, post, and final questionnaire. The median numbers of correctly identified DDIs before the program were 8 and 7 for pharmacy and medical students, respectively, out of a possible score of 15. One year after, the median identification knowledge scores were 12 and 8, respectively, for pharmacy and medical students. The median difference scores of correctly managed DDIs on this evaluation 1 year after the program were -4 and -8 for pharmacy and medical students, respectively (P<.05). CONCLUSION: This study found that the ability to identify important DDIs is poor among both pharmacy and medical students 1 year after being exposed to the educational session.