County-Level Factors Associated with Reversal of Insurer-Approved HIV Pre-Exposure Prophylaxis Prescriptions in the United States, 2018.

Identifying county-level factors that influence pre-exposure prophylaxis (PrEP) adherence is critical for ending the HIV epidemic in the United States (US). PrEP primary reversal is a term used to describe patients who do not obtain their prescribed medication from the pharmacy. This study sought to identify factors associated with PrEP reversal at the county level in 2018.

Associations of care continuity and care coordination with the overuse of healthcare services: a nationwide population-based study.

Background: Care continuity and care coordination have received increased attention as important ways of decreasing overuse/low-value care. Prior research has verified an association between care continuity and overuse or an association between care coordination and overuse. However, little is known about the relative influences of care continuity and care coordination on overuse.

Clinician Specialty and HIV PrEP Prescription Reversals and Abandonments.

Importance: Clinicians are a key component of preexposure prophylaxis (PrEP) care. Yet, no prior studies have quantitatively investigated how PrEP adherence differs by clinician specialty.

Objective: To understand the association between prescribing clinician specialty and patients not picking up (reversal/abandonment) their initial PrEP prescription.

Validation of an algorithm to prioritize patients for comprehensive medication management in primary care settings.

Background: Comprehensive medication management (CMM) programs optimize the effectiveness and safety of patients' medication regimens, but CMM may be underutilized. Whether healthcare claims data can identify patients appropriate for CMM is not well-studied.

Aim: Determine the face validity of a claims-based algorithm to prioritize patients who likely need CMM.

Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study.

Background: Patients with unmet social needs and social determinants of health (SDOH) challenges continue to face a disproportionate risk of increased prevalence of disease, health care use, higher health care costs, and worse outcomes. Some existing predictive models have used the available data on social needs and SDOH challenges to predict health-related social needs or the need for various social service referrals. Despite these one-off efforts, the work to date suggests that many technical and organizational challenges must be surmounted before SDOH-integrated solutions can be implemented on an ongoing, wide-scale basis within most US-based health care organizations.

Estimating The Impact Of Out-Of-Pocket Cost Changes On Abandonment Of HIV Pre-Exposure Prophylaxis.

Oral HIV pre-exposure prophylaxis (PrEP) is highly effective for preventing HIV. Several different developments in the US either threaten to increase or promise to decrease PrEP out-of-pocket costs and access in the coming years. In a sample of 58,529 people with a new insurer-approved PrEP prescription, we estimated risk-adjusted percentages of patients who abandoned (did not fill) their initial prescription across six out-of-pocket cost categories.

Risk of Major Bleeding Associated with Concomitant Direct-Acting Oral Anticoagulant and Clopidogrel Use: A Retrospective Cohort Study.

Background And Aim: Combined anticoagulant-antiplatelet therapy is often indicated in adults with cardiovascular disease and atrial fibrillation or venous thromboembolism. The study aim was to assess the comparative risk of bleeding between rivaroxaban and apixaban when combined with clopidogrel.

Methods: We conducted a retrospective cohort study of commercially insured US adults newly treated with a combination of rivaroxaban+clopidogrel or apixaban+clopidogrel (2015-2018) using Merative™ Marketscan Research Databases.

Discontinuation of Buprenorphine Treatment for Opioid Use Disorder During the Coronavirus Disease-2019 Pandemic: A Multilevel Framework.

Background: The coronavirus disease-2019 pandemic has been associated with large increases in opioid-related mortality, yet it is unclear whether specific subpopulations were especially likely to discontinue buprenorphine treatment for opioid use disorder as the pandemic ensued.

Objective: The aim was to assess predictors of buprenorphine discontinuation in the early months of the coronavirus disease-2019 pandemic (April-July 2020) compared with a prepandemic period (April-July 2019).

Design: In each time period, we estimated a multilevel regression models to assess risk of discontinuation in April-July for people who started buprenorphine in January-February.

Assessing the Added Value of Vital Signs Extracted from Electronic Health Records in Healthcare Risk Adjustment Models.

Purpose: Patient vital signs are related to specific health risks and outcomes but are underutilized in the prediction of health-care utilization and cost. To measure the added value of electronic health record (EHR) extracted Body Mass Index (BMI) and blood pressure (BP) values in improving healthcare risk and utilization predictions.

Patients And Methods: A sample of 12,820 adult outpatients from the Johns Hopkins Health System (JHHS) were identified between 2016 and 2017, having high data quality and recorded values for BMI and BP.

Treatment of Opioid Use Disorder With Buprenorphine Among US Adolescents and Young Adults During the Early COVID-19 Pandemic.

Purpose: The COVID-19 pandemic's impact on buprenorphine treatment for opioid use disorder among adolescents and young adults (AYAs) is unknown.

Methods: We used IQVIA Longitudinal Prescription Claims, including US AYAs aged 12-29 with at least 1 buprenorphine fill between January 2018 and August 2020, stratifying by age group and insurance. We compared buprenorphine prescriptions in March-August 2019 to March-August 2020.

Claims-based pharmacy markers for comprehensive medication management program case identification: Validation against concurrent and prospective healthcare costs and utilization.

Background: Three claims-based pharmacy markers (complex, costly and risky medications) were developed to help automatically identify patients for comprehensive medication management.

Objective: To evaluate the association between newly-developed markers and healthcare outcomes.

Methods: This was a two-year retrospective cohort study using PharMetrics Plus patient-level administrative claims in 2014 and 2015.

Comparing and validating medication complexity from insurance claims against electronic health records.

Patient effort to comply with complex medication instructions is known to be related to nonadherence and subsequent medical complications or health care costs. A widely used Medication Regimen Complexity Index (MRCI) has been used with electronic health records (EHRs) to identify patients who could benefit from pharmacist intervention. A similar claims-derived measure may be better suited for clinical decision support, since claims offer a more complete view of patient care and health utilization.

Improving the Prediction of Persistent High Health Care Utilizers: Retrospective Analysis Using Ensemble Methodology.

Background: A small proportion of high-need patients persistently use the bulk of health care services and incur disproportionate costs. Population health management (PHM) programs often refer to these patients as persistent high utilizers (PHUs). Accurate PHU prediction enables PHM programs to better align scarce health care resources with high-need PHUs while generally improving outcomes.

Assessing the Added Value of Blood Pressure Information Derived from Electronic Health Records in Predicting Health Care Cost and Utilization.

Health care providers are increasingly using clinical measures derived from electronic health records (EHRs) for risk stratification and predictive modeling. EHR-specific data elements such as prescriptions, laboratory results, and vital signs have been shown to improve risk prediction models. In this study, the value of EHR-based blood pressure (BP) values was assessed in predicting health care costs (ie, total, medical, and pharmacy) and key utilization end points (ie, hospitalization, emergency department use, and being among the highest utilizers).

Novel population-level proxy measures for suboptimal HIV preexposure prophylaxis initiation and persistence in the USA.

Objective: In the United States (USA), HIV preexposure prophylaxis (PrEP) use is suboptimal. Population-level metrics on PrEP use are limited and focus on prescriptions issued rather than how much prescriptions are picked up. We introduce PrEP reversals, defined as when patients fail to pick up PrEP prescriptions at the pharmacy point-of-sale, as a proxy for PrEP initiation and persistence.

Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data.

Background: A high proportion of health care services are persistently utilized by a small subpopulation of patients. To improve clinical outcomes while reducing costs and utilization, population health management programs often provide targeted interventions to patients who may become persistent high users/utilizers (PHUs). Enhanced prediction and management of PHUs can improve health care system efficiencies and improve the overall quality of patient care.

Dipeptidyl peptidase-4 inhibitor cardiovascular safety in patients with type 2 diabetes, with cardiovascular and renal disease: a retrospective cohort study.

Clinical trials investigating cardiovascular safety of dipeptidyl peptidase-IV inhibitors (DPP-4i) among patients with cardiovascular and renal disease rarely recruit patients with renal impairment, despite associations with increased risk for major adverse cardiovascular events (MACE). We investigated the risk of MACE associated with the use of DPP-4i among these high-risk patients. Using a new-user, retrospective, cohort design, we analyzed 2010-2015 IBM MarketScan Commercial Claims and Encounters for patients with diabetes, comorbid with cardiovascular disease and/or renal impairment.

Assessing the association between area deprivation index on COVID-19 prevalence: a contrast between rural and urban U.S. jurisdictions.

Background: The COVID-19 pandemic has impacted communities differentially, with poorer and minority populations being more adversely affected. Prior rural health research suggests such disparities may be exacerbated during the pandemic and in remote parts of the U.S.

Development of measurable criteria to identify and prioritize patients for inclusion in comprehensive medication management programs within primary care settings.

Pharmacists optimize medication use and ensure the safe and effective delivery of pharmacotherapy to patients using comprehensive medication management (CMM). Identifying and prioritizing individual patients who will most likely benefit from CMM can be challenging. Health systems have far more candidates for CMM than there are clinical pharmacists to provide this service.

Differential impact of mitigation policies and socioeconomic status on COVID-19 prevalence and social distancing in the United States.

Background: The spread of COVID-19 has highlighted the long-standing health inequalities across the U.S. as neighborhoods with fewer resources were associated with higher rates of COVID-19 transmission.

Comparing the Predictive Effects of Patient Medication Adherence Indices in Electronic Health Record and Claims-Based Risk Stratification Models.

Multiple indices are available to measure medication adherence behaviors. Medication adherence measures, however, have rarely been extracted from electronic health records (EHRs) for population-level risk predictions. This study assessed the value of medication adherence indices in improving predictive models of cost and hospitalization.

Early relaxation of community mitigation policies and risk of COVID-19 resurgence in the United States.

This study aimed to assess the impact of coronavirus disease (COVID-19) prevalence in the United States in the week leading to the relaxation of the stay-at-home orders (SAH) on future prevalence across states that implemented different SAH policies. We used data on the number of confirmed COVID-19 cases as of August 21, 2020 on county level. We classified states into four groups based on the 7-day change in prevalence and the state's approach to SAH policy.