Publications

IMPORTANCE: Metrics that detect low-value care in common forms of health care data, such as administrative claims or electronic health records, primarily focus on tests and procedures but not on medications, representing a major gap in the ability to systematically measure low-value prescribing.

OBJECTIVE: To develop a scalable and broadly applicable metric that contains a set of quality indicators (EVOLV-Rx) for use in health care data to detect and reduce low-value prescribing among older adults and that is informed by diverse stakeholders' perspectives.

DESIGN, SETTING, AND PARTICIPANTS: This qualitative study used an online modified-Delphi method to convene an expert panel of 15 physicians and pharmacists. This panel, comprising clinicians, health system leaders, and researchers, was tasked with rating and discussing candidate low-value prescribing practices that were derived from medication safety criteria; peer-reviewed literature; and qualitative studies of patient, caregiver, and physician perspectives. The RAND ExpertLens online platform was used to conduct the activities of the panel. The panelists were engaged for 3 rounds between January 1 and March 31, 2021.

MAIN OUTCOMES AND MEASURES: Panelists used a 9-point Likert scale to rate and then discuss the scientific validity and clinical usefulness of the criteria to detect low-value prescribing practices. Candidate low-value prescribing practices were rated as follows: 1 to 3, indicating low validity or usefulness; 3.5 to 6, uncertain validity or usefulness; and 6.5 to 9, high validity or usefulness. Agreement among panelists and the degree of scientific validity and clinical usefulness were assessed using the RAND/UCLA (University of California, Los Angeles) Appropriateness Method.

RESULTS: Of the 527 low-value prescribing recommendations identified, 27 discrete candidate low-value prescribing practices were considered for inclusion in EVOLV-Rx. After round 1, 18 candidate practices were rated by the panel as having high scientific validity and clinical usefulness (scores of ≥6.5). After round 2 panel deliberations, the criteria to detect 19 candidate practices were revised. After round 3, 18 candidate practices met the inclusion criteria, receiving final median scores of 6.5 or higher for both scientific validity and clinical usefulness. Of those practices that were not included in the final version of EVOLV-Rx, 3 received high scientific validity (scores ≥6.5) but uncertain clinical usefulness (scores <6.5) ratings, whereas 6 received uncertain scientific validity rating (scores <6.5).

CONCLUSIONS AND RELEVANCE: This study culminated in the development of EVOLV-Rx and involved a panel of experts who identified the 18 most salient low-value prescribing practices in the care of older adults. Applying EVOLV-Rx may enhance the detection of low-value prescribing practices, reduce polypharmacy, and enable older adults to receive high-value care across the full spectrum of health services.

OBJECTIVE: Guidelines advocate against tight glycemic control in older nursing home (NH) residents with advanced dementia (AD) or limited life expectancy (LLE). We evaluated the effect of deintensifying diabetes medications with regard to all-cause emergency department (ED) visits, hospitalizations, and death in NH residents with LLE/AD and tight glycemic control.

RESEARCH DESIGN AND METHODS: We conducted a national retrospective cohort study of 2,082 newly admitted nonhospice veteran NH residents with LLE/AD potentially overtreated for diabetes (HbA1c ≤7.5% and one or more diabetes medications) in fiscal years 2009-2015. Diabetes treatment deintensification (dose decrease or discontinuation of a noninsulin agent or stopping insulin sustained ≥7 days) was identified within 30 days after HbA1c measurement. To adjust for confounding, we used entropy weights to balance covariates between NH residents who deintensified versus continued medications. We used the Aalen-Johansen estimator to calculate the 60-day cumulative incidence and risk ratios (RRs) for ED or hospital visits and deaths.

RESULTS: Diabetes medications were deintensified for 27% of residents. In the subsequent 60 days, 28.5% of all residents were transferred to the ED or acute hospital setting for any cause and 3.9% died. After entropy weighting, deintensifying was not associated with 60-day all-cause ED visits or hospitalizations (RR 0.99 [95% CI 0.84, 1.18]) or 60-day mortality (1.52 [0.89, 2.81]).

CONCLUSIONS: Among NH residents with LLE/AD who may be inappropriately overtreated with tight glycemic control, deintensification of diabetes medications was not associated with increased risk of 60-day all-cause ED visits, hospitalization, or death.

INTRODUCTION: Evidence suggests that U.S. dentists prescribe opioids excessively. There are limited national data on recent trends in opioid prescriptions by U.S. dentists. In this study, we examined trends in opioid prescribing by general dentists and dental specialists in the U.S. from 2012 to 2019.

METHODS: Dispensed prescriptions for oral opioid analgesics written by dentists were identified from IQVIA Longitudinal Prescription Data from January 2012 through December 2019. Autoregressive integrated moving average and joinpoint regression models described monthly population-based prescribing rates (prescriptions/100,000 individuals), dentist-based prescribing rates (prescriptions/1,000 dentists), and opioid dosages (mean daily morphine milligram equivalents/day). All analyses were performed in 2020.

RESULTS: Over the 8 years, dentists prescribed >87.2 million opioid prescriptions. Population- and dentist-based prescribing rates declined monthly by -1.97 prescriptions/100,000 individuals (95% CI= -9.98, -0.97) and -39.12 prescriptions/1,000 dentists (95% CI= -58.63, -17.65), respectively. Opioid dosages declined monthly by -0.08 morphine milligram equivalents/day (95% CI= -0.13, -0.04). Joinpoint regression identified 4 timepoints (February 2016, May 2017, December 2018, and March 2019) at which monthly prescribing rate trends were often decreasing in greater magnitude than those in the previous time segment.

CONCLUSIONS: Following national trends, dentists became more conservative in prescribing opioids. A greater magnitude of decline occurred post 2016 following the implementation of strategies aimed to further regulate opioid prescribing. Understanding the factors that influence prescribing trends can aid in development of tailored resources to encourage and support a conservative approach by dentists, to prescribing opioids.

BACKGROUND: Low-value prescribing may result in adverse patient outcomes and increased medical expenditures. Clinicians' baseline strategies for navigating patient encounters involving low-value prescribing remain poorly understood, making it challenging to develop acceptable deprescribing interventions. Our objective was to characterize primary care physicians' (PCPs) approaches to reduce low-value prescribing in older adults through qualitative analysis of clinical scenarios.

METHODS: As part of an overarching qualitative study on low-value prescribing, we presented two clinical scenarios involving potential low-value prescribing during semi-structured interviews of 16 academic and community PCPs from general internal medicine, family medicine and geriatrics who care for patients aged greater than or equal to 65. We conducted a qualitative analysis of their responses to identify salient themes related to their approaches to prescribing, deprescribing, and meeting patients' expectations surrounding low-value prescribing.

RESULTS: We identified three key themes. First, when deprescribing, PCPs were motivated by their desire to mitigate patient harms and follow medication safety and deprescribing guidelines. Second, PCPs emphasized good communication with patients when navigating patient encounters related to low-value prescribing; and third, while physicians emphasized the importance of shared decision-making, they prioritized patients' well-being over satisfying their expectations.

CONCLUSIONS: When presented with real-life clinical scenarios, PCPs in our cohort sought to reduce low-value prescribing in a guideline-concordant fashion while maintaining good communication with their patients. This was driven primarily by a desire to minimize the potential for harm. This suggests that barriers other than clinician knowledge may be driving ongoing use of low-value medications in clinical practice.

Although nonsteroidal anti inflammatory drugs are superior to opioids in dental pain management, opioids are still prescribed for dental pain in the United States. Little is known about the serious adverse outcomes of short-acting opioids within the context of dental prescribing. The objective of this study was to evaluate adverse outcomes and persistent opioid use (POU) after opioid prescriptions by dentists, based on whether opioids were overprescribed or within recommendations. A cross-sectional analysis of adults with a dental visit and corresponding opioid prescription (index) from 2011 to 2018 within a nationwide commercial claims database was conducted. Opioid overprescribing was defined as >120 morphine milligram equivalents per Centers for Disease Control and Prevention guidelines. Generalized estimating equation models were used to assess adverse outcomes (emergency department visits, hospitalizations, newly diagnosed substance use disorder, naloxone administration, or death within 30 days from index) and POU (≥1 prescription 4-90 days postindex). Predicted probabilities are reported. Of 633,387 visits, 2.6% experienced an adverse outcome and 16.6% had POU. Adverse outcome risk was not different whether opioids were overprescribed or within recommendations (predicted probability 9.0%, confidence interval [CI]: 8.0%-10.2% vs 9.1%, CI: 8.1-10.3), but POU was higher when opioids were overprescribed (predicted probability 27.4%, CI: 26.1%-28.8% vs 25.2%, CI: 24.0%-26.5%). Visits associated with mild pain and those with substance use disorders had the highest risk of both outcomes. Findings from this study demonstrate that dental prescribing of opioids was associated with adverse outcomes and POU, even when prescriptions were concordant with guidelines. Additional efforts are required to improve analgesic prescribing in dentistry, especially in groups at high risk of opioid-related adverse outcomes.

INTRODUCTION: Nonopioid analgesics are more effective for most oral pain, but data suggest that dental prescribing of opioids is excessive. This study evaluates the extent to which opioids exceed recommendations and the characteristics associated with opioid overprescribing by Veterans Health Administration dentists.

METHODS: This was a national cross-sectional study of Veterans' dental visits from 2015 to 2018. Overprescribing was defined per national guidelines as >120 morphine milligram equivalents (primary outcome). The association of dental visit and patient demographic and medical characteristics was modeled with overprescribing (defined as >120 morphine milligram equivalents) using Poisson regression with clustering by facility and patient. A secondary analysis assessed opioid prescriptions >3 days' supply. The dates of analysis were January 2020‒May 2021.

RESULTS: Of the 196,595 visits, 28.7% exceeded 120 morphine milligram equivalents. Friday visits and people with chronic oral pain or substance misuse were associated with a higher prevalence of overprescribing. Women, older Veterans, and Black and Latinx Veterans were less likely to be overprescribed than men, younger Veterans, and White Veterans, respectively. Routine dental visits had a higher prevalence of opioid overprescribing than invasive visits. Opioid overprescribing decreased over time. White Veterans were more likely to receive oxycodone and hydrocodone, whereas people of Black race and Latinx ethnicity were more likely to receive codeine and tramadol. In the secondary analysis, 68.5% of opioid prescriptions exceeded a 3-day supply.

CONCLUSIONS: Nearly 1 in 3 opioids prescribed by Veterans Health Administration dentists exceed guidelines. Prescribing higher potency and quantities of opioids, especially on Fridays and to certain demographic groups, should be addressed as part of dental opioid stewardship programs.

Suicide is a leading cause of death in the US. Patients with pain conditions have higher suicidal risks. In a systematic review searching observational studies from multiple sources (e.g., MEDLINE) from 1 January 2000-12 September 2020, we evaluated existing suicide prediction models' (SPMs) performance and identified risk factors and their derived data sources among patients with pain conditions. The suicide-related outcomes included suicidal ideation, suicide attempts, suicide deaths, and suicide behaviors. Among the 87 studies included (with 8 SPM studies), 107 suicide risk factors (grouped into 27 categories) were identified. The most frequently occurring risk factor category was depression and their severity (33%). Approximately 20% of the risk factor categories would require identification from data sources beyond structured data (e.g., clinical notes). For 8 SPM studies (only 2 performing validation), the reported prediction metrics/performance varied: C-statistics (n = 3 studies) ranged 0.67-0.84, overall accuracy(n = 5): 0.78-0.96, sensitivity(n = 2): 0.65-0.91, and positive predictive values(n = 3): 0.01-0.43. Using the modified Quality in Prognosis Studies tool to assess the risk of biases, four SPM studies had moderate-to-high risk of biases. This systematic review identified a comprehensive list of risk factors that may improve predicting suicidal risks for patients with pain conditions. Future studies need to examine reasons for performance variations and SPM's clinical utility.

BACKGROUND: The Veterans Health Administration (VHA) developed the Stratification Tool for Opioid Risk Mitigation (STORM) dashboard to assist in identifying Veterans at risk for adverse opioid overdose or suicide-related events. In 2018, a policy was implemented requiring VHA facilities to complete case reviews of Veterans identified by STORM as very high risk for adverse events. Nationally, facilities were randomized in STORM implementation to four arms based on required oversight and by the timing of an increase in the number of required case reviews. To help evaluate this policy intervention, we aimed to (1) identify barriers and facilitators to implementing case reviews; (2) assess variation across the four arms; and (3) evaluate associations between facility characteristics and implementation barriers and facilitators.

METHOD: Using the Consolidated Framework for Implementation Research (CFIR), we developed a semi-structured interview guide to examine barriers to and facilitators of implementing the STORM policy. A total of 78 staff from 39 purposefully selected facilities were invited to participate in telephone interviews. Interview transcripts were coded and then organized into memos, which were rated using the -2 to + 2 CFIR rating system. Descriptive statistics were used to evaluate the mean ratings on each CFIR construct, the associations between ratings and study arm, and three facility characteristics (size, rurality, and academic detailing) associated with CFIR ratings. We used the mean CFIR rating for each site to determine which constructs differed between the sites with highest and lowest overall CFIR scores, and these constructs were described in detail.

RESULTS: Two important CFIR constructs emerged as barriers to implementation: Access to knowledge and information and Evaluating and reflecting. Little time to complete the CASE reviews was a pervasive barrier. Sites with higher overall CFIR scores showed three important facilitators: Leadership engagement, Engaging, and Implementation climate. CFIR ratings were not significantly different between the four study arms, nor associated with facility characteristics.Plain Language Summary: The Veterans Health Administration (VHA) created a tool called the Stratification Tool for Opioid Risk Mitigation dashboard. This dashboard shows Veterans at risk for opioid overdose or suicide-related events. In 2018, a national policy required all VHA facilities to complete case reviews for Veterans who were at high risk for these events. To evaluate this policy implementation, 78 staff from 39 facilities were interviewed. The Consolidated Framework for Implementation Research (CFIR) implementation framework was used to create the interview. Interview transcripts were coded and organized into site memos. The site memos were rated using CFIR's -2 to +2 rating system. Ratings did not differ for four study arms related to oversight and timing. Ratings were not associated with facility characteristics. Leadership, engagement and implementation climate were the strongest facilitators for implementation. Lack of time, knowledge, and feedback were important barriers.