Quality Measures for Patients at Risk of Adverse Outcomes in the Veterans Health Administration: Expert Panel Recommendations.

Importance: Despite longstanding efforts to improve health care quality for patients with complex needs who are at highest risk for hospitalization or death, to our knowledge, no guidance exists on what constitutes measurable high-quality care for this heterogeneous population. Identifying quality measures that are cross-cutting (ie, relevant to multiple chronic conditions and disease states) may enable health care professionals and health care systems to better design and report on quality improvement efforts for this patient population. Objective: To identify quality measures of care and prioritize quality-of-care concepts in the ambulatory primary care setting for patients in the Veterans Health Administration (VHA) who have complex care needs and are at high risk for adverse outcomes, such as hospitalization or death. Evidence Review: In this expert panel assessment and prioritization, relevant measure concepts for future quality measure development in 3 care categories (assessment, management, and other features of health care) were extracted from a systematic review, conducted from June 2020 to June 2021, of published studies that suggested, evaluated, or used indicators of quality care for patients at high risk of adverse outcomes. Measure concepts associated with single conditions, surgical or other specialty care settings, and inpatient care were excluded. A panel of 14 experts (10 VHA leaders and staff, 2 non-VHA physician investigators, and 2 veterans) discussed and rated the importance of the remaining set of potentially relevant measure concepts using a modified RAND/UCLA Appropriateness Method on January 15, 2021. Measure concepts were rated on a scale of 1 to 9, with 9 being the highest priority. A median rating of 7.5 or greater was used as the cutoff to identify the highest-priority items. Findings: The systematic review identified 519 measure concepts, from which 15 domains and 49 measure concepts were proposed for expert panel consideration. After panel discussions and changes to measure concepts, the expert panel rated 63 measure concepts in 13 domains. The measure concepts with the highest median ratings focused on caregiver availability and support, COVID-19 vaccination, and pneumonia vaccination (all rated 9.0); housing instability (rated 8.5); and physical function, depression symptoms, cognitive impairment, prescription regimen, primary care follow-up after an emergency department visit or hospitalization, and timely transmission of discharge information to primary care (all rated 8.0). Recommendations to improve care included timely assessment of housing instability, caregiver support, physical function, depression symptoms, and cognitive impairment; annual prescription regimen review; coordinated transitions in care; and preventive care including vaccinations. Conclusions and Relevance: The expert panelists identified a parsimonious set of high-priority, evidence-based, cross-cutting quality measure concepts for improving care of patients at high risk for adverse health outcomes in the VHA. These quality measures may inform both future research for patients at high risk and health care system quality improvement.

Mental Health Conditions Among Patients Seeking and Undergoing Bariatric Surgery: A Meta-analysis.

IMPORTANCE: Bariatric surgery is associated with sustained weight loss and improved physical health status for severely obese individuals. Mental health conditions may be common among patients seeking bariatric surgery; however, the prevalence of these conditions and whether they are associated with postoperative outcomes remains unknown. OBJECTIVE: To determine the prevalence of mental health conditions among bariatric surgery candidates and recipients, to evaluate the association between preoperative mental health conditions and health outcomes following bariatric surgery, and to evaluate the association between surgery and the clinical course of mental health conditions. DATA SOURCES: We searched PubMed, MEDLINE on OVID, and PsycINFO for studies published between January 1988 and November 2015. Study quality was assessed using an adapted tool for risk of bias; quality of evidence was rated based on GRADE (Grading of Recommendations Assessment, Development and Evaluation) criteria. FINDINGS: We identified 68 publications meeting inclusion criteria: 59 reporting the prevalence of preoperative mental health conditions (65,363 patients) and 27 reporting associations between preoperative mental health conditions and postoperative outcomes (50,182 patients). Among patients seeking and undergoing bariatric surgery, the most common mental health conditions, based on random-effects estimates of prevalence, were depression (19% [95% CI, 14%-25%]) and binge eating disorder (17% [95% CI, 13%-21%]). There was conflicting evidence regarding the association between preoperative mental health conditions and postoperative weight loss. Neither depression nor binge eating disorder was consistently associated with differences in weight outcomes. Bariatric surgery was, however, consistently associated with postoperative decreases in the prevalence of depression (7 studies; 8%-74% decrease) and the severity of depressive symptoms (6 studies; 40%-70% decrease). CONCLUSIONS AND RELEVANCE: Mental health conditions are common among bariatric surgery patients-in particular, depression and binge eating disorder. There is inconsistent evidence regarding the association between preoperative mental health conditions and postoperative weight loss. Moderate-quality evidence supports an association between bariatric surgery and lower rates of depression postoperatively.

Wrong-Site Surgery, Retained Surgical Items, and Surgical Fires : A Systematic Review of Surgical Never Events.

IMPORTANCE: Serious, preventable surgical events, termed never events, continue to occur despite considerable patient safety efforts. OBJECTIVE: To examine the incidence and root causes of and interventions to prevent wrong-site surgery, retained surgical items, and surgical fires in the era after the implementation of the Universal Protocol in 2004. DATA SOURCES: We searched 9 electronic databases for entries from 2004 through June 30, 2014, screened references, and consulted experts. STUDY SELECTION: Two independent reviewers identified relevant publications in June 2014. DATA EXTRACTION AND SYNTHESIS: One reviewer used a standardized form to extract data and a second reviewer checked the data. Strength of evidence was established by the review team. Data extraction was completed in January 2015. MAIN OUTCOMES AND MEASURES: Incidence of wrong-site surgery, retained surgical items, and surgical fires. RESULTS: We found 138 empirical studies that met our inclusion criteria. Incidence estimates for wrong-site surgery in US settings varied by data source and procedure (median estimate, 0.09 events per 10,000 surgical procedures). The median estimate for retained surgical items was 1.32 events per 10,000 procedures, but estimates varied by item and procedure. The per-procedure surgical fire incidence is unknown. A frequently reported root cause was inadequate communication. Methodologic challenges associated with investigating changes in rare events limit the conclusions of 78 intervention evaluations. Limited evidence supported the Universal Protocol (5 studies), education (4 studies), and team training (4 studies) interventions to prevent wrong-site surgery. Limited evidence exists to prevent retained surgical items by using data-matrix-coded sponge-counting systems (5 pertinent studies). Evidence for preventing surgical fires was insufficient, and intervention effects were not estimable. CONCLUSIONS AND RELEVANCE: Current estimates for wrong-site surgery and retained surgical items are 1 event per 100,000 and 1 event per 10,000 procedures, respectively, but the precision is uncertain, and the per-procedure prevalence of surgical fires is not known. Root-cause analyses suggest the need for improved communication. Despite promising approaches and global Universal Protocol evaluations, empirical evidence for interventions is limited.

Comparative effectiveness of pharmacologic treatments to prevent fractures: an updated systematic review.

BACKGROUND: Osteoporosis is a major contributor to the propensity to fracture among older adults, and various pharmaceuticals are available to treat it. PURPOSE: To update a review about the benefits and harms of pharmacologic treatments used to prevent fractures in adults at risk. DATA SOURCES: Multiple computerized databases were searched between 2 January 2005 and 4 March 2014 for English-language studies. STUDY SELECTION: Trials, observational studies, and systematic reviews. DATA EXTRACTION: Duplicate extraction and assessment of data about study characteristics, outcomes, and quality. DATA SYNTHESIS: From more than 52 000 titles screened, 315 articles were included in this update. There is high-strength evidence that bisphosphonates, denosumab, and teriparatide reduce fractures compared with placebo, with relative risk reductions from 0.40 to 0.60 for vertebral fractures and 0.60 to 0.80 for nonvertebral fractures. Raloxifene has been shown in placebo-controlled trials to reduce only vertebral fractures. Since 2007, there is a newly recognized adverse event of bisphosphonate use: atypical subtrochanteric femur fracture. Gastrointestinal side effects, hot flashes, thromboembolic events, and infections vary among drugs. LIMITATIONS: Few studies have directly compared drugs used to treat osteoporosis. Data in men are very sparse. Costs were not assessed. CONCLUSION: Good-quality evidence supports that several medications for bone density in osteoporotic range and/or preexisting hip or vertebral fracture reduce fracture risk. Side effects vary among drugs, and the comparative effectiveness of the drugs is unclear. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality and RAND Corporation.

Risk of bias: a simulation study of power to detect study-level moderator effects in meta-analysis.

BACKGROUND: There are both theoretical and empirical reasons to believe that design and execution factors are associated with bias in controlled trials. Statistically significant moderator effects, such as the effect of trial quality on treatment effect sizes, are rarely detected in individual meta-analyses, and evidence from meta-epidemiological datasets is inconsistent. The reasons for the disconnect between theory and empirical observation are unclear. The study objective was to explore the power to detect study level moderator effects in meta-analyses. METHODS: We generated meta-analyses using Monte-Carlo simulations and investigated the effect of number of trials, trial sample size, moderator effect size, heterogeneity, and moderator distribution on power to detect moderator effects. The simulations provide a reference guide for investigators to estimate power when planning meta-regressions. RESULTS: The power to detect moderator effects in meta-analyses, for example, effects of study quality on effect sizes, is largely determined by the degree of residual heterogeneity present in the dataset (noise not explained by the moderator). Larger trial sample sizes increase power only when residual heterogeneity is low. A large number of trials or low residual heterogeneity are necessary to detect effects. When the proportion of the moderator is not equal (for example, 25% 'high quality', 75% 'low quality' trials), power of 80% was rarely achieved in investigated scenarios. Application to an empirical meta-epidemiological dataset with substantial heterogeneity (I(2) = 92%, τ(2) = 0.285) estimated >200 trials are needed for a power of 80% to show a statistically significant result, even for a substantial moderator effect (0.2), and the number of trials with the less common feature (for example, few 'high quality' studies) affects power extensively. CONCLUSIONS: Although study characteristics, such as trial quality, may explain some proportion of heterogeneity across study results in meta-analyses, residual heterogeneity is a crucial factor in determining when associations between moderator variables and effect sizes can be statistically detected. Detecting moderator effects requires more powerful analyses than are employed in most published investigations; hence negative findings should not be considered evidence of a lack of effect, and investigations are not hypothesis-proving unless power calculations show sufficient ability to detect effects.

An Epidemiological Model for Examining Marijuana Use over the Life Course.

Trajectories of drug use are usually studied empirically by following over time persons sampled from either the general population (most often youth and young adults) or from heavy or problematic users (e.g., arrestees or those in treatment). The former, population-based samples, describe early career development, but miss the years of use that generate the greatest social costs. The latter, selected populations, help to summarize the most problematic use, but cannot easily explain how people become problem users nor are they representative of the population as a whole. This paper shows how microsimulation can synthesize both sorts of data within a single analytical framework, while retaining heterogeneous influences that can impact drug use decisions over the life course. The RAND Marijuana Microsimulation Model is constructed for marijuana use, validated, and then used to demonstrate how such models can be used to evaluate alternative policy options aimed at reducing use over the life course.