Use of Sequential Hot-Deck Imputation for Missing Health Care Systems Data for Population Health Research.

Electronic medical record (EMR) data present many opportunities for population health research. The use of EMR data for population risk models can be impeded by the high proportion of missingness in key patient variables. Common approaches like complete case analysis and multiple imputation may not be appropriate for some population health initiatives that require a single, complete analytic data set. In this study, we demonstrate a sequential hot-deck imputation (HDI) procedure to address missingness in a set of cardiometabolic measures in an EMR data set. We assessed the performance of sequential HDI within the individual variables and a commonly used composite risk score. A data set of cardiometabolic measures based on EMR data from 2 large urban hospitals was used to create a benchmark data set with simulated missingness. Sequential HDI was applied, and the resulting data were used to calculate atherosclerotic cardiovascular disease risk scores. The performance of the imputation approach was assessed using a set of metrics to evaluate the distribution and validity of the imputed data. Of the 567,841 patients, 65% had at least 1 missing cardiometabolic measure. Sequential HDI resulted in the distribution of variables and risk scores that reflected those in the simulated data while retaining correlation. When stratified by age and sex, risk scores were plausible and captured patterns expected in the general population. The use of sequential HDI was shown to be a suitable approach to multivariate missingness in EMR data. Sequential HDI could benefit population health research by providing a straightforward, computationally nonintensive approach to missing EMR data that results in a single analytic data set.

Protection of Two and Three mRNA Vaccine Doses Against Severe Outcomes Among Adults Hospitalized With COVID-19-VISION Network, August 2021 to March 2022.

BACKGROUND: We assessed coronavirus disease 2019 (COVID-19) vaccination impact on illness severity among adults hospitalized with COVID-19, August 2021-March 2022. METHODS: We evaluated differences in intensive care unit (ICU) admission, in-hospital death, and length of stay among vaccinated (2 or 3 mRNA vaccine doses) versus unvaccinated patients aged ≥18 years hospitalized for ≥24 hours with COVID-19-like illness and positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) molecular testing. We calculated odds ratios (ORs) for ICU admission and death and subdistribution hazard ratios (SHR) for time to hospital discharge adjusted for age, geographic region, calendar time, and local virus circulation. RESULTS: We included 27 149 SARS-CoV-2-positive hospitalizations. During both Delta- and Omicron-predominant periods, protection against ICU admission was strongest among 3-dose vaccinees compared with unvaccinated patients (Delta OR, 0.52 [95% CI, .28-.96]; Omicron OR, 0.69 [95% CI, .54-.87]). During both periods, risk of in-hospital death was lower among vaccinated compared with unvaccinated patients but ORs overlapped across vaccination strata. We observed SHR >1 across all vaccination strata in both periods indicating faster discharge for vaccinated patients. CONCLUSIONS: COVID-19 vaccination was associated with lower rates of ICU admission and in-hospital death in both Delta and Omicron periods compared with being unvaccinated.

Influenza vaccine effectiveness against influenza-A-associated emergency department, urgent care, and hospitalization encounters among U.S. adults, 2022-2023.

BACKGROUND: The 2022-2023 United States influenza season had unusually early influenza activity with high hospitalization rates. Vaccine-matched A(H3N2) viruses predominated, with lower levels of A(H1N1)pdm09 activity also observed. METHODS: Using the test-negative design, we evaluated influenza vaccine effectiveness (VE) during the 2022-2023 season against influenza-A-associated emergency department/urgent care (ED/UC) visits and hospitalizations from October 2022-March 2023 among adults (age ≥18 years) with acute respiratory illness (ARI). VE was estimated by comparing odds of seasonal influenza vaccination among case-patients (influenza A test-positive by molecular assay) and controls (influenza test-negative), applying inverse-propensity-to-be-vaccinated weights. RESULTS: The analysis included 85,389 ED/UC ARI encounters (17.0% influenza-A-positive; 37.8% vaccinated overall) and 19,751 hospitalizations (9.5% influenza-A-positive; 52.8% vaccinated overall). VE against influenza-A-associated ED/UC encounters was 44% (95% confidence interval [95%CI]: 40-47%) overall and 45% and 41% among adults aged 18-64 and ≥65 years, respectively. VE against influenza-A-associated hospitalizations was 35% (95%CI: 27-43%) overall and 23% and 41% among adults aged 18-64 and ≥65 years, respectively. CONCLUSIONS: VE was moderate during the 2022-2023 influenza season, a season characterized with increased burden of influenza and co-circulation with other respiratory viruses. Vaccination is likely to substantially reduce morbidity, mortality, and strain on healthcare resources.

Adapting a clinical decision support system to improve identification of pediatric hypertension in a rural health system: Design of a pragmatic trial.

BACKGROUND: Identifying hypertension (HTN) early is crucial in preventing and lowering the long-term risk of heart disease, yet HTN in children often goes undiagnosed. An electronic health record linked, web-based clinical decision support (CDS) called PedsBP can help address this care gap and has been previously shown to increase recognition of HTN by primary care clinicians. OBJECTIVES: To adapt the PedsBP tool for use in a mostly rural health system and then to evaluate the effectiveness of PedsBP for repeat of hypertensive level blood pressure (BP) measurements and HTN recognition among youth 6-17 years of age in primary care settings, comparing low-intensity and high-intensity implementation approaches. METHODS AND DESIGN: PedsBP was evaluated through a pragmatic, clinic-randomized trial. The tool was piloted in 2 primary care clinics and modified prior to the full trial. Forty community-based, primary care clinics (or clusters of clinics) were randomly allocated in a 1:1:1 ratio to usual care, low-intensity implementation (CDS only), or high-intensity implementation (CDS plus in-person training, monthly use reports, and ongoing communication between study staff and clinics). Accrual of eligible patients started on August 1, 2022 and will continue for 18 months. Primary outcomes include repeating hypertensive level BP measurements at office visits and clinical recognition of HTN. Secondary outcomes include lifestyle counseling, dietician referral, and BP at follow-up. CONCLUSION: This report focuses on the design and feasibility of adapting and implementing PedsBP in a rural primary care setting. The trial and analysis are ongoing with main results expected in mid-2024.

Patient Perspectives on Opioid Risk Discussions in Primary Care.

Purpose: Both patients and clinicians have described discussions of potential opioid risks as challenging. This study's goal was to understand patient perspectives on discussing opioid risks with primary care clinicians (PCCs). Methods: Patients identified to be at elevated risk for problems with opioids (ie, opioid use disorder [OUD] diagnosis, taking a medication for OUD, or having ≥3 opioid prescriptions in the last year) were recruited from an integrated, Upper Midwest health system to participate in semi-structured qualitative interviews. Interview questions aimed to better understand patient views on conversations about opioid risks with PCCs and perceptions of OUD screening and treatment in primary care. Interviews were analyzed using an inductive thematic analysis approach. Results: A total of 20 patients participated (mean age: 53.5 years; 65% male). Six themes emerged: 1) archetypes of patient relationships with opioids (long-term opioid use, acute opioid use, OUD in treatment, OUD no treatment) require different approaches in discussing opioid risks; 2) patients may develop their own archetypes about PCCs and opioids; 3) these archetypes may help guide how conversations about opioids are conducted (eg, PCC demeanor, terminology); 4) most patients believe that primary care is an appropriate setting for opioid risk discussions; 5) patients may have limited awareness of the availability and value of overdose rescue medications; and 6) handouts are more acceptable if perceived to come from the PCC's assessment instead of a computer. Conclusions: Results suggest that patients generally perceive discussing opioid risks with PCCs acceptable. PCCs should tailor opioid risk conversations to patients' specific situations and needs.