Adjusting for Confounding by Neighborhood Using a Proportional Odds Model and Complex Survey Data

In social epidemiology, an individual\u27s neighborhood is considered to be an important determinant of health behaviors, mediators, and outcomes. Consequently, when investigating health disparities, researchers may wish to adjust for confounding by unmeasured neighborhood factors, such as local availability of health facilities or cultural predispositions. With a simple random sample and a binary outcome, a conditional logistic regression analysis that treats individuals within a neighborhood as a matched set is a natural method to use. The authors present a generalization of this method for ordinal outcomes and complex sampling designs. The method is based on a proportional odds model and is very simple to program using standard software such as SAS PROC SURVEYLOGISTIC (SAS Institute Inc., Cary, North Carolina). The authors applied the method to analyze racial/ethnic differences in dental preventative care, using 2008 Florida Behavioral Risk Factor Surveillance System survey data. The ordinal outcome represented time since last dental cleaning, and the authors adjusted for individual-level confounding by gender, age, education, and health insurance coverage. The authors compared results with and without additional adjustment for confounding by neighborhood, operationalized as zip code. The authors found that adjustment for confounding by neighborhood greatly affected the results in this example

Evaluating the Economic Impact of Palliative and End-of-Life Care Interventions on Intensive Care Unit Utilization and Costs from the Hospital and Healthcare System Perspective.

Purpose of report: Understanding the impact of palliative care interventions on intensive care unit (ICU) costs and utilization is critical for demonstrating the value of palliative care. Performing these economic assessments, however, can be challenging. The purpose of this special report is to highlight and discuss important considerations when assessing ICU utilization and costs from the hospital perspective, with the goal of providing recommendations on methods to consider for future analyses. FINDINGS: ICU length of stay (LOS) and associated costs of care are common and important outcome measures, but must be analyzed properly to yield valid conclusions. There is significant variation in costs by day of stay in the ICU with only modest differences between an ICU day at the end of a stay and the first day on the acute care floor; this variation must be appropriately accounted for analytically. Furthermore, reporting direct variable costs, in addition to total ICU costs, is needed to understand short-term and long-term impact of a reduction in LOS. Importantly, incentives for the hospital to realize savings vary depending on reimbursement policies. SUMMARY: ICU utilization and costs are common outcomes in studies evaluating palliative care interventions. Accurate estimation and interpretation are key to understanding the economic implications of palliative care interventions

Combining Adverse Pregnancy and Perinatal Outcomes for Women Exposed to Antiepileptic Drugs During Pregnancy, Using a Latent Trait Model

Background Application of latent variable models in medical research are becoming increasingly popular. A latent trait model is developed to combine rare birth defect outcomes in an index of infant morbidity. Methods This study employed four statewide, retrospective 10-year data sources (1999 to 2009). The study cohort consisted of all female Florida Medicaid enrollees who delivered a live singleton infant during study period. Drug exposure was defined as any exposure to Antiepileptic drugs (AEDs) during pregnancy. Mothers with no AED exposure served as the AED unexposed group for comparison. Four adverse outcomes, birth defect (BD), abnormal condition of new born (ACNB), low birth weight (LBW), and pregnancy and obstetrical complication (PCOC), were examined and combined using a latent trait model to generate an overall severity index. Unidimentionality, local independence, internal homogeneity, and construct validity were evaluated for the combined outcome. Results The study cohort consisted of 3183 mother-infant pairs in total AED group, 226 in the valproate only subgroup, and 43,956 in the AED unexposed group. Compared to AED unexposed group, the rate of BD was higher in both the total AED group (12.8% vs. 10.5%, P \u3c .0001), and the valproate only subgroup (19.6% vs. 10.5%, P  \u3c .0001). The combined outcome was significantly correlated with the length of hospital stay during delivery in both the total AED group (Rho = 0.24, P \u3c .0001) and the valproate only subgroup (Rho = 0.16, P = .01). The mean score for the combined outcome in the total AED group was significantly higher (2.04 ± 0.02 vs. 1.88 ± 0.01, P \u3c .0001) than AED unexposed group, whereas the valproate only subgroup was not. Conclusions Latent trait modeling can be an effective tool for combining adverse pregnancy and perinatal outcomes to assess prenatal exposure to AED, but evaluation of the selected components is essential to ensure the validity of the combined outcome

Reduction in Drinking was Associated With Improved Clinical Outcomes in Women With HIV Infection and Unhealthy Alcohol Use: Results From a Randomized Clinical Trial of Oral Naltrexone Versus Placebo

Background Alcohol consumption is associated with poor health outcomes in women living with HIV (WLWH), but whether medication can help to reduce drinking in non–treatment‐seeking women or whether reduction in drinking improves HIV outcomes is unclear. We conducted a randomized clinical trial (RCT) of daily oral naltrexone (50 mg) versus placebo in WLWH who met criteria for current unhealthy alcohol use. Methods WLWH with current unhealthy alcohol use (\u3e7 drinks/wk or \u3e3 drinks/occasion) were randomly assigned to daily oral naltrexone 50 mg (n = 96) or placebo (n = 98) for 4 months. Drinking outcomes, including the proportion of women who reduced ( Results The participants’ mean age was 48 years, 86% were African American, and 94% were receiving HIV antiretroviral therapy. Among all participants, 89% and 85% completed the 4‐month and 7‐month follow‐ups, respectively. Participants in both groups substantially reduced drinking over time. At 1 and 3 months, naltrexone was associated with a greater reduction in drinking (p \u3c 0.05), but the proportion who reduced/quit drinking at 4 months (52% vs. 45%, p = 0.36) or 7 months (64% in both groups) was not different. HIV viral suppression at follow‐up was significantly better in participants who reduced/quit drinking versus those continuing unhealthy alcohol use at 4 months (72% vs. 53%, p = 0.02) and 7 months (74% vs. 54%, p = 0.02). Conclusions Participating in an RCT to reduce drinking was associated with significant drinking reduction regardless of medication assignment, suggesting that nonmedication aspects of research study participation (e.g., repeated assessments and support from research staff) could be important interventions to help reduce drinking outside of research studies. Drinking reduction was associated with improved HIV viral suppression, providing evidence to support recommendations to avoid unhealthy alcohol use among WLWH

Does an interactive trust-enhanced electronic consent improve patient experiences when asked to share their health records for research? A randomized trial

Objective In the context of patient broad consent for future research uses of their identifiable health record data, we compare the effectiveness of interactive trust-enhanced e-consent, interactive-only e-consent, and standard e-consent (no interactivity, no trust enhancement). Materials and Methods A randomized trial was conducted involving adult participants making a scheduled primary care visit. Participants were randomized into 1 of the 3 e-consent conditions. Primary outcomes were patient-reported satisfaction with and subjective understanding of the e-consent. Secondary outcomes were objective knowledge, perceived voluntariness, trust in medical researchers, consent decision, and time spent using the application. Outcomes were assessed immediately after use of the e-consent and at 1-week follow-up. Results Across all conditions, participants (N = 734) reported moderate-to-high satisfaction with consent (mean 4.3 of 5) and subjective understanding (79.1 of 100). Over 94% agreed to share their health record data. No statistically significant differences in outcomes were observed between conditions. Irrespective of condition, black participants and those with lower education reported lower satisfaction, subjective understanding, knowledge, perceived voluntariness, and trust in medical researchers, as well as spent more time consenting. Conclusions A large majority of patients were willing to share their identifiable health records for research, and they reported positive consent experiences. However, incorporating optional additional information and messages designed to enhance trust in the research process did not improve consent experiences. To improve poorer consent experiences of racial and ethnic minority participants and those with lower education, other novel consent technologies and processes may be valuable

A note on using the estimated versus the known propensity score to estimate the average treatment effect

We provide simple intuition why using the estimated versus known propensity score tends to increase, and never decreases, asymptotic efficiency. When a covariate is independent of response conditional on treatment, using the known score can have greater finite-sample efficiency.

Death or survival, which you measure may affect conclusions: A methodological study

Abstract Background and Aims Considering the opposite outcome—for example, survival instead of death—may affect conclusions about which subpopulation benefits more from a treatment or suffers more from an exposure. Methods For case studies on death following COVID‐19 and bankruptcy following melanoma, we compute and interpret the relative risk, odds ratio, and risk difference for different age groups. Since there is no established effect measure or outcome for either study, we redo these analyses for survival and solvency. Results In a case study on COVID‐19 that ignores confounding, the relative risk of death suggested that 40–49‐year‐old Mexicans with COVID‐19 suffered more from their unprepared healthcare system, using Italy's system as a baseline, than their 60–69‐year‐old counterparts. The relative risk of survival and the risk difference suggested the opposite conclusion. A similar phenomenon occurred in a case study on bankruptcy following melanoma treatment. Conclusion To increase transparency around this paradox, researchers reporting one outcome should note if considering the opposite outcome would yield different conclusions. When possible, researchers should also report or estimate underlying risks alongside effect measures