Search

Floating Catchment Area (FCA) methods are a popular tool to investigate accessibility to public facilities, in particular health care services. FCA approaches are attractive because, unlike other accessibility measures, they take into account the potential for congestion of facilities. This is done by 1) considering the population within the catchment area of a facility to calculate a variable that measures level of service, and then 2) aggregating the level of service by population centers subject to catchment area constraints. In this paper we discuss an effect of FCA approaches, an artifact that we term demand and level of service inflation. These artifacts are present in previous implementations of FCA methods. We argue that inflation makes interpretation of estimates of accessibility difficult, which has possible deleterious consequences for decision making. Next, we propose a simple and intuitive approach to proportionally allocate demandand and level of service in FCA calculations. The approach is based on a standardization of the impedance matrix, similar to approaches popular in the spatial statistics and econometrics literature. The result is a more intiuitive measure of accessibility that 1) provides a local version of the provider-to-population ratio; and 2) preserves the level of demand and the level of supply in a system. We illustrate the relevant issues with some examples, and then empirically by means of a case study of accessibility to family physicians in the Hamilton Census Metropolitan Area (CMA), in Ontario, Canada. Results indicate that demand and supply inflation/deflation affect the interpretation of accessibility analysis using existing FCA methods, and that the proposed adjustment can lead to more intuitive results. [ABSTRACT FROM AUTHOR]

Background: Physician Orders for Life-Sustaining Treatment (POLST) programs have expanded rapidly, but evaluating their impact on hospital care is challenging. Objectives: To demonstrate how careful study design can reveal POLST’s impact at hospital admission and why analyses of state registry data are unlikely to capture POLST’s effects. Design: Prospective cohort study. Setting and participants: Adult in-patients with Do Not Intubate and/or Do Not Resuscitate (DNR/I) orders in the electronic medical record at the time of discharge from Johns Hopkins Hospital over 18 months. For patients with unplanned readmissions within 30 days, records were reviewed to determine if a Maryland Medical Order for Life-Sustaining Treatment (MOLST) form was presented and for the time from readmission to a DNR/I order in the EMR. Analyses were stratified by whether patients could communicate or were accompanied by a proxy at readmission. Results: Among 1,507 patients with DNR/I orders at discharge, 124 (8%) had unplanned readmissions, 112 (90%) could communicate or were accompanied by a proxy at readmission, and 12 (10%) could not communicate and were unaccompanied. For patients who were unaccompanied and could not communicate, MOLST significantly decreased the median time from readmission to DNR/I order (1.2 vs 27.1 hours, P = .001), but this association was greatly attenuated among patients who could communicate or were accompanied by a proxy (16.4 vs 25.4 hours P = .10). Conclusion: Among patients who wanted to avoid intubation and/or CPR, MOLST forms were protective when the patient was unaccompanied by a healthcare proxy at admission and could not communicate. Fewer than 10% of patients met these criteria during unplanned readmissions, and state registry data does not allow this sub-population to be identified. [ABSTRACT FROM AUTHOR]

Background: Racial/ethnic disparities in rates of influenza vaccinations in the US remain an issue even among those with access, no out-of-pocket costs, and after adjusting for confounders. We used an approach called the Oaxaca-Blinder (OB) decomposition method to ascertain the contribution of covariates individually and in aggregate to the racial disparity in influenza vaccination. Methods: We included members > = 18 years of age as of 05/01/2014 with continuous enrollment through 04/30/2015. Influenza vaccination was defined by diagnosis, procedure, or medication codes, or documentation in the immunization table. Characteristics were reported by race. Logistic regression models estimated the odds of vaccination associated with: (1) race; and (2) covariates stratified by race. The Oaxaca-Blinder (OB) method calculated the contribution of covariates to the difference or disparity in vaccination between Blacks and Whites. Results: We found that among adults, 44% were vaccinated; 55% were Black; and 45% were White. Black members have 42% lower odds of vaccination than White members. The contribution of the differences in the average value of the study covariates between Black and White members (the OB covariate effect) accounted for 29% of the racial disparity. The contributions to the total White-Black disparity in vaccination included: age (16%), neighborhood median income (11%), and registration on the online patient portal (13%). The contribution of the differences in how the covariates impact vaccination (OB coefficient effect) accounted for 71% of the disparity in vaccination between Blacks and Whites. Conclusion: In conclusion, equalizing average covariate values in Blacks and Whites could reduce the racial disparity in influenza vaccination by 29%. For health system vaccine campaigns, improving registration on the patient portal may be a target component of an effective system-level strategy to reduce racial disparities in vaccination. Additional information on patient-centered factors could further improve the value of the OB approach. [ABSTRACT FROM AUTHOR]