Relationship Between Depression and/or Anxiety and Hospital Readmission Among Women After Childbirth

ObjectiveTo examine the relationship between depression and/or anxiety and any psychiatric diagnosis and readmission after childbirth.DesignCross-sectional analysis of administrative data from patient discharge records.SettingUrban academic medical center in the northeastern United States.ParticipantsWomen admitted for childbirth (N = 17,905).MethodsDifferences among participants with and without depression and/or anxiety present on admission were compared using t tests and chi-square tests. Risk-adjusted logistic regression models were used to examine the effects of depression and/or anxiety and any psychiatric diagnosis on 7-, 30-, 60-, 90-, and 180-day readmissions after childbirth.ResultsSignificant differences were noted between participants with (n = 1,169) and without (n = 16,736) depression and/or anxiety. Participants with these diagnoses had a higher mean age and a longer mean length of stay during hospitalization for childbirth. A greater proportion of these participants were White, were single, had cesarean births, and were discharged with home health services. The presence of depression and/or anxiety was not significantly associated with readmission. The effect of having any psychiatric diagnosis was significantly associated with a greater risk of readmission at 7 (odds ratio [OR] = 1.51, p = .100), 30 (OR = 1.45, p = .030), 60 (OR = 1.45, p = .026), 90 (OR = 1.56, p = .004), and 180 days (OR =1.74, p < .001) following discharge after childbirth.ConclusionIn this sample, women with a psychiatric diagnosis, but not depression and/or anxiety alone, were at increased risk for readmission after childbirth.     

Medicare's hospital readmissions reduction program and the rise in observation stays

Objective

To evaluate whether Medicare's Hospital Readmissions Reduction Program (HRRP) is associated with increased observation stay use.

Data Sources and Study Setting

A nationally representative sample of fee-for-service Medicare claims, January 2009–September 2016.

Study Design

Using a difference-in-difference (DID) design, we modeled changes in observation stays as a proportion of total hospitalizations, separately comparing the initial (acute myocardial infarction, pneumonia, heart failure) and subsequent (chronic obstructive pulmonary disease) target conditions with a control group of nontarget conditions. Each model used 3 time periods: baseline (15 months before program announcement), an intervening period between announcement and implementation, and a 2-year post-implementation period, with specific dates defined by HRRP policies.

Data Collection/Extraction Methods

We derived a 20% random sample of all hospitalizations for beneficiaries continuously enrolled for 12 months before hospitalization (N = 7,162,189).

Principal Findings

Observation stays increased similarly for the initial HRRP target and nontarget conditions in the intervening period (0.01% points per month [95% CI −0.01, 0.3]). Post-implementation, observation stays increased significantly more for target versus nontarget conditions, but the difference is quite small (0.02% points per month [95% CI 0.002, 0.04]). Results for the COPD analysis were statistically insignificant in both policy periods.

Conclusions

The increase in observation stays is likely due to other factors, including audit activity and clinical advances.     

Association between 30-day readmission rates and health information technology capabilities in US hospitals

Health information technology (IT) is often proposed as a solution to fragmentation of care, and has been hypothesized to reduce readmission risk through better information flow. However, there are numerous distinct health IT capabilities, and it is unclear which, if any, are associated with lower readmission risk.To identify the specific health IT capabilities adopted by hospitals that are associated with hospital-level risk-standardized readmission rates (RSRRs) through path analyses using structural equation modeling.This STROBE-compliant retrospective cross-sectional study included non-federal U.S. acute care hospitals, based on their adoption of specific types of health IT capabilities self-reported in a 2013 American Hospital Association IT survey as independent variables. The outcome measure included the 2014 RSRRs reported on Hospital Compare website.A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis, and corroborated by confirmatory factor analysis. Subsequent path analysis using Structural equation modeling revealed that a one-point increase in the hospital adoption of patient engagement capability latent scores (median path coefficient ß = −0.086; 95% Confidence Interval, −0.162 to −0.008), including functionalities like direct access to the electronic health records, would generally lead to a decrease in RSRRs by 0.086%. However, computerized hospital discharge and information exchange capabilities with other inpatient and outpatient providers were not associated with readmission rates.These findings suggest that improving patient access to and use of their electronic health records may be helpful in improving hospital performance on readmission; however, computerized hospital discharge and information exchange among clinicians did not seem as beneficial – perhaps because of the quality or timeliness of information transmitted. Future research should use more recent data to study, not just adoption of health IT capabilities, but also whether their usage is associated with lower readmission risk. Understanding which capabilities impact readmission risk can help policymakers and clinical stakeholders better focus their scarce resources as they invest in health IT to improve care delivery.     

A roadmap for comparing readmission policies with application to Denmark,England, Germany and the United States

Hospital readmissions receive increasing interest from policy makers because reducing unnecessary readmissions has the potential to simultaneously improve quality and save costs. This paper reviews readmission policies in Denmark, England, Germany and the United States (Medicare system). The suggested roadmap enables researchers and policy makers to systematically compare and analyse readmission policies. We find considerable differences across countries. In Germany, the readmission policy aims to avoid unintended consequences of the introduction of DRG-based payment; it focuses on readmissions of individual patients and hospitals receive only one DRG-based payment for both the initial and the re-admission. In Denmark, England and the US readmission policies aim at quality improvement and focus on readmission rates. In Denmark, readmission rates are publicly reported but payments are not adjusted in relation to readmissions. In England and the US, financial incentives penalise hospitals with readmission rates above a certain benchmark. In England, this benchmark is defined through local clinical review, while it is based on the risk-adjusted national average in the US. At present, not enough evidence exists to give recommendations on the optimal design of readmission policies. The roadmap can be a tool for systematically assessing how elements of other countries’ readmission policies can potentially be adopted to improve national policies.     

An Attempt to Stem the Tide: Exploring the Effect of a 90-Day Transitional Care Intervention on Readmissions to an Acute Male Psychiatric Unit in South Africa

Introduction

Pressure on inpatient beds often results in premature discharges, which may precipitate early readmission. This has prompted an increased interest in transitional care interventions to bridge the gap between in- and outpatient care to reduce such readmissions. Our study aimed to assess the effect of a Transitional Care Service (TCS) on readmission rates in a high pressure inpatient service which utilizes a premature discharge policy to address bed pressures.