Association of Changing Hospital Readmission Rates With Mortality Rates After Hospital Discharge

Abstract

Importance: The Affordable Care Act has led to US national reductions in hospital 30-day readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Whether readmission reductions have had the unintended consequence of increasing mortality after hospitalization is unknown.

Objective: To examine the correlation of paired trends in hospital 30-day readmission rates and hospital 30-day mortality rates after discharge.

Design, setting, and participants: Retrospective study of Medicare fee-for-service beneficiaries aged 65 years or older hospitalized with HF, AMI, or pneumonia from January 1, 2008, through December 31, 2014.

Exposure: Thirty-day risk-adjusted readmission rate (RARR).

Main outcomes and measures: Thirty-day RARRs and 30-day risk-adjusted mortality rates (RAMRs) after discharge were calculated for each condition in each month at each hospital in 2008 through 2014. Monthly trends in each hospital's 30-day RARRs and 30-day RAMRs after discharge were examined for each condition. The weighted Pearson correlation coefficient was calculated for hospitals' paired monthly trends in 30-day RARRs and 30-day RAMRs after discharge for each condition.

Results: In 2008 through 2014, 2 962 554 hospitalizations for HF, 1 229 939 for AMI, and 2 544 530 for pneumonia were identified at 5016, 4772, and 5057 hospitals, respectively. In January 2008, mean hospital 30-day RARRs and 30-day RAMRs after discharge were 24.6% and 8.4% for HF, 19.3% and 7.6% for AMI, and 18.3% and 8.5% for pneumonia. Hospital 30-day RARRs declined in the aggregate across hospitals from 2008 through 2014; monthly changes in RARRs were -0.053% (95% CI, -0.055% to -0.051%) for HF, -0.044% (95% CI, -0.047% to -0.041%) for AMI, and -0.033% (95% CI, -0.035% to -0.031%) for pneumonia. In contrast, monthly aggregate changes across hospitals in hospital 30-day RAMRs after discharge varied by condition: HF, 0.008% (95% CI, 0.007% to 0.010%); AMI, -0.003% (95% CI, -0.005% to -0.001%); and pneumonia, 0.001% (95% CI, -0.001% to 0.003%). However, correlation coefficients in hospitals' paired monthly changes in 30-day RARRs and 30-day RAMRs after discharge were weakly positive: HF, 0.066 (95% CI, 0.036 to 0.096); AMI, 0.067 (95% CI, 0.027 to 0.106); and pneumonia, 0.108 (95% CI, 0.079 to 0.137). Findings were similar in secondary analyses, including with alternate definitions of hospital mortality.

Conclusions and relevance: Among Medicare fee-for-service beneficiaries hospitalized for heart failure, acute myocardial infarction, or pneumonia, reductions in hospital 30-day readmission rates were weakly but significantly correlated with reductions in hospital 30-day mortality rates after discharge. These findings do not support increasing postdischarge mortality related to reducing hospital readmissions.

Conflict of interest statement

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. All authors work under contract with the Centers for Medicare & Medicaid Services to develop and maintain performance measures. Dr Dharmarajan reported serving as a consultant and scientific advisory board member for Clover Health at the time this research was performed. Dr Normand reported serving as a statistical consultant to Yale–New Haven Hospital. Dr Ross reported receiving grants from the US Food and Drug Administration, the Laura and John Arnold Foundation, and the Agency for Healthcare Research and Quality. Dr Krumholz reported serving as chair of the cardiac scientific advisory board for UnitedHealth; being a founder of Hugo, a personal health information platform; being a participant and participant representative of the IBM Watson Health Life Sciences Board; and serving as a member of the advisory board for Element Science and the physician advisory board for Aetna. Drs Ross, Desai, and Krumholz reported receiving funds from the Blue Cross Blue Shield Association, through Yale, to better understand medical technology evidence generation. Drs Ross and Krumholz reported receiving support from the US Food and Drug Administration and Medtronic, through Yale, to develop methods for postmarket surveillance of medical devices; and receiving research support from Medtronic and Johnson & Johnson (Janssen), through Yale, to develop methods of clinical trial data sharing.

Figures

Figure 1.. Trends in Hospital 30-Day Risk-Adjusted Readmission Rates and Hospital 30-Day Risk-Adjusted Mortality Rates After Discharge for Heart Failure, Acute Myocardial Infarction, and Pneumonia, 2008 Through 2014

Linear trends in mean monthly 30-day risk-adjusted readmission rates and 30-day risk-adjusted mortality rates after discharge from hospitalization for heart failure (A), acute myocardial infarction (B), and pneumonia (C) are shown for 3 periods: January 2008 through March 2010, April 2010 through September 2012, and October 2012 through December 2014. The vertical dotted lines denote April 1, 2010, and October 1, 2012, to be proximate to dates of passage of the Affordable Care Act and implementation of the Hospital Readmissions Reduction Program, respectively. Trend lines were fitted based on predictions of truncated time series models for the 3 periods above. Risk adjustment was made for patient age, sex, comorbidities, season, and hospital length of stay.

Figure 2.. Correlation of Paired Monthly Trends in Hospital 30-Day Risk-Adjusted Readmission Rates and Hospital 30-Day Risk-Adjusted Mortality Rates After Discharge for Heart Failure, Acute Myocardial Infarction, and Pneumonia, 2008 Through 2014

Correlations of paired monthly trends in hospital 30-day risk-adjusted readmission rates and hospital 30-day risk-adjusted mortality rates after discharge from hospitalization for heart failure (4221 hospitals) (A), acute myocardial infarction (2469 hospitals) (B), and pneumonia (4483 hospitals) (C) from 2008 through 2014 are shown. Risk adjustment was made for patient age, sex, comorbidities, season, and hospital length of stay.