Discharge Planning and Hospital Readmissions

Tuesday, June 14, 2016
Lobby (Annenberg Center)

Author(s): Rachel Henke; Zeynal Karaca; William Marder; Herbert S. Wong

Discussant: Sujoy Chakravarty

Research Objective:  Under new policy initiatives such as the Centers for Medicare & Medicaid Services (CMS) Hospital Readmission Reduction Program and the Bundled Payments for Care Improvement Initiative, hospitals are at risk for the cost of readmissions, even if the patient is admitted to another hospital. This study examines (1) whether discharge planning reduces the risk of readmission; (2) whether its effectiveness differs for planned surgical procedures versus urgent medical conditions; and (3) for patients who are readmitted, whether discharge planning increases the likelihood that the patient returns to the same hospital.

Study Design:  We conducted a quantitative analysis of Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) using an observational research design. We created a discharge-level database that combined the 2010 and 2011 SID data from 16 states with CMS Hospital Compare data, American Hospital Association data, and Area Health Resource File (AHRF) data. We identified all stays with four conditions that are subject to the Hospital Readmission Reduction Program penalty: acute myocardial infarction (AMI), heart failure, pneumonia, and hip or knee arthroplasty. We also identified patients with two additional planned surgical procedures: spinal fusion and joint replacement. We then identified 30-day all-cause readmissions for these stays. We measured the extent of discharge planning at each hospital using a composite discharge planning score based on patient Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. We measured patient characteristics using SID data, hospital characteristics using AHA data, and market characteristics using AHRF data. We estimated hierarchical models with discharges nested with hospitals to measure the relationship between discharge planning and any readmission, controlling for all patient, hospital, and market factors. For the sample of patients who were readmitted, we estimated hierarchical models to measure the relationship between discharge planning and same-hospital readmission, controlling for all patient, hospital, and market factors.

Population Studied:  Our sample included adults 18 years or older in 16 states who were admitted to the hospital for AMI (n=355,755), heart failure (n=629,891), pneumonia (n=570,234), hip or knee arthroscopy (n=568,377), spinal fusion (n=131,043), and joint replacement (n=615,719).

Principal Findings:  Discharge planning was significantly associated with lower odds of 30-day hospital readmissions for heart failure, pneumonia, hip or joint arthroplasty, spinal fusion, and joint replacement. Discharge planning was more effective at reducing the risk of readmissions for planned surgical admissions than admissions for urgent medical conditions. Discharge planning was associated with higher odds of same-hospital readmissions for heart failure, pneumonia, total hip or joint arthroplasty, and joint replacement. Discharge planning did not have a significant effect on all hospital or same-hospital readmissions for patients admitted with AMI.

Conclusions:  Hospitals that are at risk for readmissions should focus on improving inpatient discharge planning. This may reduce their readmission rate and improve their capture rate of patients who are readmitted.

Implications for Policy or Practice:  Policymakers should continue to expand initiatives that provide incentives for hospitals to improve patient care by implementing better processes for care transitions.