SPECIFIC AIM: To identify actual and latent medical errors that occur at the time of discharge, and develop a comprehensive hospital discharge toolbox to reduce errors that lead to rehospitalization. BACKGROUND: Nationally about 25 percent of hospitalized patients are readmitted within 90 days, often due to errors resulting from the discontinuity and fragmentation of care at discharge. Low-income urban patients are at high risk of re-hospitalization due to higher rates of low health literacy, lack of coordination and loss to follow-up, gaps in social supports, and other limitations. They therefore experience high morbidity and account for a disproportionate amount of health care costs. Improving the hospital discharge process is a key component of any strategy to reduce re-hospitalization. To date, there are few studies describing the essential components of the discharge process and no accepted procedures or tools designed to reduce medical errors at the time of discharge, especially for urban populations. METHODS: Our clinical research team will analyze the components of the hospital discharge and identify and measure the medical errors related to each component. High-risk patients (i.e., those previously rehospitalized within six months) will be studied using (1) process mapping of discharge events; (2) failure mode and effects analysis through assessment of discharge events to identify latent sources of error; (3) sentinel event (root cause) analysis of those repeatedly hospitalized to learn from those who have been affected by an error at discharge; (4) qualitative research with re-hospitalized patient and their families, and other key informants to further understand issues leading to rehospitalization; and (5) determining the contributions of various risks at discharge through probabilistic risk assessment. This analysis will be used to re-engineer the discharge process through the (1) development of discharge tools that address latent and active patient errors; (2) computerization of discharge tools, linking them to hospital information systems; (3) training the responsible 'sharp end' clinicians in the elements of the comprehensive discharge using simulations and case scenarios; (4) use of the newly developed electronic system to monitor and set benchmarks for key elements of the discharge; and (5) development of an organized quality improvement program that provides feedback to key sharp end providers. DELIVERABLES: Through a series of projects, we will re-engineer hospital discharge to provide an intervention that can be tested in a series of randomized trials. We will facilitate accomplishment of these objectives by organizing an advisory committee of senior Boston Medical Center (BMC) leaders to oversee the re-engineering of the discharge process. This leadership group will set the stage for institution-wide adoption of improvements once their effectiveness is proven.
| Woz, Shaula; Mitchell, Suzanne; Hesko, Caroline et al. (2012) Gender as risk factor for 30 days post-discharge hospital utilisation: a secondary data analysis. BMJ Open 2:e000428 |
| Jack, Brian W; Chetty, Veerappa K; Anthony, David et al. (2009) A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med 150:178-87 |
