Early identification of hospitalized patients with complex post-acute care needs maximizes the time to design and implement a comprehensive discharge plan. Preliminary work of the research team in academic medical centers shows that when hospital discharge planning (DP) experts are engaged early, the timely coordination of services needed to improve continuity of care, patient safety, and resource use is enhanced. Similarly, length of stay is decreased and patients report fewer unmet needs after discharge. Conversely, when DP is not initiated early in the hospital stay, patients return home with unmet needs and readmissions increase. The study team has successfully developed and implemented an early DP decision support tool (Early Screen for Discharge Planning -ESDP) that has been tested in academic medical centers. Because differences in in- situation-specific characteristics such as bed size, teaching status, and rural/urban location can create variability in the performance of predictive models, there is critical need to validate the ESDP in community settings where most hospitalized patients are cared for. The long range research goal of the investigative team is to improve patient safety and successful reintegration back into the community through improved DP strategies to meet patients'increasingly complex post-acute care needs. The purpose of this study is to determine the predictive performance of the ESDP in regional community hospitals. The central hypothesis is that the ESDP differentiates between patients in regional community hospitals who would benefit from those who would not benefit from early DP intervention as measured by problems and unmet continuing care needs, quality of life, length of stay, and referrals to post-acute services. Guided by the Quality Health Outcomes Model, a comparative, descriptive survey study will be conducted with a convenience sample of 166 adult patients admitted to a regional community hospital in the Midwest. The ESDP and sample characteristics will be collected at baseline. One week after discharge participants will complete a questionnaire consisting of the Problems after Discharge Questionnaire-English Version and the EQ5-D quality of life measure. Length of stay and use of post-acute services received will also be recorded. Descriptive statistics will summarize sample characteristics and describe the data by groups. Comparisons of the percentages of reported problems and unmet needs between participants with low and high ESDP scores will be evaluated using two-sample t or Wilcoxon rank sum tests. The EQ-5D dimensions will be compared between groups (low and high ESDP scores) using Cochran-Armitage trend tests. Hospital length of stay and the number of referrals to post-acute services will be compared between groups using two-sample t and Wilcoxon rank sum tests. The expected outcome of this study is to provide much needed validation of a standardized, highly practical decision support tool for use in regional community hospitals.
The proposed research is relevant to public health because the results will enhance discharge planning practice at a pivotal point in the hospital stay for patients admitted to regional community hospitals. This study aligns with the AHRQ goal to improve patient safety by addressing an important topic in communication and teamwork related to transitions of care and successful reintegration of patients back into the community. The impact on discharge planning practice in ubiquitous smaller, community hospitals is great as the results of the study will inform the integration of the decision support tool into the electronic medical records of regional community hospitals for use by clinicians in the planning of safe and successful transitions of care.