Hospitalization Patterns over 30 Years Across a Statewide System of Public Mental Health Hospitals: Readmission Predictors, Optimal Follow-Up Period, Readmission Clusters and Individuals with Statistically Significant High Healthcare Utilization
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Four related hospital utilization questions (optimal follow-up period, predictors of readmission, definition of individuals with statistically significant high healthcare utilization, and patterns of readmissions) were examined using data for 491,094 hospital discharges for 250,091 patients across a statewide public mental health hospital system for 30 years (1987 to 2016). Using survival analysis, the first quartile of the survival time, the time when 25% of the entire population of discharges had a readmission was 229 days. Using observed readmissions, rather than the population as in survival analysis, revealed that 50% of all observed readmissions occurred by 222 days. Both suggest that using a one year observation period for determining high utilization may be reasonable. Major predictors of readmission were diagnoses of schizophrenia (OR = 2.11) or bipolar disorder (OR = 1.57) as well as total number of previous discharges (OR = 1.23). Statistically significant z scores (p < .01) were used to determine annual (3 or more discharges) and lifetime (7 or more discharges) criteria for individuals with statistically significant high healthcare utilization that were somewhat lower than in previous research. Cluster analysis of all readmissions revealed four relatively distinct clusters of patients: short stay-quick readmission, extremely long stay, long time in community between readmissions and frequent readmissions. While no cluster corresponded exactly with the annual statistically significant high healthcare utilization criteria, the frequent readmission cluster was somewhat similar to the lifetime statistically significant high healthcare utilization criteria with 46% of this cluster’s patients having 7 or more discharges.
KeywordsPsychiatric hospital readmission High healthcare utilization Readmission patient clusters Predictors of hospital readmission
In memory of my colleague James Cooley who championed the analysis of high healthcare utilization.
Compliance with Ethical Standards
Conflict of Interest
The author received no funding for this study and has no conflict of interest to declare.
All research was conducted in accordance with the ethical standards of the institutional review board and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Data for this study was reviewed and approved by the Texas Department of State Health Services Institutional Review Board #2. Studies using only pre-existing administrative data do not require formal consent.
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