Behavioral Health Hospitalization in Central California: Predictors of Readmission
Rationale/Conceptual Basis/Background: Hospital readmissions of patients with chronic illness presents a financial burden to healthcare organizations and adversely impacts the patients’ lives. This is particularly true for people with mental health disorders. Having the ability to identify risk factors would potentially reduce hospital readmission rates. Thus, leading to a more effective allocation of case management resources to those with the most critical needs.
The Institute of Medicine (IOM) and The Joint Commission (JCAHO) standards represent two federal initiatives that address issues related to management of patients with Mental Health (MH) and Substance Abuse (SA) conditions (IOM, 2006; JCAHO, 2012). Both publications focus on improving access and the overall quality of health for these populations. While there are extensive studies on readmissions to community hospitals, the literature on predicators and readmission to behavioral health hospitals for MH and SA is extremely limited.
Methods: A rural community electronic health records data bank for 2012 to 2013 was used to conduct a retrospective examination of demographics and clinical characteristics of residents age 18 and older. Enrolled individuals were either previously hospitalized or in community treatment programs or both. Non-enrolled individuals included those never hospitalized and never enrolled in community treatment programs. The investigator examined 902 records for individuals hospitalized from January 1 to June 30, 2012. Data was analyzed over a 12-month period, for information on demographics and clinical characteristics, including diagnosis at admission, primary provider, length of stay, and number of hospital readmissions, as well as concurrent, prior, and discharge treatment.
Results: Characteristics were similar for enrolled and non-enrolled groups in terms of gender, race/ethnicity, preferred language, unemployed and not seeking work. Of the 902 records, a higher percentage of non-enrolled individuals reported a house or apartment as their residence as opposed to enrolled individuals who reside in housing with support. Enrolled individuals were more likely to be never married and have a primary provider as opposed to non-enrolled. With regard to education level completed, enrolled individuals reported higher rates of secondary education than non-enrolled. No significance was found between enrolled and non-enrolled individual readmissions at 30 days, but readmissions rates were significantly higher for the enrolled within 60 and over 90 days.
Implications: Identification of key characteristics are important when planning care for patients with mental health disorders. It is vital in discharge planning to identify patient-centered treatment and recovery plans. This is particularly true for individuals with underlying MH and SA conditions, whose decision-making abilities are impaired. Utilization of predictors for admission can assist registered nurses in strategically preparing individuals for a successful transition from hospital to community.