The purpose of the study was to discover which patient and support system characteristics and interventions documented by home health clinicians were associated with improvement in urinary and bowel incontinence contrasting logistic regression and data mining approaches.
Seventeen hundred ninety-three patients in this study experienced 2072 episodes of care. The study sample comprised all nonmaternity patients aged 18 years or older receiving skilled home health services in 2004. Subjects were drawn from a convenience sample of 15 home health agencies.
We completed a secondary analysis of data from 15 home health agencies' electronic health records. Data for this study were documented by home care clinicians using the Outcome and Assessment Information Set (OASIS) structured assessment form and the Omaha System interventions, which is a standardized terminology.
There were 684 patients with urinary incontinence and 187 with bowel incontinence. By discharge 38% improved in urinary incontinence and 45% improved their bowel incontinence. Using logistic regression, no patient or support system characteristics were identified that associated with improvement in either urinary or bowel incontinence, only a limited number of interventions were significant. A data mining decision tree was producible only for bowel incontinence, demonstrating a combination of patient and support system factors as well as selected interventions were important in determining whether patients would improve in bowel incontinence.
Home health patients have complex comorbid conditions requiring home care nurses to have broad, generalized knowledge. Future research is needed to determine if the inclusion of a certified WOC nurse would improve outcomes.
Bonnie L. Westra, PhD, RN, FAAN, Assistant Professor, School of Nursing, University of Minnesota, Minneapolis.
Kay Savik, MS, Senior Statistician, School of Nursing, University of Minnesota, Minneapolis.
Cristina Oancea, MS, Research Assistant, School of Public Health, Environmental Health, School of Nursing, University of Minnesota, Minneapolis.
Lynn Choromanski, MS, PhD-C, School of Nursing, University of Minnesota, Minneapolis.
John H. Holmes, PhD, Associate Professor of Medical Informatics in Epidemiology, School of Medicine, University of Pennsylvania Philadelphia.
Donna Bliss, PhD, RN, FAAN, FGSA, Professor in Long-Term Care of Elders, Horace T. Morse/Alumni Association Distinguished Teacher, School of Nursing Foundation Research Professorship, School of Nursing, University of Minnesota, Minneapolis.
Correspondence: Bonnie L. Westra, PhD, RN, School of Nursing, University of Minnesota, 6-135 Weaver-Densford Hall, Minneapolis, MN, 55455 (email@example.com).