Predicting improvement in urinary and bowel incontinence for home health patients using electronic health record data

Abstract

Purpose: 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.

Subjects and setting: 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 .

Design: 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.

Results: 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.

Conclusions: 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.

Figure 1

Decision tree to predict improvement in bowel incontinence