Measuring patient-level clinical outcomes of home health care

J Nurs Scholarsh. 2004;36(1):79-85. doi: 10.1111/j.1547-5069.2004.04017.x.

Abstract

Purpose: To examine the use of the Outcomes Assessment and Information Set (OASIS) data to analyze patient-level outcomes of home health care.

Design: OASIS data were obtained on 1,015 patients who received home health care services for 60 days or fewer from a large, independent home health agency between August 1998 and December 1999.

Methods: An index was constructed consisting of 16 OASIS measures, primarily activities of daily living (ADL) and instrumental activities of daily living (IADL). Scores were computed for functional status on admission and at discharge. Predictors of functional status at discharge were identified by regression analysis.

Findings: 78.1% of patients improved, 18.5% declined, and 2.8% showed no change. The model explained 57.2% of variance in functional status at discharge. Age, visual impairment, having Medicaid as a payer, urinary incontinence, cognitive impairment, and use of unplanned or emergency care were negatively associated with functional outcomes of care. Being treated for open wounds or lesions, cardiovascular and orthopedic conditions were positively associated with functional outcomes.

Conclusions: OASIS data can be used to analyze patient-level functional outcomes of short-term home health services. Further research is needed to continue refining methods of analyzing patient outcomes and their predictors.

Publication types

  • Validation Study

MeSH terms

  • Activities of Daily Living*
  • Age Factors
  • Aged
  • Analysis of Variance
  • Data Collection / methods*
  • Data Collection / standards
  • Female
  • Geriatric Assessment / methods*
  • Health Services Research / methods
  • Home Care Services / standards*
  • Humans
  • Least-Squares Analysis
  • Length of Stay / statistics & numerical data
  • Male
  • Medicaid / statistics & numerical data
  • Outcome Assessment, Health Care / methods*
  • Outcome Assessment, Health Care / standards
  • Patient Admission
  • Patient Discharge
  • Predictive Value of Tests
  • Regression Analysis
  • Risk Factors
  • United States