Describing Nursing Effectiveness Through Standardized Nursing Languages and Computerized Clinical Data

Abstract

The purpose of this descriptive exploratory study was to analyze patient data from a computerized clinical documentation system using the standardized languages of the North American Nursing Diagnosis Association, the Nursing Interventions Classification, and the Nursing Outcomes Classification. This study investigated the relationships between nursing diagnoses, interventions, and outcomes for the patient populations of Pneumonia, Congestive Heart Failure (CHF), and Total Joint Replacement (TJR). The effect of nursing interventions on patient outcomes was evaluated using repeated measures MANCOVA controlling for the variables of age, gender, acuity, and comorbid conditions.

The study sample consisted of all records of patients admitted with the primary DRG of Pneumonia, CHF, or TJR from January 1 to December 31, 1999. A total of 566 patient records were collected for analysis. The most frequent nursing diagnoses, interventions, and outcomes were identified for each of the populations. The linkages between nursing diagnoses, interventions, and outcomes from the study data closely approximated published linkage work.

Nursing interventions that were statistically significant or indicated a positive effect for patients in the Pneumonia population were Oxygen Therapy and Family Involvement. Statistically significant nursing interventions for patients with CHF were Oxygen Therapy, Anxiety Reduction, and Gastrointestinal Surveillance. The interventions of Multidisciplinary Care Conference, Orthopedic Appliance, and Tube Care: Urinary were shown to have a statistically significant effect for patients in the TJR population.

This is one of the first studies completed using computerized standardized nursing languages to determine the most effective interventions to achieve the best outcomes. The results suggest that all the necessary variables have not been identified that will explain the outcome rating changes from admission to discharge that are associated with nursing interventions. Future studies need to use larger samples and should include interventions from other disciplines.

With development of clinical nursing databases and the ability to build relational databases with other large data sets, nursing research will be able to include all relevant variables in the analysis of nursing effectiveness. It is crucial that national data sets represent nursing, so nursing does not remain unrecognized as an essential healthcare provider.