Describing Nursing Effectiveness Through Standardized Nursing Languages and Computerized Clinical Data
Authors: Scherb Cindy A. 
Published: August 2004

PURPOSE

To analyze actual patient data recorded by nurses within a computerized documentation system using standardized NANDA, NIC, and NOC nursing language in order to validate the linkages of diagnoses, interventions, and outcomes; identify the important variables for risk adjustment; and verify which nursing interventions assist patients to achieve their desired outcomes for patients with pneumonia, congestive heart failure (CHF), and total joint replacement (TJR).

METHODS

This was a descriptive exploratory study. The study sample consisted of all records of patients admitted with pneumonia, CHF, or TJR. 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. Linkages among nursing diagnoses, interventions, and outcomes from the study data were compared with published linkage work.

FINDINGS

The average number of nursing diagnoses for patients admitted with pneumonia was 9.5 (SD± 3.0), patients with CHF averaged 10.1 (SD± 2.70), and patients with TJR averaged 10.4 (SD± 2.07). Nursing diagnoses common across all three populations were knowledge deficit, ineffective airway clearance, decreased cardiac output, pain, impaired physical mobility, altered urinary elimination, risk for impaired or impaired skin integrity, and altered nutrition: less than body requirements. The average number of interventions for each patient population was pneumonia 18.3 (SD± 7.74), CHF 19.3 (SD± 7.02), and TJR 20.5 (SD± 4.28). Interventions common across all three populations were “teaching: individual,”“discharge planning,”“family involvement,”“respiratory monitoring,”“ventilation assistance,”“cardiac care,”“self‐care assistance,”“urinary elimination management,” and “gastrointestinal surveillance.” The number of outcomes for patients with pneumonia, CHF, and TJR, respectively, averaged 9.01 (SD± 3.58), 9.71 (SD± 3.0), and 9.58 (SD± 1.80). Outcomes common across the three populations were Knowledge: Illness Care, Respiratory Status: Ventilation, Cardiac Pump Effectiveness, Mobility Level, Urinary Elimination, and Nutritional Status. Results of the comparisons among nursing diagnoses, outcomes, and interventions from the study data and previously published works indicated that, for the three populations combined, 71%–85% of the interventions were classified as major, suggested, or optional.

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 five most frequent outcomes for each patient population were studied. 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 the interventions shown to have a statistically significant effect for TJR patients.

DISCUSSION

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 not all the necessary variables have been identified to explain the changes in outcome rating from admission to discharge associated with nursing interventions. Future studies need to use larger samples and should include interventions from other disciplines.

CONCLUSIONS

It is crucial that national data sets represent nursing, so nursing does not remain unrecognized as an essential healthcare provider. Considerations for future studies should include issues related to study design, system concerns, inadequate specification of variables, and documentation issues. Other research implications include the need to make data retrieval from computerized systems easier, and the need for increased collaboration between academic centers and practice to further these research efforts. The practice arena needs to evaluate the expectations of the documentation system and how the use of the study results will change practice. 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.