BACKGROUND AND OBJECTIVE: There are no nursing centric data in the hospital discharge abstract. This study investigates whether adding nursing data in the form of nursing diagnoses to medical diagnostic data in the discharge abstract can improve overall explanation of variance in commonly studied hospital outcomes. METHOD: A retrospective analyses of 123,241 sequential patient admissions to a university hospital in a Midwestern city was performed. Two data sets were combined: (1) a daily collection of patient assessments by nurses using nursing diagnosis terminology (NDX); and (2) the summary discharge information from the hospital discharge abstract including diagnosis-related group (DRG) and all payer refined DRG (APR-DRG). Each of 61 daily NDX observations were collapsed as frequency of occurrence for the hospital stay and inserted into the discharge abstract. NDX was then compared to both DRG and APR-DRG across 5 hospital outcome variables using multivariate regression or logistic regression. RESULTS AND CONCLUSIONS: In all statistical models, DRG, APR-DRG, and NDX were significantly associated with the 5 hospital outcome variables (P <.0001). When NDX was added to models containing either the DRG or the APR-DRG, explanatory power (R2) and model discrimination (c statistic) improved by 30% to 146% across the outcome variables of hospital length of stay, ICU length of stay, total charges, probably of death, and discharge to a nursing home (P <.0001). The findings support the contention that nursing care is an independent predictor of patient hospital outcomes. These nursing data are not redundant with the medical diagnosis, in particular, the DRG. The findings support the argument for including nursing care data in the hospital discharge abstract. Further study is needed to clarify which nursing data are the best fit for the current hospital discharge abstract data collection scheme.
BACKGROUND AND OBJECTIVE: There are no nursing centric data in the hospital discharge abstract. This study investigates whether adding nursing data in the form of nursing diagnoses to medical diagnostic data in the discharge abstract can improve overall explanation of variance in commonly studied hospital outcomes. METHOD: A retrospective analyses of 123,241 sequential patient admissions to a university hospital in a Midwestern city was performed. Two data sets were combined: (1) a daily collection of patient assessments by nurses using nursing diagnosis terminology (NDX); and (2) the summary discharge information from the hospital discharge abstract including diagnosis-related group (DRG) and all payer refined DRG (APR-DRG). Each of 61 daily NDX observations were collapsed as frequency of occurrence for the hospital stay and inserted into the discharge abstract. NDX was then compared to both DRG and APR-DRG across 5 hospital outcome variables using multivariate regression or logistic regression. RESULTS AND CONCLUSIONS: In all statistical models, DRG, APR-DRG, and NDX were significantly associated with the 5 hospital outcome variables (P <.0001). When NDX was added to models containing either the DRG or the APR-DRG, explanatory power (R2) and model discrimination (c statistic) improved by 30% to 146% across the outcome variables of hospital length of stay, ICU length of stay, total charges, probably of death, and discharge to a nursing home (P <.0001). The findings support the contention that nursing care is an independent predictor of patient hospital outcomes. These nursing data are not redundant with the medical diagnosis, in particular, the DRG. The findings support the argument for including nursing care data in the hospital discharge abstract. Further study is needed to clarify which nursing data are the best fit for the current hospital discharge abstract data collection scheme.
Authors: Koen Van den Heede; Emmanuel Lesaffre; Luwis Diya; Arthur Vleugels; Sean P Clarke; Linda H Aiken; Walter Sermeus Journal: Int J Nurs Stud Date: 2009-02-07 Impact factor: 5.837