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Edward J Halloran

Publications and source records attributed to Edward J Halloran.

6 recordsLinked to original sources
PubMed2006

Nurse staffing, nursing intensity, staff mix, and direct nursing care costs across Massachusetts hospitals.

OBJECTIVE: This study describes the distribution of patient-to-registered nurse (RN) ratios, RN intensity of care, total staff intensity of care, RN to total staff skill mix percent, and RN costs per patient day in 65 acute community hospitals and 9 academic medical centers in Massachusetts. METHODS: We conducted a retrospective secondary analysis of the Patients First database published by the Massachusetts Hospital Association for planned nurse staffing in 601 inpatient nursing units in the state for 2005 using a multivariate linear statistical model controlling for hospital type and unit type. Nursing unit types were identified as adult and pediatric medical/surgical, step down, critical care, neonatal level II, and neonatal level III/IV nurseries. RESULTS: Medical centers had significantly higher case-mix index (1.72 vs 1.20, P < .001), longer lengths of stay (5.18 vs 4.19, P < .001), more beds (574 vs 147, P < .001), discharges (31,597 vs 7,248, P < .001), and patient days (161,440 vs 31,020, P < .001) compared with to community hospitals. Medical centers had significantly lower patient-to-RN ratios (3.22 vs 4.64, P < .001), higher nursing intensity and total nursing staff intensity (9.62 vs 7.43/11.75 vs 9.87, both P < .001), higher percent of RN to all staff mix (79% vs 71%, P < .001), and higher RN costs per patient day ($385 vs $297, P < .001) compared with to community hospitals. There were significant differences in adult med/surg units between community hospitals and medical centers for patient-to-RN staffing ratios (5.25 vs 4.08), nursing intensity (5.1 vs 6.2 hours daily), skill mix (67% vs 73% RN), and RN costs per patient day ($203 vs $248, all P < .001). There were no significant differences between the adult step-down units. CONCLUSION: The significant differences between community hospitals and medical centers, unit type, as well as the high degree of variability in patient-to-RN ratios, nursing intensity, skill mix, and RN costs per patient day suggest that nursing resource expenditure at Massachusetts hospitals is complex and affected by case mix, unit size, and complexity of care.

Academic Medical Centers↗
PubMed2006

Nursing intensity: In the footsteps of John Thompson.

The Nursing Minimum Data Set (NMDS) provides a way to incorporate nursing data into the hospital discharge abstract to potentially compare nursing care across institutions. An extension of this framework is to use these data for directly billing and reimbursing hospital nursing care. We provide a review of the existing literature and new empirical evidence to support hospital nurse billing. Two existing large data sets are compared, one using nursing diagnosis and the other a nursing intensity based tool to collect daily nursing times. These NMDS data sources are compared to diagnostic related groups (DRG) and hospital outcomes from the UB92 discharge abstract using multivariate regression and logistic regression. Either NMDS approach provides additional explanatory power (improvements in R2) over DRG alone. The findings strengthen the argument to use primary nursing data such as nursing intensity as a basis for direct costing, billing, and reimbursement of hospital nursing care.

Diagnosis-Related Groups↗
PubMed2005

Nursing diagnoses, diagnosis-related group, and hospital outcomes.

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.

Diagnosis-Related Groups↗
PubMed2003

Avian influenza.

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Animals↗