Creating and Analyzing a Statewide Nursing Quality Measurement Database
Authors: Carolyn E. Aydin1; Linda Burnes Bolton1; Nancy Donaldson1; Diane Storer Brown1; Martha Buffum1; Janet D. Elashoff1; Meenu Sandhu1
Source: Journal of Nursing Scholarship, Volume 36, Number 4, December 2004 , pp. 371-378(8)
Publisher: Blackwell Publishing
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Abstract:
Purpose: To explicate a replicable methodology for designing and analyzing a large ongoing reliable and valid quality database to examine nurse staffing and patient care outcomes in acute care hospitals. Design: Prospective nurse staffing, process of care, and patient outcomes data based on the American Nurses Association's (ANA) nursing quality indicators collected from a voluntary convenience sample at acute care hospitals in California with rolling-site accrual. Methods: The ongoing CalNOC database development and repository project, the largest statewide effort of its kind in the United States (US), currently includes data on hospital nurse staffing, patient days, patient falls, pressure ulcer and restraint prevalence, registered nurse (RN) education, and patients' perceptions of satisfaction with care. Findings: As of May 2003, the CalNOC database contained staffing data from 842 units in 134 acute care hospitals over 20 quarters from April 1998 to March 2003. The repository also included clinical outcome information on 34,262 reported patient falls, pressure ulcer prevalence data on 41,982 patient observations, and service outcome data on patient satisfaction from 26,461 patients. Participating hospitals receive quarterly reports allowing them to benchmark their own performance against other participating hospitals. CalNOC methods have been adapted and replicated by both the Military Nursing Outcomes Database and VA Nursing Outcomes Database projects, and CalNOC nursing-sensitive measures have been endorsed by the National Quality Forum. Conclusions: This working model for collecting reliable and valid data was derived from multiple hospitals across California. The data are the basis for studies to contribute to the development of evidence-based public policy, and for ongoing study of the effects of nurse staffing on clinical and service outcomes. Journal of Nursing Scholarship, 2004; 36:4, 371-378. © 2004Sigma Theta Tau International.Keywords: quality indicators; nursing workload; data collection methods; data analysis
Document Type: Research article
DOI: 10.1111/j.1547-5069.2004.04066.x
Affiliations: 1: Carolyn E. Aydin, PhD, CalNOC Co-Investigator, Research Scientist and CalNOC Data Manager, Cedars-Sinai Health System/Burns and Allen Research Institute, Los Angeles, CA; Linda Burnes Bolton, RN, DrPH, FAAN, Gamma Tau, CalNOC Co-Investigator, Vice President and Chief Nursing Officer, Cedars-Sinai Health System/Burns and Allen Research Institute, Los Angeles, CA; Nancy Donaldson, RN, DNSc, FAAN, Alpha Eta, ANA/C CalNOC Project Director/Co-Principal Investigator, Director, Center for Research and Innovation in Patient Care, UCSF Stanford Health Care, University of California San Francisco School of Nursing, San Francisco, CA; Diane Storer Brown, RN, PhD, FNAHQ, Alpha Eta & Nu Xi-at-Large CalNOC Co-Principal Investigator, Director of Quality and Continuous Readiness, Kaiser Permanente Northern California Regions, Oakland, CA; Martha Buffum, Alpha Eta, APRN, DNSc, BC, CS, Associate Chief, Nursing Service for Research, Veterans Affairs Medical Center, San Francisco, CA; Janet D. Elashoff, PhD, Director, Biostatistics Core, Cedars-Sinai Health System/Burns and Allen Research Institute, Los Angeles, CA; Meenu Sandhu, MS, Senior Biostatistician, Cedars-Sinai Health System/Burns and Allen Research Institute, Los Angeles, CA. Correspondence to Dr. Aydin, Nursing Research and Development, Room 2021, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Los Angeles, CA 90048., Email: aydin@cshs.org
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