Skip Navigation LinksHome > May 2014 - Volume 44 - Issue 5 > Business Intelligence and Nursing Administration
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Journal of Nursing Administration:
doi: 10.1097/NNA.0000000000000060
Departments: Guest Editorial

Business Intelligence and Nursing Administration

Welton, John M. PhD, RN

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Author Information

Author Affiliation: Professor, Director of PhD Program, and Senior Scientist, Health Systems Research, School of Nursing, University of Colorado, Aurora.

The author declares no conflicts of interest.

Correspondence: Dr Welton, School of Nursing, University of Colorado, Mail Stop C288-18, ED 2 North, 13120 E 19th Avenue, Room 4320, Aurora, CO 80045 (John.Welton@ucdenver.edu).

If we want to build a better healthcare system, then we are obliged to build a better nursing care delivery system. The lessons learned from business can be applied to achieve this goal—better and timelier information can lead to better decisions that ultimately help optimize both the process and practice of nursing care. From our vantage point in nursing, many, if not most, of hospitals and healthcare systems have installed electronic health records (EHRs) and automated processes such as order entry, medication administration, results reporting, nursing documentation, and others. The key question is how can we use these data in other ways to improve efficiency, effectiveness, productivity, performance, and quality, to achieve exceptional outcomes of nursing care?

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One key component is the adoption of electronic scheduling, staffing, and assignment systems for nurses. By using information from the EHR linking individual nurses to patients, we can develop sophisticated analysis and reporting tools to identify best practices and monitor variation in nursing care. Such a system was adopted by Catholic Health Initiatives using nursing assignment and acuity data merged with other operational, clinical, and finance data to provide a robust information environment that is integrated across their healthcare system.1 These new nursing business intelligence and analytic tools provide information that previously have not been available, for example, calculating the intensity and costs of nursing care for each patient then using these data to compare nursing costs per diagnosis related group.

Why should nurse leaders care? As we move forward with healthcare reform, there will be increasing demands to improve the quality and lower costs of care. Value-based purchasing will become more widespread among 3rd party payers, and greater emphasis will be placed on primary care and more integrated care throughout the healthcare spectrum. Nurses are the largest proportion of healthcare professionals and represent 1 of the largest single costs of care. However, simply cutting nursing staff in the quest for a lower operating budget can idiosyncratically lead to lower quality, higher rates of adverse events, and higher costs.

We need to change our thinking, our attitude, and approach to traditional nursing administration and leadership and focus on the business of nursing without losing sight of our essential value to patient care. We can do this by moving to a much more information-intensive environment and develop new metrics, analytics, and data visualization tools and do so in a near–real-time environment.2 The primary strategy is to use existing data without burdening bedside nurses with additional data collection.

To achieve these broad goals, the University of Colorado College of Nursing has formed the Colorado Collaborative for Nursing Research (CCNR) in partnership with hospitals and healthcare systems to develop new methods and leverage existing healthcare data to improve clinical and operational nursing care. This academic-practice partnership is self-funded to meet the needs of the individual institutional partners and to speed development of new tools and techniques and provide a fertile and facile research environment by sharing common data. By pooling both expertise and data, the CCNR expects to pursue new approaches to healthcare and nursing systems research driven by emerging techniques from business and informatics. This effort to incorporate nursing data into existing and future large data sets can aid clinical and management decision making and inform payers and policy makers how best to optimize nursing care delivery systems.

One primary objective of the CCNR is to articulate high-level concepts and metrics relevant for improving the delivery of nursing care and then to develop a common data framework that can be used to extract key data from the EHR. Summary data will be used to compare and benchmark nursing care within and across different settings. This effort builds on previous nursing systems research with a focus on leveraging the emerging massive amounts of electronically available data collected every day by nurses. There are unique challenges and uncertainty how best to proceed in a rapidly changing healthcare environment. The tantalizing goal is to find ways to use healthcare “big data” to guide efforts to improve nursing care in ways that until recently were unthinkable.

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References

1. Caspers BA, Pickard B. Value-based resource management: a model for best value nursing care. Nurs Adm Q. 2013; 37 (2): 95–104.

2. Murphy LS, Wilson ML, Newhouse RP. Data analytics: making the most of input with strategic output. J Nurs Adm. 2013; 43 (7-8): 367–370.

© 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins

 

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