Friday, December 13, 2013

New Briefs Provide Expert Guidance for Ensuring Better State-Level Nursing Workforce Data Systems

An aging population, insurance expansion, increase in chronic disease and new care delivery and financing models are dramatically changing our nation’s health care system. We must have robust and accurate data on the nursing workforce if we are ever to ensure an adequate number nurses to meet the growing demand for health care services created by these forces. Unfortunately the foremost data source on the demographics, location, and practice behaviors of U.S. nurses has been discontinued. Now there is great pressure on states to collect their own nursing workforce data, and to collect common data elements that can be aggregated into a national dataset. This work is complex, costly, and requires significant planning and foresight.

A new set of briefs, developed by a team of researchers funded by INQRI, provides information and guidance to help states build and maintain nursing workforce data systems that will help answer questions about the current and future supply, distribution, diversity, and demand for nurses. The team included: Erin Fraher, PhD, MPP, director of the Program for Health Workforce Research and Policy at the Cecil G. Sheps Center for Health Services Research (Sheps Center), The University of North Carolina at Chapel Hill; Katie Gaul, MA, research associate at the Sheps Center; and Julie Spero, MSPH, research associate at the Sheps Center.

The three briefs address the reasons states should build data systems, how to do it, and what kinds of data should be included.

The first brief explains why states need to build better workforce data systems and identifies the types of questions a robust, well developed, longitudinal nursing workforce data system can help address:

  •  How will changing population demographics, economic conditions, and the rapid pace of health systems change affect nursing supply and demand?
  •   Are the state’s educational programs producing the workforce needed in the future?
  • Does the racial/ethnic, geographic, and specialty distribution of the workforce match population health needs?
  • What are the basic demographic and practice characteristics of the state’s nursing workforce and how are they likely to change in the future?

The second brief provides recommendations for creating, organizing, and maintaining a state-level data system, including:

  • Forming collaborative partnerships early in the process to determine which entities can best collect, analyze, and report the data, and the best ways to fund and maintain the system.
  • Housing the data system with a neutral party to ensure objectivity.
  • Considering the possible pitfalls of having the state legislate the development of a system, including the reliance on annual appropriations, limited flexibility in determining questions, and the possibility that data collection and analysis may not remain objective.
  • Ensuring adequate funding to cover such cost items as staff time, technology infrastructure, and overhead costs.
  • Identifying sustainable, long-term funding sources from the outset of the project.
  •   Properly training data system staff to ensure data are protected.

The third brief examines some of the efforts currently underway to create state-level nursing workforce data systems and highlights some of the most promising approaches to collecting data, and determining the kinds of data to collect. The researchers encourage states planning to create nursing workforce data systems to engage in some of these practices, including:

  • Using online data collection systems because they lower costs and improve data quality.
  • Using in-house information technology expertise to reduce cost, increase flexibility, and promote ownership of the data collection system.
  • Ensuring that questions and data values are consistent from year to year.
  • Avoiding using open-ended or subjective questions in the data collection process.
  • Working with the MDS to ensure consistency without compromising a state’s ability to do longitudinal comparisons.

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