Public Health Workforce Research Agenda

SESSION AUDIO:

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MODERATOR:
Kristine M. Gebbie, Dr.P.H., RN

PANELISTS:

Matthew L. Boulton, M.D., M.P.H.

Epidemiology Capacity in State Health Departments, 2004-2009

Co-Investigators: J. Hadler, M.D., M.P.H., A.J. Beck, M.P.H., CHES, L. Ferland, M.P.H., J. Lemmings, M.P.H.

The objective of this study was to summarize findings of the 2009 Council of State and Territorial Epidemiologists (CSTE) Epidemiology Capacity Assessment (ECA) and analyze trends in the state health department epidemiology workforce from 2004 to 2009. CSTE provided data from the 2004, 2006 and 2009 ECA for this study. Analysis was completed by CSTE and the Center of Excellence for Public Health Workforce Studies at the University of Michigan. Descriptive results were reported for the 2009 ECA and analytic statistics were used to show relationship between state population and number of epidemiologists. Results of the 2009 ECA revealed a total of 2,193 epidemiologists are employed by state health departments, a decrease of 12% over the past 5 years. The proportion of epidemiologists with a degree, training, or coursework in epidemiology rose to 87% in 2009, an increase of 7%. Approximately 68% more epidemiologists are needed for state health departments to reach full epidemiology capacity. One-third or fewer states reported substantial to full capacity in five epidemiology program areas; environmental health, injury, occupational health, substance abuse, and oral health, whereas greater than 50% of all states reported substantial to full capacity in infectious disease, bioterrorism, maternal and child health, and chronic disease. Fewer than half of all states utilize newer surveillance technology, such as web-based provider reporting systems (41%); automated cluster detection software (24%); geo-coding for births (39%), deaths (41%) and case report data (29%); and outbreak management systems (31%). Epidemiology capacity in state health departments, as measured by states’ ability to carry out Essential Services of Public Health, utilize technological capabilities to conduct public health surveillance, and employ needed number of epidemiologists in all program areas, is suboptimal and shows a decreasing 5-year trend. Diminishing federal emergency preparedness funding may be adversely impacting epidemiology capacity in state health departments.

Claude E. Fox, M.D., M.P.H.

Developing a Predictive Staffing Model for Public Health Nursing

Co-Investigator: R. Magisano, B.S., M.P.H.

The research objective was to identify a predictive model for determining the appropriate staffing of public health nursing in public health clinics.  Data sets and sources used included the World Health Organization, European Public Health Association, ASTHO, NACCHO, ASTPHND, London School of Tropical Medicine and Hygiene, King’s College of London, University of New South Wales, World Federation of Public Health Organizations among others. With the push for accreditation of public health departments in the US, the next logical step was to determine what would be the appropriate level of staffing for different health departments depending on workload and services mix.  Such a staffing model would need to take into account the different services that health departments might provide as well as varying roles and responsibilities of public health nurses. We conducted phone interviews with US public health organizations along with a literature review and e-mail contact with other international public health organizations to determine if a mechanism to determine the appropriate level of staffing for public health nurses had been used elsewhere and whether models were potentially adaptable for use in Florida and the US.  A key finding was that while there has been rapid development of measurement systems in the US and other countries for nursing services in a variety of settings such as hospitals, virtually nothing exists for public health nursing.  It appears in many quarters that public health nursing is ill defined and subsequently, tools developed to measure productivity for public health nursing are not sophisticated.  Much more progress has been made with respect to hospital nurse staffing techniques.  Another problem is that US counties and states as well as other countries vary enormously in what they define as public health nursing along with its inherent roles and responsibilities.

Hugh H. Tilson, M.D., Dr. P.H.

Wanted: The Workforce to Work on the Workforce Agenda

To overcome the absence of an evidence base required for substantive recommendations about the public health infrastructure workforce, the field of public health needs a robust, sustainable, competent infrastructure within academia to conduct required workforce research as part of the larger field of public health systems and services research. This commentary will discuss the cadre of leaders, researchers and supporters needed to create a robust workforce research effort; the need for a guaranteed, continuing stream of funding to support the effort; the competent researchers who will add knowledge to the field; and a strategic approach to developing the research infrastructure to ensure geographic, disciplinary, and institutional relevance.

William Mase, Dr.P.H., M.P.H., M.A.

Public Health Workforce Quality Improvement: From Measurement to Application

Co-Investigators: J.W. Holsinger, M.D., Ph.D., K. Meganathan, M.S.

This public health workforce research initiative expands practice-based employee trust measurement in a time-one time-two (T1 – T2) quantitative design methodology.  The initiative is an expansion of previously conducted research within the Cincinnati Health Department and the Northern Kentucky Health District.  Tailored workforce-based quality improvement (QI) initiatives were to be developed and implemented within the two local health departments (LHD’s). Workforce-based QI was a product of strategic initiatives defined by leadership of both health departments and informed by a critical review of the data collected in 2008.  Analysis of additional independent variables and interaction terms were evaluated and are presented for supervisor/employee gender concordance, race concordance, and years of service.   Site-specific QI initiatives were developed and implemented within one of the LHD’s.  In January of 2010 the T-2 measurement within both LHD’s will be completed.  Note:  Data for the T2 analysis was not available at the time of this submission.   Re-test measurement following QI intervention is vital in assessing trust relationship change and is intended to serve as a quality improvement indicator.  In addition to the T1-T2 employee trust measurement, unanticipated findings associated with reduction in workforce within one of the study sites are presented.