Below are some frequently asked questions and answers about conducting health workforce research. You can also search the FAQs by topic.

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Q: How reliable are different sources of physician supply data?

Topics: Data Collection, Workforce Supply

A: An article by DesRoches et al (2015) compared the National Provider and Plan Enumeration System (NPPES), the American Medical Association Masterfile, and the SK&A physician file to evaluate data accuracy. The authors performed this analysis in the context of using the selected datasets for sampling frameworks and counting physicians in a given area. The authors found that while none of the files were perfect, the NPPES contained broader coverage and NPPES and SK&A data had reasonably accurate and current address information. The AMA Masterfile had lower rates of correct address information.

State licensure data are another matter. Some state medical boards require only basic information, including a mailing address for licensing correspondence. Some states collect more robust data through licensure, including multiple practice addresses, and demographic, education, and practice characteristics. Some states conduct regular surveys. States may or may not systematically verify the licensure or survey data.

Different data sources have different limitations. Before using any dataset as a sampling frame or for research, it is essential to understand the data’s purpose and how they are collected, verified, and updated.

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Q: Why don’t different data sources match?

Topics: Data Collection, Methodology

A: There are multiple approaches to collecting data and data are often collected for different purposes. As a result, it is important to understand the methodology behind each dataset and its intended use in order to make valid comparisons. For example, the Bureau of Labor Statistics Occupational Employment Statistics collects data from employment surveys; the data count jobs, not workers, and they count employed, not self-employed positions. Professional association masterfiles (eg, AMA, ADA) are based on membership surveys and other sources, and data may not accurately account for professionals that are licensed and practicing in more than one state. State licensure data are self-reported through license applications and renewals, and hinge on the licensees accuracy and timeliness. The National Provider and Plan Enumeration System (NPPES) is a registry of providers that submit Medicare and Medicaid claims; this is an administrative database where the billing address of the provider may not match the provider’s practice location. Health professionals are mobile, some more than others, and change jobs and locations; these moves may not be reflected accurately or in a timely manner.

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Q: What are some new directions that health workforce research and planning are taking?

Topics: Emerging Models and Innovations, Methodology

A: While it is important to understand how many health professionals there are and in which professions, specialties, employment settings, and geographic locations they practice, health workforce research is moving beyond understanding supply to better understanding demand for health professionals, how they are training and practicing, how they impact the quadruple aim, and how to more effectively plan for the future. The Global Health Workforce Alliance reports, “The current discourse on HRH is evolving from an exclusive focus on availability of health workers – ie, numbers – towards according equal importance to accessibility, acceptability, quality and performance.

A special issue of Health Services Research in 2017 provides a summary and examples for how health workforce research is evolving. Washko and Fennell summarize 4 main themes, including “(1) the changing roles of health care providers, (2) the changing combinations of different providers who work together to deliver care, (3) the impact of these workforce changes on quality of care and access to care, and (4) advances in methodological challenges inherent in the study of evolving health workforce changes.”

HRSA has funded 7 Health Workforce Research Centers (HWRCs) to conduct and disseminate “rigorous research that strengthens evidence-based policy and enhances government’s and the public’s understanding of issues and trends in the health workforce” to help inform health workforce planning and policy. The HWRCs’ research focuses on allied health, behavioral health, ”emerging topics”, long-term care, oral health, and technical assistance. In 2017, the George Washington University HWRC compiled a report, Health Workforce Centers (HWRCs) Key Findings, 2013-2016, that identifies 3 main themes in the HWRCs’ work, including understanding the evolving health workforce configuration; spotlighting job growth and career paths in middle- and low-skilled health professions; and identifying workforce strategies to increase access to high-quality health care.

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Q: What staff and resources are needed to undertake health workforce data collection and analysis?

Topics: Data Collection, Methodology

A: This depends on many different factors, such as how many health professionals you want to track, the method used to collect data (licensure, survey, continuous monitoring, secondary data), the types of deliverables for which you’re accountable, and organization structure. If the data system is embedded within a larger organization, such as a university or state government office, it is likely that some administration, finance, and infrastructure resources are already available for basic operation. If the data system is a stand-alone organization, you will need to secure funding.

In terms of staff, you may consider having a director to guide the work, make decisions, present results and acquire funding; one or more project managers/researchers to analyze data, write reports and present results; and a data manager to collect, clean and analyze data. Other positions may include communications specialist, visualization specialist, research assistant, administrative assistant, grants manager, and financial manager.

Additional resources needed include computer hardware and software for data management, statistical analysis, GIS, and graphic design.

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