Q&A with Jean Moore, Director of the SUNY Center for Health Workforce Studies
By Laura Trude, HWIC Information Specialist
The Health Resources and Services Administration contracted with the Lewin Group to create a Uniform Health Workforce Minimum Dataset (MDS) that includes a standard set of basic questions on the demographic, educational, and practice characteristics of health professionals. The MDS is designed to support consistency in health workforce data collection by states and professional associations, among others, in order to facilitate data comparison and workforce planning. While groups representing specific health professions in the United States have created minimum datasets, this marks the first effort to create national standards for a MDS which can be applied across professions. Jean Moore, the lead staff subcontractor for the project, addresses the development of the dataset, its goals, and Lewin Group’s current progress.
What is the vision for the uniform minimum dataset?
Probably the first thing we should clear up is what we mean by “minimum dataset,” or MDS. The MDS that is currently under development is designed to answer basic questions on health workforce supply. The questions focus on demographic, educational, and practice characteristics of health professionals. Building consensus on a constant set of basic questions used by all groups engaged in health workforce data collection can ultimately support consistency and uniformity of all data that are collected. That paves the way for comparative health workforce data analyses.
There are a number of important target audiences for the MDS. One is states, because there are a number of states that are either collecting health workforce data or thinking about doing so. Another important group is professional associations. If both states and professional associations collect health professions data consistently, then you have some real opportunities for health workforce data analysis at both national and state levels. This could go a long way to describing the supply and distribution of health professions. These data could also be extremely valuable in the identification of supply and demand gaps. It can serve multiple purposes, and consistency is really the key.
Which professions is the Lewin Group currently focusing on?
Ultimately, the goal is to incorporate all health professions, but we recognized that we needed to start somewhere. Right now, we’re focused on physicians, registered nurses, advanced practice nurses (nurse practitioners, clinical nurse specialists, and nurse midwives), physician assistants, dentists, dental hygienists, licensed practice nurses, pharmacists, and physical therapists. At the end of the day, we are going to want to expand the MDS to include all health professions.
How were those professions chosen?
One set of professions of great interest relates to the analysis done for health professional shortage area (HPSA) designations. Having data on physicians, nurse practitioners (NPs), physician assistants (PAs), and nurse midwives can support an analysis of primary care capacity that could lead to the designation of primary care HPSAs. The data on dentists and dental hygienists could help inform the identification of dental HPSAs. HPSA designations are important because they’re used for a variety of health professional recruitment and retention programs, including federal scholarship and loan repayment programs as well as Medicare rate enhancements.
As we develop the key questions we need to be asking health professionals, we think that one size is not going to fit all, because if we want to use these for HPSA designations, then we may need more detail on some practitioners. For example, while the ZIP code of someone’s workplace would be sufficient for most professions, we would want to know the actual practice addresses of physicians, physician assistants, nurse practitioners, and nurse midwives in order to meet the requirements for HPSA designation. Thus, the key questions for a profession depend upon the research questions you want to answer using the MDS.
What process was used to determine which questions to include? What are some of the snags you have run into while developing the minimum dataset?
The MDS focuses on demographic, educational, and practice characteristics. While the categories seem pretty straightforward, it’s really no small feat to come up with what we believe to be the right questions.
One of the things we did that was extremely enlightening was to pull together in early December a small group of researchers and some other stakeholders who really understood issues related to health workforce data collection. They helped us think through what these questions ought to focus on. When we came out of this meeting, it was very clear that there were some specific demographic areas we needed to address, including age, gender, and race/ethnicity, among others. Everybody said, “Look, these are the key things that we just have to know.” It was very instructive to help us focus, but it also makes you aware of the diversity of opinions about how to get at the information you need.
So we used that as a jumping off point. We came up with a set of questions about the basics and then we recognized that there are things that we really want to know that fall outside of the MDS. For example, in New York, our center is involved with conducting re-registration surveys. One of the questions we ask relates to where somebody went to high school because we want to understand the extent to which our health workforce draws from people who are from New York. So some demographic questions that clearly fall outside of the MDS are very important to us. We’re talking about coming up with level-one, basic questions and also additional questions that could be of value to groups depending on their issues of interest.
The basic MDS questions may have some very short answers or more comprehensive answers. Here’s an example: when you ask about ethnicity, you can say, “Are you Hispanic or Latino? Yes or no?” Or you can provide some more detail and say, “Yes, Puerto Rican; yes, Mexican-American; yes, Cuban or yes, other.” Now you are getting into more detail that may be more relevant for some states than others. You definitely want to know ethnicity and you can just make it a yes or no question or you can ask a more detailed question. But the question also has to be able to be summed up to the more basic answer. If you ask if somebody is Asian, some organizations may want to know if they are Chinese, Japanese, Vietnamese, Asian-Indian, Filipino, or Korean. As long as you can sum it up to the more basic answer, such as the number of people in a particular health profession who report their race as Asian, then you can compare the data.
I wouldn’t say it’s a snag; it sounds pretty straightforward, but the devil is in details, as they say. And that’s what we’re focusing on right now — trying to flesh out the most appropriate level of detail that we think makes sense for the majority of stakeholders. It’s complicated and it’s important for us to make sure that we do this well. At the end of the day, it becomes the data that we will be living with going forward related to health professions. We’re working very hard right now to fine-tune the questions to make sure that the MDS can do all of the things that we need it to do.
Designing something that has the potential to be used for HPSA analysis and creating some shortcuts to the definition of shortage areas can be a real win-win for everybody. It’s critical to understand primary care shortages, and creating a way to facilitate that analysis through data collection is of great interest. That’s not to say that some states don’t do that already. We do it in New York with the data that we collect from our re-registration surveys. So it can be done, and we are now figuring out how we can do it in a way that will be useful for all states that want to use this approach for identifying shortages.
Do you foresee any challenges for getting states and organizations to use this minimum dataset?
I think one of the biggest challenges is, now more than ever, the resources needed to be able to do this. While it wouldn’t be very hard to build the MDS questions into re-registration at the state level and the member data collected from professional associations nationwide, you need resources to make it happen and to make it happen well.
Another challenge is building relationships; for example at the state level with the licensing boards, because their willingness to support this effort is key going forward. Different state licensing boards have different perspectives on this. Some licensing boards say, “Look, we’re here to license people. We’re not about health workforce planning.” So sometimes it’s hard to convince them about the value of the data collection. There are other places where there’s a long history of collaboration that has yielded terrific results. Probably the best example of that is what goes on in North Carolina where the licensing boards have collaborated with a workforce research center to provide the data needed for health workforce planning in the state.
I also think that if resources become available for this, the Health Resources and Services Administration (HRSA) will try to do as much as they can to really support states and professional associations to adopt the MDS questions and to find ways to create access to these data for researchers, planners, and policymakers. The exciting part is that if you can get everyone to collect information in a consistent way, then you can aggregate it up so that you not only know what’s happening in your state, but you can look across the country and understand what’s happening elsewhere and how your state fits in. The broad use of the MDS beyond a state just looking at itself can provide a more comprehensive analysis of the health workforce. The potential is just tremendous as this builds momentum.
We presented the idea of the MDS and some examples of the kinds of questions we’re thinking about asking to the HRSA state workforce planning grantees. And there is a lot of interest because it falls on states to try to understand and anticipate supply and demand gaps of their health professions and develop programs and policies to address potential gaps, and address recruitment and retention issues.
What issues still need to be addressed in the development of the dataset?
We intend to share drafts of surveys with different groups to get their feedback on whether or not we missed anything related to their specific issues, professions, or states. We’re also interested in scope of practice variations from state to state. Questions that are developed for a New York survey of nurse practitioners may be less relevant for a state that has different scope of practice rules. We’re going to come up with what we think are the best approaches, but it’s going to be very important to get feedback from states and associations about which questions work best for them and if, in fact, we can support that variation.
Are there any final comments you would like to add?
I’m extremely excited about this project because I think that creating opportunities for health workforce planning at both state and national levels is really important, now more than ever. My sense is that there’s growing recognition that we just have to have these data if we want to transform the health care delivery system into something that’s more cost-effective, more efficient, and better at managing chronic disease. As health reform initiatives create more access to health insurance for people who have historically gone without it, we’ve got to make sure we know the workforce we have in order to help us figure out the workforce we’re going to need for future.
Please note that the views expressed in this article are the opinions of the interviewee and do not reflect the official policies, positions, or opinions of the Health Workforce Information Center or its funder.