1044: The Jobs Public Health Needs Now: Rethinking Workforce for the Data Age

JOHN SHEEHAN: 

This is Public Health Review Morning Edition for Wednesday, December 17, 2025. I'm John Sheehan, with news from the Association of State and Territorial Health Officials.

Today, we discuss an unexpected challenge in public health. Traditional job classifications no longer match up to the reality of the modern data landscape. Leveraging the Public Health Infrastructure Grant, or PHIG, state, local, and territorial health agencies can build classification systems that enhance recruitment and retention of an informatics-savvy workforce. Updating job classifications can help clarify new roles, alleviate pressure on existing roles, and enable health agencies to sustain workforce infrastructure that's flexible and forward-looking. Here to explain what that means, and why it's crucial for public health departments and agencies to understand it, is Ari Whiteman, ASTHO senior advisor for public health data and informatics workforce.

Ari Whiteman, welcome to the show.

ARI WHITEMAN: 

Thanks for having me.

SHEEHAN: 

Ari, your brief says that recent public health data modernization efforts have actually exposed, kind of, a weakness, and that weakness is traditional job classifications. What's going on?

WHITEMAN: 

So, as state and territorial health offices continue to modernize and move forward into the next few years of public health, our understanding of what's needed from a data management standpoint has changed as well as we really get a better sense of the interoperability of electronic health records that come from all different places across our communities. We now require staff that are able to handle and understand those nuances from a really, sort of, back-end perspective. You know, we, for many years and decades, even have had epidemiologists and public health analysts that have been trained to understand, you know, how to run analyses and come to conclusions about various health trends, but this new landscape of health data is much more complicated, and the attempt to break down silos behind, you know, where data comes from and how it's interconnected across this health landscape requires new sets of skills and expertise, and that's really what this sort of forward-thinking, you know, new approach towards job classification series is all about.

SHEEHAN: 

Sure, and that makes complete sense, that as technology progresses, the landscape changes. And I think it's interesting that, sort of, that 'where the rubber meets the road,' in that case is- is just the job description of like, what a job is that someone's expected to perform. Can you explain some of the- some of the hesitancy or resistance to change that might be, that might, that might come up as a result?

WHITEMAN: 

Yeah. So, you know, any process we know in government, whether it's state or federal, takes a long time. There's a lot of people involved. It's, you know, it takes a lot of power to move a big ship. And I think that some of the hesitance might be, you know, about, you know, you know, the world. What's been working so far has been working for us, or maybe there's funding challenges. But I think that one of the, you know, major arguments for doing this kind of thing, for creating a new informatics-based classification series for jobs is really in the opportunity cost of not doing it. You know, as- as states and territories move forward and modernizing their data systems, which at this point is, you know, a train that's left the station already, it's continuing, you know, in in hopefully, in perpetuity, you know. There's going to be a cost of doing things the more traditional way. You know there's a cost to not having people that understand the interconnectedness of health data from across different sources. And you know, locations of health data comes from, whether it's hospitals, clinics, other states, other territories, all the various places that these records can come from, having someone who doesn't understand how to collect these pieces of information from various sources, combine them and make them into a usable format for the epidemiologists to then analyze. It limits what you're able to do from a surveillance standpoint, from a response standpoint, so this really is thinking about, how can we modernize and break down the silos that we've experienced in public health data, really up until the last 10 years or so? This is about thinking forward.

SHEEHAN: 

And you touched on this a little bit, but could you, can you expand a little more on what it means to create an informatics-based job classification?

WHITEMAN: 

Yeah, so we know it's, it's not necessarily a simple process, but basically, there's a few steps in the process. So, we think about the idea of identifying the need. You know, what makes this different job classification series more valuable than what we already have? You know, that's something that we'd have to think through, certainly at first, understanding the approval processes and requirements that are required for your particular health department. Every health department has different ways of doing things. Understanding what's needed from an approval and, sort of, bureaucratic or administrative process for your particular health department is an important next step. After that, you need to gather job descriptions, competencies, and key skills that are required for this, for this particular type of job series that are unique across the other public health job- job classification series. And then lastly, there's salary benchmarking and other processes and considerations that take place as you go through this, this- this, this sort of journey, if you will. We are at ASTHO putting together documentation to help guide you through this process. We have links and external documents and resources from across the, you know, network of collaborators that we work with that have already gone through processes like this that- that hopefully will assist you in taking similar steps.

SHEEHAN: 

And can you give us an example of some of the roadblocks or the logjams that can happen when maybe a job role is different than the way it was traditionally classified?

WHITEMAN: 

Yeah, you know, I think one of the issues that we're experiencing now is that, you know, there are new skills that, you know, as we've talked about, there's- there's new skills and new challenges that are coming about because of this data modernization wave that's taking place across the country. And one of the issues we're seeing is that traditional public health analysts, data analysts or, you know, epidemiologists, don't necessarily have the backgrounds or training to be able to understand how to navigate these complicated waters. In many ways, these new processes are not health-related. They're more, sort of, general data-related issues. Theoretically, data modernization can take place across any industry, and I think that, it's - would be the same sort of challenges. So here, what we're asking people to do, in many cases, is people with complex and well-trained backgrounds in health sciences, or, you know, understanding health disparities, are being asked to work on projects or problems that are really more about data infrastructure or data storage interoperability standards across electronic health records. Things that, honestly, they don't really teach you about in grad school very much. That's a whole separate conversation. But really, that's, I think, where we see, you know, particular log jams where people just don't have the skills and training to meet this new need. And so, that's really where this is coming about, is identifying the responsibilities and the potential to bring on new people, new staff, that do have these skills and expertise, and many of them might not even have those backgrounds in particularly health sciences. They might just be data management gurus that are just really good at this kind of thing. Understand how to break down barriers and join data sets from across the, you know, the landscape, and again, that doesn't necessarily require a health background in particular. So, you know, I think that's, that's where this is particularly exciting, is the idea and potential to bring in people who may, maybe are in other disciplines, who could provide a lot of value in public health because of their knowledge and experience in working with data.

SHEEHAN: 

Yeah, and continue with that train of thought, what- what's, sort of, the upside of having people that- that know, a current or a modern data infrastructure.

WHITEMAN: 

Yeah. So, so again, this, sort of, gets at this opportunity cost. And if you think about, for example, in in the event of an outbreak, or even COVID, or, you know, we experienced this very much during during COVID a few years ago, where states, and federal authorities, and territories were attempting to gather testing data or vaccine data that was coming from all different types of sources, hospitals, clinics, university systems, nonprofits that were doing all kinds of different community outreach, and, you know, all kinds of information that was being collected from all different types of sources. There were people that had to gather and put that information into a single, usable format. It took a lot of time to understand, you know, how to make data from different sources speak to each other, how to allow standards for across the data landscape, so that we can glean actionable information in an operational standpoint from this data that's coming from all different types of places, that is a costly input in terms of a time and resources process, and therefore, I think a lot of the value that's- that's in a position like this, or in creating positions like this, is having people on staff that understand those processes.

SHEEHAN: 

Yeah, absolutely. Data is only as good as the people you've got interpreting it.

WHITEMAN: 

Right. And this is also, you know, I think there's a difference between data interpretation and then the- what's required to get the data into the shape that it can be interpreted in the first place. One of the criticisms that people had, you know, during the COVID response was that it would take, you know, the latest data ... on- on some of these national dashboards was only from three weeks or a month ago. But the reality was, it takes a lot of time for data from 50 states, plus all the territories, and all the health centers and hospitals that are within those systems, to take those in for all those disparate pieces of information and put them together and make them usable. So ideally, you know, part of what we are looking to do out of advising states and territories to bring on staff that have these skill sets, is to allow for us to have, again, shorter processes for accumulating, storing, and understanding data from different systems. And again, that- that all leads to more actionable and faster interpretation, which therefore leads to faster and more actionable public health, you know, interventions in the community.

SHEEHAN: 

Along those lines, do you have any suggestions or first step for, say, an office or even an individual who wants to get- get started down this road?

WHITEMAN: 

Yeah. So, ASTHO is working on a number of different documents and resources for states and territories that are interested in developing a public health informatics job classification series. We have a 'how-to' guide that will be appended to this brief. And we'd love for you to check out these documents on our website where you can follow the steps that we've laid out to create this- this, you know, job classification series for yourself. I would also like to note that we at ASTHO have directly supported states and territories in their process for doing this work. So, if you're interested in working with us or collaborating with us, or receiving, you know, support or advice from us on going through this, and hopefully, you know, we can tailor our advice to your specific situation, we would certainly look forward to doing so.

SHEEHAN: 

Ari Whiteman is ASTHO's senior advisor for public health data and informatics workforce, and holds a PhD in health, geography, and epidemiology from UNC Charlotte.

ASTHO announced the sixth cohort of its Developing Executive Leaders in Public Health Program, which aims to strengthen leadership capacity among mid- to-senior-level public health professionals. This year's scholars will participate in a cohort-based experience that includes executive coaching, leadership development, and skill-building sessions. Find more details in the show notes.

This has been Public Health Review Morning Edition. I'm John Sheehan for the Association of State and Territorial Health Officials.