Introducing the Certificate of Need Panel Database

Certificate of Need (CON) laws require healthcare providers to obtain state approval before opening new facilities, expanding existing facilities, or introducing certain healthcare services or equipment. We’ve covered them frequently here, and I’ve written several papers on them.

But my research evaluating the effects of CON on healthcare facilities, spending, and outcomes (along with everyone else’s) always had the drawback that we relied on fairly crude measures of CON- often just a binary measure of whether a state had any CON requirements at all. The problem with this is that different states have wildly different approaches to CON- some states like Vermont require CON for as many as 27 separate types of health facilities, services, or equipment, including major ones like hospitals, while other states like Ohio require CON for only a single type (nursing homes). Previous attempts to catalog this variation tended to produce single-year snapshots (e.g. Institute for Justice, Cicero, Mercatus, NCSL). These are helpful for policymakers wanting to see how their state compares to others, but not so useful to researchers trying to measure the effects of CON, who would typically prefer many years of historical data.

The dataset us CON researchers have always wanted is now here!

It tracks 31 different types of healthcare facilities, services, and equipment that are sometimes regulated by CON, showing which ones required a CON in each state in every year back to 1990 (going even further back for some states). This means our national panel has more than 55,000 data points.

Number of Certificate of Need Requirements Per State, 2025

I’ve spent the last 2+ years working on this with a large team of coauthors (Sriparna Ghosh, Conor Norris, and Justin Leventhal) and research assistants, with support from Providence College and the Knee Regulatory Research Center at WVU. It involved reading decades of old state statutes on HeinOnline and Westlaw. We’ve released a paper, Certificate of Need: A New Comprehensive Panel, explaining the dataset in more detail and sharing ideas for how researchers could use it.

Change In Certificate of Need Requirements Per State, 1990 to 2025
Change In Number of States Requiring Each Type of CON From 1990 to 2025

The dataset is public and free for everyone to use- we just ask that people cite us (though feel free to ask any of the dataset’s creators if you do want us as coauthors on your paper using the data). I’d love to hear your ideas for how you might use it, or how we can improve it- this is Version 1.0 but we plan to maintain and improve it going forward so that it can become the standard for the field.

Kaggle Wins for Data Sharing

I like to take existing datasets, clean them up, and share them in easier to use formats. When I started doing this back in 2022, my strategy was to host the datasets with the Open Science Foundation and share the links here and on my personal website.

OSF is great for allowing large uploads and complex projects, but not great for discovery. I saw several of my students struggle to navigate their pages to find the appropriate data files, and they seem to have poor SEO. Their analytics show that my data files there get few views, and most of the ones they get come from people who were already on the OSF site.

This year I decided to upload my new projects like County Demographics data to Kaggle.com in addition to OSF, and so far Kaggle is the clear winner. My datasets are getting more downloads on Kaggle than views on OSF. I’ve noticed that Kaggle pages tend to rank highly on Google and especially on Google Dataset Search. I think Kaggle also gets more internal referrals, since they host popular machine learning competitions.

Kaggle has its own problems of course, like one of its prominent download buttons only downloading the first 10 columns for CSV or XLSX files by default. But it is the best tool I have found so far for getting datasets in the hands of people who will find them useful. Let me know if you’ve found a better one.