Data: F30s and MD/PhD programs, program size

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Lucca

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Hey All,

3 years ago @Fencer posted some data on NIH F30 NRSA awards and the size of MD/PhD programs.

Because I've been playing around with ggplot2 in R and was interested to see if anything had changed since, I followed his methodology and used the NIH RePORTER system to search for active F30s, downloaded and sorted the data according to institution, and then used AAMC T36 B-11 to find which institutions were awarded F30s as a proportion of their MD/PhD program size.

Here's what I found for all institutions with at least 2 active F30s as of 12/27/2016:
kdkQkzn.png


Minimum number of F30s awarded: 2
1st Quartile: 4
Median: 6.0
Mean: 6.4
3rd Quartile: 8.0
Max: 14.0

GTZUOrF.png


Minimum proportion of MD/PhD program with an active F30: 1.00%
1st Quartile: 4.0 %
Median: 7.4%
Mean: 8.4%
3rd Quartile: 11.4%
Max: 19%

While MSTPs dominate the number of active F30s by raw numbers, they also tend to be much larger than their non-MSTP counterparts. Also, it should be noted that AAMC T36 B-11 lists the total program size. It would be more appropriate to recreate these graphs using the proportion of each program with active F30s starting at GS1 and above (when one might be expected to apply for the F30). Unfortunately, we do not have that data. Cleveland Clinic Lerner College of Medicine has 2 active F30s but it is not an MD/PhD program so I estimated the program size at 200 (50/yr * 4 -- I know it's a 5 year program, but it is already a fairly pointless datapoint in this graph and I noticed that after the fact).

There are programs like the one at the University of Washington that boast of having F30 funding rates of nearly 100%. However, it is obvious that not every MD/PhD student at the University of Washington is applying and obtaining an F30 (their F30/Program Size ratio is about 9%), so this information provides a little more context when reading those self-reported numbers.

One last observation: Where the hell is Johns Hopkins?

Note that I did not include the F31 (or CTSA) award in these graphs, but only the F30, which could explain why I did not retrieve F30/Program Size ratios quite as high as @Fencer did in 2013.

Hope this info is of interest to any of you. Please let me know if you have suggestions or further questions and I can go back to the data and try to respond when I have the time.

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Great post. I attached other data.
 

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Was all of this self-compiled?

I found it on SDN a few years ago, but don't remember what thread it was in or who posted it. It is supposedly accurate though, and seems to agree with the attached stats.
 

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Great post. Increasingly however it seems like some institutions are moving away from the F30 mechanism for MSTP-supported students - e.g. NINDS and NIBIB as of June 2016. I'd love to hear from those in the know if this will be the new norm across institutions, or just temporary
 
Hey All,

3 years ago @Fencer posted some data on NIH F30 NRSA awards and the size of MD/PhD programs.
....

Note that I did not include the F31 (or CTSA) award in these graphs, but only the F30, which could explain why I did not retrieve F30/Program Size ratios quite as high as @Fencer did in 2013.

Hope this info is of interest to any of you. Please let me know if you have suggestions or further questions and I can go back to the data and try to respond when I have the time.

An easier AAMC table to use to calculate the program census is table B-12 ( https://www.aamc.org/download/321556/data/factstableb12.pdf )

If you obtain the ratio of NIH F30 awards divided by the census, then you obtain a more accurate comparison of the maximum funding rate for each program. However, since my post, the NIH has decided to have two different FOAs for F30 awards, one for MSTP funded institutions and another for non-MSTP funded institutions.

MSTPs (NIGMS T32 awards) fund about 20-30% of the slots in each of these programs, often assigning T32 slots to students in their first 3 years of training (MS 1,2, GS 1). The eligibility to apply for a F30 is only during the first 4 years, typically submitting in year 4 (GS 2), once the PhD project (i.e.: the proposed science in the fellowship training grant) has been thought and developed, but not yet fully completed. The F30 can cover up to 6 years of training (less if awardee was supported by T32) which might include MS-3,4. The cost of tuition/salary during PhD training GS 2 - 4) is often charged to the grants of the PhD mentor, thus, about 60-70% of MSTP costs is eventually paid by NIH, and if the MSTP student gets F30 funding, then perhaps close to 80% for that particular student (it is less b/c tuition is paid up to a cap & only 60%). That was part of their rationale to create a two-tier F30 system this year. The data collected above is prior to the new FOAs, perhaps only 1 cycle of new two-tier F30s. Institutions use endowments and other funds to cover the rest of MSTP training costs (tuition, stipends, fees, administration, speakers, etc.). If you look at table B-12, MSTPs are larger programs with 40 - 195 students, whereas there are only about 20 MD/PhD programs with census of more than 30 MD/PhD students that are not MSTP. How to pick between non-MSTPs? Use data like F30 funding rates...
 
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Great post. Increasingly however it seems like some institutions are moving away from the F30 mechanism for MSTP-supported students - e.g. NINDS and NIBIB as of June 2016. I'd love to hear from those in the know if this will be the new norm across institutions, or just temporary

Fwiw, I applied to nibib funded programs this year and asked if I could apply for the f30/31 before I did, and got the impression that they encourage it :lame:
 
I found it on SDN a few years ago, but don't remember what thread it was in or who posted it. It is supposedly accurate though, and seems to agree with the attached stats.

lol at this approach... "I found some old data on SDN--I have no idea what the source was or if it's reliable."

If you want to do a real analysis, you can obtain the data here: https://projectreporter.nih.gov/reporter.cfm
 
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Hey All,

3 years ago @Fencer posted some data on NIH F30 NRSA awards and the size of MD/PhD programs.

Because I've been playing around with ggplot2 in R and was interested to see if anything had changed since, I followed his methodology and used the NIH RePORTER system to search for active F30s, downloaded and sorted the data according to institution, and then used AAMC T36 B-11 to find which institutions were awarded F30s as a proportion of their MD/PhD program size.

Here's what I found for all institutions with at least 2 active F30s as of 12/27/2016:
kdkQkzn.png


Minimum number of F30s awarded: 2
1st Quartile: 4
Median: 6.0
Mean: 6.4
3rd Quartile: 8.0
Max: 14.0

GTZUOrF.png


Minimum proportion of MD/PhD program with an active F30: 1.00%
1st Quartile: 4.0 %
Median: 7.4%
Mean: 8.4%
3rd Quartile: 11.4%
Max: 19%

While MSTPs dominate the number of active F30s by raw numbers, they also tend to be much larger than their non-MSTP counterparts. Also, it should be noted that AAMC T36 B-11 lists the total program size. It would be more appropriate to recreate these graphs using the proportion of each program with active F30s starting at GS1 and above (when one might be expected to apply for the F30). Unfortunately, we do not have that data. Cleveland Clinic Lerner College of Medicine has 2 active F30s but it is not an MD/PhD program so I estimated the program size at 200 (50/yr * 4 -- I know it's a 5 year program, but it is already a fairly pointless datapoint in this graph and I noticed that after the fact).

There are programs like the one at the University of Washington that boast of having F30 funding rates of nearly 100%. However, it is obvious that not every MD/PhD student at the University of Washington is applying and obtaining an F30 (their F30/Program Size ratio is about 9%), so this information provides a little more context when reading those self-reported numbers.

One last observation: Where the hell is Johns Hopkins?

Note that I did not include the F31 (or CTSA) award in these graphs, but only the F30, which could explain why I did not retrieve F30/Program Size ratios quite as high as @Fencer did in 2013.

Hope this info is of interest to any of you. Please let me know if you have suggestions or further questions and I can go back to the data and try to respond when I have the time.

This is excellent work, but I think there may be a glitch in your data collection. I am a GY-3 in the MD/PhD program at University of Kansas. I know that, as of the time you collected data, we had 3 active F30s but I do not think we are on here.

Cheers
 
This is excellent work, but I think there may be a glitch in your data collection. I am a GY-3 in the MD/PhD program at University of Kansas. I know that, as of the time you collected data, we had 3 active F30s but I do not think we are on here.

Cheers

hmm it appears ur right. It's been a while but I'll see if Kansas was missing from the file I downloaded from the search database or if I messed up somewhere.
 
hmm it appears ur right. It's been a while but I'll see if Kansas was missing from the file I downloaded from the search database or if I messed up somewhere.
Sounds good. Just want to make sure Kansas gets the credit it deserves (11.1% of program have active F30s). Seems like a decent way to evaluate a non-MSTP program. We just received word that another student's F30 application was awarded, as well, so we are coming for you OHSU!

Rock chalk
 
Sounds good. Just want to make sure Kansas gets the credit it deserves (11.1% of program have active F30s). Seems like a decent way to evaluate a non-MSTP program. We just received word that another student's F30 application was awarded, as well, so we are coming for you OHSU!

Rock chalk

UK is definitely in the raw data from the NIH reporter system. It is listed in the raw data as "University of Kansas Medical Center" and when parsing the data I probably either made a typo in the school name or used another name for the program. When I get the time I'll update the OP, I still have the scripts so it shouldnt take very long to make a new figure.

edit: I actually know exactly what the problem was. The AAMC list of MD/PhD programs has Kansas listed as "University of Kansas School of Medicine". What I did was take all the institutions in the raw data and cut it down to only the F30s that relate to institutions with MD/PhD programs (according to the AAMC). Since the names dont match up, Kansas numbers were lost in the process.
 
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Great work, as usual, Lucca; thanks for putting this together.
I am also curious to know why Hopkins is missing from that list. I made a point to ask every program director about the F30 success rate at interviews and was told Hopkins has had a "near 100% success rate" in the last 5 years, when I asked. Surely that's not fewer than 2 folks (even if the data are for just 1 year)...
 
Great work, as usual, Lucca; thanks for putting this together.
I am also curious to know why Hopkins is missing from that list. I made a point to ask every program director about the F30 success rate at interviews and was told Hopkins has had a "near 100% success rate" in the last 5 years, when I asked. Surely that's not fewer than 2 folks (even if the data are for just 1 year)...

My guess is the search was done using the wrong school name listed in project reporter. There are currently 4 students with F30s. 1-2 is the typical number of new F30s each year and it generally seems those that apply get them.
 
My guess is the search was done using the wrong school name listed in project reporter. There are currently 4 students with F30s. 1-2 is the typical number of new F30s each year and it generally seems those that apply get them.

Like Kansas, there’s probably a mismatch between the program name in the AAMC banks and the program name in the RePorTer. Unfortunately I’m quite busy with grad school + AMCAS at the moment so I can’t update these charts, but anyone is welcome to follow my basic method :)
 
I just checked manually, and Hopkins seems to have 4 students with F30, also Weill Cornell seems to have 14 total and UPenn has 17. Unless I am missing something, there is seems to be a discrepancy.
 
Things change every year, and even every few weeks. I did recheck Lucca's data when it was obtained back in 2016. It was accurate. I had a prior dataset from 2014 that I made into a thread. The point is that several non-MSTP programs are suitable locations for greatness...

I can tell you that my program has a couple that have not made it to NIH reporter despite receiving a NOA for very near future.
 
OHSU was a MSTP from 2004-2010, and regained their MSTP award back in July 2016 (check this out in NIH Reporter). Kudos to them!

NIH MSTP applications have a lot of moving parts, often being several hundredths of pages in the core application (including faculty biosketches) but the update allows for student biosketches, so you might end up submitting 1000+ pages (even without the relatively new rule of no appendix).
 
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As someone who has written 2 MSTP grants (1 funded and 1 scored but not funded) and who has reviewed them, you need to understand that these institutional application often exceed 1000 pages. Attention to detail is critical. The FOA for the MSTP grants changed in 2019 and again will be changing in 2021. The review process now requires actively monitored mentoring programs for mentors, enhanced assessment of training, and other factors in the curriculum (R&R) that were not described in previous proposals. All changes mean that you just can't update the training tables (which have also changed over the years) and submit a renewal. It takes a LOT of work. As a society, we host webinars for all programs to help them see the factors that are seen as innovative and worth emulating. If a new director assumes that is just a casual re-write, they are doomed to fail and it takes an extra year to resubmit. In general, all MSTPs have a critical size and substantial institutional commitment. For example, a new Dean slashing costs might doom a program's renewal.
 
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Fencer is trying to scare me into retirement.

Seriously though, the NIH does not play around and will nail programs that do not measure up. In fact, in my years running an MD-PhD program, 5 of the top 10 schools in the US News rankings have had their MSTP grant reduced due to significant deficiencies in their program. In these cases, the NIH reduced the funding by a third and forced them reapply in 3 years instead of 5 years. This is a form of shock therapy intended to catch the attention of the dean. In every case, it worked. The program leadership was replaced (not that they were necessarily at fault) and the dean dumped a ton of money in the program. (This makes sense, even for the densest dean. Each student represents a commitment of $500,00 or more in stipend and tuition. If the grant is lost, the Dean is on the hook for some of that cost. Students admitted in 2020 are still on the payroll in 2028, even if you lost your grant in 2025.) These programs all did what was necessary to improve, and were renewed for 5 years at the next grant submission.

As Fencer indicated, MD-PhD programs are pretty unique in that we actively work to make our "competitors" better. This attitude of mutual aid is a hallmark of MD-PhD programs. We believe that we all benefit when we all are strong. It does my school no good if Harvard (or Indiana) has a crappy MD-PhD program. My school needs to be able to attract well-trained individuals into faculty positions, and we need Harvard (and Indiana) to train excellent physician-scientists. I have served as an external reviewer for several programs, and have suggested changes to make them stronger programs. We, too, have opened our program to our peers, sharing our data and exposing our shortcomings to them. They suggested improvements that allowed us to get our best priority score ever on our last renewal. (Though reviewer 3, who shall remain nameless, gave us a hard time.) It is truly a privilege to work with people like Fencer, who will fight with me over an applicant, then treat me to an extraordinary glass of wine when we are at a conference and help me figure out how to make my program better.
 
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