FutureDocs Forecasting Tool An Open Source Physician Projection Model
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Transcript of FutureDocs Forecasting Tool An Open Source Physician Projection Model
FutureDocs Forecasting Tool
An Open Source Physician Projection Model
Erin P. Fraher, PhD, MPPwith G. Mark Holmes, PhD and Andy Knapton, MSc
Cecil G. Sheps Center for Health Services ResearchUniversity of North Carolina at Chapel Hill
July 29, 2014
This project is funded by a grant from The Physicians Foundation.
In case your editor calls, here’s why our model is innovative in 2 slides: Slide 1
Starts with different question-what services will patients need versus how many doctors will we need?
Uses different geography-state and sub-state data highlight differences between “haves” and “have nots”
Displays data in interactive format-model is web-based, open source and designed to be customized, challenged and improved
Seeks different outcome-designed to educate and engage stakeholders in redesigning system
This project is funded by a grant from The Physicians Foundation.
In case your editor calls, here’s why our model is innovative in 2 slides: Slide 2
Mindset — it’s a tool, not an answer. Tool allows user to choose from:
3 models — supply, utilization, relative capacity (a.k.a. “surplus/shortage”)
3 types of visualizations — maps, line charts and population pyramids
3 geographic views — national, state and sub-state level 5+ alternate futures — “what if” scenarios regarding ACA
implementation, physician FTEs, retirement, use of NPs and PAs, and redistributing graduate medical education (GME)
This project is funded by a grant from The Physicians Foundation.
Presentation Overview
Highlight why our model is a disruptive innovation Explain (at ~60,000 feet!) methodology Demonstrate sample findings Answer your questions
This project is funded by a grant from The Physicians Foundation.
Our model is a disruptive innovation that challenges traditional workforce modeling
Silo-based projections by physician specialty No “what if” scenarios Proprietary (read: black box) &
uncustomizable models Not regularly updated Lack friendly and interactive user interface
This project is funded by a grant from The Physicians Foundation.
https://www2.shepscenter.unc.edu/workforce
This project is funded by a grant from The Physicians Foundation.
Innovations in modeling physician supply
Supply Side Innovations Modeled patient care hours (patient care FTE) First model to include detailed GME training pathways,
including sub-specialization trends Includes scenario that redistributes GME slots to states and
specialties where greatest need
This project is funded by a grant from The Physicians Foundation.
Created Clinical Service Areas (CSAs) to capture why and where people seek care 19 Clinical Service Areas (e.g., respiratory conditions, circulatory
conditions, endocrinology, mental health, preventative care, etc.) Modeled use of health care in 3 settings:
outpatient (including physician offices and hospital outpatient settings)
inpatient settings emergency departments
Innovations in modeling patient use of health care services
This project is funded by a grant from The Physicians Foundation.
Developed sub-state unit of geography, Tertiary Service Areas (TSAs)
To capture sub-state variation, created TSAs Based on Dartmouth’s Hospital Referral Regions
TSAs are markets that encompass primary and specialty care services
Health system consolidation and ACOs and ACO-like structures create need for region-based data
This project is funded by a grant from The Physicians Foundation.
Plasticity matrix brings supply and service use together by mapping physicians to services
Starting question: what health services will patients need?
Next question: which physician specialties can provide those services?
Innovation: plasticity matrix maps services provided by physicians in different specialties to patients’ visits
This project is funded by a grant from The Physicians Foundation.
Plasticity—Providers and Services: A sample matrix for outpatient settings
Number of outpatient visits, select specialties and CSAs
This project is funded by a grant from The Physicians Foundation.
Plasticity—Providers and Services: A sample matrix for outpatient settings
Within a CSA, how are outpatient visits are distributed across specialties?
Number of outpatient visits, select specialties and CSAs
This project is funded by a grant from The Physicians Foundation.
Plasticity—Providers and Services: A sample matrix for outpatient settings
Number of outpatient visits provided per FTE per year, select specialties and CSAs
This project is funded by a grant from The Physicians Foundation.
Plasticity—Providers and Services: A sample matrix for outpatient settings
Within a specialty, how are visits distributed across CSAs?
Number of outpatient visits provided per FTE per year, select specialties and CSAs
This project is funded by a grant from The Physicians Foundation.
These Innovations turn workforce modeling upside down
Model does not produce estimate of counts of physicians needed by specialty
Instead, it asks: what are patients’ needs for care and how can those needs be met by different workforce configurations in different geographies?
This project is funded by a grant from The Physicians Foundation.
“Relative Capacity”: Indicator of how well physician supply matches use of servicesModel calculates “relative capacity”—a measure for each clinical service area in each geography
= supply of visits physicians in that TSA/State can provide utilization of visits needed by population in TSA/State
<.85=shortage .85-1.15=in balance >1.15=surplus
This project is funded by a grant from The Physicians Foundation.
You end up with a picture that shows capacity of workforce to meet demand for
different types of health servicesShortage/Surplus for Outpatient Circulatory Visits by TSA, 2014
Washington, DC
Boston, MA
New York, NY
Atlanta, GA
Raleigh-Durham, NC
Miami-Fort Lauderdale, FL
Dallas-Fort Worth, TX Houston, TX
San Francisco, CA
Los Angeles, CA
Slidell, LA
Rochester, MN
Boulder, CO
Huntington, WV
Bangor, ME
This project is funded by a grant from The Physicians Foundation.
Just a few interesting findings to show model capacity
FutureDocs Forecasting Tool
This project is funded by a grant from The Physicians Foundation.
Supply model: Pediatric surgical FTEs double between 2011 and 2030
699
1,402
This project is funded by a grant from The Physicians Foundation.
Supply model: 12% decline in general internal medicine FTEs
51,553
58,849
This project is funded by a grant from The Physicians Foundation.
Not much change in shortage/surplus for all visits at the national level
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This project is funded by a grant from The Physicians Foundation.
But looking at national data conceals broad variation between geographies
Shortage/Surplus for All Visits, All Settings by TSA, 2014Aurora, IL
New Orleans, LA
Washington, DC
Boston, MA
New York, NY
Atlanta, GA
Raleigh-Durham, NC
Miami-Fort Lauderdale, FL
Dallas-Fort Worth, TX Houston, TX
San Francisco, CA
Los Angeles, CA
Slidell, LA
Rochester, MN
Boulder, CO
Huntington, WV
Bangor, ME
Melrose Park, IL
This project is funded by a grant from The Physicians Foundation.
Health system is rapidly changing.Need scenarios to model “what ifs”
Model includes scenarios for: Baseline model (2011) assumes ACA not implemented Utilization side — implement exchanges and different
Medicaid assumptions On supply side — change retirement, FTE, use of
NPs/PAs, and redistribute GME
This project is funded by a grant from The Physicians Foundation.
What would be effect on shortage/surplus if all states expanded Medicaid?
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Shortage/surplus for all visits in all settings if all states expand Medicaid
This project is funded by a grant from The Physicians Foundation.
The model highlightsdifferential effect between states:
Medicaid expansion has larger effect in Texas…
This project is funded by a grant from The Physicians Foundation.
…And a smaller effect in Massachusetts
This project is funded by a grant from The Physicians Foundation.
We modestly redistributed GME slots to specialties/states where demand > capacity in 2030
State Number of slots received
Nevada 88
Tennessee 50
Florida 47
Montana 36
Utah 16
Georgia 10
New Mexico 7
Total 254
State Number of slots removed
New York 101
Michigan 73
Washington, DC 63
West Virginia 7
Rhode Island 6
Massachusetts 4
Total 254
Specialty that loses the most slots: Emergency medicine, 60 slots Specialty that gains the most slots: General internal medicine, 61 slots
(Note that family medicine gains 55 slots.)
This project is funded by a grant from The Physicians Foundation.
Example: GME scenario removes 40 emergency medicine slots from New York, reducing emergency
medicine physician supply in that state
3,785 patient care FTEs under baseline, 20303,499 patient care FTEs under GME redistribution, 2030-7.6% difference
This project is funded by a grant from The Physicians Foundation.
But New York still has surplus capacity for ED visits, even when 40 residency slots are removed
2.58 supply/visits under baseline, 20302.41 supply/visits under GME redistribution, 2030-6.6% difference
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This project is funded by a grant from The Physicians Foundation.
GME redistribution has differential effect by state: Nevada benefits but IM still declines
171 patient care FTEs under baseline, 2030189 patient care FTEs under GME redistribution, 2030+10.5% difference
This project is funded by a grant from The Physicians Foundation.
Now let’s field some questions…
We’ll take the next 10 minutes for any questions For interview requests please contact