01Research
Healthcare labor markets, workforce shortages, and the substitutability of care
Health systems are, above all, made of people. My dissertation studies what happens when the supply of those people shifts — when caregivers gain or lose childcare, when immigration policy changes who is available to work, and when the providers on shift shape the care a mother receives. Three papers, three margins of the same question.
WORKING PAPER 01 · DRAFT COMPLETE
Schools Reopening and Nursing Home Staff Labor Supply
When schools closed during the pandemic, did childcare obligations pull certified nursing assistants out of nursing homes — and did reopening bring them back?
204,455
workers observed
1,658
facilities
21
states
Why it matters
Nursing home staffing collapsed during COVID-19, with deadly consequences for residents. But it was hard to tell how much of the collapse came from infection risk, burnout, or wages — versus a quieter channel: the workers, overwhelmingly women, who suddenly had children at home all day. Isolating the childcare channel matters because it points to a very different set of policy fixes.
How I answer it
I link the CMS Payroll-Based Journal — daily, worker-level staffing records — to district-by-district variation in school reopening modality (in-person, hybrid, remote). Because neighboring districts reopened differently for reasons unrelated to nursing home conditions, this variation lets me isolate the childcare channel from everything else happening in the pandemic labor market.
What I find
A 10 percentage-point increase in in-person schooling raises CNA hours by 0.27 hours per worker-month, concentrated on the intensive margin — existing staff working more, rather than new staff returning.
What it means for policy
Childcare access is long-term care workforce policy. When schools function as childcare infrastructure, closing them quietly drains the caregiving workforce that the most vulnerable populations depend on.
WORKING PAPER 02 · PRELIMINARY ANALYSES COMPLETE
Variance, Drivers, and Timeliness of Facility-Based Obstetric Care in Kakamega County, Kenya
When a mother delivers in a Kenyan health facility, what determines whether she gets good, timely care — the facility she chose, the provider she drew, or the moment she arrived?
1,742
deliveries observed
10
facilities
−2.4pp
post-handoff quality
Why it matters
Getting mothers to deliver in facilities was the great maternal health push of the last two decades — and it worked. But facility delivery only saves lives if the care inside is good. Understanding where quality varies (between facilities? between providers? delivery to delivery?) tells us whether to invest in infrastructure, training, staffing, or care processes.
How I answer it
Using direct clinical observations of 1,742 deliveries across 10 facilities from Kenya's Service Delivery Redesign, I decompose the variance in care quality and timeliness across facility, provider, and delivery levels, estimate peer effects among providers working together, and measure what happens to care quality when a delivery is handed off between providers.
What I find
Quality variance concentrates at the facility and provider levels — but timeliness variance lives at the delivery level. Providers exert measurable peer effects on each other (~0.06 after case-mix and leave-one-out corrections), and care quality drops 2.4 percentage points after a shift handoff.
What it means for policy
Quality improvement and timeliness improvement are different problems. Quality tracks who and where; timeliness tracks when and what else is happening — so staffing-level and workflow interventions, not just training, are on the critical path.
WORKING PAPER 03 · DATA COLLECTED, ANALYSIS UNDER WAY
Immigrant Labor Supply and the Capital Margin of U.S. Nursing Homes
When immigrant caregivers become scarce, do nursing homes buy machines to replace them — or machines to help the workers who remain?
HCRIS
facility capex data
Bartik IV
identification
SNFs
U.S. skilled nursing
Why it matters
The U.S. long-term care workforce is disproportionately foreign-born, and immigration policy swings its supply. Economists usually study the labor response to these shocks. But there's a capital margin too: facilities can respond by substituting equipment for people, or by investing in technology that makes remaining workers more productive. Which one happens shapes both care quality and what restrictive immigration policy actually costs.
How I answer it
A shift-share (Bartik) instrument — national immigration flows interacted with pre-period settlement patterns — isolates plausibly exogenous variation in local immigrant labor supply, linked to facility-level capital expenditure from Medicare cost reports (HCRIS).
What I find
Analysis beginning — data collection complete.
What it means for policy
If capital substitutes for scarce caregivers, immigration restrictions accelerate automation of intimate care work; if capital complements labor, restrictions simply make care scarcer and more expensive. The answer determines who bears the cost.
Published work
TB & HIV economics
Before the dissertation, my research measured the costs, cost-effectiveness, and delivery of TB and HIV care in sub-Saharan Africa — 14 peer-reviewed papers in NEJM, PLOS Medicine, BMJ Global Health, Value in Health, JIAS, IJTLD, Implementation Science, and others. Selected work:
- 2021
Costs along the TB diagnostic pathway in Ugandafirst author
International Journal of Tuberculosis and Lung Disease
- 2020
Redefining and revisiting cost estimates of routine ART care in Zambiafirst author
Journal of the International AIDS Society
- 2021
Multicomponent strategy with decentralized molecular testing for tuberculosis
New England Journal of Medicine · with Cattamanchi et al.
- 2022
Cost-effectiveness of digital adherence technologies for TB treatment
Value in Health · with Thompson et al.
- 2022
Cost-effectiveness of human-centered design for TB case finding
BMJ Global Health · with Liu et al.
- 2021
Community health worker-delivered TB evaluation
PLOS Medicine · with Cattamanchi et al.
- 2020
A costing framework for TB interventions
Implementation Science · with Sohn et al.