Distribution across 10 profiles.
Middle half of Health Economists score between 25% and 31%.
0%
50%
100%
p10 · 23%
32% · p90
Task breakdown by work type
On-screen work81%
Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.
In-person + screen8%
Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.
Computer + action1%
Computer input, real-world output — needs someone to act on it, not just software.
Fully in-person9%
No computer required. Furthest from automation — the strongest human advantage.
Typical tasks
3 synthetic profiles for a Health Economist, ordered by automation exposure.
Tab between them to see how task mix drives the score difference.
TaskTimeTypeExposure
Conduct literature reviews and synthesize evidence from published studies to support policy analysis, health technology assessment, or grant proposals
deep expertisesocial core
25%DD
19%
Build and maintain econometric models to analyze healthcare cost trends, utilization patterns, and treatment outcomes using administrative claims data and survey datasets
deep expertisesocial element
20%DD
22%
Prepare written reports, policy briefs, and presentations translating statistical findings into actionable insights for stakeholders (payers, government agencies, hospital systems)
deep expertisesocial core
18%DD
17%
Collaborate with clinical teams, data scientists, and project leads in meetings to scope research questions, validate assumptions, and troubleshoot analytical challenges
some context neededsocial core
13%AA
10%
Respond to ad-hoc analytical requests from internal clients or external partners, including rapid feasibility assessments and custom data pulls
some context neededsocial core
11%AD
14%
Design and execute cost-effectiveness analyses or budget impact models to evaluate new drugs, devices, or care delivery interventions
deep expertisesocial element
8%DD
28%
Clean, validate, and prepare large healthcare datasets (reconciling data quality issues, handling missing values, creating analysis-ready cohorts)
1%DD
68%
TaskTimeTypeExposure
Conduct literature reviews and synthesize evidence from published studies to support policy analysis, health technology assessment, or grant proposals
deep expertisesocial core
26%DD
18%
Build and maintain econometric models to analyze healthcare cost trends, utilization patterns, and treatment outcomes using administrative claims data and survey datasets
deep expertisesocial element
26%DD
31%
Design and execute cost-effectiveness analyses or budget impact models to evaluate new drugs, devices, or care delivery interventions
deep expertisesocial element
12%DD
28%
Respond to ad-hoc analytical requests from internal clients or external partners, including rapid feasibility assessments and custom data pulls
some context neededsocial core
12%AD
19%
Prepare written reports, policy briefs, and presentations translating statistical findings into actionable insights for stakeholders (payers, government agencies, hospital systems)
deep expertisesocial core
11%DD
16%
Clean, validate, and prepare large healthcare datasets (reconciling data quality issues, handling missing values, creating analysis-ready cohorts)
10%DD
62%
Collaborate with clinical teams, data scientists, and project leads in meetings to scope research questions, validate assumptions, and troubleshoot analytical challenges
some context neededsocial core
1%AA
4%
TaskTimeTypeExposure
Conduct literature reviews and synthesize evidence from published studies to support policy analysis, health technology assessment, or grant proposals
deep expertisesocial core
23%DD
15%
Prepare written reports, policy briefs, and presentations translating statistical findings into actionable insights for stakeholders (payers, government agencies, hospital systems)
some context neededsocial core
19%DD
28%
Design and execute cost-effectiveness analyses or budget impact models to evaluate new drugs, devices, or care delivery interventions
18%DD
57%
Build and maintain econometric models to analyze healthcare cost trends, utilization patterns, and treatment outcomes using administrative claims data and survey datasets
18%DD
49%
Clean, validate, and prepare large healthcare datasets (reconciling data quality issues, handling missing values, creating analysis-ready cohorts)
14%DD
60%
Respond to ad-hoc analytical requests from internal clients or external partners, including rapid feasibility assessments and custom data pulls
some context neededsocial core
5%AD
20%
Collaborate with clinical teams, data scientists, and project leads in meetings to scope research questions, validate assumptions, and troubleshoot analytical challenges
deep expertisesocial core
1%AA
3%
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AI tools for this role
Tools relevant to the most automatable tasks in this profession.
