Romero N. Santiago

Mentors: Guy David, Ph.D. and Mark Neuman, M.D.

Elements that distort efficient matching of patients to

physicians may impact patient wellbeing. Perverse incentives to take or avoid difficult cases. For the same condition, recommendations may vary

by specialty (supplier induced demand). Inefficient matching is potentially costly to the

healthcare system. Hospital reputation and malpractice pressure may

not provide sufficient incentives to induce efficient matching.

Motivation

Review previous research discussing current

framework of task-talent matching Read through the literature to find various incentives

that could help explain cause of inefficient matching Analyze task-talent matching in a specific region and

specialty to observe degree of matching problem

Strategy Used to Study Task-Talent Matching

Are highly talented physicians performing the most

difficult cases? Theoretical Framework Empirical Work Valuable insights about research experience

Project Overview

“Hierarchies and the Organization of Knowledge in

Production” – Garicano “Knowledge-based hierarchy” – production workers and

specialized problem solvers (industrial sector). Pyramidal structure with multiple levels, communication

costs incurred with specialization Knowledge of problem solvers incorporates knowledge of

those asking them for advice on solving a particular problem In medicine, no fine line between base level

(production worker) and problem solver, levels overlap.

Garicano’s Pyramid Hierarchy is Not a Perfect Fit for Medicine

“Referrals” – Garicano and Santos Agent diagnosing opportunity/task incentivized to keep

most valuable ones and refer least valuable Top-down diagnosis generates no inefficiency, unlike

bottom-up arrangements “Specialization and Matching” – Epstein and colleagues Physicians in group partnerships specialize more than

solo physicians, utilizing referral system Matching of specialists to patient heightened under firm

or group practice.

Specialization Creates Matching Issue Through Incentives

Utilized the Florida Department of Health website Board-certified cardiac surgeons (162) Graduation Year from Medical School Residency and Fellowship Information

Age of patient utilized as proxy for task difficulty Years of experience used as proxy for talent Data represents inpatient cases from 2005 to 2007 Mean age of patient = 66 years Standard Deviation = 10.7 years Mean Experience for Surgeon = 28.8 years Standard Deviation = 7.9 years

Macroscopic View of Florida’s Cardiac Surgeon Population

Using Experience=15 as Cutoff Experience<15 Experience>=15

Age<70 233 (60%) 24215 (57%)

Age>=70 153 (40%) 18130 (43%)

Experience<15 Experience>=15

Age<80 343 (89%) 37359 (88%)

Age>=80 43 (11%) 4986 (12%)

Experience<15 Experience>=15

Age<90 380 (98%) 41804 (99%)

Age>=90 6 (2%) 541 (1%)

Chi-squared values were 0.21, 0.70, and 0.63 respectively

Using Experience = 20 as Cutoff

Experience<20 Experience>=20

Age<70 2815 (56%) 21633 (57%)

Age>=70 2174 (44%) 16109 (43%)

Experience<20 Experience>=20

Age<80 4393 (88%) 33309 (88%)

Age>=80 596 (12%) 4433 (12%)

Experience<20 Experience>=20

Age<90 4923 (99%) 37261 (99%)

Age>=90 66 (1%) 481 (1%)

Chi-squared values were 0.23, 0.68, and 0.77 respectively

Using Experience=25 as cutoff

Experience<25 Experience>=25

Age<70 6962 (58%) 17486 (57%)

Age>=70 5044 (42%) 13239 (43%)

Experience<25 Experience>=25

Age<80 10635 (89%) 27067 (88%)

Age>=80 1371 (11%) 3658 (12%)

Experience<25 Experience>=25

Age<90 11852 (99%) 30332 (99%)

Age>=90 154 (1%) 393 (1%)

Chi-squared values were 0.05, 0.16, and 0.98 respectively

Look for a more accurate way to define task and talent, as

age and experience are very approximate proxies Analyzing various comorbidity indices to account for

preexisting conditions among patients (task) Attempt to verify payment structure’s effect on task and

talent matching in cardiac surgery Compare and contrast incentives and payment structures

of various specialties

Next Steps

Thoroughly understanding the significance of

assumptions is crucial. Health services research requires an interdisciplinary

approach and mindset. Learning about prior research done in one’s topic is

essential for future growth and advancement. Communication and conversation is vital. Combining Economics and Medicine

Interdisciplinary Mindset and Communication are the Keys to Success

Leonard Davis Institute of Health Economics Anesthesiology Department at Penn Medicine Mentors: Guy David, Ph.D. and Mark Neuman, M.D. LDI Staff Joanne Levy, Elisabeth Madden, Hoag Levins, Megan Pellegrino Renee Zawacki

Special Recognition