David Chan

All Publications

• Improving Efficiency in Medical Diagnosis. JAMA Agha, L., Skinner, J., Chan, D. 2022

  View details for DOI 10.1001/jama.2022.8587

  View details for PubMedID 35604676

• Selection with Variation in Diagnostic Skill: Evidence from Radiologists. The quarterly journal of economics Chan, D. C., Gentzkow, M., Yu, C. 2022; 137 (2): 729-783

  Abstract

  Physicians, judges, teachers, and agents in many other settings differ systematically in the decisions they make when faced with similar cases. Standard approaches to interpreting and exploiting such differences assume they arise solely from variation in preferences. We develop an alternative framework that allows variation in preferences and diagnostic skill and show that both dimensions may be partially identified in standard settings under quasi-random assignment. We apply this framework to study pneumonia diagnoses by radiologists. Diagnosis rates vary widely among radiologists, and descriptive evidence suggests that a large component of this variation is due to differences in diagnostic skill. Our estimated model suggests that radiologists view failing to diagnose a patient with pneumonia as more costly than incorrectly diagnosing one without, and that this leads less skilled radiologists to optimally choose lower diagnostic thresholds. Variation in skill can explain 39% of the variation in diagnostic decisions, and policies that improve skill perform better than uniform decision guidelines. Failing to account for skill variation can lead to highly misleading results in research designs that use agent assignments as instruments.

  View details for DOI 10.1093/qje/qjab048

  View details for PubMedID 35422677

  View details for PubMedCentralID PMC8992547

• Mortality among US veterans after emergency visits to Veterans Affairs and other hospitals: retrospective cohort study. BMJ (Clinical research ed.) Chan, D. C., Danesh, K., Costantini, S., Card, D., Taylor, L., Studdert, D. M. 2022; 376: e068099

  Abstract

  OBJECTIVE: To measure and compare mortality outcomes between dually eligible veterans transported by ambulance to a Veterans Affairs hospital and those transported to a non-Veterans Affairs hospital.DESIGN: Retrospective cohort study using data from medical charts and administrative files.SETTING: Emergency visits by ambulance to 140 Veteran Affairs and 2622 non-Veteran Affairs hospitals across 46 US states and the District of Columbia in 2001-18.PARTICIPANTS: National cohort of 583248 veterans (aged ≥65 years) enrolled in both the Veterans Health Administration and Medicare programs, who resided within 20 miles of at least one Veterans Affairs hospital and at least one non-Veterans Affairs hospital, in areas where ambulances regularly transported patients to both types of hospitals.INTERVENTION: Emergency treatment at a Veterans Affairs hospital.MAIN OUTCOME MEASURE: Deaths in the 30 day period after the ambulance ride. Linear probability models of mortality were used, with adjustment for patients' demographic characteristics, residential zip codes, comorbid conditions, and other variables.RESULTS: Of 1470157 ambulance rides, 231611 (15.8%) went to Veterans Affairs hospitals and 1238546 (84.2%) went to non-Veterans Affairs hospitals. The adjusted mortality rate at 30 days was 20.1% lower among patients taken to Veterans Affairs hospitals than among patients taken to non-Veterans Affairs hospitals (9.32 deaths per 100 patients (95% confidence interval 9.15 to 9.50) v 11.67 (11.58 to 11.76)). The mortality advantage associated with Veterans Affairs hospitals was particularly large for patients who were black (-25.8%), were Hispanic (-22.7%), and had received care at the same hospital in the previous year.CONCLUSIONS: These findings indicate that within a month of being treated with emergency care at Veterans Affairs hospitals, dually eligible veterans had substantially lower risk of death than those treated at non-Veterans Affairs hospitals. The nature of this mortality advantage warrants further investigation, as does its generalizability to other types of patients and care. Nonetheless, the finding is relevant to assessments of the merit of policies that encourage private healthcare alternatives for veterans.

  View details for DOI 10.1136/bmj-2021-068099

  View details for PubMedID 35173019

• Selection with Variation in Diagnostic Skill: Evidence from Radiologists* QUARTERLY JOURNAL OF ECONOMICS Chan, D. C., Gentzkow, M., Yu, C. 2022

  View details for DOI 10.1093/qje/qjab048

  View details for Web of Science ID 000763802200001

• Economic Incentives for Chest Physicians. Chest Chan, D. C., Gottlieb, J. D. 1800

  View details for DOI 10.1016/j.chest.2021.12.652

  View details for PubMedID 35007551

• Influence and Information in Team Decisions: Evidence from Medical Residency AMERICAN ECONOMIC JOURNAL-ECONOMIC POLICY Chan, D. C. 2021; 13 (1): 106–37

  View details for DOI 10.1257/pol.20180501

  View details for Web of Science ID 000615235700004

• Effects of a Workplace Wellness Program on Employee Health, Health Beliefs, and Medical Use: A Randomized Clinical Trial. JAMA internal medicine Reif, J., Chan, D., Jones, D., Payne, L., Molitor, D. 2020

  Abstract

  Importance: Many employers use workplace wellness programs to improve employee health and reduce medical costs, but randomized evaluations of their efficacy are rare.Objective: To evaluate the effect of a comprehensive workplace wellness program on employee health, health beliefs, and medical use after 12 and 24 months.Design, Setting, and Participants: This randomized clinical trial of 4834 employees of the University of Illinois at Urbana-Champaign was conducted from August 9, 2016, to April 26, 2018. Members of the treatment group (n=3300) received incentives to participate in the workplace wellness program. Members of the control group (n=1534) did not participate in the wellness program. Statistical analysis was performed on April 9, 2020.Interventions: The 2-year workplace wellness program included financial incentives and paid time off for annual on-site biometric screenings, annual health risk assessments, and ongoing wellness activities (eg, physical activity, smoking cessation, and disease management).Main Outcomes and Measures: Measures taken at 12 and 24 months included clinician-collected biometrics (16 outcomes), administrative claims related to medical diagnoses (diabetes, hypertension, and hyperlipidemia) and medical use (office visits, inpatient visits, and emergency department visits), and self-reported health behaviors and health beliefs (14 outcomes).Results: Among the 4834 participants (2770 women; mean [SD] age, 43.9 [11.3] years), no significant effects of the program on biometrics, medical diagnoses, or medical use were seen after 12 or 24 months. A significantly higher proportion of employees in the treatment group than in the control group reported having a primary care physician after 24 months (1106 of 1200 [92.2%] vs 477 of 554 [86.1%]; adjusted P=.002). The intervention significantly improved a set of employee health beliefs on average: participant beliefs about their chance of having a body mass index greater than 30, high cholesterol, high blood pressure, and impaired glucose level jointly decreased by 0.07 SDs (95% CI, -0.12 to -0.01 SDs; P=.02); however, effects on individual belief measures were not significant.Conclusions and Relevance: This randomized clinical trial showed that a comprehensive workplace wellness program had no significant effects on measured physical health outcomes, rates of medical diagnoses, or the use of health care services after 24 months, but it increased the proportion of employees reporting that they have a primary care physician and improved employee beliefs about their own health.Trial Registration: American Economic Association Randomized Controlled Trial Registry number: AEARCTR-0001368.

  View details for DOI 10.1001/jamainternmed.2020.1321

  View details for PubMedID 32453346

• Provider Discretion and Variation in Resource Allocation: The Case of Triage Decisions Chan, D. C., Gruber, J. AMER ECONOMIC ASSOC. 2020: 279–83

  View details for DOI 10.1257/pandp.20201032

  View details for Web of Science ID 000534590600053

• INDUSTRY INPUT IN POLICY MAKING: EVIDENCE FROM MEDICARE QUARTERLY JOURNAL OF ECONOMICS Chan, D. C., Dickstein, M. J. 2019; 134 (3): 1299–1342

  View details for DOI 10.1093/qje/qjz005

  View details for Web of Science ID 000489162800004

• Valuations of Surgical Procedures in the Medicare Fee Schedule Reply NEW ENGLAND JOURNAL OF MEDICINE Chan, D. C., Huynh, J., Studdert, D. M. 2019; 381 (4): 391

  View details for Web of Science ID 000477993600026

• Accuracy of Valuations of Surgical Procedures in the Medicare Fee Schedule NEW ENGLAND JOURNAL OF MEDICINE Chan, D. C., Huynh, J., Studdert, D. M. 2019; 380 (16): 1546–54

  View details for DOI 10.1056/NEJMsa1807379

  View details for Web of Science ID 000465144100015

• Accuracy of Valuations of Surgical Procedures in the Medicare Fee Schedule. The New England journal of medicine Chan, D. C., Huynh, J., Studdert, D. M. 2019; 380 (16): 1546–54

  Abstract

  BACKGROUND: The Relative Value Scale Update Committee (RUC) of the American Medical Association plays a central role in determining physician reimbursement. The RUC's role and performance have been criticized but subjected to little empirical evaluation.METHODS: We analyzed the accuracy of valuations of 293 common surgical procedures from 2005 through 2015. We compared the RUC's estimates of procedure time with "benchmark" times for the same procedures derived from the clinical registry maintained by the American College of Surgeons National Surgical Quality Improvement Program (NSQIP). We characterized inaccuracies, quantified their effect on physician revenue, and examined whether re-review corrected them.RESULTS: At the time of 108 RUC reviews, the mean absolute discrepancy between RUC time estimates and benchmark times was 18.5 minutes, or 19.8% of the RUC time. However, RUC time estimates were neither systematically shorter nor longer than benchmark times overall (beta, 0.97; 95% confidence interval, 0.94 to 1.01; P=0.10). Our analyses suggest that whereas orthopedic surgeons and urologists received higher payments than they would have if benchmark times had been used ($160 million and $40 million more, respectively, in Medicare reimbursement in 2011 through 2015), cardiothoracic surgeons, neurosurgeons, and vascular surgeons received lower payments ($130 million, $60 million, and $30 million less, respectively). The accuracy of RUC time estimates improved in 47% of RUC revaluations, worsened in 27%, and was unchanged in 25%. (Percentages do not sum to 100 because of rounding.).CONCLUSIONS: In this analysis of frequently conducted operations, we found substantial absolute discrepancies between intraoperative times as estimated by the RUC and the times recorded for the same procedures in a surgical registry, but the RUC did not systematically overestimate or underestimate times. (Funded by the National Institutes of Health.).

  View details for PubMedID 30995374

• Valuations of Surgical Procedures in the Medicare Fee Schedule. Reply. The New England journal of medicine Chan, D. C., Huynh, J. n., Studdert, D. M. 2019; 381 (4): 391

  View details for DOI 10.1056/NEJMc1906724

  View details for PubMedID 31340110

• The Efficiency of Slacking off: Evidence From the Emergency Department ECONOMETRICA Chan, D. C. 2018; 86 (3): 997–1030

  View details for DOI 10.3982/ECTA13565

  View details for Web of Science ID 000434093400006

• The Efficiency of Slacking Off: Evidence from the Emergency Department Econometrica Chan, D. C. 2018; Forthcoming
• Teamwork and Moral Hazard: Evidence from the Emergency Department JOURNAL OF POLITICAL ECONOMY Chan, D. C. 2016; 124 (3): 734-770

  View details for DOI 10.1086/685910

  View details for Web of Science ID 000376987700004

• The Impact of Massachusetts Health Care Reform on Access, Quality, and Costs of Care for the Already-Insured. Health services research Joynt, K. E., Chan, D. C., Zheng, J., Orav, E. J., Jha, A. K. 2014

  Abstract

  To assess the impact of Massachusetts Health Reform (MHR) on access, quality, and costs of outpatient care for the already-insured.Medicare data from before (2006) and after (2009) MHR implementation.We performed a retrospective difference-in-differences analysis of quantity of outpatient visits, proportion of outpatient quality metrics met, and costs of care for Medicare patients with ≥1 chronic disease in 2006 versus 2009. We used the remaining states in New England as controls.We used existing Medicare claims data provided by the Centers for Medicare and Medicaid Services.MHR was not associated with a decrease in outpatient visits per year compared to controls (9.4 prereform to 9.6 postreform in MA vs. 9.4-9.5 in controls, p = .32). Quality of care in MA improved more than controls for hemoglobin A1c monitoring, mammography, and influenza vaccination, and similarly to controls for diabetic eye examination, colon cancer screening, and pneumococcal vaccination. Average costs for patients in Massachusetts increased from $9,389 to $10,668, versus $8,375 to $9,114 in control states (p < .001).MHR was not associated with worsening in access or quality of outpatient care for the already-insured, and it had modest effects on costs. This has implications for other states expanding insurance coverage under the Affordable Care Act.

  View details for DOI 10.1111/1475-6773.12228

  View details for PubMedID 25219772

• Insurance Expansion In Massachusetts Did Not Reduce Access Among Previously Insured Medicare Patients HEALTH AFFAIRS Joynt, K. E., Chan, D., Orav, E. J., Jha, A. K. 2013; 32 (3): 571-578

  Abstract

  Critics of Massachusetts's health reform, a model for the Affordable Care Act, have argued that insurance expansion probably had a negative spillover effect leading to worse outcomes among already insured patients, such as vulnerable Medicare patients. Using Medicare data from 2004 to 2009, we examined trends in preventable hospitalizations for conditions such as uncontrolled hypertension and diabetes--markers of access to effective primary care--in Massachusetts compared to control states. We found that after Massachusetts's health reform, preventable hospitalization rates for Medicare patients actually decreased more in Massachusetts than in control states (a reduction of 101 admissions per 100,000 patients per quarter compared to a reduction of 83 admissions). Therefore, we found no evidence that Massachusetts's insurance expansion had a deleterious spillover effect on preventable hospitalizations among the previously insured. Our findings should offer some reassurance that it is possible to expand access to uninsured Americans without negatively affecting important clinical outcomes for those who are already insured.

  View details for DOI 10.1377/hlthaff.2012.1018

  View details for Web of Science ID 000316557900017

  View details for PubMedID 23459737

• Patient, Physician, and Payment Predictors of Statin Adherence MEDICAL CARE Chan, D. C., Shrank, W. H., Cutler, D., Jan, S., Fischer, M. A., Liu, J., Avorn, J., Solomon, D., Brookhart, A., Choudhry, N. K. 2010; 48 (3): 196-202

  Abstract

  Although many patient, physician, and payment predictors of adherence have been described, knowledge of their relative strength and overall ability to explain adherence is limited.To measure the contributions of patient, physician, and payment predictors in explaining adherence to statins.Retrospective cohort study using administrative data.A total of 14,257 patients insured by Horizon Blue Cross Blue Shield of New Jersey who were newly prescribed a statin cholesterol-lowering medication.Adherence to statin medication was measured during the year after the initial prescription, based on proportion of days covered. The impact of patient, physician, and payment predictors of adherence were evaluated using multivariate logistic regression. The explanatory power of these models was evaluated with C statistics, a measure of the goodness of fit.Overall, 36.4% of patients were fully adherent. Older patient age, male gender, lower neighborhood percent black composition, higher median income, and fewer number of emergency department visits were significant patient predictors of adherence. Having a statin prescribed by a cardiologist, a patient's primary care physician, or a US medical graduate were significant physician predictors of adherence. Lower copayments also predicted adherence. All of our models had low explanatory power. Multivariate models including patient covariates only had greater explanatory power (C = 0.613) than models with physician variables only (C = 0.566) or copayments only (C = 0.543). A fully specified model had only slightly more explanatory power (C = 0.633) than the model with patient characteristics alone.Despite relatively comprehensive claims data on patients, physicians, and out-of-pocket costs, our overall ability to explain adherence remains poor. Administrative data likely do not capture many complex mechanisms underlying adherence.

  View details for DOI 10.1097/MLR.0b013e3181c132ad

  View details for Web of Science ID 000275198200002

  View details for PubMedID 19890219

• How Sensitive are Low Income Families to Health Plan Prices? American Economic Review Papers and Proceedings Chan, D., Gruber, J. 2010: 292-296

  View details for DOI 10.1257/aer.100.2.292

• Improving Safety And Eliminating Redundant Tests: Cutting Costs In U. S. Hospitals HEALTH AFFAIRS Jha, A. K., Chan, D. C., Ridgway, A. B., Franz, C., Bates, D. W. 2009; 28 (5): 1475-1484

  Abstract

  High costs and unsafe care are major challenges for U.S. hospitals. Two sources of raised costs and unsafe care are adverse events in hospitals and tests ordered by several different physicians. After reviewing rates of these two occurrences in U.S. hospitals and simulating their costs, we estimated that in 2004 alone, eliminating readily preventable adverse events would have resulted in direct savings of more than $16.6 billion (5.5 percent of total inpatient costs). Eliminating redundant tests would have saved an additional $8 billion (2.7 percent). Addressing these situations could generate major savings to the system while improving patient care.

  View details for DOI 10.1377/hlthaff.28.5.1475

  View details for Web of Science ID 000269646100031

  View details for PubMedID 19738266

• Quantitative Risk Stratification in Markov Chains with Limiting Conditional Distributions 29th Annual Meeting of the Society-for-Medical-Decision-Making Chan, D. C., Pollett, P. K., Weinstein, M. C. SAGE PUBLICATIONS INC. 2009: 532–40

  Abstract

  Many clinical decisions require patient risk stratification. The authors introduce the concept of limiting conditional distributions, which describe the equilibrium proportion of surviving patients occupying each disease state in a Markov chain with death. Such distributions can quantitatively describe risk stratification.The authors first establish conditions for the existence of a positive limiting conditional distribution in a general Markov chain and describe a framework for risk stratification using the limiting conditional distribution. They then apply their framework to a clinical example of a treatment indicated for high-risk patients, first to infer the risk of patients selected for treatment in clinical trials and then to predict the outcomes of expanding treatment to other populations of risk.For the general chain, a positive limiting conditional distribution exists only if patients in the earliest state have the lowest combined risk of progression or death. The authors show that in their general framework, outcomes and population risk are interchangeable. For the clinical example, they estimate that previous clinical trials have selected the upper quintile of patient risk for this treatment, but they also show that expanded treatment would weakly dominate this degree of targeted treatment, and universal treatment may be cost-effective.Limiting conditional distributions exist in most Markov models of progressive diseases and are well suited to represent risk stratification quantitatively. This framework can characterize patient risk in clinical trials and predict outcomes for other populations of risk.

  View details for DOI 10.1177/0272989X08330121

  View details for Web of Science ID 000268291200015

  View details for PubMedID 19336745

• Heart failure disease management programs: A cost-effectiveness analysis AMERICAN HEART JOURNAL Chan, D. C., Heidenreich, P. A., Weinstein, M. C., Fonarow, G. C. 2008; 155 (2): 332-338

  Abstract

  Heart failure (HF) disease management programs have shown impressive reductions in hospitalizations and mortality, but in studies limited to short time frames and high-risk patient populations. Current guidelines thus only recommend disease management targeted to high-risk patients with HF.This study applied a new technique to infer the degree to which clinical trials have targeted patients by risk based on observed rates of hospitalization and death. A Markov model was used to assess the incremental life expectancy and cost of providing disease management for high-risk to low-risk patients. Sensitivity analyses of various long-term scenarios and of reduced effectiveness in low-risk patients were also considered.The incremental cost-effectiveness ratio of extending coverage to all patients was $9700 per life-year gained in the base case. In aggregate, universal coverage almost quadrupled life-years saved as compared to coverage of only the highest quintile of risk. A worst case analysis with simultaneous conservative assumptions yielded an incremental cost-effectiveness ratio of $110,000 per life-year gained. In a probabilistic sensitivity analysis, 99.74% of possible incremental cost-effectiveness ratios were <$50,000 per life-year gained.Heart failure disease management programs are likely cost-effective in the long-term along the whole spectrum of patient risk. Health gains could be extended by enrolling a broader group of patients with HF in disease management.

  View details for DOI 10.1016/j.ahj.2007.10.001

  View details for Web of Science ID 000252812800024

  View details for PubMedID 18215605