Bio


Nirav R. Shah, MD, MPH, is Senior Scholar at Stanford University’s Clinical Excellence Research Center. He is a leader in patient safety and quality, innovation and digital health, and the strategies required to transition to lower-cost, patient-centered health care. Board-certified in Internal Medicine, Dr. Shah is a graduate of Harvard College and Yale School of Medicine, and is an elected member of the National Academy of Medicine. He serves as an independent director for STERIS plc, as trustee for The John A. Hartford Foundation, as Senior Fellow of the Institute for Healthcare Improvement (IHI), and as a member of the HHS Secretary's Advisory Committee on National Health Promotion and Disease Prevention Objectives for 2030. Previously, he served as senior vice president and Chief Operating Officer for clinical operations for Kaiser Permanente in Southern California, and as Commissioner of the New York State Department of Health.

Academic Appointments


Professional Education


  • AB, Harvard College
  • MD, MPH, Yale University

All Publications


  • Health Care in 2030: Will Artificial Intelligence Replace Physicians? Annals of internal medicine Shah, N. R. 2019

    View details for PubMedID 30802901

  • Segmentation of High-Cost Adults in an Integrated Healthcare System Based on Empirical Clustering of Acute and Chronic Conditions JOURNAL OF GENERAL INTERNAL MEDICINE Davis, A. C., Shen, E., Shah, N. R., Glenn, B. A., Ponce, N., Telesca, D., Gould, M. K., Needleman, J. 2018; 33 (12): 2171–79

    Abstract

    High-cost patients are a frequent focus of improvement projects based on primary care and other settings. Efforts to characterize high-cost, high-need patients are needed to inform care planning, but such efforts often rely on a priori assumptions, masking underlying complexities of a heterogenous population.To define recognizable subgroups of patients among high-cost adults based on clinical conditions, and describe their survival and future spending.Retrospective observational cohort study.Within a large integrated delivery system with 2.7 million adult members, we selected the top 1% of continuously enrolled adults with respect to total healthcare expenditures during 2010.We used latent class analysis to identify clusters of alike patients based on 53 hierarchical condition categories. Prognosis as measured by healthcare spending and survival was assessed through 2014 for the resulting classes of patients.Among 21,183 high-cost adults, seven clinically distinctive subgroups of patients emerged. Classes included end-stage renal disease (12% of high-cost population), cardiopulmonary conditions (17%), diabetes with multiple comorbidities (8%), acute illness superimposed on chronic conditions (11%), conditions requiring highly specialized care (14%), neurologic and catastrophic conditions (5%), and patients with few comorbidities (the largest class, 33%). Over 4 years of follow-up, 6566 (31%) patients died, and survival in the classes ranged from 43 to 88%. Spending regressed to the mean in all classes except the ESRD and diabetes with multiple comorbidities groups.Data-driven characterization of high-cost adults yielded clinically intuitive classes that were associated with survival and reflected markedly different healthcare needs. Relatively few high-cost patients remain persistently high cost over 4 years. Our results suggest that high-cost patients, while not a monolithic group, can be segmented into few subgroups. These subgroups may be the focus of future work to understand appropriateness of care and design interventions accordingly.

    View details for PubMedID 30182326

    View details for PubMedCentralID PMC6258619

  • Putting the Health of Communities and Populations First JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Goldman, L. R., Kumanyika, S. K., Shah, N. R. 2016; 316 (16): 1649-1650

    View details for DOI 10.1001/jama.2016.14800

    View details for Web of Science ID 000386107800017

    View details for PubMedID 27668815

  • Redesigning the Regulatory Framework for Ambulatory Care Services in New York MILBANK QUARTERLY Chokshi, D. A., Rugge, J., Shah, N. R. 2014; 92 (4): 776-795

    Abstract

    Policy Points: The landscape of ambulatory care services in the United States is rapidly changing on account of payment reform, primary care transformation, and the rise of convenient care options such as retail clinics. New York State has undertaken a redesign of regulatory policy for ambulatory care rooted in the Triple Aim (better health, higher-quality care, lower costs)-with a particular emphasis on continuity of care for patients. Key tenets of the regulatory approach include defining and tracking the taxonomy of ambulatory care services as well as ensuring that convenient care options do not erode continuity of care for patients.While hospitals remain important centers of gravity in the health system, services are increasingly being delivered through ambulatory care. This shift to ambulatory care is giving rise to new delivery structures, such as retail clinics and urgent care centers, as well as reinventing existing ambulatory care capacity, as seen with the patient-centered medical home model and the movement toward team-based care. To protect the public's interests, oversight of ambulatory care services must keep pace with these rapid changes. With this purpose, in January 2013 the New York Public Health and Health Planning Council undertook a redesign of the regulatory framework for the state's ambulatory care services. This article describes the principles undergirding the framework as well as the regulatory recommendations themselves.We explored and analyzed the regulation of ambulatory care services in New York in accordance with the available gray and peer-reviewed literature and legislative documents. The deliberations of the Public Health and Health Planning Council informed our review.The vision of high-performing ambulatory care should be rooted in the Triple Aim (better health, higher-quality care, lower costs), with a particular emphasis on continuity of care for patients. There is a pressing need to better define the taxonomy of ambulatory care services. From the state government's perspective, this clarification requires better reporting from new health care entities (eg, retail clinics), connections with regional and state health information technology hubs, and coordination among state agencies. A uniform nomenclature also would improve consumers' understanding of rights and responsibilities. Finally, the regulatory mechanisms employed-from mandatory reporting to licensure to regional planning to the certificate of need-should remain flexible and match the degree of consensus regarding the appropriate regulatory path.Few other states have embarked on a wide-ranging assessment of their regulation of ambulatory care services. By moving toward adopting the regulatory approach described here, New York aims to balance sound oversight with pluralism and innovation in health care delivery.

    View details for DOI 10.1111/1468-0009.12092

    View details for Web of Science ID 000346588500013

    View details for PubMedID 25492604

    View details for PubMedCentralID PMC4266176

  • Liberating Data to Transform Health Care New York's Open Data Experience JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Martin, E. G., Helbig, N., Shah, N. R. 2014; 311 (24): 2481-2482

    View details for Web of Science ID 000337757000018

    View details for PubMedID 25058079

  • Housing as Health Care - New York's Boundary-Crossing Experiment NEW ENGLAND JOURNAL OF MEDICINE Doran, K. M., Misa, E. J., Shah, N. R. 2013; 369 (25): 2374-2377

    View details for DOI 10.1056/NEJMp1310121

    View details for Web of Science ID 000328586000005

    View details for PubMedID 24350949

  • Managing the Human Toll Caused by Seasonal Influenza New York State's Mandate to Vaccinate or Mask JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Caplan, A., Shah, N. R. 2013; 310 (17): 1797-1798

    View details for DOI 10.1001/jama.2013.280633

    View details for Web of Science ID 000326550900008

    View details for PubMedID 24081030

  • Should Health Care Systems Become Insurers? JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Shah, N. R., Chokshi, D. A. 2013; 310 (15): 1561-1562

    View details for DOI 10.1001/jama.2013.280015

    View details for Web of Science ID 000325624800015

    View details for PubMedID 24129460

  • Managing Potential Conflicts of Interest in State Medicaid Pharmacy and Therapeutics Committees Seeking Harmony JAMA INTERNAL MEDICINE Shah, N. 2013; 173 (5): 344-344
  • Methodological Controversies from Comparative Effectiveness (CE) Studies Using Claims vs. Electronic Health Record (EHR) Data Setoguchi, S., Shah, N., Roy, J., Winkelmayer, W., Glynn, R. WILEY-BLACKWELL. 2010: S16–S17
  • Utility of different lipid measures to predict coronary heart disease JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Remick, J., Underberg, J. A., Shah, N. R. 2008; 299 (1): 35-36

    View details for Web of Science ID 000252052000012

    View details for PubMedID 18167402

  • Biomarkers for prediction of cardiovascular events NEW ENGLAND JOURNAL OF MEDICINE Mints, G., Shah, N. R. 2007; 356 (14): 1473-1474

    View details for Web of Science ID 000245419600023

    View details for PubMedID 17415904

  • Bridging the inferential gap: The electronic health record and clinical evidence HEALTH AFFAIRS Stewart, W. F., Shah, N. R., Selna, M. J., Paulus, R. A., Walker, J. M. 2007; 26 (2): W181-W191

    Abstract

    Most clinical decisions involve bridging the inferential gap: Clinicians are required to "fill in" where they lack knowledge or where no knowledge yet exists. In this context we consider how the inferential gap is a product, in part, of how knowledge is created, the limits to gaining access to such knowledge, and the variable ways in which knowledge is translated into decisions. We consider how electronic health records (EHRs) will help narrow this gap by accelerating the creation of evidence relevant to everyday practice needs and facilitating real-time use of knowledge in practice.

    View details for DOI 10.1377/hlthaff.26.2.w181

    View details for Web of Science ID 000244763500057

    View details for PubMedID 17259202

    View details for PubMedCentralID PMC2670472

  • What is the best evidence for making clinical decisions? JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Shah, N. R. 2000; 284 (24): 3127-3127

    View details for Web of Science ID 000165994100025

    View details for PubMedID 11135773

  • Randomized, controlled trials, observational studies, and the hierarchy of research designs. NEW ENGLAND JOURNAL OF MEDICINE Concato, J., Shah, N., Horwitz, R. I. 2000; 342 (25): 1887-1892

    Abstract

    In the hierarchy of research designs, the results of randomized, controlled trials are considered to be evidence of the highest grade, whereas observational studies are viewed as having less validity because they reportedly overestimate treatment effects. We used published meta-analyses to identify randomized clinical trials and observational studies that examined the same clinical topics. We then compared the results of the original reports according to the type of research design.A search of the Medline data base for articles published in five major medical journals from 1991 to 1995 identified meta-analyses of randomized, controlled trials and meta-analyses of either cohort or case-control studies that assessed the same intervention. For each of five topics, summary estimates and 95 percent confidence intervals were calculated on the basis of data from the individual randomized, controlled trials and the individual observational studies.For the five clinical topics and 99 reports evaluated, the average results of the observational studies were remarkably similar to those of the randomized, controlled trials. For example, analysis of 13 randomized, controlled trials of the effectiveness of bacille Calmette-Guérin vaccine in preventing active tuberculosis yielded a relative risk of 0.49 (95 percent confidence interval, 0.34 to 0.70) among vaccinated patients, as compared with an odds ratio of 0.50 (95 percent confidence interval, 0.39 to 0.65) from 10 case-control studies. In addition, the range of the point estimates for the effect of vaccination was wider for the randomized, controlled trials (0.20 to 1.56) than for the observational studies (0.17 to 0.84).The results of well-designed observational studies (with either a cohort or a case-control design) do not systematically overestimate the magnitude of the effects of treatment as compared with those in randomized, controlled trials on the same topic.

    View details for Web of Science ID 000087704700007

    View details for PubMedID 10861325

    View details for PubMedCentralID PMC1557642