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Ira Leeds

Assistant Professor of Surgery (Colon and Rectal); Assistant Professor, Biomedical Informatics & Data Science; Clinical Member, Cancer Prevention and Control Program - Yale Cancer Center; Clinical Fellow, Clinical Epidemiology Research Center (CERC)

Contact Information


Mailing Address

  • Yale School of Medicine

    Colorectal Surgery, PO Box 208062

    New Haven, CT 06520-8062

    United States

Research Summary

I investigate how we as a healthcare system can address areas of clinical uncertainty where our internal decision-making based on experience and intuition may be imperfect. The clinical context often varies but my collaborators and I apply mixed methods to identify areas of imperfect clinical decision making (e.g., Big Data analysis of secondary data sets, local natural experiments, behavioral experiments) as well as investigate downstream solutions (e.g., clinical decision support, shared decision-making models, data visualization). These studies often reveal misalignment between clinical decision-making and optimal healthcare utilization, so more recently we also model these decision points using cost-effectiveness techniques to better inform where common clinical practice may ultimately be causing societal harm due to healthcare resource depletion.

Extensive Research Description

The overarching context of my research focuses on preoperative decision making between surgeons and patients with the intent to identify where the inputs and outputs of these decisions do not readily align with patient, surgeon, and societal goals.

The publications below demonstrate a consistent record of surgeons and patients having difficulty at the time of decision-making being able to simultaneously assess the individualized risk factors for worse postoperative outcomes for a given patient and a specific disease. Our hypothesis is that there is too much signal noise in patient's histories and clinical data combined with a distracting clinical atmosphere that impairs effective shared decision-making.

Other publications below describe various interventions employed (data visualization schemes, clinical decision support tools, rapid psychosocial assessment techniques) to either improve the inputs needed for high quality decision-making (i.e., enhanced information assessment and organization) or facilitate the outputs of decision-making (i.e., clinical decision support to align available data with intended outcome).

The importance of effective decision-making has been routinely demonstrated for high-complication diseases such as colorectal cancer and inflammatory bowel disease. The premise of many of our proposed interventions emphasizes addressing decision points in highly morbid diseases in patients who are also high-risk due to comorbidities or low physiologic reserve (i.e., frailty).

Finally, we test our interventions using a variety of cost-effectiveness models such as decision analysis decision trees and Markov model simulations to ascertain whether the interventions and decisions being made meet conventional means test for overall benefit to society and population health.


Research Interests

Anal Gland Neoplasms; Colitis, Ulcerative; Colorectal Surgery; Cost-Benefit Analysis; Costs and Cost Analysis; Decision Making; Decision Making, Computer-Assisted; Decision Trees; Postoperative Complications; Postoperative Period; Preoperative Care; General Surgery; Colorectal Neoplasms; Inflammatory Bowel Diseases; Risk Assessment; Decision Support Systems, Clinical; Surgical Oncology

Public Health Interests

Aging; Cancer; Clinical Guidelines; Clinical Trials; Health Care Financing

Selected Publications