Deciding without Data
Open accessAbstract
INTRODUCTION: Physician decisions drive most of the increases in health care expenditures, yet virtually no published literature has sought to understand the types of evidence used by physicians as they make decisions in real time. METHODS: Ten pediatric cardiologists recorded every clinically significant decision made during procedures, test interpretation, or delivery of inpatient and outpatient care during 5 full days and 5 half days of care delivery. The basis for each decision was assigned to one of 10 predetermined categories, ranging from arbitrary and anecdotal, to various qualities of published studies, to parental preference and avoiding a lawsuit. RESULTS: During the 7.5 days, 1188 decisions (158/day) were made. Almost 80% of decisions were deemed by the physicians to have no basis in any prior published data and fewer than 3% of decisions were based on a study specific to the question at hand. CONCLUSIONS: In this pilot study, physicians were unable to cite a formal evidence source for most of their real-time clinical decision making, including those that consumed medical resources. Novel approaches to building an evidence base produced from real-time clinical decisions may be essential for health care reform based on data.
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In some specialties less than 20% of daily medical decisions are supported by quality evidence.
“However, in some specialties less than 20% of daily medical decisions are supported by quality evidence.2,3”
From Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems (2025) · cites this paper as [2]
Nearly 80% of care decisions lack high-quality evidence due to no specific study being available.
“Challenges in obtaining evidence stem from two sources: (1) nearly 80% of care decisions lack high-quality evidence due to no specific study being available 2 and (2) difficulty in contextualizing available studies for the specific intricacies of the patient at hand.”
From Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems (2025) · cites this paper as [2]
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- Authors
- Darst, J. R., Newburger, J. W., Resch, S., Rathod, R. H., & Lock, J. E.
- Affiliations
- Boston Children's Hospital (US)
- Harvard University (US)
- Corresponding author
- Darst, Jeffrey R.
- Venue
- Congenital Heart Disease
- Published
- 2010-07-23
- Volume
- 5
- Issue
- 4
- Pages
- 339-342
- ISSN
- 1747-079X (ISSN-L)
- 1747-0803
- PMC
- PMC4283550
- OpenAlex
- W2129833620
- Cited by
- 57
- References
- 13
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 3 · 2020: 4 · 2018: 1 · 2016: 1 · 2015: 8 · 2014: 10 · 2013: 10 · 2012: 3
- FWCI
- 10.25
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Congenital Heart Disease (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Heart, Lung, and Blood Institute (T32HL007572)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Sciences Research and Education
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Keywords
- clinical decision-making, evidence-based medicine, pediatric cardiology, evidence base, health care expenditure, parental preferences
- MeSH terms
- Boston, Decision Support Techniques, Heart Defects, Congenital, Hospitals, Pediatric, Humans, Outcome and Process Assessment, Health Care, Patient Care Management, Cardiology Service, Hospital, Program Development, Treatment Outcome, Practice Guidelines as Topic, Patient Selection, Critical Pathways, Evidence-Based Medicine
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