Health Care Information Technology Vendors' “Hold Harmless” Clause: Implications for Patients and Clinicians
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Hold harmless clauses in many HIT contracts harm organizational learning, innovation, and safety by discouraging reporting and sharing of experiences and data.
“The ' hold harmless ' clauses 53 found in many HIT contracts are anathema to organizational learning, innovation, and safety because they stifle reporting and sharing of experiences and data”
From Health information technology: fallacies and sober realities (2010) · cites this paper as [53]
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References 10 · Cited by 99
- Authors
- Koppel, R., & Kreda, D.
- Affiliations
- University of Pennsylvania (US)
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2009-03-25
- Volume
- 301
- Issue
- 12
- Pages
- 1276
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W1975504213
- Cited by
- 99
- References
- 10
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 1 · 2023: 5 · 2022: 2 · 2021: 2 · 2020: 3 · 2019: 5 · 2018: 4 · 2017: 6 · 2016: 4 · 2015: 14 · 2013: 12 · 2012: 5
- FWCI
- 30.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Pharmacy › Medical Malpractice and Liability Issues
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Physical Sciences › Computer Science › Information Systems › Thoreau and American Literature
- Keywords
- health information technology, software companies, liability, contract law, electronic health records
- MeSH terms
- Commerce, Ethics, Professional, Forecasting, Health Personnel, Humans, Medical Informatics, United States, Liability, Legal
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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