The case for randomized controlled trials to assess the impact of clinical information systems
Open accessAbstract
There is a persistent view of a significant minority in the medical informatics community that the randomized controlled trial (RCT) has a limited role to play in evaluating clinical information systems. A common reason voiced by skeptics is that these systems are fundamentally different from drug interventions, so the RCT is irrelevant. There is an urgent need to promote the use of RCTs, given the shift to evidence-based policy and the need to demonstrate cost-effectiveness of these systems. The authors suggest returning to first principles and argue that what is required is clarity about how to match methods to evaluation questions. The authors address common concerns about RCTs, and the extent to which they are fallacious, and also discuss the challenges of conducting RCTs in informatics and alternative study designs when randomized trials are infeasible. While neither a perfect nor universal evaluation method, RCTs form an important part of an evaluator's toolkit.
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The study used a methodologically innovative design, captured contemporaneous multifaceted real time longitudinal data, and had theoretical grounding.
“We also used a methodologically innovative design,86 captured contemporaneous multifaceted real time longitudinal data, and had theoretical grounding.19 87”
From Implementation and adoption of nationwide electronic health records in secondary care in England: final qualitative results from prospective national evaluation in early adopter hospitals (2011) · cites this paper as [86]
The Background and 'Question Appropriate study design' sections discuss how to choose methods for evaluating clinical information systems, but do not describe or assess the citing study's design. The 'Theory or case studies can reliably predict what works' section discusses theory-based approaches generally. I found no passage establishing that the citing study used an innovative design, collected the stated longitudinal data, or had theoretical grounding; the copy provides no page numbers for these passages. (LLM, conf=0.74)
Experimental — accuracy not yet measuredRCTs have only infrequently been used in EHR evaluations.
“Despite the exalted status of RCTs as the gold standard for assessing cause and effect or therapeutic impact, they have only infrequently been used in EHR evaluations [19].”
Positivist approaches, including RCTs and before-after studies, are less able to conduct meaningful real-time formative evaluations that address such concerns.
“Positivist approaches, including RCTs and before-after studies, despite health care’s long tradition and continuing calls for their use [11,19], are less able to conduct meaningful real-time formative evaluations that address such concerns.”
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- Authors
- Liu, J. L. Y., & Wyatt, J. C.
- Affiliations
- University of Dundee (GB)
- Corresponding author
- Liu, J. L. Y.
- ORCID
- Wyatt, J. C.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-03-01
- Volume
- 18
- Issue
- 2
- Pages
- 173-180
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC3116250
- OpenAlex
- W2164176905
- Cited by
- 66
- References
- 127
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 1 · 2022: 3 · 2021: 4 · 2020: 3 · 2019: 4 · 2018: 3 · 2017: 5 · 2016: 8 · 2015: 7 · 2014: 2 · 2013: 9 · 2012: 9
- FWCI
- 12.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Discovery Research Portal (University of Dundee) (publishedVersion)
- DigitalGeorgetown (Georgetown University Library) (submittedVersion)
- Funders
- Scottish Funding Council
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- randomized controlled trials, clinical information systems, evidence-based policy, cost-effectiveness, evaluation methodology
- MeSH terms
- Health Services Research, Humans, Information Systems, Research Design, Randomized Controlled Trials as Topic, Evidence-Based Practice
About these checks
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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