Trial reportMedical care2016
How Patient Comments Affect Consumers' Use of Physician Performance Measures.
Trial report in Medical care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- How is patient trust transferred from online medical platforms to offline?Frontiers in public health · 2025Article
- Web-Based Public Reporting as a Decision-Making Tool for Consumers of Long-Term Care in the United States and the United Kingdom: Systematic Analysis of Report Cards.JMIR formative research · 2023Article
- Evaluation of a protocol for eliciting narrative accounts of pediatric inpatient experiences of care.Health services research · 2023Article
- Developing the Quality in Nutrition Care Model for Dietitians (QUINCE-MOD) in primary care: A mixed-method survey of healthcare consumers and professionals.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2023Article
- The Impact of Popular Science Articles by Physicians on Their Performance on Online Medical Platforms.Healthcare (Basel, Switzerland) · 2022Article
- Factors Associated with the Patient/Client Use of Report Cards, Physician Rating Websites, Social Media, and Google for Hospital and Physician Selection: A Nationwide Survey.Healthcare (Basel, Switzerland) · 2022Article
- How do consumers respond when presented with novel doctor performance information? A multivariate regression analysis.Health expectations : an international journal of public participation in health care and health policy · 2022Article
- A Rigorous Approach to Large-Scale Elicitation and Analysis of Patient Narratives.Medical care research and review : MCRR · 2020Article
- What Words Convey: The Potential for Patient Narratives to Inform Quality Improvement.The Milbank quarterly · 2019Article
- Do Crowdsourced Hospital Ratings Coincide with Hospital Compare Measures of Clinical and Nonclinical Quality?Health services research · 2018Article
- What Do Patients Think About Their Radiation Oncologists? An Assessment of Online Patient Reviews on Healthgrades.Cureus · 2018Article
- Effects of Anti- Versus Pro-Vaccine Narratives on Responses by Recipients Varying in Numeracy: A Cross-sectional Survey-Based Experiment.Medical decision making : an international journal of the Society for Medical Decision Making · 2017Article
- Hospital Quality Reporting in the United States: Does Report Card Design and Incorporation of Patient Narrative Comments Affect Hospital Choice?Health services research · 2017Article
- Consumer Decision-Making Based on Review Websites: Are There Differences Between Choosing a Hotel and Choosing a Physician?Journal of medical Internet research · 2016Article
- Breaking Narrative Ground: Innovative Methods for Rigorously Eliciting and Assessing Patient Narratives.Health services research · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundPatients' comments about doctors are increasingly available on the internet. The effects of these anecdotal accounts on consumers' engagement with reports on doctor quality, use of more statistically reliable performance measures, and ability to choose doctors wisely are unknown.
objectiveTo examine the effects of providing patient comments along with standardized performance information in a web-based public report.
designParticipants were randomly assigned to view 1 of 6 versions of a website presenting comparative performance information on fictitious primary care doctors. Versions varied by the combination of information types [Consumer Assessment of Healthcare Providers and Systems (CAHPS), Healthcare Effectiveness Data and Information Set (HEDIS), and patient comments] and number of doctors.
participantsA random sample of working-age adults (N=848) from an online panel representing the noninstitutionalized population of the United States. MAIN MEASURES: Time spent and actions taken on the website, probing of standardized measures, and decision quality (chosen doctor rated highest on quantifiable metrics, chosen doctor not dominated by another choice). Secondary outcomes were perceived usefulness and trustworthiness of performance metrics and evaluations of the website. KEY
resultsInclusion of patient comments increased time spent on the website by 35%-42% and actions taken (clicks) by 106%-117% compared with versions presenting only CAHPS and HEDIS measures (P<0.01). It also reduced participants' attention to standardized measures (eg, percentage of time probing HEDIS measures dropped by 67%, P<0.01). When patient comments were present, fewer participants chose the doctor scoring highest on standardized metrics (44%-49% vs. 61%-62%, P<0.01).
conclusionsIncluding patient comments in physician performance reports enhances consumers' engagement but reduces their attention to standardized measures and substantially increases suboptimal choices. More research is needed to explore whether integrated reporting strategies could leverage the positive effects of patient comments on consumer engagement without undermining consumers' use of other important metrics for informing choice among doctors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.