Evidence map›Paper›PMID 34665240›Full record

ArticleJAMA network open2021

Association Between Crowdsourced Health Care Facility Ratings and Mortality in US Counties.

Daniel C Stokes, Arthur P Pelullo, Nandita Mitra, Zachary F Meisel, Eugenia C South, David A Asch, Raina M Merchant

Abstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Daniel C StokesDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles.
Arthur P PelulloCenter for Digital Health, Penn Medicine, University of Pennsylvania, Philadelphia.
Nandita MitraDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia.
Zachary F MeiselLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia.
Eugenia C SouthLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia.
David A AschLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia.
Raina M MerchantCenter for Digital Health, Penn Medicine, University of Pennsylvania, Philadelphia.

Funding

Analyzing Online Reviews to Evaluate Quality of Care at Substance Use Disorder Treatment FacilitiesR21DA050761 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI MERCHANT, RAINA · 2020 to 2021
$446k
NIDA NIH HHS R21 DA050761
6 · The paper itself

Abstract

Importance: Mortality across US counties varies considerably, from 252 to 1847 deaths per 100 000 people in 2018. Although patient satisfaction with health care is associated with patient- and facility-level health outcomes, the association between health care satisfaction and community-level health outcomes is not known. Objective: To examine the association between online ratings of health care facilities and mortality across US counties and to identify language specific to 1-star (lowest rating) and 5-star (highest rating) reviews in counties with high vs low mortality. Design, Setting, and Participants: This retrospective population-based cross-sectional study examined reviews and ratings of 95 120 essential health care facilities across 1301 US counties. Counties that had at least 1 essential health care facility with reviews available on Yelp, an online review platform, were included. Essential health care was defined according to the 10 essential health benefits covered by Affordable Care Act insurance plans. Main Outcomes and Measures: The mean rating of essential health care facilities was calculated by county from January 1, 2015, to December 31, 2019. Ratings were on a scale of 1 to 5 stars, with 1 being the worst rating and 5 the best. County-level composite measures of health behaviors, clinical care, social and economic factors, and physical environment were obtained from the University of Wisconsin School of Medicine and Public Health County Health Rankings database. The 2018 age-adjusted mortality by county was obtained from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiological Research database. Multiple linear regression analysis was used to estimate the association between mean facility rating and mortality, adjusting for county health ranking variables. Words with frequencies of use that were significantly different across 1-star and 5-star reviews in counties with high vs low mortality were identified. Results: The 95 120 facilities meeting inclusion criteria were distributed across 1301 of 3142 US counties (41.4%). At the county level, a 1-point increase in mean rating was associated with a mean (SE) age-adjusted decrease of 18.05 (3.68) deaths per 100 000 people (P < .001). Words specific to 1-star reviews in high-mortality counties included told, rude, and wait, and words specific to 5-star reviews in low-mortality counties included Dr, pain, and professional. Conclusions and Relevance: This study found that, at the county level, higher online ratings of essential health care facilities were associated with lower mortality. Equivalent online ratings did not necessarily reflect equivalent experiences of care across counties with different mortality levels, as evidenced by variations in the frequency of use of key words in reviews. These findings suggest that online ratings and reviews may provide insight into unequal experiences of essential health care.

Indexed as

Patient SatisfactionAdultCross-Sectional StudiesCrowdsourcingFemaleHealth FacilitiesHumansMaleMiddle AgedMortalityRetrospective StudiesUnited States

Identifiers

PMID34665240
PMCPMC8527362

What OpenQuestion holds

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Registered trials

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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.