Evidence map›Paper›PMID 31593550›Full record

ReviewJMIR public health and surveillance2019

Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review.

Elizabeth Golembiewski, Katie S Allen, Amber M Blackmon, Rachel J Hinrichs, Joshua R Vest

Abstract readReview
In one paragraph

Review in JMIR public health and surveillance, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
–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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

5 authors.

Elizabeth Golembiewski *IUPUI Richard M Fairbanks School of Public Health, Indianapolis, IN, United States.ORCID http://orcid.org/0000-0003-1015-3935
Katie S Allen *IUPUI Richard M Fairbanks School of Public Health, Indianapolis, IN, United States.ORCID http://orcid.org/0000-0002-6058-6280
Amber M Blackmon *IUPUI Richard M Fairbanks School of Public Health, Indianapolis, IN, United States.ORCID http://orcid.org/0000-0002-9889-430X
Rachel J Hinrichs *IUPUI University Library, Indianapolis, IN, United States.ORCID http://orcid.org/0000-0003-0762-744X
Joshua R Vest *IUPUI Richard M Fairbanks School of Public Health, Indianapolis, IN, United States.ORCID http://orcid.org/0000-0002-7226-9688

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNonclinical determinants of health are of increasing importance to health care delivery and health policy. Concurrent with growing interest in better addressing patients' nonmedical issues is the exponential growth in availability of data sources that provide insight into these nonclinical determinants of health.

objectiveThis review aimed to characterize the state of the existing literature on the use of nonclinical health indicators in conjunction with clinical data sources.

methodsWe conducted a rapid review of articles and relevant agency publications published in English. Eligible studies described the effect of, the methods for, or the need for combining nonclinical data with clinical data and were published in the United States between January 2010 and April 2018. Additional reports were obtained by manual searching. Records were screened for inclusion in 2 rounds by 4 trained reviewers with interrater reliability checks. From each article, we abstracted the measures, data sources, and level of measurement (individual or aggregate) for each nonclinical determinant of health reported.

resultsA total of 178 articles were included in the review. The articles collectively reported on 744 different nonclinical determinants of health measures. Measures related to socioeconomic status and material conditions were most prevalent (included in 90% of articles), followed by the closely related domain of social circumstances (included in 25% of articles), reflecting the widespread availability and use of standard demographic measures such as household income, marital status, education, race, and ethnicity in public health surveillance. Measures related to health-related behaviors (eg, smoking, diet, tobacco, and substance abuse), the built environment (eg, transportation, sidewalks, and buildings), natural environment (eg, air quality and pollution), and health services and conditions (eg, provider of care supply, utilization, and disease prevalence) were less common, whereas measures related to public policies were rare. When combining nonclinical and clinical data, a majority of studies associated aggregate, area-level nonclinical measures with individual-level clinical data by matching geographical location.

conclusionsA variety of nonclinical determinants of health measures have been widely but unevenly used in conjunction with clinical data to support population health research.

Indexed as

inequalitiespopulation characteristicssocial conditionssocial determinants of healthsocioeconomic factors

Identifiers

PMID31593550
PMCPMC6803891

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.