Evidence map›Paper›PMID 22195174›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2011

Semantic interoperability of Health Risk Assessments.

Jay Rajda, Daniel J Vreeman, Henry G Wei

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Jay RajdaActiveHealth Management, New York, NY, USA.
Daniel J Vreeman
Henry G Wei

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The health insurance and benefits industry has administered Health Risk Assessments (HRAs) at an increasing rate. These are used to collect data on modifiable health risk factors for wellness and disease management programs. However, there is significant variability in the semantics of these assessments, making it difficult to compare data sets from the output of 2 different HRAs. There is also an increasing need to exchange this data with Health Information Exchanges and Electronic Medical Records. To standardize the data and concepts from these tools, we outline a process to determine presence of certain common elements of modifiable health risk extracted from these surveys. This information is coded using concept identifiers, which allows cross-survey comparison and analysis. We propose that using LOINC codes or other universal coding schema may allow semantic interoperability of a variety of HRA tools across the industry, research, and clinical settings.

Indexed as

Health Status IndicatorsSystems IntegrationDatabases as TopicDecision Support Systems, ClinicalHumansLogical Observation Identifiers Names and CodesRisk AssessmentRisk FactorsSemanticsSurveys and Questionnaires

Identifiers

PMID22195174
PMCPMC3243143

What OpenQuestion holds

Textmetadata
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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.