Evidence map›Paper›PMID 30156452›Full record

ArticleJournal of managed care & specialty pharmacy2018

Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration.

Jonathan R Linder, Nancee V Waterbury, Bruce Alexander, Brian C Lund

Open access · bronzeAbstract readEvaluation Study
In one paragraph

Article in Journal of managed care & specialty pharmacy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 84% of its field
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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
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

4 authors at 1 institution in 1 country.

Jonathan R Linder1 Department of Pharmacy Services, VA Health Care System, Iowa City, Iowa.
Nancee V Waterbury1 Department of Pharmacy Services, VA Health Care System, Iowa City, Iowa.
Bruce Alexander2 Center for Comprehensive Access & Delivery Research & Evaluation, Iowa City VA Health Care System, Iowa City, Iowa.
Brian C Lund2 Center for Comprehensive Access & Delivery Research & Evaluation, Iowa City VA Health Care System, Iowa City, Iowa.
Iowa City VA Health Care System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthImpact is a novel algorithm using administrative health care data to stratify patients according to risk for incident diabetes.

objectivesTo (a) independently assess the predictive validity of HealthImpact and (b) explore its utility in diabetes screening within a nationally integrated health care system.

methodsNational Veterans Health Administration data were used to create 2 cohorts. The replication cohort included patients without diagnosed diabetes as of October 1, 2012, to determine if HealthImpact scores were significantly associated with diabetes (type 1 or 2) incidence within the subsequent 3 years. The utility cohort included patients without diagnosed diabetes as of August 1, 2015, and assessed diabetes screening rates in the 2 years surrounding this index date, stratified by HealthImpact scores.

resultsThe 3-year incidence of diabetes in the replication cohort (n = 3,287,240) was 9.1%. Of 100,617 (3.1%) patients with HealthImpact scores > 90, 30,028 developed diabetes, yielding a positive predictive value of 29.8%. These patients accounted for 9.9% of all incident diabetes cases (sensitivity). Sensitivity and negative predictive value improved with descending HealthImpact threshold scores (e.g., > 75, > 50), whereas specificity and positive predictive value declined. Of 3,499,406 patients in the utility cohort, 85.3% received either a blood glucose or hemoglobin A1c test during the 2-year observation period. Among 101,355 patients with a HealthImpact score > 90, nearly all (98.3%) were screened, and 86.3% had an A1c test.

conclusionsOur independent analysis corroborates the validity of HealthImpact in stratifying patients according to diabetes risk. However, its practical utility to enhance diabetes screening in a real-world clinical environment will be strongly dependent on the pattern and frequency of existing screening practices. DISCLOSURES: This work was supported by the Iowa City VA Health Care System and by the Department of Veterans Affairs, Office of Research and Development, Health Services Research and Development Service (Lund, CIN 13-412). The authors have no conflicts of interest. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the U.S. government.

Indexed as

AdolescentAdultAgedCohort StudiesDatabases, FactualDiabetes Mellitus, Type 2FemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsUnited StatesUnited States Department of Veterans AffairsVeterans HealthYoung Adult

Identifiers

PMID30156452
PMCPMC10398202
OpenAlexW2889362566

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.