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Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration
BACKGROUND: HealthImpact is a novel algorithm using administrative health care data to stratify patients according to risk for incident diabetes. OBJECTIVES: To (a) independently assess the predictive validity of HealthImpact and (b) explore its utility in diabetes screening within a nationally inte...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academy of Managed Care Pharmacy
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398202/ https://www.ncbi.nlm.nih.gov/pubmed/30156452 http://dx.doi.org/10.18553/jmcp.2018.24.9.862 |
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author | Linder, Jonathan R. Waterbury, Nancee V. Alexander, Bruce Lund, Brian C. |
author_facet | Linder, Jonathan R. Waterbury, Nancee V. Alexander, Bruce Lund, Brian C. |
author_sort | Linder, Jonathan R. |
collection | PubMed |
description | BACKGROUND: HealthImpact is a novel algorithm using administrative health care data to stratify patients according to risk for incident diabetes. OBJECTIVES: To (a) independently assess the predictive validity of HealthImpact and (b) explore its utility in diabetes screening within a nationally integrated health care system. METHODS: National 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. RESULTS: The 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. CONCLUSIONS: Our 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. |
format | Online Article Text |
id | pubmed-10398202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Academy of Managed Care Pharmacy |
record_format | MEDLINE/PubMed |
spelling | pubmed-103982022023-08-04 Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration Linder, Jonathan R. Waterbury, Nancee V. Alexander, Bruce Lund, Brian C. J Manag Care Spec Pharm Research BACKGROUND: HealthImpact is a novel algorithm using administrative health care data to stratify patients according to risk for incident diabetes. OBJECTIVES: To (a) independently assess the predictive validity of HealthImpact and (b) explore its utility in diabetes screening within a nationally integrated health care system. METHODS: National 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. RESULTS: The 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. CONCLUSIONS: Our 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. Academy of Managed Care Pharmacy 2018-09 /pmc/articles/PMC10398202/ /pubmed/30156452 http://dx.doi.org/10.18553/jmcp.2018.24.9.862 Text en Copyright © 2018, Academy of Managed Care Pharmacy. All rights reserved. https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Research Linder, Jonathan R. Waterbury, Nancee V. Alexander, Bruce Lund, Brian C. Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration |
title | Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration |
title_full | Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration |
title_fullStr | Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration |
title_full_unstemmed | Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration |
title_short | Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration |
title_sort | evaluation of the healthimpact diabetes risk model in the veterans health administration |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398202/ https://www.ncbi.nlm.nih.gov/pubmed/30156452 http://dx.doi.org/10.18553/jmcp.2018.24.9.862 |
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