Development and Optimization of the Veterans Affairs' National Heart Failure Dashboard for Population Health Management
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved..
BACKGROUND: In 2020, the Veterans Affairs (VA) health care system deployed a heart failure (HF) dashboard for use nationally. The initial version was notably imprecise and unreliable for the identification of HF subtypes. We describe the development and subsequent optimization of the VA national HF dashboard.
MATERIALS AND METHODS: This study describes the stepwise process for improving the accuracy of the VA national HF dashboard, including defining the initial dashboard, improving case definitions, using natural language processing for patient identification, and incorporating an imaging-quality hierarchy model. Optimization further included evaluating whether to require concurrent ICD-codes for inclusion in the dashboard and assessing various imaging modalities for patient characterization.
RESULTS: Through multiple rounds of optimization, the dashboard accuracy (defined as the proportion of true results to the total population) was improved from 54.1% to 89.2% for the identification of HF with reduced ejection fraction (HFrEF) and from 53.9% to 88.0% for the identification of HF with preserved ejection fraction (HFpEF). To align with current guidelines, HF with mildly reduced ejection fraction (HFmrEF) was added to the dashboard output with 88.0% accuracy.
CONCLUSIONS: The inclusion of an imaging-quality hierarchy model and natural-language processing algorithm improved the accuracy of the VA national HF dashboard. The revised dashboard informatics algorithm has higher use rates and improved reliability for the health management of the population.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
|---|---|
| Enthalten in: |
Journal of cardiac failure - 30(2024), 3 vom: 31. März, Seite 452-459 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Brownell, Nicholas [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Heart failure |
|---|
| Anmerkungen: |
Date Completed 18.03.2024 Date Revised 20.03.2024 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1016/j.cardfail.2023.08.024 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM362542783 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM362542783 | ||
| 003 | DE-627 | ||
| 005 | 20240320233502.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.cardfail.2023.08.024 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1337.xml |
| 035 | |a (DE-627)NLM362542783 | ||
| 035 | |a (NLM)37757994 | ||
| 035 | |a (PII)S1071-9164(23)00343-3 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Brownell, Nicholas |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Development and Optimization of the Veterans Affairs' National Heart Failure Dashboard for Population Health Management |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 18.03.2024 | ||
| 500 | |a Date Revised 20.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a BACKGROUND: In 2020, the Veterans Affairs (VA) health care system deployed a heart failure (HF) dashboard for use nationally. The initial version was notably imprecise and unreliable for the identification of HF subtypes. We describe the development and subsequent optimization of the VA national HF dashboard | ||
| 520 | |a MATERIALS AND METHODS: This study describes the stepwise process for improving the accuracy of the VA national HF dashboard, including defining the initial dashboard, improving case definitions, using natural language processing for patient identification, and incorporating an imaging-quality hierarchy model. Optimization further included evaluating whether to require concurrent ICD-codes for inclusion in the dashboard and assessing various imaging modalities for patient characterization | ||
| 520 | |a RESULTS: Through multiple rounds of optimization, the dashboard accuracy (defined as the proportion of true results to the total population) was improved from 54.1% to 89.2% for the identification of HF with reduced ejection fraction (HFrEF) and from 53.9% to 88.0% for the identification of HF with preserved ejection fraction (HFpEF). To align with current guidelines, HF with mildly reduced ejection fraction (HFmrEF) was added to the dashboard output with 88.0% accuracy | ||
| 520 | |a CONCLUSIONS: The inclusion of an imaging-quality hierarchy model and natural-language processing algorithm improved the accuracy of the VA national HF dashboard. The revised dashboard informatics algorithm has higher use rates and improved reliability for the health management of the population | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Learning health system | |
| 650 | 4 | |a heart failure | |
| 650 | 4 | |a left ventricular ejection fraction | |
| 650 | 4 | |a medical informatics | |
| 650 | 4 | |a natural language processing | |
| 650 | 4 | |a population health | |
| 700 | 1 | |a Kay, Chad |e verfasserin |4 aut | |
| 700 | 1 | |a Parra, David |e verfasserin |4 aut | |
| 700 | 1 | |a Anderson, Shawn |e verfasserin |4 aut | |
| 700 | 1 | |a Ballister, Briana |e verfasserin |4 aut | |
| 700 | 1 | |a Cave, Brandon |e verfasserin |4 aut | |
| 700 | 1 | |a Conn, Jessica |e verfasserin |4 aut | |
| 700 | 1 | |a Dev, Sandesh |e verfasserin |4 aut | |
| 700 | 1 | |a Kaiser, Stephanie |e verfasserin |4 aut | |
| 700 | 1 | |a ROGERs, Jennifer |e verfasserin |4 aut | |
| 700 | 1 | |a Touloupas, Anna Drew |e verfasserin |4 aut | |
| 700 | 1 | |a Verbosky, Natalie |e verfasserin |4 aut | |
| 700 | 1 | |a Yassa, Nardine-Mary |e verfasserin |4 aut | |
| 700 | 1 | |a Young, Emily |e verfasserin |4 aut | |
| 700 | 1 | |a Ziaeian, Boback |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of cardiac failure |d 1995 |g 30(2024), 3 vom: 31. März, Seite 452-459 |w (DE-627)NLM087692775 |x 1532-8414 |7 nnns |
| 773 | 1 | 8 | |g volume:30 |g year:2024 |g number:3 |g day:31 |g month:03 |g pages:452-459 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.cardfail.2023.08.024 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 30 |j 2024 |e 3 |b 31 |c 03 |h 452-459 | ||