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Validation of an algorithm to identify heart failure hospitalisations in patients with diabetes within the veterans
Caroline A Presley1,2, Jea Young Min1,3, Jonathan Chipman4
1Veterans Health Administration-Tennessee Valley Healthcare System, Geriatric Research Education Clinical Center (GRECC), HSR&D Center, Nashville, Tennessee, USA.
Insights
An algorithm using International Classification of Diseases Ninth Revision (ICD-9) and diagnosis-related group (DRG) codes accurately identifies hospitalizations for decompensated heart failure (HF) in diabetic Veterans Health Administration (VHA) patients.
Area of Science:
- Health Informatics
- Cardiology
- Public Health
Background:
- Identifying hospitalizations for decompensated heart failure (HF) is crucial for patient care, especially in populations with comorbidities like diabetes.
- The Veterans Health Administration (VHA) system presents unique challenges and opportunities for healthcare data analysis.
Purpose of the Study:
- To validate an algorithm for identifying hospitalizations due to decompensated heart failure (HF).
- The algorithm utilizes primary discharge diagnosis (International Classification of Diseases Ninth Revision (ICD-9)) and diagnosis-related group (DRG) codes.
- The study focuses on patients with diabetes within the VHA system.
Main Methods:
- A validation study was conducted using a random sample of hospitalizations from 2001-2012 within a VHA healthcare system.
- Chart abstraction using Framingham criteria served as the referent standard.
- Positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity were calculated for the algorithm and its components.
Main Results:
- The overall algorithm demonstrated a high positive predictive value (PPV) of 89.7% and negative predictive value (NPV) of 93.9%.
- Specificity was very high at 99.4%, while sensitivity was 45.1%.
- The PPV was highest when both ICD-9 and DRG criteria were met (92.1%).
Conclusions:
- The developed algorithm, incorporating ICD-9 and DRG codes, shows excellent PPV for identifying decompensated HF hospitalizations in diabetic VHA patients.
- This validated algorithm can improve the accuracy of identifying HF hospitalizations within large healthcare systems.
- The findings support the use of administrative data for epidemiological research in cardiovascular disease.
Objectives:
We aimed to validate an algorithm using both primary discharge diagnosis (International Classification of Diseases Ninth Revision (ICD-9)) and diagnosis-related group (DRG) codes to identify hospitalisations due to decompensated heart failure (HF) in a population of patients with diabetes within the Veterans Health Administration (VHA) system.
Design:
Validation study.
Setting:
Veterans Health Administration-Tennessee Valley Healthcare System PARTICIPANTS: We identified and reviewed a stratified, random sample of hospitalisations between 2001 and 2012 within a single VHA healthcare system of adults who received regular VHA care and were initiated on an antidiabetic medication between 2001 and 2008. We sampled 500 hospitalisations; 400 hospitalisations that fulfilled algorithm criteria, 100 that did not. Of these, 497 had adequate information for inclusion. The mean patient age was 66.1 years (SD 11.4). Majority of patients were male (98.8%); 75% were white and 20% were black.
Primary And Secondary Outcome Measures:
To determine if a hospitalisation was due to HF, we performed chart abstraction using Framingham criteria as the referent standard. We calculated the positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity for the overall algorithm and each component (primary diagnosis code (ICD-9), DRG code or both).
Results:
The algorithm had a PPV of 89.7% (95% CI 86.8 to 92.7), NPV of 93.9% (89.1 to 98.6), sensitivity of 45.1% (25.1 to 65.1) and specificity of 99.4% (99.2 to 99.6). The PPV was highest for hospitalisations that fulfilled both the ICD-9 and DRG algorithm criteria (92.1% (89.1 to 95.1)) and lowest for hospitalisations that fulfilled only DRG algorithm criteria (62.5% (28.4 to 96.6)).
Conclusions:
Our algorithm, which included primary discharge diagnosis and DRG codes, demonstrated excellent PPV for identification of hospitalisations due to decompensated HF among patients with diabetes in the VHA system.
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