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Do functional status and Medicare claims data improve the predictive accuracy of an electronic health record mortality index? Findings from a national Veterans Affairs cohort.
Deardorff, William James; Jing, Bocheng; Jeon, Sun Y; Boscardin, W John; Lee, Alexandra K; Fung, Kathy Z; Lee, Sei J.
Afiliação
  • Deardorff WJ; Division of Geriatrics, University of California, San Francisco, 490 Illinois Street, Floor 08, San Francisco, CA, 94158, USA. william.deardorff@ucsf.edu.
  • Jing B; Division of Geriatrics, University of California, San Francisco, 490 Illinois Street, Floor 08, San Francisco, CA, 94158, USA.
  • Jeon SY; Division of Geriatrics, University of California, San Francisco, 490 Illinois Street, Floor 08, San Francisco, CA, 94158, USA.
  • Boscardin WJ; Division of Geriatrics, University of California, San Francisco, 490 Illinois Street, Floor 08, San Francisco, CA, 94158, USA.
  • Lee AK; Division of Geriatrics, University of California, San Francisco, 490 Illinois Street, Floor 08, San Francisco, CA, 94158, USA.
  • Fung KZ; Geriatrics, Palliative and Extended Care Service Line, San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA.
  • Lee SJ; Geriatrics, Palliative and Extended Care Service Line, San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA.
BMC Geriatr ; 22(1): 434, 2022 05 18.
Article em En | MEDLINE | ID: mdl-35585537
ABSTRACT

BACKGROUND:

Electronic health record (EHR) prediction models may be easier to use in busy clinical settings since EHR data can be auto-populated into models. This study assessed whether adding functional status and/or Medicare claims data (which are often not available in EHRs) improves the accuracy of a previously developed Veterans Affairs (VA) EHR-based mortality index.

METHODS:

This was a retrospective cohort study of veterans aged 75 years and older enrolled in VA primary care clinics followed from January 2014 to April 2020 (n = 62,014). We randomly split participants into development (n = 49,612) and validation (n = 12,402) cohorts. The primary outcome was all-cause mortality. We performed logistic regression with backward stepwise selection to develop a 100-predictor base model using 854 EHR candidate variables, including demographics, laboratory values, medications, healthcare utilization, diagnosis codes, and vitals. We incorporated functional measures in a base + function model by adding activities of daily living (range 0-5) and instrumental activities of daily living (range 0-7) scores. Medicare data, including healthcare utilization (e.g., emergency department visits, hospitalizations) and diagnosis codes, were incorporated in a base + Medicare model. A base + function + Medicare model included all data elements. We assessed model performance with the c-statistic, reclassification metrics, fraction of new information provided, and calibration plots.

RESULTS:

In the overall cohort, mean age was 82.6 years and 98.6% were male. At the end of follow-up, 30,263 participants (48.8%) had died. The base model c-statistic was 0.809 (95% CI 0.805-0.812) in the development cohort and 0.804 (95% CI 0.796-0.812) in the validation cohort. Validation cohort c-statistics for the base + function, base + Medicare, and base + function + Medicare models were 0.809 (95% CI 0.801-0.816), 0.811 (95% CI 0.803-0.818), and 0.814 (95% CI 0.807-0.822), respectively. Adding functional status and Medicare data resulted in similarly small improvements among other model performance measures. All models showed excellent calibration.

CONCLUSIONS:

Incorporation of functional status and Medicare data into a VA EHR-based mortality index led to small but likely clinically insignificant improvements in model performance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Veteranos / Medicare Tipo de estudo: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Aged80 / Female / Humans / Male País/Região como assunto: America do norte Idioma: En Revista: BMC Geriatr Assunto da revista: GERIATRIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Veteranos / Medicare Tipo de estudo: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Aged80 / Female / Humans / Male País/Região como assunto: America do norte Idioma: En Revista: BMC Geriatr Assunto da revista: GERIATRIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos