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Capturing the care of complex community-based health center patients: A comparison of multimorbidity indices and clinical classification software.
Navale, Suparna M; Koroukian, Siran; Cook, Nicole; Templeton, Anna; McGrath, Brenda M; Crocker, Laura; Bensken, Wyatt P; Quiñones, Ana R; Schiltz, Nicholas K; Wei, Melissa Y; Stange, Kurt C.
Afiliação
  • Navale SM; OCHIN, Inc., Portland, Oregon, USA.
  • Koroukian S; Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
  • Cook N; OCHIN, Inc., Portland, Oregon, USA.
  • Templeton A; OCHIN, Inc., Portland, Oregon, USA.
  • McGrath BM; OCHIN, Inc., Portland, Oregon, USA.
  • Crocker L; OCHIN, Inc., Portland, Oregon, USA.
  • Bensken WP; OCHIN, Inc., Portland, Oregon, USA.
  • Quiñones AR; Department of Family Medicine, and OHSU-PSU School of Public Health, Oregon Health & Science University, Portland, Oregon, USA.
  • Schiltz NK; Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio, USA.
  • Wei MY; Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, California, USA.
  • Stange KC; Center for Community Health Integration, Case Western Reserve University, Cleveland, Ohio, USA.
Health Serv Res ; 2024 Aug 30.
Article em En | MEDLINE | ID: mdl-39212052
ABSTRACT

OBJECTIVE:

To compare morbidity burden captured from multimorbidity indices and aggregated measures of clinically meaningful categories captured in primary care community-based health center (CBHC) patients. DATA SOURCES AND STUDY

SETTING:

Electronic health records of patients seen in 2019 in OCHIN's national network of CBHCs serving patients in rural and underserved communities. STUDY

DESIGN:

Age-stratified analyses comparing the most common conditions captured by the Charlson, Elixhauser, and Multimorbidity Weighted (MWI) indices, and Classification Software Refined (CCSR) and Chronic Condition Indicator (CCI) algorithms. DATA COLLECTION/EXTRACTION

METHODS:

Active ICD-10 conditions on patients' problem list in 2019. PRINCIPAL

FINDINGS:

Approximately 35%-56% of patients with at least one condition are not captured by the Charlson, Elixhauser, and MWI indices. When stratified by age, this range broadens to 9%-90% with higher percentages in younger patients. The CCSR and CCI reflect a broader range of acute and chronic conditions prevalent among CBHC patients.

CONCLUSION:

Three commonly used indices to capture morbidity burden reflect conditions most prevalent among older adults, but do not capture those on problem lists for younger CBHC patients. An index with an expanded range of care conditions is needed to understand the complex care provided to primary care populations across the lifespan.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Health Serv Res / Health serv. res / Health services research Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Health Serv Res / Health serv. res / Health services research Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos