학술논문

The Serious Illness Population: Ascertainment via Electronic Health Record or Claims Data
Document Type
article
Source
Journal of Pain and Symptom Management. 62(3)
Subject
Health Services
Clinical Research
Patient Safety
Generic health relevance
Good Health and Well Being
Adolescent
Adult
Electronic Health Records
Emergency Service
Hospital
Humans
Information Storage and Retrieval
Medicare
Middle Aged
Palliative Care
United States
Young Adult
Health services research
medicare advantage
palliative care
Medical and Health Sciences
Anesthesiology
Language
Abstract
ContextPalliative care can improve the lives of people with serious illness, yet clear operational definitions of this population do not exist. Prior efforts to identify this population have not focused on Medicare Advantage (MA) and commercial health plan enrollees.ObjectivesWe aimed to operationalize our conceptual definition of serious illness to identify those with serious medical conditions (SMC) among commercial insurance and MA enrollees, and to compare the populations identified through electronic health record (EHR) or claims data sources.MethodsWe used de-identified claims and EHR data from the OptumLabs Data Warehouse (2016-2017), to identify adults age ≥18 with SMC and examine their utilization and mortality. Within the subset found in both data sources, we compared the performance of claims and EHR data.ResultsWithin claims, SMC was identified among 10% of those aged ≥18 (5.4% ages 18-64, 27% age ≥65). Within EHR, SMC was identified among 9% of those aged ≥18 (5.6% ages 18-64, 21% ages ≥65). Hospital, emergency department and mortality rates were similar between the EHR and claims-based groups. Only 50% of people identified as having SMC were recognized by both data sources.ConclusionThese results demonstrate the feasibility of identifying adults with SMC in a commercially insured population, including MA enrollees; yet separate use of EHR or claims result in populations that differ. Future research should examine methods to combine these data sources to optimize identification and support population management, quality measurement, and research to improve the care of those living with serious illness.