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Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

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Hospital Readmission and Social Risk Factors Identified from Physician Notes.

Amol S Navathe^1,2,3,4, Feiran Zhong⁴, Victor J Lei⁴

¹Division of Health Policy, University of Pennsylvania, Philadelphia, PA.

Health Services Research

|March 16, 2017

Summary

This summary is machine-generated.

Physician notes reveal significantly higher prevalence of social risk factors in cardiovascular disease patients than administrative data. This improved identification can help better address patient social needs and reduce 30-day readmissions.

Keywords:

Social determinants of health natural language processing quality of care readmissions

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Area of Science:

Health Services Research
Clinical Informatics
Public Health

Background:

Social determinants of health significantly impact patient outcomes, including hospital readmissions.
Traditional administrative data sources (claims, structured EHR data) may underestimate the prevalence of social risk factors.

Purpose of the Study:

To compare the prevalence of seven social factors identified in physician notes versus claims and structured electronic health records (EHRs).
To assess the association between these social factors and 30-day readmissions among cardiovascular disease patients.

Main Methods:

An observational study analyzed data from 49,319 cardiovascular disease admissions between 2011 and 2013.
Data sources included all-payer claims, EHR data, and physician notes extracted from a centralized clinical registry.
Multivariable logistic regression was used to adjust for patient characteristics.

Main Results:

Physician notes identified all seven social characteristics at higher rates than claims and structured EHR data.
Prevalence of poor social support increased from 0.4% in administrative data to 16.0% in physician notes.
Housing instability, depression, drug abuse, and poor social support were significantly associated with increased 30-day readmission risk.

Conclusions:

Social risk factors are substantially more prevalent than typically represented in administrative healthcare data.
Automated analysis of physician notes offers a promising approach for more accurate identification of patients' social needs.
Improved identification of social needs can potentially lead to targeted interventions to reduce readmissions.