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Diagnosis Prevalence and Comorbidity in a Population of Mobile Integrated Community Health Care Patients

Published online by Cambridge University Press:  27 December 2018

Becca M. Scharf ,
Rick A. Bissell ,
Jamie L. Trevitt  and
J. Lee Jenkins
Becca M. Scharf
Affiliation:
University of Maryland Baltimore County, Baltimore, MarylandUSA
Rick A. Bissell
Affiliation:
University of Maryland Baltimore County, Baltimore, MarylandUSA
Jamie L. Trevitt
Affiliation:
University of Maryland Baltimore County, Baltimore, MarylandUSA
J. Lee Jenkins*
Affiliation:
University of Maryland Baltimore County, Baltimore, MarylandUSA Johns Hopkins University School of Medicine, Baltimore, MarylandUSA
*
Correspondence:J. Lee Jenkins, MD, MS 1000 Hilltop Circle Baltimore, Maryland 21250 USA E-mail: [email protected]
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Abstract

Introduction

Frequent calls to 911 and requests for emergency services by individuals place a costly burden on emergency response systems and emergency departments (EDs) in the United States. Many of the calls by these individuals are non-emergent exacerbations of chronic conditions and could be treated more effectively and cost efficiently through another health care service. Mobile integrated community health (MICH) programs present a possible partial solution to the over-utilization of emergency services by addressing factors which contribute to a patient’s likelihood of frequent Emergency Medical Services (EMS) use. To provide effective care to eligible individuals, MICH providers must have a working understanding of the common conditions they will encounter.

Objective

The purpose of this descriptive study was to evaluate the diagnosis prevalence and comorbidity among participants in the Queen Anne’s County (Maryland USA) MICH Program. This fundamental knowledge of the most common medical conditions within the MICH Program will inform future mobile integrated health programs and providers.

Methods

This study examined preliminary data from the MICH Program, as well as 2017 Maryland census data. It involved secondary analysis of de-identified patient records and descriptive statistical analysis of the disease prevalence, degree of comorbidity, insurance coverage, and demographic characteristics among 97 program participants. Diagnoses were grouped by their ICD-9 classification codes to determine the most common categories of medical conditions. Multiple linear regression models and chi-squared tests were used to assess the association between age, sex, race, ICD-9 diagnosis groups, and comorbidity among program enrollees.

Results

Results indicated the most prevalent diagnoses included hypertension, high cholesterol, esophageal reflux, and diabetes mellitus. Additionally, 94.85% of MICH patients were comorbid; the number of comorbidities per patient ranged from one to 13 conditions, with a mean of 5.88 diagnoses per patient (SD=2.74).

Conclusion

Overall, patients in the MICH Program are decidedly medically complex and may be well-suited to additional community intervention to better manage their many conditions. The potential for MICH programs to simultaneously improve patient outcomes and reduce health care costs by expanding into larger public health and addressing the needs of the most vulnerable citizens warrants further study.

ScharfBM, BissellRA, TrevittJL, JenkinsJL.Diagnosis Prevalence and Comorbidity in a Population of Mobile Integrated Community Health Care PatientsPrehosp Disaster Med. 2019;34(1):46–55.

Keywords

community healthcomorbidityEmergency Medical Servicesmobile healthpublic health
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 34 , Issue 1 , February 2019 , pp. 46 - 55
Copyright
© World Association for Disaster and Emergency Medicine 2018 

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Footnotes

Conflicts of interest: none

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