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

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 patients.Prehosp Disaster Med. 2019;34(1):46-55.

Variables influencing medical usage rates, injury patterns, and levels of care for mass gatherings.

OBJECTIVES: Mass gatherings create difficult environments for which to plan emergency medical responses. The purpose of this study was to identify those variables that are associated with increased medical usage rates (MURs) and certain injury patterns that can be used to facilitate the planning process. METHODS: Patient information collected at three types of mass gatherings (professional American football and baseball games and rock concerts) over a three-year period was reviewed retrospectively. Specific variables were abstracted: (1) event type; (2) gender; (3) age; (4) weather; and (5) attendance. All 216 events (total attendance 9,708,567) studied were held in the same metropolitan region. All MURs are reported as patients per 10,000 (PPTT). RESULTS: The 5,899 patient encounters yielded a MUR of 6.1 PPTT. Patient encounters totaled 3,659 for baseball games (4.85 PPTT), 1,204 for football games (6.75 PPTT), and 1,036 for rock concerts (30 PPTT). The MUR for Location A concerts (no mosh pits) was 7.49 PPTT, whereas the MUR for the one Location B concert (with mosh pits) was 110 PPTT. The MUR for Location A concerts was higher than for baseball, but not football games (p = 0.005). Gender distribution was equal among patrons seeking medical care. The mean values for patient ages were 29 years at baseball games, 33 years at football games, and 20 years at concerts. The MUR at events held when the apparent temperature was 80 degrees F significantly lower statistically than that at events conducted at temperatures <80 degrees F were (18 degrees C) (4.90 vs. 8.10 PPTT (p = 0.005)). The occurrence of precipitation and increased attendance did not predict an increased MUR. Medical care was sought mostly for minor/basic-level care (84%) and less so for advanced-level care (16%). Medical cases occurred more often at sporting events (69%), and were more common than were cases with traumatic injuries (31%). Concerts with precipitation and rock concerts had a positive association with the incidence of trauma and the incidence of injuries; whereas age and gender were not associated with medical or traumatic diagnoses. CONCLUSIONS: Event type and apparent temperature were the variables that best predicted MUR as well as specific injury patterns and levels of care.

Mass-gathering medical care: a review of the literature.

UNLABELLED: Mass-gatherings events provide a difficult setting for which to plan an appropriate emergency medical response. Many of the variables that affect the level and types of medical needs, have not been fully researched. This review examines these variables. METHODS: An extensive review was conducted using the computerized databases Medline and Healthstar from 1977 through May 2002. Articles selected contained information pertaining to mass-gathering variables. These articles were read, abstracted, analyzed, and compiled. RESULTS: Multiple variables are present during a mass gathering, and they interact in complex and dynamic ways. The interaction of these variables contributes to the number of patients treated at an event (medical usage rate) as well as the observed injury patterns. Important variables include weather, event type, event duration, age, crowd mood and density, attendance, and alcohol and drug use. CONCLUSIONS: Developing an understanding of the variables associated with mass gatherings should be the first step for event planners. After these variables are considered, a thorough needs analysis can be performed and resource allocation can be based on objective data.