International Classification of Disease Coding of Exertional Heat Illness in U.S. Army Soldiers.

Mil Med

173rd IBCT(A) Brigade, Vincenza, Italy, CMR 473 BOX 1439, APO, AE 09606.

Published: September 2017

AI Article Synopsis

  • The study investigates the accuracy of ICD-9 coding for exertional heat illnesses (EHI) among U.S. Army soldiers, focusing on whether the correct diagnostic codes were used.
  • Out of 290 cases analyzed, 80 met the diagnostic criteria for heat injury or stroke, but 28 were incorrectly coded; additionally, 66 out of 210 non-qualifying cases were inaccurately diagnosed as heat-related.
  • Overall, the sensitivity was 0.65, specificity was 0.69, with positive predictive value of 0.44 and negative predictive value of 0.84, indicating a significant number of misclassifications in the ICD-9 coding for EHI.

Article Abstract

Introduction: The severity of exertional heat illnesses (EHI) ranges from relatively minor heat exhaustion to potentially life-threatening heat stroke. Epidemiological surveillance of the types of and trends in EHI incidence depends on application of the appropriate International Classification of Disease, 9th Revision (ICD-9) diagnostic code. However, data examining whether the appropriate EHI ICD-9 code is selected are lacking. The purpose of this study was to determine whether the appropriate ICD-9 code is selected in a cohort of EHI casualties.

Materials And Methods: Chart reviews of 290 EHI casualties that occurred in U.S. Army soldiers from 2009 to 2012 were conducted. The ICD-9 diagnostic code was extracted, as were the initial and peak values for aspartate transaminase, alanine transaminase, creatine kinase, and creatinine. Diagnostic criteria for heat injury and heat stroke include evidence of organ and/or tissue damage; 2 out of 3 of the following must have been met to be considered heat injury (ICD-9 code 992.8) or heat stroke (ICD-9 code 992.0): aspartate transaminase/ alanine transaminase fold increase >3, creatine kinase fold increase >5, and/or creatinine ≥1.5mg/dL. Contingency tables were constructed from which sensitivity, specificity, and positive and negative predictive value were calculated.

Results: The 290 cases in this cohort represent ∼29% of all EHI at Fort Benning and ∼6% of all EHI Army-wide during the study period. There were 80 cases that met the laboratory diagnostic criteria for heat injury/stroke, however of those, 28 cases were diagnosed as an EHI other than heat injury/stroke (sensitivity = 0.65). 210 cases did not meet the laboratory diagnostic criteria, but 66 of those were incorrectly diagnosed as heat injury or heat stroke (specificity = 0.69). Positive and negative predictive values were 0.44 and 0.84, respectively. In total, the incorrect ICD-9 code was applied to 94 of 290 total cases.

Conclusions: Our data suggest that caution is warranted when examining epidemiological surveillance data on EHI severity, as there was disagreement between the laboratory data and the selected ICD-9 code in ∼1/3 of all cases in this cohort. Of note is the lack of an ICD-9 or -10 code for heat injury; we recommend coding for heat exhaustion as the primary diagnosis and additional codes to capture the accompanying muscle, tissue, and/or organ damage.

Download full-text PDF

Source
http://dx.doi.org/10.7205/MILMED-D-16-00429DOI Listing

Publication Analysis

Top Keywords

icd-9 code
24
heat stroke
16
heat injury
16
heat
14
diagnostic criteria
12
ehi
9
icd-9
9
code
9
international classification
8
classification disease
8

Similar Publications

Purpose: Studies of healthcare encounters leading to cancer diagnosis have increased over recent years. While some studies examine healthcare utilization before the cancer registry date of diagnosis, relevant pre-diagnosis interactions are not always immediately prior to this date due to date abstraction guidelines. We evaluated agreement of a registry date with a claims-based index and examined Emergency Department (ED) involvement in cancer diagnosis as an example of possible pre-diagnostic healthcare misclassification that could arise from improper date choice.

View Article and Find Full Text PDF

Cardiogenic shock (CS) is one of the leading causes of death in patients with myocardial infarction, myocarditis, and congestive heart failure. The utilization patterns of specialist palliative care (PC) consultation in these patients are currently unknown. To determine the utilization of PC in patients with CS and the overall comorbidities of that population.

View Article and Find Full Text PDF

Background: Medical comorbidity burden has a substantial impact on care for patients with dementia and has major impacts on quality of life. No nationwide study has evaluated trends in medical comorbidity burden of patients with a new diagnosis of dementia. We therefore performed a nationwide study of medical claims data to understand the prevalence of comorbid medical conditions at time of dementia diagnosis in real-world clinical practice.

View Article and Find Full Text PDF

Background: Cognitive problems are thought to increase vulnerability to geriatric traumatic brain injury (TBI) due to increased fall risk, but little is known about prevalence of cognitive impairment and Alzheimer's disease and related dementias (ADRD) among elders who receive treatment for a TBI.

Method: Enrollees 65 and older in the nationally representative Health and Retirement Study (HRS) who consented to link survey data to Medicare claims and without a TBI prior to enrollment were studied. We used claims 2000-2018 to obtain incident TBI diagnoses, defined using inpatient and outpatient International Classification of Disease (ICD) 9 and 10 codes received the same day as an emergency room (ER) visit code and a computed tomography (CT) scan code.

View Article and Find Full Text PDF

Background: It is not well understood how incidence patterns of subtypes of Alzheimer's disease and related dementias (ADRD) have evolved in real-world practice. While cohort and brain bank studies provide precise biological definition of ADRD subtypes, these populations may not be representative and may not reflect how dementia is coded and diagnosed in routine clinical practice. Therefore, we sought to perform a nationally representative study of medical claims data to understand trends in diagnosis of dementia by dementia subtypes in routine clinical practice.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!