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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Injury Severity Score coding: Data analyst v. emerging m-health technology.

R T Spence¹, E Zargaran, M Hameed

¹Codman Center, Massachusetts General Hospital, Boston, USA; Department of General Surgery, Faculty of Health Sciences, University of Cape Town, South Africa. spnric004@myuct.ac.za.

South African Medical Journal = Suid-Afrikaanse Tydskrif Vir Geneeskunde

|October 12, 2016

Summary

Mobile health technology offers a cost-effective solution for injury severity scoring in trauma care, comparable to traditional methods. This innovation improves accessibility in high-incidence trauma regions worldwide.

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Area of Science:

Trauma care and injury severity assessment.
Mobile health (m-health) applications in medicine.
Global health disparities in trauma management.

Background:

The high cost of Abbreviated Injury Scale (AIS) coding limits its use in resource-limited, high-trauma incidence areas.
Mobile health technology presents a potential cost-effective alternative to traditional AIS coding.
This study investigated m-health utility in a South African trauma center.

Purpose of the Study:

To evaluate the feasibility and accuracy of a mobile health application for injury severity scoring.
To compare m-health-derived Injury Severity Scores (ISS) with traditional AIS coding methods.
To determine if m-health technology can provide a cost-effective alternative for trauma centers globally.

Main Methods:

A prospective study of 57 surgically managed trauma patients over one month.
Clinician-entered data via an m-health app (ISS eTHR) and standard AIS coding (ISS VGH) were used.
Statistical analysis included Bland-Altman plots, kappa statistics, intraclass correlation coefficients (ICC), and logistic regression models.

Main Results:

Mean ISS difference was 0.4 (95% CI -0.8 - 1.6), with comparable model performance for predicting complications.
Intraclass correlation coefficients (ICC) for individual and categorical ISS were 0.88 and 0.81, respectively.
Kappa statistic for ordinal categories was 0.53, indicating moderate agreement.

Conclusions:

Injury Severity Scores (ISS) derived from m-health technology (eTHR) are comparable to gold-standard coding (VGH).
Emerging m-health technology offers a viable, cost-effective alternative for injury severity scoring in trauma care.
This approach can enhance trauma data collection and management in resource-constrained settings.