Traumatic Brain Injury in Myanmar: Preliminary Results and Development of an Adjunct Electronic Medical Record.


Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
08 2020
Historique:
received: 04 03 2020
revised: 01 05 2020
accepted: 02 05 2020
pubmed: 16 5 2020
medline: 18 12 2020
entrez: 16 5 2020
Statut: ppublish

Résumé

The treatment of traumatic brain injury (TBI) in Myanmar is a major health issue. Comprehensive appreciation of the pathology is limited given the lack of granular metadata available. In this proof-of-concept study, we analyzed demographic data on TBI generated from a novel, prospective, online database in a lower-middle income country. Neurosurgery residents were given an electronic tablet for data entry into an online database. Metadata-driven data capture was carried out prospectively by trained residents, and the information was reviewed weekly by the supervising team in the United States. Complete data were available on 242/253 (96%) patients. Age at admission was 37 years (range 16-85), and length of stay was 3.53 days (1-21). Etiologies included motorcycle accidents, falls, assaults, pedestrian vehicular injuries, and industrial accidents. Dispositions were primarily to home (211). Average Glasgow Coma Scale score at admission was 12.97. There was a 68% mortality rate of patients directly admitted to the North Okkalappa General and Teaching Hospital with a Glasgow Coma Scale score <8 versus 75% for patients transferred in from other facilities. Surgery was performed on 30 patients (12.4%). Despite a lack of formal training in electronic medical records or research, the resident team was able to capture the majority of admissions with granular-level data. This helped shed light on the etiology and severity of TBI in Myanmar. As a result, more effective transport systems and access to trauma care must be achieved. Accessible regional trauma centers with investment in intensive care units, operative care, anesthesia, and imaging resources are necessary.

Sections du résumé

BACKGROUND
The treatment of traumatic brain injury (TBI) in Myanmar is a major health issue. Comprehensive appreciation of the pathology is limited given the lack of granular metadata available. In this proof-of-concept study, we analyzed demographic data on TBI generated from a novel, prospective, online database in a lower-middle income country.
METHODS
Neurosurgery residents were given an electronic tablet for data entry into an online database. Metadata-driven data capture was carried out prospectively by trained residents, and the information was reviewed weekly by the supervising team in the United States.
RESULTS
Complete data were available on 242/253 (96%) patients. Age at admission was 37 years (range 16-85), and length of stay was 3.53 days (1-21). Etiologies included motorcycle accidents, falls, assaults, pedestrian vehicular injuries, and industrial accidents. Dispositions were primarily to home (211). Average Glasgow Coma Scale score at admission was 12.97. There was a 68% mortality rate of patients directly admitted to the North Okkalappa General and Teaching Hospital with a Glasgow Coma Scale score <8 versus 75% for patients transferred in from other facilities. Surgery was performed on 30 patients (12.4%).
CONCLUSIONS
Despite a lack of formal training in electronic medical records or research, the resident team was able to capture the majority of admissions with granular-level data. This helped shed light on the etiology and severity of TBI in Myanmar. As a result, more effective transport systems and access to trauma care must be achieved. Accessible regional trauma centers with investment in intensive care units, operative care, anesthesia, and imaging resources are necessary.

Identifiants

pubmed: 32413564
pii: S1878-8750(20)30976-1
doi: 10.1016/j.wneu.2020.05.016
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e260-e265

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Jack P Rock (JP)

Department of Neurosurgery, Henry Ford Health System, Detroit, Michigan, USA. Electronic address: jrock1@hfhs.org.

Tyler Prentiss (T)

Department of Global Health Initiative, Henry Ford Health System, Detroit, Michigan, USA.

Su Myat Mo (SM)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Nang Saw Myat Hnin Aye (NS)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Karam Asmaro (K)

Department of Neurosurgery, Henry Ford Health System, Detroit, Michigan, USA.

Aung Thurein Win (AT)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Aye Mya Phyu (AM)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Thint Myat (T)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Thet Maung Maung (TM)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Ai Ai Khaing (AA)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Zayya Naung (Z)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Kee B Park (KB)

Program in Global Surgery and Social Change, Harvard Medical School, Boston, Massachusetts, USA.

Kyi Hlaing (K)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Win Myaing (W)

Department of Neurosurgery, North Okkalappa General Hospital, Yangon, Myanmar.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH