Disease models of traditional medicine departments of some district hospitals in Quang Binh province

Authors

  • Tuan Linh Nguyen*
  • Quang Huy Doan

Keywords:

disease model, Quang Binh province, traditional medicine

Abstract

This study was carried out with the aim of describing the disease patterns of inpatients at the Department of Traditional Medicine of three district hospitals in Quang Binh province in 2019-2021 by cross-sectional descriptive method. The research subjects of this study include all inpatients at the Department of Traditional Medicine of three hospitals, namely Bo Trach District General Hospital, Le Thuy District General Hospital, and Tuyen Hoa District General Hospital from January 2019 to the end of December 2021. The collected data are processed by biomedical statistical algorithms with the support of SPSS 20.0 software. The research results showed that in 2019 sciatica accounted for 35.4%. In 2020, this data slightly decreased to 30.7%, in 2021 the disease accounted for the largest proportion was schizophrenia (44.0%). In 2019, 97.85% of cases had treatment results “Stable and discharged”. In addition, the duration of inpatient treatment gradually increased over the years (2019 was 7.88±1.39 (day), 2020
was 8.98±1.59 (day), and 2021 was 9.64±1.69 (day).

DOI:

https://doi.org/10.31276/VJST.66(5).40-42

Classification number

3.5

Author Biographies

Tuan Linh Nguyen

Bo Trach District General Hospital, Hoan Lao Town, Bo Trach District, Quang Binh Province, Vietnam

Quang Huy Doan

Vietnam University of Traditional Medicine, 2 Tran Phu Street, Mo Lao Ward, Ha Dong District, Hanoi, Vietnam

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Published

2024-05-25

Received 2 August 2022; revised 23 August 2022; accepted 26 August 2022

How to Cite

Nguyen Tuan Linh, & Doan Quang Huy. (2024). Disease models of traditional medicine departments of some district hospitals in Quang Binh province. Version B of Vietnam Journal of Science and Technology, 66(5). https://doi.org/10.31276/VJST.66(5).40-42

Issue

Section

Medical and Pharmacological Sciences