Evaluation of the District Health Information System in District Kotli, Azad Jammu and Kashmir: A Retrospective Analysis

Cureus. 2024 Jan 30;16(1):e53242. doi: 10.7759/cureus.53242. eCollection 2024 Jan.

Abstract

Background: It is essential to implement a high-quality electronic database for keeping important information. The District Health Information System (DHIS) is an active data-keeping system in Pakistan. This study aimed to evaluate the patients' data from the DHIS dashboard for the District Headquarters Hospital, Kotli, Azad Jammu and Kashmir (AJK).

Methodology: The data was requested from the hospital administration at District Headquarters Hospital, Kotli, AJK, and the data was analyzed after permission was granted. The data was given in two forms; one was a hard copy of the data for August and September and the other was a comma-separated values file for October and November, 2023.

Results: The highest frequency of patients was received in the department of emergency and trauma and the patient's median age was between 15 and 49 years. The second department was medicine with the >50 years of age. Common conditions that needed more attention were chronic obstructive pulmonary disease, acute respiratory infection, diarrhea, pneumonia, diabetes mellitus, hypertension, and ischemic heart disease.

Conclusion: For nations with constrained healthcare systems and funds, primary health care (PHC) is the only viable approach for managing non-communicable diseases (NCDs). However, PHC systems intended for infectious diseases have not sufficiently adapted to the growing requirement of chronic care for NCD. Research using health information databases offers numerous benefits, such as the evaluation of large data sets and unexpected prevalence of disease in certain populations, such as a higher prevalence of disease in one gender or age group. Health information system-based data analysis or studies are less expensive and faster but lack scientific control over data collection.

Keywords: communicable diseases; district healthcare; global burden of disease; non-communicable diseases; time-series data management.