scholarly journals Design and implementation of a health management information system in Malawi: issues, innovations and results

2005 ◽  
Vol 20 (6) ◽  
pp. 375-384 ◽  
Author(s):  
Chet N Chaulagai ◽  
Christon M Moyo ◽  
Jaap Koot ◽  
Humphrey BM Moyo ◽  
Thokozani C Sambakunsi ◽  
...  
2013 ◽  
Vol 411-414 ◽  
pp. 223-226
Author(s):  
Zhi Biao Li ◽  
Jian Qiang Du ◽  
Hui Zhu ◽  
Wen Wen Xiong ◽  
Zhi Yong Liu

This paper conducts a study on the design and implementation of Assessment and Intervention of Sub-health Management Information System (AISH-MIS). A Lightweight Java EE framework based on the analysis of the Struts, Hibernate and Spring is introduced. Under this framework, the intermediate tier is divided into three layers, Web layer, Service layer, PO layer. With the multitiered framework, System has better maintainability and reliability. Furthermore, this paper present the modules diagram of the system and describes eight modules architecture.


2020 ◽  
Author(s):  
SUSAN F. RUMISHA ◽  
EMANUEL P. LYIMO ◽  
IRENE R. MREMI ◽  
PATRICK K. TUNGU ◽  
VICTOR S. MWINGIRA ◽  
...  

Abstract Background: Effective planning for disease prevention and control requiresaccurate, adequately-analysed, interpreted and communicated data. This study assessed the quality of routine Health Management Information System (HMIS) data at healthcare facility (HF) and district levels in Tanzania. Methods: HMIS tools used at primary health care facilities (dispensary, health centre, hospital) and district office were reviewed to assess their availability, completeness, and accuracy of collected data. The assessment involved seven health service areas namely, Outpatient department, Inpatient department, Antenatal care, Family Planning, Post-natal care, Labour and Delivery and Provider-initiated Testing and Counselling.Results: A total of 115 HFs in 11 districts were assessed. Registers (availability rate=91.1%; interquartile range (IQR):66.7%-100%) and reportforms (86.9%;IQR:62.2%-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%;IQR:35.6%-100%). Tools availability at dispensary was 91.1%, health-centre 82.2% and hospital 77.8%, and was poor in urban districts. The availability rate atthe district level was 65% (IQR:48%-75%). Reports were highly over-represented in comparison to registers’ records, with large differences observed at HF phase of the data journey and more profound in hospitals.Tool availability and data quality varied by service-areas, indicators, facility level, and districts, however, with a remarkable improvement over the years.Conclusion: There are high variations and improvements in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the HFs. These results highlight the need to design tailored and inter-service strategies for improving data quality.


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