An education management information system with simultaneous monitoring of stress stimulators for students Mental Health management

2016 ◽  
Vol 24 (6) ◽  
pp. 889-897 ◽  
Author(s):  
S. Manimaran ◽  
S. Jayakumar ◽  
K. Bhagya Lakshmi
1997 ◽  
Vol 42 (7) ◽  
pp. 744-749 ◽  
Author(s):  
J Renée Robinson ◽  
Douglas J Tataryn

Objectives: To determine the accuracy of data contained in Manitoba's Mental Health Management Information System (MHMIS) as compared with client charts and to determine which factors influence completeness and accuracy. Method: Data on diagnosis, open date and close date, demographic information, and contact information were obtained from client charts and compared with data extracted from the MHMIS. Semistructured interviews were conducted with individuals who contribute data to the MHMIS. Results: Data on required demographic variables, primary diagnosis, and open and close dates are highly similar in the 2 sources. The correlation between data sources on the number of client contacts is also good. Conclusion: This study establishes the reliability of MHMIS data. MHMIS data, in combination with hospital abstracts and physician claims data, provide the information needed to serve as a psychiatric case register (PCR) and can be used for psychiatric epidemiology as well as for planning, monitoring, and evaluating mental health services.


2014 ◽  
Vol 599-601 ◽  
pp. 1993-1996
Author(s):  
Yu Fen Zhou

The software of the mental health records management system application mode were analyzed, and the mental health management information system adopts centralized deployment and decentralized application mode, the system adopts B/S/S structure mode, can be convenient and fast to provide a full range of community correction object mental health management information system, system maintenance system is mainly divided into administrator, judicial bureau management, community manager, counselor, correction, correction object family this several user role.


10.1596/27080 ◽  
2012 ◽  
Author(s):  
Emilio Porta ◽  
Jennifer Klein ◽  
Gustavo Arcia ◽  
Harriet Nannyonjo

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.


2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Athi Linda Yani ◽  
Mohamad Ali Murtadho

Bongkot village has many people suffering from mental disorders. There are around fifty people suffering from mental disorders. Prediction of mental disorders at table three is usually done through interviews. Cadres need to fill out the form provided on the Towards Healthy Soul Card (KMSJ) at the interview. The form needs to be filled out based on the results of the interview to predict whether the interviewee has a mental illness or not. If the results of the interview are predicted to have a mental disorder, the cadre will recommend appropriate follow-up. This process is certainly prone to mistakes because it only depends on cadre knowledge. Predictions will certainly affect the recommendations given. in this community service program, the authors propose to apply Information Technology (IT) to reduce the risk of such errors. The system is named the Mental Health Posyandu Management Information System (SIM). The system is expected to be able to improve the efficiency and effectiveness of services at the posyandu, the output of this service produces an online-based application related to the service of mental health posyandu with the address www. poskeswa.com.


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