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KMID : 1100520200260020146
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Healthcare Informatics Research
2020 Volume.26 No. 2 p.146 ~ p.152
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Monitoring Mental Healthcare Services Using Business Analytics
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Housbane Samy
Khoubila Adil
Ajbal Khaoula
Serhier Zineb
Agoub Mohamed
Battas Omar
Othmani Mohamed Bennani
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Abstract
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Objectives: Monitoring healthcare activities is the first step for health stakeholders and health professionals to improve the quality and performance of healthcare services. However, monitoring remains a challenge for healthcare facilities, especially in developing countries. Fortunately, advances in business analytics address this need. This paper aims to describe the experience of a low-income healthcare facility in a developing country in using business analytics descriptive techniques and to discuss business analytics implementation challenges and opportunities in such an environment.
Methods: Business analytics descriptive techniques were applied on 3 years’ electronic medical records of outpatient consultation of the University Psychiatric Centre (CPU) of Casablanca. Statistical analysis was conducted to compare results over years.
Results: Over the 3 monitored years, the monthly number of computerized physician order entries increased significantly (p < 0.001). Physicians improved their personal recording over years. Schizophrenia as well as depressive and bipolar disorders were noted at the top of outpatient mental disorders. Antipsychotics are the most prescribed drugs, and a significant annual decrease in outpatient care wait time was noted (p < 0.001).
Conclusions: Business analytics allowed CPU to monitor mental healthcare outpatient activity and to adopt its business processes according to outcomes. However, challenges mainly in the organizational dimension of the decision-making process and the definition of strategic key metrics, data structuration, and the quality of data entry had to be considered for the optimal use of business analytics.
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KEYWORD
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Health Information Systems, Data Science, Mental Health Services, Computer-Assisted Decision Making, Management Decision Support Systems
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