A Fuzzy Decision Support System for Medical Service Quality Management in Hospitals

Medical service quality in hospitals and clinical centres is expected to satisfy the patient’s satisfaction and the high precision diagnosis. Periodic assessment of the medical services increases the quality and the staff efficiency. Such quality assessments are analyzed using sophisticated computing techniques such as fuzzy, genetic algorithms, etc. Therefore, this article introduces a Quality Improvement Method using Fuzzy Decision Support (QIM-FDS) for periodic service enhancements in hospitals. This method acquires the diagnosis, care-taking, and environmental factors validated using the two levels of FDS. The first FDS handles the quality improvement and the second deals with recommendations. From the previous patient suggestions/complaints, the quality improvements are performed such that the varying inputs result in high service recommendations. The first FDS and the overall recommendations (from patients) towards the above considerations are accounted for in the second fuzzification process. This consideration assimilates the service demands and is the highest patient response for retaining the same level. Therefore, the fuzzification performs the different condition verification in the second decision-making. The joint FDS processes focus on delivering high-level improvements towards the considered factors.