Smart healthcare has become a health policy services that utilize technologies including wearables, the Internet of things, smartphones, etc., to access information continuously and to link patients, equipment and medical facilities, and then effectively handles and responds in an intelligent way to the needs of medical ecosystems. The smart healthcare management system digitally helps the patient to have used medical assistance and services like emergency response, diagnostic service, and surveillance services at any time and in any location. The evaluation of such a management system must be studied for innovative ideas similar to direct healthcare services. Therefore, this study proposes a Smart Healthcare Management Evaluation using Fuzzy Decision Making (SHME-FDM) method to assess the technological integration efficiency. This study thus evaluates the privacy protection of healthcare data of the smart healthcare management system using the Fuzzy Analytical Hierarchy Process- Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy AHP-TOPSIS). Here, this study uses the fuzzy-based neural network for healthcare predictions. The experimental analysis evaluates the accuracy, reliability and error rate of the fuzzy results. The security risk analysis findings show that the proposed fuzzy model can give the highest risk evaluation performance compared to existing models.