Privacy-preserving fractal healthcare information system model based on K-anonymization to improve collaboration among physicians

Transformers are considered as a key in the transmission and distribution of electrical energy. The healthcare sector is a very important industry to serve high-quality services and healthcare treatment to citizens in every country in the world. In the field of healthcare, organizations include individual centres supported by the separate healthcare information systems (HISs), such as in hospitals. Health information systems (HISs) help to ensure that patients immediately receive appropriate treatment. In addition, the healthcare information system (HIS) can be employed as a tool to communicate between skills of members. The collaboration model has become an important requirement in the healthcare environments (Hospitals) to exchange information among physicians that can inform on critical decisions related to healthcare services. In the recent literature review, many studies mentioned that there is a lack of collaboration among hospitals in most developing countries. Such a lack of collaborative effort among physicians based on HIS can affect the medical research services due to the manual and stand-alone systems where these systems do not have real-time technology. Hence, there is a need for an integrated HIS to ensure a collaborative healthcare environment. The fractal approach has been successfully used in designing integrated collaborative HISs which provide an open, autonomic, flexible and collaborative method for linking system units. The term “collaboration” in the field of healthcare is defined as the communication that occurs among healthcare practitioners when sharing information and skills regarding patient care. Sharing this healthcare information among different organizations can significantly benefit both medical treatment and scientific research in relevant sectors. However, sharing this data would directly pose a threat to patients’ privacy. Data sharing in healthcare remains a challenge due to widespread privacy concerns. The privacy preservation of the sharing of information is a crucial impediment to achieve collaboration through health research using HISs. This study has focused on protecting the privacy of sharing information based on fractal healthcare information systems using the K-anonymization model. This study aims: i) To determine the current level of collaboration among physicians; with the factors that affect this collaboration in selected Malaysian hospitals based on privacy preservation; ii) To develop and evaluate a Privacy Preserving Fractal Healthcare Information System (PPFHIS) model to enhance sharing of information in the distributed HIS based on privacy preservation. The data collection has been carried out at two public hospitals in Selangor, as a sample study. The quantitative approach used is the questionnaire survey. The questionnaires were distributed among one hundred and fifty physicians; however, only one hundred and ten questionnaires were completed and considered for analysis. The result showed the lack of collaboration among physicians. This lack of collaboration occurred due to significant factors, such as the privacy issue during information sharing between different hospitals; the system units maintaining autonomy; large amounts of data being difficult to manage and control according to the mixed system (paper and computerized system) used in the hospitals; the new knowledge is not being acquired in a timely manner. Three experts validated the system model and the system prototype before users’ evaluation. The PPFHIS was implemented by the fifty respondents from the two hospitals to evaluate the system usability and the effect of this system in improving collaboration among physicians. Results indicated that the PPFHIS is satisfactory (system usability scores = 76.05). In addition, the privacy concerns significantly affect the sharing of information among physicians. Nonetheless, privacy preservation for the sharing of information improves the collaboration in medical research. These results demonstrate that the combination of Fractal features in sharing information and the K-anonymization model to protect the privacy through HIS improve the collaboration among physicians and enhance healthcare services as well as research activities.

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