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Abstract. Healthcare has always been a sensitive and a complex process. Rapid strides have been made both in the field of information technology as well as health care successfully integrating both for better facilities and services offered by the health-givers. Electronic health records (EHRs) is the product of this integration and forms an integral part of the automated healthcare system. Accessing of EHR by each stakeholder complements the issues of data disclosure, confidentiality, authenticity and privacy that are likely to occur due to many reasons. This paper aims at studying and identifying security threats to EHR in the hospital information system currently prevailing in the hospitals (HIS). It further categorizes the threats based on security characteristics and rates them on the basis of impact and magnitude of loss to the patients. The paper highlights real-time scenarios with each as an important requirement of the health-givers on one hand, can also be a reason of security breaches on other hand. It concludes by listing challenges and recommendations to curb security threats commonly found in the physical setup of healthcare environment.

With enhanced interoperability in healthcare environment the exchange of electronic health records (EHRs), both intra and inter organisations, has increased manifold. Sharing of the EHR creates room for illegal disclosures and confidentiality breaches. Interoperable healthcare is a complex system with many independent components. To design a secured framework for such a system, one need to understand the most important security attributes and predict various dependencies among them. The security attributes selected for statistical analysis are taken from the real-time study of patient-doctor relationship existing in any hospital or clinic. Hospitals with functional EHR-systems are the prerequisite of this study. The dependencies in the obtained data are generated through classification technique, chi-squared automatic interaction detection (CHAID). The decision tree obtained is analysed and verified using regression. The paper enabled the identification of the salient feature controlling which would maximally reduce security threats while sharing EHRs in interoperable healthcare environment.

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