Abstract
Healthcare providers are legally bound to ensure the privacy preservation of healthcare metadata. Usually, privacy concerning research focuses on providing technical and inter-/intra-organizational solutions in a fragmented manner. In this wake, an overarching evaluation of the fundamental (technical, organizational, and third-party) privacy-preserving measures in healthcare metadata handling is missing. Thus, this research work provides a multilevel privacy assurance evaluation of privacy-preserving measures of the Dutch healthcare metadata landscape. The normative and empirical evaluation comprises the content analysis and process mining discovery and conformance checking techniques using real-world healthcare datasets. For clarity, we illustrate our evaluation findings using conceptual modeling frameworks, namely e3-value modeling and REA ontology. The conceptual modeling frameworks highlight the financial aspect of metadata share with a clear description of vital stakeholders, their mutual interactions, and respective exchange of information resources. The frameworks are further verified using experts’ opinions. Based on our empirical and normative evaluations, we provide the multilevel privacy assurance evaluation with a level of privacy increase and decrease. Furthermore, we verify that the privacy utility trade-off is crucial in shaping privacy increase/decrease because data utility in healthcare is vital for efficient, effective healthcare services and the financial facilitation of healthcare enterprises.
Highlights
Big Data Analytics (BDA) of Electronic Health Record (EHR) is a prerequisite in advancing efficient and effective healthcare and clinical research [1]
As an element of consumerism and service-dominant logic [76], the value chain starts with the healthcare consumers, i.e., the patients
The principal utilizes the postulates of privacy by policy, privacy by design/architecture, and the patient’s informed consent; see Figure 3
Summary
Big Data Analytics (BDA) of Electronic Health Record (EHR) is a prerequisite in advancing efficient and effective healthcare and clinical research [1]. BDA is the application of advanced analytical methods for big data streams to extract useful value [2]. Big Data Analytics (BDA) is significant in understanding, rationalizing, and utilizing healthcare data for multiple purposes [3]. While performing BDA, healthcare providers must avert from data-related ethical issues such as biased decision making, unwanted disclosures, and inaccuracies. In this wake, the healthcare providers ascribe their healthcare data analytics practices to responsible data science [4]. Metadata is data about data or structured data, such as structured patients’ data accompanying lab measurements or images
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