# Multilevel Privacy Assurance Evaluation of Healthcare Metadata
## 3 Multilevel Privacy Assurance Evaluation: Results and Evaluation
### At Individual Level: Results and Evaluation
#### 3.1.2 Evaluation
Still, the pre-GDPR era includes subjective privacy-preserving healthcare metadata handling by healthcare providers. The term subjective implies that the healthcare providers' business goals subjectively dictated the data pipeline of the patients. Here, the loophole was that the business goal of healthcare organizations could have been starkly different from the objectives of the patients while receiving care services. Thus, the patients exercised limited powers concerning their healthcare metadata's purpose, usage, disclosure, and retention. In post-GDPR era, the GDPR with its clause 7 disintegrates the integral aspects of IC. It defines IC as an explicit, autonomous, and automated decision-making and profiling at the onset of data collection. Moreover, IC gives the data subjects the right to access, object, erase, rectify and restrict their sensitive metadata sharing at any point in time. For metadata storage and sharing, the IC concerning issue is peer reviewed, readily received, and portable metadata (Article 20). The latter part promotes data utility and hampers the privacy-preserving measures. Privacy primarily has dichotomous aspects; first, the autonomous, explicit, and informed decision-making, and second is direct/indirect control over PII with powers to object, erase, rectify, and restrict the personal data processing at any point in time. Here, data utility satisfies three criteria: uninterrupted data collection, anonymization/pseudonymization, and uninterrupted data storage and sharing and is described in the context of IC in the following paragraph. GDPR future expectations-based era: For an effective application of Informed Consent, a diagnostic lab (as biorepository and biodata bank) is selected as a case study for focused evaluation of the topic using content analysis. The idea of IC raises confusion because the patients are usually unaware of their healthcare metadata processing, primarily when some Trusted Third Party (TTP) researches the data, for example, AI machine vendors, clinical/scientific researchers, and the data analysts for IoT in healthcare. As disintegrated, anonymous processors ameliorate data transparency but lag in accountability. Accountability of Trusted Third Party (TTP) is vital for better health outcomes of the patients and the society at large. The EU suggests contract-based relationships with healthcare providers and TTP. The contracts must mention the description of TTPs' applied information security measures. In the contract, the signing bodies must mention the vital aspects such as the compensations at the data leak incident, inform about the data outsourcing, and delete the data after assigned data processing. In case of no contract signing, the healthcare provider would be held accountable. The regulatory and legislative authorities at the EU and national levels must unite to fill the TTP-based loopholes. For cryptography in healthcare, anonymization is one-way cryptography that is irreversible and removes personal identifiers and permanently deteriorates the performance of the analytical data. Pseudonymization is two-way cryptography where the identifiers are coded and are reversible, unlike anonymization [79]. Pseudonymization is a preferred privacy-preserving measure in healthcare, as it does not affect the healthcare data utility. The GDPR future expectations-based era requires the improved clause 7 with the implantation of a broad,open-ended IC at the onset of data collection. Furthermore, for uninterrupted data collection, the issue is that the patients' IC is required in each phase with the exceptions of scientific studies. This exception applies, provided that the scientific studies are based on the public's vital and legitimate interest. To this end, the solution is to define public, vital, and legitimate interest and to ensure a broad, open-ended IC at the onset of the data collection.