<div> Blockchain technology is widely used in almost every domain of life nowadays including healthcare sector. Although there are existing frameworks to govern healthcare data but they have certain limitations in effectiveness of data governance to ensure security and privacy. This study aimed to evaluate effectiveness of health care data governance frameworks, examining security and privacy concerns and limitations within the existing frameworks of ISO Standards, GDPR, and HIPAA. In this study quantitative research approach was followed. A sample of 250 participants from Islamabad, Lahore and Karachi based healthcare experts, IT specialist, blockchain research and developer, administrator was selected. The collected data was analyzed though frequencies and descriptive statistical tests with the help of SPSS. The results revealed un-satisfaction for data governance frameworks, i.e., ISO standards, GDPR, and HIPAA in terms of security concerns, i.e., data encryption, access controls, audit trails, interoperability and standards, smart contracts for compliance, data integrity, regulatory compliance monitoring and privacy concerns, i.e., consent management, anonymization and pseudonymization, data minimization. The participants agreed that there is a need of integration of reliable data governance framework in health care data management. Various personalized governance techniques, targeted security upgrades, and continuous improvement in the specific customized data governance framework has been presented based on the findings of the study. An implementation of blockchain-based systems is recommended in order to ensure and expand the security and privacy of healthcare data management. </div>

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[Frequency analysis].

H Bernt · PubMed · 1988

Cited by 0

Frequency analysis

Randall, R. B · Virtual Defense Library (Ministerio de Defensa) · 1987

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Frequency Analysis

Anders Hedegaard Hansen · Fluid mechanics and its applications · 2023

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Frequency analysis

SpringerReference · 2011

Cited by 1

Frequency analysis

Randall, R B, Tech, B A · CERN Document Server (European Organization for Nuclear Research) · 1987

Cited by 0

Frequency analysis

Randall, R. B. · 1987

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Multichannel frequency and time-frequency analysis

Thomas Koenig, Roberto D. Pascual‐Marqui · Cambridge University Press eBooks · 2009

Time series of EEG scalp potential differences typically appear to be composed of oscillations at various frequencies. Although the amplitude and spatial distributions of these oscillations may fluctuate in time, the quantification of these oscillations as a function of frequency and location (i.e. the multichannel spectral analysis of the EEG) is very reproducible within and across subjects and systematically varies depending on a series of physiologically interesting factors. To mention a few examples, EEG spectral analysis has been successfully employed to characterize a subject's age, state of arousal, the presence of neurological or psychiatric disorders, drugs or task demand as systematic deviations of spectral power from a norm.

Cited by 19Open access

Frequency-Domain Analysis

Constantino Antonio García Martínez, Abraham Otero Quintana, Xosé A. Vila et al. · Use R! · 2024

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