Health data is data that relates to a person’s health, such as their state of health, examinations and test results, medications, and causes of death. With the advancement of the digitalization of healthcare, health data has become an important component of healthcare systems worldwide. Malaysia has followed suit.
GOOD HEALTH DATA = HEALTHY HEALTH DATA
Good and healthy data is how well the organization of data supports its business objectives. Criteria for healthy data include being easily discoverable, understandable, and providing value to the people that need to use it. Adapting health digitalization in a healthcare environment requires participation, involvement, and commitment from various stakeholders.
Good health data is crucial for efficient healthcare, policymaking, and research. However, achieving good-quality data requires a lot of effort and comes at a cost. This article intends to explore the various costs associated with producing good health data from a healthcare facility's point of view.
HEALTH DATA INFRASTRUCTURE
Information technology (IT) infrastructures utilized for health data storage, access, and analysis are known as health data infrastructures. One of the most apparent costs of good health data is the financial investment required to develop and maintain a robust health information system (HIS). Upgrading from manually kept records to electronic medical records (EMR) systems, health databases, and other digital platforms that collect, store, and manage health data is inevitable in adapting to changes to improve health data quality. The development of HIS requires substantial capital investment in hardware, software, and cybersecurity measures to protect sensitive health information from cybersecurity threats.
TRAINING AND CAPACITY BUILDING
To ensure the effective management and utilization of health data, healthcare professionals and data managers must be adequately trained. In Malaysia, there is a big gap that must be filled for capacity building to enhance the skills of those who manage and analyze health data. This includes training in data entry, management, analysis, and interpretation. In order to fill the gap, it is imperative for hospital managers and human resource departments at healthcare centers to identify personnel who are suitable and have a deep interest in taking on roles dealing with hospital data. Healthcare institutions must also consider investing in educating their staff to increase their digital literacy and keep pace with the evolving landscape of health data. In addition, remuneration to retain skilled health data scientists and IT professionals in the healthcare sector can be challenging and costly.
TECHNOLOGICAL ADVANCEMENTS AND INTEGRATION
Currently, mainstream programs like Microsoft Excel and SPSS are used for manual analysis of health data. Integrating cutting-edge technology like artificial intelligence (AI), machine learning (ML), and big data analytics into health data systems is essential to moving toward more holistic data management. Large
datasets may be analyzed more easily and accurately, which also makes it possible to predict outbreaks, identify patterns, and customize patient care.
Nevertheless, implementing these advanced technologies is expensive. It necessitates the purchase of specialist software in addition to regular upkeep and updates. Moreover, it can be difficult and time-consuming to integrate new technologies into current health systems; frequently, this requires re-engineering workflows and procedures.
ETHICAL AND LEGAL CONSIDERATIONS
The ethical and legal implications of health data management are another critical component of its cost. Ensuring the privacy and confidentiality of patient data is paramount. Malaysia's Personal Data Protection Act 2010 (PDPA) sets the legal framework for data protection, but compliance with these regulations requires continuous effort and resources.
Healthcare institutions must implement strict data governance policies, conduct regular audits, and ensure that all staff are aware of their responsibilities regarding data privacy. Non-compliance can have serious consequences, including legal repercussions, a decline in public confidence, and possible patient injury.
THE VALUES OF GOOD HEALTH DATA
The advantages of having high-quality health data significantly outweigh the expenditures. Better patient outcomes, more effective healthcare delivery, and well-informed clinical and policy decisions are all achievable with the proper utilization of high-quality health data.
For example, Malaysia's capacity to monitor and evaluate health data played a critical role in controlling the COVID-19 pandemic. The Malaysian government's initiative to develop applications for contact tracing, MySejahtera, and the commitment of its users to provide information demonstrated how efficient data administration and collection could improve public health responses.
Good health data also encourages innovation and research. It makes it possible for scientists to carry out epidemiological investigations, create novel therapies, and enhance healthcare regulations. Over time, this results in a population that is healthier and pays less for healthcare.
CONCLUSION
The expenses for top-notch health information comprise training, advancements in technology, financial commitments, and ethical concerns. Even though the costs are high, these investments significantly benefit patient outcomes, research, and healthcare delivery. In order to ensure the continual development of a robust health data ecosystem, it is crucial to recognize and address these costs as Malaysia advances its health information infrastructure.
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