One of the fundamental questions that the global digitization wave is trying to answer is how to automate, simplify and optimize the use of data. Every industry is looking to take control and use data to improve operational performance and create added value in its processes. The healthcare industry is no exception to this.
Healthcare organizations recognize that their most valuable asset in today’s digital age is the vast amount of transactional data they have stored and collected over the years. The job is to integrate and connect this data to produce something useful.
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First and foremost, physicians can create advanced patient profiles. Combining a patient’s electronic medical record with lab data from medical wearables and consumer devices creates a complete picture of the patient. This provides physicians with a for continued treatment. Digitizing patient medical records can improve the availability and accessibility of information while increasing the likelihood that data will be archived.
Additionally, as the number of accurate patient profiles grows, physicians can apply predictive analytics to preventive care, enabling more proactive approaches to disease detection, prediction, diagnosis and treatment. Such data also serve as valuable information for medical and pharmaceutical research, accelerating the process of breakthrough discovery and ultimately improving public health in general.
From an operational perspective, monitoring and managing data related to patient visits will help identify and resolve inefficiencies in registration, testing, image processing, and information access. It enables us to improve the patient experience with the institution.
Data has revolutionized healthcare, but it is not without its challenges. Electronic medical records have placed a tremendous burden on healthcare organizations, which must manage data, ensuring integrity, interoperability and security while complying with related policies and regulations.
Data Quality
Data is the fuel that drives the operation of any information system. Therefore, ensuring data integrity means ensuring the system’s functionality and effectiveness. In the medical industry, being too accurate is never a problem. The availability of quality data determines the quality of care patients receive.
Poor quality data – incomplete, ineffective, inaccurate, redundant, non -standardized and nonsensical data – contributes to medical errors, directly threatening patient health and safety and undermining healthcare institutions. Besides damaging the reputation of the company, it also leads.
In addition, poor-quality data significantly impacts day-to-day operations, such as inefficient internal and external communication, payment errors, and processing delays. In addition, flawed data can hinder medical research and development efforts by providing misleading information, which can lead to false discoveries and results. “If you put garbage in, you will only get garbage out .”
Data Interoperability
For data to be most useful in all industries, it must create consistent meaning and be shared and communicated among people, organizations and systems. This is called interoperability. Data interoperability integrates patient data from various electronic health systems, giving patients full control over what records they share and with whom while fostering research and innovation in medicine.
It has an important meaning in terms of “to do”. However, one of the long-standing challenges of the healthcare industry is that achieving data interoperability is not just about technical issues such as consistency of data across different systems and organizations; it is about processes. It also requires an integrated structure and the willingness of stakeholders to share information.
Data Security
In an era where personal information is digitized and used across organizations, systems and even boundaries, the healthcare industry faces major data security and patient privacy challenges. According to Verizon’s 2018 Data Breach Investigations Report, security breaches from the healthcare sector accounted for approximately 28% of all confirmed breaches, most of which were due to human error. Additionally, the healthcare industry has to deal with a large amount of fraud.
Policy Settings
Many countries worldwide understand the security risks associated with patient data in the digital age and have enacted strict laws to control the use of medical data. However, this constrained and complex regulatory environment is preventing countries from realizing the full potential of big data in healthcare.
With technological innovation occurring at an alarming rate, healthcare organizations will undoubtedly adopt the best technology use cases for their operations to improve efficiency and better serve their patients. Under these circumstances, government data usage restrictions are likely to raise significant compliance issues and hamper the very process of improving healthcare organizations.
Therefore, policymakers must strike a balance between data security, data accessibility, and potential for data misuse to foster innovation and knowledge sharing and to set appropriate policies that ensure data privacy.