Health Data and Information

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1 Health Data Requirements
In the recent past, clinical and health research fields have utilized the use of health data management systems. This is mainly attributed to the increase in technological advancement, the importance of data analytics in guiding healthcare workers on which decisions to make (Ismail et al., 2020). The disruptive incidents in the healthcare field have led to huge data files and the Internet of Things (IoT) to be connected to the smart health information system that will enable healthcare providers to come up with appropriate diagnoses based on past health history. In this study, we seek to find out the fundamental requirements needed to incorporate the maximum utilization of health data in making decisions (McKenzie & Clark, 2009).
For the health data collected to be utilized to the maximum, a secure and efficient system has to be in place to ensure the data collected is being used via a system that will enable healthcare workers (physicians and nurses) to get access to the design and upload any recent records and to analyze as well to make informed decisions on the diagnosis, prognoses and public insights (Raghupathi & Raghupathi, 2014). The evolution of health data management has changed from analogue methods such as books and paper charts to digital techniques such as Electronic Health Records (EHR's). The use of digital approaches has caused a paradigm shift in how data management has been taken care of and those with the notion that digital methods were not adaptable to biomedical care and research.
The adoption of digital methods such as EHR's has improved the efficiency, efficacy, and effectiveness of the health care provider. Health care workers can provide more services, thus enhancing the health care quality. The quality of patient care has been improved due to the easy access to data in real-time (King et al., 2014). According to Ismail et al., (2020), there has being a change in health data management definition over the years. The recent report on health data management is the use of advanced technologies in offering healthcare services and thus an increase in quality of healthcare services.
The requirements needed in health data management are up-to-date healthcare record, security, sharing, participation of the patient, real-time data, privacy and public insights (Ismail et al., 2020). In terms of medical record time, the data should identify the patient’s demographics and the history of health situations. Other information that can be included is any ongoing medication, laboratory tests and radiology results, if any. Another requirement is that the data should be real-time data that will enhance healthcare quality through easy access to quality data. Patient participation is another essential requirement in health data management. Since the hospitals are the custodians of the data, patients should be allowed access to and monitor the medical data to build trust in the health data management systems.
Sharing of medical records of a patient's treatment is a crucial requirement since the patient might seek medical services in a different health care facility. This will contribute significantly to medical providers to examine the previous medical records. Under sharing, there are three categories: under degree 1, patient's health records are shared in the healthcare facility that the patient is receiving the healthcare services. Degree 2 of sharing involves sharing data with the patient's family and friends and lastly is degree 3 of sharing, in which healthcare records is shared in different healthcare facilities. With the increased cases of data insecurities such as hacking, there is a need for a proper security system to enable the patients' medical records to be handled through cloud computing. How the data will be held will require privacy so that unauthorized persons who could manipulate the data. Lastly, public insights will be necessary for the predictions, patterns and trends as this will help avoid life-threatening situations.
The acknowledgement that data insecurity is a threat to the health data, there are ways in which authentication and identity management should be handled in order to improve the overall security. For instance, the use of biometrics, smart card technology, tokens, photo identification and username together with password would be essential in ensuring the data is secured. Basic authentication depends with the sensitivity of the data, frequency of access and availability of resources. Single Sign On (SSO) ensure that an individual accesses resources securely on a daily basis while enabling the users to authenticate themselves with ease when logging in with a single form of identification to the servers. The advantage of SSOs is the effectiveness the users experience when accessing the server using a single login without having to memorize log in details.
Smart cards would also be used in securing the information from hackers as it is used in many countries in healthcare sector. The advantage of smart cards is the ease to use, low cost of using it and the portability and durability and ability to support multiple applications. Smartcards are also capable of encrypted patient information, biometric signatures and personal identification. Biometrics authentication such as fingerprints, retinal scan and voice imprint are essential in the verification and securing of the portal.
2. Data Analytics Requirements
Health data is an example of big data analytics that require advanced technology to efficiently process the data to make appropriate and informed decisions. The handling of big data in the modern world has become a global phenomenon in making sense of the data (Lau et al....