5 Challenges Faced in Healthcare Data Management/Analytics

The healthcare industry is currently going through a gigantic digital transformation. Much of this is related to the ways and the data quality that is being used and captured.

Various companies and organisations are accumulating data from several sources such as, insurance claims, healthcare management system, lab results, clinical notes, drug prescriptions and wearable technologies.

The world wide flow of digitization seeks to respond to one of the fundamental questions which is, how to simplify, optimize and automate the use of data.

In the present scenario, healthcare organisations and institutions have come to realise that the most useful benefit in this era of digitalization is the huge piles of transactional and historical data that is being stored and collected for years.

A systematic data will always continue to help the healthcare world in many ways. First of all, physicians are able to develop and determine the profiles of patients more, with each passing day.

If a combination is done taking the Electronic Medical Record (EMR) of the patient with the data from the medical wearable technologies and consumer level testing, then an overall picture of the patient and his or her health condition can be figured out or drawn.

More the number of accurate profiles of patients rises up in number, the physician will, as well, be able to use predictive analytics and take preventive care to detect, diagnose, anticipate and treat different kinds of diseases.

These data are absolutely invaluable inputs for pharmaceutical and healthcare research, which in turn, speeds up the procedure for discovering new methods and treatments, and resulting in the improvement of public health.

If the data quality is monitored and maintained properly, especially the ones related to the patient’s visits, then it can improve in resolving and pinpointing certain inefficiencies or inadequacies in testing, registering, imaging and accessing information.

Healthcare email data has brought about important very essential transformations over time, but of course with the benefits comes the challenges that are faced in healthcare management or analytics. The introduction of electronic healthcare records imposes a huge pressure on the healthcare team to handle huge data in ways that must assure- integrity, security, safety and interoperability, while agreeing with certain regulations and policies.

In order to fulfill many benefits, the big challenges that are faced in healthcare data management  are as follows:

Data precision – there is minimum data governance that is actually effective and capturing data stands as one of the biggest hindrances for healthcare companies. For efficient use of data, it should stay precise, clean and correctly arranged so that it can be applied in various healthcare processes.

Data interoperability – data should be transferred and shared among organisations, people and systems as well as it needs to have consistent meaning in order to be useful to any kind of industry- this is known as interoperability.

Data interoperability has a very particular definition in the healthcare industry because it makes the patients capable to control their own records and decide whom to share with, it consolidates the data of a patient from a range of electronic healthcare processes and at the same time facilitates the research and innovation process.

It is a great challenge for the healthcare industry to maintain data interoperability because there are continuous technical issues and there are parties’ willingness to share their personal information, which is not always successful.

Data certainty – While dealing with extremely sensitive patient data and other data, the organisations and Healthcare companies should operate or handle it with great cautiousness. Any leakage of details can cause huge loss and damage to the organisation as a whole. It is also unethical to disclose any personal details or data without any prior authorisation.

Data quality – is considered to be the fuel that generates the operations and working of any type of information system. Thus, assuring data integrity means ensuring the whole procedure’s or system’s effectiveness and the way it functions.

Data cannot be more appropriate in the healthcare world where the availability of quality data rules over the type and quality of service and treatment that one individual receives.

Dirty data, which is generally comprised of inaccuracy, incompleteness, duplication, non-standardization and invalidity- can lead to ruin the data quality and create mistakes in the medical field.

Dirty data results in direct threat to the well being and safety of every individual who is being treated, damaging the reputation of the healthcare provider and will lead to costly lawsuits.

Further, bad data quality can disturb the working of daily operations which consists of enormous necessary payments, distorted and disturbed external and internal communication and delayed services and treatments.

It is also capable of inhibiting development activities such as medical research, information that can mislead both doctors and patients and discover incorrect and improper ways of treatment.

Data security – in this modern age where personal information and details are digitised and moved all around and crosses all boundaries of systems and organisations, the Healthcare air industry faces one of the biggest questions of patient privacy and data security.

According to Data Breach Investigation Report 2018, security disturbances from healthcare faculty takes up almost twenty eight percent of all confirmed dysfunctions, with the maximum number coming from human errors.

The healthcare industry also needs to handle the huge heaps and piles of improper conducts. A report from 2018 stated that in Australia, HealthEngine, which is a doctor appointment system, leaked private identifiable data of almost two hundred patients, every month, between March and August.

A very strategic approach is required to manage healthcare data where data quality, security and data interoperability should be balanced and addressed equally. If you have a doubt of carrying dirty data or anything about the strategies that you have adopted, then immediately review your structure from a data expert today.

It is very important to understand the concept and role of the support received from the government in maintaining and encouraging the infrastructure of that part of the legislature which allows the healthcare industry to utilise and handle data and analytics in different certified ways which will yield most values to all individuals.

Healthcare data is to project out and rise rapidly, in the coming years. Since this data brings a lot to the table, it is important to use the data appropriately.

About Author 

Prabhakar Alok is an SEO Specialist at Ampliz. He has been also featured as the best digital marketer in India to follow at Software Suggest Website. He has 5+ years of experience in the SEO Industry. Prabhakar has also written 100+ blog posts. Over the last 7 years he has built a reputation for developing the best business strategies, incubating new business models and expanding partner channels world-wide.

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