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By Robert Jordan
Today, healthcare sectors are undergoing a tremendous transformation as they move towards a more data-driven path. As this revolution unfolds, there is an extensive amount of potential to be seen in data-driven healthcare. Meaning, it can streamline data while also improving systems for institutions, practitioners, and patients.
As an emerging platform, eHealth & digital health continues to be defined in varying terms. WHO (World Health Organization) terms eHealth as “the utilization of information & communication tech for health.” Digital health on another note is characterized in a broader sense as an umbrella term that covers areas like telehealth, eHealth, and more.
Regardless of its definition, the bigger player in question here is Data – the leading component that triggers the healthcare industry to move ahead. Big data analysis accumulates information and allows for the identification of trends & patterns.
For the healthcare sector, this means reaping several important benefits such as a decrease in medication errors, facilitation of chronic care, more accurate staffing, and more.
What Drives a Data-Driven Healthcare?
Moving towards data-driven healthcare means focusing on new technologies alone is not sufficient. There are other interconnected factors that can both enable or hinder the transformation.
As such, here are 5 factors that drive and influence data-driven healthcare:
1. Technology Trends
As our current technology enables a more effective passage for patient-clinician engagement to improve overall health outcomes, access to health tech continues to become a commodity.
This leads to a growing acceptance towards wearable medical devices that actively monitor the conditions of patients along with cloudification that allows better communications amongst care teams. Thus, increasing the utilization of digital health records.
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These ongoing trends administer an essential foundation for upcoming innovations, including the utilization of AI & precision medicine that combines big data analytics & machine learning algorithms.
2. Data Security
Factoring in the massive data amount and its value for health sectors, ensuring security is extremely vital, however, healthcare data security can be quite complex. Hence, technical measures alone can’t be seen as a solution.
To reach a competent amount of data protection, acting out in an organizational level is extremely vital.
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Moreover, the transformation of data-driven healthcare isn’t defined only by how data is gathered & analyzed but also by the involvement of all stakeholders within the ecosystem, including suppliers of healthcare providers, partners, patients, and government.
3. Public-Private Partnerships
These are established specifically to utilize the potentiality of big data present in healthcare as well as include partners that are working within the data chain.
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But the association between public & private sectors in analyzing biomedical data gives rise to certain ethical issues like legislative framework, Data ownership that raises ownership questions over raw data & research outputs, and the commercialization concerning research results.
To ease these tensions over the utilization of biomedical data, it’s crucial to express and share openly how public benefit can be produced and distributed through the partnership.
4. Patient Participation
Individuals concerned with their care lead to the increase of data-driven healthcare. But, not all are willing to provide their health data due to various reasons like reluctance on sharing sensitive information, or even scope of the data use, meaning, if individuals lack the understanding of the benefits involved in sharing data, they will simply not share it.
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We can observe this reluctance to share one’s health data while studying the intake regarding contact-tracing applications developed for reducing the spread of the coronavirus.
From June – October 2020, only 7 million individuals downloaded Immuni, the Italian contact-tracing application. According to CENSIS (research institute), its market penetration index reached only around 16%.
5. Change Management within the Industry
A key factor that hinders healthcare transformation is its resistance against change. This resistance often arises within the change effort when developing the change initiative as well as when implementing the change.
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Within the healthcare sector, resisting change is quite common due to the implementation of tight & time-consuming procedures.
And so, any form of change effort that impacts patient treatment and their care must go through various levels of approval from management before its official implementation.
The healthcare industry continues to face changes as it prepares to completely transform patient care. During this early level of ‘data-driven revolution, trends like the increased acceptance of utilizing wearable healthcare devices, the cloudification of health records, and the incorporation of AI finally come into play.
These new technologies assist in generating a great amount of data that can be processed & secured for creating value. Today, data-driven healthcare has finally started to squeeze through the cracks & crevices to open up immense potential for an improved health outcome.
Robert Jordan, a seasoned marketing professional with over 12 years of experience, currently working as Media Relations Manager at InfoClutch Inc, which offers most sought after technology database including AWS customers list, Salesforce clients list with other services. Have expertise in setting up the lead flow for budding startups and takes it to the next level. Have a deep interest in marketing, b2b & technology related discussions. His passion is writing. Currently he works as scholarship essay writer at Studyclerk.