Health data is the term coined for data that is helpful regarding healthcare-related decision making, research, innovation, prevention and treatment strategies, public health activities, and more.
Health data can stem from diverse sources such as EHRs, referrals, prescriptions, treatment outcomes, etc. Due to its wide use, health data is a valuable to many stakeholders including clinicians, patients, policymakers and other healthcare professionals.
The Value of Healthcare Data
Healthcare data includes not only patient data, but also medical tracking data, scheduling, chronic disease monitoring and more. Close to $5 billion is invested every year in new initiatives for these types of data, but what about access to this data?
A shift through Artificial Intelligence (AI) and automation will ultimately help healthcare data free itself from being stuck between dozens of standards such as HL7 (version 2 and 3), FHIR, LOINC, and DICOM in the long run. However, as interoperability initiatives are only in the beginning phases, healthcare professionals are still going to need to do many manually intensive data processes before benefiting from technologies such as blockchain and automation processes.
In the long run, these technologies will arm healthcare professionals with better patient records that will not only be more easily accessible but will help in the detection of important correlations in lab reports, drug interactions and countless others.
On the flip side, there is also value in healthcare data for hackers. According to the 2017 Breach Level Index Report, 25% of the total data breaches incurred were in the healthcare industry, making it the largest industry affected. This raises the issue of needing to find balance between data accessibility and data security.
The value in healthcare data is not having an overdose or flood of information at arm‘s reach, but rather having a managed complex process of data that flows from and among patients, clinics, hospitals, EHRs, devices and other channels. Through better data generation come better data and an improved healthcare data ecosystem.
Creating a Health Data Ecosystem
A healthcare data ecosystem within and among healthcare establishments could provide greater benefits to data interoperability and a potential long-term data-rich society.
A research study published on the NCBI website entitled “Understanding value in health data ecosystems” presents opportunities and challenges linked to five key areas:
- Collaboration and coordination
- Through collective interdependencies between stakeholders and sectors, key aspects of data sharing can be addressed including technical, legal, structural and social data access.
- Public acceptability and engagement
- Through informed patients and other stakeholders, everyone can understand the opportunities and risks of health data use and the management of the benefits and risks that come along with increased data access.
- Data protection regulation
- Stemming from the EU’s General Data Protection Regulation (GDPR), governance frameworks for anonymized health data use will be possible and more frequent as they are implemented in technological solutions going forward.
- Data quality and interoperability
- Although technical issues such as data quality assurance, IT infrastructures, secure data storage and transfer forms are arising, many efforts are trying to fix these through new data mining techniques, new probabilistic matching techniques (for data linkage and anonymity) as well as cloud computing attempts.
- Workforce capacity
- Training healthcare professionals to properly approach health data (access, interpret and act) will require technical informatics and educational curriculums to ensure data engagement is consistent and durable.
Interpreted and used correctly, health data could improve the effectiveness and efficiency of health research, healthcare delivery and its continuously dynamic development. Overall, health data presents a compelling opportunity to create greater value through longer-term positive outcomes for patients.