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Rising wave of data integration in COVID times
Abhishek Khanduja Associate Manager – Healthcare Presales and Solutions Group | September 15, 2020
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As healthcare enterprises prepare for the world beyond COVID, delivering enhanced care, bringing down the expenditure, and providing top-notch digital and mobile experience to the customers are some of the top priorities for 2020 and 2021. This has led healthcare organizations to revisit their data strategy and leverage big data technology to improve both clinical and financial outcomes.

As compared to other industries, the Healthcare industry has always been rich in data—be it claims data, clinical data, patient data, pharmacy data, etc. And there is a new stream of data that got introduced due to the widespread adoption of wearables and bio monitors. As Per a report published by Stanford University, the overall healthcare services data is expected to grow at 48% per annum, making it the highest when compared to manufacturing, financial services, or media and entertainment.

But a large portion of the healthcare services data often remains trapped in silos, presenting a fragmented view of patients, making care delivery less efficient and more variable. The amount of data generated tops exabytes and, to leverage this data effectively, the industry spends $300Bn due to poor integration mechanisms and an inability to process the data in a usable form. Historically, the healthcare industry has been a laggard when it comes to processing and integrating data flowing from multiple sources such as claims data and clinical data. This insufficiency was brought to the fore by COVID-19 due to the lack of a proper mechanism to collect and share structured data that could have helped devise an early response to the current crisis, enabled by seamless data sharing and an integrated view.

The reason data integration is a focus area in healthcare organizations

Healthcare enterprises have realized the need of health analytics and big data technology for better clinical and financial decision making, but the industry is sorely plagued by the challenge of enabling communication between different healthcare systems across the value chain to generate meaningful insights. That’s why data integration has become a focus area where healthcare enterprises are looking for effective ways to aggregate, analyze, and prioritize patient/member data. Aggregated healthcare data that is free to move across locations can be used more meaningfully, allowing care providers to unlock actionable clinical insights, and health plan executives manage their cost and outcomes better. Healthcare and life sciences enterprises have adjacent industries like pharma, medical devices, medical tech, CROs and others who are interested in integrating data from healthcare providers or payers. A few of the key healthcare imperatives that are highly dependent on data integration are: -

Advanced health analytics capabilities: Data science can help organizations improve real-time care management practices, reduce operational and financial risks, for example, find correlations, associations of symptoms, familiar antecedents, habits, and clinical variables to predict the evolution of certain diseases’ progression/prevention.

Data-driven care for better health outcomes: Today’s connected ecosystem in healthcare generates digital data that can be leveraged to drive various initiatives such as population health management. By embracing big data and IoT, healthcare enterprises have a real opportunity to improve quality, cut costs, and ensure that every decision made has a good chance of being the right one.

Value-based care: Since the focus is shifting to a value-based model from a fee-for-service model, the health system is now measured by metrics such as health outcome, patient satisfaction, quality, etc. Evolving healthcare delivery models stress on sharing of patient data for care coordination and outcomes monitoring.

Operational efficiency: Meaningful insights into different business processes can provide significant avenues to streamline processes across the ecosystem, revisit metrics and KPIs to spot opportunities to improve overall efficiency.

Regulatory push: Though the industry is witnessing a tectonic shift toward value-based care that is highly data-driven, there is a constant push by Centers for Medicare & Medicaid Services (CMS) to promote interoperability across the healthcare value chain by introducing regulations such as CMS interoperability and patient access final rule, and blue connect. These regulations focus on placing patients first, giving them access to their health information when they need it the most, in a way they can best use it.

Why data integration is a huge roadblock in healthcare?

Siloed EMRs: In recent years, electronic medical record (EMR) has become an important source of data in healthcare as it can be used to drive decision making , improve healthcare quality, and facilitate medical research. But data integration remains a major challenge in deriving useful information due to siloed EMRs and a lack of mechanism to aggregate data.

Lack of standard data format: Healthcare data is fragmented, coming from multiple sources in various formats, serving as a major challenge for communication between different health systems. Over the years, organizations have accumulated various data formats that lack a common standard, causing inaccuracies and delays in interoperability efforts.

Poor data strategy offers no value: The absence of a holistic approach to data handling among multiple stakeholders, with lack of data ownership and data governance, results in a loss of important information during transition, affecting the whole ecosystem.

Legacy systems in healthcare: Elements in a healthcare ecosystem must be able to communicate and interact with each other as well as with new smart devices. However, there is an infrastructural bottleneck as a lot of healthcare systems still reside on legacy platforms that can neither communicate with each other properly, nor can its data be consumed by modern systems.

Regulations: The woes of healthcare data complexity are not only limited to multiple non-standard formats used by different health systems but also the government regulations from a compliance perspective. This makes the overall healthcare data integration process delicate and challenging. Besides, the new regulations—where CMS mandates the payers and providers to share the data among themselves to give uninterrupted access to patients—have made interoperability a crucial factor.

Connecting the unconnected

To gain competitive advantage, healthcare organizations need a comprehensive and structured view of the end-to-end healthcare value chain, which can be enabled by HCL with:

Accelerators: HCL has built a set of tested, platform-agnostic, pre-built APIs adhering to interoperability standards, integration templates, and standard implementation practices to help organizations address their integration needs easily, accelerating the implementation process to meet regulatory timelines.

Practice COE: HCL has established a practice COE that is specific to integrations, which focuses on training/onboarding of resources on various healthcare standards—HL7 v2 / v3, EDI X12, CDA, NCPDP, DICOM, LOINC, SNOMED, FHIR, with in-depth experience. The practice COE helps in quicker onboarding of resources who understand the nuances of the data being handled, comprising techno-functional consultants who access a client’s existing technical landscape and arrive at an optimal solution to address the client’s needs.

Partnerships: With efficient players in the industry for integration, HCL will be able to give a holistic approach and create win-win solutions for the involved stakeholders.

  • Partnerships with such organizations shall break down silos and help in building innovative solutions in a quick turnaround time, adhering to interoperability standards to achieve tangible outcomes.

The road ahead

It is clear that aggregating data across the healthcare value chain and analyzing it can improve health and financial outcomes drastically. But putting this healthcare data in motion to generate a 360-degree view remains a broken process. With an emphasis on extracting patient data from the systems, successful EMR data integration is key to achieving data-driven healthcare and better outcomes. To solve the data puzzle, the industry needs to redraw the data integration strategy by leveraging relatively new standard such as Fast Healthcare Interoperability Resources (FHIR), which has got a tremendous early uptake that makes it an essential component to health information exchange and interoperability in modern health IT. With reimbursements tied to value-based care delivery models, healthcare enterprises are incentivized toward this cause. Also, a renewed push from CMS to promote interoperability, and counting on this pandemic, would also act as an accelerator to enable healthcare enterprises to overcome data integration roadblocks and eventually achieve 100% interoperability.

Aggregating data across the healthcare value chain and analyzing it can improve the health and financial outcome drastically.