28 Feb Data integration: Changing the pharma and healthcare landscape
By Nimita Limaye, Technology Networks
The integration paradigm fueling data insights
Despite the data explosion in the past 10-15 years, this has largely been “data unrealized” – its value has not been exploited. Subsequent investments in data integration strategies, technology, and analytics have transformed a medley of free-floating data points into an integrated, coherent message. Pharma has leveraged data integration across the value chain, from discovery through development to commercialization. Healthcare is also leveraging data integration strategies to drive value-based healthcare models.
The integration of this data has created the opportunity to delve deep into the real world and generate meaningful insights, optimize patient recruitment, develop a better understanding of various therapeutics, and directly improve patient outcomes.
Data integration is triggering significant change in the healthcare industry
Innovative projects lead the way
Data integration has been driven by various FHIR initiatives involving key stakeholders, such as the payer-focusedDa Vinci Project, and the provider-centered Argonaut initiative. Technology initiatives include Certified EHR Technology (CEHRT) and SMART APP have been launched. CEHRT, which became effective in 2019, provides an assurance that an EHR system offers the necessary technological capability, functionality, and security to help them meet the meaningful use criteria. To avoid a downward payment adjustment, health care providers are required to use the 2015 Edition CEHRT (Bresnick, 2018, CMS.gov). The SMART APP Launch provides a framework that connects third-party applications to EHRs. However, despite these initiatives, industry challenges still do exist in terms of integration with legacy approaches and shifting from transaction-oriented standards to FHIR-based interaction-oriented standards (Heath, 2016).
Medicare’s Blue Button 2.0 leverages FHIR-based APIs which allow subjects to download their personal health data directly from CMS and share it with providers or retain it for their own records. End-users such as developers, providers, and researchers can also mine that data and generate actionable insights from the same at no cost and the sandbox has been created in such a way that the data cannot be traced back to patients (Bresnick, 2018). Read more …