To deliver patient-centered care and improve long-term health outcomes, healthcare organizations are increasingly investing in efforts to address patients’ social needs, such as housing, employment, education, transportation and family support, in addition to their clinical needs, according to a new study by the Deloitte Center for Health Solutions.
According to the second annual study from Inovalon and Quest Diagnostics to gauge physician and health plan executive perspectives on the industry’s transition to value-based care, physicians still lack the tools needed to succeed in a value-based care system, with many indicating electronic health records (EHRs) have yet to realize their potential to improve patient outcomes. Last year’s survey revealed similar desire among physicians for tools to accelerate value-based care.
The U.S. healthcare system has been plagued by rising costs and inefficiencies attributed to the fragmented nature of care delivery and communication. As frameworks for interoperability and interconnectedness evolve to eliminate healthcare siloes, there will be opportunities to more quickly aggregate historically fragmented disparate data sources – which, when applying advanced parallel processing, the ability for real-time machine learning and NLP and other artificial intelligence (AI)-related approaches can be realized. The goal is to make that enhanced, patient-specific analytical derivative available to the healthcare delivery system so it can change how payers, providers, and other healthcare organizations engage with patients and drive better outcomes under value-based care.
As the healthcare ecosystem continues to transition to value-based care models, we will see significant investments and related advancements in applications of machine learning – which is the underpinning of artificial intelligence (AI) of computers and processes used in healthcare.
An adaptive, flexible and integrated risk adjustment accuracy platform is needed to deliver actionable insights into patient data and drive meaningful improvements in today’s complex healthcare landscape. Technology that constantly refreshes the analytics so that you aren’t seeking to close gaps in care that have already closed allows for a more efficient and holistic look at your patient data.