How Digital Health Connectivity and AI Can Help Close Critical Patient Care Gaps

Gaps in care present complex challenges to healthcare organizations and can lead to rising risks for patients. With the evolution of the digital patient record (aka the electronic health record (EHR)), care teams are still potentially missing gaps in care because of missing clinical data, static data, and disconnected disparate data.

What is the cost of patient data gaps? Lack of complete and intuitive patient information can result in rising risk to patients and declining overall health outcomes. This is a risk that providers and care teams do not want to take.

See how AI can make data more actionable here

The answer is an intelligently connected healthcare enterprise with seamlessly interoperability and data sharing. Access to complete and insightful data can play an important role in the transformation of care delivery, by improving quality, safety, and outcomes, while increasing appropriate volume for healthcare services. An intelligent data enterprise is an important mechanism through which healthcare providers and payers, alike, can uncover and draw attention to care gaps in their patient population, better enabling the health of the population with more complete, meaningful data.

A digitalized, end-to-end interoperable data enterprise has the potential to close care gaps, support strong care collaboration and data sharing, and improve outcomes while reducing cost. Artificial Intelligence (AI) can help empower data management to better identify missing data, predict patient-centric outcomes; and provide the opportunity for continuous improvement in the delivery of care.

With smart data insights, the care team can track, evaluate, prioritize, and make more informed decisions regarding the care of their patients. Comprehensive data access provides a more holistic view of patient specific health information, and when combined with AI, can assist physicians and clinicians to determine the best care pathway evaluating predicting outcomes based on patient specific data. These complex algorithms collect and analyze the data behind the scenes, and then translate data into intelligent, yet simplified visualizations for the care team.

Integrated System Management knows that the priorities and challenges for each healthcare organization are diverse. We are experts in working with our healthcare customers to understand their needs, market, requirements and data gaps to design customized, impactful blueprints to reinvent their health data enterprise.

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