Clinical Evaluation: An AI Assistant for Primary Care
By: Navina View more from Navina >>
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Improving payer-provider collaboration in healthcare with AI
By: XSOLIS
Type: White Paper
Due to a dependence on legacy systems and technology, many clinical teams have been forced to perform more unnecessary administrative tasks and spend less time on clinical interventions.
Despite these problems, most healthcare organizations stick with the status quo in nonclinical administrative functions or make modest changes with minimal impact. But with spending on the rise, as well as friction between payers and providers, now is the time for change.
Read on to discover how fully leveraging AI can improve understanding and communication between payers and providers and drive more efficient health outcomes.
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How AI in utilization management enables better care
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Due to the limitations of traditional utilization management and review (UM/UR) methods in healthcare, providers and payers often struggle to work together and lack the ability to collaborate in real time.
The result is often a redundant, time-consuming process that contributes to clinician burnout and can have negative consequences for patients, whose experiences hang in the balance if care is delayed. It has become clear that a new plan is needed.
Download this white paper to delve further into this problem and explore the potential of a purpose-built tool that leverages AI and ML to remove subjectivity in the UM/UR process, leading to improved outcomes for payers, providers, and patients.
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With the recent boom in Artificial Intelligence solutions, healthcare organizations and software vendors are looking at ways to implement AI into existing workflows and processes. Yet healthcare organizations seeking to incorporate this new technology should consider several factors.Navina, a pioneer in clinical AI that turns fragmented, multi-source patient data into actionable insights that physicians can trust, has published a helpful guide to implementing AI in healthcare organizations.
Download the guide to get useful tips for every stage of implementation, including selecting the right AI partner, achieving high clinician adoption and setting organizational KPIs.
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