Webinar: Patient Scheduling Analytics - Understanding Patient Behavior and Preferences to Deliver the Most Efficient and Effective Clinical Care

Published May 22 2020
6.23 Stock Photo
June
23
Online
11am ET

The unfolding COVID-19 pandemic has brought renewed focus to population-centered clinical programs and operations – including various ongoing population health initiatives.  Health systems are struggling to understand and analyze patient status as they navigate through the scheduling system – and to measure the impact of variances as patient visits move from on-site to telehealth.  Many scheduling systems are not prepared to leverage such attributes to help predict patient response to new visit alternatives.

The ability of health systems to characterize patients into discrete sub-groups based on diagnosis, provider relationships, tailored care plans, anticipated resource needs, and various social determinants – including access to or familiarity with communications technology – is helping care teams analyze and predict patients’ behavior in terms of care plan and visit compliance, and acting proactively to ensure the best [clinical and financial] results. 

Using attributes such as: patient age – patients’ willingness to try telehealth visits – the nature and goals of the visit (e.g., procedure-based, assessment-only, new or existing patient) – travel distance – concerns around social distancing – and the reach of remote staff – providers are able to adjust their approach to ambulatory visits to increase compliance and improve outcomes – including reducing the impact of deferred revenue.

The Alithya Healthcare Solutions Team has developed an end-user analytics application to identify patients at risk for missing scheduled visits – for various reasons – and prioritizing them for intervention by the clinical and administrative staff.  This webinar demonstrates the use of end-user analytics tools to understand the evolving needs of diverse patient populations – to enable health providers to deploy and allocate appropriate resources (i.e., staff, technology, inventory) for reaching these patients – and to prioritize the delivery of the most relevant services to enable the most beneficial outcomes.

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