Learn how Clinovera optimized surgical scheduling based on the number of upcoming surgeries (demand) and availability of critical resources – surgeons and operating rooms (supply) for a leading U.S. healthcare system.
About the Client
- Leading Healthcare System in the U.S.
- Business: Orthopedic and Neurological Surgery Department
- Summary: Business Discovery to come up with a new scheduling workflow and technology solution to address supply and demand challenges in surgery departments
- Services: Organizational Transformation, Business Process Redesign, Technology Advisory
Our client, a leading nonprofit multispecialty academic medical center, integrates clinical and hospital care with research and education. Its healthcare network of 26 hospitals is based in Ohio and spans the Mid-Eastern U.S.
The Innovation department of the organization contracted Clinovera to analyze existing departmental processes and propose a technology solution for optimized surgical scheduling based on the population of patients expecting surgeries (demand) and availability of critical resources – surgeons and operating rooms (supply). The organization wanted to ensure that the IP and the solution could be licensed to other healthcare organizations and consequently had to be independent of a specific EHR and other systems used to manage surgical resources.
The Clinovera team, composed of clinical analysts and a technical architect, analyzed the existing processes and systems and interviewed the department leads, scheduling staff, practice managers, and IT staff responsible for systems and data integration.
Following an assessment and requirement steps, the team implemented two critical applications targeting different groups of users:
- A collaborative system for surgeons and surgical staff to express, capture, and reconcile their scheduling preferences, eliminating inefficient manual processes and ad-hoc personal meetings involving dozens of participants.
- An intelligent and platform-agnostic scheduling system that guides staff during patient scheduling to select optimal surgery slots based on resource availability and patient and provider preferences.
The proposed application was integrated with the EHR and other relevant systems using FHIR API. The Clinovera team proposed a phased approach where the applications will collect relevant data, which will later be used as training data sets for Machine Learning algorithms to make scheduling guidance more targeted and intelligent.
The client is in the process of designing and implementing the solution based on Clinovera’s advisory.