3 Ways Hospitals Can Recover Surgery Revenue Using AI and Automation - MedCity News

No department is more important than surgical services to a hospital’s overall financial health, nor more important to its reputation and growth potential.

Hospitals’ operating suites contain much of their advanced, automated technology, such as robots and lasers, but too often hospitals still rely on an unwieldy mix of legacy technologies—spreadsheets, electronic health record (EHR) tools, phone calls and faxes— for surgical services management.

Most surgical suites lack effective automation to address these two common challenges:

  • Manual processes: The surgical schedule is typically characterized by stressed, overstretched administrative staff at both ends: in the hospital and in the surgeons’ practices. Automation should remove friction from each step and ease their burden end-to-end.
  • Inadequate analyses: Turning data into action can be difficult when systems are not specifically designed to analyze and present data in a way that motivates users to take the necessary actions. Master data visualization and performance analytics are a given for any software, but most perioperative management software is not sophisticated enough to coordinate the steps that maximize planning time and strategically fill the void.

However, hospitals can overcome these challenges by adopting automation software that uses artificial intelligence (AI) and machine learning to identify problems, apply automation and behavioral science to orchestrate actions, then use statistical analysis to help accountability and performance management.

Here are three ways automation software tools allow hospitals to increase revenue and utilization:

Unlock operating room time

It is only natural for people to conserve scarce resources to ensure they are there when they need them. This is what surgeons tend to do with operating room (OR) “block time.” Blocked time allows them to establish predictable schedules for themselves and their patients and assures them that they can perform procedures in a timely manner.

When they don’t need all their time, they should free it up, but often don’t. Their schedulers are too busy and they can hold it “just in case” and only release it when they’re sure they can’t use it, which might be too late for someone else to use it. Typically 30% or more of available hours go unused, and slots that can be rebooked at short notice cannot be used for procedures that require more lead time and may represent greater value to the hospital.

Software with advanced machine learning capabilities can learn the booking patterns of each block owner with high precision. With enough historical data, a truly intelligent machine learning model can predict up to 30 days out how likely a surgeon is to use a particular slot that has not yet been scheduled, and use behavioral science principles to free it up for use by another a surgeon.

Strategically grow OR cases

OR software enabled by advanced machine learning (AI category) and behavioral sciences can intelligently automate manual planning processes. It can account for many variables at once: which surgeons prefer Tuesday mornings or typically need longer operating times, which require a robotic room, how many days of turnaround time each surgeon typically needs, how often a surgeon starts procedures with delay and which surgeons perform the procedures that represent the highest value to the hospital. It can store and analyze more information than even the most experienced human planner.

This intelligence allows the system to identify the optimal surgeon for a particular slot and automatically connect to his schedule, just as an online retailer can look at the buying habits of millions of customers and recommend products with sometimes eerie accuracy. If that surgeon cannot use the slot, the scheduler clicks the corresponding button and the system moves to the next one in the list. No more random hit or miss, no more first come, first served, no more manually calling to find a case.

Surgeon planners can also tap into the system through a search function that works like an online travel booking site that shows the best flight options in seconds. They enter multiple search criteria (time of day, case type, length of procedure, room type, preferred location) and receive a list of slots that are the best fit. Especially for independent practices, when it is so easy for surgeon schedulers to find available operating times, they will contact the hospital first using this software and save themselves the hassle of calling other facilities.

Gain market share

According to a recent survey by The Health Management Academy, 86% of health system executives say that increasing referrals and reducing churn is important or extremely important to increasing surgery revenue. In general, there are three ways to achieve these goals, depending on the hospital’s market characteristics, current services and strategic plan:

  • Identify the doctors who refer patients to surgeons – and which other surgeons they refer patients to. Surgeons can use this information to see where they may be losing referrals and take steps to strengthen their relationships with referring physicians.
  • See common usage patterns for “splitters”. What other equipment do they use, how often, and for what procedures? Armed with this information, surgical leaders can offer to block time or modify the time they already have to encourage surgeons to stay at their hospitals and also discover what other factors might make other sites more attractive.
  • Identify surgeons who perform the types of procedures surgery leaders want to attract to their hospitals and see where they are performing those procedures now. This information gives administrators a starting point to analyze how to reach these valuable surgeons and what to do to attract them.

To obtain these capabilities, claims data from multiple clearinghouses are combined and then stripped of identifying information to protect patient privacy. Even when we don’t know the identity of individual patients, a process called “tokenization” allows records to be linked together by the same patient, creating a detailed picture of their care journey across multiple providers. Machine learning is then applied to fill in any gaps and improve the accuracy of the data. Surgical leaders can then identify practice and referral patterns: which surgeons perform what types of procedures and which primary care physicians refer patients to those surgeons.

Manual processes and inadequate analytics often prevent hospitals from meeting OR revenue and utilization goals. By leveraging automation, behavioral sciences, and comprehensive real-world data, hospitals can unlock the full potential of their operational enterprises and drive perioperative growth.

Photo: hoozone, Getty Images

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