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

Hospital operating rooms contain much of their advanced and automated technology, such as robots and lasers, but too often hospitals still rely on an awkward mix of legacy technologies: spreadsheets, electronic health record (EHR) tools, phone calls and fax – manage surgical services.

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

  • Manual processes: Surgical scheduling is typically characterized by stressed and overworked administrative staff at both ends: in the hospital and in the surgeons’ offices. Automation should remove friction with every step and lighten their burdens from end to end.
  • Inadequate analysis: Turning data into action can be difficult when systems aren’t specifically designed to analyze and present data in a way that motivates users to take necessary action. Basic data visualization and performance analysis are a given for any software, but most perioperative management software is not sophisticated enough to coordinate steps that maximize planning turnaround times and strategically fill schedules. empty spaces.

However, hospitals can overcome these challenges through the adoption of automation software, which uses artificial intelligence (AI) and machine learning to identify problems, apply automation and behavioral science to orchestrate actions, then leverage statistical analysis to help manage accountability and performance.

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

Unlock operating room time

It is natural for people to conserve scarce resources to make sure they are there when they are needed. This is what surgeons tend to do with operating room (OR) “lockdown time.” Time blocking allows them to establish predictable schedules for themselves and their patients and ensures they can perform procedures in a timely manner.

When they don’t need all their time, they should release it, but often they don’t. Their planners are too busy and might hang on to it “just in case” and only release it when they’re sure they can’t use it, which might be too late for anyone 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 longer turnaround times and may represent more value to the hospital.

Software with advanced machine learning capabilities can learn the booking patterns of each block owner with great accuracy. With enough historical data, a truly intelligent machine learning model can predict up to 30 days the likelihood of a surgeon using a given slot that hasn’t been scheduled yet, and employ behavioral science principles to free it up for use by a surgeon. other surgeon.

Strategically scale up OR cases

OR software enabled by advanced machine learning (a category of artificial intelligence) and behavioral science can intelligently automate manual scheduling processes. It can take into account many variables at the same time: which surgeons prefer Tuesday mornings or generally need longer surgical times, which ones need the robotic room, how many days of lead time each surgeon generally needs, how often a surgeon starts procedures late and which surgeons perform the procedures that represent the highest value for the hospital. It can hold and analyze more information than even the most experienced human programmer.

This intelligence allows the system to identify the optimal surgeon for a particular slot and automatically contact their programmer, just as an online retailer can examine the shopping habits of millions of customers and recommend products with sometimes unnerving accuracy. If that surgeon cannot use the slot, the scheduler clicks the appropriate button and the system moves to the next one in the list. No more hit-or-miss, no more first-come, first-serve, no more manual calls to find a case.

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

Earn market share

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

  • Identify which physicians refer patients to surgeons and which other surgeons refer patients to. Surgeons can use this information to see where they might be missing out on referrals and take steps to strengthen their relationships with those referring physicians.
  • Look at the overall usage patterns of the “splitters”. What other facilities do they use, how often and for what procedures? Armed with this information, surgical leaders can offer a time freeze, or modify the time they already have, to encourage surgeons to stay in their hospitals, and also find out what other factors might make other sites more attractive.
  • Identify surgeons performing the types of procedures surgical leaders want to attract to their hospitals and see where they are performing those procedures now. This information provides administrators with a starting point for analyzing how to reach these high-value surgeons and what to do to attract them.

To achieve these capabilities, claim data from multiple clearinghouses is 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 of the same patient to be linked together, creating a detailed picture of their journey of care across multiple providers. Machine learning is then applied to fill any gaps and improve the accuracy of the data. Surgical leaders can then identify patterns of practice and referrals: which surgeons perform which types of procedures, and which primary care physicians refer patients to those surgeons.

Manual processes and inadequate analytics often prevent hospitals from meeting revenue and OR utilization goals. Using automation, behavioral science, and comprehensive real-world data, hospitals can unleash the full potential of their OR operations and boost perioperative growth.

Photo: hoozone, Getty Images

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