Remote health and homecare solutions have played a significant role in the fight against the COVID-19 pandemic. However, now that healthcare systems have adapted to change, and elective surgeries are back in motion, staff shortages have taught hospitals and providers a critical lesson - when guided properly, machines can do as good a job as humans when it comes to patient care and safety.
To achieve their financial objectives, hospitals need to precisely manage finite resources such as inpatient beds, operating rooms (OR), and staff. Gaining a competitive edge and maximizing the value of these assets for the community is possible only through effective and advanced technology adoption.
Making the case for machine-driven perioperative care
Opportunities for improvements, via the machine-first approach, are present throughout the duration of perioperative care episodes, as evidenced by:
1. Variation in pre-operative testing protocols and unnecessary testing
2. Inconsistent or deficient pre-operative assessment and patient preparation for surgery
3. Limited use of evidence-informed guidelines and protocols for certain types of surgery
4. Highly variable and unpredictable surgical times and poorly optimized use of medical supplies
5. Lack of or inappropriate post-operative pain care
6. Poor discharge planning, care transitions, and patient follow-up
In the US, significant investments have gone into improving EHR systems, bed management, patient flow, and OR systems. If mined and analyzed strategically, the vast amounts of data produced by these systems can help hospitals align their clinical and operational plans with better financial outcomes. This includes:
- Optimizing clinical activity with existing resources (increase admissions, transfers, and surgical volume)
- Reducing emergency departments and post-anesthetic care unit boarding (reduce walk-outs, ambulance diversions, and lost transfers)
- Staffing with the right skills and better accuracy
How can technology unlock the opportunity in the challenge?
To realize the improvements many institutions, use measurements, analysis, feedback, and accountability tools and processes. However, many of these technologies are outdated and fall short of leveraging the real power of the data generated by modern healthcare systems.
Predictive modelling of operating rooms to improve block scheduling
Delays or late cancellations of surgical procedures can result in staff dissatisfaction and patient anxiety, as well as extra costs. However, block scheduling can help eliminate these sorts of difficulties by:
- Establishing “draw-downs” and optimizing room utilization
- Reducing costs from having under-utilized rooms
- Reducing cost per occupied bed
Heat-mapping the operating room schedule helps visualize peak operating hours, minimizing non-productive time. Following is a sample illustration of a heat-mapped operating room schedule.
AI-based algorithms to handle variability in surgical operations and outcomes
Today, there is considerable room to improve inpatient surgery cost efficiency and optimize resource utilization for surgical specialties, consultations, and various types of post-discharge care procedures. Advanced AI algorithms not only identify these patterns but can also account for variations and program them into resource utilization protocols. In fact, these algorithms can directly benefit hospitals by reducing surgery duration, lengths-of-stay, discharge dispositions, and in-hospital complication rates.
Machine Learning algorithms for effective preoperative assessment
Self-learning models based on historical data can not only improve the effectiveness of preoperative assessments but can also assist in selective test ordering by staff anesthesiologists. Specifics include:
- Advanced analytics to stratify the risk of each patient and measure outcomes
- ML models to provide clinical decision support and risk intervention protocols
- ML models for patient population studies during the care continuum for reduced costs
Leverage digital communication platforms to improve coordination and collaboration
Leveraging a multi-device compatible communication platform can directly result in shorter hospital stays, greater quality of care, and improved clinical outcomes via improved communication. Examples of such enablers include augmented reality patient information interfaces and intelligent conversational chatbots for enhanced user experiences.
The A Team
Going forward, in the post COVID-19 world, advanced analytics and automation using AI and ML are the technological A Team for optimizing perioperative performance. For example, a large hospital network providing community-based NHS and social care leveraged this sort of technology solution to address their biggest problems.
- Lack of OR efficiency that led to increasingly frustrated surgeons
- Same-day surgical cancellations rose to 10.2%
- Less than 50% of cases had on-time starts
- Long turnover times
- Utilize predictive analytics to redesign scheduling blocks to match demand
- Strengthen OR governance and processes
- Average turnover reduced from 57 to 34 minutes
- Average OR utilization increased from 62% to 72%
- Increased surgeon satisfaction
With these sorts of results in place, it is easy to see how AI and ML technologies can quickly boost a surgical suite’s efficiency in perioperative performance. Using these frameworks makes it easier to integrate and analyze the output from all data-generating platforms and drive greater medical collaboration between surgical and non-surgical specialties.