- 86% of surgeons reported an increase in preoperative workload before Total Joint Arthroplasty or TJA (2020 AAHKS surveys)
- There is a huge need for faster, safer, and more accurate preoperative efficiency for elective orthopedic procedures
- Intelligent AI-based preoperative planning solutions can ease the overall preoperative burden for surgeons and their staff
Surgeons and their healthcare teams are more focused on patient selection, necessary medical optimization, and patient education than ever before.
More than 98% of surgeons perform preoperative optimization before a total joint arthroplasty procedure (2020 AAHKS surveys). 94% of surgeons surveyed said they faced an increase in preoperative optimization work done to lower length of stay, reduce readmission rates, and improve patient recovery. 86% reported an overall increase in preoperative work burden.
The surveys found that surgeons spent over 2.5 hours in preoperative optimization tasks not captured in current workload estimates. The majority of these tasks were on patient selection and risk assessment of comorbidities. Additionally, healthcare staff members spend more time on preoperative patient education. This trend is not surprising because patient selection and education are some of the most important steps for outpatient hip and knee surgeries and same-day discharges in Ambulatory Surgical Centers (ASCs).
Preoperative optimization is not the only step adding to an orthopedic surgeon’s workload. The rest of the preoperative planning process also needs to be refined. These steps include templating, communication with patients and medical device companies, and the use of preoperative planning technologies.
Effective preoperative planning can improve patient recovery and reduce the length of stay (LOS). Apart from preoperative optimization, there is an intense urgency to enhance the overall planning process to improve outcomes and meet the growing demand for outpatient surgery in ASCs.
Preoperative planning steps include templating, coordination with medical device companies for the right implants, implant and instrument sterilization, and inventory and logistics management.
New technologies such as patient-specific instrumentation and 3D-printed implants are being used to help improve recovery and outcomes. However, they can add time to the overall preoperative process. And in an ASC or outpatient surgery setting, adding even ten minutes of inefficiencies can impact case schedules and lower cost-effectiveness.
Experts estimate a massive surgeon shortage by 2025 – with orthopedic surgeons in the top five. But demand for orthopedic procedures is through the roof. Surgeons who used to perform a few hundred cases annually are now expected to handle upwards of 1000 cases a year! Demand for orthopedic procedures is expected to double in the next ten years and hit over 13 million annual procedures by 2030.
The burden on orthopedic surgeons is only going to increase. Our health systems have to ramp up efforts to streamline the surgical process to meet patient expectations and keep surgeons from burning out.
Artificial Intelligence integrated into the orthopedic surgical workflow will improve efficiency -just like it does in the rest of our lives.
Recommendation engines that run on AI help us decide what to buy, what shows to watch, schedule our busy calendars, order groceries, and even manage our communication. In the medical field, AI is already at work assisting radiologists in reading medical images, helping oncologists diagnose cancers, and optimizing healthcare administrative tasks. AI can help assess the risk of cardiac arrest and flag ICU patients in need of immediate assistance. According to a report from Sage Growth Partners, nine in ten hospitals have artificial intelligence platforms. Similarly, AI can help improve the world of orthopedics.
Patient-specific and 3D-printing technologies currently rely on hand-drawn digital models of each patient’s joint anatomy to size implants in the preoperative process. Intelligent AI-based preoperative planning solutions can auto-generate 3D anatomic models directly from 2D x-ray images. This saves a tremendous amount of time and increases accuracy by reducing the potential for manual error.
Accurate 3D anatomic models also help surgeons visualize areas of a patient’s anatomy that may have been difficult to see in 2D images. This way, surgeons and their teams can enhance the patient selection and preoperative optimization process.
AI can also generate entire surgical plans automatically. Using AI-generated surgical plans, surgeons and their teams can fine-tune their patient education process to set the right expectations and improve recovery. Over time, machine learning and deep learning algorithms can even learn from postoperative data to help surgeons with preoperative optimization and patient selection.
With AI, surgeons select the most suitable patients for TJA faster, and device companies can size implants for each patient more accurately using AI-based 3D models. This efficiency can lower the overall cost of sterilization and inventory management for surgical facilities and medical device companies.
Integrated intelligent AI can improve the complete preoperative process for elective orthopedic procedures, including: