Surgery Prep: AI Predicts Counseling Time for Patients

The relentless pressure to maximize efficiency in healthcare is colliding with the equally critical need for personalized patient care. A new tool developed by Kaiser Permanente researchers offers a compelling solution: an automated system that predicts the length of preoperative appointments, ensuring clinicians have adequate time with each patient based on individual risk factors and complexity. This isn’t simply about smoother schedules; it’s a strategic move towards proactive, preventative care that could redefine perioperative medicine – and potentially, outpatient care more broadly.

For years, healthcare systems have struggled with the tension between standardized protocols and individualized patient needs. The perioperative period – the time surrounding surgery – is particularly vulnerable. A rushed preoperative consultation can lead to overlooked medical conditions, inadequate patient education, and ultimately, increased risk of complications. Kaiser Permanente’s approach, focusing on a dedicated perioperative medicine (POM) team meeting with all surgical patients, is already a step towards better care. However, ensuring those meetings are appropriately allocated time has been a challenge. The sheer volume – 250,000 surgeries annually at KPNC alone – demands a scalable solution.

The brilliance of TimEHR lies in its data source. Rather than relying solely on diagnoses and procedures, the system analyzes *how* clinicians interact with patient records. The audit logs, mandated by HIPAA, reveal the time spent reviewing medications, test results, and medical history. This “time-spent” metric, analogous to website analytics tracking user engagement, provides a surprisingly accurate predictor of appointment length. This is a significant shift; it’s not just *what* information is in the record, but *how* that information is processed by the care team that matters.

The Forward Look: The implications of this research extend far beyond surgical preparation. The success of TimEHR demonstrates the potential of EHR audit logs as a rich, previously underutilized data source. Kaiser Permanente is already planning to explore applying this methodology to other outpatient settings, such as primary care. Imagine a system that accurately predicts the complexity of a routine check-up, ensuring doctors aren’t squeezed for time and patients receive the attention they deserve. Furthermore, this approach could be instrumental in addressing clinician burnout by optimizing schedules and reducing administrative burden. We can anticipate increased investment in “workflow analytics” – tools that analyze how clinicians actually spend their time – and a growing emphasis on using that data to improve care delivery. The challenge will be ensuring data privacy and security as these systems become more sophisticated, and addressing potential biases embedded within the audit log data itself. However, the direction is clear: the future of healthcare scheduling is data-driven, personalized, and focused on optimizing both patient outcomes and clinician well-being.