Wrong-site surgery, including operations on the wrong body part (site) or side (e.g., left vs. right), is the most common type of surgical error and can lead to severe, permanent harm or death. The Joint Commission reported 112 surgical errors out of 1,411 incidents in 2023, a 26% increase from 2022. Wrong-site surgery accounted for 62% of these cases.
Wrong-site surgeries occur most frequently in orthopedics, neurosurgery, and urology. According to the study, the most common types of procedures that involved wrong-site surgery were spine surgery, including spinal fusion and excision of intervertebral discs, arthroscopy, and surgeries on muscles and tendons. Patient injuries resulting from these errors include the need for additional surgery, pain, worsened injury, total loss, and death, etc., Only 60% of the cases were settled. The top contributing factors to wrong-site surgery were:
However, inconsistencies in medical documentation do not always indicate errors. A diagnosis that does not specify a body part or side might still be accurate if it justifies a particular surgery. An example could be a diagnosis of diabetes-related gangrene without specifying the body part or side, paired with a right lower leg amputation. To further explore this issue, we conducted a preliminary retrospective analysis of 8.93 million inpatient records from the U.S. CMS in 2020. We categorized records based on whether the diagnoses and surgeries involved the same or different body parts, and whether they specified right side, left side, or both. We particularly focused on cases where site and side records were inconsistent, resulting in 1,064 records with right-side procedures and left-side diagnoses, and 1,106 records with right-side diagnoses and left-side procedures. Each medical record was reviewed by physicians to identify whether the inconsistencies were clinically justifiable or actual errors, based on the following criteria:
The findings revealed that in cases of right-side procedures with left-side diagnoses, 49% of inconsistencies were clinically justifiable, while 51% were actual errors. For right-side diagnoses with left-side procedures, 45% of inconsistencies were justifiable, with 55% were actual errors. These results raise concerns about whether the errors are just mistakes in the documentation or if they actually happened to patients. With approximately 51 million inpatient surgeries performed annually in the U.S.—about 1.62 surgeries every second—this high frequency highlights the need for us to implement more effective approaches to prevent surgical errors. According to the 2024 Global Patient Safety Report from the World Health Organization, only 38% of countries worldwide have implemented reporting systems for preventable and highly destructive medical errors, known as 'Never Events'—medical errors that should never occur. Many of these errors remain underestimated and overlooked. Beyond retrospective reviews, we should also consider using modern technology to prevent surgical errors in real-time. This includes proactive prediction and analysis of diagnoses and clinical evidence to guide accurate surgical decisions and documentation. Overcoming the limitations of traditional rule-based systems and evaluating clinical justification—especially in cases where diagnoses are vague, incomplete, or lack clear specifications of body parts or sides—will mark significant progress in the development of medical AI.
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 The HIMSS theme this year: "Health that Connects, Tech that Cares," highlights the importance of patient-centered practices that connect information, technology, and policy, emphasizing human-centeredness, quality, and interoperability. As forward-thinking tech companies proudly show off their achievements in chatGPT and generative AI, conservative healthcare providers are taking a more introspective attitude, assessing potential impacts and necessary responses. What breakthroughs can we expect at the intersection of these perspectives in the following years? Medical Coding and Payment in Digital Health Due to the pandemic, the U.S. has expanded digital healthcare payment coverage to include telemedicine, remote physiologic monitoring (RPM), remote therapeutic monitoring (RTM), remote assessments, and medical AI. In addition, Medicare is implementing a new Physician Fee Schedule (PFS) and influencing policies that promote medical quality and performance evaluation, such as the Traditional Merit-based Incentive Payment System (MIPS), the new MIPS Values Pathway (MVPs) framework, Alternative Payment Models (APMs), and Accountable Care Organizations (ACOs). As the industry focuses on digital, remote, and quality care, on-demand access to in-demand healthcare services is expected to create new business opportunities supported by more flexible and diverse coding and payment systems. Revenue Relates To Record Quality, Backed By Thorough Analysis And Documentation U.S. hospitals are struggling with prolonged revenue cycles, rising denial rates, and changing reimbursement regulations after the pandemic. To overcome financial challenges, many hospitals are turning to AI and analytics tools to improve the quality of medical records, address workforce shortages and burnout, and ensure both clinical and financial performance. Administrators, physician assistants, specialists, and clinical supervisors must collaborate in their clinical documentation integrity (CDI) efforts to capture missing data from various analyses. Traditional computer-assisted physician documentation (CAPD) systems are no longer sufficient; only proactive physician nudges and documentation assistance can effectively eliminate gaps in the medical record. For example, systems that flag hemoglobin or iron abnormality in lab data or identify brain lesions in scattered notes can actively remind physicians and expedite accurate diagnoses. While major vendors such as EPIC, 3M, and Optum offer these features, most are rule-based rather than AI-driven. Hospitals like Pediatrics still need to create their own rules and analyze data under the constraints of the system architecture to develop automated, customized nudge applications. Technology in Healthcare: Balancing Quality and Economic Benefits Speakers from UNC Health and Mayo Clinic revealed that their institutions have approximately 35,000-40,000 and 130,000 connected medical devices, respectively. Despite cybersecurity concerns, the medical data generated by these devices must be linked to medical records and utilized effectively. The vast amount of medical information can be standardized and coordinated only through analytics and AI tools that support medical record documentation, allowing healthcare professionals to access critical insights. Telemedicine policy has experienced profound reform in the wake of COVID-19. The recovering healthcare industry must adapt to the new digital era at its own pace. It may be too early for the widespread use of NLP and ChatGPT in clinical practice. Instead of blindly pursuing the latest technology trends, hospitals are more focused on adopting new approaches that effectively utilize various generations of technology to tackle both new and existing problems while balancing medical quality and economic benefits to improve patient outcomes and resource allocation. #himss23 #cdi Reference
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