Improve Patient Outcomes Through Automated Event Detection

Improving patient outcomes is a top priority for all healthcare organizations, but the path to achieving this goal is often paved with challenges. Approximately one in every 10 patients experience harm in healthcare¹—whether medication errors, surgical errors, healthcare-associated infections, sepsis, diagnostic errors, etc.—though only a fraction are reported,² leaving healthcare providers with an incomplete understanding of the problems affecting their patients. Inconsistent reporting, a heavy documentation burden, and a lack of resources to uncover breaches in patient safety and quality can all contribute to this issue. 

In this article, we will discuss:

• Factors impacting surgical patient outcomes

• Improving patient outcomes through resilient systems and visibility

• The role of AI in improving patient outcomes

• How to leverage technology to improve patient outcomes

Factors Impacting Surgical Patient Outcomes 

The first step in developing strategies to drive meaningful improvement is recognizing the key factors that can impact patient outcomes. A wide range of clinical and operational factors can have a direct influence on the wellbeing and recovery of patients, from surgical complications to medication errors. Healthcare organizations can begin to implement targeted interventions and create more resilient systems to enhance the quality of care³ by gaining deeper visibility into these issues. 

Patient outcomes can be significantly impacted by a variety of factors, such as: 

• Surgical hypothermia: Unintended perioperative hypothermia⁴ can lead to a higher risk of surgical site infections, coagulopathy, and prolonged hospital stays. 

• Excess bleeding: Excessive blood loss during surgery⁵ can result in complications such as hemodynamic instability, organ dysfunction, and increased transfusion requirements. 

• Excess hypotension: Prolonged periods of low blood pressure⁶ can compromise organ perfusion and increase the risk of adverse events like myocardial infarction, stroke, and acute kidney injury. 

• Prolonged anesthesia: Extended exposure to anesthetic agents⁷ may contribute to postoperative delirium, cognitive dysfunction, and other complications. 

• Surgeon/team fatigue: Fatigue among surgical teams⁸ can impair decision-making, increase the risk of errors, and compromise patient safety. 

• Poor team communication: Breakdowns in communication⁹ within the surgical team can lead to misunderstandings, delays in care, and adverse events. 

• Failure to conduct surgical safety checklists: The omission of critical safety steps, such as the World Health Organization's (WHO) Surgical Safety Checklist,¹⁰ can increase the risk of preventable complications. 

Improving Patient Outcomes Through Resilient Systems and Visibility 

The key to improving patient outcomes lies in creating resilient systems that can identify, address, and learn from safety and quality events, but an organization must first increase visibility into these issues. Traditional approaches, such as relying on self-reporting, often fail to capture the full scope of the problem, leaving healthcare providers with an incomplete understanding of what is happening within their facilities. 

The Role of AI in Improving Patient Outcomes 

Artificial intelligence (AI) can play a crucial role in improving patient outcomes by supporting the detection of safety and quality events.¹¹ AI-powered systems can continuously monitor patient data from various sources, including video footage, electronic health record (EHR) data, and medical devices, to identify potential issues in real-time. These automated triggers can then alert the appropriate quality and safety committee designees, enabling them to focus precious time on investigating incidents and identifying trends. 

One of the significant benefits of AI-driven event detection is the ability to provide a more comprehensive and unbiased understanding of what occurred. Healthcare quality and safety personnel can review video footage to gain deeper insight¹² into the sequence of events, the actions taken by the care team, and any contributing factors that may have influenced the outcome. This information can then be used to inform process improvements, policy changes, and targeted training efforts to prevent similar incidents from occurring in the future. 

The Path Forward: Leveraging Technology to Improve Patient Outcomes 

Improving patient outcomes is a complex and multifaceted challenge, but new technologies are simplifying this mission for healthcare organizations. Providers can gain greater visibility into the factors impacting their patients' wellbeing by leveraging the power of AI-driven automated event detection¹³ to make informed decisions and implement targeted interventions that drive meaningful improvements. Healthcare organizations may take a significant step toward ensuring the best possible outcomes for their patients by creating resilient systems and learning from past mistakes. 

If your organization is interested in learning more about how to leverage technology to improve patient outcomes, contact us.  

Recommended Reading 

1. World Health Organization. (2023, September 11). Patient Safety. https://www.who.int/news-room/fact-sheets/detail/patient-safety. Accessed August 21, 2024.  

2. Aljabari, S., Kadhim, Z. (2021). Common Barriers to Reporting Medical Errors. ScientificWorldJournal, 6494889. https://doi.org/10.1155%2F2021%2F6494889.  

3. Deutsch, E.S., Van, C.M., & Mossburg, S.E. (2022). Resilient Healthcare and the Safety-I and Safety-II Frameworks. PSNet. Rockville (MD): Agency for Healthcare Research and Quality, US Department of Health and Human Services. https://psnet.ahrq.gov/perspective/resilient-healthcare-and-safety-i-and-safety-ii-frameworks. Accessed August 21, 2024. 

4. Brooks, C. & Matulewicz, S.B. (2022). Understanding the Sangers of Perioperative Hypothermia. Outpatient Surgery. https://www.aorn.org/outpatient-surgery/article/2022-February-perioperative-hypothermia. Accessed August 21, 2024. 

5. Kwon, Y.S., Kim, H., Lee, H., et. al. (2021). Effect of Intra- and Post-Operative Fluid and Blood Volume on Postoperative Pulmonary Edema in Patients with Intraoperative Massive Bleeding. J Clin Med, 10(18):4224. https://doi.org/10.3390%2Fjcm10184224.

6. Kouz, K., Hoppe, P., Briesenick, L. & Saugel, B. (2020). Intraoperative hypotension: Pathophysiology, clinical relevance, and therapeutic approaches. Indian J Anaesth, 64(2):90-96. https://doi.org/10.4103%2Fija.IJA_939_19.  

7. Vacas, S., Cole, D.J. & Cannesson, M. (2021). Cognitive Decline Associated With Anesthesia and Surgery in Older Patients. JAMA,326(9):863–864. https://doi.org/10.1001/jama.2021.4773.  

8. Gaba, D.M. and Howard, S.K. (2002). Fatigue among Clinicians and the Safety of Patients. NEJM, 347(16):1249-1255. https://doi.org/10.1056/NEJMsa020846.  

9. Improving Communication and Teamwork in the Surgical Environment Module: Facilitator Notes. Content last reviewed May 2017. Agency for Healthcare Research and Quality, Rockville, MD. 
   https://www.ahrq.gov/hai/tools/ambulatory-surgery/sections/implementation/training-tools/improving-fac-notes.html. Accessed August 21, 2024. 

10. Surgical Safety Technologies. (2024). AI-Driven Optimization Platform for Healthcare. https://www.surgicalsafety.com/blog/who-surgical-safety-checklist. Accessed August 21, 2024. 

11. Eppler, M.B., Sayegh, A.S., Maas, M., et. al. (2023). Automated Capture of Intraoperative Adverse Events Using Artificial Intelligence: A Systematic Review and Meta-Analysis. J Clin Med.,12(4):1687. https://doi.org/10.3390/jcm12041687.  

12. Incze, T., Pinkney, S.J., Li, C., et. al. Using the Operating Room Black Box to Assess Surgical Team Member Adaptation Under Uncertainty: An Observational Study. Annals of Surgery 280(1):75-81. https://doi.org/10.1097/SLA.0000000000006191.  

13. Surgical Safety Technologies. (2024). AI-Driven Optimization Platform for Healthcare. https://www.surgicalsafety.com/platform/black-box-platform. Accessed August 21, 2024.