Diagnostic Characteristics of Patient Self-Assessment of Preoperative Cardiac Risk for Non-Cardiac Surgery - Foundations for Patient Driven Decision Support.

Surgery is a frequent health care intervention with an estimated 6 million non-cardiac surgical procedures performed every year in the United States, with progressive growth in the number of procedures noted each subsequent year(1). Preoperative medical evaluations have been a cornerstone of pre-surgical care planning and patient management. The clinical providers who carry out these pre-operative evaluations are guided by their medical knowledge, institutional policies and clinical practice guidelines. To address the challenge of standardizing the evaluation and management of perioperative cardiovascular complications of non-cardiac surgery, the American College of Cardiology/American Heart Association (ACC/AHA) issued perioperative guidelines for non-cardiac surgery in 2007 with a focused update on preoperative beta blockade in 2009(2), followed by the latest update in 2014 (3). These guidelines modified recommendations on the Revised Cardiac Risk Index (RCRI) (4,5) to highlight a set of conditions associated with higher post-operative morbidity and mortality for patients undergoing non-cardiac surgery. As surgical interventions continue to evolve with increasingly complex and costly procedures, there is a critical need to improve the preoperative assessment to effectively identify clinical risk factors and manage existing co-morbidities. In the typical perioperative window, from one month before to one month after the surgical intervention, targeted risk mitigation can be implemented to reduce surgical complication risk. In the context of growing surgical work volumes, there is a paucity of well-trained primary providers and preoperative assessment clinics to address patient needs with ongoing growth in the number of preoperative assessments (6–8). An important partner for the surgical team is the patient, who ultimately has the most at stake from the surgical benefits and potential complications (9). Unfortunately, few tools are available for patients to self-identify surgical risk and empower them to work in tandem with multi-disciplinary surgical teams. Such tools could help patients become better informed of their surgical risk and address an important knowledge gap since most patients have limited recall of the risks and benefits of surgical interventions after completing the pre-operative clinical workup (10,11). In addition to the potential educational and clinical benefits to patients, patient driven decision support tools could also be a cost-effective adjunct tool for surgical quality efforts including Accountable Care Organizations (ACO), medical homes, and other efforts to enhance clinical quality. Having effective patient driven clinical assessments can provide surgical providers a greater appreciation of risks prior to their planned procedures and facilitate optimized multi-specialty care delivery. Decision support tools that offer patient self-assessment can potentially help mitigate time pressures in the typical 30-day preoperative window by adding important triage data to better identify the at-risk populations. To use patient-driven clinical information to its optimal capacity, it is important to establish its validity and reliability. The ability of patients to self-identify clinical risk factors has been previously established in many studies of chronic disease (12–17). There are several strategic advantages to having patients identify their own clinical risk factors, both to have patients better understand their own clinical conditions and risk of surgical complications, as well as potential cost savings with obtaining valid clinical information without the cost of provider mediation (11,18,19). However, tools for patient self-identification of clinical risk factors have not always crossed directly from large research studies into use in clinical care (9,17). Technologies like clinical decision support systems (CDSS) hold immense potential to enable patients to access higher tiers of the knowledge pyramid, thereby gaining from the collective wisdom of scientific literature. This study aims to create and validate prediction rules to form the basis for a future patient generated risk prediction tools. These validated tools integrated into electronic and patient interfacing formats like personal health records, mobile and internet-based applications can be instrumental in promoting patient-centric health care and timely risk stratification of preoperative risk.