Understanding physician-level barriers to the use of individualized risk estimates in percutaneous coronary intervention

Abstract

Background The foundation of precision medicine is the ability to tailor therapy based upon the expected risks and benefits of treatment for each individual patient. In a prior study, we implemented a software platform, ePRISM, to execute validated risk-stratification models for patients undergoing percutaneous coronary intervention and found substantial variability in the use of the personalized estimates to tailor care. A better understanding of physicians’ perspectives about the use of individualized risk-estimates is needed to overcome barriers to their adoption. Methods In a qualitative research study, we conducted interviews, in-person or by telephone, with 27 physicians at 8 centers that used ePRISM until thematic saturation occurred. Data were coded using descriptive content analyses. Results Three major themes emerged amongst physicians who did not use ePRISM to support decisions-making: 1) “Experience versus Evidence,” physicians’ preference to rely upon personal experience and subjective assessments rather than objective risk estimates; 2) “Omission of Therapy,” the perception that the use of risk models leads to unacceptable omission of potentially beneficial therapy; and 3) ”Unnecessary Information,” the opinion that information derived from risk models is not needed because physicians’ decision-making is already sound and they already know the information. Conclusions Barriers to the use of risk models in clinical practice include physicians’ perceptions that their experience is sufficient, that models may lead to omission of therapy in patients that may benefit from therapy, and that they already provide good care. Anticipating and overcoming these barriers may improve the adoption of precision medicine.

Physicians' Views on Utilization of an Electronic Health Record–Embedded Calculator to Assess Risk for Venous Thromboembolism among Medical Inpatients: A Qualitative Study

“… 23 A qualitative evaluation of physicians' perspectives on the tool found that physicians did not use ePRISM because they preferred to rely on their personal experience, felt their own decision-making was sound, and worried that the model would lead to patients not being offered a potentially beneficial therapy. 24 Similarly, we found providers often preferred to rely on their clinical judgment, particularly when they distrusted the calculator.…”

Developing and Testing a Personalized, Evidence-Based, Shared Decision-Making Tool for Stent Selection in Percutaneous Coronary Intervention Using a Pre-Post Study Design

“…While physician engagement in SDM is essential for the process to work as intended, prior research has suggested that several physician-level barriers exist to the incorporation of personalized risk models into clinical care. 29 Such findings suggest that formal medical education regarding approaches to risk stratification, shared decision-making and cost effectiveness is needed, to promote evidence-based decision-making and improve the quality and cost-effectiveness of health care in the United States. To honor patients' preferences and for patients to participate in treatment decisions, a transformation in the process of PCI and stent selection is needed.…”

“…Importantly, our finding that stent concordance was 98% for patients who preferred to receive DES and only 53% for patients who preferred to receive BMS suggests that physicians are prone to use DES and may be reluctant to change their decisionmaking when patient preferences differ from their own. 29 This finding warrants further investigation, to better understand and overcome such physician biases, and to better engage physicians in SDM to deliver treatment that is preferred by patients.…”

Palliative treatment of coronary “atherosclerotic cancer” by drug-eluting or bare-metal stents: From oculo-stenotic reflex period to age of precision medicine

“…Recently, the precision medicine is defined as an evidence-based approach that uses innovative tools and biological and data science to customize disease prevention, detection, and treatment, and improve the effectiveness and quality of patient care 28 . The foundation of precision medicine is the ability to tailor therapy based upon the expected risks and benefits of treatment for each individual patient 28, 29, 30. It is in contrast to a “one-size-fits-all” approach, in which disease treatment and prevention strategies are developed for the average person, with less consideration for the differences between individuals.…”