The term “clinical decision support” (CDS) has been used for a long time to describe many different mechanisms offering clinical knowledge to clinicians in the clinical setting. But most organizations utilize solutions that deliver what can best be described as “passive support” requiring both user initiation and a lot of extra work for the clinician.
While CDS to date has provided clinicians with access to peer-reviewed clinical literature and treatment guidelines through stand-alone solutions or the Up to Date “button” built into many EHRs, the burden of application (in terms of review of this material and interpretation) to a given patient’s case has been the clinician’s alone. One could argue that the established CDS solutions are really just “clinical decision resources.”
Caseloads, unique patient variables, the pace with which new data is being published combined with the fact that peer-reviewed materials must be often be accessed across a multiple platforms makes putting evidence-based medicine into practice really challenging. And I think that most, if not all, of my colleagues would agree.
But it’s exactly these pain points and challenges that the next generation of “clinical decision support” is addressing. And for that reason, we feel that it’s important that clinicians and their organizations understand what’s available to them now. So with this post, I want to take the time to expand on three key features of a clinical decision support system that we believe truly support and empower the clinician medicine and which enable evidence-based point-of-care clinical decision-making.
This first feature may be obvious, but implementing it is the biggest challenge. We believe a next generation or “advanced” CDS solutions should provide decision support at the point of care, not prior to or after the patient encounter. It must be part of the clinician’s existing clinical workflow in order to be successfully utilized and adopted. While pop-ups and alerts have their value in reminding clinicians to act on a task, I find it disruptive and I quickly dismiss them so that I can focus on the task I was already doing in the first place. If and when I need support, I want to be the one to initiate it, but I also don’t want to have to leave my EHR’s application window to get to it. We’ve been fortunate to work with EHR companies who understand this: when integrated with our select partners, Infera is launched directly from the patient encounter within the EHR.
Second, a CDS solutions should also analyze patient data and provide actionable recommendations for care, which should guide the clinician towards a decision, not further deliberation or additional research. What I expect to see as a clinician end user is high-value content that provides guidance for the question(s) I have at that point in time. This content can be delivered in many formats, but the overall recommendation should be actionable for that particular patient. In short, I should see only the information most relevant to my patient’s condition so that I can decide on the best plan of care based on all available patient data and evidence-based guidelines.
Lastly, a CDS solutions should provide transparency in how it arrives at a recommendation so that the clinician can confidently confirm whether or not to proceed with the recommended actions. Much of the time I want to confirm whether my plan for a patient is aligned with the most current standards of care and evidence-based best practice. If I perceive there to be a gap, I want the tool to also guide me to the information that explains why. So any recommendations delivered must be referenced and provide me with a path to the relevant source articles, calculators, treatment guidelines, etc.
To me as a clinician, and Inferscience, these three features represent the fullest realization of the goals of clinical decision support. They not only make the practice of evidence-based medicine much easier on clinicians which can improve patient care but CDS solutions that provided these features can enable hospitals, health systems and group medical practices to improve their quality metrics, operational efficiency and reimbursement.
