Clinical care guidelines have been shown to improve the quality of care, save lives, and prevent unnecessary, costly treatment, procedures and hospitalizations. However, implementing them consistently across a practice requires a level of interconnectedness most providers lack – especially if they do not currently use electronic health record (EHR) integration software.
This article explores the role such solutions can play in elevating patient outcomes.
How Does EHR Integration Support Clinical Care Guidelines?
EHR integration software and decision support enables providers to quickly access, review, and action guidelines without disrupting their daily workflow.
Without such a system, providers struggle with:
- Communication gaps: best practices are not properly communicated or internalized.
- Guideline complexity: The guidelines are constantly being updated and are becoming increasingly complex.
- Inadequate personalization: Guideline directed management is too general and can’t possibly apply to every patient perfectly
- Time constraints: Locating and adhering to guidelines takes up too much time for busy providers.
As a result, we hear regular laments in the literature about how only a minority of patients are getting care based on a specific guideline even though the guidelines are widely available.
Why We Need New Clinical Decision Support Technology
Current clinical decision support tools and solutions offer great information, but it is just one source of information that a clinician considers. Support tools and solutions have no doubt brought a great deal of value to physicians and patients, e.g. online reference tools and mobile applications with automated system message pop-up notifications.
However, busy clinicians like me often find these alerts distracting and lacking full context. I use a number of these tools (MD Calc, UpToDate, etc.) but I have found that they provide me with generalized information about a care guideline, which I must then hunt for and review pertinent details of my patients’ conditions to determine whether and how it applies.
How many of you have ever spent time searching for a critical lab detail for a patient in your EHR, just to determine whether the guideline you searched for in UpToDate applies? Even the built in EHR clinical decision support alerts have for me been irrelevant or rudimentary.
I’d like to utilize all the patient data from my EHR, but it just seems impossible!
So what is the solution? Is there a solution? An unlikely ally in helping clinicians practice evidence based care may be the much-maligned electronic health record (EHR). As many of you may agree, I often feel like I spend twice as much time in my EHR than face to face with my patients. I also admit to resenting my EHR because it is clunky, poorly designed and time consuming. However, there is a gold mine of patient data in there.
For years I wondered, what if there was a tool to capture that data, apply it against evidence based algorithms and give the patient recommendations for care while I am in the exam room? Such a tool would help clinicians practice evidence-based care without having to spend a lot of time reading a long complex guideline and then deciding how to apply it to the patient, all within the workflow of an office visit.
With HCC Assistant, clinicians are in control and, most importantly, receive the most relevant and current care recommendations based on an individual patient’s condition.
My vision for this tool starts with the clinician – with them triggering the decision making process when it is necessary for additional evidence-based guidance and at the same time utilizing the gold mine of information in the EHR.
Some companies are starting to build such tools although they are limited by the reluctance of EHR companies to integrate with them. However, there are forward thinking EHR companies such as Allscripts and Athena which have opened their APIs to allow outside developers to harness the patient data contained in a patient chart to provide specific personalized recommendations. Because these forward thinking companies exist, it allows applications like HCC Assistant the opportunity to integrate with their EHR systems.
Conclusion: The Future of Clinical Decision Support
I have high hopes for the future of clinical decision support – but it will require a few important steps. New protocols such as FHIR and CDS Hooks should help specialized clinical decision support tools like HCC Assistant to realize their full potential. And market forces and government encouragement should nudge all major EHR companies to open up APIs to outside developers.
As I say every day to my colleagues at Inferscience: Such a day could not come soon enough!