Expert clinical rules automate steps in delivering evidence-based care in the electronic health record

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Is there an effective way to rapidly develop, implement, share and maintain Clinical Decision Support (CDS) rules across multiple institutions?

Purpose and Background

There has been much written and discussed about the use of evidence-based clinical decision support improving patient outcomes, but little about how to accomplish this in a complex real world environment where many hospitals may share similar, yet unique information systems and cultures. This paper describes one organization’s framework to facilitate the collaborative, organized, and efficient development, implementation and sharing of automated, evidenced-based, clinical decision support rules across a multi-hospital integrated delivery system. The organization had shared a single EHR vendor, but each site had some unique characteristics that created a desire to have some rules that were universal and required, some that were offered to all institutions and some that were site specific.

Description of Process

The authors describe a well designed but intensive process that required three full time informatics experts at one institution and dedicated multidisciplinary teams at every institution consisting of physicians, nurses, pharmacists, lab personnel, information technologists and administrators. This process had been in place for three years as of publication.

There is a specified process required in order to develop a rule that is strictly adhered to that consists of the following steps:

  • Request for CDS rule generated
  • Oversight group reviews suggestion for appropriateness of evidence base and logistics and then approves / disapproves or offers alternative to achieving goal
  • Redesign of clinical workflow modeled for CDS rules prior to implementation with an evaluation as to potential impact
  • Development of CDS module, educating clinicians and staff regarding workflow and use and piloting at one institution for a minimum of three months
  • If evaluation and feedback from end users was favorable CDS rule either made available as optional or required to other hospitals, if not it was either modified or retired

In addition there were a number of innovative solutions for tracking, storing, and sharing the most up to date versions of CDS rules that included:

  • A web-based CDS rule request process with associated database
  • A web searchable database of available clinical rules that had an index and meta-tagged information regarding intended purpose, how the rule operates within the EHR, workflow issues addressed, altered by the rule and other information.

Outcomes

The authors were able to develop a process that allowed sharing of CDS rules amongst at least nine separate hospital systems that shared a commons EHR that had a software tool that facilitated development. There are now more than one hundred thirty CDS rules in use, all with an evidence-based core. Of these 27 are system wide rules for hospitals, 17 are system wide for outpatient settings, 12 are highly recommended, 70 are general use and only 3 have been withdrawn due to changes in the evidence or workflow issues within the three year timeframe the paper describes.

Conclusion

The authors conclude that it is indeed possible to develop a policy and process to develop evidence-based CDS rules in a timely, effective manner that can be multi-purposed between hospitals and outpatient clinics and offices within an integrated healthcare setting. They argue that this very intensive process actually will save the institution time and resources, both human time and dollars in the long term. They also believe that patient care will be enhanced, although not yet validated within their institutions.

Comments

The authors have accomplished an impressive task, sharing CDS rules, workflow solutions and assessment and development tasks amongst hospital and outpatient settings that are spread across several states. This model of carefully reviewing the request for a rule, piloting in one institution first and detailing out the workflow required ahead of time is a unique process that deserves to be carefully evaluated for emulation.

There are some important caveats however for generalization: There were several dedicated, well trained informatics experts committed to and leading this process from the outset. In all likelihood they were already well known and respected within the cooperating institutions. In addition all the hospitals had the same EHR system, which is a major hurdle to overcome for those systems that have different systems. Imagine the value of a shared coding schema within this system and the advantage that gives them in being able to generalize a CDS rule. It does appear though that this would be a cost effective manner to develop and maintain rules given the ability to rapidly multiply the effect of design and development.

It should be interesting to stay tuned to the health outcome and user satisfaction data that is likely to follow from this descriptive article.