Intelligent clinical forms leads to Smart clinical Decision Support Systems

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Integration of clinical decision support systems (CDSS) with Electronic Health Records can improve healthcare quality significantly especially “intelligent forms and templates”, which helps to provide real time recommendations for treatment plan.

Whether the conditions are acute or chronic, intelligent forms have ability to improve the patient care tremendously. Challenges which are encountered in adopting CDSS are basically integration with clinical workflow and patient wise contextual relevance.

Problems of adopting CDSS originate from five basic reasons, which are:

1. Clinical decision support systems as stand-alone applications that is not able to satisfactorily integrate into the provider’s workflow.

2. Alerts and reminders are mostly interruptive in nature.

3. Clinical decision support interventions are not associated to actions (e.g., the capability to order the medications triggered by the reminder immediately).

4. A provider may or may not trust the clinical decision support system is useful to their decision making at hand.

5. Despite EHRs have progressed in their capability to capture coded clinical information but it may not be sufficient coded data to drive decision support.

To address the hindrances to the judicious use of CDSS, the objectives of the Intelligent Form were many:

  • Develop a clinical documentation tool with a right mix of free text, structured,and coded data entry modalities to improve data entry with minimum stress.
  • Give clinical decision support that is precise, dynamic, context-driven, actionable, and integrated into the workflow of documenting a clinical note.
  • Improve workflow by allowing common actions and decreasing the redundancy of data entry.
  • Develop one Intelligent Form per patient, supply clinical decision and workflow support for any number of acute and chronic conditions that the patient may have.

The intelligent Form is designed to fit into a provider’s workflow before, after, and during the patient’s clinical visit where CDSS have the biggest impact on provider’s behavior. Based on the clinical data coded coupled with evidence based medicine information, a customized recommendation during the patient interaction and documentation can be provided.  So the gap between real world practice challenges and best evidences can be narrowed or filled.

In a recent survey it was found that CDSS helped provider’s performance go up by 40% in predicting diagnosis, managing order systems and improving prescriptions. Hence, the goal is to develop a clinical decision support system with sophisticated content that integrates flawlessly into a provider’s clinical workflow with ease of use.  Such an intelligent system would boost patient care in those clinics and practices that adopt the decision support system in a great way.

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