Question

Clinical Decision Support is considered a major reason to implement health IT systems/EHRs. Based on randomized controlled studies,the results on the effectiveness of CDS is mixed. What has been your experience with CDS? What is your view on the research to date on CDS? Any suggestions as to how to improve either the technology in terms of functionality or interactivity with providers (e.g., how it is used)? Is this “growing pains” for a new technology—what do you think is a potential path-forward for more effective CDS.

Answer 1

Clinical decision support systems, or CDS, represent a paradigm shift in healthcare today.CDS includes a variety of tools and interventions computerized as well as non- computerized. High-quality clinical decision support systems (CDSS), computerized CDS, are essential to achieve the full benefits of electronic health records and computerized physician order entry. A CDSS can take into account all data available in the EHR making it possible to notice changes outside the scope of the professional and notice changes specific for a certain patient, within normal limits. However, to use of CDSS in practice, it is important to understand the basic requirements of these systems.CDSS can support the use of clinical data science in daily clinical practice. CDSS are used to augment clinicians in their complex decision-making processes. Since their first use in the 1980s, CDSS have seen a rapid evolution. They are now commonly administered through electronic medical records and other computerized clinical workflows, which has been facilitated by increasing global adoption of electronic medical records with advanced capabilities. Despite these advances, there remain unknowns regarding the effect CDSS have on the providers who use them, patient outcomes, and costs.

Clinical decision support systems are today, a reality. More complex , useful systems will be developed in the near future, forging CDSS an essential part of ICU monitoring. However, we need to understand the algorithms embedded in CDSS and to assess them correctly. They will need to first prove their worthiness before becoming indispensable.Healthcare professionals working in the ICU environment are exposed to a large amount of data, both because of the intrinsic complexity of the patients, as well as patients’ close monitoring. There is also an exponential increase in medical knowledge, and thus an exponential difficulty in treating patients accordingly. Even interventions clearly established in the medical literature as beneficial are not universally applied. For example, when the LUNG-SAFE study was conducted, three interventions had proven to improve survival in Acute Respiratory Distress Syndrome (ARDS): low tidal volume <6 ml/kg, prolonged sessions of prone positioning and neuromuscular blocking for 48 hours; provided data showed mean tidal volume of 7.6 ml/kg, use of prone position in 16% of the cases and NMBA in 37.8%. One-thousand eight hundred to 250,000 deaths per year have been estimated to be due to medical errors regarding adverse effects .Derived costs from medical errors reached 19.5 billion in 2008.

Use of computer systems during clinical practice started during the 1960s . Clinical Decision Support Systems are defined as “a process for enhancing health-related decisions and actions with organised clinical knowledge, to improve health care delivery.” In other words, CDSS are health information technology that builds upon the foundation of an electronic health record (EHR) to provide professionals with specific, filtered and organised information.

Recently, several elements make possible the deployment of this concept into significant and practical applications: Digitalisation and increased connection of medical devices with EHR.Possibility of incorporating CDSS both in the EHR and in the medical devices themselves, from monitors to ventilators.Improvement in data processing: new analytical techniques, based on the analysis of big data, and different forms of machine learning.Change from an old working model focused on ICU mortality to a new model focused on the patient’s continued care (including ICU and hospital ward).,

Reducing the rate of medical errors, Reducing unnecessary or duplicate testing,Reducing length of stay and instances of hospital-acquired conditions and by Reducing hospital readmissions can improve either the technology in terms of functionality or interactivity with providers.

Much has been written about alert fatigue. If a CDS system issues numerous alerts that are irrelevant, clinicians will quickly learn to ignore the system-which could mean that an extremely important alert goes unheeded. It is essential that the CDS system be silent until truly ready to provide meaningful support. Its alerts must be accurate, and they must be delivered when they are the most useful. If the system is both exact and timely, alerts will be infrequent-but when they do arrive, they can contribute significantly to reducing errors, inefficiencies, lengths of stay and readmissions.

To make CDS more effective we can make a stratergy. By making a table I'll let you know:

Pillar 1: best knowledge available when needed	Strategic objective A: represent clinical knowledge and CDS interventions in standardized formats (both human and machine-interpretable), so that a variety of knowledge developers can produce this information in a way that knowledge users can readily understand, assess and apply it.
Strategic objective B: collect, organize, and distribute clinical knowledge and CDS interventions in one or more services from which users can readily find the specific material they need and incorporate it into their own information systems and processes.
Pillar 2: high adoption and effective use	Strategic objective C: address policy/legal/financial barriers and create additional support and enablers for widespread CDS adoption and deployment.
Strategic objective D: improve clinical adoption and usage of CDS interventions by helping clinical knowledge and information system producers and implementers design CDS systems that are easy to deploy and use and by identifying and disseminating best practices for CDS deployment.
Pillar 3: continuous improvement of knowledge and CDS methods	Strategic objective E: assess and refine the national experience with CDS by systematically capturing, organizing and examining existing deployments. Share lessons learned and use them to continually enhance implementation best practices.
Strategic objective F: advance care-guiding knowledge by fully leveraging the data available in interoperable EHR to enhance clinical knowledge and improve health management.