Abstract C10: IT-enabled clinical cognitive support for differential diagnosis improvement, treatment planning and medical mistake mitigation
Authors: Melrose John Peter 
Published: March 2017

(a) This poster describes background, purpose, scope, structure and function of the Cloud Healthcare Appliance Real-Time (CHART) solution as a service; which is a conceptual suite of information technology (IT) analytics and middleware software, deployed in “the cloud” (i.e. - an Internet-accessible and professionally managed data center) and accessible by licensed healthcare provider subscriber subject matter experts via a secure portal; for the purpose of designing, developing and deploying automated use cases for cognitive support of medical practice and healthcare delivery (e.g. -- differential diagnosis and treatment planning, medical technology alarm/alert fatigue mitigation, patient course-in-treatment management) with minimal cost and complexity.

(b) The procedure consists of use case automation design (including definition of required complex event monitoring, natural language-based case/evidence acquisition, Bayesian similarity and predictive analysis, Boolean decision rules, process flow including activities and staff/system actors, and key performance indicator-based process monitoring and continuous improvement enablement) using non-programming techniques such as drag-and-drop; development (including process connectivity to existing provider electronic health records a.k.a. EHRs and other Internet-accessible data sources and services using software-defined networking and HIPAA-compliant encryption/de-identification) with minimal IT professional assistance; and deployment via desktop and mobile digital data devices. The included software already is production-proven in other industries worldwide, so the typical high cost and risk associated with software development projects is avoided. The proposed poster will describe the implementation and utilization of the vendor-agnostic CHART; and how the clinical cognitive support it provides will improve accuracy and speed of oncology diagnosis, will mitigate medical mistakes, will facilitate progress from iterative to sequential treatment through integration of the clinical care and medical learning processes (re Bohner RMJ, “Designing Care …,” Harvard Business Press, Boston, 2009, pp. 128-150), and will ensure much-improved economy, efficiency and effectiveness and for healthcare providers.

(c) All available data/information re CHART is available at the web site (www.chartsaas.org) or in the form of presentations (e.g. -- http://bit.ly/28St6MM) and other collateral such as grand rounds solution sheets re central line acquired blood stream infection (CLABSI) and white papers. For example, the benefit of CHART vis a vis the hand-off/sign-out problem (http://1.usa.gov/28UVuAA), is described in our recent Becker's Hospital Review article (http://bit.ly/24k0zov).

(d) The urgent need for IT-enabled clinical cognitive support for differential diagnosis improvement, treatment planning and medical mistake mitigation (and most other healthcare provider challenges) can be rationalized as follows: BECAUSE .25M U.S. patients die every year from medical mistake mitigation (http://bit.ly/1rtW6Sa); AND medical mistakes happen because healthcare complexity creates cognitive overload (http://1.usa.gov/291u3mr); THEREFORE cognitive overload requires cognitive support for healthcare providers (http://1.usa.gov/1JXulDM , in particular the testimony of Tejal Gandhi, MD, MPH and Peter Pronovost, MD, PhD); AND healthcare providers need the cognitive support that only information technology (IT) can provide for information management, decision support and process improvement as provided by the CHART solution as a service. Although CHART is only a concept at this point in time, its structure and function have been realized for the most part by commercial off the shelf (COTS) cloud-based intelligent business process management suites (CiBPMS, re http://gtnr.it/28RSLE1).

Note: This abstract was not presented at the conference.

Citation Format: John Peter Melrose. IT-enabled clinical cognitive support for differential diagnosis improvement, treatment planning and medical mistake mitigation. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr C10.