A Human(e) Factor in Clinical Decision Support Systems.

Tim Bezemer,Saskia Haitjema,Mark Ch De Groot,Imo E Hoefer,Annelien L Bredenoord,Teus H Kappen,Enja Blasse,Wouter W Van Solinge,Maarten J Ten Berg

doi:10.2196/11732

Abstract

The overwhelming amount, production speed, multidimensionality, and potential value of data currently available—often simplified and referred to as big data —exceed the limits of understanding of the human brain. At the same time, developments in data analytics and computational power provide the opportunity to obtain new insights and transfer data-provided added value to clinical practice in real time. What is the role of the health care professional in collaboration with the data scientist in the changing landscape of modern care? We discuss how health care professionals should provide expert knowledge in each of the stages of clinical decision support design: data level, algorithm level, and decision support level. Including various ethical considerations, we advocate for health care professionals to responsibly initiate and guide interprofessional teams, including patients, and embrace novel analytic technologies to translate big data into patient benefit driven by human(e) values.

Highlights

Medical data collection and interpretation used to be the domain of health care professionals, the broad availability of health data in unprecedented amounts has significantly and irrevocably changed the landscape of modern care
We show that a well-designed clinical decision support (CDS) system needs expert knowledge of health care professionals in all 3 phases of development: data, algorithm, and decision support (Table 1)
In the era of CDS, we advocate for health care professionals to responsibly initiate and guide interprofessional teams, including patients, and embrace novel analytic technologies to translate big data into patient benefit driven by human(e) values

Summary

Introduction

Medical data collection and interpretation used to be the domain of health care professionals, the broad availability of health data in unprecedented amounts has significantly and irrevocably changed the landscape of modern care. Developments in data analytics and computational power provide the opportunity to obtain new insights and transfer data-provided added value to clinical practice in real time Such systems are called clinical decision support (CDS) and can broadly be defined as “information systems designed to aid in the clinical decision-making process, by integrating different sources of health information such as Electronic Health Records, laboratory test results, etc” [1]. We show that a well-designed CDS system needs expert knowledge of health care professionals in all 3 phases of development: data, algorithm, and decision support (Table 1). In the era of CDS, we advocate for health care professionals to responsibly initiate and guide interprofessional teams, including patients, and embrace novel analytic technologies to translate big data into patient benefit driven by human(e) values. Excellent: these type of data are readily available and can be used for a plethora of purposes

Design flexibility

Findings

Discussion