Comprehending the Health Informatics Spectrum: Grappling with System Entropy and Advancing Quality Clinical Research.

Abstract

Clinical research is complex. The knowledge base is information and data rich where value and success depend upon focused, well designed connectivity of systems achieved through stakeholder collaboration. Quality data, information, and knowledge must be utilized in an effective, efficient, and timely manner to affect important clinical decisions and communicate health prevention strategies. In recent decades, it has become apparent that information communication technology (ICT) solutions potentially offer multidimensional opportunities for transforming health care and clinical research. However, it is also recognized that successful utilization of ICT in improving patient care and health outcomes depends on a number of factors such as the effective integration of diverse sources of health data; how and by whom quality data are captured; reproducible methods on how data are interrogated and reanalyzed; robust policies and procedures for data privacy, security and access; usable consumer and clinical user interfaces; effective diverse stakeholder engagement; and navigating the numerous eclectic and non-interoperable legacy proprietary health ICT solutions in hospital and clinic environments (1, 2). This is broadly termed health informatics (HI). We outline three scenarios from across the health spectrum where these issues are exemplified: (i) for a given clinical trial methodology and study design, the nature of how quality data is captured, by whom, how it is aggregated, reused and repurposed is just as critical as the data content itself. This becomes critical with the desire to simultaneously evaluate and optimize the effective and cost-effective use of new medications (3); (ii) in a systems biology context, clever strategies to combine disparate datasets at the gene, gene expression, protein as well as at a protein–protein interaction levels are essential to unlock underlying molecular mechanisms that affect routine clinical decisions (4); and (iii) in evidence-based medicine, encoding expert clinical knowledge into decision support systems and data standards for collecting diverse patient’s physiological measurements are critical to ensure effective cross jurisdictional data sharing for diseases (5). These three examples highlight the potential broad spectrum of the role of ICT in health. Simply stated, at one end of the spectrum, health ICT systems are critical for the routine day-to-day running of hospitals and clinics. These systems are used by various health stakeholders for a diverse range of clinical services and administrative procedures. More recently, there is an increasing demand to reuse and repurpose health data contained within these ICT systems for clinical research and reporting such as compliance, efficiency metrics, funding of health programs, epidemiological studies, and health promotion. On the other end of the spectrum, clinical research embeds ICT and its application involving bioinformaticians, biostatisticians, and analytic workflow environments within research projects. There is a growing demand to embed outputs of this research as evidence to inform health-care policy and improve clinical practice. The significant challenge is how we bridge these two ends of the spectrum. While the overall driver of improved patient outcomes is shared, the demands placed on available ICT systems for data capture, access, and analysis are usually beyond what they were originally designed for. We contend that the field of HI is the important bridge that delivers the promise spanning ICT spectrum in both health care and clinical research. We now explore the challenges in HI that need to be overcome.