Journal:Comprehending the health informatics spectrum: Grappling with system entropy and advancing quality clinical research

Full article title	Comprehending the health informatics spectrum: Grappling with system entropy and advancing quality clinical research
Journal	Frontiers in Public Health
Author(s)	Bellgard, Matthew I.; Chartres, Nigel; Watts, Gerald F.; Wilton, Steve; Fletcher, Sue; Hunter, Adam; Snelling, Tom
Author affiliation(s)	Murdoch University, Health Informatics Society of Australia, University of Western Australia, Royal Perth Hospital, Perron Institute for Neurological and Translational Science, Princess Margaret Hospital for Children, Charles Darwin University
Primary contact	Email: mbellgard at ccg dot murdoch dot edu dot au
Editors	Stefanov, Rumen
Year published	2017
Volume and issue	5
Page(s)	224
DOI	10.3389/fpubh.2017.00224
ISSN	2296-2565
Distribution license	Creative Commons Attribution 4.0 International
Website	http://journal.frontiersin.org/article/10.3389/fpubh.2017.00224/full
Download	http://journal.frontiersin.org/article/10.3389/fpubh.2017.00224/pdf (PDF)

Introduction

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. 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; (ii) in a systems biology context, clever strategies to combine disparate datasets at the gene-, gene expression-, protein- and protein–protein-interaction levels are essential to unlock underlying molecular mechanisms that affect routine clinical decisions; and (iii) in evidence-based medicine, encoding expert clinical knowledge into decision support systems and data standards for collecting diverse patients' physiological measurements are critical to ensure effective cross jurisdictional data sharing for diseases.

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 healthcare 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.

Key HI challenges within the current environment

Key challenge 1: Defining HI

There are numerous broad definitions of HI. One such definition is that HI is “an evolving scientific discipline that deals with the collection, storage, retrieval, communication and optimal use of health and related data, information and knowledge.” The discipline draws on computational and information science methodologies and technologies to support clinical decision-making to improve health care. Such a broad definition has both advantages and disadvantages. On the one hand, this definition is a “catch all” for the spectrum of ICT in health care and clinical research. On the other, such a broad definition impacts a diverse range of health-related stakeholders from researchers, clinicians, nurses, public, allied health, health professionals, government departments, administrators, and software engineers. This presents a significant challenge of ensuring effective communication and uptake of robust HI.

Key challenge 2: Current health ICT ecosystems

In reality, health ICT ecosystems are largely fragmented. For example, typically within a hospital ICT system environment, there are stand-alone systems, meaning that important health data are also siloed. Depending on the nature of these systems (some of which are as simple as spreadsheets), it is highly likely to contain significant data entry errors, duplications, inconsistencies, and incompleteness. The key challenge here is that fragmented ICT systems impede the ability to monitor chronic diseases, effectively follow-up patients after hospital discharge, prevent avoidable complications (for example, hospital readmissions), or enable longitudinal epidemiological studies. This has a flow of cost burden effect and can inhibit efficiency gains within the health system. In Australia, numerous healthcare business units (such as radiology, pharmacy, pathology, and radio oncology) typically have their own ICT systems that do not interface with each other, and most hospital systems do not interact with external systems, such as general practice clinics or private clinic rooms. Therefore, ownership and management of data become an important barrier between healthcare business units and affect the quality of patient care. Furthermore, when proprietary systems are deployed and hosted by third parties, the ability of the client to exercise their ownership rights over their data requires clarification at the outset of the hosting arrangements.

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In several cases the PubMed ID was missing and was added to make the reference more useful.