E-HEALTH flexible systems to be implemented in a relatively short time, with a focus on training and on integrating systems into the realities of the complexity of clinical work. But this is not sufficient to gain the transformative benefits that the health system needs from ICT. Given that $462 million was allocated to individual e-health records alone in the 2010–11 federal Budget, clarity about what is desired and expected from e-health is becoming an urgent prob- lem.10 The key lies in how ICT in health care is viewed and what performance matches that of their medical colleagues.15,16 As other industries have shown, substitution and role changes are areas in which ICT can lead to the greatest gains.17 In its transformative capacity, ICT is disruptive.18 A “disruptive technology” is a technological innovation that eventually overturns existing practices and transforms the landscape of a particlular industry. Disruptive technologies can change traditional patterns of face with patients.” This is a cry echoed around the wo Much of this frustration is related to intermittent bu for, and the constant changing and updating of, ICT sy one in five participants surveyed at an annual elect record (EMR) trade fair in the US in 2007 had been process of uninstalling an EMR system.7 Not only consuming in itself, but it inevitably requires retraining next upgrade, and can increase scepticism. Risk MJA • Volume 193 Numb people want it to do. At present, the focus is on creating efficiency and safety gains by using computers to automate existing manual processes. For example, computerised ordering systems largely sub- stitute paper orders with electronic orders. This has produced demonstrable and sustained improvements in the speed with which test results are available to clinicians.11,12 Substantially reduced rates of medication errors following automation of the prescribing process are further promising evidence of the benefits of ICT.13,14 While vitally important, these substitutional and evolutionary uses of ICT largely undervalue its revolutionary potential. ICT has the capacity to transform work practices and processes by creating opportunities for health professionals to take on new roles and to provide care in different and innovative ways. Decision support within computerised ordering systems and telemedicine are only two examples. Such systems create opportunities for health professionals other than doctors to order certain tests and to make treatment decisions when experts may not be at hand. Available evidence suggests outcomes do not suffer. For instance, nurses’ performance in answering clinical questions unaided generally falls below that of doctors, but when supported by online evidence systems, their innovative models of health care delivery. As other industries have shown, substitution and role changes are areas in which MJA 2010; 193: 399–400 ICT can lead to the greatest gains. See also page 397 put great e contribute Stable in The Medical Journal of Australia ISSN: 0025- 729X 4 October 2010 193 7 399-400 ©The Medical Journal of Australia 2010 www.mja.com.au E-Health and a rifle to an expert archer and she will probably miss the mark, despite having superior technology in her hands. What happens, then, when you arm the health sector with an array of new information and communication technologies (ICTs) that promise to revolutionise the delivery of care? The evidence is that ICTs have fallen short of the target. The global expansion of ICT is now consuming more than $US3.5 trillion a year. It is a paradise for those selling technology. The chief consumers among health sectors are those in the United Kingdom, the United States, Canada, Australia and other developed countries. Having seen ICT boost productivity and improve service outcomes in other industries, health sectors are keen to reap the benefits for themselves and so have been rapidly increasing investment in the new technologies.1-3 The rhetoric of vendors and governments espouses the financial benefits and improved quality of care that will result. But those on the front-line of hospitals and clinics tell a different story. The existence of entrenched, non-standardised work practices tailored to specific patient populations or organisational systems or cultures means that ICT can fail to meet health profession- als’ specific needs, and high levels of autonomy among staff, and their unique requirements, mean they often remain unconvinced of the potential gains from ICT. Indeed, they are frequently in a position to resist the latest technology on these grounds alone. When technology does not integrate into everyday work practices, things can go wrong.4,5 An Australian survey of 10000 nurses in 20076 revealed that only 40% felt ICT was making their working lives easier. As one participant observed, the installation of a new electronic reporting system at her workplace did not replace the four paper-based systems already in use; it just added to them, largely due to a failure to integrate systems: “After 20 years of technology growth, I now spend more time filling out paper work and far less time face to rld. rsts of funding stems. Nearly ronic medical or was in the is this time- of users in the of errors and inefficiencies increases when organisations are forced to run paper and computer systems in parallel.8,9 Workarounds abound, the potential streamlining of work processes is hard to realise, and staff ffort into maintaining multiple systems. These factors all to suboptimal outcomes. vestments are required that allow organisation-wide, Will information and communication technology disrupt the health system and deliver on its promise? Johanna I Westbrook and Jeffrey Braithwaite ABSTRACT • Investment in information and communication technology (ICT) in the health sector can bring important benefits. To date, the focus has been on automating clinical work practices such as ordering tests and prescriptions, which significantly improves efficiency and safety. • Uptake of ICT has been slow and the results less favourable than anticipated for various reasons, including poor integration of systems into complex clinical work processes, limited training, and the intermittent nature of ICT funding. As a result, many health care organisations have been operating hybrid paper and computer systems that introduce new patient risks, staff frustration, and outcomes below expectation. • The focus must shift from automation of clinical work to innovation; from evolutionary application of ICT to revolutionary uses. Health professionals must embrace ICT as a “disruptive technology” that will produce significant changes in their roles and responsibilities and lead to real health reform with new, H er 7 • 4 October 2010 399 work and enable less highly paid professionals to do progressively E-HEALTH more sophisticated things in less expensive ways.19 Much of the discomfort felt by health professionals about ICT is a response to this potential for disruption. As ICT markedly alters people’s roles and shifts responsibilities,20 it challenges the status quo, and this is seen by many as a threat to the established routines that enable organisa- tions to function, as well as to other valuable practices. Small wonder that ICT is viewed by some health professionals as a danger to the things they cherish. New technologies do not automatically lead to improvements in accompanying work practices, organisational structures and models of care. As the metaphor of the archer illustrates, new technologies have to be matched by new skills and behaviours.21 But making this happen is fraught with difficulty and expense. Most efforts to reform clinical work practices as part of health ICT implementation projects have adopted traditional business process re-engineering22 methods, which use workflow models that are comparatively simple, top-down and linear.23 But this is the wrong fit for the complex, collaborative nature of medical work and for the unique organisational and workforce characteristics of the health sector, in which the various professional groups have high levels of self-sufficiency and are distinctly tribal24 in their behaviour. As a result, potentially signifi- cant changes to work practices are rarely explored, and a disconcert- ingly large number of major health ICT projects have been floundering or failing to deliver the much-touted benefits.25-27 We need fresh approaches that look at how work is conducted in real- world clinical settings — not as specified in linear policy and procedure manuals — and assess how ICT can create opportunities for supporting new care delivery models rather than replicating existing practices. This includes patients having an active role in the process. The time has come to apply ICT to the health system in a way that creates real reform, making quantum gains in the information that clinicians and managers have at their fingertips to help them make better decisions. If used to its full potential, ICT can enhance professional roles and workflows, leading to streamlined systems and improved quality of care. It is time to see ICT in this new light, as a genuine enabler of these outcomes. It is not just a technical fix, requiring more elegant machines and software, according to the technophiles’ arguments. Nor is it mostly a behavioural problem, needing “change management” or professional consulting firms to manage it, as policymakers and managers think. It is both, and clinicians at the coalface need to be integrally involved in design, application and adaptation of their practices and behaviours to make things work in new ways. Until we heed this lesson, we will continue to see ICT as a mere tool for automating existing activities — further entrenching existing problems — rather than as an opportunity for truly reforming health care delivery. Competing interests None identified. Author details Johanna I Westbrook, PhD, FACMI, FACHI, Director, Centre for Health Systems and Safety Research Jeffrey Braithwaite, MBA, PhD, FCHSM, Director, Centre for Clinical Governance Research Australian Institute of Health Innovation, Faculty of Medicine, University of New South Wales, Sydney, NSW. References 1 LeMay R. E-Health: Australia’s $5bn black hole. ZDNet Australia 15 Dec 2008. http://www.zdnet.com.au/news/software/soa/E-Health-Australia-s-5bn-black- hole/0,130061733,339293816,00.htm?feed=pt_deloitte_touche_tohmatsu (accessed Aug 2010). 2 McDougall P. UK imposes deadline to fix sick e-health program. Information- Week Government 28 Apr 2009. http://www.informationweek.com/news/gov- ernment/federal/showArticle.jhtml?articleID=217200451 (accessed Aug 2010). 3 Canada Health Infoway. Annual report 2007–2008. The e-volution of health care: making a difference. Toronto: Canada Health Infoway, 2008. http://www2.info- way-inforoute.ca/Documents/Infoway_Annual_Report_2007-2008_Eng.pdf (accessed Aug 2010). 4 Koppel R, Metlay J, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA 2005; 293: 1197-1203. 5 Han Y, Carcillo J, Venkataraman S, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics 2005; 116: 1506-1512. 6 Australian Nursing Federation. Nurses and information technology. Final report. Canberra: Commonwealth of Australia, 2007. http://www.anf.org.au/it_project/ PDF/IT_Project.pdf (accessed Aug 2010). 7 Conn J. Failure, de-installation of EHRs abound: study. ModernHealthcare.com 30 Oct 2007. http://www.modernhealthcare.com/apps/pbcs.dll/article?AID=/ 20071030/FREE/310300002/0/FRONTPAGE (accessed Aug 2010). 8 Callen J, Paoloni R, Georgiou A, et al. The rate of missed test results in an emergency department: an evaluation using an electronic test order and results viewing system. Methods Inf Med 2010; 49: 37-43. 9 Campbell E, Sittig DF, Ash J, et al. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc 2006; 13: 547-556. 10 Australian Government. Budget 2010–11. Budget at a glance. http:// www.budget.gov.au/2010-11/content/at_a_glance/html/at_a_glance.htm (accessed Aug 2010). 11 Westbrook J, Georgiou A, Dimos A, Germanos T. Computerised pathology test order entry reduces laboratory turnaround times and influences tests ordered by hospital clinicians: a controlled before and after study. J Clin Pathol 2006; 59: 533-536. 12 Westbrook J, Georgiou A, Lam M. Does computerised provider order entry reduce test turnaround times? A before and after study at four hospitals. Stud Health Technol Inform 2009; 150: 527-531. 13 Westbrook J, Lo C, Reckmann M, et al. The effectiveness of an electronic medication management system to reduce prescribing errors in hospitals. In: Proceedings of the 18th National Health Informatics Conference; 2010 Aug 24– 26; Melbourne, Australia. 14 Reckmann M, Westbrook J, Koh Y, et al. Does computerized provider order entry reduce prescribing errors for hospital inpatients? A systematic review. J Am Med Inform Assoc 2009; 16: 613-623. 15 Westbrook J, Coiera E, Gosling AS. Do online information retrieval systems help experienced clinicians answer clinical questions? J Am Med Inform Assoc 2005; 12: 315-321. 16 Westbrook J, Gosling A, Coiera E. The impact of an online evidence system on confidence in decision making in a controlled setting. Med Decis Making 2005; 25: 147-148. 17 Department of Broadband, Communications and the Digital Economy. Aus- tralia’s digital economy: future directions. Final report. Canberra: Common- wealth of Australia, 2009. http://www.dbcde.gov.au/__data/assets/pdf_file/0006/ 117681/DIGITAL_ECONOMY_FUTURE_DIRECTIONS_FINAL_REPORT.pdf (accessed Aug 2010). 18 Coye M, Kell J. How hospitals confront new technology. Health Aff (Millwood) 2006; 25: 163-173. 19 Christensen C, Bohmer R, Kenagy J. Will disruptive innovations cure health care? Harv Bus Rev 2000; 78: 102-112. 20 Georgiou A, Westbrook J, Braithwaite J, et al. When requests become orders — a formative investigation into the impact of computerised physician order entry systems on a pathology service. Int J Med Inform 2007; 76: 583-591. 21 Fonkych K, Taylor R. The state and pattern of health information technology adoption. Santa Monica, Calif: RAND Corporation, 2005. 22 Hammer M. Reengineering work: don’t automate, obliterate. Harv Bus Rev 1990; 68: 104-112. 23 Zuboff S. The emperor’s new information economy. In: Orlikowski W, Walsham G, Jones M, et al, editors. Information technology and changes in organizational work — proceedings of the IFIP WG82 working conference on information technology and changes in organizational work. London: Chapman and Hall, 1996. 24 Braithwaite J, Westbrook M. Rethinking clinical organisational structures: an attitude survey of doctors, nurses and allied health staff in clinical directorates. J Health Serv Res Policy 2005; 10: 10-17. 25 Berger R, Kichak BA. Computerized physician order entry: helpful or harmful? J Med Inform Assoc 2004; 11: 100-103. 26 Beynon-Davies P, Lloyd-Williams M. When health information systems fail. Top Health Inf Manage 1999; 20: 66-79. 27 Collier R. Auditor General blasts eHealth Ontario. CMAJ 2009; 181: E261. 400 MJA • Volume 193 Number 7 • 4 October 2010 Correspondence: J.Westbrook@unsw.edu.au (Received 28 Jun 2010, accepted 11 Aug 2010) ❏ Will information and communication technology disrupt the health system and deliver on its promise? Johanna I Westbrook and Jeffrey Braithwaite H Competing interests Author details References 1 LeMay R. E-Health: Australia’s $5bn black hole. ZDNet Australia 15 Dec 2008. http://www.zdnet.com.au/news/software/soa/E-Health-Australia-s-5bn-black- hole/0,130061733,339293816,00.htm?feed=pt_deloitte_touche_tohmatsu (accessed Aug 2010). 2 McDougall P. UK imposes deadline to fix sick e-health program. InformationWeek Government 28 Apr 2009. http://www.informationweek.com/news/government/federal/showArticle.jhtml?articleID=217200451 (accessed Aug 2010). 3 Canada Health Infoway. Annual report 2007-2008. The e-volution of health care: making a difference. Toronto: Canada Health Infoway, 2008. http://www2.infoway-inforoute.ca/Documents/Infoway_Annual_Report_2007-2008_Eng.pdf (accessed Aug 2010). 4 Koppel R, Metlay J, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA 2005; 293: 1197-1203. 5 Han Y, Carcillo J, Venkataraman S, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics 2005; 116: 1506-1512. 6 Australian Nursing Federation. Nurses and information technology. Final report. Canberra: Commonwealth of Australia, 2007. http://www.anf.org.au/it_project/ PDF/IT_Project.pdf (accessed Aug 2010). 7 Conn J. Failure, de-installation of EHRs abound: study. ModernHealthcare.com 30 Oct 2007. http://www.modernhealthcare.com/apps/pbcs.dll/article?AID=/ 20071030/FREE/310300002/0/FRONTPAGE (accessed Aug 2010). 8 Callen J, Paoloni R, Georgiou A, et al. The rate of missed test results in an emergency department: an evaluation using an electronic test order and results viewing system. Methods Inf Med 2010; 49: 37-43. 9 Campbell E, Sittig DF, Ash J, et al. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc 2006; 13: 547-556. 10 Australian Government. Budget 2010-11. Budget at a glance. http:// www.budget.gov.au/2010-11/content/at_a_glance/html/at_a_glance.htm (accessed Aug 2010). 11 Westbrook J, Georgiou A, Dimos A, Germanos T. Computerised pathology test order entry reduces laboratory turnaround times and influences tests ordered by hospital clinicians: a controlled before and after study. J Clin Pathol 2006; 59: 533-536. 12 Westbrook J, Georgiou A, Lam M. Does computerised provider order entry reduce test turnaround times? A before and after study at four hospitals. Stud Health Technol Inform 2009; 150: 527-531. 13 Westbrook J, Lo C, Reckmann M, et al. The effectiveness of an electronic medication management system to reduce prescribing errors in hospitals. In: Proceedings of the 18th National Health Informatics Conference; 2010 Aug 24- 26; Melbourne, Australia. 14 Reckmann M, Westbrook J, Koh Y, et al. Does computerized provider order entry reduce prescribing errors for hospital inpatients? A systematic review. J Am Med Inform Assoc 2009; 16: 613-623. 15 Westbrook J, Coiera E, Gosling AS. Do online information retrieval systems help experienced clinicians answer clinical questions? J Am Med Inform Assoc 2005; 12: 315-321. 16 Westbrook J, Gosling A, Coiera E. The impact of an online evidence system on confidence in decision making in a controlled setting. Med Decis Making 2005; 25: 147-148. 17 Department of Broadband, Communications and the Digital Economy. Australia’s digital economy: future directions. Final report... 18 Coye M, Kell J. How hospitals confront new technology. Health Aff (Millwood) 2006; 25: 163-173. 19 Christensen C, Bohmer R, Kenagy J. Will disruptive innovations cure health care? Harv Bus Rev 2000; 78: 102-112. 20 Georgiou A, Westbrook J, Braithwaite J, et al. When requests become orders - a formative investigation into the impact of computerised physician order entry systems on a pathology service. Int J Med Inform 2007; 76: 583-591. 21 Fonkych K, Taylor R. The state and pattern of health information technology adoption. Santa Monica, Calif: RAND Corporation, 2005. 22 Hammer M. Reengineering work: don’t automate, obliterate. Harv Bus Rev 1990; 68: 104-112. 23 Zuboff S. The emperor’s new information economy. In: Orlikowski W, Walsham G, Jones M, et al, editors. Information technology... 24 Braithwaite J, Westbrook M. Rethinking clinical organisational structures: an attitude survey of doctors, nurses and allied health staff in clinical directorates. J Health Serv Res Policy 2005; 10: 10-17. 25 Berger R, Kichak BA. Computerized physician order entry: helpful or harmful? J Med Inform Assoc 2004; 11: 100-103. 26 Beynon-Davies P, Lloyd-Williams M. When health information systems fail. Top Health Inf Manage 1999; 20: 66-79. 27 Collier R. Auditor General blasts eHealth Ontario. CMAJ 2009; 181: E261.