To decay is system: The challenges of keeping a health information system alive
Introduction
Designing and building information systems for the health care industry has received attention for at least three decades [1]. Despite remarkable technical progress, failures have still been reported when integrating technically sound systems into processes of care [2]. An IMIA IT in Health Care—Socio-technical Approaches Conference in 2004 reflected this theme in its title “To err is system”, alluding to the 2000 Institute of Medicine report “To err is human” [3]. The socio-technical approach of system development and introduction [4], attempts to handle change [5] or user expectations, strains and strain relief systematically [6], beneficial as they may be, cannot prevent significant failures from occurring. The impact of one such failure in 2003 was so deep that it created headlines in national newspapers [7]. But what happens down the road, when a system has been successfully integrated into work processes and has been well accepted by its clinical users, remains to be studied. Will the system remain ‘as is’ for the next month, year, or decade or will it have to be continually altered to suit the changes in the organizational environment? Is it an inherent trait of systems to decay, unless carefully safeguarded against all kinds of influences? This paper points out that seemingly minor environmental changes may cause a system to deteriorate in its usability in non-anticipated ways unless it evolves or its users evolve. The paper also demonstrates that regular upgrades and creative, partially subvert workarounds by flexible end-users can compensate for the process of system deterioration. Other imposed changes can cause catastrophic failures. Mechanisms of decay will be classified according to their origins. Most of these decaying effects will be substantiated by reference to published reports or episodic and systematic observation from the author's work environment. Some speculative ones will likely resonate immediately with professionals in the field.
This is a conceptual paper intended to direct attention to the factors that become effective as soon as a system has gone live. For some of the phenomena of decay a frame of investigation will be suggested. This frame is intended to guide future empirical work in the field of medical or health informatics towards systematic observations that may eventually support or reject the conjectures made in this article. Some suggested concrete methods to prevent decay systematically and to steer systematic evolution need further investigation.
Section snippets
What are origins of system decay?
Reasons of degradation or failure can be organized in a variety of ways. One can set out from data and knowledge required in clinical care and proceed towards the processes of care, key functions in the processes, etc. Or one can locate reasons of decay first in hardware then basic and application software and move on to clinical workflows enhanced by decision support system. Yet another principle of analyzing decay is applied here: In an inside out manner we start with causes that apply to the
How can a phenomenon of decay be investigated systematically?
Generally we can regard any pattern of varying use of some technology as a sociological phenomenon that can be empirically studied by methods from anthropology, behavioral science, organizational psychology, etc. (see [8] for a collection of such approaches). Drawing on such approaches, reasons suspected to effect decay or interventions intended to stop decay can be hypothesized and systematic observation can be organized. This may go as far as to conjecture a cause–effect relation where decay
Systematic investigation of decay—an example
In the following we will use the “Processes of care” sphere to outline systematic observation. With a set of software systems in daily use in a clinical setting several observables suggest themselves as indicators for sub-optimal or decaying function. Looking at the scenarios in Section 3.2, we may trace:
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Number of user ids per person. When suddenly the number of users who apply for more than one id surges, this may optimistically be interpreted as higher acceptance or penetration of IT in the
Different levels of criticality
In the first place a crucial distinction should be made. All of us have seen obvious non-compatibilities like in Section 3.3; they do not go unnoticed and require immediate action. We have seen different kinds of graceful degradation worked around by creative human users like in Sections 3.1 Targeted users, 3.2 Processes of care, 3.4 State-of-the-art medical knowledge. Gradually decaying user trust and satisfaction can be expected when the number of required workarounds increases. Most
Discussion
The analysis so far seems to suggest that decay is a part of the life cycle of information systems. This is in accordance with common experience that well-organized processes will begin to fade after a while because changes in the implicit circumstances for their functioning have gone unnoticed. Far fetched, as this may appear this is also in accordance with the laws of thermodynamics that predict development away from unlikely ordered to more likely less ordered states unless energy is added
Acknowledgments
The author wants to thank the anonymous reviewers of former versions for valuable comments to get the arguments more straight. Valuable comments and hints to pertinent other work were also contributed by Shobha Phansalkar, University of Utah. Thank you also to my Medical Informatics students at Heidelberg-Heilbronn University whose journal club contributions and controversial views on the topic helped to come up with more pertinent examples. Thank you to my medical students who highly
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