A New Informatics Geography

Abstract

Introduction: Anyone with knowledge of information systems has experienced frustration when it comes to system implementation or use. Unanticipated challenges arise frequently and unanticipated consequences may follow.

Objective: Working from first principles, to understand why information technology (IT) is often challenging, identify which IT endeavors are more likely to succeed, and predict the best role that technology can play in different tasks and settings.

Results: The fundamental purpose of IT is to enhance our ability to undertake tasks, supplying new information that changes what we decide and ultimately what occurs in the world. The value of this information (VOI) can be calculated at different stages of the decision-making process and will vary depending on how technology is used. We can imagine a task space that describes the relative benefits of task completion by humans or computers and that contains specific areas where humans or computers are superior. There is a third area where neither is strong and a final joint workspace where humans and computers working in partnership produce the best results.

Conclusion: By understanding that information has value and that VOI can be quantified, we can make decisions about how best to support the work we do. Evaluation of the expected utility of task completion by humans or computers should allow us to decide whether solutions should depend on technology, humans, or a partnership between the two.

Keywords: Human-computer interaction; communication; expected value; utility; value of information; workaround.

Fig. 1

Today’s informatics geography contains many perils for those who take the journey from system design to routine use. That journey has many parallels with the experiences of a travelling Hobbit in Tolkein’s Lord of the Rings [14]. Many of us spend all our days in the Shire, which is a wonderful place. Here we conceive new information frameworks, architectures, terminologies, and ontologies, intended we are sure for widespread use throughout the land. We never however leave to find out if they are. Everything however, changes when you leave the Shire and cross the River of Implementation, and bring a real information system into actual use. The people you meet bring you unanticipated problems. When you cross the Workaround Mountains you meet folk that are frustratingly expert at doing what they want to do, no matter what your technology tells them to do. The people in the Human-factors Marshes are expert at doing exactly what your technology tells them to do, even when it is the wrong thing to do. If you are really unlucky your journey will take you to the very dark place of Mordor, the home of large-scale IT failures. When you are here, you are always under the watchful, unforgiving, gaze of the Great Eye of Public Opinion. (Figure loosely adapted from [14]).

Fig. 2

For any decision task, there is an information value chain that starts with a user interacting with an information source, and goes through many steps before outcomes are observed in the world. The number of events is typically higher earlier in the chain, and the value of events is higher further down the chain. Combining event frequency (or probability) with event value (or utility) provides the expected utility of each point in the chain. (From Guide to Health Informatics (3rd Ed.) [4])

Fig. 3

The expected utility for a technology intervention may vary at any step in the information value chain. This figure illustrates hypothetical expected utility profiles for four different classes of technology interventions compared to a common non-technological baseline. An intervention (i) may improve the quality of interactions in a health service but provide little additional information compared to current practice (e.g. teleconsultation); (ii) may optimize the quality of information capture (e.g. Electronic Health Record); (iii) may improve the quality and efficiency of clinical processes (e.g. electronic care pathways) or (iv) may intervene directly in the decision-making process to improve clinical outcomes (e.g. decision support systems). Some portions of the profile may dip, and show a net cost rather than benefit (e.g. interacting with EHRs requires more time than normal for doctors). (From Guide to Health Informatics (3rd Ed.) [4])

Fig. 4

A task space can be defined by the expected utility (EU) of executing a given task by a computer (C) and by a human (H). The equivalent benefit line is where EU(C) = EU(H). Above that line there is greater utility in using technology, and below that line the utility is greater if completed by humans.

Fig. 5

The four different quadrants of the task space are better suited for automation, humans alone, for a partnership between the two, or best avoided.

Fig. 6

For a given technology, the expected utility (EU) of completing a given task by human or computer can be plotted over task space. Figure 2 broke the information value chain down into 5 separate tasks (numbered one to five here). Here, the hypothetical profile for current generation electronic health records from Figure 3 is replotted into task space. The curve described by such plots is a function of the given task, the specific technology implementation, the human user, and the context of use. The shape of the plot varies by changing any of these four variables.