Categorizing the unintended sociotechnical consequences of computerized provider order entry

https://doi.org/10.1016/j.ijmedinf.2006.05.017Get rights and content

Abstract

Objective

To describe the kinds of unintended consequences related to the implementation of computerized provider order entry (CPOE) in the outpatient setting.

Design

Ethnographic and interview data were collected by an interdisciplinary team over a 7 month period at four clinics.

Measurements

Instances of unintended consequences were categorized using an expanded Diffusion of Innovations theory framework.

Results

The framework was clarified and expanded. There are both desirable and undesirable unintended consequences, and they can be either direct or indirect, but there are also many consequences that are not clearly either desirable or undesirable or may even be both, depending on one's perspective. The undesirable consequences include error and security concerns and issues related to alerts, workflow, ergonomics, interpersonal relations, and reimplementations.

Conclusion

Consequences of implementing and reimplementing clinical systems are complex. The expanded Diffusion of Innovations theory framework is a useful tool for analyzing such consequences.

Introduction

Use of computerized provider order entry (CPOE) is not yet widespread [1], but valuable lessons can be learned from the pioneering organizations that have adopted CPOE. These lessons generally involve sociotechnical issues, defined as issues involving the interplay of organizational and technical components of a system. The more we know about sociotechnical issues, the better prepared we can be for the clinical systems implementation process. For example, there are unintended consequences resulting from CPOE implementation [2], and knowledge about these consequences can potentially help avoid them in the future.

CPOE, in the narrow sense, is defined as a process in which a provider who has ordering authority uses a computer to enter medical orders directly. The process eliminates the need for an intermediary to respond to written or verbal orders given by a provider. An expanded definition of CPOE was used in this study, to include not only this narrow definition, but to also encompass accompanying processes such as decision support, documentation, and order delivery, both to the receiving department and the patient. CPOE is receiving growing worldwide interest because there is some evidence that it increases medical safety by reducing medical errors [3], [4], [5], [6], [7], [8].

Diffusion of Innovations (DOI) theory provided the framework for this study. Diffusion has been defined by Everett Rogers as “the process by which an innovation is communicated through certain channels over time among the members of a social system” and an innovation is defined as “an idea, practice, or objective perceived as new by an individual, a group, or an organization [9, p. 5].” The basic theory has been tested and validated in numerous studies. A great many researchers have focused on the characteristics of innovations. DOI theory outlines five attributes which have been shown in many studies to be important in assessing the diffusion potential of an innovation: relative advantage (is it better than the idea it supercedes?); compatibility (is it consistent with existing values and needs of users?); complexity (is it hard to understand and use?); trialability (can you experiment with it?); and observability (are results visible to others?). Another factor that is important in diffusion is communication, the process of sharing ideas, which can be done through a variety of channels ranging from mass communications to face-to-face interactions. Time is the third element of the diffusion process, and at the individual level people can be categorized as innovators, early adopters, early majority adopters, late majority adopters, or laggards. At the diffusion process level, time is a measure of the rate of adoption or spread of use through a population. The fourth main element of diffusion is the social system, a set of individuals or organizations through which the innovation diffuses [9].

The basic DOI theory elements of innovation attributes, communication, time, and the social system have been studied and validated in over 5000 publications since the first edition of Rogers’ book was published [9, p. xviii]. Diffusion researchers have added to our knowledge of the basic theory and extended and enriched it over the years. Information technology diffusion research was of special interest to Rogers toward the end of his career. In the last edition of the book, the late author stressed that information technology “may be changing the diffusion process in certain fundamental ways such as removing, or at least greatly diminishing, the role of spacial distance in who talks to whom about a new idea” [9, p. xiv].

Fig. 1 depicts the authors’ interpretation of the DOI model, with the addition of “consequences.” Once an innovation has been adopted, there are inevitable consequences, but, according to Rogers, the consequences of adoption are the least studied aspect of the innovation diffusion process. DOI theory outlines a classification of consequences: desirable or undesirable; direct or indirect; anticipated or unanticipated. The term “unintended” connotes consequences that are primarily both unanticipated and undesirable. Rogers has described types of consequences in words, but not graphically.

Studies in the information technology literature are beginning to focus on post-adoption behaviors such as continuance [10]. Researchers have also recognized that complex systems, even if successfully adopted by some definitions, may not be effectively used and that “unanticipated (and sometimes contradictory) changes may result from an implementation that was technologically labeled as successful.” [11, p. 1].

The aim of this study is to describe kinds of unintended consequences related to CPOE in the outpatient setting. Many diffusion studies have been quantitative because they measure the numbers of adopters over time, but Rogers, stating that “the usual survey research methods may be inappropriate for investigating consequences,” [9, p. 470] has recommended qualitative methods for investigating this aspect of diffusion theory. We have selected several qualitative methods because they can be particularly useful for identifying both overt and subtle consequences, and many that users of a system do not know occur. By watching clinicians in the field, ethnographers can discover issues previously unrecognized by the subjects. We used observation and interview techniques for gathering data over a 7-month period of study at four large outpatient clinics. We developed a categorization scheme for consequences based on Rogers’ Diffusion of Innovations model and then we analyzed examples from our research using this scheme.

Section snippets

Prior data collection

Prior research at four sites formed a backdrop for the study described here. All of the organizations studied are using CPOE successfully, but they vary according to type and geographic location. Interviews at each site were held with administrators, information technology related staff, and clinical end user staff at all levels. Ethnographic observation was done in a wide variety of settings within the clinics and hospitals, including physician offices, exam rooms, pharmacies, emergency

Results

Prior to a detailed analysis, the team used the DOI framework for consequences to develop a graphical depiction of a hierarchical model, and then used this model during analysis to help build an understanding of CPOE consequences.

Discussion

This study was limited in its covering only one site, although methodological rigor was maintained in other ways with its being multidisciplinary, multimethod, long term, and part of a multi-site study.

The Diffusion of Innovations model as depicted with the consequences loop seems well suited for describing the iterative nature of CPOE implementations. They are often upgraded, or reimplemented, in either minor or sometimes major respects. It seems that with each upgrade, there are concomitant

Conclusion

The detailed analysis of examples of unintended consequences indicated there were some desirable unintended consequences in addition to undesirable unintended consequences. There were error and security concerns, and issues related to alerts, workflow, ergonomics, interpersonal relations, and reimplementation. Even in a highly successful organization using clinical systems optimally, there are unintended consequences since not all outcomes can be foreseen. As more research is done about

Acknowledgements

This paper is based on one presented at the Second International Conference on Information Technology in Health Care, Portland, OR, USA, September 14, 2004. This work was funded by grant LM06942 from the U.S. National Library of Medicine, National Institutes of Health. Special thanks are extended to P. Zoe Stavri, PhD for her assistance with analysis.

References (14)

There are more references available in the full text version of this article.

Cited by (0)

View full text