Hospital Based Integrated Order Entry System

Implementation of an integrated electronic medical record requires direct physician order entry. This application involves multi-level changes in the whole system of care, from physicians attitudes to interdepartmental relations. This study reports the results of the first round ofa modified Delphi, where a diverse group of individuals were asked to identify the most importantfacilitating and impeding factors associated with implementation ofan order entry application. From a Q-sort of their responses, we identified 20 systemic, behavioral, and attitudinal dimensions perceived to be causal factors in successful implementation. We also explored how these dimensions may influence success by comparing successful with unsuccessful hospitals in terms of the frequency with which these dimensions were differently mentioned by respondents. We found that although available functionality was the most commonly mentioned factor by all participants, hardware availability, physician involvement, administration support, and medical administration involvement were more often mentioned by successful hospitals than by less successful hospitals. These results suggest that these factors were not present in the less successful hospitals. We also found that the frequency of responses within each category varied depending on the institutional role of the individuals responding. Those involved in support tended to see organizational variables as more important than those in clinical positions, whereas clinicians viewed administrative support and involvement of the chief as more important. These findings support the notion that the changes involved in instituting a physician order entry system are system wide and involve individual as well as organizationalfactors. INTRODUCTION The Salt Lake City Information Service Center of the Veteran's Administration (SLC ISC) released their order entry system, Order Entry/Results Reporting 2.5 (OE/RR 2.5), to the field in March, 1993. OE/RR 2.5 integrated several clinical packages (e.g., pharmacy and lab) and provided a single environment where clinicians can enter clinical orders and obtain clinically relevant patient information. Response to the package has varied widely across institutions. A series of studies were planned to identify factors that discriminate successful from non successful implementation of OE/RR 2.5 in order to prepare for the next version. This paper reports on the first study of the series. A fully integrated hospital information system is essential in order to maximize quality management activities, cost control, and clinical decision support. Full acceptance and implementation of an electronic medical record is often viewed as a direct function of physician change as these professionals must make radical changes in their everyday work [1,2,3]. However, the literature on physician change indicates that such change is difficult to achieve and often not long lasting [4]. Yet physician behavior change actually occurs in the context of a larger institutional setting. As work in Total Quality Management has illustrated, individuals are rarely the barriers to change [5]. Rather, it is often system level factors interacting with individuals that cause failures. The purpose of this study is to simultaneously identify both individual and institutional level variables associated with successful adoption by physicians of an integrated order entry system. Specifying the causal variables of a multidetermined event, such as the successful change to on-line order entry, is difficult because people often do not have accurate access to the causes of their behavior [6]. Participants perceptions of a changing system will vary depending on whether the implementation was successful [7], and whether they had direct involvement in the process [8]. In addition, different cognitive and behavioral variables are important at different stages of change [9]. Individuals already committed to a change focus more on issues surrounding actual implementation, whereas those still contemplating the change are more concerned with the pros and cons [10]. Furthermore, each category of individuals has their 0195-4210/94/$5.00 ( 1994 AMIA, Inc. 653 own perspectives. Physicians will have their own unique perception of the value of an electronic medical record, one that is different from those developing the software, and different again from those in charge of implementing and supporting the change. No particular point of view or point in time may provide the complete picture. In this first study, salient dimensions were derived from open-ended responses of people directly involved in implementation attempts of a direct order entry system. An effort was made to have participants represent all of the varied hospital departments that would be involved in such an implementation attempt. Physician representation included administrators, nominated opinion leaders [111, and randomly selected users. The results from this first study will allow the development of a questionnaire based on the identified dimensions in a second study. METHODS Two sets of hospitals were identified based on their relative success at implementing OE1RR 2.5 and their participation as either beta sites or with early implementation. The first set consisted of three hospitals judged to be successful at implementing order entry 2.5 and the second set consisted of three relatively unsuccessful hospitals. Success was defined two ways. The first consisted of nomination by OE/RR 2.5 software engineers working at the SLC ISC, and secondly by the percentage of providers directly using order entry at each institution as reported by participants of the study. The percentage of providers using order entry differed significantly between hospital sets [E(1,37) = 34.97; p. =. 00; Means: success = 74.4%; failure = 15.3%]. A questionnaire was mailed to the following individuals from each institution: 1) Medical Administration Staff, such as chiefs of staff and directors of bed services; 2) Administrators, including the director of the Information Resource Management department (IRM) which provides hardware and software support, Nursing, and Medical Records; 3) Support staff, such as the computer support staff from pharmacy and lab who had been assigned to assist with the implementation of OE/RR, specifically designeted coordinators responsible for training and implementing OE/RR 2.5, and IRM staff; 3) Users, including ward clerks, physicians, and nurses; and 4) Physician opinion leaders nominated by a random selection of 5 physicians from each institution. Over the 6 hospitals, ninety-two individuals received a questionnaire. Fifty seven percent (n = 52) responded. Of those fifty-two, twelve reported that they did not know enough to answer the questions. This left a sample size of forty. Twenty responded from the predefined successful hospitals and twenty responded from the less successful hospitals. The response rate did not differ significantly by institution. The questionnaire consisted of five questions: 1) What proportion of physicians, nurse practitioners, and physician assistants at your institution enter most of their orders directly using OE/RR 2.5? ; 2 ) What proportion nurses directly use OE/RR 2.5? 3) How well do you think OE/RR 2.5 meets the clinical needs of practitioners? This question is answered on a 1 (not at all) to 5 (very well) scale? ; 4) Please list 6 to 10 of the most significant facilitating factors for implementing OE/RR 2.5 at your institution? ; 5) Please list 6 to 10 of the most significant barriers impeding the implementing OEIRR 2.5 at your institution? To identify valid dimensions, the open-ended responses to the above questionnaire were sorted independently into categories by two clinicians (author 1 and author 3) working at the ISC using a modified Q-sort. The sorting was done separately for facilitating factors and for barriers. Neither the number of categories nor their content was specified a priori. One author produced 10 categories and another 14 for both facilitating factors and barriers. Two categories across both sorters had greater than 80% overlap in content and the remaining differences were essentially the inclusion of two categories in one by the third author. After discussion between sorters, the categories were agreed upon. Individual response items were then coded into these categories by two independent raters. Initial agreement between raters was acceptable with 78% of the items coded in the same category. RESULTS Identification of Dimensions Table 1 and 2 list the identified categories in the order of frequency of response. Totals are greater than the number of respondents as some people mentioned items from the same category more than once. These are the categories that reflect the causal factors perceived to be most salient by the respondents. Functionality was an important factor for all respondents. This category had the most items for both facilitating factors and barriers. In addition, many of the categories of the facilitating factors are the inverse of the barriers. In other words, there were only twenty unique categories overall. For example, the presence of supporting