CPOE System Design Aspects and Their Qualitative Effect on Usability

Although many studies have discussed the benefits of Computerized Provider Order Entry (CPOE) systems, their configuration can have a great impact on clinicians’ adoption of these systems. Poorly designed CPOE systems can lead to usability problems, users’ dissatisfaction and may disrupt normal flow of clinical activities. This paper reports on a literature review focused on the identification of CPOE medication systems’ design aspects that impact CPOE systems’ usability and create opportunities for medication errors. Our review is based on a systematic literature search in PubMed, EMBASE and Ovid MEDLINE for relevant publications from 1986-2006. We categorized the design aspects extracted from relevant publications into six different groups: 1) timing of alerts, 2) log in/out procedures, 3) pick lists and drop down menus, 4) clues and guidelines, 5) documentation and data entry options, and 6) screen display and layout. Our review shows that the manner in which a CPOE system is configured can have a high impact on ease of system use, task behavior of clinicians in ordering drugs, and medication errors. Characterization of consequences associated with certain CPOE design aspects provides insight into how CPOE system designs can be improved to enhance physicians’ adoption of these systems and their success. Recommendations are provided to enable CPOE system designers to create CPOE systems that are not only more user friendly and efficient but safer

Role of Computerized Physician Order Entry Usability in the Reduction of Prescribing Errors

Some hospitals have implemented computerized physician order entry (CPOE) systems to reduce the medical error rates. However, research in this area has been very limited, especially regarding the impact of CPOE use on the reduction of prescribing errors. Moreover, the past studies have dealt with the overall impact of CPOE on the reduction of broadly termed "medical errors", and they have not specified which medical errors have been reduced by CPOE. Furthermore, the majority of the past research in this field has been either qualitative or has not used robust empirical techniques. This research examined the impacts of usability of CPOE systems on the reduction of doctors' prescribing errors. Methods: One hundred and sixty-six questionnaires were used for quantitative data analyses. Since the data was not normally distributed, partial least square path modelling-as the second generation of multivariate data analyses-was applied to analyze data. Results: It was found that the ease of use of the system and information quality can significantly reduce prescribing errors. Moreover, the user interface consistency and system error prevention have a significant positive impact on the perceived ease of use. More than 50% of the respondents believed that CPOE reduces the likelihood of drug allergy, drug interaction, and drug dosing errors thus improving patient safety. Conclusions: Prescribing errors in terms of drug allergy, drug interaction, and drug dosing errors are reduced if the CPOE is not error-prone and easy to use, if the user interface is consistent, and if it provides quality information to doctors

Comparison of a prototype for indications-based prescribing with 2 commercial prescribing systems

Importance: The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed. Objective: To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication. Design, Setting, and Participants: This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems\u27 outpatient practices. Usability tests were conducted between April and October of 2017. Main Outcomes and Measures: Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors. Results: Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1\u27s system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2\u27s system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P \u3c .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P \u3c .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype. Conclusions and Relevance: Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction

Comparison of a prototype for indications-based prescribing with 2 commercial prescribing systems

Importance: The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed. Objective: To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication. Design, Setting, and Participants: This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems\u27 outpatient practices. Usability tests were conducted between April and October of 2017. Main Outcomes and Measures: Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors. Results: Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1\u27s system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2\u27s system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P \u3c .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P \u3c .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype. Conclusions and Relevance: Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction

Attending unintended transformations of health care infrastructure

Introduction: Western health care is under pressure from growing demands on quality and efficiency. The development and implementation of information technology, IT is a key mean of health care authorities to improve on health care infrastructure. <br><br> Theory and methods: Against a background of theories on human-computer interaction and IT-mediated communication, different empirical studies of IT implementation in health care are analyzed. The outcome is an analytical discernment between different relations of communication and levels of interaction with IT in health care infrastructure. These relations and levels are synthesized into a framework for identifying tensions and potential problems in the mediation of health care with the IT system. These problems are also known as unexpected adverse consequences, UACs, from IT implementation into clinical health care practices. <br><br> Results: This paper develops a conceptual framework for addressing transformations of communication and workflow in health care as a result of implementing IT. <br><br> Conclusion and discussion: The purpose of the conceptual framework is to support the attention to and continuous screening for errors and unintended consequences of IT implementation into health care practices and outcomes

A Systematic Review Of The Types And Causes Of Prescribing Errors Generated From Using Computerized Provider Order Entry Systems in Primary and Secondary Care

Objective To understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems. Materials and Methods We conducted a systematic review of the literature published between January 2004 and June 2015 using three large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Studies that reported qualitative data about the types and causes of these errors were included. A narrative synthesis of all eligible studies was undertaken. Results A total of 1185 publications were identified, of which 34 were included in the review. We identified 8 key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, nonintuitive or inflexible ordering, repeat prescriptions and automated processes, users’ work processes, and clinical decision support systems. Displaying an incomplete list of a patient’s medications on the computer screen often contributed to prescribing errors. Lack of system flexibility resulted in users employing error-prone workarounds, such as the addition of contradictory free-text comments. Users’ misinterpretations of how text was presented in CPOE systems were also linked with the occurrence of prescribing errors. Discussion and Conclusions Human factors design is important to reduce error rates. Drop-down menus should be designed with safeguards to decrease the likelihood of selection errors. Development of more sophisticated clinical decision support, which can perform checks on free-text, may also prevent errors. Further research is needed to ensure that systems minimize error likelihood and meet users’ workflow expectations

COMBINING HUMAN FACTORS AND DATA SCIENCE METHODS TO EVALUATE THE USE OF FREE TEXT COMMUNICATION ORDERS IN ELECTRONIC HEALTH RECORDS

Medication errors are a leading cause of death in the United States. Electronic Health Records (EHR) along with Computerized Provider Order Entry (CPOE) are considered promising ways to reduce these errors. However, EHR systems have not eliminated medication errors. Moreover, in some cases they have facilitated errors due to issues such as poor usability and negative effects on clinical workflows. The use of unexpected free text within a CPOE system can serve as a marker that the system does not adequately support clinical workflow. Prior studies have looked at the use of free text within medication orders, but the inclusion of medication related information in communication for non-medication orders (CNMOs), a type of free text order, has not been adequately studied. This mixed-methods study identified the prevalence, nature and reasons for the inclusion of medication related information in CNMOs using a large sample of CNMOs placed at a mid-Atlantic hospital system in 2017, and via interviews with physicians. The study found that more than 42% of CNMOs contain medication related information. Moreover, the use of CNMOs varied significantly across provider types, hospital locations, patient settings and other factors. The study found 10 themes that might cause providers to adopt such workarounds, including missing functionality and poor usability. The viii study also identified several general challenges in communicating medication information in the EHR, and potential solutions to mitigate these challenges. This dissertation also demonstrates how natural language processing could be used to identify medication related CNMOs

A Fit between Clinical Workflow and Health Care Information Systems: Not waiting for Godot but making the journey

Health care has long suffered from inefficiencies due to the fragmentation of patient care information and the lack of coordination between health professionals [1]. Health care information systems (HISs) have been lauded as tools to remedy such inefficiencies [2, 3]. The primary idea behind the support of their implementation in health care is that these systems support clinical workflow and thereby decrease medical errors [2]. However, their introduction to health care settings have been accompanied by a transformation of the way their primary users, care providers, carry out clinical tasks and establish or maintain work relationships [4]. Studies have shown that these transformations have not always been productive [5, 6]

Electronic Prescribing Usability: Reduction of Mental Workload and Prescribing Errors Among Community Physicians

Background: Medical errors are common in hospitals, and research is always needed to find ways of reducing these. This study attempts to address three gaps in this field. First, the factors leading to the reduction of mental workload and its relationship with the reduction of prescribing errors by improving electronic prescribing (e-prescribing) usability have not been empirically examined before. Second, the past research in the field of e-prescribing usability lacks robust theoretical models. Third, there are no existing studies to examine the direct influences of user interface consistency and error prevention with the reduction of mental workload and prescribing errors. Materials and Methods: A quantitative survey method was used to collect data from 188 community physicians. The partial least squares path modeling technique was applied to analyze the data. Results: Prescribing errors were reduced by improving the information quality, user interface consistency, system ease of use, and mental workload reduction. Mental workload is reduced by ease of use, error prevention, and consistency. No significant relationships between prescribing error reduction with error prevention and also between information quality with mental workload reduction were found. Conclusions: The designers of e-prescribing should improve the error prevention and consistency of the system and make it easy to use if they wish for the system to reduce users’ mental workload. They should also improve the system information quality, ease of use, and consistency if they claim that their system reduces physicians’ prescribing errors. The system should also reduce users’ mental workload to meet this objective

Usability flaws of medication-related alerting functions: A systematic qualitative review

AbstractIntroductionMedication-related alerting functions may include usability flaws that limit their optimal use. A first step on the way to preventing usability flaws is to understand the characteristics of these usability flaws. This systematic qualitative review aims to analyze the type of usability flaws found in medication-related alerting functions.MethodPapers were searched via PubMed, Scopus and Ergonomics Abstracts databases, along with references lists. Paper selection, data extraction and data analysis was performed by two to three Human Factors experts. Meaningful semantic units representing instances of usability flaws were the main data extracted. They were analyzed through qualitative methods: categorization following general usability heuristics and through an inductive process for the flaws specific to medication-related alerting functions.Main resultsFrom the 6380 papers initially identified, 26 met all eligibility criteria. The analysis of the papers identified a total of 168 instances of usability flaws that could be classified into 13 categories of usability flaws representing either violations of general usability principles (i.e. they could be found in any system, e.g. guidance and workload issues) or infractions specific to medication-related alerting functions. The latter refer to issues of low signal-to-noise ratio, incomplete content of alerts, transparency, presentation mode and timing, missing alert features, tasks and control distribution.Main conclusionThe list of 168 instances of usability flaws of medication-related alerting functions provides a source of knowledge for checking the usability of medication-related alerting functions during their design and evaluation process and ultimately constructs evidence-based usability design principles for these functions