Impact of an Electronic Medical Record Implementation on Drug Allergy Overrides in a Large Southeastern HMO Setting

Renny Varghese Impact of an Electronic Medical Record Implementation on Drug Allergy Overrides in a Large Southeastern HMO Setting (Under the direction of Russell Toal, Associate Professor) Electronic medical records (EMRs) have become recognized as an important tool for improving patient safety and quality of care. Decision support tools such as alerting functions for patient medication allergies are a key part of reducing the frequency of serious medication problems. Kaiser Permanente Georgia (KPGA) implemented its EMR system in the primary care departments at Kaiser\u27s twelve facilities in the greater metro Atlanta area over a six month period beginning in June 2005 and ending December 2005. The aim of this study is to analyze the impact of the EMR implementation on the number of drug allergy overrides within this large HMO outpatient setting. Research was conducted by comparing the rate of drug allergy overrides during pre and post EMR implementation. The timeline will be six months pre and post implementation. Observing the impact of the incidence rate of drug allergy alerts after the implementation provided insight into the effectiveness of EMRs in reducing contraindicated drug allergies. Results show that the incidence rate of drug allergy overrides per 1,000 filled prescriptions rose by a statistically significant 5.9% (ñ \u3e 0.0002; 95% CI [-1.531, -0.767]) following the implementation. Although results were unexpected, several factors are discussed as to the reason for the increase. Further research is recommended to explore trends in provider behavior, KPGA specific facilities and departments, and in other KP regions and non-KP healthcare settings. INDEX WORDS: electronic medical records, drug allergy overrides, patient safety, medication errors, decision support tools, outpatient setting, primary care, computerized provider order entr

Process Improvement to Reduce Route of Medication Administration Errors in Patients with Enteral Feeding Tubes

Advances in health information management in the form electronic health records, computerized provider order entry systems, and clinical decision support systems and tools have enhanced the productivity, effectiveness, and efficiency of healthcare. However, the cost of these positive effects does come at the expense of other factors. Along with the introduction of Clinical Provider Order Entry (CPOE) systems, organizations have experienced new possibilities for medication errors and risks to patient safety. Factors associated with these errors should be evaluated in detail in order to mitigate the causes of these types of errors and to plan strategies for prevention. Continued research into how to improve the quality of these systems is necessary to promote the usability and acceptance of CPOE systems by prescribers and to continue to make an impact on the frequency of medication errors within health care organizations. Health care organizations must develop strategies to improve the rate of medication errors caused by CPOE systems. Strategies may vary from organization to organization, and depend upon organization-specific resources. Ideally, a plan to improve patient safety and prevent errors related to CPOE systems would include stakeholders such as the clinical team and providers, involve a system that can audit the frequency of errors, and include ongoing education about the problem and the proposed solution. A plan to prevent errors and improve patient safety that is not-dependent upon the intricacies of a specific electronic medical record is ideal. A strategy that can carry-over from one electronic medical record system to the next and that can address the central problem with accuracy, efficiency, and evidence-based research will be proposed

An investigation of healthcare professionals’ experiences of training and using electronic prescribing systems: four literature reviews and two qualitative studies undertaken in the UK hospital context

Electronic prescribing (ePrescribing) is the process of ordering medicines electronically for a patient and has been associated with reduced medication errors and improved patient safety. However, these systems have also been associated with unintended adverse consequences. There is a lack of published research about users’ experiences of these systems in UK hospitals. The aim of this research was therefore to firstly describe the literature pertaining to the recent developments and persisting issues with ePrescribing and clinical decision support systems (CDS) (chapter 2). Two further systematic literature reviews (chapters 3 and 4) were then conducted to understand the unintended consequences of ePrescribing and clinical decision support (CDS) systems across both adult and paediatric patients. These revealed a taxonomy of factors, which have contributed to errors during use of these systems e.g., the screen layout, default settings and inappropriate drug-dosage support. The researcher then conducted a qualitative study (chapters 7-10) to explore users’ experiences of using and being trained to use ePrescribing systems. This study involved conducting semi-structured interviews and observations, which revealed key challenges facing users, including issues with using the ‘Medication List’ and how information was presented. Users experienced benefits and challenges when customising the system, including the screen display; however, the process was sometimes overly complex. Users also described the benefits and challenges associated with different forms of interruptive and passive CDS. Order sets, for instance, encouraged more efficient prescribing, yet users often found them difficult to find within the system. A lack of training resulted in users failing to use all features of the ePrescribing system and left some healthcare staff feeling underprepared for using the system in their role. A further literature review (chapter 5) was then performed to complement emerging themes relating to how users were trained to use ePrescribing systems, which were generated as part of a qualitative study. This review revealed the range of approaches used to train users and the need for further research in this area. The literature review and qualitative study-based findings led to a follow-on study (chapter 10), whereby the researcher conducted semi-structured interviews to examine how users were trained to use ePrescribing systems across four NHS Hospital Trusts. A range of approaches were used to train users; tailored training, using clinically specific scenarios or matching the user’s profession to that of the trainer were preferred over lectures and e-learning may offer an efficient way of training large numbers of staff. However, further research is needed to investigate this and whether alternative approaches such as the use of students as trainers could be useful. This programme of work revealed the importance of human factors and user involvement in the design and ongoing development of ePrescribing systems. Training also played a role in users’ experiences of using the system and hospitals should carefully consider the training approaches used. This thesis provides recommendations gathered from the literature and primary data collection that can help inform organisations, system developers and further research in this area

Implementing Clinical Decision Support Aimed at Reducing Co-Prescribing of Opioids and Benzodiazepines at Adventist HealthCare Maryland

Clinical Decision Support (CDS) leverages computerized toolsets to provide condition specific guidance that aids providers in clinical decision making processes (AHRQ, 2019; AMIA, n.d.; ONC, 2018). Research has shown that applying CDS, interruptive within the electronic health record (EHR) prescribing workflow, can assist providers with avoiding unsafe medication prescribing, such as 1) multiple opioids and 2) opioid-benzodiazepine combinations (Malte et al., 2018; Smith et al., 2019, Price-Haywood et al., 2020; Nelson et al., 2022). In an effort to decrease the co-prescribing rate for 1) multiple opioids and 2) opioid-benzodiazepine combinations, Adventist HealthCare Maryland (AHC) launched a performance improvement project in 2022 that focused on decreasing the health system’s average co-prescribing rate to fall within the 2% to 5% range. To achieve this goal, AHC implemented two (2) EHR-based CDS alerts that were interruptive within the prescribing workflow. Project results showed that AHC was not able to reach the 2% to 5% range, yet the overall co-prescribing rate decreased by 1.56%. The limitations with EHR functionality, differences between the planned design versus actual implementation of the alerts, alerting gaps, and alerting noise were all areas that needed to be improved to determine if the performance target could have been met with the CDS. Some recommended paths forward were to 1) address the design and technical challenges with the alerts, 2) enhance provider-level reporting around opioid and benzodiazepine prescribing to hospital and departmental administration, 3) continue educational efforts around co-prescribing, particularly for the top co-prescribing roles, and 4) explore a consistent role of pharmacy in reviewing prescriptions during the discharge process

Understanding Advice Sharing among Physicians: Towards Trust-Based Clinical Alerts

Safe prescribing of medications relies on drug safety alerts, but up to 96% of such warnings are ignored by physicians. Prior research has proposed improvements to the design of alerts, but with limited increase in adherence. We propose a different perspective: before re-designing alerts, we focus on improving the trust between physicians and computerized advice by examining why physicians trust their medical colleagues. To understand trusted advice among physicians, we conducted three contextual inquiries in a hospital setting (22 participants), and corroborated our findings with a survey (37 participants). Drivers that guide physicians in trusting peer advice include: timeliness of the advice, collaborative language, empathy, level of specialization and medical hierarchy. Based on these findings, we introduce seven design directions for trust-based alerts: endorsement, transparency, team sensing, collaborative, empathic, conflict mitigating and agency laden. Our work contributes to novel alert design strategies to improve the effectiveness of drug safety advice

Electronic Prescribing In Children (EPIC): an evaluation of implementation at a children’s hospital.

Medication errors are common and can cause significant mortality and morbidity. Electronic prescribing (EP), with or without clinical decision support systems (CDSS), is a complex intervention that has been proposed as a solution. US studies indicate that there may be a reduction in medication errors as well as adverse events, but equally new errors may be introduced. There is a paucity of studies assessing the use and impact of EP in the UK hospital setting, especially those involving paediatric patients. The aim of this thesis was to investigate and evaluate the implementation of an EP system at a children's hospital in the UK. The objectives were to assess the effect on prescribing errors, to explore the level of CDSS available and in use within the system, to identify any changes in practice and workflow patterns of healthcare professionals, and to determine the views of patients and users. Mixed qualitative and quantitative methods were used within an evaluation framework (the Cornford framework). The results show an overall reduction in prescribing errors directly as a result of more complete and legible prescriptions after EP. Outpatient errors decreased from 1219/1574 (77.4%) to 33/648 (5.1%), a 72.3% reduction [95% confidence interval (CI) -74.6% to -69.3%]. The number of outpatient visits that were error free increased from 185/883 (21%) to 225/250 (90%), 95% Cl of difference in proportions, 64% to 73.4%. Inpatient errors decreased from 85/1267 (6.7%) to 96/ 2079 (4.6%), 95% CI of difference in proportions, -3.4% to -0.5% There was an increase in discharge prescription errors from 839/1098 (76.4%>) to 1777/2057 (86.4%), 95% CI of difference in proportions, 7.88% to 12.94%. The dosing error rate in all types of prescriptions was lower after EP: 88/3939 (2.2%) vs. 57/4784 (1.2%), 95% CI of difference in proportions, -1.6% to -0.5%, but there was no statistically significant change in severity ratings of dosing errors. New types of errors, such as selection errors, were seen due to EP. Although principles of the medicines use process remained the same, the practical approach to tasks was altered. The system was accepted by users and patients, but there was a desire for further improvements, especially in the level of clinical decision support available to the end user. In conclusion, the EP system was implemented successfully. The benefits in medication safety appear to be the results of effective interaction between system functionality and usability, user acceptance and organisational infrastructure

Factors Associated with Ordering and Completion of Laboratory Monitoring Tests for High-Risk Medications in the Ambulatory Setting: A Dissertation

Since the Institute of Medicine highlighted the devastating impact of medical errors in their seminal report, “To Err is Human” (2000), efforts have been underway to improve patient safety. A portion of medical errors are due to medication errors, and a large portion of these can be attributed to inadequate laboratory monitoring. In this thesis, I attempt to address this small but important corner of this patient safety endeavor. Why are patients not getting their laboratory monitoring tests? Do they fail to complete them or do doctors not order the tests in the first place? Which prescribers and which patients are least likely to do what is needed for testing to happen and what interventions would be most promising? To address these questions, I conducted a systematic review of existing interventions. I then proceeded with three aims: 1) To identify reasons that patients give for missing monitoring tests; 2) To identify patient and provider factors associated with monitoring test ordering; and 3) To identify patient and provider factors associated with completion of ordered testing. To achieve these aims, I worked with patients and data at the Fallon Clinic. For aim 1, I conducted a qualitative analysis of their reasons for missing tests as well as reporting completion and ordering rates. For aims 2 and 3, I used electronic medical record data and conducted a regression with patient and provider characteristics as covariates to identify factors contributing to test ordering and completion. Interviews revealed that patients had few barriers to completion, with forgetting being the most common reason for missing a test. The quantitative studies showed that: older patients with more interactions with the health care system were more likely to have tests ordered and were more likely to complete them; providers who more frequently prescribe a drug were more likely to order testing for it; and drug-test combinations that were particularly dangerous, indicated by a black box warning, were more likely to have appropriate ordering, though for these combinations, primary care providers were less likely to order tests appropriately, and patients were less likely to complete tests. Taken together, my work can inform future interventions in laboratory monitoring and patient safety