A Case-Study of Metoclopramide Prescription Error : A Grim Reminder.

The integration of Computerized Provider Order Entry (CPOE) systems in hospitals has been instrumental in reducing medication errors and enhancing patient safety. This study examines the implications of a software oversight in a CPOE system : Metoclopramide had a concentrated formulation (100 mg) delisted (and then not manufactured) in 2014 due to safety concerns. Despite this, the CPOE system continued to accept prescriptions for this formulation because it was not removed from the medication library by the pharmacist. The objective of our study was to describe this specific prescription error related to an outdated the medication library of the CPOE. We analyzed all metoclopramide prescriptions from 2014, to 2023. Our findings showed that errors involving 100 mg or more dosages were relatively rare, at 2.98 per 1000 prescriptions (34 errors in 11,372 prescriptions). Notably, 47.1% of these errors occurred during on-call shifts, and 68% of these errors led to actual administration. These errors correlated with periods of higher nurse workload. The findings advocate for the integration of dedicated pharmacists into ICU teams to minimize medication errors and enhance patient outcomes, and a proactive medication management in healthcare.

Reducing pediatric asthma hospital length of stay through evidence-based quality improvement and deployment of computerized provider order entry.

Objective: Evaluate the impact of multi-component quality improvement for pediatric asthma care focusing on serial use of an evidence-based clinical pathway via paper order sets, pathway integration into computerized provider order entry (CPOE), use of a clinical respiratory score (CRS) and a discharge checklist. Methods: Outcomes were assessed over three intervention periods and 50 months on: time to beta-agonist and steroid first administration, frequency of readmissions and hospital length of stay. A general linear model estimated mean log(LOS) over time and between study periods. Time to discharge was transformed using the natural logarithm. Results: No improvements in time to first beta-agonist or steroid administration were observed. There was a reduction in 100-day readmissions (p = 0.008): decreasing from 7.4 to 2.1% after introduction of paper order sets and CRS (adjusted p = 0.04); to 3.9% after CPOE implementation (adjusted p = 0.53) and to 2.2% when a discharge checklist was added (adjusted p = 0.01). There was a statistically significant reduction in LOS between study periods (p = 0.015). The geometric mean LOS in hours during study periods 1-4 were: 34.8 (95% CI: 32.2, 37.6), 29.3 (95% CI: 27.5, 31.3), 29.0 (95% CI: 27.0, 31.3) and 23.1 (95% CI: 22.1, 24.2). Pair-wise comparisons between periods were statistically significant (adjusted p ≤ 0.003), except for Periods 2 and 3 (adjusted p = 0.83). Conclusions: Hospital length of stay and 100-day readmissions rate in a predominantly Hispanic, Medicaid patient population were reduced by utilization of an evidence-based best practices asthma management pathway and CRS within CPOE, combined with a checklist to expedite discharge.

A Late Attempt to Involve End Users in the Design of Medication-Related Alerts: Survey Study.

BACKGROUND: When users of electronic medical records (EMRs) are presented with large numbers of irrelevant computerized alerts, they experience alert fatigue, begin to ignore alert information, and override alerts without processing or heeding alert recommendations. Anecdotally, doctors at our study site were dissatisfied with the medication-related alerts being generated, both in terms of volume being experienced and clinical relevance. OBJECTIVE: This study aimed to involve end users in the redesign of medication-related alerts in a hospital EMR, 4 years post implementation. METHODS: This work was undertaken at a private not-for-profit teaching hospital in Sydney, Australia. Since EMR implementation in 2015, the organization elected to implement all medication-related alert types available in the system for prescribers: allergy and intolerance alerts, therapeutic duplication alerts, pregnancy alerts, and drug-drug interaction alerts. The EMR included no medication administration alerts for nurses. To obtain feedback on current alerts and suggestions for redesign, a Web-based survey was distributed to all doctors and nurses at the site via hospital mailing lists. RESULTS: Despite a general dissatisfaction with alerts, very few end users completed the survey. In total, only 3.37% (36/1066) of doctors and 14.5% (60/411) of nurses took part. Approximately 90% (30/33) of doctors who responded held the view that too many alerts were triggered in the EMR. Doctors suggested that most alerts be removed and that alerts be more specific and less sensitive. In contrast, 97% (58/60) of the nurse respondents indicated that they would like to receive medication administration alerts in the EMR. Most nurses indicated that they would like to receive all the alert types available at all severity levels. CONCLUSIONS: Attempting to engage with end users several years post implementation was challenging. Involving users so late in the implementation process may lead to clinicians viewing the provision of feedback to be futile. Seeking user feedback on usefulness, volume, and design of alerts is extremely valuable; however, we suggest this is undertaken early, preferably before system implementation.

Avoiding chemotherapy prescribing errors: Analysis and innovative strategies.

BACKGROUND: At Freiburg University Medical Center, chemotherapy prescriptions are processed via a computerized physician order entry (CPOE) tool and clinically checked by a designated chemotherapy surveillance team. Any error detected is reported instantly, corrected, and prospectively recorded. The objective of the current study was to gain insight into the causes, potential consequences, and future preventability of chemotherapy prescribing errors. METHODS: A detailed analysis of 18,823 consecutive antineoplastic orders placed in 2013 through 2014 was performed. In cooperation with information technology (IT) specialists, the intercepted errors were analyzed for effective future prevention using IT measures. Potential error consequences were determined by case discussions between pharmacists and physicians. RESULTS: Within 24 months, a total of 406 chemotherapy prescribing errors were intercepted that affected 375 (2%) of the total orders. Errors were classified as clinically relevant in 279 of the chemotherapy orders (1.5%). In these cases, reduced therapeutic efficacy (0.44%), the need for increased monitoring (0.48%), prolonged hospital stay (0.55%), and fatality (0.02%) were avoided as potential consequences. The most efficient conventional measures for error prevention comprised checking the order history and patient's medical record, and a detailed knowledge of chemotherapy protocols. Of all the errors analyzed, 61% would be avoided through further software development. The improvements identified are implemented through a validated next-generation CPOE tool. CONCLUSIONS: The upgraded CPOE tool can be shared across other hospitals to raise safety standards and spread potential benefits across a wider patient population. The current analysis also highlighted that approximately 30% to 40% of errors cannot be avoided electronically. Therefore, pharmacovigilance initiatives remain indispensable.

Randomized Clinical Trial of a Clinical Decision Support Tool for Improving the Appropriateness Scores for Ordering Imaging Studies in Primary and Specialty Care Ambulatory Clinics.

OBJECTIVE. The objective of our study was to evaluate whether the use of a clinical decision support (CDS) tool improved the appropriateness scores of orders for advanced imaging in clinical practice. MATERIALS AND METHODS. We used a stepped-wedge, cluster randomized clinical trial to evaluate the effectiveness of a CDS tool in an integrated health care system. Clinicians entered structured indications for each CT and MRI order, and the indications were electronically scored against appropriateness criteria to assign an appropriateness score. We compared the proportion of orders with adjusted appropriateness scores of 7 or greater (on a 1-9 scale) before and after activation of best practice alerts (BPAs) triggered for orders with low or marginal appropriateness scores. Secondary outcomes included the rate per month of orders for advanced imaging and the proportion of orders for which the radiology department requested changes. RESULTS. Between October 2015 and February 2016, 941 clinicians ordered 22,279 CT or MRI studies that met eligibility criteria. Before activation of the BPA, the mean proportion of appropriate orders (adjusted for time and clinic effect) was 77.0% (95% CI, 75.5-78.4%), which increased to 80.1% (95% CI, 78.7-81.5%) after activation (p = 0.001). There was no significant change in the rate of orders per month for advanced imaging. The proportion of order changes requested by the radiology department decreased from 5.7% (95% CI, 5.6-5.9%) before CDS implementation to 5.3% (95% CI, 5.1-5.5%) after CDS implementation (p < 0.001). CONCLUSION. Using an evidence-based CDS tool in clinical practice was associated with a modest but significant improvement in the appropriateness scores of advanced imaging orders.

The Effect of Patient-Specific Drug-Drug Interaction Alerting on the Frequency of Alerts: A Pilot Study.

Background: False-positive drug-drug interaction alerts are frequent and result in alert fatigue that can result in prescribers bypassing important alerts. Development of a method to present patient-appropriate alerts is needed to help restore alert relevance. Objective: The purpose of this study was to assess the potential for patient-specific drug-drug interaction (DDI) alerts to reduce alert burden. Methods: This project was conducted at a tertiary care medical center. Seven of the most frequently encountered DDI alerts were chosen for developing patient-specific, algorithm-based DDI alerts. For each of the DDI pairs, 2 algorithms featuring different values for modifying factors were made. DDI alerts from the 7 drug pairs were collected over 30 days. Outcome measures included the number of DDI alerts generated before and after patient-specific algorithm application to the same patients over the same time period. Results: A total of 14 algorithms were generated, and each was evaluated by comparing the number of alerts generated by our existing, customized clinical decision support (CDS) software and the patient-specific algorithms. The CDS DDI alerting software generated an average of 185.3 alerts per drug pair over the 30-day study period. Patient-specific algorithms reduced the number of alerts resulting from the algorithms by 11.3% to 93.5%. Conclusion and Relevance: Patient-specific DDI alerting is an innovative and effective approach to reduce the number of DDI alerts, may potentially increase the appropriateness of alerts, and may decrease the potential for alert fatigue.

Clinical relevance of alerts from a decision support system, PHARAO, for drug safety assessment in the older adults.

BACKGROUND: PHARAO is a decision support system developed to evaluate the risk for a set of either common or serious side-effects resulting from a combination of pharmacodynamic effects from a patient's medications. The objective of this study was to investigate the validity of the risk scores for the common side-effects generated by PHARAO in older patients. METHODS: Side-effects included were sedation, constipation, orthostatic symptoms, anticholinergic and serotonergic effects. The alerts generated by PHARAO were tested in 745 persons ≥65 years old. Dispensed prescriptions retrieved from the Swedish prescribed drug register were used to generate the pharmacological risk scores of patients' medications. Symptoms possibly related to side-effects were extracted from medical records data. RESULTS: The PHARAO system generated 776 alerts, most often for the risk of anticholinergic symptoms. The total specificity estimates of the PHARAO system were 0.95, 0.89 and 0.78 for high, intermediate and low risk alerts, respectively. The corresponding sensitivity estimates were between 0.12 and 0.37. The negative predictive value was 0.90 and the positive predictive value ranged between 0.20-0.25. CONCLUSIONS: The PHARAO system had a high specificity and negative predictive value to detect symptoms possibly associated with the of patients' medications, while the sensitivity and positive predictive value were low. The PHARAO system has the potential to minimise the risk of over-alerts in combination with a drug-drug interaction alert system, but should be used in connection with a medical evaluation of the patient.

Computerized prescriber order entry and opiate prescription in ambulatory care visits.

OBJECTIVES: To assess the impact of computerized prescriber order entry (CPOE) on opioid-prescribing practices. METHODS: This study analyzed 233,390 office-based medical visits in the 2011-2015 National Ambulatory Medical Care Survey. We used survey-adjusted logistic regression analysis comparing prescription of opiate medications by physicians with and without CPOE. Results were adjusted by covariates describing patient demographics, insurance status, and geography; clinical factors including noncancer pain, cancer, and other chronic medical problems; and physician specialty category and solo practitioner status. RESULTS: Opiates were prescribed in 10.4% of patient visits to physicians with access to CPOE in the sample, compared with 7.5% of visits to physicians without access to CPOE. The adjusted odds of opiate prescription were 1.35 times greater in visits to physicians who had access to CPOE (P = 0.001; 95% CI 1.14-1.58). Among patients visits citing pain (n = 52,978), the adjusted odds of opioid prescription were significantly greater when physicians had access to CPOE (odds ratio 1.28, 95% CI 1.02-1.61; P = 0.035). CONCLUSION: These findings support efforts to review and redesign embedded CPOE tools to improve guideline adherence and reduce problematic opiate prescription.

Electronic medical orders for life-sustaining treatment in New York State: Length of stay, direct costs in an ICU setting.

OBJECTIVE: In the United States, approximately 20% patients die annually during a hospitalization with an intensive care unit (ICU) stay. Each year, critical care costs exceed $82 billion, accounting for 13% of all inpatient hospital costs. Treatment of sepsis is listed as the most expensive condition in US hospitals, costing more than $20 billion annually. Electronic Medical Orders for Life-Sustaining Treatment (eMOLST) is a standardized documentation process used in New York State to convey patients' wishes regarding cardiopulmonary resuscitation and other life-sustaining treatments. No study to date has looked at the effect of eMOLST as an advance care planning tool on ICU and hospital costs using estimates of direct costs. The objective of our study was to investigate whether signing of eMOLST results in any reduction in length of stay and direct costs for a community-based hospital in New York State. METHOD: A retrospective chart review was conducted between July 2016 and July 2017. Primary outcome measures included length of hospital stay, ICU length of stay, total direct costs, and ICU costs. Inclusion criteria were patients ≥65 years of age and admitted into the ICU with a diagnosis of sepsis. An independent samples t test was used to test for significant differences between those who had or had not completed the eMOLST form. RESULT: There were no statistical differences for patients who completed or did not complete the eMOLST form on hospital's total direct cost, ICU cost, total length of hospital stay, and total hours spent in the ICU. SIGNIFICANCE OF RESULTS: Completing an eMOLST form did not have any effect on reducing total direct cost, ICU cost, total length of hospital stay, and total hours spent in the ICU.

Electronic physician notifications to improve guideline-based anticoagulation in atrial fibrillation: a randomized controlled trial.

BACKGROUND: Oral anticoagulants reduce the risk of stroke in patients with atrial fibrillation. However, many patients with atrial fibrillation at elevated stroke risk are not treated with oral anticoagulants. OBJECTIVE: To test whether electronic notifications sent to primary care physicians increase the proportion of ambulatory patients prescribed oral anticoagulants. DESIGN: Randomized controlled trial conducted from February to May 2017 within 18 practices in an academic primary care network. PARTICIPANTS: Primary care physicians (n = 175) and their patients with atrial fibrillation, at elevated stroke risk, and not prescribed oral anticoagulants. INTERVENTION: Patients of each physician were randomized to the notification or usual care arm. Physicians received baseline email notifications and up to three reminders with patient information, educational material and primary care guidelines for anticoagulation management, and surveys in the notification arm. MAIN MEASURES: The primary outcome was the proportion of patients prescribed oral anticoagulants at 3 months in the notification (n = 972) vs. usual care (n = 1364) arms, compared using logistic regression with clustering by physician. Secondary measures included survey-based physician assessment of reasons why patients were not prescribed oral anticoagulants and how primary care physicians might be influenced by the notification. KEY RESULTS: Over 3 months, a small proportion of patients were newly prescribed oral anticoagulants with no significant difference in the notification (3.9%, 95% CI 2.8-5.3%) and usual care (3.2%, 95% CI 2.4-4.2%) arms (p = 0.37). The most common, non-exclusive reasons why patients were not on oral anticoagulants included atrial fibrillation was transient (30%) or paroxysmal (12%), patient/family declined (22%), high bleeding risk (20%), fall risk (19%), and frailty (10%). For 95% of patients, physicians stated they would not change their management after reviewing the alert. CONCLUSIONS: Electronic physician notification did not increase anticoagulation in patients with atrial fibrillation at elevated stroke risk. Primary care physicians did not prescribe anticoagulants because they perceived the bleeding risk was too high or stroke risk was too low. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT02950285.

Reduced Effectiveness of Interruptive Drug-Drug Interaction Alerts after Conversion to a Commercial Electronic Health Record.

BACKGROUND: Drug-drug interaction (DDI) alerts in electronic health records (EHRs) can help prevent adverse drug events, but such alerts are frequently overridden, raising concerns about their clinical usefulness and contribution to alert fatigue. OBJECTIVE: To study the effect of conversion to a commercial EHR on DDI alert and acceptance rates. DESIGN: Two before-and-after studies. PARTICIPANTS: 3277 clinicians who received a DDI alert in the outpatient setting. INTERVENTION: Introduction of a new, commercial EHR and subsequent adjustment of DDI alerting criteria. MAIN MEASURES: Alert burden and proportion of alerts accepted. KEY RESULTS: Overall interruptive DDI alert burden increased by a factor of 6 from the legacy EHR to the commercial EHR. The acceptance rate for the most severe alerts fell from 100 to 8.4%, and from 29.3 to 7.5% for medium severity alerts (P < 0.001). After disabling the least severe alerts, total DDI alert burden fell by 50.5%, and acceptance of Tier 1 alerts rose from 9.1 to 12.7% (P < 0.01). CONCLUSIONS: Changing from a highly tailored DDI alerting system to a more general one as part of an EHR conversion decreased acceptance of DDI alerts and increased alert burden on users. The decrease in acceptance rates cannot be fully explained by differences in the clinical knowledge base, nor can it be fully explained by alert fatigue associated with increased alert burden. Instead, workflow factors probably predominate, including timing of alerts in the prescribing process, lack of differentiation of more and less severe alerts, and features of how users interact with alerts.

Effectiveness of a standardized electronic admission order set for acute exacerbation of chronic obstructive pulmonary disease.

BACKGROUND: Variation in hospital management of patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) may prolong length of stay, increasing the risk of hospital-acquired complications and worsening quality of life. We sought to determine whether an evidence-based computerized AECOPD admission order set could improve quality and reduce length of stay. METHODS: The order set was designed by a provincial COPD working group and implemented voluntarily among three physician groups in a Canadian tertiary-care teaching hospital. The primary outcome was length of stay for patients admitted during order set implementation period, compared to the previous 12 months. Secondary outcomes included length of stay of patients admitted with and without order set after implementation, all-cause readmissions, and emergency department visits. RESULTS: There were 556 admissions prior to and 857 admissions after order set implementation, for which the order set was used in 47%. There was no difference in overall length of stay after implementation (median 6.37 days (95% confidence interval 5.94, 6.81) pre-implementation vs. 6.02 days (95% confidence interval 5.59, 6.46) post-implementation, p = 0.26). In the post-implementation period, order set use was associated with a 1.15-day reduction in length of stay (95% confidence interval - 0.5, - 1.81, p = 0.001) compared to patients admitted without the order set. There was no difference in readmissions. CONCLUSIONS: Use of a computerized guidelines-based admission order set for COPD exacerbations reduced hospital length of stay without increasing readmissions. Interventions to increase order set use could lead to greater improvements in length of stay and quality of care.

Evidence-based usability design principles for medication alerting systems.

BACKGROUND: Usability flaws in medication alerting systems may have a negative impact on clinical use and patient safety. In order to prevent the release of alerting systems that contain such flaws, it is necessary to provide designers and evaluators with evidence-based usability design principles. The objective of the present study was to develop a comprehensive, structured list of evidence-based usability design principles for medication alerting systems. METHODS: Nine sets of design principles for medication alerting systems were analyzed, summarized, and structured. We then matched the summarized principles with a list of usability flaws in order to determine the level of underlying evidence. RESULTS: Fifty-eight principles were summarized from the literature and two additional principles were defined, so that each flaw was matched with a principle. We organized the 60 summarized usability design principles into 6 meta-principles, 38 principles, and 16 sub-principles. Only 15 principles were not matched with a usability flaw. The 6 meta-principles respectively covered the improvement of the signal-to-noise ratio, the support for collaborative working, the fit with a clinician's workflow, the data display, the transparency of the alerting system, and the actionable tools to be provided within an alert. CONCLUSIONS: It is possible to develop an evidence-based, structured, comprehensive list of usability design principles that are specific to medication alerting systems and are illustrated by the corresponding usability flaws. This list represents an improvement over the current literature. Each principle is now associated with the best available evidence of its violation. This knowledge may help to improve the usability of medication alerting systems and, ultimately, decrease the harmful consequences of the systems' usability flaws.

Does Computerized Physician Order Entry Benefit from Dynamic Structured Data Entry? A Quasi-Experimental Study.

BACKGROUND: With advancements in information technology, computerized physician order entry (CPOE) and electronic Medical Records (eMR), have become widely utilized in medical settings. The predominant mode of CPOE in Taiwan is free text entry (FTE). Dynamic structured data entry (DSDE) was introduced more recently, and has increasingly drawn attention from hospitals across Taiwan. This study assesses how DSDE compares to FTE for CPOE. METHODS: A quasi-experimental study was employed to investigate the time-savings, productivity, and efficiency effects of DSDE in an outpatient setting in the gynecological department of a major hospital in Taiwan. Trained female actor patients were employed in trials of both entry methods. Data were submitted to Shapiro-Wilk and Shapiro-Francia tests to assess normality, and then to paired t-tests to assess differences between DSDE and FTE. RESULTS: Relative to FTE, the use of DSDE resulted in an average of 97% time saved and 55% more abundant and detailed content in medical records. In addition, for each clause entry in a medical record, the time saved is 133% for DSDE compared to FTE. CONCLUSION: The results suggest that DSDE is a much more efficient and productive entry method for clinicians in hospital outpatient settings. Upgrading eMR systems to the DSDE format would benefit both patients and clinicians.

Nursing Student Experiences Regarding Safe Use of Electronic Health Records: A Pilot Study of the Safety and Assurance Factors for EHR Resilience Guides.

Previous research has linked improper electronic health record configuration and use with adverse patient events. In response to this problem, the US Office of the National Coordinator for Health Information Technology developed the Safety and Assurance Factors for EHR Resilience guides to evaluate electronic health records for optimal use and safety features. During the course of their education, nursing students are exposed to a variety of clinical practice settings and electronic health records. This descriptive study evaluated 108 undergraduate and 51 graduate nursing students' ratings of electronic health record features and safe practices, as well as what they learned from utilizing the computerized provider order entry and clinician communication Safety and Assurance Factors for EHR Resilience guide checklists. More than 80% of the undergraduate and 70% of the graduate students reported that they experienced user problems with electronic health records in the past. More than 50% of the students felt that electronic health records contribute to adverse patient outcomes. Students reported that many of the features assessed were not fully implemented in their electronic health record. These findings highlight areas where electronic health records can be improved to optimize patient safety. The majority of students reported that utilizing the Safety and Assurance Factors for EHR Resilience guides increased their understanding of electronic health record features.

Auditing The Completeness and Legibility of Computerized Radiological Request Forms.

Certain Saudi healthcare organizations transfer outpatients to medical imaging departments for radiological examinations in a manual process that relies on the use of paper-based forms. With the increased implementation of electronic medical records in Saudi Hospitals, little is known about the completeness and legibility of information captured in  electronic-based medical imaging forms. The purpose of this study is to audit the completeness and legibility of medical imaging paper-based forms in comparison with electronic-based medical imaging forms. As a secondary objective, we also examined the number of errors found on the forms.An observational retrospective cross-sectional study was utilized to audit the completeness and legibility of both paper and electronic forms collected between March 1 and May 15, 2015. The study measured the association among categorical variables using Chi-Square analysis. The results of this investigation show a significant association between form completion and type of record (i.e., paper vs. electronic) where electronic-based systems were found to be more complete than paper-based records. Electrnoic based records were also found to improve form legibility, promote user adherence to complete the forms and minimize entry errors. In conclusion, electronic-based medical imaging forms are more complete and legible than paper based forms. Future studies should evaluate other hospitals and compare both legibility and completeness of electronic-based medical imaging forms and conduct usability evaluation studies with users to explore the impacts of system design on both completeness and legibility of electronic forms, in general, but more specifically, electronic-based medical imaging forms.

Perioperative blood ordering optimization process using information from an anesthesia information management system.

BACKGROUND: As part of ongoing perioperative surgical home implantation process, we applied a previously published algorithm for creation of a maximum surgical blood order schedule (MSBOS) to our operating rooms. We hypothesized that using the MSBOS we could show a reduction in unnecessary preoperative blood testing and associated costs. STUDY DESIGN AND METHODS: Data regarding all surgical cases done at UC Irvine Health's operating rooms from January 1, 2011, to January 1, 2014 were extracted from the anesthesia information management systems (AIMS). After the data were organized into surgical specialties and operative sites, blood order recommendations were generated based on five specific case characteristics of the group. Next, we assessed current ordering practices in comparison to actual blood utilization to identify potential areas of wastage and performed a cost analysis comparing the annual hospital costs from preoperative blood orders if the blood order schedule were to be followed to historical practices. RESULTS: Of the 19,138 patients who were categorized by the MSBOS as needing no blood sample, 2694 (14.0%) had a type and screen (T/S) ordered and 1116 (5.8%) had a type and crossmatch ordered. Of the 6073 procedures where MSBOS recommended only a T/S, 2355 (38.8%) had blood crossmatched. The cost analysis demonstrated an annual reduction in actual hospital costs of $57,335 with the MSBOS compared to historical blood ordering practices. CONCLUSION: We showed that the algorithm for development of a multispecialty blood order schedule is transferable and yielded reductions in preoperative blood product screening at our institution.

Nature and frequency of drug therapy alerts generated by clinical decision support in community pharmacy.

PURPOSE: The purpose of this study is to investigate the nature, frequency, and determinants of drug therapy alerts generated by a clinical decision support system (CDSS) in community pharmacy in order to propose CDSS improvement strategies. METHODS: This is a retrospective analysis of dispensed drugs and drug therapy alerts generated by a CDSS in community pharmacies. RESULTS: Data were extracted from the CDSS of 123 community pharmacies. After taking a 10% random sample of patients with a prescription in the period August 2013-July 2014, 1,672,169 dispensed prescriptions from 81,742 patients were included in the analysis. Of all processed prescriptions, 43% led to one or more drug safety alerts, most frequently drug-drug interaction alerts (15% of all prescriptions), drug-disease interaction alerts (14%), duplicate medication alerts (13%), and dosing alerts (7%). The majority of prescriptions with alerts (80%) were clustered in a minority of patients (16%). The therapeutic drug group of the prescribed drug was the most important determinant of alert generation. Prescriptions for antithrombotic agents accounted for 9.4% of all prescriptions with an alert, beta-blocking agents for 7.5% and angiotensin-converting-enzyme inhibitors for 6.1%. DISCUSSION AND CONCLUSION: The investigated CDSS in Dutch community pharmacy generated one or more drug therapy alerts in nearly half of the processed prescriptions. The majority of alerts were concentrated in a minority of therapeutic drug groups and patients. To decrease the alert burden, CDSS improvements should be directed at the prioritization and integration of drug therapy alerts for these therapeutic groups within patients.

Taxonomy of delays in the implementation of hospital computerized physician order entry and clinical decision support systems for prescribing: a longitudinal qualitative study.

BACKGROUND: Implementation delays are common in health information technology (HIT) projects. In this paper, we sought to explore the reasons for delays in implementing major hospital-based HIT, through studying computerized physician order entry (CPOE) and clinical decision support (CDS) systems for prescribing and to develop a provisional taxonomy of causes of implementation delays. METHODS: We undertook a series of longitudinal, qualitative case studies to investigate the implementation and adoption of CPOE and CDS systems for prescribing in hospitals in the U.K. We used a combination of semi-structured interviews from six case study sites and two whole day expert roundtable discussions to collect data. Interviews were carried out with users, implementers and suppliers of CPOE/CDS systems. We used thematic analysis to examine the results, drawing on perspectives surrounding the biography of artefacts. RESULTS: We identified 15 major factors contributing to delays in implementation of CPOE and CDS systems. These were then categorized in a two-by-two delay classification matrix: one axis distinguishing tactical versus unintended causes of delay, and the second axis illustrating internal i.e., (the adopting hospital) versus external (i.e., suppliers, other hospitals, policymakers) related causes. CONCLUSIONS: Our taxonomy of delays in HIT implementation should enable system developers, implementers and policymakers to better plan and manage future implementations. More detailed planning at the outset, considering long-term strategies, sustained user engagement, and phased implementation approaches appeared to reduce the risks of delays. It should however be noted that whilst some delays are likely to be preventable, other delays cannot be easily avoided and taking steps to minimize these may negatively affect the longer-term use of the system.

Effectiveness and Safety of a Clinical Decision Rule to Reduce Repeat Ionized Calcium Testing: A Pre/Post Test Intervention.

The American Recovery and Reinvestment Act authorizes the Centers for Medicare and Medicaid Services to reimburse hospitals that demonstrate meaningful use of certified electronic health record technology. We sought to demonstrate meaningful use by developing and implementing one clinical decision support rule in the computerized physician order entry system that targets clinician-ordered repeat ionized calcium measurement at the University of Connecticut Health Center. The rule consists of a pop-up computer reminder that is triggered by ordering a second ionized calcium test within 72 hours after an initial normal test, with no clear indication for repeat testing. We implemented the rule on December 14, 2010, and have reviewed all data collected through December 2014. We found that the number of repeat tests decreased from 46% to 14% with no significant increase in the number of serious adverse events. We conclude that computerized reminders can decrease unnecessary repeat testing in the inpatient setting.