Technology-induced errors associated with computerized provider order entry software for older patients.

Background The introduction of new technologies in the prescribing process has seen the emergence of new types of medication errors. Objective To determine the prevalence and consequences of technology-induced prescription errors associated with a computerized provider order entry (CPOE) system in hospitalized older patients. Setting Patients 65 years or older admitted to the Departments of Internal Medicine, General Surgery, and Vascular Surgery of a tertiary hospital. Method Prospective observational 6-month study. Technology-induced errors were classified according to various taxonomies. Interrater reliability was measured. Consequences were assessed by interviewing patients and healthcare providers and classified according to their severity. Main outcome measure Prevalence of technology-induced errors. Results A total of 117 patients were included and 107 technology-induced errors were recorded. The prevalence of these errors was 3.65%. Half of the errors were clinical errors (n = 54) and the majority of these were classified as wrong dose, wrong strength, or wrong formulation. Clinical errors were 9 times more likely to be more severe than procedural errors (14.8 vs 1.9%; OR 9.04, 95% CI 1.09-75.07). Most of the errors did not reach the patient. Almost all errors were related to human-machine interactions due to wrong (n = 61) or partial (n = 41) entries. Conclusion Technology-induced errors are common and intrinsic to the implementation of new technologies such as CPOE. The majority of errors appear to be related to human-machine interactions and are of low severity. Prospective trials should be conducted to analyse in detail the way these errors occur and to establish strategies to solve them and increase patient safety.

Effect of computerized prescriber order entry on pharmacy: experience of one health system.

PURPOSE: Pharmacists' satisfaction with a computerized prescriber order-entry (CPOE) system and the impact of CPOE on pharmacy workflows and order verification were investigated. SUMMARY: A mixed-method study was conducted to evaluate the implementation of a CPOE system in three hospitals of a large Michigan-based health system and early user experience with the system. Surveys of pharmacists before (n = 54) and after (n = 42) CPOE implementation indicated that they held generally positive expectations about CPOE prior to and during system implementation and continued to hold positive views about CPOE after several months of system use. In interviews and focus group discussions, pharmacists reported a number of important CPOE benefits, but they also cited challenges related to CPOE provider alerts, uncertainty about medication timing, and the need to support providers by serving as informal CPOE system trainers. Direct observation of pharmacists before and after CPOE implementation indicated decreases in both the rate of order clarification events (from 0.89 to 0.35 per hour, p < 0.001) and the average time spent per hour clarifying orders (from 4.75 to 2.11 minutes, p = 0.008). CONCLUSION: Several months after CPOE implementation, pharmacists indicated that several aspects of their workload had improved, including the process of medication order clarification, their ability to prioritize work, and their ability to move around within the hospital to respond to demand. However, pharmacists also noted that order ambiguity still existed and that the system needed to be optimized to gain efficiencies and increase clarity.

Drug interaction alert override rates in the Meaningful Use era: no evidence of progress.

BACKGROUND: Interruptive drug interaction alerts may reduce adverse drug events and are required for Stage I Meaningful Use attestation. For the last decade override rates have been very high. Despite their widespread use in commercial EHR systems, previously described interventions to improve alert frequency and acceptance have not been well studied. OBJECTIVES: (1) To measure override rates of inpatient medication alerts within a commercial clinical decision support system, and assess the impact of local customization efforts. (2) To compare override rates between drug-drug interaction and drug-allergy interaction alerts, between attending and resident physicians, and between public and academic hospitals. (3) To measure the correlation between physicians' individual alert quantities and override rates as an indicator of potential alert fatigue. METHODS: We retrospectively analyzed physician responses to drug-drug and drug-allergy interaction alerts, as generated by a common decision support product in a large teaching hospital system. RESULTS: (1) Over four days, 461 different physicians entered 18,354 medication orders, resulting in 2,455 visible alerts; 2,280 alerts (93%) were overridden. (2) The drug-drug alert override rate was 95.1%, statistically higher than the rate for drug-allergy alerts (90.9%) (p < 0.001). There was no significant difference in override rates between attendings and residents, or between hospitals. (3) Physicians saw a mean of 1.3 alerts per day, and the number of alerts per physician was not significantly correlated with override rate (R2 = 0.03, p = 0.41). CONCLUSIONS: Despite intensive efforts to improve a commercial drug interaction alert system and to reduce alerting, override rates remain as high as reported over a decade ago. Alert fatigue does not seem to contribute. The results suggest the need to fundamentally question the premises of drug interaction alert systems.

Impact of a pharmacotherapy alerting system on medication errors.

PURPOSE: An evaluation of a rules-based pharmacotherapy alerting system configured to identify improperly verified new medication orders in an inpatient setting is described. METHODS: A retrospective pre-post cohort study was conducted to assess order-verification alerts and pharmacy interventions at a 900-bed hospital before and after implementation of a commercial pharmacotherapy alerting system. In the preintervention phase of the study, the pharmacotherapy alerting system was used on a limited basis, with clinical pharmacists responding to all alerts and the resulting data used to refine the trigger rules; for the intervention phase, the pharmacotherapy alerting system was programmed to alert only on order-verification errors involving four medications (darbepoetin, filgrastim, fondaparinux, and warfarin). In the event of alerts, a pharmacy response team provided nearly real-time feedback to the order-verification pharmacist, mainly via e-mail or paging. RESULTS: From the preintervention period to the intervention period, there was a 36% decrease in the frequency of order-verification alerts (p = 0.035), and the average number of alerts per day declined from 1.0 to 0.6, suggesting that the pharmacotherapy alerting system and associated oversight mechanisms were effective in enabling pharmacy staff to prevent future errors at the order-verification step before such errors could result in patient harm. The review team spent an average of 10.2 minutes carrying out interventions in response to alerts during the intervention phase. CONCLUSION: Incorporation of a real-time pharmacotherapy alerting system with an oversight response process reduced the number of pharmacotherapy alerts and facilitated interception and prevention of adverse drug events.

[New technologies applied to the medication-dispensing process, error analysis and contributing factors]. / Nuevas tecnologías aplicadas al proceso de dispensación de medicamentos. Análisis de errores y factores contribuyentes.

OBJECTIVE: Calculate error prevalence occurred in different medication-dispensing systems, the stages of occurrence, and contributing factors. METHODOLOGY: Prospective observational study. The staging of the dispensing process were reviewed in five dispensing systems: Stock, Unitary-Dose dispensing systems (UDDS) without Computerized Prescription Order Entry (CPOE), CPOE-UDDS, Automated Dispensing Systems (ADS) without CPOE and CPOE-ADS. Dispensing errors were identified, together with the stages of occurrence of such errors and their contributing factors. RESULTS: 2,181 errors were detected among 54,169 opportunities of error. Error-rate: Stock, 10.7%; no-CPOE-UDDS, 3.7%, CPOE-UDDS, 2.2%, no-CPOE-ADS, 20.7%; CPOE-ADS, 2.9%. Most frequent stage when error occurs: Stock, preparation of order; no-CPOE-UDDS and CPOE-UDDS, filling of the unit dose cart; no-CPOE-ADS and CPOE-ADS, filling of the ADS. Most frequent error: Stock, no-CPOE-ADS and CPOE-ADS, omission; CPOE-UDDS, different amount of drug and no-CPOE-UDDS, extra medication. Contributing factor: Stock, CPOE-ADS and no-CPOE-ADS, stock out/supply problems; CPOE-UDDS, inexperienced personnel and deficient communication system between professionals; no-CPOE-UDDS, deficient communication system between professionals. CONCLUSIONS: Applying new technologies to the dispensing process has increased its safety, particularly, implementation of CPOE has enabled to reduce dispensing errors.

Preventing medication errors with smart infusion technology.

PURPOSE: Processes that pharmacists can use to identify high-risk areas and drugs that require special focus in error-prevention efforts are discussed, with emphasis on the need for i.v. medication error prevention. SUMMARY: Pharmacists can help determine where best to focus medication safety efforts and innovative technology by identifying areas that pose the greatest risk of harm to a patient, such as medications, administration routes, patient care areas, and diagnosis-related groups. Delivery of i.v. medications via infusion devices has traditionally not been a major concern for pharmacists. The introduction of "smart" infusion technology has changed that paradigm by requiring pharmacist involvement in defining minimum and maximum doses for continuous and bolus infusions used within a health care facility. This technology provides a software filter to prevent key-stroke errors in programming infusion devices for delivery of i.v. drugs, as well as a new source of data with which to measure medication errors at the bedside. Implementation of smart infusion technology at Vanderbilt University Medical Center appeared to prevent errors involving heparin. In addition to having an immediate positive impact at the bedside, the technology was relatively easy to implement. CONCLUSION: Smart infusion systems represent an innovative technology that can provide an additional layer of protection at the point of care to help avert i.v. drug errors and prevent patient harm.

Wireless access to a pharmaceutical database: a demonstrator for data driven Wireless Application Protocol (WAP) applications in medical information processing.

BACKGROUND: The Wireless Application Protocol technology implemented in newer mobile phones has built-in facilities for handling much of the information processing needed in clinical work. OBJECTIVES: To test a practical approach we ported a relational database of the Danish pharmaceutical catalogue to Wireless Application Protocol using open source freeware at all steps. METHODS: We used Apache 1.3 web software on a Linux server. Data containing the Danish pharmaceutical catalogue were imported from an ASCII file into a MySQL 3.22.32 database using a Practical Extraction and Report Language script for easy update of the database. Data were distributed in 35 interrelated tables. Each pharmaceutical brand name was given its own card with links to general information about the drug, active substances, contraindications etc. Access was available through 1) browsing therapeutic groups and 2) searching for a brand name. The database interface was programmed in the server-side scripting language PHP3. RESULTS: A free, open source Wireless Application Protocol gateway to a pharmaceutical catalogue was established to allow dial-in access independent of commercial Wireless Application Protocol service providers. The application was tested on the Nokia 7110 and Ericsson R320s cellular phones. CONCLUSIONS: We have demonstrated that Wireless Application Protocol-based access to a dynamic clinical database can be established using open source freeware. The project opens perspectives for a further integration of Wireless Application Protocol phone functions in clinical information processing: Global System for Mobile communication telephony for bilateral communication, asynchronous unilateral communication via e-mail and Short Message Service, built-in calculator, calendar, personal organizer, phone number catalogue and Dictaphone function via answering machine technology. An independent Wireless Application Protocol gateway may be placed within hospital firewalls, which may be an advantage with respect to security. However, if Wireless Application Protocol phones are to become effective tools for physicians, special attention must be paid to the limitations of the devices. Input tools of Wireless Application Protocol phones should be improved, for instance by increased use of speech control.

Be a watchdog.

Review the advances in computerized prescriber order entry and automated storage and administration devices, which effectively reduce medication errors.

Electronic prescriptions: just what the doctor ordered.

Electronic prescription systems address many of the ills in the current paper-based system of getting drug orders from physicians to pharmacies. This new automation application shows tremendous potential for saving time and money and reducing the chance for medication errors. But many hurdles must be overcome before electronic prescribing is widely used.

Selecting a pharmacy computer system for the future.

Major advances are occurring in the field of computer science that have placed us at the threshold of a significant revolution in the management and application of clinical data. These advances will have a profound effect on the practice of pharmacy and are occurring at a time when many hospital pharmacies are deciding whether to enhance or replace their current systems. To best position your department for the future, it is essential that you are knowledgeable of the advances being made, have a vision for how they will affect your practice, and undergo a well-organized and thorough selection process.

Automation and the future practice of pharmacy--changing the focus of pharmacy.

Automation technology offers great potential in pharmacy practice. To realize the full benefits of the potential inherent in automation systems, it is necessary to understand basic concepts of automation and to realize that automation is simply a tool to help achieve the goals of practice. The goal of pharmacy practice is pharmaceutical care. Through using the techniques of reengineering, pharmacies can be redesigned with the help of automation to facilitate the accomplishment of that goal. Essential to achieving that goal is the necessity to change the focus of pharmacy from distribution to pharmaceutical care. Reengineering and automation are the tools to help make that change in focus.