Controlled Substance Reconciliation Accuracy Improvement Using Near Real-Time Drug Transaction Capture from Automated Dispensing Cabinets.

BACKGROUND: Accurate accounting of controlled drug transactions by inpatient hospital pharmacies is a requirement in the United States under the Controlled Substances Act. At many hospitals, manual distribution of controlled substances from pharmacies is being replaced by automated dispensing cabinets (ADCs) at the point of care. Despite the promise of improved accountability, a high prevalence (15%) of controlled substance discrepancies between ADC records and anesthesia information management systems (AIMS) has been published, with a similar incidence (15.8%; 95% confidence interval [CI], 15.3% to 16.2%) noted at our institution. Most reconciliation errors are clerical. In this study, we describe a method to capture drug transactions in near real-time from our ADCs, compare them with documentation in our AIMS, and evaluate subsequent improvement in reconciliation accuracy. METHODS: ADC-controlled substance transactions are transmitted to a hospital interface server, parsed, reformatted, and sent to a software script written in Perl. The script extracts the data and writes them to a SQL Server database. Concurrently, controlled drug totals for each patient having care are documented in the AIMS and compared with the balance of the ADC transactions (i.e., vending, transferring, wasting, and returning drug). Every minute, a reconciliation report is available to anesthesia providers over the hospital Intranet from AIMS workstations. The report lists all patients, the current provider, the balance of ADC transactions, the totals from the AIMS, the difference, and whether the case is still ongoing or had concluded. Accuracy and latency of the ADC transaction capture process were assessed via simulation and by comparison with pharmacy database records, maintained by the vendor on a central server located remotely from the hospital network. For assessment of reconciliation accuracy over time, data were collected from our AIMS from January 2012 to June 2013 (Baseline), July 2013 to April 2014 (Next Day Reports), and May 2014 to September 2015 (Near Real-Time Reports) and reconciled against pharmacy records from the central pharmacy database maintained by the vendor. Control chart (batch means) methods were used between successive epochs to determine if improvement had taken place. RESULTS: During simulation, 100% of 10,000 messages, transmitted at a rate of 1295 per minute, were accurately captured and inserted into the database. Latency (transmission time to local database insertion time) was 46.3 ± 0.44 milliseconds (SEM). During acceptance testing, only 1 of 1384 transactions analyzed had a difference between the near real-time process and what was in the central database; this was for a "John Doe" patient whose name had been changed subsequent to data capture. Once a transaction was entered at the ADC workstation, 84.9% (n = 18 bins; 95% CI, 78.4% to 91.3%) of these transactions were available in the database on the AIMS server within 2 minutes. Within 5 minutes, 98.2% (n = 18 bins; 95% CI, 97.2% to 99.3%) were available. Among 145,642 transactions present in the central pharmacy database, only 24 were missing from the local database table (mean = 0.018%; 95% CI, 0.002% to 0.034%). Implementation of near real-time reporting improved the controlled substance reconciliation error rate compared to the previous Next Day Reports epoch, from 8.8% to 5.2% (difference = -3.6%; 95% CI, -4.3% to -2.8%; P < 10). Errors were distributed among staff, with 50% of discrepancies accounted for by 12.4% of providers and 80% accounted for by 28.5% of providers executing transactions during the Near Real-Time Reports epoch. CONCLUSIONS: The near real-time system for the capture of transactional data flowing over the hospital network was highly accurate, reliable, and exhibited acceptable latency. This methodology can be used to implement similar data capture for transactions from their drug ADCs. Reconciliation accuracy improved significantly as a result of implementation. Our approach may be of particular utility at facilities with limited pharmacy resources to audit anesthesia records for controlled substance administration and reconcile them against dispensing records.

Smartphone apps to support hospital prescribing and pharmacology education: a review of current provision.

Junior doctors write the majority of hospital prescriptions but many indicate they feel underprepared to assume this responsibility and around 10% of prescriptions contain errors. Medical smartphone apps are now widely used in clinical practice and present an opportunity to provide support to inexperienced prescribers. This study assesses the contemporary range of smartphone apps with prescribing or related content. Six smartphone app stores were searched for apps aimed at the healthcare professional with drug, pharmacology or prescribing content. Three hundred and six apps were identified. 34% appeared to be for use within the clinical environment in order to aid prescribing, 14% out with the clinical setting and 51% of apps were deemed appropriate for both clinical and non-clinical use. Apps with drug reference material, such as textbooks, manuals or medical apps with drug information were the commonest apps found (51%), followed by apps offering drug or infusion rate dose calculation (26%). 68% of apps charged for download, with a mean price of £14.25 per app and a range of £0.62-101.90. A diverse range of pharmacology-themed apps are available and there is further potential for the development of contemporary apps to improve prescribing performance. Personalized app stores may help universities/healthcare organizations offer high quality apps to students to aid in pharmacology education. Users of prescribing apps must be aware of the lack of information regarding the medical expertise of app developers. This will enable them to make informed choices about the use of such apps in their clinical practice.

Smart infusion technology: a minimum safety standard for intensive care?

There is overwhelming evidence that medication errors present a risk to patients. This risk is highest in the intensive care unit (ICU) setting and even greater when medications are administered via an infusion pump. Standard pumps will not alert for, or prevent, drug calculation, drug unit, button push, or multiple of ten errors when medication delivery data is inputted. However, the literature suggests that smart pumps programmed with hard (unchangeable) limits can significantly reduce drug errors at the point of administration. Staff at St George's Hospital paediatric ICU wanted to implement an infusion pump system that would be immediately effective in reducing medication errors at the point of administration. This article presents an overview of the relevant literature together with clinical examples from the authors' ICU, which demonstrates their experiences with smart pumps. It is the authors' firm belief that smart infusion technology sets a new minimum safety standard for intensive care.

Survey of information technology in Intensive Care Units in Ontario, Canada.

BACKGROUND: The Intensive Care Unit (ICU) is a data-rich environment where information technology (IT) may enhance patient care. We surveyed ICUs in the province of Ontario, Canada, to determine the availability, implementation and variability of information systems. METHODS: A self-administered internet-based survey was completed by ICU directors between May and October 2006. We measured the spectrum of ICU clinical data accessible electronically, the availability of decision support tools, the availability of electronic imaging systems for radiology, the use of electronic order entry and medication administration systems, and the availability of hardware and wireless or mobile systems. We used Fisher's Exact tests to compare IT availability and Classification and Regression Trees (CART) to estimate the optimal cut-point for the number of computers per ICU bed. RESULTS: We obtained responses from 50 hospitals (68.5% of institutions with level 3 ICUs), of which 21 (42%) were university-affiliated. The majority electronically accessed laboratory data and imaging reports (92%) and used picture archiving and communication systems (PACS) (76%). Other computing functions were less prevalent (medication administration records 46%, physician or nursing notes 26%; medication order entry 22%). No association was noted between IT availability and ICU size or university affiliation. Sites used clinical information systems from15 different vendors and 8 different PACS systems were in use. Half of the respondents described the number of computers available as insufficient. Wireless networks and mobile computing systems were used in 23 ICUs (46%). CONCLUSION: Ontario ICUs demontrate a high prevalence of the use of basic information technology systems. However, implementation of the more complex and potentially more beneficial applications is low. The wide variation in vendors utilized may impair information exchange, interoperability and uniform data collection.

Errors prevented by and associated with bar-code medication administration systems.

As expected, bar-code medication administration systems can prevent medication errors. However, health care organizations must be aware of identified failure points in bar coding that may contribute to errors.

Bar-coded medication labeling: setting the stage for bar-code-enabled point-of-care systems.

In February, the U.S. Food and Drug Administration (FDA) issued its final ruling requiring that all drug and biological products sold to hospitals incorporate bar codes on their labels. The ruling smooths the way for widespread adoption of bar-code-enabled point-of-care (BPOC) systems, which are a valuable tool for reducing medication errors. BPOC systems help ensure that the right medications reach the right patient at the right time by allowing bar codes on a patient's ID wristband to be checked against the medication packaging. But BPOC systems will only become truly effective if medications are widely available in unit-dose packaging. Right now only about a third of all medications are available in this form. Although this situation is likely to improve, hospitals wanting to take advantage of BPOC technology soon may need to do some drug repackaging themselves (or have it done by a third party), along with a lot of other groundwork. Widespread BPOC use may still be several years away, but the time to start preparing is now.

Documenting pharmacist interventions on an intranet.

The process of developing and implementing an intranet Web site for clinical intervention documentation is described. An inpatient pharmacy department initiated an organizationwide effort to improve documentation of interventions by pharmacists at its seven hospitals to achieve real-time capture of meaningful benchmarking data. Standardization of intervention types would allow the health system to contrast and compare medication use, process improvement, and patient care initiatives among its hospitals. After completing a needs assessment and reviewing current methodologies, a computerized tracking tool was developed in-house and integrated with the organization's intranet. Representatives from all hospitals agreed on content and functionality requirements for the Web site. The site was completed and activated in February 2002. Before this Web site was established, the most documented intervention types were Renal Adjustment and Clarify Dose, with a daily average of four and three, respectively. After site activation, daily averages for Renal Adjustment remained unchanged, but Clarify Dose is now documented nine times per day. Drug Information and i.v.-to-p.o. intervention types, which previously averaged less than one intervention per day, are now documented an average of four times daily. Approximately 91% of staff pharmacists are using this site. Future plans for this site include enhanced accessibility to the site with wireless personal digital assistants. The design and implementation of an intranet Web site to document pharmacists' interventions doubled the rate of intervention documentation and standardized the intervention types among hospitals in the health system.

Mobile physician order entry.

Because both computerized physician order entry (CPOE) systems and mobile technologies such as handheld devices have the potential to greatly impact the industry's future, IT vendors, hospitals, and clinicians are simply merging them into a logical convergence--"CPOE on a handheld"--with an expectation of full functionality on all platforms: computer workstations, rolling laptops, tablet PCs, and handheld devices. For these trends to succeed together, however, this expectation must be revised to establish a distinct category--mobile physician order entry (MPOE)--that is different from CPOE in form, function, and implementation.

Improving patient safety by identifying side effects from introducing bar coding in medication administration.

OBJECTIVE: In addition to providing new capabilities, the introduction of technology in complex, sociotechnical systems, such as health care and aviation, can have unanticipated side effects on technical, social, and organizational dimensions. To identify potential accidents in the making, the authors looked for side effects from a natural experiment, the implementation of bar code medication administration (BCMA), a technology designed to reduce adverse drug events (ADEs). DESIGN: Cross-sectional observational study of medication passes before (21 hours of observation of 7 nurses at 1 hospital) and after (60 hours of observation of 26 nurses at 3 hospitals) BCMA implementation. MEASUREMENTS: Detailed, handwritten field notes of targeted ethnographic observations of in situ nurse-BCMA interactions were iteratively analyzed using process tracing and five conceptual frameworks. RESULTS: Ethnographic observations distilled into 67 nurse-BCMA interactions were classified into 12 categories. We identified five negative side effects after BCMA implementation: (1) nurses confused by automated removal of medications by BCMA, (2) degraded coordination between nurses and physicians, (3) nurses dropping activities to reduce workload during busy periods, (4) increased prioritization of monitored activities during goal conflicts, and (5) decreased ability to deviate from routine sequences. CONCLUSION: These side effects might create new paths to ADEs. We recommend design revisions, modification of organizational policies, and "best practices" training that could potentially minimize or eliminate these side effects before they contribute to adverse outcomes.

Using personal digital assistants to access drug information.

The use of personal digital assistants (PDAs) to access drug information in a health system is described. Given the widespread use of PDAs at an 872-bed university health system, an opportunity existed to provide current drug information to physicians via these devices. As part of the health system's intranet, extensive online content had been made available through a browser; extension to PDAs was a natural next step. There were two primary requirements: the ability to synchronize information with the database server when a PDA was used and the development of content and applications by using existing staff. Mobile enterprise software was chosen that supports multiple PDA platforms, is easy to use, and does not require programming skills. The software works through customized "channels," or collections of information from a content provider. The customized channel service works over the Internet. Two channels of content were created, an ambulatory care channel and an inpatient care channel. The ambulatory care channel contains a list of preferred ambulatory care agents, poison control information, the locations of outpatient pharmacies, drug information, and safety tips for prescribing. The inpatient channel contains the inpatient formulary, current news and events, information on currrent drug shortages and recalls, pharmacy contact information, and medication safety tips. When a user synchronizes his or her PDA, the software contacts the department's intranet servers and processes the request. The data are compressed and downloaded to the user's PDA. A university health system successfully used PDAs to access drug and other information.

Equipment management guide. Improving the drug distribution process--do you need an automated decentralized pharmacy dispensing system?

In this Equipment Management Guide, we provide guidance to help hospitals determine whether implementing an automated decentralized pharmacy dispensing system (ADPDS) will be an effective way to improve their drug distribution process. We describe the ADPDSs themselves and then discuss factors that hospitals should consider before deciding on such a system. Specifically, we identify several areas that many pharmacies target for improvement and discuss whether and how an ADPDS can help the facility make the desired improvements. We also provide guidance for determining the cost-effectiveness of such a system, as well as for selecting a system that will most appropriately meet the hospital's needs. In the Evaluation that follows this Guide, we present our criteria for evaluating ADPDSs and the results of our testing of three such systems.

Automated decentralized pharmacy dispensing systems.

Automated decentralized pharmacy dispensing systems (ADPDSs) are medication management systems that allow hospitals to store and dispense drugs near the point of use. These systems, which can be compared with the automated teller machines used by banks, provide nurses with ready access to medications while maintaining tight control of drug distribution. In this study, we evaluated three ADPDSs from two suppliers, focusing on whether these systems can store and dispense drugs in a safe, secure, and effective manner. When rating the systems, we considered their applicability to two different implementation schemes: The use of a system with a pharmacy profile interface. This feature broadens the capabilities of the system by allowing more information to be provided at the dispensing cabinet and by providing better integration of the information from this cabinet with the pharmacy's information system. Two of the evaluated systems have this feature and were rated Acceptable. The use of a system without a pharmacy profile interface. We rated all three of the evaluated systems Acceptable for such implementations. To decide which scheme is most appropriate for a particular hospital, the facility will need to determine both how it intends to use the ADPDS and what it hopes to achieve by implementing the system. By performing this type of analysis, the facility can then determine which ADPDS features and capabilities are needed to accomplish its goals. To help facilities make these decisions, we have provided an Equipment Management Guide, "Improving the Drug Distribution Process-Do You Need an Automated Decentralized Pharmacy Dispensing System?," which precedes this Evaluation. In addition, readers unfamiliar with the roles of both the pharmacy and the pharmacist within the hospital can refer to the Primer, "Functions of a Hospital Pharmacy," also published in this issue.