A Quality Improvement Bundle Including Pay for Performance for the Standardization of Order Set Use in Moderate Asthma.

OBJECTIVE: In order to standardize use of our hospital's computerized asthma order set, which was developed based on an asthma clinical practice guideline, for moderately ill children presenting for care of asthma, we developed a quality improvement bundle, including a time-limited pay-for-performance component, for pediatric emergency department and pediatric urgent care faculty members. METHODS: Following baseline measurement, we used a run-in period for education, feedback, and improvement of the asthma order set. Then, faculty members earned 0.1% of salary during each of 10 successive months (evaluation period) in which the asthma order set was used in managing 90% or more of eligible patients. RESULTS: At baseline, the asthma order set was used in managing 60.5% of eligible patients. Order set use rose sharply during the run-in period. During the 10-month evaluation period, use of the asthma order set was significantly above baseline, with a mean of 91.6%; faculty earned pay-for-performance bonuses during 8 of 10 possible months. Following completion of the evaluation period, asthma order set use remained high. CONCLUSIONS: A quality improvement bundle, including a time-limited pay-for-performance component, was associated with a sustained increase in the use of a computerized asthma order set for managing moderately ill asthmatic children.

Use of computer-assisted drug therapy outside the operating room.

PURPOSE OF REVIEW: The number of procedures performed in the out-of-operating room setting under sedation has increased many fold in recent years. Sedation techniques aim to achieve rapid patient turnover through the use of short-acting drugs with minimal residual side-effects (mainly propofol and opioids). Even for common procedures, the practice of sedation delivery varies widely among providers. Computer-based sedation models have the potential to assist sedation providers and offer a more consistent and safer sedation experience for patients. RECENT FINDINGS: Target-controlled infusions using propofol and other short-acting opioids for sedation have shown promising results in terms of increasing patient safety and allowing for more rapid wake-up times. Target-controlled infusion systems with real-time patient monitoring can titrate drug doses automatically to maintain optimal depth of sedation. The best recent example of this is the propofol-based Sedasys sedation system. Sedasys redefined individualized sedation by the addition of an automated clinical parameter that monitors depth of sedation. However, because of poor adoption and cost issues, it has been recently withdrawn by the manufacturer. SUMMARY: Present automated drug delivery systems can assist in the provision of sedation for out-of-operating room procedures but cannot substitute for anesthesia providers. Use of the available technology has the potential to improve patient outcomes, decrease provider workload, and have a long-term economic impact on anesthesia care delivery outside of the operating room.

Reinforcement learning strategies for clinical trials in nonsmall cell lung cancer.

Typical regimens for advanced metastatic stage IIIB/IV nonsmall cell lung cancer (NSCLC) consist of multiple lines of treatment. We present an adaptive reinforcement learning approach to discover optimal individualized treatment regimens from a specially designed clinical trial (a "clinical reinforcement trial") of an experimental treatment for patients with advanced NSCLC who have not been treated previously with systemic therapy. In addition to the complexity of the problem of selecting optimal compounds for first- and second-line treatments based on prognostic factors, another primary goal is to determine the optimal time to initiate second-line therapy, either immediately or delayed after induction therapy, yielding the longest overall survival time. A reinforcement learning method called Q-learning is utilized, which involves learning an optimal regimen from patient data generated from the clinical reinforcement trial. Approximating the Q-function with time-indexed parameters can be achieved by using a modification of support vector regression that can utilize censored data. Within this framework, a simulation study shows that the procedure can extract optimal regimens for two lines of treatment directly from clinical data without prior knowledge of the treatment effect mechanism. In addition, we demonstrate that the design reliably selects the best initial time for second-line therapy while taking into account the heterogeneity of NSCLC across patients.

Effectiveness of interruptive alerts in increasing application functionality utilization: a controlled trial.

Medical applications frequently contain a wide range of functionalities. Users are often unaware of all of the functionalities available. More effective ways of delivering information about available functionalities to the users are needed. We conducted a pseudo-randomized controlled trial to determine whether interruptive alerts will increase utilization of several functionalities by the users of the Pre-Admission Medication List (PAML) Builder application at two academic medical centers. In a log-linear model, alerts increased total utilization of the promoted functionalities per PAML built by 70% compared to the controls at the site level (p<0.0001). At the user level, frequency of utilization of the PAML Builder functionalities by individual users increased by 0.03 for every extra alert shown to the user (p<0.0001). Alerts led to a nearly 2-fold increase in utilization of the promoted functionalities. Interruptive alerts are an effective method of delivering information about application functionalities to users.

Drug safety alert generation and overriding in a large Dutch university medical centre.

PURPOSE: To evaluate numbers and types of drug safety alerts generated and overridden in a large Dutch university medical centre. METHODS: A disguised observation study lasting 25 days on two internal medicine wards evaluating alert generation and handling of alerts. A retrospective analysis was also performed of all drug safety alerts overridden in the hospital using pharmacy log files over 24 months. RESULTS: In the disguised observation study 34% of the orders generated a drug safety alert of which 91% were overridden. The majority of alerts generated (56%) concerned drug-drug interactions (DDIs) and these were overridden more often (98%) than overdoses (89%) or duplicate orders (80%). All drug safety alerts concerning admission medicines were overridden.Retrospective analysis of pharmacy log files for all wards revealed one override per five prescriptions. Of all overrides, DDIs accounted for 59%, overdoses 24% and duplicate orders 17%. DDI alerts of medium-level seriousness were overridden more often (55%) than low-level (22%) or high-level DDIs (19%). In 36% of DDI overrides, it would have been possible to monitor effects by measuring serum levels. The top 20 of overridden DDIs accounted for 76% of all DDI overrides. CONCLUSIONS: Drug safety alerts were generated in one third of orders and were frequently overridden. Duplicate order alerts more often resulted in order cancellation (20%) than did alerts for overdose (11%) or DDIs (2%). DDIs were most frequently overridden. Only a small number of DDIs caused these overrides. Studies on improvement of alert handling should focus on these frequently-overridden DDIs.

Computerized community cholesterol control (4C): meeting the challenge of secondary prevention.

BACKGROUND: Dyslipidemia remains underdiagnosed and undertreated in patients with coronary artery disease. The Computer-based Clinical Decision Support System provides an opportunity t close these gaps. OBJECTIVES: To study the impact of computerized intervention on secondary prevention of CAD. METHODS: The CDSS was programmed to automatically detect patients with CAD and to evaluate the availability of an updated lipoprotein profile and treatment with lipid-lowering drugs. The program produced automatic computer-generated monitoring and treatment recommendations. Adjusted primary clinics were randomly assigned to intervention (n=56) or standard care arms (n=56). Reminders were mailed to the primary medical teams in the intervention arm every 4 months updating them with current lipid levels and recommendations for further treatment. Compliance and lipid levels were monitored. The study group comprised all patients with CAD who were alive at least 3 months after hospitalization. RESULTS: Follow-up was available for 7448 patients (median 19.8 months, range 6-36 months). Overall, 51.7% of patients were adequately screened, and 55.7% of patients were compliant with treatment to lower lipid level. In patients with initial low density lipoprotein >120 mg/dl, a significant decrease in LDL levels was observed in both arms, but was more pronounced in the intervention arm: 121.9 +/- 34.2 vs. 124.3 +/- 34.6 mg/dl (P < 0.02). A significantly lower rate of cardiac rehospitalizations was documented in patients who were adequately treated with lipid-lowering drugs, 37% vs. 40.9% (P < 0.001). CONCLUSIONS: This initial assessment of our data represent a real-world snapshot where physicians and CAD patients often do not adhere to clinical guidelines, presenting a major obstacle to implementing effective secondary prevention. Our automatic computerized reminders system substantially facilitates adherence to guidelines and supports wide-range implementation.

Optimal timing and duration of induction therapy for HIV-1 infection.

The tradeoff between the need to suppress drug-resistant viruses and the problem of treatment toxicity has led to the development of various drug-sparing HIV-1 treatment strategies. Here we use a stochastic simulation model for viral dynamics to investigate how the timing and duration of the induction phase of induction-maintenance therapies might be optimized. Our model suggests that under a variety of biologically plausible conditions, 6-10 mo of induction therapy are needed to achieve durable suppression and maximize the probability of eradicating viruses resistant to the maintenance regimen. For induction regimens of more limited duration, a delayed-induction or -intensification period initiated sometime after the start of maintenance therapy appears to be optimal. The optimal delay length depends on the fitness of resistant viruses and the rate at which target-cell populations recover after therapy is initiated. These observations have implications for both the timing and the kinds of drugs selected for induction-maintenance and therapy-intensification strategies.

Reasons for declining computerized insulin protocol recommendations: application of a framework.

Clinical decision support systems (CDS) can interpret detailed treatment protocols for ICU care providers. In open-loop systems, clinicians can decline protocol recommendations. We capture their reasons for declining as part of ongoing, iterative protocol validation and refinement processes. Even though our protocol was well-accepted by clinicians overall, noncompliance patterns revealed potential protocol improvement targets, and suggested ways to reduce barriers impeding software use. We applied Rita Kukafka and colleagues' (2003) IT implementation framework to identify and categorize reasons documented by ICU nurses when declining recommendations from an insulin-titration protocol. Two methods were used to operationalize the framework: reasons for declining recommendations from actual software use, and a nurse questionnaire. Applying the framework exposed limitations of our data sources, and suggested ways to address those limitations; and facilitated our analyses and interpretations.

Development and pilot testing of the Neuromuscular Blockade Advisory System.

The neuromuscular blocker advisory system (NMBAS) is a computer program developed to provide advisory guidance to anesthesiologists on the timing and dose of rocuronium to paralyze patients during surgery. It is believed that the use of such a system will administer the minimally effective amount of drug, maintaining the patient in a state of paralysis that is useful for surgery yet easily reversible. This will improve patient safety and result in more efficient care. In this paper we present the NMBAS, its basic methodology, and its development though a pilot study. Novel methods of handling neuromuscular response data are presented, including relaxation measurement and the enhanced-train-of-four sensing modality. New methods of handling nonlinearities at the neuromuscular junction to allow application of adaptive control techniques are presented. A novel form of modelling combining model swapping and RLSE adaptation to accommodate the patient variation seen with NMB drugs is introduced. A pilot study testing the NMBAS was undergone to prepare the NMBAS for application in a full clinical trial, in which patients undergoing prostate brachytherapy surgeries using rocuronium for intubation were admitted.

What Features of Smartphone Medication Applications Are Patients with Chronic Diseases and Caregivers Looking for?

We explored the desired features of medication applications for patients with chronic disease and their caregivers with a questionnaire survey, 50 from patients and 50 from their caregivers. Although the majority of people (75%) are willing to use medication apps, the actual usage rate is quite low (11%). Worrying about privacy of personal information seems to be the main reason of not using applications. The overall score desired for use was 3.29 ± 1.02 (out of 5). Searching medications and diseases and assistance with making doctors' appointments are the most wanted categories. Online shopping for drugs and delivery were the least desired items. The main concerns for people who do not want certain features include: they are not useful, worrying about buying counterfeit drugs and reliability of content. Compared with patients, caregivers seems to be more concerned on nutrition tips for chronic illness, fall detection, and privacy protection (P < 0.05 for all).

Physician perspectives of CYP2C19 and clopidogrel drug-gene interaction active clinical decision support alerts.

OBJECTIVE: To determine if physicians find clinical decision support alerts for pharmacogenomic drug-gene interactions useful and assess their perceptions of usability aspects that impact usefulness. MATERIALS AND METHODS: 52 physicians participated in an online simulation and questionnaire involving a prototype alert for the clopidogrel and CYP2C19 drug-gene interaction. RESULTS: Only 4% of participants stated they would override the alert. 92% agreed that the alerts were useful. 87% found the visual interface appropriate, 91% felt the timing of the alert was appropriate and 75% were unfamiliar with the specific drug-gene interaction. 80% of providers preferred the ability to order the recommended medication within the alert. Qualitative responses suggested that supplementary information is important, but should be provided as external links, and that the utility of pharmacogenomic alerts depends on the broader ecosystem of alerts. PRINCIPAL CONCLUSIONS: Pharmacogenomic alerts would be welcomed by many physicians, can be built with minimalist design principles, and are appropriately placed at the end of the prescribing process. Since many physicians lack familiarity with pharmacogenomics but have limited time, information and educational resources within the alert should be carefully selected and presented in concise ways.

Medication errors: a prospective cohort study of hand-written and computerised physician order entry in the intensive care unit.

INTRODUCTION: The study aimed to compare the impact of computerised physician order entry (CPOE) without decision support with hand-written prescribing (HWP) on the frequency, type and outcome of medication errors (MEs) in the intensive care unit. METHODS: Details of MEs were collected before, and at several time points after, the change from HWP to CPOE. The study was conducted in a London teaching hospital's 22-bedded general ICU. The sampling periods were 28 weeks before and 2, 10, 25 and 37 weeks after introduction of CPOE. The unit pharmacist prospectively recorded details of MEs and the total number of drugs prescribed daily during the data collection periods, during the course of his normal chart review. RESULTS: The total proportion of MEs was significantly lower with CPOE (117 errors from 2429 prescriptions, 4.8%) than with HWP (69 errors from 1036 prescriptions, 6.7%) (p < 0.04). The proportion of errors reduced with time following the introduction of CPOE (p < 0.001). Two errors with CPOE led to patient harm requiring an increase in length of stay and, if administered, three prescriptions with CPOE could potentially have led to permanent harm or death. Differences in the types of error between systems were noted. There was a reduction in major/moderate patient outcomes with CPOE when non-intercepted and intercepted errors were combined (p = 0.01). The mean baseline APACHE II score did not differ significantly between the HWP and the CPOE periods (19.4 versus 20.0, respectively, p = 0.71). CONCLUSION: Introduction of CPOE was associated with a reduction in the proportion of MEs and an improvement in the overall patient outcome score (if intercepted errors were included). Moderate and major errors, however, remain a significant concern with CPOE.

Determinants of physician use of an ambulatory prescription expert system.

PURPOSE: To determine whether physician experience with and attitude towards computers is associated with adoption of a voluntary ambulatory prescription writing expert system. METHODS: A prescription expert system was implemented in an academic internal medicine residency training clinic and physician utilization was tracked electronically. A physician attitude and behavior survey (response rate=89%) was conducted six months after implementation. RESULTS: There was wide variability in system adoption and degree of usage, though 72% of physicians reported predominant usage (> or =50% of prescriptions) of the expert system six months after implementation. Self-reported and measured technology usage were strongly correlated (r=0.70, p<0.0001). Variation in use was strongly associated with physician attitude toward issues of system efficiency and effect on quality, but not with prior computer experience, level of training, or satisfaction with their primary care practice. Non-adopters felt that electronic prescribing was more time consuming and also more likely to believe that their patients preferred hand-written prescriptions. CONCLUSION: A voluntary electronic prescription system was readily adopted by a majority of physicians who believed it would have a positive impact on the quality and efficiency of care. However, dissatisfaction with system capabilities among both adopters and non-adopters suggests the importance of user education and expectation management following system selection.

Evaluation of a clinical decision support rule-set for medication adjustments in mHealth-based heart failure management.

Decision-support based medication adjustment in heart failure management. Prospective analysis of clinical decision support in fifteen patients that collected vital parameters and medication intake up to one year within a clinical trial. Correlation of event episodes and medication adjustments with respect to applied rule-sets and medication classes. 713 events were grouped to 195 event episodes. Physicians performed 86 medication adjustments. 30 of them were triggered by event episodes. 35% of all performed medication adjustments occurred between event episodes. 20% of all episodes triggered a medication adjustment. 15% of all episodes triggered the expected medication adjustment. Correlation between episodes and medication adjustment was low. Further analysis needs to be done, to evaluate reasons for low correlation and how the rule-set should be adapted to increase reliability.

The use of a PID controller to model vecuronium pharmacokinetics and pharmacodynamics during liver transplantation. Proportional-integral-derivative.

A four-phase proportional-integral-derivative (PID) controller was evaluated under the extremely unstable conditions of liver transplantation. Vecuronium was delivered to achieve 80%-90% neuromuscular blockade as measured by electromyogram (EMG). The first two controller phases delivered boluses and a constant infusion calculated to rapidly achieve setpoint, followed by a proportional-derivative (PD) phase at 35% from setpoint, and PID within 10% of the setpoint. During liver transplantation, the sources of system instability included large blood losses, temperature changes, and loss of hepatic drug metabolism during removal and replacement. During prolonged surgery, and when blood losses were not severe, the EMG remained within 10% of setpoint. Controller performance was more variable during system instability. Plasma sampling and two-compartment modelling of the infusion and response with a weighting factor for blood loss allowed estimation of the sources and degree of instability for improved design of future controllers.

Prediction of serum vancomycin concentrations using one-, two- and three-compartment models with implemented population pharmacokinetic parameters and with the Bayesian method.

Although previous studies have shown that vancomycin has a complicated pharmacokinetic profile requiring description using a two- or, better, three-compartment model, until recently predictions of serum vancomycin concentrations have been mainly based on one- or two-compartment models using computer software packages. In this study, we have predicted serum vancomycin concentrations in 59 patients using one-, two- and three-compartment models with implemented population pharmacokinetic parameters in the Abbott PKS program and by use of the Bayesian method. The percentage errors of predictions made using the one-compartment model were smaller when either the Bayesian method or implemented population pharmacokinetic parameters were used (medians of -8.61% and -9.49%, respectively). Predictions using the one-compartment model with the Bayesian method were less biased (median of -1.52 microgmL(-1). The best predictions were those made using the three-compartment model with the Bayesian method-they were most accurate (median of 3.40 microgmL(-1) and highly precise (median of 11.53 microg(2)mL(-1)). The results suggest that predictions made using the one-compartment model with implemented population pharmacokinetic parameters are preferable if no samples are available, otherwise predictions made using the three-compartment model with the Bayesian method are preferable. The results also supported our previous argument that the greater the number of compartments involved in individualization, the better the predictions obtained using the Bayesian method.

[An informational and statistical validation of plant compounds for the treatment of patients with chronic glomerulonephritis]. / Informatyko-statystychne obhruntuvannia fitokompozytsii dlia likuvannia khvorykh na khronichnyi hlomerulonefryt.

Chronic glomerulonephritis (ChGN) is a grave poorly controlled disease for which no efficient method of pathogenetic therapy is available. In looking for efficient methods of treatment plants were of traditional (folk) medicine. The present investigation involves an approach based on the concepts of informational content of complicated prescriptions which form the basis of traditional medicine. Methods have been worked out of informational screening of structure of composite multicomponent herbal remedies, on the basis of the information theory using statistical methods. Computer the analysis has been performed of 176 phytotherapeutic formulae for the treatment of ChGN, based on the folk medicine experience. Phytocompositions have been selected to be used for a target-oriented action on human organism in ChGN, being characterized by duplication of components of unidirectional action. Herbs plants were singled out, incompatible in the treatment of ChGN.

Comparison of two kinds of interface, based on guided navigation or usability principles, for improving the adoption of computerized decision support systems: application to the prescription of antibiotics.

CONTEXT: It is important to consider the way in which information is presented by the interfaces of clinical decision support systems, to favor the adoption of these systems by physicians. Interface design can focus on decision processes (guided navigation) or usability principles. OBJECTIVE: The aim of this study was to compare these two approaches in terms of perceived usability, accuracy rate, and confidence in the system. MATERIALS AND METHODS: We displayed clinical practice guidelines for antibiotic treatment via two types of interface, which we compared in a crossover design. General practitioners were asked to provide responses for 10 clinical cases and the System Usability Scale (SUS) for each interface. We assessed SUS scores, the number of correct responses, and the confidence level for each interface. RESULTS: SUS score and percentage confidence were significantly higher for the interface designed according to usability principles (81 vs 51, p=0.00004, and 88.8% vs 80.7%, p=0.004). The percentage of correct responses was similar for the two interfaces. DISCUSSION/CONCLUSION: The interface designed according to usability principles was perceived to be more usable and inspired greater confidence among physicians than the guided navigation interface. Consideration of usability principles in the construction of an interface--in particular 'effective information presentation', 'consistency', 'efficient interactions', 'effective use of language', and 'minimizing cognitive load'--seemed to improve perceived usability and confidence in the system.

Impact of a clinical decision support system for high-alert medications on the prevention of prescription errors.

OBJECTIVE: To evaluate the impact of a high-alert medication clinical decision support system called HARMLESS on point-of-order entry errors in a tertiary hospital. METHOD: HARMLESS was designed to provide three kinds of interventions for five high-alert medications: clinical knowledge support, pop-ups for erroneous orders that block the order or provide a warning, and order recommendations. The impact of this program on prescription order was evaluated by comparing the orders in 6 month periods before and after implementing the program, by analyzing the intervention log data, and by checking for order pattern changes. RESULT: During the entire evaluation period, there were 357,417 orders and 5233 logs. After HARMLESS deployment, orders that omitted dilution fluids and exceeded the maximum dose dropped from 12,878 and 214 cases to 0 and 9 cases, respectively. The latter nine cases were unexpected, but after the responsible programming error was corrected, there were no further such cases. If all blocking interventions were seen as errors that were prevented, this meant that 4137 errors (3584 of which were 'dilution fluid omitted' errors) were prevented over the 6-month post-deployment period. There were some unexpected order pattern changes after deployment and several unexpected errors emerged, including intramuscular or intravenous push orders for potassium chloride (although a case review revealed that the drug was not actually administered via these methods) and an increase in pro re nata (PRN; administer when required) orders for most drugs. CONCLUSION: HARMLESS effectively implemented blocking interventions but was associated with the emergence of unexpected errors. After a program is deployed, it must be monitored and subjected to data analysis to fix bugs and prevent the emergence of new error types.