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BACKGROUND - Asthma is one of the most common childhood illnesses. Guideline-driven clinical care positively affects patient outcomes for care. There are several asthma guidelines and reminder methods for implementation to help integrate them into clinical workflow. Our goal is to determine the most prevalent method of guideline implementation; establish which methods significantly improved clinical care; and identify the factors most commonly associated with a successful and sustainable implementation.
METHODS - PUBMED (MEDLINE), OVID CINAHL, ISI Web of Science, and EMBASE.
STUDY SELECTION - Studies were included if they evaluated an asthma protocol or prompt, evaluated an intervention, a clinical trial of a protocol implementation, and qualitative studies as part of a protocol intervention. Studies were excluded if they had non-human subjects, were studies on efficacy and effectiveness of drugs, did not include an evaluation component, studied an educational intervention only, or were a case report, survey, editorial, letter to the editor.
RESULTS - From 14,478 abstracts, we included 101 full-text articles in the analysis. The most frequent study design was pre-post, followed by prospective, population based case series or consecutive case series, and randomized trials. Paper-based reminders were the most frequent with fully computerized, then computer generated, and other modalities. No study reported a decrease in health care practitioner performance or declining patient outcomes. The most common primary outcome measure was compliance with provided or prescribing guidelines, key clinical indicators such as patient outcomes or quality of life, and length of stay.
CONCLUSIONS - Paper-based implementations are by far the most popular approach to implement a guideline or protocol. The number of publications on asthma protocol reminder systems is increasing. The number of computerized and computer-generated studies is also increasing. Asthma guidelines generally improved patient care and practitioner performance regardless of the implementation method.
INTRODUCTION - Pediatric asthma exacerbations account for >1.8 million emergency department (ED) visits annually. Asthma guidelines are intended to guide time-dependent treatment decisions that improve clinical outcomes; however, guideline adherence is inadequate. We examined whether an automatic disease detection system increases clinicians' use of paper-based guidelines and decreases time to a disposition decision.
METHODS - We evaluated a computerized asthma detection system that triggered NHLBI-adopted, evidence-based practice to improve care in an urban, tertiary care pediatric ED in a 3-month (7/09-9/09) prospective, randomized controlled trial. A probabilistic system screened all ED patients for acute asthma. For intervention patients, the system generated the asthma protocol at triage for intervention patients to guide early treatment initiation, while clinicians followed standard processes for control patients. The primary outcome measures included time to patient disposition.
RESULTS - The system identified 1100 patients with asthma exacerbations, of which 704 had a final asthma diagnosis determined by a physician-established reference standard. The positive predictive value for the probabilistic system was 65%. The median time to disposition decision did not differ among the intervention (289 min; IQR = (184, 375)) and control group (288 min; IQR = (185, 375)) (p=0.21). The hospital admission rate was unchanged between intervention (37%) and control groups (35%) (p = 0.545). ED length of stay did not differ among the intervention (331 min; IQR = (226, 581)) and control group (331 min; IQR = (222, 516)) (p = 0.568).
CONCLUSION - Despite a high level of support from the ED leadership and staff, a focused education effort, and implementation of an automated disease detection, the use of the paper-based asthma protocol remained low and time to patient disposition did not change.
Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
OBJECTIVE - To evaluate the performance of a system that extracts medication information and administration-related actions from patient short message service (SMS) messages.
DESIGN - Mobile technologies provide a platform for electronic patient-centered medication management. MyMediHealth (MMH) is a medication management system that includes a medication scheduler, a medication administration record, and a reminder engine that sends text messages to cell phones. The object of this work was to extend MMH to allow two-way interaction using mobile phone-based SMS technology. Unprompted text-message communication with patients using natural language could engage patients in their healthcare, but presents unique natural language processing challenges. The authors developed a new functional component of MMH, the Patient-centered Automated SMS Tagging Engine (PASTE). The PASTE web service uses natural language processing methods, custom lexicons, and existing knowledge sources to extract and tag medication information from patient text messages.
MEASUREMENTS - A pilot evaluation of PASTE was completed using 130 medication messages anonymously submitted by 16 volunteers via a website. System output was compared with manually tagged messages.
RESULTS - Verified medication names, medication terms, and action terms reached high F-measures of 91.3%, 94.7%, and 90.4%, respectively. The overall medication name F-measure was 79.8%, and the medication action term F-measure was 90%.
CONCLUSION - Other studies have demonstrated systems that successfully extract medication information from clinical documents using semantic tagging, regular expression-based approaches, or a combination of both approaches. This evaluation demonstrates the feasibility of extracting medication information from patient-generated medication messages.
BACKGROUND - Primary care physicians (PCPs) care for most non-dialysis-dependent patients with chronic kidney disease (CKD). Studies suggest that PCPs may deliver suboptimal CKD care. One means to improve PCP treatment of CKD is clinical decision support systems (CDSSs).
STUDY DESIGN - Cluster-randomized controlled trial.
SETTING & PARTICIPANTS - 30 PCPs in a university-based outpatient general internal medicine practice and their 248 patients with moderate to advanced CKD who had not been referred to a nephrologist.
INTERVENTION - 2 CKD educational sessions were held for PCPs in both arms. The 15 intervention-arm PCPs also received real-time automated electronic medical record alerts for patients with estimated glomerular filtration rates <45 mL/min/1.73 m(2) recommending renal referral and urine albumin quantification if not done within the prior year.
OUTCOMES - Primary outcome was referral to a nephrologist; secondary outcomes were albuminuria/proteinuria assessment, CKD documentation, optimal blood pressure (ie, <130/80 mm Hg), and use of renoprotective medications.
RESULTS - The intervention and control arms did not differ in renal referrals (9.7% vs 16.5%, respectively; between-group difference, -6.8%; 95% CI, -15.5% to 1.8%; P = 0.1) or proteinuria assessments (39.3% vs 30.1%, respectively; between-group difference, 9.2%; 95% CI, -2.7% to 21.1%; P = 0.1). For intervention and control patients without a baseline proteinuria assessment, 27.7% versus 16.3%, respectively, had one at follow-up (P = 0.06). After controlling for clustering, these findings were largely unchanged and no significant differences were apparent between groups.
LIMITATIONS - Small single-center university-based practice, use of a passive CDSS that required PCPs to trigger the electronic order set.
CONCLUSIONS - PCPs were willing to partake in a randomized trial of a CDSS to improve outpatient CKD care. Although CDSSs may have potential, larger studies are needed to further explore how best to deploy them to enhance CKD care.
Copyright © 2011 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
OBJECTIVE - Alerting systems, a type of clinical decision support, are increasingly prevalent in healthcare, yet few studies have concurrently measured the appropriateness of alerts with provider responses to alerts. Recent reports of suboptimal alert system design and implementation highlight the need for better evaluation to inform future designs. The authors present a comprehensive framework for evaluating the clinical appropriateness of synchronous, interruptive medication safety alerts.
METHODS - Through literature review and iterative testing, metrics were developed that describe successes, justifiable overrides, provider non-adherence, and unintended adverse consequences of clinical decision support alerts. The framework was validated by applying it to a medication alerting system for patients with acute kidney injury (AKI).
RESULTS - Through expert review, the framework assesses each alert episode for appropriateness of the alert display and the necessity and urgency of a clinical response. Primary outcomes of the framework include the false positive alert rate, alert override rate, provider non-adherence rate, and rate of provider response appropriateness. Application of the framework to evaluate an existing AKI medication alerting system provided a more complete understanding of the process outcomes measured in the AKI medication alerting system. The authors confirmed that previous alerts and provider responses were most often appropriate.
CONCLUSION - The new evaluation model offers a potentially effective method for assessing the clinical appropriateness of synchronous interruptive medication alerts prior to evaluating patient outcomes in a comparative trial. More work can determine the generalizability of the framework for use in other settings and other alert types.
BACKGROUND - Pneumococcal vaccination is an effective strategy to prevent invasive pneumococcal disease in the elderly. Emergency department (ED) visits present an underutilized opportunity to increase vaccination rates; however, designing a sustainable vaccination program in an ED is challenging. We examined whether an information technology supported approach would provide a feasible and sustainable method to increase vaccination rates in an adult ED.
METHODS - During a 1-year period we prospectively evaluated a team-oriented, workflow-embedded reminder system that integrated four different information systems. The computerized triage application screened all patients 65 years and older for pneumococcal vaccine eligibility with information from the electronic patient record. For eligible patients the computerized provider order entry system reminded clinicians to place a vaccination order, which was passed to the order tracking application. Documentation of vaccine administration was then added to the longitudinal electronic patient record. The primary outcome was the vaccine administration rate in the ED. Multivariate logistic regression analysis was used to estimate the odds ratios and their 95% confidence intervals, representing the overall relative risks of ED workload related variables associated with vaccination rate.
RESULTS - Among 3371 patients 65 years old and older screened at triage 1309 (38.8%) were up-to-date with pneumococcal vaccination and 2062 (61.2%) were eligible for vaccination. Of the eligible patients, 621 (30.1%) consented to receive the vaccination during their ED visit. Physicians received prompts for 428 (68.9%) patients. When prompted, physicians declined to order the vaccine in 192 (30.9%) patients, while 222 (10.8%) of eligible patients actually received the vaccine. The computerized reminder system increased vaccination rate from a baseline of 38.8% to 45.4%. Vaccination during the ED visit was associated younger age (OR: 0.972, CI: 0.953-0.991), Caucasian race (OR: 0.329, CI: 0.241-0.448), and longer ED boarding times (OR: 1.039, CI: 1.013-1.065).
CONCLUSION - The integrated informatics solution seems to be a feasible and sustainable model to increase vaccination rates in a challenging ED environment.
Copyright © 2011 Elsevier Ltd. All rights reserved.
PURPOSE - Patients receiving cancer-related thoracotomy are highly symptomatic in the first weeks after surgery. This study examined whether at-home symptom monitoring plus feedback to clinicians about severe symptoms contributes to more effective postoperative symptom control.
PATIENTS AND METHODS - We enrolled 100 patients receiving thoracotomy for lung cancer or lung metastasis in a two-arm randomized controlled trial; 79 patients completed the study. After hospital discharge, patients rated symptoms twice weekly for 4 weeks via automated telephone calls. For intervention group patients, an e-mail alert was forwarded to the patient's clinical team for response if any of a subset of symptoms (pain, disturbed sleep, distress, shortness of breath, or constipation) reached a predetermined severity threshold. No alerts were generated for controls. Group differences in symptom threshold events were examined by generalized estimating equation modeling.
RESULTS - The intervention group experienced greater reduction in symptom threshold events than did controls (19% v 8%, respectively) and a more rapid decline in symptom threshold events. The difference in average reduction in symptom interference between groups was -0.36 (SE, 0.078; P = .02). Clinicians responded to 84% of e-mail alerts. Both groups reported equally high satisfaction with the automated system and with postoperative symptom control.
CONCLUSION - Frequent symptom monitoring with alerts to clinicians when symptoms became moderate or severe reduced symptom severity during the 4 weeks after thoracic surgery. Methods of automated symptom monitoring and triage may improve symptom control after major cancer surgery. These results should be confirmed in a larger study.
OBJECTIVE - To evaluate the impact of generic substitution decision support on electronic (e-) prescribing of generic medications.
DESIGN - The authors analyzed retrospective outpatient e-prescribing data from an academic medical center and affiliated network for July 1, 2005-September 30, 2008 using an interrupted time-series design to assess the rate of generic prescribing before and after implementing generic substitution decision support. To assess background secular trends, e-prescribing was compared with a concurrent random sample of hand-generated prescriptions.
MEASUREMENTS - Proportion of generic medications prescribed before and after the intervention, evaluated over time, and compared with a sample of prescriptions generated without e-prescribing.
RESULTS - The proportion of generic medication prescriptions increased from 32.1% to 54.2% after the intervention (22.1% increase, 95% CI 21.9% to 22.3%), with no diminution in magnitude of improvement post-intervention. In the concurrent control group, increases in proportion of generic prescriptions (29.3% to 31.4% to 37.4% in the pre-intervention, post-intervention, and end-of-study periods, respectively) were not commensurate with the intervention. There was a larger change in generic prescribing rates among authorized prescribers (24.6%) than nurses (18.5%; adjusted OR 1.38, 95% CI 1.17 to 1.63). Two years after the intervention, the proportion of generic prescribing remained significantly higher for e-prescriptions (58.1%; 95% CI 57.5% to 58.7%) than for hand-generated prescriptions ordered at the same time (37.4%; 95% CI 34.9% to 39.9%) (p<0.0001). Generic prescribing increased significantly in every specialty.
CONCLUSION - Implementation of generic substitution decision support was associated with dramatic and sustained improvements in the rate of outpatient generic e-prescribing across all specialties.
Preventive care measures remain underutilized despite recommendations to increase their use. The objective of this review was to examine the characteristics, types, and effects of paper- and computer-based interventions for preventive care measures. The study provides an update to a previous systematic review. We included randomized controlled trials that implemented a physician reminder and measured the effects on the frequency of providing preventive care. Of the 1,535 articles identified, 28 met inclusion criteria and were combined with the 33 studies from the previous review. The studies involved 264 preventive care interventions, 4,638 clinicians and 144,605 patients. Implementation strategies included combined paper-based with computer generated reminders in 34 studies (56%), paper-based reminders in 19 studies (31%), and fully computerized reminders in 8 studies (13%). The average increase for the three strategies in delivering preventive care measures ranged between 12% and 14%. Cardiac care and smoking cessation reminders were most effective. Computer-generated prompts were the most commonly implemented reminders. Clinician reminders are a successful approach for increasing the rates of delivering preventive care; however, their effectiveness remains modest. Despite increased implementation of electronic health records, randomized controlled trials evaluating computerized reminder systems are infrequent.
BACKGROUND - A cross-sectional content analysis nested within a randomized, controlled trial was conducted to collect information on provider responses to computer alerts regarding guideline recommendations for patients with suboptimal hypertension care.
METHODS - Participants were providers who cared for 1,017 patients with uncontrolled hypertension on a single antihypertensive agent within Veterans Affairs primary care clinics. All reasons for action or inaction were sorted into a framework to explain the variation in guideline adaptation.
RESULTS - The 184 negative provider responses to computer alerts contained explanations for not changing patient treatment; 76 responses to the alerts were positive, that is, the provider was going to make a change in antihypertensive regimen. The negative responses were categorized as: inertia of practice (66%), lack of agreement with specific guidelines (5%), patient-based factors (17%), environmental factors (10%), and lack of knowledge (2%). Most of the 135 providers classified as inertia of practice indicated, "Continue current medications and I will discuss at the next visit." The median number of days until the next visit was 45 days (interquartile range, 29 to 78 days).
DISCUSSION - Clinical inertia was the primary reason for failing to engage in otherwise indicated treatment change in a subgroup of patients. A framework was provided as a taxonomy for classification of provider barriers.