Clinical Study of an Online Tool for Standardizing Hospital Care.

We assessed if use of an online clinical decision support tool improved standardization and quality of care in hospitalized patients with lower extremity cellulitis (LEC). This was a 14-month preintervention and postintervention study of 85 LEC admissions. There was significantly higher usage of the online LEC care process model (CPM) in the postintervention phase (p < .001). There was a trend toward higher rates of appropriate antibiotic regimen in the postintervention group both initially and at discharge (p = .063 for both). A sensitivity analysis of CPM users versus nonusers demonstrated a significantly higher rate of appropriate initial antibiotics prescribed when the CPM was used (p < .001). Use of this online CPM was associated with improved standardization, as demonstrated by increased ordering of an appropriate initial antibiotic regimen for hospitalized patients with LEC.

An automated clinical alert system for newly-diagnosed atrial fibrillation.

OBJECTIVE: Clinical decision support systems that notify providers of abnormal test results have produced mixed results. We sought to develop, implement, and evaluate the impact of a computer-based clinical alert system intended to improve atrial fibrillation stroke prophylaxis, and identify reasons providers do not implement a guideline-concordant response. MATERIALS AND METHODS: We conducted a cohort study with historical controls among patients at a tertiary care hospital. We developed a decision rule to identify newly-diagnosed atrial fibrillation, automatically notify providers, and direct them to online evidence-based management guidelines. We tracked all notifications from December 2009 to February 2010 (notification period) and applied the same decision rule to all patients from December 2008 to February 2009 (control period). Primary outcomes were accuracy of notification (confirmed through chart review) and prescription of warfarin within 30 days. RESULTS: During the notification period 604 notifications were triggered, of which 268 (44%) were confirmed as newly-diagnosed atrial fibrillation. The notifications not confirmed as newly-diagnosed involved patients with no recent electrocardiogram at our institution. Thirty-four of 125 high-risk patients (27%) received warfarin in the notification period, compared with 34 of 94 (36%) in the control period (odds ratio, 0.66 [95% CI, 0.37-1.17]; p = 0.16). Common reasons to not prescribe warfarin (identified from chart review of 151 patients) included upcoming surgical procedure, choice to use aspirin, and discrepancy between clinical notes and the medication record. CONCLUSIONS: An automated system to identify newly-diagnosed atrial fibrillation, notify providers, and encourage access to management guidelines did not change provider behaviors.

A comprehensive information technology system to support physician learning at the point of care.

MayoExpert is a multifaceted information system integrated with the electronic medical record (EMR) across Mayo Clinic's multisite health system. It was developed as a technology-based solution to manage information, standardize clinical practice, and promote and document learning in clinical contexts. Features include urgent test result notifications; models illustrating expert-approved care processes; concise, expert-approved answers to frequently asked questions (FAQs); a directory of topic-specific experts; and a portfolio for provider licensure and credentialing. The authors evaluate MayoExpert's reach, effectiveness, adoption, implementation, and maintenance. Evaluation data sources included usage statistics, user surveys, and pilot studies.As of October 2013, MayoExpert was available at 94 clinical sites in 12 states and contained 1,368 clinical topics, answers to 7,640 FAQs, and 92 care process models. In 2012, MayoExpert was accessed at least once by 2,578/3,643 (71%) staff physicians, 900/1,374 (66%) midlevel providers, and 1,728/2,291 (75%) residents and fellows. In a 2013 survey of MayoExpert users with 536 respondents, all features were highly rated (≥67% favorable). More providers reported using MayoExpert to answer questions before/after than during patient visits (68% versus 36%). During November 2012 to April 2013, MayoExpert sent 1,660 notifications of new-onset atrial fibrillation and 1,590 notifications of prolonged QT. MayoExpert has become part of routine clinical and educational operations, and its care process models now define Mayo Clinic best practices. MayoExpert's infrastructure and content will continue to expand with improved templates and content organization, new care process models, additional notifications, better EMR integration, and improved support for credentialing activities.

Speed and accuracy of a point of care web-based knowledge resource for clinicians: a controlled crossover trial.

BACKGROUND: Effective knowledge translation at the point of care requires that clinicians quickly find correct answers to clinical questions, and that they have appropriate confidence in their answers. Web-based knowledge resources can facilitate this process. OBJECTIVE: The objective of our study was to evaluate a novel Web-based knowledge resource in comparison with other available Web-based resources, using outcomes of accuracy, time, and confidence. METHODS: We conducted a controlled, crossover trial involving 59 practicing clinicians. Each participant answered questions related to two clinical scenarios. For one scenario, participants used a locally developed Web-based resource, and for the second scenario, they used other self-selected Web-based resources. The local knowledge resource ("AskMayoExpert") was designed to provide very concise evidence-based answers to commonly asked clinical questions. Outcomes included time to a correct response with at least 80% confidence (primary outcome), accuracy, time, and confidence. RESULTS: Answers were more often accurate when using the local resource than when using other Web-based resources, with odds ratio 6.2 (95% CI 2.6-14.5; P<.001) when averaged across scenarios. Time to find an answer was faster, and confidence in that answer was consistently higher, for the local resource (P<.001). Overconfidence was also less frequent with the local resource. In a time-to-event analysis, the chance of responding correctly with at least 80% confidence was 2.5 times greater when using the local resource than with other resources (95% CI 1.6-3.8; P<.001). CONCLUSIONS: Clinicians using a Web-based knowledge resource designed to provide quick, concise answers at the point of care found answers with greater accuracy and confidence than when using other self-selected Web-based resources. Further study to improve the design and implementation of knowledge resources may improve point of care learning.

Meningeal coccidioidomycosis diagnosed by real-time polymerase chain reaction analysis of cerebrospinal fluid.

We describe two cases of coccidioidal meningitis (CM) diagnosed using real-time polymerase chain reaction (PCR) analysis of cerebrospinal fluid. These cases highlight the promise of PCR as a diagnostic method to assist in the rapid diagnosis of CM.

Physician decision making and cardiac risk: effects of knowledge, risk perception, risk tolerance, and fuzzy processing.

Despite training, professionals sometimes make serious errors in risky decision making. The authors investigated judgments and decisions for 9 hypothetical patients at 3 levels of cardiac risk, comparing student and physician groups varying in domain-specific knowledge. Decisions were examined regarding whether they deviated from guidelines, how risk perceptions and risk tolerances determined decisions, and how the latter differed for knowledge groups. More knowledgeable professionals were better at discriminating levels of risk according to external correspondence criteria but committed similar errors in disjunctive probability judgments, violating internal coherence criteria. Also, higher knowledge groups relied on fewer dimensions of information than did lower knowledge groups. Consistent with fuzzy-trace theory, experts achieved better discrimination by processing less information and made sharper all-or-none distinctions among decision categories.