Use Of Clinical Prediction Rules Research Articles

Internet Tool to Support Self-Assessment and Self-Swabbing of Sore Throat: Development and Feasibility Study.

Sore throat is a common problem and a common reason for the overuse of antibiotics. A web-based tool that helps people assess their sore throat, through the use of clinical prediction rules, taking throat swabs or saliva samples, and taking throat photographs, has the potential to improve self-management and help identify those who are the most and least likely to benefit from antibiotics. We aimed to develop a web-based tool to help patients and parents or carers self-assess sore throat symptoms and take throat photographs, swabs, and saliva samples for diagnostic testing. We then explored the acceptability and feasibility of using the tool in adults and children with sore throats. We used the Person-Based Approach to develop a web-based tool and then recruited adults and children with sore throats who participated in this study by attending general practices or through social media advertising. Participants self-assessed the presence of FeverPAIN and Centor score criteria and attempted to photograph their throat and take throat swabs and saliva tests. Study processes were observed via video call, and participants were interviewed about their views on using the web-based tool. Self-assessed throat inflammation and pus were compared to clinician evaluation of patients' throat photographs. A total of 45 participants (33 adults and 12 children) were recruited. Of these, 35 (78%) and 32 (71%) participants completed all scoring elements for FeverPAIN and Centor scores, respectively, and most (30/45, 67%) of them reported finding self-assessment relatively easy. No valid response was provided for swollen lymph nodes, throat inflammation, and pus on the throat by 11 (24%), 9 (20%), and 13 (29%) participants respectively. A total of 18 (40%) participants provided a throat photograph of adequate quality for clinical assessment. Patient assessment of inflammation had a sensitivity of 100% (3/3) and specificity of 47% (7/15) compared with the clinician-assessed photographs. For pus on the throat, the sensitivity was 100% (3/3) and the specificity was 71% (10/14). A total of 89% (40/45), 93% (42/45), 89% (40/45), and 80% (30/45) of participants provided analyzable bacterial swabs, viral swabs, saliva sponges, and saliva drool samples, respectively. Participants were generally happy and confident in providing samples, with saliva samples rated as slightly more acceptable than swab samples. Most adult and parent participants were able to use a web-based intervention to assess the clinical features of throat infections and generate scores using clinical prediction rules. However, some had difficulties assessing clinical signs, such as lymph nodes, throat pus, and inflammation, and scores were assessed as sensitive but not specific. Many participants had problems taking photographs of adequate quality, but most were able to take throat swabs and saliva samples.

Reducing prescribing of antibiotics for acute respiratory infections using a frontline nurse-led EHR-Integrated clinical decision support tool: protocol for a stepped wedge randomized control trial

BackgroundOverprescribing of antibiotics for acute respiratory infections (ARIs) remains a major issue in outpatient settings. Use of clinical prediction rules (CPRs) can reduce inappropriate antibiotic prescribing but they remain underutilized by physicians and advanced practice providers. A registered nurse (RN)-led model of an electronic health record-integrated CPR (iCPR) for low-acuity ARIs may be an effective alternative to address the barriers to a physician-driven model.MethodsFollowing qualitative usability testing, we will conduct a stepped-wedge practice-level cluster randomized controlled trial (RCT) examining the effect of iCPR-guided RN care for low acuity patients with ARI. The primary hypothesis to be tested is: Implementation of RN-led iCPR tools will reduce antibiotic prescribing across diverse primary care settings. Specifically, this study aims to: (1) determine the impact of iCPRs on rapid strep test and chest x-ray ordering and antibiotic prescribing rates when used by RNs; (2) examine resource use patterns and cost-effectiveness of RN visits across diverse clinical settings; (3) determine the impact of iCPR-guided care on patient satisfaction; and (4) ascertain the effect of the intervention on RN and physician burnout.DiscussionThis study represents an innovative approach to using an iCPR model led by RNs and specifically designed to address inappropriate antibiotic prescribing. This study has the potential to provide guidance on the effectiveness of delegating care of low-acuity patients with ARIs to RNs to increase use of iCPRs and reduce antibiotic overprescribing for ARIs in outpatient settings.Trial registrationClinicalTrials.gov Identifier: NCT04255303, Registered February 5 2020, https://clinicaltrials.gov/ct2/show/NCT04255303.

Atypical Pathogens in Adult Community-Acquired Pneumonia and Implications for Empiric Antibiotic Treatment: A Narrative Review.

Atypical pathogens are intracellular bacteria causing community-acquired pneumonia (CAP) in a significant minority of patients. Legionella spp., Chlamydia pneumoniae and psittaci, Mycoplasma pneumoniae, and Coxiella burnetii are commonly included in this category. M. pneumoniae is present in 5-8% of CAP, being the second most frequent pathogen after Streptococcus pneumoniae. Legionella pneumophila is found in 3-5% of inpatients. Chlamydia spp. and Coxiella burnetii are present in less than 1% of patients. Legionella longbeachae is relatively frequent in New Zealand and Australia and might also be present in other parts of the world. Uncertainty remains on the prevalence of atypical pathogens, due to limitations in diagnostic means and methodological issues in epidemiological studies. Despite differences between CAP caused by typical and atypical pathogens, the clinical presentation alone does not allow accurate discrimination. Hence, antibiotics active against atypical pathogens (macrolides, tetracyclines and fluoroquinolones) should be included in the empiric antibiotic treatment of all patients with severe CAP. For patients with milder disease, evidence is lacking and recommendations differ between guidelines. Use of clinical prediction rules to identify patients most likely to be infected with atypical pathogens, and strategies of narrowing the antibiotic spectrum according to initial microbiologic investigations, should be the focus of future investigations.

Unreliability of Clinical Prediction Rules to Exclude without Echocardiography Infective Endocarditis in Staphylococcus aureus Bacteremia

Background: It is unclear whether the use of clinical prediction rules is sufficient to rule out infective endocarditis (IE) in patients with Staphylococcus aureus bacteremia (SAB) without an echocardiogram evaluation, either transthoracic (TTE) and/or transesophageal (TEE). Our primary purpose was to test the usefulness of PREDICT, POSITIVE, and VIRSTA scores to rule out IE without echocardiography. Our secondary purpose was to evaluate whether not performing an echocardiogram evaluation is associated with higher mortality. Methods: We conducted a unicentric retrospective cohort including all patients with a first SAB episode from January 2015 to December 2020. IE was defined according to modified Duke criteria. We predefined threshold cutoff points to consider that IE was ruled out by means of the mentioned scores. To assess 30-day mortality, we used a multivariable regression model considering performing an echocardiogram as covariate. Results: Out of 404 patients, IE was diagnosed in 50 (12.4%). Prevalence of IE within patients with negative PREDICT, POSITIVE, and VIRSTA scores was: 3.6% (95% CI 0.1–6.9%), 4.9% (95% CI 2.2–7.7%), and 2.2% (95% CI 0.2–4.3%), respectively. Patients with negative VIRSTA and negative TTE had an IE prevalence of 0.9% (95% CI 0–2.8%). Performing an echocardiogram was independently associated with lower 30-day mortality (OR 0.24 95% CI 0.10–0.54, p = 0.001). Conclusion: PREDICT and POSITIVE scores were not sufficient to rule out IE without TEE. In patients with negative VIRSTA score, it was doubtful if IE could be discarded with a negative TTE. Not performing an echocardiogram was associated with worse outcomes, which might be related to presence of occult IE. Further studies are needed to assess the usefulness of clinical prediction rules in avoiding echocardiographic evaluation in SAB patients.

A Meta-Analysis of the Prognostic Accuracy of Clinical Prediction Rules for Post-Pulmonary Embolism Mortality in Patients with Cancer

Introduction: Pulmonary embolism (PE) is a common complication of cancer and its treatments; it is a leading cause of morbidity and mortality in patients with malignancy. While extensive work has been done in evaluating PE risk of patients with cancer, there are limited data on the prognostication of adverse outcomes when these patients do experience an event. Guidelines recommend the use of clinical prediction rules to help clinicians identify patients at low- and higher-risk for adverse outcomes and guide the appropriate level of care. However, no single clinical prediction rule has been shown to be superior in stratifying these patients. Thus, we sought to determine the accuracy of clinical prediction rules for identifying patients with cancer and acute PE at low risk for mortality.Methods: A systematic literature search of Medline and Scopus from January 1, 2000 through July 1, 2017 was performed, along with a manual search of references. Studies deriving/validating at least one clinical prediction rule for early post-PE all-cause mortality in patients with cancer and providing mortality data over at least the index PE hospitalization but not longer than 90 days were included. Only full-text, English-language articles were included. A bivariate model was used to pool sensitivity and specificity estimates for each clinical prediction rule using a random-effects approach. Traditional random effects meta-analysis was performed to estimate the weighted proportion of patients deemed at low risk for early mortality and their odds ratios for death compared with high-risk patients. Statistical heterogeneity was assessed with the I2 statistic with values >50% deemed as high.Results: We identified 1,104 non-duplicate citations from our literature search. Eight studies evaluating ten clinical prediction rules in 3,974 (range 124 to 1,075) unique patients were ultimately included in our meta-analysis (Table). Mean/median patient age ranged from 59 to 71 years. The majority of included patients were receiving chemotherapy and/or radiotherapy (50 to 75% of patients), and metastatic disease was observed in 49% to 74% of patients. The Hestia and EPIPHANY index rules displayed the highest sensitivities (98.1% [95% CI = 75.6% to 99.9%] and 97.4% [95% CI = 93.2% to 99.0%], respectively) with the remaining rules' sensitivities ranging from 0.88 to 0.97; only the GPS tool had a sensitivity of 0.60. Of the six clinical prediction rules with sensitivities ≥95%, none had specificities >33%. Traditional random-effects meta-analysis suggested anywhere from 6.6% to 51.6% of cancer patients with PE were at low risk and that low-risk patients had a 43% to 94% lower odds of death compared with those at high risk.Conclusions: There is a limited total body of evidence on the ten clinical prediction rules included in our meta-analysis. As such, the results of clinical prediction rules as well as other patient-specific clinical factors should continue to be used in identifying appropriate treatment for patients with cancer experiencing an acute PE. [Display omitted] DisclosuresColeman:Bayer AG: Consultancy, Honoraria, Research Funding; Janssen Pharmaceuticals: Consultancy, Honoraria, Research Funding; Boehringer Ingelheim: Consultancy, Honoraria.

Borderline Nerve Conduction Velocities for Median Neuropathy at the Carpal Tunnel

Patient knowledge of the frequency with which electrodiagnostic testing (EDx) for suspected median neuropathy at the carpal tunnel addresses nuance in the distinction between normal and abnormal neurophysiology might help them make an informed decision about whether or not to have this test. We reviewed a large set of consecutive EDx for possible carpal tunnel syndrome (CTS) and associated medical records to determine (1) the percentage of EDx measurements within 10% of threshold values; (2) discordance between clinician and EDx diagnosis of CTS using diagnostic performance characteristics; and (3) demographic and disease characteristics independently associated with EDx diagnosis of median neuropathy at the carpal tunnel. We retrospectively reviewed nerve conduction study (NCS) results of 537 consecutive patients evaluated for possible idiopathic median neuropathy at the carpal tunnel. We measured the number of patients within 10% of 3 NCS diagnostic thresholds; the diagnostic performance characteristics comparing clinician and EDx diagnosis; and patient and disease characteristics associated with EDx diagnosis of CTS. The 3 NCS parameters were within 10% of the threshold for diagnosis of median neuropathy at the carpal tunnel in 2.6% to 33% of patients. Overall, 76% of EDx results were interpreted as median neuropathy at the carpal tunnel, 19% as normal, and 5% as another diagnosis (eg, cervical radiculopathy). Patients with normal EDx were significantly younger, more likely not to report paresthesias/numbness, more likely to have prior normal EDx, and less likely to have had a previous contralateral carpal tunnel release. This data set reflecting management strategies for suspected CTS at a large institution confirms inherent diagnostic uncertainty, relatively strong concordance between clinician and EDx diagnosis, and the importance of focusing on paresthesia rather than pain. These findings support the use of clinical prediction rules and may help inform a patient's decision regarding whether or not to have EDx. Diagnostic III.

A systematic review of clinical prediction rules for the diagnosis of chronic heart failure.

AimsThis study sought to review the literature for clinical prediction models for the diagnosis of patients with chronic heart failure in the community and to validate the models in a novel cohort of patients with a suspected diagnosis of chronic heart failure.Methods and resultsMEDLINE and Embase were searched from 1946 to Q4 2017. Studies were eligible if they contained at least one multivariable model for the diagnosis of chronic heart failure applicable to the primary care setting. The CHARMS checklist was used to evaluate models. We also validated models, where possible, in a novel cohort of patients with a suspected diagnosis of heart failure referred to a rapid access diagnostic clinic.In total, 5310 articles were identified with nine articles subsequently meeting the eligibility criteria. Three models had undergone internal validation, and four had undergone external validation. No clinical impact studies have been completed to date. Area under the curve (AUC) varied from 0.74 to 0.93 and from 0.60 to 0.65 in the novel cohort for clinical models alone with AUC up to 0.89 in combination with electrocardiogram and B‐type natriuretic peptide (BNP). The AUC for BNP was 0.86 (95% confidence interval 83.3–88.6%).ConclusionsThis review demonstrates that there are a number of clinical prediction rules relevant to the diagnosis of chronic heart failure in the literature. Clinical impact studies are required to compare the use of clinical prediction rules and biomarker strategies in this setting.

New guidelines from the Thrombosis and Haemostasis Society of Australia and New Zealand for the diagnosis and management of venous thromboembolism.

Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), is the third most common cardiovascular disease and, globally, more than an estimated 10 million people have it yearly. It is a chronic and recurrent disease. The symptoms of VTE are non-specific and the diagnosis should actively be sought once considered. The mainstay of VTE treatment is anticoagulation, with few patients requiring additional intervention. A working group of experts in the area recently completed an evidence-based guideline for the diagnosis and management of DVT and PE on behalf of the Thrombosis and Haemostasis Society of Australia and New Zealand (www.thanz.org.au/resources/thanz-guidelines). The diagnosis of VTE should be established with imaging; it may be excluded by the use of clinical prediction rules combined with D-dimer testing. Proximal DVT or PE caused by a major surgery or trauma that is no longer present should be treated with anticoagulant therapy for 3 months. Proximal DVT or PE that is unprovoked or associated with a transient risk factor (non-surgical) should be treated with anticoagulant therapy for 3-6 months. Proximal DVT or PE that is recurrent (two or more) and provoked by active cancer or antiphospholipid syndrome should receive extended anticoagulation. Distal DVT caused by a major provoking factor that is no longer present should be treated with anticoagulant therapy for 6 weeks. For patients continuing with extended anticoagulant therapy, either therapeutic or low dose direct oral anticoagulants can be prescribed and is preferred over warfarin in the absence of contraindications. Routine thrombophilia testing is not indicated. Thrombolysis or a suitable alternative is indicated for massive (haemodynamically unstable) PE. Most patients with acute VTE should be treated with a factor Xa inhibitor and be assessed for extended anticoagulation.

Adaptive design of a clinical decision support tool: What the impact on utilization rates means for future CDS research.

OBJECTIVEWe employed an agile, user-centered approach to the design of a clinical decision support tool in our prior integrated clinical prediction rule study, which achieved high adoption rates. To understand if applying this user-centered process to adapt clinical decision support tools is effective in improving the use of clinical prediction rules, we examined utilization rates of a clinical decision support tool adapted from the original integrated clinical prediction rule study tool to determine if applying this user-centered process to design yields enhanced utilization rates similar to the integrated clinical prediction rule study.MATERIALS & METHODS: We conducted pre-deployment usability testing and semi-structured group interviews at 6 months post-deployment with 75 providers at 14 intervention clinics across the two sites to collect user feedback. Qualitative data analysis is bifurcated into immediate and delayed stages; we reported on immediate-stage findings from real-time field notes used to generate a set of rapid, pragmatic recommendations for iterative refinement. Monthly utilization rates were calculated and examined over 12 months.RESULTSWe hypothesized a well-validated, user-centered clinical decision support tool would lead to relatively high adoption rates. Then 6 months post-deployment, integrated clinical prediction rule study tool utilization rates were substantially lower than anticipated based on the original integrated clinical prediction rule study trial (68%) at 17% (Health System A) and 5% (Health System B). User feedback at 6 months resulted in recommendations for tool refinement, which were incorporated when possible into tool design; however, utilization rates at 12 months post-deployment remained low at 14% and 4% respectively.DISCUSSIONAlthough valuable, findings demonstrate the limitations of a user-centered approach given the complexity of clinical decision support.CONCLUSIONStrategies for addressing persistent external factors impacting clinical decision support adoption should be considered in addition to the user-centered design and implementation of clinical decision support.

LO74: Cost-effectiveness of pathways for diagnosing pulmonary embolism in Canada

Introduction: Pulmonary embolism (PE) is a common cardiovascular condition with high mortality rates if left untreated. Given the non-specific and varied symptoms of PE, its diagnosis remains challenging and approaches can lend themselves to inefficiencies through over-testing and over-diagnosis. Clinicians rely on a multi-component and sequential approach, including clinical risk assessment, rule-out biomarkers, and diagnostic imaging. This study assessed the potential cost-effectiveness of different diagnostic algorithms. Methods: A cost-utility model was developed with an upfront decision tree capturing the diagnostic accuracy and a Markov cohort model reflecting the lifetime disease progression and clinical utility of each diagnostic strategy. 57 diagnostic strategies were evaluated that were permutations of various clinical risk assessment, rule-out biomarkers and diagnostic imaging modalities. Diagnostic test accuracy was informed by systematic reviews and meta-analyses, and costs (2016 CAD) were obtained from Canadian costing databases to reflect a health-care payer perspective. Separate scenario analyses were conducted on patients contra-indicated for computed tomography (CT) or who are pregnant as this entails a comparison of a different set of diagnostic strategies. Results: Six diagnostic strategies formed the efficiency frontier. Diagnosing patients with PE was generally cost-effective if willingness-to-pay was greater than $1,481 per quality-adjusted-life year (QALY). CT dominated other imaging modality given its greater diagnostic accuracy, lower rates of non-diagnostic findings and lowest overall costs. The use of clinical prediction rules to determine clinical pre-test probability of PE and the application of rule-out test for patients with low-to-moderate risk of PE may be cost-effective while reducing the proportion of patients requiring CT and lowering radiation exposure. At a willingness-to-pay of $50,000 per QALY, the strategy of Wells (2 tier) --> d-dimer --> CT --> CT was the most likely cost-effective diagnostic strategy. However, different diagnostic strategies were considered cost-effective for pregnant patients and those contra-indicated for CT. Conclusion: This study highlighted the value of economic modelling to inform judicious use of resources in achieving a diagnosis for PE. These findings, in conjunction with a recent health technology assessment, may help to inform clinical practice and guidelines. Which strategy would be considered cost-effective reflected ones willingness to trade-off between misdiagnosis and over-diagnosis.

Clinical prediction rules for mortality in patients with pulmonary embolism and cancer to guide outpatient management: a meta‐analysis

Background Cancer treatment is commonly complicated by pulmonary embolism (PE), which remains a leading cause of morbidity and mortality in these patients. Some guidelines recommend the use of clinical prediction rules (CPRs) to help clinicians identify patients at low risk of mortality and therefore guide care. Objective To determine and compare the accuracy of available CPRs for identifying cancer patients with PE at low risk of mortality. Methods A literature search of Medline and Scopus (January 2000 to August 2017) was performed. Studies deriving/validating ≥1 CPR for early post-PE all-cause mortality were included. A bivariate, random-effects model was used to pool sensitivity and specificity estimates for each CPR. Traditional random-effects meta-analysis was performed to estimate the weighted proportion of patients deemed at low risk of early mortality, mortality in low risk patients and odds ratios for death compared with higher-risk patients. Results Eight studies evaluating 10 CPRs were included. The highest sensitivities were observed with Hestia (98.1%, 95% confidence interval [CI]=75.6-99.9%) and the EPIPHANY index (97.4%, 95% CI=93.2-99.0%); sensitivities of remaining rules ranged from 59.9 to 96.6%. Of the six CPRs with sensitivities ≥95%, none had specificities >33%. Random-effects meta-analysis suggested that 6.6-51.6% of cancer patients with PE were at low risk of mortality, 0-14.3% of low-risk patients died and low-risk patients had a 43-94% lower odds of death compared with those at higher risk. Conclusions Because of the limited total body of evidence regarding CPRs, their results, in conjunction with other pertinent patient-specific clinical factors, should continue to be used in identifying appropriate management for PE in patients with cancer.

Validity and reliability of clinical prediction rules used to screen for cervical spine injury in alert low-risk patients with blunt trauma to the neck: part 2. A systematic review from the Cervical Assessment and Diagnosis Research Evaluation (CADRE) Collaboration.

To update findings of the 2000-2010 Bone and Joint Decade Task Force on Neck Pain and its Associated Disorders (Neck Pain Task Force) on the validity and reliability of clinical prediction rules used to screen for cervical spine injury in alert low-risk adult patients with blunt trauma to the neck. We searched four databases from 2005 to 2015. Pairs of independent reviewers critically appraised eligible studies using the modified QUADAS-2 and QAREL criteria. We synthesized low risk of bias studies following best evidence synthesis principles. We screened 679 citations; five had a low risk of bias and were included in our synthesis. The sensitivity of the Canadian C-spine rule ranged from 0.90 to 1.00 with negative predictive values ranging from 99 to 100%. Inter-rater reliability of the Canadian C-spine rule varied from k=0.60 between nurses and physicians to k=0.93 among paramedics. The inter-rater reliability of the Nexus Low-Risk Criteria was k=0.53 between resident physicians and faculty physicians. Our review adds new evidence to the Neck Pain Task Force and supports the use of clinical prediction rules in emergency care settings to screen for cervical spine injury in alert low-risk adult patients with blunt trauma to the neck. The Canadian C-spine rule consistently demonstrated excellent sensitivity and negative predictive values. Our review, however, suggests that the reproducibility of the clinical predictions rules varies depending on the examiners level of training and experience.

Familiarity With and Use of Clinical Prediction Rules and Patient-Rated Outcome Measures

Familiarity With and Use of Clinical Prediction Rules and Patient-Rated Outcome Measures

Approach to Suspected Acute Pulmonary Embolism: Should We Use Scoring Systems?

Modern diagnostic strategies for pulmonary embolism diagnosis almost all rely on an initial assessment of the pretest probability. Clinical prediction rules are decision-making tools using combinations of easily available clinical predictors to define the probability of a disease. The assessment of the clinical probability of pulmonary embolism has an important impact on the diagnostic strategy and on therapeutic management. Clinical prediction rules provide accurate and reproducible estimates of clinical probability. They should be derived and validated following strict methodological standards. The use of clinical prediction rules should be encouraged, since their implementation in local guidelines for pulmonary embolism diagnosis has been shown to improve patients' outcomes.

Review of nucleic acid amplification tests and clinical prediction rules for diagnosis of tuberculosis in acute care facilities.

Tuberculosis (TB) remains an important cause of hospitalization and mortality in the United States. Prevention of TB transmission in acute care facilities relies on prompt identification and implementation of airborne isolation, rapid diagnosis, and treatment of presumptive pulmonary TB patients. In areas with low TB burden, this strategy may result in inefficient utilization of airborne infection isolation rooms (AIIRs). We reviewed TB epidemiology and diagnostic approaches to inform optimal TB detection in low-burden settings. Published clinical prediction rules for individual studies have a sensitivity ranging from 81% to 100% and specificity ranging from 14% to 63% for detection of culture-positive pulmonary TB patients admitted to acute care facilities. Nucleic acid amplification tests (NAATs) have a specificity of >98%, and the sensitivity of NAATs varies by acid-fast bacilli sputum smear status (positive smear, ≥95%; negative smear, 50%-70%). We propose an infection prevention strategy using a clinical prediction rule to identify patients who warrant diagnostic evaluation for TB in an AIIR with an NAAT. Future studies are needed to evaluate whether use of clinical prediction rules and NAATs results in optimized utilization of AIIRs and improved detection and treatment of presumptive pulmonary TB patients.

A Multistep Maturity Model for the Implementation of Electronic and Computable Diagnostic Clinical Prediction Rules (eCPRs).

Introduction:The use of Clinical Prediction Rules (CPRs) has been advocated as one way of implementing actionable evidence-based rules in clinical practice. The current highly manual nature of deriving CPRs makes them difficult to use and maintain. Addressing the known limitations of CPRs requires implementing more flexible and dynamic models of CPR development. We describe the application of Information and Communication Technology (ICT) to provide a platform for the derivation and dissemination of CPRs derived through analysis and continual learning from electronic patient data.Model Components:We propose a multistep maturity model for constructing electronic and computable CPRs (eCPRs). The model has six levels – from the lowest level of CPR maturity (literaturebased CPRs) to a fully electronic and computable service-oriented model of CPRs that are sensitive to specific demographic patient populations. We describe examples of implementations of the core model components – focusing on CPR representation, interoperability, electronic dissemination, CPR learning, and user interface requirements.Conclusion:The traditional focus on derivation and narrow validation of CPRs has severely limited their wider acceptance. The evolution and maturity model described here outlines a progression toward eCPRs consistent with the vision of a learning health system (LHS) – using central repositories of CPR knowledge, accessible open standards, and generalizable models to avoid repetition of previous work. This is useful for developing more ambitious strategies to address limitations of the traditional CPR development life cycle. The model described here is a starting point for promoting discussion about what a more dynamic CPR development process should look like.

Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: A sociotechnical analysis

Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making.

Systematic Review of Randomized Controlled Trials of Clinical Prediction Rules for Physical Therapy in Low Back Pain

Systematic review. To evaluate randomized controlled trials validating the effects of a clinical prediction rule for patients with non-specific low back pain (LBP). The outcomes of interest were any back pain or pain-related measures. LBP is a common and costly condition. Interventions for back pain seem to have, at best, small to moderate mean beneficial effects. Identifying subgroups of patients who may respond better to certain treatments may help to improve clinical outcomes in back pain. The development of clinical prediction rules is an attempt to determine who will respond best to certain treatments. We conducted electronic searches of MEDLINE (1980-2009), EMBASE (1980-2009), PsycINFO (1980-2009), Allied and Complementary Medicine (1980-2009), PubMed (1980-2009), ISI Web of Knowledge (1980-2009), and the Cochrane Library (1980-2009). The reference lists of relevant articles were searched for further references. We identified 1821 potential citations; 3 articles were included. The results from the available data do not support the use of clinical prediction rules in the management of non-specific LBP. There is a lack of good quality randomized controlled trials validating the effects of a clinical prediction rule for LBP. Furthermore, there is no agreement on appropriate methodology for the validation and impact analysis. The evidence for, and development of, the existing prediction rules is generally weak.

2009 evidence-based clinical practice guidelines for diagnosing a first episode of lower extremities deep vein thrombosis in ambulatory outpatients

The GRADE working group has recently suggested a rigorous framework for clinical practice guidelines (CPG) addressing diagnostic tests and test strategies based on the impact of alternative approaches on patient-important outcomes. The framework mandates explicit evidence summaries, ratings of the quality of evidence, and specifying recommendations as strong or weak. To test the feasibility and performance of the GRADE approach, we applied this framework to well-researched issues in the diagnoses of deep venous thrombosis (DVT). A 16-member panel with interest in thromboembolism and CPG development identified pertinent clinical questions. Our search for relevant studies included existing CPG and systematic reviews. We summarized the data in form of evidence tables and developed recommendations including, when needed, a formal consensus process. We provide three groups of recommendations for clinicians practicing in settings with access to different types of D-dimer tests -- highly sensitive, moderately sensitive, and no availability of D-dimer. We consider the use of clinical prediction rules in guiding the diagnostic process, the potential for negative D-dimer or venous ultrasound (US) to rule out disease, and the role of follow-up testing (US following positive D-dimer result, D-dimer following negative US, and serial US) depending on the probability of DVT at the start of diagnostic process. We recommend the following: that clinicians without access to a highly or moderately sensitive D-dimer test rely on US to guide DVT diagnosis; that those with access use the highly sensitive D-dimer to determine, in patients with low or moderate probability of DVT (by the Wells rule) whether US is needed; that in patients with low pre-test probability (pre-TP) and a negative D-dimer (either highly or moderately sensitive) they follow patients without further testing; that in patients with high pre-test probability they perform a compression ultrasound without D-dimer testing.

Diagnosis and management of venous thromboembolism: Results of a survey on current clinical practice

Background The implementation of evidence from clinical studies into daily clinical practice is not a straightforward process. We developed a standardized questionnaire to explore clinical practice patterns in the management of VTE, in particular about the use of pre-clinical probability and D-dimer testing and on the home treatment of pulmonary embolism (PE). Methods The standardized questionnaire was sent to all 394 physician members of the Italian Society of Thrombosis and Haemostasis (SISET) by e-mail. The questionnaire contained three groups of questions: about general information, about the diagnostic process for both deep venous thrombosis (DVT) and PE, and about home-therapy of PE. Results One hundred and twenty-eight (32.5%) physicians responded the questionnaire. For DVT diagnosis 69 (54.3%) physicians answered that they always use the D-dimer test; 4 (3.1%) do never use it; whereas only 11 (8.7%) take notice of the D-dimer result before visiting the patients; 38 (29.9%) use only clinical judgment to assess pre-clinical probability of disease. For the diagnosis of PE 80 (66.1%) physicians always use the D-dimer test, whereas 3 (2.5%) do never use it; whereas 14 (11.7%) take notice of the D-dimer result before visiting the patients; 50 (41.3%) use only clinical judgment to assess pre-clinical probability. Sixty-six (59.5%) clinicians declared to treat patients with PE at home, when feasible. Conclusion The diagnostic approach to VTE among expert physicians appears to be heterogeneous; in particular there is no widespread use of clinical prediction rules. The majority of expert physicians appear to consider the possibility of treating at home patients with PE.