Anil N. Makam

Use of cardiac biomarker testing in the emergency department.

IMPORTANCE Cardiac biomarker testing is not routinely indicated in the emergency department (ED) because of low utility and potential downstream harms from false-positive results. However, current rates of testing are unknown. OBJECTIVE To determine the use of cardiac biomarker testing overall, as well as stratified by disposition status and selected characteristics. DESIGN, SETTING, AND PARTICIPANTS Retrospective study of ED visits by adults (≥18 years old) selected from the 2009 and 2010 National Hospital Ambulatory Medical Care Survey, a probability sample of ED visits in the United States. EXPOSURES Selected patient, visit, and ED characteristics. MAIN OUTCOMES AND MEASURES Receipt of cardiac biomarker testing during the ED visit. RESULTS Of 44,448 ED visits, cardiac biomarkers were tested in 16.9% of visits, representing 28.6 million visits. Biomarker testing occurred in 8.2% of visits in the absence of acute coronary syndrome (ACS)-related symptoms, representing 8.5 million visits, almost one-third of all visits with biomarker testing. Among individuals subsequently hospitalized, cardiac biomarkers were tested in 47.0% of all visits. In this group, biomarkers were tested in 35.4% of visits despite the absence of ACS-related symptoms. Among all ED visits, the number of other tests or services performed was the strongest predictor of biomarker testing independent of symptoms of ACS. Compared with 0 to 5 other tests or services performed, more than 10 other tests or services performed was associated with 59.55 (95% CI, 39.23-90.40) times the odds of biomarker testing. The adjusted probabilities of biomarker testing if 0 to 5, 6 to 10, or more than 10 other tests or services performed were 6.3%, 34.3%, and 62.3%, respectively. CONCLUSIONS AND RELEVANCE Cardiac biomarker testing in the ED is common even among those without symptoms suggestive of ACS. Cardiac biomarker testing is also frequently used during visits with a high volume of other tests or services independent of the clinical presentation. More attention is needed to develop strategies for appropriate use of cardiac biomarkers.

Identifying patients with diabetes and the earliest date of diagnosis in real time: an electronic health record case-finding algorithm

BackgroundEffective population management of patients with diabetes requires timely recognition. Current case-finding algorithms can accurately detect patients with diabetes, but lack real-time identification. We sought to develop and validate an automated, real-time diabetes case-finding algorithm to identify patients with diabetes at the earliest possible date.MethodsThe source population included 160,872 unique patients from a large public hospital system between January 2009 and April 2011. A diabetes case-finding algorithm was iteratively derived using chart review and subsequently validated (n = 343) in a stratified random sample of patients, using data extracted from the electronic health records (EHR). A point-based algorithm using encounter diagnoses, clinical history, pharmacy data, and laboratory results was used to identify diabetes cases. The date when accumulated points reached a specified threshold equated to the diagnosis date. Physician chart review served as the gold standard.ResultsThe electronic model had a sensitivity of 97%, specificity of 90%, positive predictive value of 90%, and negative predictive value of 96% for the identification of patients with diabetes. The kappa score for agreement between the model and physician for the diagnosis date allowing for a 3-month delay was 0.97, where 78.4% of cases had exact agreement on the precise date.ConclusionsA diabetes case-finding algorithm using data exclusively extracted from a comprehensive EHR can accurately identify patients with diabetes at the earliest possible date within a healthcare system. The real-time capability may enable proactive disease management.

Envisioning a Social-Health Information Exchange as a Platform to Support a Patient-Centered Medical Neighborhood: A Feasibility Study

ABSTRACTBACKGROUNDSocial determinants directly contribute to poorer health, and coordination between healthcare and community-based resources is pivotal to addressing these needs. However, our healthcare system remains poorly equipped to address social determinants of health. The potential of health information technology to bridge this gap across the delivery of healthcare and social services remains unrealized.OBJECTIVE, DESIGN, AND PARTICIPANTSWe conducted in-depth, in-person interviews with 50 healthcare and social service providers to determine the feasibility of a social-health information exchange (S-HIE) in an urban safety-net setting in Dallas County, Texas. After completion of interviews, we conducted a town hall meeting to identify desired functionalities for a S-HIE.APPROACHWe conducted thematic analysis of interview responses using the constant comparative method to explore perceptions about current communication and coordination across sectors, and barriers and enablers to S-HIE implementation. We sought participant confirmation of findings and conducted a forced-rank vote during the town hall to prioritize potential S-HIE functionalities.KEY RESULTSWe found that healthcare and social service providers perceived a need for improved information sharing, communication, and care coordination across sectors and were enthusiastic about the potential of a S-HIE, but shared many technical, legal, and ethical concerns around cross-sector information sharing. Desired technical S-HIE functionalities encompassed fairly simple transactional operations such as the ability to view basic demographic information, visit and referral data, and medical history from both healthcare and social service settings.CONCLUSIONSA S-HIE is an innovative and feasible approach to enabling better linkages between healthcare and social service providers. However, to develop S-HIEs in communities across the country, policy interventions are needed to standardize regulatory requirements, to foster increased IT capability and uptake among social service agencies, and to align healthcare and social service priorities to enable dissemination and broader adoption of this and similar IT initiatives.

Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: A systematic review

BACKGROUND Although timely treatment of sepsis improves outcomes, delays in administering evidence-based therapies are common. PURPOSE To determine whether automated real-time electronic sepsis alerts can: (1) accurately identify sepsis and (2) improve process measures and outcomes. DATA SOURCES We systematically searched MEDLINE, Embase, The Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature from database inception through June 27, 2014. STUDY SELECTION Included studies that empirically evaluated 1 or both of the prespecified objectives. DATA EXTRACTION Two independent reviewers extracted data and assessed the risk of bias. Diagnostic accuracy of sepsis identification was measured by sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratio (LR). Effectiveness was assessed by changes in sepsis care process measures and outcomes. DATA SYNTHESIS Of 1293 citations, 8 studies met inclusion criteria, 5 for the identification of sepsis (n = 35,423) and 5 for the effectiveness of sepsis alerts (n = 6894). Though definition of sepsis alert thresholds varied, most included systemic inflammatory response syndrome criteria ± evidence of shock. Diagnostic accuracy varied greatly, with PPV ranging from 20.5% to 53.8%, NPV 76.5% to 99.7%, LR+ 1.2 to 145.8, and LR- 0.06 to 0.86. There was modest evidence for improvement in process measures (ie, antibiotic escalation), but only among patients in non-critical care settings; there were no corresponding improvements in mortality or length of stay. Minimal data were reported on potential harms due to false positive alerts. CONCLUSIONS Automated sepsis alerts derived from electronic health data may improve care processes but tend to have poor PPV and do not improve mortality or length of stay.

Blood Culture Use in the Emergency Department in Patients Hospitalized for Community-Acquired Pneumonia

To the Editor: Routine blood cultures for all patients hospitalized with community-acquired pneumonia have limited utility, and false-positive results lead to inappropriate antimicrobial use and longer hospital stays.1 As a result, performance measures and practice guidelines that promoted obtaining blood cultures in all such patients were modified in 2005–2007 to recommend routine collection in only the sickest patients.1, 2 Using a national sample of emergency department (ED) visits, we examined patterns of obtaining cultures in adults hospitalized with community-acquired pneumonia.

Factors associated with primary vein graft occlusion in a multicenter trial with mandated ultrasound surveillance

OBJECTIVE Even in the setting of duplex ultrasound (DUS) surveillance, a significant number of lower extremity vein bypass grafts (LEVBGs) become occluded as a first event. We sought to identify factors that may contribute to these primary occlusions. METHODS This was a retrospective analysis of the Project of Ex Vivo Graft Engineering via Transfection III (PREVENT III) multicenter randomized clinical trial, in which 1404 patients with critical limb ischemia (CLI) underwent LEVBG with 1-year follow-up. Subjects were to undergo DUS at regular intervals (1, 3, 6, and 12 months), with reintervention based on prespecified DUS criteria. Patients who had nontechnical graft occlusion as the initial graft-related event were identified, and multivariate analysis was used to determine factors associated with primary graft occlusion. RESULTS Primary vein graft occlusion occurred in 200 subjects and accounted for 36% of all primary patency events and 64% of all graft occlusions in the trial. Primary occlusion events were evenly distributed throughout the first postoperative year. Rates of recurrent CLI, loss of secondary patency, and major amputation in those with primary occlusion were 55%, 79%, and 22% respectively as compared to 18%, 10%, and 10% for subjects without primary occlusion (P < .001). On multivariate analysis, African-American race (subdistribution hazard ratio [SHR], 1.50; 95% confidence interval [CI], 1.06-2.12), a graft diameter <3 mm (SHR, 2.31; 95% CI, 1.33-4.01), and nonadherence with ultrasound surveillance (SHR, 1.58; 95% CI, 1.10-2.27) were independently associated with primary graft occlusion. Of the 123 subjects who received their last scheduled surveillance DUS prior to a primary occlusion event, 39 had a critical ultrasound abnormality identified but failed to undergo graft revision, while 84 had no critical ultrasound abnormality identified. Among these 84 subjects, female gender (SHR, 1.65; 95% CI, 1.07-2.54), and graft diameter <3 mm (SHR, 2.12; 95% CI, 1.03-4.37) were independent factors associated with unheralded graft occlusion. CONCLUSIONS Among patients undergoing LEVBG for CLI, almost half of primary patency events are occlusions even in the setting of a DUS surveillance protocol. African Americans, patients with smaller-diameter grafts, and those who are nonadherent with surveillance ultrasound are at increased risk. Failure to intervene on critical findings, and lack of sensitivity of DUS threshold criteria to predict thrombosis, are also important contributors. These findings suggest that prevention of vein graft thrombosis requires further improvements in risk stratification, surveillance, and the timing of reinterventions.

An Evidence-Based Medicine Approach to Antihyperglycemic Therapy in Diabetes Mellitus to Overcome Overtreatment

Overtreatment is pervasive in medicine and leads to potential patient harms and excessive costs in health care. Although evidence-based medicine is often derided as practice by rote algorithmic medicine, the appropriate application of key evidence-based medicine principles in clinical decision making is fundamental to preventing overtreatment and promoting high-value, individualized patient-centered care. Specifically, this article discusses the importance of (1) using absolute rather than relative estimates of benefits to inform treatment decisions; (2) considering the time horizon to benefit of treatments; (3) balancing potential harms and benefits; and (4) using shared decision making by physicians to incorporate the patient’s values and preferences into treatment decisions. Here, we illustrate the application of these principles to considering the decision of whether or not to recommend intensive glycemic control to patients to minimize microvascular and cardiovascular complications in type 2 diabetes mellitus. Through this lens, this example will illustrate how an evidence-based medicine approach can be used to individualize glycemic goals and prevent overtreatment, and can serve as a template for applying evidence-based medicine to inform treatment decisions for other conditions to optimize health and individualize patient care.

Clinical Criteria to Identify Patients With Sepsis

Clinical Criteria to Identify Patients With Sepsis To the Editor Dr Seymour and colleagues1 assessed the predictive validity of various clinical criteria to identify patients with sepsis. However, their conclusion that the Sequential [Sepsisrelated] Organ Failure Assessment (SOFA) and quick SOFA (qSOFA) scores are more clinically useful than the systemic inflammatory response syndrome (SIRS) criteria was primarily based on differences in the area under the receiver operating curve (AUROC), which has several limitations.2 First, differences in the AUROC may be of minimal clinical relevance. For example, although the American College of Cardiology/American Heart Association (ACC/AHA) and the Adult Treatment Panel III cardiovascular risk prediction models have similar AUROCs, the ACC/AHA model recommends statin therapy for more adults and better reclassifies patients according to their true risk (net reclassification index [NRI], 0.332).3,4 To better assess for clinically meaningful differences in the utility of different sepsis diagnostic criteria, the authors should report the overall categorical NRI (for ≥2 vs <2 points), event and nonevent NRIs, and risk reclassification tables. Second, Seymour and colleagues proposed implementing both the SOFA and qSOFA scores in practice by defining patients with scores of 2 points or greater as having “sepsis” and those with less than 2 points as not having sepsis. However, the reported AUROCs were calculated using continuous scores. Assessing the performance of each set of clinical criteria using the dichotomous categorization and reporting the positive and negative predictive values and corresponding likelihood ratios compared with the SIRS criteria would be more clinically relevant than reporting the differences in the AUROC or the relative difference in outcomes across deciles of baseline risk. Most important, it is unclear that the lower AUROC reflects inferior predictive validity of the SIRS criteria. Rather, the lower AUROC (and relative fold difference in outcomes) may reflect the influence of incorporation bias. The current standard of care for clinicians during the period of this study was to initiate early goal-directed therapy for patients with suspected sepsis based on SIRS criteria. Thus, the lower performance of SIRS for predicting mortality may simply be an artifact—patients diagnosed as having sepsis by 2 or more SIRS criteria were more likely to have received early goal-directed therapy and less likely to die as a consequence.5 Before the current diagnostic criteria for sepsis are replaced, we believe that more robust analyses are needed, including a prospective study of the utility of these various clinical criteria that would eliminate the influence of incorporation bias.

Risk of Thiazide-Induced Metabolic Adverse Events in Older Adults

To evaluate the risk and predictors of thiazide‐induced adverse events (AEs) in multimorbid older adults in real‐world clinical settings.

Is everyone really breathing 20 times a minute? Assessing epidemiology and variation in recorded respiratory rate in hospitalised adults

Background Respiratory rate (RR) is an independent predictor of adverse outcomes and an integral component of many risk prediction scores for hospitalised adults. Yet, it is unclear if RR is recorded accurately. We sought to assess the potential accuracy of RR by analysing the distribution and variation as a proxy, since RR should be normally distributed if recorded accurately. Methods We conducted a descriptive observational study of electronic health record data from consecutive hospitalisations from 2009 to 2010 from six diverse hospitals. We assessed the distribution of the maximum RR on admission, using heart rate (HR) as a comparison since this is objectively measured. We assessed RR patterns among selected subgroups expected to have greater physiological variation using the coefficient of variation (CV=SD/mean). Results Among 36 966 hospitalisations, recorded RR was not normally distributed (p<0.001), but right skewed (skewness=3.99) with values clustered at 18 and 20 (kurtosis=23.9). In contrast, HR was relatively normally distributed. Patients with a cardiopulmonary diagnosis or hypoxia only had modestly greater variation (CV increase of 2%–6%). Among 1318 patients transferred from the ward to the intensive care unit (n=1318), RR variation the day preceding transfer was similar to that observed on admission (CV 0.24 vs 0.26), even for those transferred with respiratory failure (CV 0.25). Conclusions The observed patterns suggest that RR is inaccurately recorded, even among those with cardiopulmonary compromise, and represents a ‘spot’ estimate with values of 18 and 20 breaths per minute representing ‘normal.’ While spot estimates may potentially be adequate to indicate clinical stability, inaccurate RR may alternatively lead to misclassification of disease severity, potentially jeopardising patient safety. Thus, we recommend greater training for hospital personnel to accurately record RR.