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OBJECTIVES: To determine if a real-time monitoring system with automated clinician alerts improves 3-hour sepsis bundle adherence. DESIGN: Prospective, pragmatic clinical trial. Allocation alternated every 7 days. SETTING: Quaternary hospital from December 1, 2020 to November 30, 2021. PATIENTS: Adult emergency department or inpatients meeting objective sepsis criteria triggered an electronic medical record (EMR)-embedded best practice advisory. Enrollment occurred when clinicians acknowledged the advisory indicating they felt sepsis was likely. INTERVENTION: Real-time automated EMR monitoring identified suspected sepsis patients with incomplete bundle measures within 1-hour of completion deadlines and generated reminder pages. Clinicians responsible for intervention group patients received reminder pages; no pages were sent for controls. The primary analysis cohort was the subset of enrolled patients at risk of bundle nonadherent care that had reminder pages generated. MEASUREMENTS AND MAIN RESULTS: The primary outcome was orders for all 3-hour bundle elements within guideline time limits. Secondary outcomes included guideline-adherent delivery of all 3-hour bundle elements, 28-day mortality, antibiotic discontinuation within 48-hours, and pathogen recovery from any culture within 7 days of time-zero. Among 3,269 enrolled patients, 1,377 had reminder pages generated and were included in the primary analysis. There were 670 (48.7%) at-risk patients randomized to paging alerts and 707 (51.3%) to control. Bundle-adherent orders were placed for 198 intervention patients (29.6%) versus 149 (21.1%) controls (difference: 8.5%; 95% CI, 3.9-13.1%; p = 0.0003). Bundle-adherent care was delivered for 152 (22.7%) intervention versus 121 (17.1%) control patients (difference: 5.6%; 95% CI, 1.4-9.8%; p = 0.0095). Mortality was similar between groups (8.4% vs 8.3%), as were early antibiotic discontinuation (35.1% vs 33.4%) and pan-culture negativity (69.0% vs 68.2%). CONCLUSIONS: Real-time monitoring and paging alerts significantly increased orders for and delivery of guideline-adherent care for suspected sepsis patients at risk of 3-hour bundle nonadherence. The trial was underpowered to determine whether adherence affected mortality. Despite enrolling patients with clinically suspected sepsis, early antibiotic discontinuation and pan-culture negativity were common, highlighting challenges in identifying appropriate patients for sepsis bundle application.
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Sepse , Choque Séptico , Adulto , Humanos , Estudos Prospectivos , Retroalimentação , Mortalidade Hospitalar , Antibacterianos/uso terapêutico , Fidelidade a DiretrizesRESUMO
STUDY OBJECTIVE: Procedural competency is essential to the practice of emergency medicine. However, there are limited data quantifying emergency department procedural volumes to inform the work of educators and credentialing bodies. In this study, we characterize procedural scope and volume in a regional health care system and compare rates between practice settings and over time. METHODS: Cross-sectional data were acquired from electronic medical records of a regional health care system from March 2017 through February 2022. Nonspecific entries, esoteric procedures, and nonprocedural clinical skills were excluded. Procedural rates were compared: (1) between academic and community hospitals, (2) across study years, and (3) across seasons. Analyses were repeated for pediatric encounters, and with study year 4 removed to assess the influence of the first year of the coronavirus disease 2019 pandemic on results. RESULTS: There were 131,976 instances of 40 qualifying procedures in 1,979,935 unique visits across 9 EDs. Several high-acuity procedures had similar rates in academic and community settings, including cardiac pacing, cricothyrotomy, and lateral canthotomy. Year-over-year procedural rates were stable or increasing for most procedures, with a notable exception of lumbar puncture. Most procedures did not have significant seasonal variation, and most findings were stable when study year 4 was removed from the analysis. CONCLUSION: All procedures were performed in all settings and rates of several emergent procedures were similar in both settings, underscoring the importance of broad procedural competence for all emergency physicians. Educators and credentialing organizations can use these data to inform decisions regarding curriculum design and certification requirements.
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COVID-19 , Medicina de Emergência , Humanos , Criança , Serviço Hospitalar de Emergência , Estudos Transversais , COVID-19/epidemiologia , Medicina de Emergência/educação , Atenção à Saúde , Competência ClínicaRESUMO
STUDY OBJECTIVE: Early notification of admissions from the emergency department (ED) may allow hospitals to plan for inpatient bed demand. This study aimed to assess Epic's ED Likelihood to Occupy an Inpatient Bed predictive model and its application in improving hospital bed planning workflows. METHODS: All ED adult (18 years and older) visits from September 2021 to August 2022 at a large regional health care system were included. The primary outcome was inpatient admission. The predictive model is a random forest algorithm that uses demographic and clinical features. The model was implemented prospectively, with scores generated every 15 minutes. The area under the receiver operator curves (AUROC) and precision-recall curves (AUPRC) were calculated using the maximum score prior to the outcome and for each prediction independently. Test characteristics and lead time were calculated over a range of model score thresholds. RESULTS: Over 11 months, 329,194 encounters were evaluated, with an incidence of inpatient admission of 25.4%. The encounter-level AUROC was 0.849 (95% confidence interval [CI], 0.848 to 0.851), and the AUPRC was 0.643 (95% CI, 0.640 to 0.647). With a prediction horizon of 6 hours, the AUROC was 0.758 (95% CI, 0.758 to 0.759,) and the AUPRC was 0.470 (95% CI, 0.469 to 0.471). At a predictive model threshold of 40, the sensitivity was 0.49, the positive predictive value was 0.65, and the median lead-time warning was 127 minutes before the inpatient bed request. CONCLUSION: The Epic ED Likelihood to Occupy an Inpatient Bed model may improve hospital bed planning workflows. Further study is needed to determine its operational effect.
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Pacientes Internados , Admissão do Paciente , Adulto , Humanos , Estudos Prospectivos , Hospitalização , Serviço Hospitalar de Emergência , Estudos RetrospectivosRESUMO
STUDY OBJECTIVE: Delays in the second dose of antibiotics in the emergency department (ED) are associated with increased morbidity and mortality in patients with serious infections. We analyzed the influence of clinical decision support to prevent delays in second doses of broad-spectrum antibiotics in the ED. METHODS: We allocated adult patients who received cefepime or piperacillin/tazobactam in 9 EDs within an integrated health care system to an electronic alert that reminded ED clinicians to reorder antibiotics at the appropriate interval vs usual care. The primary outcome was a median delay in antibiotic administration. Secondary outcomes were rates of intensive care unit (ICU) admission, hospital mortality, and hospital length of stay. We included a post hoc secondary outcome of frequency of major delay (>25% of expected interval for second antibiotic dose). RESULTS: A total of 1,113 ED patients treated with cefepime or piperacillin/tazobactam were enrolled in the study, of whom 420 remained under ED care when their second dose was due and were included in the final analysis. The clinical decision support tool was associated with reduced antibiotic delays (median difference 35 minutes, 95% confidence interval [CI], 5 to 65). There were no differences in ICU transfers, inpatient mortality, or hospital length of stay. The clinical decision support tool was associated with decreased probability of major delay (absolute risk reduction 13%, 95% CI, 6 to 20). CONCLUSIONS: The implementation of a clinical decision support alert reminding clinicians to reorder second doses of antibiotics was associated with a reduction in the length and frequency of antibiotic delays in the ED. There was no effect on the rates of ICU transfers, inpatient mortality, or hospital length of stay.
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Antibacterianos , Hospitalização , Adulto , Humanos , Antibacterianos/uso terapêutico , Cefepima , Combinação Piperacilina e Tazobactam , Serviço Hospitalar de Emergência , Tempo de Internação , Estudos RetrospectivosRESUMO
INTRODUCTION: ED health care professionals are at the frontline of evaluation and management of patients with acute, and often undifferentiated, illness. During the initial phase of the SARS-CoV-2 outbreak, there were concerns that ED health care professionals may have been at increased risk of exposure to SARS-CoV-2 due to difficulty in early identification of patients. This study assessed the seroprevalence of SARS-CoV-2 antibodies among ED health care professionals without confirmed history of COVID-19 infection at a quaternary academic medical center. METHODS: This study used a cross-sectional design. An ED health care professional was deemed eligible if they had worked at least 4 shifts in the adult emergency department from April 1, 2020, through May 31, 2020, were asymptomatic on the day of blood draw, and were not known to have had prior documented COVID-19 infection. The study period was December 17, 2020, to January 27, 2021. Eligible participants completed a questionnaire and had a blood sample drawn. Samples were run on the Roche Cobas Elecsys Anti-SARS-CoV-2 antibody assay. RESULTS: Of 103 health care professionals (16 attending physicians, 4 emergency residents, 16 advanced practice professionals, and 67 full-time emergency nurses), only 3 (2.9%; exact 95% CI, 0.6%-8.3%) were seropositive for SARS-CoV-2 antibodies. DISCUSSION: At this quaternary academic medical center, among those who volunteered to take an antibody test, there was a low seroprevalence of SARS-CoV-2 antibodies among ED clinicians who were asymptomatic at the time of blood draw and not known to have had prior COVID-19 infection.
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COVID-19 , Adulto , Anticorpos Antivirais , COVID-19/epidemiologia , Estudos Transversais , Pessoal de Saúde , Humanos , SARS-CoV-2 , Estudos SoroepidemiológicosRESUMO
BACKGROUND: US hospitals are required by the Centers for Medicare and Medicaid Services to publicly report central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), Clostridioidesdiffficile, methicillin-resistant Staphylococcus aureus bacteremia, and selected surgical site infections for benchmarking and pay-for-performance programs. It is unclear, however, to what extent these conditions capture the full breadth of serious healthcare-associated infections (HAIs). The Centers for Disease Control and Prevention's (CDC's) hospital-onset Adult Sepsis Event (HO-ASE) definition could facilitate more comprehensive and efficient surveillance for serious HAIs, but the overlap between HO-ASE and currently reportable HAIs is unknown. METHODS: We retrospectively assessed the overlap between HO-ASEs and reportable HAIs among adults hospitalized between June 2015-June 2018 in 3 hospitals. Medical record reviews were conducted for 110 randomly selected HO-ASE cases to determine clinical correlates. RESULTS: Among 282 441 hospitalized patients, 2301 (0.8%) met HO-ASE criteria and 1260 (0.4%) had reportable HAIs. In-hospital mortality rates were higher with HO-ASEs than reportable HAIs (28.6% vs 12.9%). Mortality rates for HO-ASE missed by reportable HAIs were substantially higher than mortality rates for reportable HAIs missed by HO-ASE (28.1% vs 6.3%). Reportable HAIs were only present in 334/2301 (14.5%) HO-ASEs, most commonly CLABSIs (6.0% of HO-ASEs), C. difficile (5.0%), and CAUTIs (3.0%). On medical record review, most HO-ASEs were caused by pneumonia (39.1%, of which only 34.9% were ventilator-associated), bloodstream infections (17.4%, of which only 10.5% were central line-associated), non-C. difficile intra-abdominal infections (14.5%), urinary infections (7.3%, of which 87.5% were catheter-associated), and skin/soft tissue infections (6.4%). CONCLUSIONS: CDC's HO-ASE definition detects many serious nosocomial infections missed by currently reportable HAIs. HO-ASE surveillance could increase the efficiency and clinical significance of surveillance while identifying new targets for prevention.
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Infecções Relacionadas a Cateter , Clostridioides difficile , Infecção Hospitalar , Staphylococcus aureus Resistente à Meticilina , Pneumonia Associada à Ventilação Mecânica , Sepse , Adulto , Idoso , Infecções Relacionadas a Cateter/epidemiologia , Infecção Hospitalar/epidemiologia , Atenção à Saúde , Hospitais , Humanos , Medicare , Reembolso de Incentivo , Estudos Retrospectivos , Sepse/epidemiologia , Estados Unidos/epidemiologiaRESUMO
BACKGROUND: Isolation of hospitalized persons under investigation (PUIs) for coronavirus disease 2019 (COVID-19) reduces nosocomial transmission risk. Efficient evaluation of PUIs is needed to preserve scarce healthcare resources. We describe the development, implementation, and outcomes of an inpatient diagnostic algorithm and clinical decision support system (CDSS) to evaluate PUIs. METHODS: We conducted a pre-post study of CORAL (COvid Risk cALculator), a CDSS that guides frontline clinicians through a risk-stratified COVID-19 diagnostic workup, removes transmission-based precautions when workup is complete and negative, and triages complex cases to infectious diseases (ID) physician review. Before CORAL, ID physicians reviewed all PUI records to guide workup and precautions. After CORAL, frontline clinicians evaluated PUIs directly using CORAL. We compared pre- and post-CORAL frequency of repeated severe acute respiratory syndrome coronavirus 2 nucleic acid amplification tests (NAATs), time from NAAT result to PUI status discontinuation, total duration of PUI status, and ID physician work hours, using linear and logistic regression, adjusted for COVID-19 incidence. RESULTS: Fewer PUIs underwent repeated testing after an initial negative NAAT after CORAL than before CORAL (54% vs 67%, respectively; adjusted odd ratio, 0.53 [95% confidence interval, .44-.63]; Pâ <â .01). CORAL significantly reduced average time to PUI status discontinuation (adjusted difference [standard error], -7.4 [0.8] hours per patient), total duration of PUI status (-19.5 [1.9] hours per patient), and average ID physician work-hours (-57.4 [2.0] hours per day) (all Pâ <â .01). No patients had a positive NAAT result within 7 days after discontinuation of precautions via CORAL. CONCLUSIONS: CORAL is an efficient and effective CDSS to guide frontline clinicians through the diagnostic evaluation of PUIs and safe discontinuation of precautions.
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Antozoários , COVID-19 , Animais , Humanos , Técnicas de Amplificação de Ácido Nucleico , Razão de Chances , SARS-CoV-2RESUMO
STUDY OBJECTIVE: Tetanus is the most common vaccination given in the emergency department; yet, administrations of tetanus vaccine boosters in the ED may not comply with the US Centers for Disease Control and Prevention's recommended vaccination schedule. We implemented a clinical decision support alert in the electronic health record that warned providers when ordering a tetanus vaccine if a prior one had been given within 10 years and studied its efficacy to reduce potentially unnecessary vaccines in the ED. METHODS: This was a retrospective, quasi-experimental, 1-group, pretest-posttest study in 3 hospital EDs in Boston, MA. We studied adult patients for whom tetanus vaccines were ordered despite a history of vaccination within the prior 10 years. We compared the number of potentially unnecessary tetanus vaccine administrations in a baseline phase (when the clinical decision support alert was not visible) versus an intervention phase. RESULTS: Of eligible patients, 22.1% (95% confidence interval [CI] 21.8% to 22.4%) had prior tetanus vaccines within 5 years, 12.8% (95% CI 12.5% to 13.0%) within 5 to 10 years, 3.8% (95% CI 3.6% to 3.9%) more than 10 years ago, and 61.3% (95% CI 60.9% to 61.7%) had no prior tetanus vaccination documentation. Of 60,983 encounters, 337 met the inclusion criteria. A tetanus vaccination was administered in 91% (95% CI 87% to 96%) of encounters in the baseline phase, compared to 55% (95% CI 47% to 62%) during the intervention. The absolute risk reduction was 36.7% (95% CI 28.0% to 45.4%), and the number of encounters needed to alert to avoid 1 potentially unnecessary tetanus vaccine (number needed to treat) was 2.7 (95% CI 2.2% to 3.6%). For patients with tetanus vaccines within the prior 5 years, the absolute risk reduction was 47.9% (95% CI 35.5 % to 60.3%) and the number needed to treat was 2.1 (95% CI 1.7% to 2.8%). CONCLUSION: A clinical decision support alert that warns ED clinicians that a patient may have an up-to-date tetanus vaccination status reduces potentially unnecessary vaccinations.
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Sistemas de Apoio a Decisões Clínicas/normas , Esquemas de Imunização , Toxoide Tetânico/administração & dosagem , Vacinação/estatística & dados numéricos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Serviço Hospitalar de Emergência/estatística & dados numéricos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Ensaios Clínicos Controlados não Aleatórios como Assunto , Melhoria de Qualidade , Estudos Retrospectivos , Toxoide Tetânico/efeitos adversos , Toxoide Tetânico/imunologia , Procedimentos Desnecessários , Adulto JovemRESUMO
BACKGROUND: The impact of alcohol or opioid use disorders on medication dosing for procedural sedation in the emergency department (ED) is unclear, as most of the literature is from gastrointestinal endoscopy. Exploring how these patient factors affect sedative and analgesic medications may inform more nuanced sedation strategies in the emergency department. METHODS: This was a retrospective chart-review cohort study across five EDs from 2015 to 2020. Included were adult patients who underwent procedural sedation in the ED, categorized into three a priori groups: alcohol use disorder (AUD), opioid use disorder (OUD), and individuals with neither (non-SUD). Wilcoxon test was used to compare the time-averaged dose of agents between groups. Logistic regression was used to model multi-agent sedations. The propofol time-averaged dose was the primary outcome. Secondary outcomes included other agents, sedation duration, and switching to other agents. RESULTS: 2725 sedations were included in the analysis. 59 patients had a history of AUD, and 40 had a history of OUD. Time-averaged doses of medications did not differ significantly between AUD and non-SUD patients. Likewise, patients with OUD did not receive different doses of medications compared to non-SUD. The propofol doses for non-SUD, AUD, and OUD were 0.033 IQR 0.04; 0.042 IQR 0.05; and 0.058 IQR 0.04 mg/kg*min, respectively. Sedation duration was not different across groups. Having AUD or OUD is not associated with increased odds of requiring multiple sedative agents. CONCLUSION: Although sedation in patients with AUD or OUD may be associated with significant case bias, these patient factors did not significantly alter outcomes compared to the general population. This study suggests there is no evidence to proactively adjust medication strategy in ED patients with AUD or OUD.
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Relação Dose-Resposta a Droga , Hipnóticos e Sedativos/administração & dosagem , Transtornos Relacionados ao Uso de Substâncias/complicações , Adulto , Idoso , Estudos de Coortes , Mineração de Dados , Serviço Hospitalar de Emergência/organização & administração , Serviço Hospitalar de Emergência/estatística & dados numéricos , Feminino , Humanos , Hipnóticos e Sedativos/uso terapêutico , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Transtornos Relacionados ao Uso de Substâncias/fisiopatologia , Resultado do TratamentoRESUMO
OBJECTIVE: Prior data suggest Emergency Department (ED) visits for many emergency conditions decreased during the initial COVID-19 surge. However, the pandemic's impact on the wide range of conditions seen in EDs, and the resources required for treating them, has been less studied. We sought to provide a comprehensive analysis of ED visits and associated resource utilization during the initial COVID-19 surge. METHODS: We performed a retrospective analysis from 5 hospitals in a large health system in Massachusetts, comparing ED encounters from 3/1/2020-4/30/2020 to identical weeks from the prior year. Data collected included demographics, ESI, diagnosis, consultations ordered, bedside procedures, and inpatient procedures within 48 h. We compared raw frequencies between time periods and calculated incidence rate ratios. RESULTS: ED volumes decreased by 30.9% in 2020 compared to 2019. Average acuity of ED presentations increased, while most non-COVID-19 diagnoses decreased. The number and incidence rate of all non-critical care ED procedures decreased, while the occurrence of intubations and central lines increased. Most subspecialty consultations decreased, including to psychiatry, trauma surgery, and cardiology. Most non-elective procedures related to ED encounters also decreased, including craniotomies and appendectomies. CONCLUSION: Our health system experienced decreases in nearly all non-COVID-19 conditions presenting to EDs during the initial phase of the pandemic, including those requiring specialty consultation and urgent inpatient procedures. Findings have implications for both public health and health system planning.
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COVID-19/epidemiologia , Gerenciamento Clínico , Serviço Hospitalar de Emergência/estatística & dados numéricos , Pandemias , COVID-19/terapia , Feminino , Seguimentos , Humanos , Masculino , Massachusetts/epidemiologia , Pessoa de Meia-Idade , Estudos Retrospectivos , SARS-CoV-2RESUMO
Importance: Patients with limited English proficiency (LEP) face multiple barriers and are at risk for worse health outcomes compared with patients with English proficiency (EP). In sepsis, a major cause of mortality in the US, the association of LEP with health outcomes is not widely explored. Objective: To assess the association between LEP and inpatient mortality among patients with sepsis and test the hypothesis that LEP would be associated with higher mortality rates. Design, Setting, and Participants: This retrospective cohort study of hospitalized patients with sepsis included those who met the Centers for Disease Control and Prevention's sepsis criteria, received antibiotics within 24 hours, and were admitted through the emergency department. Data were collected from the electronic medical records of a large New England tertiary care center from January 1, 2016, to December 31, 2019. Data were analyzed from January 8, 2021, to March 2, 2023. Exposures: Limited English proficiency, gathered via self-reported language preference in electronic medical records. Main Outcomes and Measures: The primary outcome was inpatient mortality. The analysis used multivariable generalized estimating equation models with propensity score adjustment and analysis of covariance to analyze the association between LEP and inpatient mortality due to sepsis. Results: A total of 2709 patients met the inclusion criteria, with a mean (SD) age of 65.0 (16.2) years; 1523 (56.2%) were men and 327 (12.1%) had LEP. Nine patients (0.3%) were American Indian or Alaska Native, 101 (3.7%) were Asian, 314 (11.6%) were Black, 226 (8.3%) were Hispanic, 38 (1.4%) were Native Hawaiian or Other Pacific Islander or of other race or ethnicity, 1968 (72.6%) were White, and 6 (0.2%) were multiracial. Unadjusted mortality included 466 of 2382 patients with EP (19.6%) and 69 of 327 with LEP (21.1%). No significant difference was found in mortality odds for the LEP compared with EP groups (odds ratio [OR], 1.12 [95% CI, 0.88-1.42]). When stratified by race and ethnicity, odds of inpatient mortality for patients with LEP were significantly higher among the non-Hispanic White subgroup (OR, 1.76 [95% CI, 1.41-2.21]). This significant difference was also present in adjusted analyses (adjusted OR, 1.56 [95% CI, 1.02-2.39]). No significant differences were found in inpatient mortality between LEP and EP in the racial and ethnic minority subgroup (OR, 0.99 [95% CI, 0.63-1.58]; adjusted OR, 0.91 [95% CI, 0.56-1.48]). Conclusions and Relevance: In a large diverse academic medical center, LEP had no significant association overall with sepsis mortality. In a subgroup analysis, LEP was associated with increased mortality among individuals identifying as non-Hispanic White. This finding highlights a potential language-based inequity in sepsis care. Further studies are needed to understand drivers of this inequity, how it may manifest in other diverse health systems, and to inform equitable care models for patients with LEP.
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Proficiência Limitada em Inglês , Sepse , Estados Unidos/epidemiologia , Masculino , Humanos , Idoso , Feminino , Etnicidade , Estudos Retrospectivos , Grupos MinoritáriosRESUMO
A clinical decision support system, EvalMpox, was developed to apply person under investigation (PUI) criteria for patients presenting with rash and to recommend testing for PUIs. Of 668 patients evaluated, an EvalMpox recommendation for testing had a positive predictive value of 35% and a negative predictive value of 99% for a positive mpox test.
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Background: For persons with suspected pulmonary tuberculosis, the guidelines of the Centers for Disease Control and Prevention recommend collecting 3 respiratory specimens 8 to 24 hours apart for acid-fast bacilli (AFB) smear and culture, in addition to 1 nucleic acid amplification test (NAAT). However, data supporting this approach are limited. Our objective was to estimate the performance of 1, 2, or 3 AFB smears with or without NAATs to detect pulmonary tuberculosis in a low-prevalence setting. Methods: We conducted a retrospective study of hospitalized persons at 8 Massachusetts acute care facilities who underwent mycobacterial culture on 1 or more respiratory specimens between July 2016 and December 2022. We evaluated percentage positivity and yield on serial AFB smears and NAATs among people with growth of Mycobacterium tuberculosis on mycobacterial cultures. Results: Among 104 participants with culture-confirmed pulmonary tuberculosis, the first AFB smear was positive in 41 cases (39%). A second AFB smear was positive in 11 (22%) of the 49 cases in which it was performed. No third AFB smears were positive following 2 initial negative smears. Of 52 smear-negative cases, 36 had a NAAT performed, leading to 23 additional diagnoses. Overall sensitivity to detect tuberculosis prior to culture positivity was higher in any strategy involving 1 or 2 NAATs (74%-79%), even without AFB smears, as compared with 3 smears alone (60%). Conclusions: Tuberculosis diagnostic testing with 2 AFB smears offered the same yield as 3 AFB smears while potentially reducing laboratory burden and duration of airborne infection isolation. Use of 1 or 2 NAATs increased sensitivity to detect culture-positive pulmonary tuberculosis when added to AFB smear-based diagnostic testing alone.
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OBJECTIVES: There is considerable variation in ordering practices for the initial laboratory evaluation of monoclonal gammopathies (MGs) despite clear society guidelines to include serum free light chain (sFLC) testing. We assessed the ability of a clinical decision support (CDS) alert to improve guideline compliance and analyzed its clinical impact. METHODS: We designed and deployed a targeted CDS alert to educate and prompt providers to order an sFLC assay when ordering serum protein electrophoresis (SPEP) testing. RESULTS: The alert was highly effective at increasing the co-ordering of SPEP and sFLC testing. Preimplementation, 62.8% of all SPEP evaluations included sFLC testing, while nearly 90% of evaluations included an sFLC assay postimplementation. In patients with no prior sFLC testing, analysis of sFLC orders prompted by the alert led to the determination that 28.9% (800/2,769) of these patients had an abnormal κ/λ ratio. In 452 of these patients, the sFLC assay provided the only laboratory evidence of a monoclonal protein. Moreover, within this population, there were numerous instances of new diagnoses of multiple myeloma and other MGs. CONCLUSIONS: The CDS alert increased compliance with society guidelines and improved the diagnostic evaluation of patients with suspected MGs.
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Sistemas de Apoio a Decisões Clínicas , Mieloma Múltiplo , Paraproteinemias , Humanos , Paraproteinemias/diagnóstico , Cadeias Leves de ImunoglobulinaRESUMO
OBJECTIVE: To improve problem list documentation and care quality. MATERIALS AND METHODS: We developed algorithms to infer clinical problems a patient has that are not recorded on the coded problem list using structured data in the electronic health record (EHR) for 12 clinically significant heart, lung, and blood diseases. We also developed a clinical decision support (CDS) intervention which suggests adding missing problems to the problem list. We evaluated the intervention at 4 diverse healthcare systems using 3 different EHRs in a randomized trial using 3 predetermined outcome measures: alert acceptance, problem addition, and National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set (NCQA HEDIS) clinical quality measures. RESULTS: There were 288 832 opportunities to add a problem in the intervention arm and the problem was added 63 777 times (acceptance rate 22.1%). The intervention arm had 4.6 times as many problems added as the control arm. There were no significant differences in any of the clinical quality measures. DISCUSSION: The CDS intervention was highly effective at improving problem list completeness. However, the improvement in problem list utilization was not associated with improvement in the quality measures. The lack of effect on quality measures suggests that problem list documentation is not directly associated with improvements in quality measured by National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set (NCQA HEDIS) quality measures. However, improved problem list accuracy has other benefits, including clinical care, patient comprehension of health conditions, accurate CDS and population health, and for research. CONCLUSION: An EHR-embedded CDS intervention was effective at improving problem list completeness but was not associated with improvement in quality measures.
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Sistemas de Apoio a Decisões Clínicas , Humanos , Registros Eletrônicos de Saúde , Qualidade da Assistência à SaúdeRESUMO
OBJECTIVE: Surviving Sepsis guidelines recommend blood cultures before administration of intravenous (IV) antibiotics for patients with sepsis or moderate to high risk of bacteremia. Clinical decision support (CDS) that reminds emergency department (ED) providers to obtain blood cultures when ordering IV antibiotics may lead to improvements in this process measure. METHODS: This was a multicenter causal impact analysis comparing timely blood culture collections prior to IV antibiotics for adult ED patients 1 year before and after a CDS intervention implementation in the electronic health record. A Bayesian structured time-series model compared daily timely blood cultures collected compared to a forecasted synthetic control. Mixed effects models evaluated the impact of the intervention controlling for confounders. RESULTS: The analysis included 54â538 patients over 2 years. In the baseline phase, 46.1% had blood cultures prior to IV antibiotics, compared to 58.8% after the intervention. Causal impact analysis determined an absolute increase of 13.1% (95% CI 10.4-15.7%) of timely blood culture collections overall, although the difference in patients with a sepsis diagnosis or who met CDC Adult Sepsis Event criteria was not significant, absolute difference 8.0% (95% CI -0.2 to 15.8). Blood culture positivity increased in the intervention phase, and contamination rates were similar in both study phases. DISCUSSION: CDS improved blood culture collection before IV antibiotics in the ED, without increasing overutilization. CONCLUSION: A simple CDS alert increased timely blood culture collections in ED patients for whom concern for infection was high enough to warrant IV antibiotics.
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Sistemas de Apoio a Decisões Clínicas , Sepse , Adulto , Antibacterianos/uso terapêutico , Teorema de Bayes , Hemocultura , Serviço Hospitalar de Emergência , Humanos , Estudos Retrospectivos , Sepse/diagnóstico , Sepse/tratamento farmacológicoRESUMO
OBJECTIVES: To improve clinical decision support (CDS) by allowing users to provide real-time feedback when they interact with CDS tools and by creating processes for responding to and acting on this feedback. METHODS: Two organizations implemented similar real-time feedback tools and processes in their electronic health record and gathered data over a 30-month period. At both sites, users could provide feedback by using Likert feedback links embedded in all end-user facing alerts, with results stored outside the electronic health record, and provide feedback as a comment when they overrode an alert. Both systems are monitored daily by clinical informatics teams. RESULTS: The two sites received 2,639 Likert feedback comments and 623,270 override comments over a 30-month period. Through four case studies, we describe our use of end-user feedback to rapidly respond to build errors, as well as identifying inaccurate knowledge management, user-interface issues, and unique workflows. CONCLUSION: Feedback on CDS tools can be solicited in multiple ways, and it contains valuable and actionable suggestions to improve CDS alerts. Additionally, end users appreciate knowing their feedback is being received and may also make other suggestions to improve the electronic health record. Incorporation of end-user feedback into CDS monitoring, evaluation, and remediation is a way to improve CDS.
Assuntos
Sistemas de Apoio a Decisões Clínicas , Retroalimentação , Registros Eletrônicos de Saúde , Fluxo de TrabalhoRESUMO
OBJECTIVE: To create and validate a simple and transferable machine learning model from electronic health record data to accurately predict clinical deterioration in patients with covid-19 across institutions, through use of a novel paradigm for model development and code sharing. DESIGN: Retrospective cohort study. SETTING: One US hospital during 2015-21 was used for model training and internal validation. External validation was conducted on patients admitted to hospital with covid-19 at 12 other US medical centers during 2020-21. PARTICIPANTS: 33 119 adults (≥18 years) admitted to hospital with respiratory distress or covid-19. MAIN OUTCOME MEASURES: An ensemble of linear models was trained on the development cohort to predict a composite outcome of clinical deterioration within the first five days of hospital admission, defined as in-hospital mortality or any of three treatments indicating severe illness: mechanical ventilation, heated high flow nasal cannula, or intravenous vasopressors. The model was based on nine clinical and personal characteristic variables selected from 2686 variables available in the electronic health record. Internal and external validation performance was measured using the area under the receiver operating characteristic curve (AUROC) and the expected calibration error-the difference between predicted risk and actual risk. Potential bed day savings were estimated by calculating how many bed days hospitals could save per patient if low risk patients identified by the model were discharged early. RESULTS: 9291 covid-19 related hospital admissions at 13 medical centers were used for model validation, of which 1510 (16.3%) were related to the primary outcome. When the model was applied to the internal validation cohort, it achieved an AUROC of 0.80 (95% confidence interval 0.77 to 0.84) and an expected calibration error of 0.01 (95% confidence interval 0.00 to 0.02). Performance was consistent when validated in the 12 external medical centers (AUROC range 0.77-0.84), across subgroups of sex, age, race, and ethnicity (AUROC range 0.78-0.84), and across quarters (AUROC range 0.73-0.83). Using the model to triage low risk patients could potentially save up to 7.8 bed days per patient resulting from early discharge. CONCLUSION: A model to predict clinical deterioration was developed rapidly in response to the covid-19 pandemic at a single hospital, was applied externally without the sharing of data, and performed well across multiple medical centers, patient subgroups, and time periods, showing its potential as a tool for use in optimizing healthcare resources.
Assuntos
COVID-19/diagnóstico , Regras de Decisão Clínica , Hospitalização/estatística & dados numéricos , Aprendizado de Máquina , Medição de Risco/métodos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Área Sob a Curva , Deterioração Clínica , Registros Eletrônicos de Saúde , Feminino , Hospitais , Humanos , Modelos Lineares , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Prognóstico , Curva ROC , Estudos Retrospectivos , SARS-CoV-2 , Adulto JovemRESUMO
OBJECTIVES: While well-designed clinical decision support (CDS) alerts can improve patient care, utilization management, and population health, excessive alerting may be counterproductive, leading to clinician burden and alert fatigue. We sought to develop machine learning models to predict whether a clinician will accept the advice provided by a CDS alert. Such models could reduce alert burden by targeting CDS alerts to specific cases where they are most likely to be effective. MATERIALS AND METHODS: We focused on a set of laboratory test ordering alerts, deployed at 8 hospitals within the Partners Healthcare System. The alerts notified clinicians of duplicate laboratory test orders and advised discontinuation. We captured key attributes surrounding 60 399 alert firings, including clinician and patient variables, and whether the clinician complied with the alert. Using these data, we developed logistic regression models to predict alert compliance. RESULTS: We identified key factors that predicted alert compliance; for example, clinicians were less likely to comply with duplicate test alerts triggered in patients with a prior abnormal result for the test or in the context of a nonvisit-based encounter (eg, phone call). Likewise, differences in practice patterns between clinicians appeared to impact alert compliance. Our best-performing predictive model achieved an area under the receiver operating characteristic curve (AUC) of 0.82. Incorporating this model into the alerting logic could have averted more than 1900 alerts at a cost of fewer than 200 additional duplicate tests. CONCLUSIONS: Deploying predictive models to target CDS alerts may substantially reduce clinician alert burden while maintaining most or all the CDS benefit.