Development of a Qualified Clinical Data Registry for emergency medicine

The passage of the Medicare Access and CHIP Reauthorization Act (MACRA) in 2015 marked a fundamental transition in physician payment by the Centers for Medicare and Medicaid Services (CMS) from traditional fee-for service to value-based models. MACRA led to the creation of the CMS Quality Payment Program (QPP), which bases the value of physician care in large part on physician quality reporting. The QPP enabled a shift away from legacy CMS-stewarded quality measures that had limited applicability to individual specialties toward specialty-specific quality measures developed and stewarded by physician specialty societies using Qualified Clinical Data Registries (QCDRs). This article describes the development of the first nationally available emergency medicine QCDR as a means for emergency physicians to participate in the QPP, measure, and benchmark emergency physician quality

Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department

BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. METHODS: In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results. RESULTS: The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders. CONCLUSIONS: Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance

Variation in the use of observation status evaluation in Massachusetts acute care hospitals, 2003–2006

Background Observation evaluation is an alternate pathway to inpatient admission following Emergency Department (ED) assessment. Aims We aimed to describe the variation in observation use and charges between acute care hospitals in Massachusetts from 2003 to 2006. Methods Retrospective pilot analysis of hospital administrative data. Patients discharged from a Massachusetts hospital between 2003 and 2006 after an observation visit or inpatient hospitalization for six emergency medical conditions, grouped by the Clinical Classification System (CCS), were included. Patients discharged with a primary obstetric condition were excluded. The primary outcome measure, “Observation Proportion ” (pOBS), was the use of observation evaluation relative to inpatient evaluation (pOBS = n Observation/(n Observation + n Inpatient). We calculated pOBS, descriptive statistics of use and charges by the hospital for each condition. Results From 2003 to 2006 the number of observation visits in Massachusetts increased 3.9 % [95 % confidence interval (CI) 3.8 % to 4.0%] from 128,825 to 133,859, while inpatient hospitalization increased 1.29 % (95 % CI 1.26 % to 1.31%) from 832,415 to 843,617. Nonspecific chest pain (CCS 102) was the most frequently observed condition with 85,843 (16.3 % of total) observation evaluations. Observation visits for nonspecific chest pain increased 43.5 % from 2003 to 2006. Relative observation utilization (pOBS) for nonspecific chest pain ranged from 25 % to 95% across hospitals. Wide variation in hospital use of observation and charges was seen for all six emergency medical conditions. Conclusions There was wide variation in use of observation across six common emergency conditions in Massachusetts in this pilot analysis. This variation may have a substantial impact on hospital resource utilization. Further investigation into the patient, provider and hospital-level characteristics that explain the variation in observation use could help improve hospital efficiency

Telehealth Clinical Appropriateness and Quality

Contrary to common perception, telehealth is not simply a substitute for in-person care. With an array of modalities—live audio–video, asynchronous patient communication, and remote patient monitoring, to name a few—telehealth creates entirely new avenues of care delivery (Table 1). Although our current care model is reactive—relying on episodic visits to an office or hospital—telehealth allows us to be proactive, filling in the gaps to provide a continuum of care. Widespread uptake of telehealth has created fertile ground for long-overdue health system reform. In this study, we describe essential next steps: redefine telehealth clinical appropriateness, evolve payment models, provide necessary training, and reimagine the patient–physician interaction

Evaluation of Pulmonary Embolism in the Emergency Department and Consistency With a National Quality Measure: Quantifying the opportunity for improvement

Background The National Quality Forum (NQF) has endorsed a performance measure designed to increase imaging efficiency for the evaluation of pulmonary embolism (PE) in the emergency department (ED). To our knowledge, no published data have examined the effect of patient-level predictors on performance. Methods To quantify the prevalence of avoidable imaging in ED patients with suspected PE, we performed a prospective, multicenter observational study of ED patients evaluated for PE from 2004 through 2007 at 11 US EDs. Adult patients tested for PE were enrolled, with data collected in a standardized instrument. The primary outcome was the proportion of imaging that was potentially avoidable according to the NQF measure. Avoidable imaging was defined as imaging in a patient with low pretest probability for PE, who either did not have a D-dimer test ordered or who had a negative D-dimer test result. We performed subanalyses testing alternative pretest probability cutoffs and imaging definitions on measure performance as well as a secondary analysis to identify factors associated with inappropriate imaging. χ2 Test was used for bivariate analysis of categorical variables and multivariable logistic regression for the secondary analysis. Results We enrolled 5940 patients, of whom 4113 (69%) had low pretest probability of PE. Imaging was performed in 2238 low-risk patients (38%), of whom 811 had no D-dimer testing, and 394 had negative D-dimer test results. Imaging was avoidable, according to the NQF measure, in 1205 patients (32%; 95% CI, 31%-34%). Avoidable imaging owing to not ordering a D-dimer test was associated with age (odds ratio [OR], 1.15 per decade; 95% CI, 1.10-1.21). Avoidable imaging owing to imaging after a negative D-dimer test result was associated with inactive malignant disease (OR, 1.66; 95% CI, 1.11-2.49). Conclusions One-third of imaging performed for suspected PE may be categorized as avoidable. Improving adherence to established diagnostic protocols is likely to result in significantly fewer patients receiving unnecessary irradiation and substantial savings

Pre-COVID-19 Hospital Quality and Hospital Response to COVID-19: Examining Associations between Risk-Adjusted Mortality for Patients Hospitalised with COVID-19 and Pre-COVID-19 Hospital Quality

OBJECTIVES: The extent to which care quality influenced outcomes for patients hospitalised with COVID-19 is unknown. Our objective was to determine if prepandemic hospital quality is associated with mortality among Medicare patients hospitalised with COVID-19. DESIGN: This is a retrospective observational study. We calculated hospital-level risk-standardised in-hospital and 30-day mortality rates (risk-standardised mortality rates, RSMRs) for patients hospitalised with COVID-19, and correlation coefficients between RSMRs and pre-COVID-19 hospital quality, overall and stratified by hospital characteristics. SETTING: Short-term acute care hospitals and critical access hospitals in the USA. PARTICIPANTS: Hospitalised Medicare beneficiaries (Fee-For-Service and Medicare Advantage) age 65 and older hospitalised with COVID-19, discharged between 1 April 2020 and 30 September 2021. INTERVENTION/EXPOSURE: Pre-COVID-19 hospital quality. OUTCOMES: Risk-standardised COVID-19 in-hospital and 30-day mortality rates (RSMRs). RESULTS: In-hospital (n=4256) RSMRs for Medicare patients hospitalised with COVID-19 (April 2020-September 2021) ranged from 4.5% to 59.9% (median 18.2%; IQR 14.7%-23.7%); 30-day RSMRs ranged from 12.9% to 56.2% (IQR 24.6%-30.6%). COVID-19 RSMRs were negatively correlated with star rating summary scores (in-hospital correlation coefficient -0.41, p CONCLUSIONS: Hospitals with better prepandemic quality may have care structures and processes that allowed for better care delivery and outcomes during the COVID-19 pandemic. Understanding the relationship between pre-COVID-19 hospital quality and COVID-19 outcomes will allow policy-makers and hospitals better prepare for future public health emergencies

The Association Between Prolonged SARS-CoV-2 Symptoms and Work Outcomes

While the early effects of the COVID-19 pandemic on the United States labor market are well-established, less is known about the long-term impact of SARS-CoV-2 infection and Long COVID on employment. To address this gap, we analyzed self-reported data from a prospective, national cohort study to estimate the effects of SARS-CoV-2 symptoms at three months post-infection on missed workdays and return to work. The analysis included 2,939 adults in the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE) study who tested positive for their initial SARS-CoV-2 infection at the time of enrollment, were employed before the pandemic, and completed a baseline and three-month electronic survey. At three months post-infection, 40.8% of participants reported at least one SARS-CoV-2 symptom and 9.6% of participants reported five or more SARS-CoV-2 symptoms. When asked about missed work due to their SARS-CoV-2 infection at three months, 7.2% of participants reported missing ≥10 workdays and 13.9% of participants reported not returning to work since their infection. At three months, participants with ≥5 symptoms had a higher adjusted odds ratio of missing ≥10 workdays (2.96, 95% CI 1.81-4.83) and not returning to work (2.44, 95% CI 1.58-3.76) compared to those with no symptoms. Prolonged SARS-CoV-2 symptoms were common, affecting 4-in-10 participants at three-months post-infection, and were associated with increased odds of work loss, most pronounced among adults with ≥5 symptoms at three months. Despite the end of the federal Public Health Emergency for COVID-19 and efforts to return to normal , policymakers must consider the clinical and economic implications of the COVID-19 pandemic on people\u27s employment status and work absenteeism, particularly as data characterizing the numerous health and well-being impacts of Long COVID continue to emerge. Improved understanding of risk factors for lost work time may guide efforts to support people in returning to work

Prevalence of Symptoms ≤12 Months After Acute Illness, by COVID-19 Testing Status Among Adults - United States, December 2020-March 2023

To further the understanding of post-COVID conditions, and provide a more nuanced description of symptom progression, resolution, emergence, and reemergence after SARS-CoV-2 infection or COVID-like illness, analysts examined data from the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE), a prospective multicenter cohort study. This report includes analysis of data on self-reported symptoms collected from 1,296 adults with COVID-like illness who were tested for SARS-CoV-2 using a Food and Drug Administration-approved polymerase chain reaction or antigen test at the time of enrollment and reported symptoms at 3-month intervals for 12 months. Prevalence of any symptom decreased substantially between baseline and the 3-month follow-up, from 98.4% to 48.2% for persons who received a positive SARS-CoV-2 test results (COVID test-positive participants) and from 88.2% to 36.6% for persons who received negative SARS-CoV-2 test results (COVID test-negative participants). Persistent symptoms decreased through 12 months; no difference between the groups was observed at 12 months (prevalence among COVID test-positive and COVID test-negative participants = 18.3% and 16.1%, respectively; p\u3e0.05). Both groups reported symptoms that emerged or reemerged at 6, 9, and 12 months. Thus, these symptoms are not unique to COVID-19 or to post-COVID conditions. Awareness that symptoms might persist for up to 12 months, and that many symptoms might emerge or reemerge in the year after COVID-like illness, can assist health care providers in understanding the clinical signs and symptoms associated with post-COVID-like conditions

Association Between SARS-CoV-2 Variants and Frequency of Acute Symptoms: Analysis of a Multi-institutional Prospective Cohort Study-December 20, 2020-June 20, 2022.

Background: While prior work examining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern focused on hospitalization and death, less is known about differences in clinical presentation. We compared the prevalence of acute symptoms across pre-Delta, Delta, and Omicron. Methods: We conducted an analysis of the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE), a cohort study enrolling symptomatic SARS-CoV-2-positive participants. We determined the association between the pre-Delta, Delta, and Omicron time periods and the prevalence of 21 coronavirus disease 2019 (COVID-19) acute symptoms. Results: We enrolled 4113 participants from December 2020 to June 2022. Pre-Delta vs Delta vs Omicron participants had increasing sore throat (40.9%, 54.6%, 70.6%; Conclusions: Participants infected during Omicron were more likely to report symptoms of common respiratory viruses, such as sore throat, and less likely to report loss of smell and taste. Trial Registration: NCT04610515