Satisfaction of Older Patients With Emergency Department Care: Psychometric Properties and Construct Validity of the Consumer Emergency Care Satisfaction Scale.

BACKGROUND: Patient satisfaction is an important indicator of quality of care, but its measurement remains challenging. The Consumer Emergency Care Satisfaction Scale (CECSS) was developed to measure patient satisfaction in the emergency department (ED). Although this is a valid and reliable tool, several aspects of the CECSS need to be improved, including the definition, dimension, and scoring of scales. PURPOSE: The purpose of this study was to examine the construct validity of the CECSS and make suggestions on how to improve the tool to measure overall satisfaction with ED care. METHODS: We administered 2 surveys to older adults who presented with a fall to the ED and used electronic health record data to examine construct validity of the CECSS and ceiling effects. RESULTS: Using several criteria, we improved construct validity of the CECSS, reduced ceiling effects, and standardized scoring. CONCLUSION: We addressed several methodological issues with the CECSS and provided recommendations for improvement.

Comparing emergency department use among individuals with varying levels of cognitive impairment.

INTRODUCTION: As the population ages, Alzheimer's disease and related dementias (ADRD) are becoming increasingly common in patients presenting to the emergency department (ED). This study compares the frequency of ED use among a cohort of individuals with well-defined cognitive performance (cognitively intact, mild cognitive impairment (MCI), and ADRD). METHODS: We performed a retrospective cohort study of English-speaking, community-dwelling individuals evaluated at four health system-based multidisciplinary memory clinics from 2014-2016. We obtained demographic and clinical data, including neuropsychological testing results, through chart review and linkage to electronic health record data. We characterized the frequency and quantity of ED use within one year (6 months before and after) of cognitive evaluation and compared ED use between the three groups using bivariate and multivariate approaches. RESULTS: Of the 779 eligible patients, 89 were diagnosed as cognitively intact, 372 as MCI, and 318 as ADRD. The proportion of subjects with any annual ED use did not increase significantly with greater cognitive impairment: cognitively intact (16.9%), MCI (26.1%), and ADRD (28.9%) (p = 0.072). Average number of ED visits increased similarly: cognitively intact (0.27, SD 0.72), MCI (0.41, SD 0.91), and ADRD (0.55, SD 1.25) (p = 0.059). Multivariate logistic regression results showed that patients with MCI (odds ratio (OR) 1.62; CI = 0.87-3.00) and ADRD (OR 1.84; CI = 0.98-3.46) did not significantly differ from cognitively intact adults in any ED use. Multivariate negative binomial regression found patients with MCI (incidence rate ratio (IRR) 1.38; CI = 0.79-2.41) and ADRD (IRR 1.76, CI = 1.00-3.10) had elevated but non-significant risk of an ED visit compared to cognitively intact individuals. CONCLUSION: Though there was no significant difference in ED use in this small sample from one health system, our estimates are comparable to other published work. Results suggested a trend towards higher utilization among adults with MCI or ADRD compared to those who were cognitively intact. We must confirm our findings in other settings to better understand how to optimize systems of acute illness care for individuals with MCI and ADRD.

Utility of bedside assessment to evaluate for cervical-spine fracture post ground-level fall for patients 65 years and older.

OBJECTIVES: The effectiveness of current assessment tools for cervical fracture are mixed with respect to elderly patients. We aim to examine utility of history and physical exam to assess for cervical fracture for elderly patients suffering a ground-level fall. METHODS: Retrospective cohort from a tertiary-care ED for patients ≥65 years, including dementia, after ground-level fall. Logistic regression was used to examine predictability of various clinical factors. Neurologic deficits were considered a hard sign for imaging and were not assessed. RESULTS: Of 1035 patient encounters analyzed, 683 had CT cervical-spine (C-spine) imaging (66.0%) and 16 (1.5%) had cervical fracture. C-spine tenderness (OR 4.7, 95% CI 1.5-14.1), neck pain (OR 10.5, 95% CI 3.4-32.5), altered mental status (AMS) (OR 5.1, 95% CI 1.7-15.6), and external trauma above the clavicles (ETC) (OR 3.8, 95% CI 1.2-12.3) predicted cervical fracture. C-spine tenderness and neck pain were collinear and run-in separate models. Dementia (OR 0.2, 95% CI 0.4-0.9) did not predict cervical fracture in this population. A combination of ETC, C-spine tenderness, and AMS had a sensitivity = 100% and specificity = 40.0% for detection of cervical fracture. ETC was found in all but two fractures requiring intervention with negative predictive value = 99.3%. CONCLUSIONS: Clinical assessment for elderly patients without neurologic signs, together with the absence of ETC, cervical tenderness, and AMS may be reliable in ruling out cervical fracture after a ground-level fall, including patients with history of dementia. Fractures requiring intervention were rare in patients without ETC. However, findings are retrospective and prospective validation is required.

Effect of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the United States : A Simulation Modeling Approach.

BACKGROUND: Across the United States, various social distancing measures were implemented to control the spread of coronavirus disease 2019 (COVID-19). However, the effectiveness of such measures for specific regions with varying population demographic characteristics and different levels of adherence to social distancing is uncertain. OBJECTIVE: To determine the effect of social distancing measures in unique regions. DESIGN: An agent-based simulation model. SETTING: Agent-based model applied to Dane County, Wisconsin; the Milwaukee metropolitan (metro) area; and New York City (NYC). PATIENTS: Synthetic population at different ages. INTERVENTION: Different times for implementing and easing social distancing measures at different levels of adherence. MEASUREMENTS: The model represented the social network and interactions among persons in a region, considering population demographic characteristics, limited testing availability, "imported" infections, asymptomatic disease transmission, and age-specific adherence to social distancing measures. The primary outcome was the total number of confirmed COVID-19 cases. RESULTS: The timing of and adherence to social distancing had a major effect on COVID-19 occurrence. In NYC, implementing social distancing measures 1 week earlier would have reduced the total number of confirmed cases from 203 261 to 41 366 as of 31 May 2020, whereas a 1-week delay could have increased the number of confirmed cases to 1 407 600. A delay in implementation had a differential effect on the number of cases in the Milwaukee metro area versus Dane County, indicating that the effect of social distancing measures varies even within the same state. LIMITATION: The effect of weather conditions on transmission dynamics was not considered. CONCLUSION: The timing of implementing and easing social distancing measures has major effects on the number of COVID-19 cases. PRIMARY FUNDING SOURCE: National Institute of Allergy and Infectious Diseases.

Usability of a Human Factors-based Clinical Decision Support in the Emergency Department: Lessons Learned for Design and Implementation.

OBJECTIVE: To evaluate the usability and use of human factors (HF)-based clinical decision support (CDS) implemented in the emergency department (ED). BACKGROUND: Clinical decision support can improve patient safety; however, the acceptance and use of CDS has faced challenges. Following a human-centered design process, we designed a CDS to support pulmonary embolism (PE) diagnosis in the ED. We demonstrated high usability of the CDS during scenario-based usability testing. We implemented the HF-based CDS in one ED in December 2018. METHOD: We conducted a survey of ED physicians to evaluate the usability and use of the HF-based CDS. We distributed the survey via Qualtrics, a web-based survey platform. We compared the computer system usability questionnaire scores of the CDS between those collected in the usability testing to use of the CDS in the real environment. We asked physicians about their acceptance and use of the CDS, barriers to using the CDS, and areas for improvement. RESULTS: Forty-seven physicians (56%) completed the survey. Physicians agreed that diagnosing PE is a major problem and risk scores can support the PE diagnostic process. Usability of the CDS was reported as high, both in the experimental setting and the real clinical setting. However, use of the CDS was low. We identified several barriers to the CDS use in the clinical environment, in particular a lack of workflow integration. CONCLUSION: Design of CDS should be a continuous process and focus on the technology's usability in the context of the broad work system and clinician workflow.

Older Adult Patients and Care Partners as Knowledge Brokers in Fragmented Health Care.

OBJECTIVE: To describe older adult patients' and care partners' knowledge broker roles during emergency department (ED) visits. BACKGROUND: Older adult patients are vulnerable to communication and coordination challenges during an ED visit, which can be exacerbated by the time and resource constrained ED environment. Yet, as a constant throughout the patient journey, patients and care partners can act as an information conduit, or knowledge broker, between fragmented care systems to attain high-quality, safe care. METHODS: Participants included 14 older adult patients (≥ 65 years old) and their care partners (e.g., spouse, adult child) who presented to the ED after having experienced a fall. Human factors researchers collected observation data from patients, care partners and clinician interactions during the patient's ED visit. We used an inductive content analysis to determine the role of patients and care partners as knowledge brokers. RESULTS: We found that patients and care partners act as knowledge brokers by providing information about diagnostic testing, medications, the patient's health history, and care accommodations at the disposition location. Patients and care partners filled the role of knowledge broker proactively (i.e. offer information) and reactively (i.e. are asked to provide information by clinicians or staff), within-ED work system and across work systems (e.g., between the ED and hospital), and in anticipation of future knowledge brokering. CONCLUSION: Patients and care partners, acting as knowledge brokers, often fill gaps in communication and participate in care coordination that assists in mitigating health care fragmentation.

Effect of a split-flow physician in triage model on abdominal CT ordering rate and yield.

OBJECTIVE: The objective of this study was to compare the rate and clinical yield of computed tomography (CT) imaging between patients presenting with abdominal pain initially seen by a physician in triage (PIT) versus those seen only by physicians working in the main emergency department (ED). METHODS: A retrospective study was conducted of all self-arrivals >18 years old presenting to a single ED with abdominal pain. Nine-hundred patients were randomly selected from both the PIT and traditional patient flow groups and rates and yields of CT imaging were compared, both alone and in a model controlling for potential confounders. Predetermined criteria for CT significance included need for admission, consult, or targeted medications. RESULTS: The overall rate of CT imaging (unadjusted) did not differ between the PIT and traditional groups, 48.7% (95% CI 45.4-51.9) vs. 45.1% (95% CI 41.8-48.4), respectively (p = .13). The CT yield for patients seen in in the PIT group was also similar to that of the traditional group: 49.1% (95% CI 44.4-53.8) vs. 50.5% (95% CI 45.6-55.4) (p = .68). In the logistic regression model, when controlling for age, gender, ESI-acuity, race and insurance payor, PIT vs. traditional was not a predictor of CT ordering (OR 1.14, 95% CI 0.94-1.38). CONCLUSIONS: For patients with abdominal pain, we found no significant differences in rates of CT ordering or CT yield for patients seen in a PIT vs. traditional models, suggesting the increased efficiencies offered by PIT models do not come at the cost of increased or decreased imaging utilization.

Comparing the Timeliness of Treatment in Younger vs. Older Patients with ST-Segment Elevation Myocardial Infarction: A Multi-Center Cohort Study.

BACKGROUND: ST-segment elevation myocardial infarction (STEMI) predominantly affects older adults. Lower incidence among younger patients may challenge diagnosis. OBJECTIVES: We hypothesize that among patients ≤ 50 years old, emergent percutaneous coronary intervention (PCI) for STEMI is delayed when compared with patients aged > 50 years. METHODS: This 3-year, 10-center retrospective cohort study included emergency department (ED) STEMI patients ≥ 18 years of age treated with emergent PCI. We excluded patients with an electrocardiogram (ECG) completed prior to ED arrival or a nondiagnostic initial ECG. Our primary outcome was door-to-balloon (D2B) time. We compared characteristics and outcomes among younger vs. older STEMI patients, and among age subgroups. RESULTS: There were 576 ED STEMI PCI patients, of whom 100 were ≤ 50 years old and 476 were > 50 years old. Median age was 44 years in the younger cohort (interquartile range [IQR] 41-47) vs. 62 years (IQR 57-70) among older patients. Median D2B time for the younger cohort was 76.5 min (IQR 67.5-102.5) vs. 81.0 min (IQR 65.0-105.5) in the older cohort (p = 0.91). This outcome did not change when ages 40 or 45 years were used to demarcate younger vs. older. The younger cohort had a higher prevalence of nonwhite races (38% vs. 21%; p < 0.001) and those currently smoking (36% vs. 23%; p = 0.005). The very young (≤30 years; 6/576) and very old (>80 years; 45/576) had 5.51 and 2.2 greater odds of delays. CONCLUSION: We found no statistically significant difference in D2B times between patients ≤ 50 years old and those > 50 years old. Nonwhite patients and those who smoke were disproportionately represented within the younger population. The very young and very old had higher odds of D2B times > 90 min.

Class II malocclusion correction with Invisalign: Is it possible?

INTRODUCTION: This research aimed to determine whether Class II malocclusion can be treated with clear aligners after completing treatment with the initial set of aligners. METHODS: A sample of 80 adult patients were divided into Group 1 with Class I molar malocclusions (n = 40 [11 men and 29 women]; 38.70 ± 15.90 years) and Group 2 with Class II molar malocclusions (n = 40 [11 men and 29 women]; 35.25 ± 15.21 years). All patients had finished treatment with the initial set of Invisalign aligners (Align Technology, Santa Jose, Calif) without known centric occlusion-centric relation discrepancies, issues of compliance, or overcorrection. The 7 measurements using the American Board of Orthodontics (ABO) Model Grading System and millimetric measurements for anteroposterior (AP) and vertical dimensions were assessed and compared between the 2 groups at pretreatment, posttreatment ClinCheck (Align Technology) prediction, and posttreatment. RESULTS: No improvements were observed in the AP correction. The amount of AP correction in patients with Class II malocclusion was 6.8% of the predicted amount. The amount of overbite correction achieved was 28.8% and 38.9% of the predicted amounts in patients with Class I and Class II malocclusion, respectively. Significant improvements in alignment and interproximal contact scores were observed, with only slight improvements in total ABO scores. An increase in mean occlusal contacts score was observed after treatment. No patient with Class II malocclusions would meet the ABO standards after Invisalign treatment. CONCLUSIONS: The Invisalign system successfully achieves certain tooth movements but fails to achieve other movements predictably. No significant Class II correction or overjet reduction was observed with elastics for an average of 7-month duration in the adult population. Additional refinements may be necessary to address problems created during treatment, as evidenced by a posterior open bite incidence.

The Average Effect of Emergency Department Admission on Readmission and Mortality for Older Adults With Chest Pain.

BACKGROUND: Many older adults (65+) present to the Emergency Department (ED) with chest pain, but do not have otherwise clear clinical indication of whether they should be admitted or discharged. This uncertainty leads to decisions that are highly variable-in addition to already being costly-which could have adverse consequences, since older adults are particularly vulnerable from hospitalization. OBJECTIVE: The objective of this study was to determine whether admitting versus discharging an older adult presenting to the ED with chest pain reduces risk of mortality and readmission. STUDY DESIGN: Electronic health records were curated from an academic hospital system between January 1, 2014, and September 27, 2018. Average effects of admission on 30-day readmission and mortality were estimated using a new causal inference approach based on a latent-variable model of the admission process. Additional analyses assessed moderators and robustness of estimates. SUBJECTS: Older patients (n=3090) presenting to University of Wisconsin Hospital ED. MEASURES: Readmission and mortality within 25, 30, and 35 days of discharge from the ED for discharged patients or the hospital for admitted patients RESULTS:: For older chest pain patients, admission is estimated to lower the 30-day risk of readmission by 42.8% (95% confidence interval: 41.0%-44.6%) but increase the 30-day risk of mortality by 0.8% (95% confidence interval: 0.4%-1.2%). Individuals with higher hierarchical conditional category scores or diabetes with complications have both lower 30-day risk of readmission and higher 30-day risk of mortality compared with their counterparts (P≤0.02). CONCLUSIONS: Our findings suggest ED admission may prevent readmission at the cost of increasing mortality risk for older chest pain patients, especially those with comorbidity. Additional studies are needed to validate these findings.

1-D imaging of rotation-vibration non-equilibrium from pure rotational ultrafast coherent anti-Stokes Raman scattering.

We present one-dimensional (1-D) imaging of rotation-vibration non-equilibrium measured by two-beam pure rotational hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (fs/ps CARS). Simultaneous measurements of the spatial distribution of molecular rotation-vibration non-equilibrium are critical for understanding molecular energy transfer in low temperature plasmas and hypersonic flows. However, non-equilibrium CARS thermometry until now was limited to point measurements. The red shift of rotational energy levels by vibrational excitation was used to determine the rotational and vibrational temperatures from 1-D images of the pure rotational spectrum. Vibrational temperatures up to 5500 K were detected in a CH4/N2 nanosecond-pulsed pin-to-pin plasma within 2 mm near the cathode. This approach enables study of non-equilibrium systems with 40 µm spatial resolution.

Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits.

BACKGROUND: Machine learning is increasingly used for risk stratification in health care. Achieving accurate predictive models do not improve outcomes if they cannot be translated into efficacious intervention. Here we examine the potential utility of automated risk stratification and referral intervention to screen older adults for fall risk after emergency department (ED) visits. OBJECTIVE: This study evaluated several machine learning methodologies for the creation of a risk stratification algorithm using electronic health record data and estimated the effects of a resultant intervention based on algorithm performance in test data. METHODS: Data available at the time of ED discharge were retrospectively collected and separated into training and test datasets. Algorithms were developed to predict the outcome of a return visit for fall within 6 months of an ED index visit. Models included random forests, AdaBoost, and regression-based methods. We evaluated models both by the area under the receiver operating characteristic (ROC) curve, also referred to as area under the curve (AUC), and by projected clinical impact, estimating number needed to treat (NNT) and referrals per week for a fall risk intervention. RESULTS: The random forest model achieved an AUC of 0.78, with slightly lower performance in regression-based models. Algorithms with similar performance, when evaluated by AUC, differed when placed into a clinical context with the defined task of estimated NNT in a real-world scenario. CONCLUSION: The ability to translate the results of our analysis to the potential tradeoff between referral numbers and NNT offers decisionmakers the ability to envision the effects of a proposed intervention before implementation.

Generation of narrowband pulses from chirped broadband pulse frequency mixing.

We extend an approach based upon sum-frequency generation of oppositely chirped pulses to narrow the bandwidths of broadband femtosecond pulses. We efficiently generate near-transform-limited pulses with durations of several picoseconds, while reducing the pulse bandwidth by a factor of 120, which is more than twice the reduction reported in previous literature. Such extreme bandwidth narrowing of a broadband pulse enhances the effects of dispersion nonlinearities. Precise chirp control enables us to characterize the efficacy of frequency mixing broadband pulses with nonlinear temporal chirps. We demonstrate the use of these narrowband pulses as probes in coherent anti-Stokes Raman spectroscopy.

Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review.

STUDY OBJECTIVE: As electronic health records evolve, integration of computerized clinical decision support offers the promise of sorting, collecting, and presenting this information to improve patient care. We conducted a systematic review to examine the scope and influence of electronic health record-integrated clinical decision support technologies implemented in the emergency department (ED). METHODS: A literature search was conducted in 4 databases from their inception through January 18, 2018: PubMed, Scopus, the Cumulative Index of Nursing and Allied Health, and Cochrane Central. Studies were included if they examined the effect of a decision support intervention that was implemented in a comprehensive electronic health record in the ED setting. Standardized data collection forms were developed and used to abstract study information and assess risk of bias. RESULTS: A total of 2,558 potential studies were identified after removal of duplicates. Of these, 42 met inclusion criteria. Common targets for clinical decision support intervention included medication and radiology ordering practices, as well as more comprehensive systems supporting diagnosis and treatment for specific disease entities. The majority of studies (83%) reported positive effects on outcomes studied. Most studies (76%) used a pre-post experimental design, with only 3 (7%) randomized controlled trials. CONCLUSION: Numerous studies suggest that clinical decision support interventions are effective in changing physician practice with respect to process outcomes such as guideline adherence; however, many studies are small and poorly controlled. Future studies should consider the inclusion of more specific information in regard to design choices, attempt to improve on uncontrolled before-after designs, and focus on clinically relevant outcomes wherever possible.

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.

Role network measures to assess healthcare team adaptation to complex situations: the case of venous thromboembolism prophylaxis.

Hospitals are complex environments that rely on clinicians working together to provide appropriate care to patients. These clinical teams adapt their interactions to meet changing situational needs. Venous thromboembolism (VTE) prophylaxis is a complex process that occurs throughout a patient's hospitalisation, presenting five stages with different levels of complexity: admission, interruption, re-initiation, initiation, and transfer. The objective of our study is to understand how the VTE prophylaxis team adapts as the complexity in the process changes; we do this by using social network analysis (SNA) measures. We interviewed 45 clinicians representing 9 different cases, creating 43 role networks. The role networks were analysed using SNA measures to understand team changes between low and high complexity stages. When comparing low and high complexity stages, we found two team adaptation mechanisms: (1) relative increase in the number of people, team activities, and interactions within the team, or (2) relative increase in discussion among the team, reflected by an increase in reciprocity.   Practitioner Summary: The reason for this study was to quantify team adaptation to complexity in a process using social network analysis (SNA). The VTE prophylaxis team adapted to complexity by two different mechanisms, by increasing the roles, activities, and interactions among the team or by increasing the two-way communication and discussion throughout the team. We demonstrated the ability for SNA to identify adaptation within a team.

Effectiveness of Outpatient Antibiotics After Surgical Drainage of Abscesses in Reducing Treatment Failure.

BACKGROUND: The optimal approach to outpatient antibiotic use after surgical drainage of abscesses is unclear given conflicting clinical trial results. OBJECTIVE: Our primary objective was to evaluate the real-world effectiveness of outpatient antibiotic prescribing after surgical drainage of cutaneous abscesses on reducing treatment failure. METHODS: We performed a retrospective observational study using data extracted from the electronic health record of a single academic health care system. All emergency department (ED) visits that resulted in discharge with a surgical drainage of a cutaneous abscess procedure code were included in the sample. All visits were categorized into having received or not having received an antibiotic prescription at the index visit. Outcome frequencies were compared using Pearson's chi-squared test. A multivariable logistic regression model was used to estimate the odds of treatment failure among those who did and did not receive an antibiotic prescription at their index ED visit. RESULTS: The final sample consisted of 421 index ED visits, of which 303 (72%) received an antibiotic prescription. Treatment with antibiotics after drainage did not significantly reduce the odds of composite treatment failure within 30 days when controlling for sociodemographic and clinical encounter variables (odds ratio 0.52, 95% confidence interval 0.23-1.21). CONCLUSIONS: This real-world, comparative effectiveness analysis did not demonstrate any significant reduction in treatment failure with the use of antibiotics after drainage of abscesses in the ED. It is unclear if the clinical benefit observed under controlled trial conditions will carry over to routine clinical practice where varied antibiotic regimens are the norm and local bacterial resistance patterns vary.