The psychosocial health, experiences and needs of older adults and care partners during the first surge of the COVID-19 pandemic: a mixed-methods study.

BACKGROUND: Minimal research has leveraged qualitative data methods to gain a better understanding of the experiences and needs of older adults (OAs) and care partners of OAs with and without Alzheimer's Disease (AD) and AD-related dementias (AD/ADRD) during the first surge of the COVID-19 pandemic. In this study, we: 1) quantitatively evaluated the psychosocial health of community-dwelling OAs; 2) quantitatively evaluated the perceived stress of care partners for OAs; 3) qualitatively characterized the experiences and needs of community-dwelling OAs and their care partners; and 4) explored differences in the experiences of care partners of OAs with and without AD/ADRD during the first surge of the COVID-19 pandemic in the New York metropolitan area. METHODS: In this mixed-methods study, telephone interviews were conducted with 26 OAs and 29 care partners (16 of whom cared for OAs with AD/ADRD) from April to July 2020. Quantitative data included: demographics; clinical characteristics (Katz Index of independence in activities of daily living (Katz ADL) and the Lawton-Brody instrumental activities of daily living scale (Lawton-Brody)); and psychosocial health: stress was assessed via the Perceived Stress Scale (PSS), social isolation via the Lubben Social Network Scale (LSNS), loneliness via the DeJong Loneliness Scale (DeJong), and depression and anxiety via the Patient Health Questionnaire-Anxiety and Depression (PHQ). Qualitative questions focused on uncovering the experiences and needs of OAs and their care partners. RESULTS: OAs (N = 26) were mostly female (57.7%), and White (76.9%), average age of 81.42 years. While OAs were independent (M = 5.60, Katz ADL) and highly functional (M = 6.92, Lawton-Brody), and expressed low levels of loneliness, stress, depression and anxiety (M = 1.95 on DeJong; M = 12.67 on PSS; M = 1.05 on PHQ depression; and M = 1.09 on PHQ anxiety), open-ended questions elicited themes of fear and worry. Care partners (N = 29) were mostly female (75.9%), White (72.4%), and married (72.4%), and reported moderate stress (M = 16.52 on the PSS), as well as a psychological impact of the pandemic. CONCLUSIONS: Early in the pandemic, OAs reported minimal stress and loneliness; this may have been related to their reports of frequent interaction with family, even if only virtually. By contrast, care partners were moderately stressed and worried, potentially more than usual due to the additional challenges they face when trying to meet their loved ones' needs during a pandemic.

Trajectories of hypoxemia and pulmonary mechanics of COVID-19 ARDS in the NorthCARDS dataset.

BACKGROUND: Understanding heterogeneity seen in patients with COVIDARDS and comparing to non-COVIDARDS may inform tailored treatments. METHODS: A multidisciplinary team of frontline clinicians and data scientists worked to create the Northwell COVIDARDS dataset (NorthCARDS) leveraging over 11,542 COVID-19 hospital admissions. The data was then summarized to examine descriptive differences based on clinically meaningful categories of lung compliance, and to examine trends in oxygenation. FINDINGS: Of the 1536 COVIDARDS patients in the NorthCARDS dataset, there were 531 (34.6%) who had very low lung compliance (< 20 ml/cmH2O), 970 (63.2%) with low-normal compliance (20-50 ml/cmH2O), and 35 (2.2%) with high lung compliance (> 50 ml/cmH2O). The very low compliance group had double the median time to intubation compared to the low-normal group (107.3 h (IQR 25.8, 239.2) vs. 39.5 h (IQR 5.4, 91.6)). Overall, 68.8% (n = 1057) of the patients died during hospitalization. In comparison to non-COVIDARDS reports, there were less patients in the high compliance category (2.2% vs. 12%, compliance ≥ 50 mL/cmH20), and more patients with P/F ≤ 150 (59.8% vs. 45.6%). There is a statistically significant correlation between compliance and P/F ratio. The Oxygenation Index is the highest in the very low compliance group (12.51, SD(6.15)), and lowest in high compliance group (8.78, SD(4.93)). CONCLUSIONS: The respiratory system compliance distribution of COVIDARDS is similar to non-COVIDARDS. In some patients, there may be a relation between time to intubation and duration of high levels of supplemental oxygen treatment on trajectory of lung compliance.

Geriatrics-focused indicators predict mortality more than age in older adults hospitalized with COVID-19.

BACKGROUND: Age has been implicated as the main risk factor for COVID-19-related mortality. Our objective was to utilize administrative data to build an explanatory model accounting for geriatrics-focused indicators to predict mortality in hospitalized older adults with COVID-19. METHODS: Retrospective cohort study of adults age 65 and older (N = 4783) hospitalized with COVID-19 in the greater New York metropolitan area between 3/1/20-4/20/20. Data included patient demographics and clinical presentation. Stepwise logistic regression with Akaike Information Criterion minimization was used. RESULTS: The average age was 77.4 (SD = 8.4), 55.9% were male, 20.3% were African American, and 15.0% were Hispanic. In multivariable analysis, male sex (adjusted odds ration (adjOR) = 1.06, 95% CI:1.03-1.09); Asian race (adjOR = 1.08, CI:1.03-1.13); history of chronic kidney disease (adjOR = 1.05, CI:1.01-1.09) and interstitial lung disease (adjOR = 1.35, CI:1.28-1.42); low or normal body mass index (adjOR:1.03, CI:1.00-1.07); higher comorbidity index (adjOR = 1.01, CI:1.01-1.02); admission from a facility (adjOR = 1.14, CI:1.09-1.20); and mechanical ventilation (adjOR = 1.52, CI:1.43-1.62) were associated with mortality. While age was not an independent predictor of mortality, increasing age (centered at 65) interacted with hypertension (adjOR = 1.02, CI:0.98-1.07, reducing by a factor of 0.96 every 10 years); early Do-Not-Resuscitate (DNR, life-sustaining treatment preferences) (adjOR = 1.38, CI:1.22-1.57, reducing by a factor of 0.92 every 10 years); and severe illness on admission (at 65, adjOR = 1.47, CI:1.40-1.54, reducing by a factor of 0.96 every 10 years). CONCLUSION: Our findings highlight that residence prior to admission, early DNR, and acute illness severity are important predictors of mortality in hospitalized older adults with COVID-19. Readily available administrative geriatrics-focused indicators that go beyond age can be utilized when considering prognosis.

Patterns and outcomes of prescribing venous thromboembolism prophylaxis in hospitalized older adults: a retrospective cohort study.

Venous thromboembolism (VTE) is a major cause of morbidity and mortality in the United States. Hospitalized, medically ill older adults have increased risk; despite guidelines, data suggest suboptimal pharmacologic prophylaxis rates. Factors influencing provider prescribing non-compliance are unclear. We aimed to describe VTE prophylaxis practices and identify risk factors for, and outcomes of, prescribing non-compliance. A retrospective study was conducted of hospitalized adults aged ≥ 75 years, admitted to the medicine service of a large academic tertiary center from May 1, 2014 to June 30, 2015. The primary outcome was non-compliance, defined as the absence of an order for VTE prophylaxis for the duration of hospitalization or an interruption of prophylaxis exceeding 24 h. Secondary measures included in-hospital mortality, length of stay (LOS), and 30-day readmissions. Of 3751 patients (mean age 84.7 years), 97.6% of charts had prophylaxis orders; 11.0% showed non-compliance. Pharmacologic prophylaxis was prescribed in 83.3% of patients and mechanical prophylaxis alone in 14.3%. Factors associated with non-compliance included: higher body mass index (BMI) (p = 0.04), myocardial infarction (p = 0.01), congestive heart failure (p = 0.001), metastatic tumor (p = 0.01). Low mobility was not significantly associated with compliance. Subcutaneous unfractionated heparin was associated with compliance (p < 0.0001); warfarin (p < 0.0001), heparin infusion (p < 0.0001) and low-molecular-weight heparin (p < 0.0001) with non-compliance. Non-compliance was associated with increased mortality (p = 0.01), LOS (p < 0.0001), readmissions (p = 0.0004). Known VTE risk factors (mobility, BMI, comorbidities) were not associated with prescriber compliance patterns. Integrating risk assessment models into provider practice may improve compliance.

The association of clinically relevant variables with chest radiograph lung disease burden quantified in real-time by radiologists upon initial presentation in individuals hospitalized with COVID-19.

OBJECTIVES: We aimed to correlate lung disease burden on presentation chest radiographs (CXR), quantified at the time of study interpretation, with clinical presentation in patients hospitalized with coronavirus disease 2019 (COVID-19). MATERIAL AND METHODS: This retrospective cross-sectional study included 5833 consecutive adult patients, aged 18 and older, hospitalized with a diagnosis of COVID-19 with a CXR quantified in real-time while hospitalized in 1 of 12 acute care hospitals across a multihospital integrated healthcare network between March 24, 2020, and May 22, 2020. Lung disease burden was quantified in real-time by 118 radiologists on 5833 CXR at the time of exam interpretation with each lung annotated by the degree of lung opacity as clear (0%), mild (1-33%), moderate (34-66%), or severe (67-100%). CXR findings were classified as (1) clear versus disease, (2) unilateral versus bilateral, (3) symmetric versus asymmetric, or (4) not severe versus severe. Lung disease burden was characterized on initial presentation by patient demographics, co-morbidities, vital signs, and lab results with chi-square used for univariate analysis and logistic regression for multivariable analysis. RESULTS: Patients with severe lung disease were more likely to have oxygen impairment, an elevated respiratory rate, low albumin, high lactate dehydrogenase, and high ferritin compared to non-severe lung disease. A lack of opacities in COVID-19 was associated with a low estimated glomerular filtration rate, hypernatremia, and hypoglycemia. CONCLUSIONS: COVID-19 lung disease burden quantified in real-time on presentation CXR was characterized by demographics, comorbidities, emergency severity index, Charlson Comorbidity Index, vital signs, and lab results on 5833 patients. This novel approach to real-time quantified chest radiograph lung disease burden by radiologists needs further research to understand how this information can be incorporated to improve clinical care for pulmonary-related diseases.. An absence of opacities in COVID-19 may be associated with poor oral intake and a prerenal state as evidenced by the association of clear CXRs with a low eGFR, hypernatremia, and hypoglycemia.

A radiographic, deep transfer learning framework, adapted to estimate lung opacities from chest x-rays.

Chest radiographs (CXRs) are the most widely available radiographic imaging modality used to detect respiratory diseases that result in lung opacities. CXR reports often use non-standardized language that result in subjective, qualitative, and non-reproducible opacity estimates. Our goal was to develop a robust deep transfer learning framework and adapt it to estimate the degree of lung opacity from CXRs. Following CXR data selection based on exclusion criteria, segmentation schemes were used for ROI (Region Of Interest) extraction, and all combinations of segmentation, data balancing, and classification methods were tested to pick the top performing models. Multifold cross validation was used to determine the best model from the initial selected top models, based on appropriate performance metrics, as well as a novel Macro-Averaged Heatmap Concordance Score (MA HCS). Performance of the best model is compared against that of expert physician annotators, and heatmaps were produced. Finally, model performance sensitivity analysis across patient populations of interest was performed. The proposed framework was adapted to the specific use case of estimation of degree of CXR lung opacity using ordinal multiclass classification. Acquired between March 24, 2020, and May 22, 2020, 38,365 prospectively annotated CXRs from 17,418 patients were used. We tested three neural network architectures (ResNet-50, VGG-16, and ChexNet), three segmentation schemes (no segmentation, lung segmentation, and lateral segmentation based on spine detection), and three data balancing strategies (undersampling, double-stage sampling, and synthetic minority oversampling) using 38,079 CXR images for training, and validation with 286 images as the out-of-the-box dataset that underwent expert radiologist adjudication. Based on the results of these experiments, the ResNet-50 model with undersampling and no ROI segmentation is recommended for lung opacity classification, based on optimal values for the MAE metric and HCS (Heatmap Concordance Score). The degree of agreement between the opacity scores predicted by this model with respect to the two sets of radiologist scores (OR or Original Reader and OOBTR or Out Of Box Reader) in terms of performance metrics is superior to the inter-radiologist opacity score agreement.

Oropharyngeal Dysphagia in Hospitalized Older Adults With Dementia: A Mixed-Methods Study of Care Partners.

PURPOSE: Oropharyngeal dysphagia (OD) affects nearly 90% of hospitalized persons with dementia. Yet, little is known about the care partner experience. The purpose of our study was to describe the experience of care partners related to OD management in patients with dementia as they transition from the hospital to the community setting. METHOD: Using a mixed-methods approach, we conducted telephone interviews with care partners of recently hospitalized older adults with dementia and OD. Interviews consisted of quantitative/qualitative assessments: communication with health care team, perception about risks/benefits of dysphagia diet, and informational needs. Descriptive statistics were used for quantitative data. For the qualitative data, transcripts were independently coded by research team and categorized into themes. RESULTS: Of the care partners interviewed (N = 24), mean age was 63.5 (SD = 14.9), 62.5% were female, and 66.7% were White. Nearly 60% of patients had severe dementia, and 66.7% required feeding assistance. Care partners (n = 18) reported moderate burden of 14.11 (SD = 10.03). Most care partners (83.3%) first learned about OD during hospitalization. Only 29.2% of care partners reported that they discussed OD with a physician. Care partner perception of dysphagia diet risks/benefits ranged widely: 33.3% thought dysphagia diets would promote a more enjoyable existence. Over half (54.2%) of care partners indicated no choice regarding dysphagia diets was presented to them. Two thirds (n = 16) of care partners were nonadherent to diet recommendations; the top reason (n = 13%) was diet refusal by patients. Although 83.3% of care partners wanted additional information regarding dysphagia management, only 20.8% sought any. CONCLUSIONS: Our findings highlight that care partners of persons with dementia face significant OD-related communication and informational gaps, which may lead to elevated burden. Future studies are needed to address unmet OD-related care partner needs.

Reducing Behavioral and Psychological Symptoms of Dementia in Acutely Ill Patients via Patient Engagement Specialists: A Pilot Feasibility Study.

Behavioral and psychological symptoms of dementia (BPSD) are common in hospitalized persons living with dementia (PLWD). This pilot aimed to test the feasibility of an innovative model of care, PES-4-BPSD (a dementia unit staffed with Patient Engagement Specialists, PES). Non-randomized pilot feasibility trial was conducted, enrolling N = 158 patients to the intervention unit (n = 79, a 10-bed dementia unit, staffed with nursing assistants, NAs, with mental health backgrounds, PES) and an enhanced control unit (n = 79, 40-bed medicine unit, staffed with NAs). All NAs/PES (N = 63) received dementia training, with completion rate of 82.5%. Overall, patients had ~1 NPI-Q (Neuropsychiatric Inventory Questionnaire) assessment/48 hr. 97% (n = 153) of PLWD exhibited at least one behavior. Average NPI-Q scores did not differ across intervention (5.36) and control (3.87) units (p = .23). Patients on the intervention unit had 88% (p = .002) shorter duration of constant observation. A dementia care unit staffed by PES is an innovative model requiring further research.

Early DNR in Older Adults Hospitalized with SARS-CoV-2 Infection During Initial Pandemic Surge.

The role of early Do Not Resuscitate (DNR) in hospitalized older adults (OAs) with SARS-CoV-2 infection is unknown. The objective of the study was to identify characteristics and outcomes associated with early DNR in hospitalized OAs with SARS-CoV-2. We conducted a retrospective chart review of older adults (65+) hospitalized with COVID-19 in New York, USA, between March 1, 2020, and April 20, 2020. Patient characteristics and hospital outcomes were collected. Early DNR (within 24 hours of admission) was compared to non-early DNR (late DNR, after 24 hours of admission, or no DNR). Outcomes included hospital morbidity and mortality. Of 4961 patients, early DNR prevalence was 5.7% (n = 283). Compared to non-early DNR, the early DNR group was older (85.0 vs 76.8, P < .001), women (51.2% vs 43.6%, P = .012), with higher comorbidity index (3.88 vs 3.36, P < .001), facility-based (49.1% vs 19.1%, P < .001), with dementia (13.3% vs 4.6%, P < .001), and severely ill on presentation (57.9% vs 32.3%, P < .001). In multivariable analyses, the early DNR group had higher mortality risk (OR: 2.94, 95% CI: 2.10-4.11), less hospital delirium (OR: 0.55, 95% CI: 0.40-.77), lower use of invasive mechanical ventilation (IMV, OR: 0.37, 95% CI: .21-.67), and shorter length of stay (LOS, 4.8 vs 10.3 days, P < .001), compared to non-early DNR. Regarding early vs late DNR, while there was no difference in mortality (OR: 1.12, 95% CI: 0.85-1.62), the early DNR group experienced less delirium (OR: 0.55, 95% CI: .40-.75), IMV (OR: 0.53, 95% CI: 0.29-.96), and shorter LOS (4.82 vs 10.63 days, OR: 0.35, 95% CI: 0.30-.41). In conclusion, early DNR prevalence in hospitalized OAs with COVID-19 was low, and compared to non-early DNR is associated with higher mortality but lower morbidity.

Factors and Outcomes Associated With Dysphagia in Hospitalized Persons With Dementia.

OBJECTIVES: Dysphagia is prevalent in older adults with dementia, particularly in the acute care setting. The objective of this study was to use an innovative approach to extract a more representative sample of patients with dysphagia from the electronic health record (EHR) to determine patient characteristics, hospital practices, and outcomes associated with dysphagia in hospitalized persons with dementia. DESIGN: A retrospective study of hospitalized adults (aged ≥65 years) with dementia was conducted in 7 hospitals across the greater New York metropolitan area. SETTING AND PARTICIPANTS: Data were obtained from the inpatient EHR with the following inclusion criteria: age ≥65 years; admitted to one of 7 health system hospitals between January 1, 2019, and December 31, 2019; and documented past medical diagnosis of dementia (based on International Classification of Diseases, Ninth Revision). METHODS: A diagnosis of dysphagia was defined as nurse documentation of a positive bedside swallow screening, nurse documentation of "difficulty swallowing" as reason for not performing bedside swallow screening, and physician documentation of a dysphagia diagnosis. RESULTS: Of adults with dementia (N = 8637), the average age was 84.5 years, 61.6% were female, and 18.1% were Black and 9.3% Hispanic. Dysphagia was identified in 41.8% (n = 3610). In multivariable models, dysphagia was associated with invasive mechanical ventilation [odds ratio (OR) 4.53, 95% CI 3.55-5.78], delirium (OR 1.53, 95% CI 1.40-1.68), increased length of stay (B = 3.29, 95% CI 2.98-3.60), and mortality (OR 4.44, 95% CI 3.54-5.55). CONCLUSIONS AND IMPLICATIONS: Given its high prevalence, underrecognition, and associated poor outcomes, improving large-scale dysphagia identification can impact clinical care and advance research in hospitalized persons with dementia.

Patient Factors and Hospital Outcomes Associated With Atypical Presentation in Hospitalized Older Adults With COVID-19 During the First Surge of the Pandemic.

BACKGROUND: Literature indicates an atypical presentation of COVID-19 among older adults (OAs). Our purpose is to identify the frequency of atypical presentation and compare demographic and clinical factors, and short-term outcomes, between typical versus atypical presentations in OAs hospitalized with COVID-19 during the first surge of the pandemic. METHODS: Data from the inpatient electronic health record were extracted for patients aged 65 and older, admitted to our health systems' hospitals with COVID-19 between March 1 and April 20, 2020. Presentation as reported by the OA or his/her representative is documented by the admitting professional and includes both symptoms and signs. Natural language processing was used to code the presence/absence of each symptom or sign. Typical presentation was defined as words indicating fever, cough, or shortness of breath; atypical presentation was defined as words indicating functional decline or altered mental status. RESULTS: Of 4 961 unique OAs, atypical presentation characterized by functional decline or altered mental status was present in 24.9% and 11.3%, respectively. Atypical presentation was associated with older age, female gender, Black race, non-Hispanic ethnicity, higher comorbidity index, and the presence of dementia and diabetes mellitus. Those who presented typically were 1.39 times more likely than those who presented atypically to receive intensive care unit-level care. Hospital outcomes of mortality, length of stay, and 30-day readmission were similar between OAs with typical versus atypical presentations. CONCLUSION: Although atypical presentation in OAs is not associated with the same need for acute intervention as respiratory distress, it must not be dismissed.

Development and validation of self-monitoring auto-updating prognostic models of survival for hospitalized COVID-19 patients.

Clinical prognostic models can assist patient care decisions. However, their performance can drift over time and location, necessitating model monitoring and updating. Despite rapid and significant changes during the pandemic, prognostic models for COVID-19 patients do not currently account for these drifts. We develop a framework for continuously monitoring and updating prognostic models and apply it to predict 28-day survival in COVID-19 patients. We use demographic, laboratory, and clinical data from electronic health records of 34912 hospitalized COVID-19 patients from March 2020 until May 2022 and compare three modeling methods. Model calibration performance drift is immediately detected with minor fluctuations in discrimination. The overall calibration on the prospective validation cohort is significantly improved when comparing the dynamically updated models against their static counterparts. Our findings suggest that, using this framework, models remain accurate and well-calibrated across various waves, variants, race and sex and yield positive net-benefits.

Retrospective analysis of 1118 outpatient chest CT scans to determine factors associated with excess scan length.

RATIONALE OBJECTIVES: Excess z-axis scanning continues as an unnecessary source of radiation. This study seeks to determine patient, technologist and CT factors that affect excess scan length for chest CT. MATERIALS AND METHODS: Retrospective evaluation of 1118 consecutive noncontrast chest CT scans, over twelve consecutive months, was performed for evaluation of scan length above and below the lung parenchyma. Scan length >2 cm was considered excessive. Bivariate analysis for mean excess scan length and presence of excess scan length analyzed technologist's exam volume during the study period, patient age, patient gender, day of week, and time of day as categorical variables. Technologists performing >100 chest CT scans during the study period were considered high-volume while all others were considered low-volume. RESULTS: Mean excess scan length was 5 mm, 29 mm, and 33 mm above the lungs, below the lungs, and total. 81% and 95% of studies had excess scanning above the lungs and below the lungs respectively. Multivariable analysis showed that high volume technologists, male patients, and patients younger than 65 had a greater amount of excess scan length and presence of excessive scanning above the lungs; high volume technologists and male patients had a greater amount of excess scan length below the lungs, and high volume technologists and patients older than 65 had greater presence of excessive scanning below the lungs, each p < 0.001. CONCLUSIONS: Excess scanning on chest CT is common, varies by patient age and gender and was significantly greater for high volume technologists.

Using Charlson Comorbidity Index to Predict Short-Term Clinical Outcomes in Hospitalized Older Adults.

This study examined the prognostic value of the Charlson Comorbidity Index (CCI) in predicting short-term clinical outcomes in hospitalized older adults. We conducted a retrospective cohort study of patients, older than 75 years, admitted to the medicine service at a large tertiary hospital (New York). We used the Enhanced International Classification of Disease, 9th Revision, Clinical Modification adaptation to abstract the CCI from electronic medical records. The CCI scores were compared, using the standard Deyo version and the Schneeweiss version. Outcome measures included in-hospital mortality, length of stay (LOS), and 30-day readmissions. When comparing Charlson/Deyo and Charlson/Deyo/Schneeweiss with and without age, we found similar significant association with regard to in-hospital mortality, with a moderate predictive ability (area under the curve [AUC]: 0.5906-0.6433). However, for 30-day readmissions and LOS, the predictive ability was poor (AUC: 0.5598-0.6106 and ρ: 0.11-0.12, respectively). The CCI is, at most, a moderate predictor of in-hospital mortality and a poor predictor of other important healthcare outcomes relevant to administrative healthcare practices.

A Computerized Method for Measuring Computed Tomography Pulmonary Angiography Yield in the Emergency Department: Validation Study.

BACKGROUND: Use of computed tomography pulmonary angiography (CTPA) in the assessment of pulmonary embolism (PE) has markedly increased over the past two decades. While this technology has improved the accuracy of radiological testing for PE, CTPA also carries the risk of substantial iatrogenic harm. Each CTPA carries a 14% risk of contrast-induced nephropathy and a lifetime malignancy risk that can be as high as 2.76%. The appropriate use of CTPA can be estimated by monitoring the CTPA yield, the percentage of tests positive for PE. This is the first study to propose and validate a computerized method for measuring the CTPA yield in the emergency department (ED). OBJECTIVE: The objective of our study was to assess the validity of a novel computerized method of calculating the CTPA yield in the ED. METHODS: The electronic health record databases at two tertiary care academic hospitals were queried for CTPA orders completed in the ED over 1-month periods. These visits were linked with an inpatient admission with a discharge diagnosis of PE based on the International Classification of Diseases codes. The computerized the CTPA yield was calculated as the number of CTPA orders with an associated inpatient discharge diagnosis of PE divided by the total number of orders for completed CTPA. This computerized method was then validated by 2 independent reviewers performing a manual chart review, which included reading the free-text radiology reports for each CTPA. RESULTS: A total of 349 CTPA orders were completed during the 1-month periods at the two institutions. Of them, acute PE was diagnosed on CTPA in 28 studies, with a CTPA yield of 7.7%. The computerized method correctly identified 27 of 28 scans positive for PE. The one discordant scan was tied to a patient who was discharged directly from the ED and, as a result, never received an inpatient discharge diagnosis. CONCLUSIONS: This is the first successful validation study of a computerized method for calculating the CTPA yield in the ED. This method for data extraction allows for an accurate determination of the CTPA yield and is more efficient than manual chart review. With this ability, health care systems can monitor the appropriate use of CTPA and the effect of interventions to reduce overuse and decrease preventable iatrogenic harm.