National Healthcare Quality and Disparities Report
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 25 of 34 Research Studies DisplayedHaimovich AD, Shah MN, Southerland LT
Automating risk stratification for geriatric syndromes in the emergency department.
This study discussed using automated risk stratification to implement screening programs for geriatric syndromes in the emergency department (ED). This method would reduce significant workloads at a time of record-breaking ED patient volumes, staff shortages, and hospital boarding crises. The authors defined the concept of automated risk stratification and screening using existing electronic health record (EHR) data. They discussed progress made in three potential use cases in the ED: falls, cognitive impairment, and end-of-life and palliative care; emphasizing the importance of linking automated screening with systems of healthcare delivery. They found that research progress and operational deployment vary by use case, ranging from deployed solutions in falls screening to algorithmic validation in cognitive impairment and end-of-life care, but should still be considered a potential solution.
AHRQ-funded; HS027735.
Citation: Haimovich AD, Shah MN, Southerland LT .
Automating risk stratification for geriatric syndromes in the emergency department.
J Am Geriatr Soc 2024 Jan; 72(1):258-67. doi: 10.1111/jgs.18594..
Keywords: Elderly, Emergency Department, Risk, Health Information Technology (HIT)
Song J, Min SH, Chae S
Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care.
The purpose of this study was to characterize risk factor patterns documented in home health care (HHC) clinical notes and explore their relationships with hospitalizations or emergency department (ED) visits. The researchers analyzed data for 73,350 episodes of care from one large HHC organization utilizing dynamic time warping and hierarchical clustering analysis to characterize the patterns of risk factors over time documented in clinical notes. The study found that six temporal clusters emerged, reflecting varying patterns in how risk factors were documented. Patients with a sharp increase in documented risk factors over time had a 3 times greater probability of hospitalization or ED visit than patients with no documented risk factors. The majority of risk factors were found in the physiological domain, and a minority were found in the environmental domain.
AHRQ-funded; HS027742.
Citation: Song J, Min SH, Chae S .
Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care.
J Am Med Inform Assoc 2023 Oct 19; 30(11):1801-10. doi: 10.1093/jamia/ocad101..
Keywords: Emergency Department, Hospitalization, Home Healthcare, Risk
Chae S, Davoudi A, Song J
Predicting emergency department visits and hospitalizations for patients with heart failure in home healthcare using a time series risk model.
This study’s objective was to develop a time series risk model for predicting emergency department (ED) visits and hospitalizations in patients with heart failure (HF) using longitudinal electronic health record data. The authors explored which data sources yield the best-performing models over various time windows. They used data collected from 9362 patients from a large home healthcare (HHC) agency and iteratively developed risk models using both structured and unstructured data. They developed seven specific sets of variables including: (1) the Outcome and Assessment Information Set, (2) vital signs, (3) visit characteristics, (4) rule-based natural language processing-derived variables, (5) term frequency-inverse document frequency variables, (6) Bio-Clinical Bidirectional Encoder Representations from Transformers variables, and (7) topic modeling. Risk models for 18 time windows (1-15, 45, and 60 days) before an ED visit or hospitalization were developed. They compared risk prediction performances using recall, precision, accuracy, F1, and area under the receiver operating curve (AUC). The best-performing model was built using a combination of all 7 sets of variables and the time window of 4 days before an ED visit or hospitalization.
AHRQ-funded; HS027742.
Citation: Chae S, Davoudi A, Song J .
Predicting emergency department visits and hospitalizations for patients with heart failure in home healthcare using a time series risk model.
J Am Med Inform Assoc 2023 Sep 25; 30(10):1622-33. doi: 10.1093/jamia/ocad129..
Keywords: Hospitalization, Emergency Department, Risk
Ray EM, Hinton SP, Reeder-Hayes KE
Risk factors for return to the emergency department and readmission in patients with hospital-diagnosed advanced lung cancer.
The objectives of this study were to examine the patterns of care and risk factors for subsequent acute care utilization among patients with hospital-diagnosed advanced lung cancer (ALC). Researchers identified patients with incident ALC from 2007-13 and an index hospitalization within 7 days of diagnosis in Surveillance, Epidemiology, and End Results-Medicare. Results showed that more than half of the incident ALC patients were hospitalized around the time of diagnosis; among those who survived to discharge, only 37% received systemic cancer treatment. Many patients experienced an early readmittance and most died within 6 months. The researchers conclude that such patients may benefit from increased access to palliative and other supportive care during hospitalization to prevent subsequent health care utilization.
AHRQ-funded; HS000032.
Citation: Ray EM, Hinton SP, Reeder-Hayes KE .
Risk factors for return to the emergency department and readmission in patients with hospital-diagnosed advanced lung cancer.
Med Care 2023 Apr;61(4):237-46. doi: 10.1097/mlr.0000000000001829.
Keywords: Emergency Department, Hospital Readmissions, Cancer: Lung Cancer, Cancer, Risk
Song J, Chae S, Bowles KH
The identification of clusters of risk factors and their association with hospitalizations or emergency department visits in home health care.
The purpose of this retrospective cohort study was to identify risk factor clusters in home health care and assess whether the clusters are related with hospitalizations or emergency department visits. The researchers included 61,454 patients associated with 79,079 episodes receiving home health care from one of the largest home health care organizations in the U.S. The study found that a total of 11.6% of home health episodes resulted in hospitalizations or emergency department visits. Three clusters were formed by the risk factors: 1) Cluster 1- a combination of risk factors related to situations where patients may experience increased pain ("impaired physical comfort with pain"). 2) Cluster 2 - characterized by multiple comorbidities or other risks for hospitalization (e.g., prior falls, called "high comorbidity burden"). 3) Cluster 3 - "impaired cognitive/psychological and skin integrity" which includes dementia or skin ulcer. The risk of hospitalizations or emergency department visits increased by 1.95 times for Cluster 2 and by 2.12 times for Cluster 3 when compared to cluster 1. The study concluded that Varying combinations of risk factors affected the likelihood of negative outcomes.
AHRQ-funded; HS027742.
Citation: Song J, Chae S, Bowles KH .
The identification of clusters of risk factors and their association with hospitalizations or emergency department visits in home health care.
J Adv Nurs 2023 Feb; 79(2):593-604. doi: 10.1111/jan.15498..
Keywords: Emergency Department, Hospitalization, Home Healthcare, Risk
Jacobsohn GC, Leaf M, Liao F
Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
The authors used a collaborative and iterative approach to design and implement an automated clinical decision support system (CDS) for Emergency Department (ED) providers to identify and refer older adult ED patients at high risk of future falls. The system was developed using collaborative input from an interdisciplinary design team and integrated seamlessly into existing ED workflows. A key feature of development was the unique combination of patient experience strategies, human-centered design, and implementation science, which allowed for the CDS tool and intervention implementation strategies to be designed simultaneously. Challenges included: usability problems, data inaccessibility, time constraints, low appointment availability, high volume of patients, and others. The study concluded that using the collaborative, iterative approach was successful in achieving all project goals, and could be applied to other cases.
AHRQ-funded; HS024558.
Citation: Jacobsohn GC, Leaf M, Liao F .
Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
Healthc 2022 Mar;10(1):100598. doi: 10.1016/j.hjdsi.2021.100598..
Keywords: Elderly, Clinical Decision Support (CDS), Shared Decision Making, Falls, Risk, Emergency Department, Health Information Technology (HIT)
Zhang NJ, Rameau P, Julemis M
Automated pulmonary embolism risk assessment using the Wells criteria: validation study.
The authors sought to create an automated process to calculate the Wells score for pulmonary embolism for emergency department patients, which might reduce unnecessary computed tomography pulmonary angiography (CTPA) testing. They designed the process using electronic health records data elements, including free-text fields, and calculated Wells scores for a sample of adult emergency department visits that resulted in a CTPA study for pulmonary embolism at two tertiary care hospitals in New York. After validation, the authors concluded that the development of the automated process to classify risk for pulmonary embolism in emergency department visits was successful.
AHRQ-funded; HS026196.
Citation: Zhang NJ, Rameau P, Julemis M .
Automated pulmonary embolism risk assessment using the Wells criteria: validation study.
JMIR Form Res 2022 Feb 28;6(2):e32230. doi: 10.2196/32230.
Keywords: Blood Clots, Respiratory Conditions, Risk, Emergency Department
Smulowitz PB, Burke RC, Ostrovsky D
Attitudes toward risk among emergency physicians and advanced practice clinicians in Massachusetts.
Risk aversion is a personality trait influential to decision making in medicine. Little is known about how emergency department (ED) clinicians differ in their attitudes toward risk taking. In this study, the investigators conducted a cross-sectional survey of practicing ED clinicians (physicians and advanced practice clinicians [APCs]) in Massachusetts using the following 4 existing validated scales: the Risk-Taking Scale (RTS), Stress from Uncertainty Scale (SUS), the Fear of Malpractice Scale (FMS), and the Need for (Cognitive) Closure Scale (NCC).
AHRQ-funded; HS26730.
Citation: Smulowitz PB, Burke RC, Ostrovsky D .
Attitudes toward risk among emergency physicians and advanced practice clinicians in Massachusetts.
J Am Coll Emerg Physicians Open 2021 Oct;2(5):e12573. doi: 10.1002/emp2.12573..
Keywords: Emergency Department, Risk
Enayati M, Sir M, Zhang X
Monitoring diagnostic safety risks in emergency departments: protocol for a machine learning study.
This study’s objective will be to identify variables associated with diagnostic errors in emergency departments using large-scale EHR data and machine learning techniques. It will use trigger algorithms with electronic health record (EHR) data repositories to generate a large data set of records that are labeled trigger-positive or trigger-negative, depending on if they meet certain criteria. This study will be conducted by 2 academic medical centers with affiliated community hospitals.
AHRQ-funded; HS027363; HS026622.
Citation: Enayati M, Sir M, Zhang X .
Monitoring diagnostic safety risks in emergency departments: protocol for a machine learning study.
JMIR Res Protoc 2021 Jun 14;10(6):e24642. doi: 10.2196/24642..
Keywords: Emergency Department, Diagnostic Safety and Quality, Patient Safety, Risk, Electronic Health Records (EHRs), Health Information Technology (HIT)
Cifra CL, Westlund E, Ten Eyck P
An estimate of missed pediatric sepsis in the emergency department.
AHRQ-funded; HS025753.
Citation: Cifra CL, Westlund E, Ten Eyck P .
An estimate of missed pediatric sepsis in the emergency department.
Diagnosis 2021;8(2):193-98. doi: 10.1515/dx-2020-0023..
Keywords: Children/Adolescents, Sepsis, Emergency Department, Diagnostic Safety and Quality, Medical Errors, Risk
Lin CY, Xie J, Freedman SB
Predicting adverse outcomes for Shiga toxin-producing Escherichia coli infections in emergency departments.
Investigators assessed the performance of a hemolytic uremic syndrome (HUS) severity score among children with Shiga toxin-producing Escherichia coli (STEC) infections and HUS by stratifying them according to their risk of adverse events. They found that the HUS severity score was able to discriminate between high- and low-risk children less than 5 years old with STEC-associated HUS at a statistically acceptable level; however, it did not appear to provide clinical benefit at a meaningful risk threshold.
AHRQ-funded; HS026503.
Citation: Lin CY, Xie J, Freedman SB .
Predicting adverse outcomes for Shiga toxin-producing Escherichia coli infections in emergency departments.
J Pediatr 2021 May;232:200-06.e4. doi: 10.1016/j.jpeds.2020.12.077..
Keywords: Children/Adolescents, Infectious Diseases, Emergency Department, Risk
Daymont C, Balamuth F, Scott HF
Elevated heart rate and risk of revisit with admission in pediatric emergency patients.
This study examines whether emergency department (ED) heart rate (HR) values can identify children at elevated risk of ED revisit with admission. The authors performed a retrospective cohort study of children ages 0-18 years discharged from a tertiary-care pediatric ED from 2013 to 2014. They created percentile curves for the last recorded HR for age using data from calendar year 2013 and used receiver operating characteristic (ROC) curves to characterize the performance of the percentiles for predicting ED revisit with admission within 72 hours. They evaluated 183,433 eligible ED visits and found that the last recorded HR for age had poor discrimination for predicting revisit with admission.
AHRQ-funded; HS023827.
Citation: Daymont C, Balamuth F, Scott HF .
Elevated heart rate and risk of revisit with admission in pediatric emergency patients.
Pediatr Emerg Care 2021 Apr;37(4):e185-e91. doi: 10.1097/pec.0000000000001552..
Keywords: Children/Adolescents, Emergency Department, Risk, Hospitalization
Lumpkin ST, Mihas P, Baldwin X
Surgical patient values frame and modify the impact of risk factors for non-routine postdischarge care: a mixed-methods study.
This mixed methods study looked at patient perspectives on risk factors of non-routine postdischarge care (emergency department visit or rehospitalization) for adult colorectal surgery patients. Surgery patients were identified from hospital records from 2017 to 2018. The authors enrolled 258 participants, surveyed 167, and interviewed 18. Depressive symptoms were found to be one of the many risk factors confirmed to increase non-routine health utilization.
AHRQ-funded; HS026363.
Citation: Lumpkin ST, Mihas P, Baldwin X .
Surgical patient values frame and modify the impact of risk factors for non-routine postdischarge care: a mixed-methods study.
Am J Surg 2021 Jan;221(1):195-203. doi: 10.1016/j.amjsurg.2020.05.016..
Keywords: Digestive Disease and Health, Surgery, Risk, Hospital Readmissions, Emergency Department
Topaz M, Woo K, Ryvicker M
Home healthcare clinical notes predict patient hospitalization and emergency department visits.
About 30% of home healthcare patients are hospitalized or visit an emergency department (ED) during a home healthcare (HHC) episode. Novel data science methods are increasingly used to improve identification of patients at risk for negative outcomes. The aim of the study was to identify patients at heightened risk hospitalization or ED visits using HHC narrative data (clinical notes).
AHRQ-funded; HS027742.
Citation: Topaz M, Woo K, Ryvicker M .
Home healthcare clinical notes predict patient hospitalization and emergency department visits.
Nurs Res 2020 Nov/Dec;69(6):448-54. doi: 10.1097/nnr.0000000000000470..
Keywords: Elderly, Home Healthcare, Emergency Department, Hospitalization, Risk, Electronic Health Records (EHRs), Health Information Technology (HIT)
Griffey RT, Schneider RM, Todorov AA
The emergency department trigger tool: a novel approach to screening for quality and safety events.
The goal of this study was to develop an automated version of a previously developed emergency department (ED) trigger tool to track the likelihood of an adverse event. Thirty triggers were associated with risk of harm. The authors identified 1,726 records out of 76,894 ED visits with greater than or equal to 1 trigger. They compared the results of the automated tool to the previous version and found it performed well. They began with a broad set of candidate triggers and validated a computerized query that eliminates the need for manual screening of triggers and also identified a refined set of triggers associated with adverse events in the ED.
AHRQ-funded; HS025052.
Citation: Griffey RT, Schneider RM, Todorov AA .
The emergency department trigger tool: a novel approach to screening for quality and safety events.
Ann Emerg Med 2020 Aug;76(2):230-40. doi: 10.1016/j.annemergmed.2019.07.032..
Keywords: Emergency Department, Patient Safety, Adverse Events, Medical Errors, Quality of Care, Risk
Shang J, Russell D, Dowding D
A predictive risk model for infection-related hospitalization among home healthcare patients.
Infection prevention is a high priority for home healthcare (HHC), but tools are lacking to identify patients at highest risk of developing infections. The purpose of this study was to develop and test a predictive risk model to identify HHC patients at risk of an infection-related hospitalization or emergency department visit. A nonexperimental study using secondary data was conducted.
AHRQ-funded; HS024723.
Citation: Shang J, Russell D, Dowding D .
A predictive risk model for infection-related hospitalization among home healthcare patients.
J Healthc Qual 2020 May/Jun;42(3):136-47. doi: 10.1097/jhq.0000000000000214..
Keywords: Elderly, Home Healthcare, Infectious Diseases, Community-Acquired Infections, Risk, Hospitalization, Emergency Department
Scott HF, Colborn KL, Sevick CJ
Development and validation of a predictive model of the risk of pediatric septic shock using data known at the time of hospital arrival.
The purpose of this observational cohort study was to derive and validate a model of risk of septic shock among children with suspected sepsis, using data known in the electronic health record at hospital arrival. The investigators concluded that their model estimated the risk of septic shock in children at hospital arrival earlier than existing models. They indicate it leveraged the predictive value of routine electronic health record data through a modern predictive algorithm and suggest it has the potential to enhance clinical risk stratification in the critical moments before deterioration.
AHRQ-funded; HS025696.
Citation: Scott HF, Colborn KL, Sevick CJ .
Development and validation of a predictive model of the risk of pediatric septic shock using data known at the time of hospital arrival.
J Pediatr 2020 Feb;217:145-51.e6. doi: 10.1016/j.jpeds.2019.09.079..
Keywords: Children/Adolescents, Sepsis, Emergency Department, Hospitals, Risk, Electronic Health Records (EHRs), Health Information Technology (HIT)
Paredes AZ, Malik AT, Cluse M
Discharge disposition to skilled nursing facility after emergent general surgery predicts a poor prognosis.
Emergency general surgery can have a profound impact on the functional status of even previously independent patients. In this study, the investigators examined the role and influence of discharging a patient to a skilled nursing facility. They concluded that after accounting for patient severity and perioperative course, discharge to a skilled nursing facility was an independent risk factor for death, readmission, and postdischarge complications.
AHRQ-funded; HS022694.
Citation: Paredes AZ, Malik AT, Cluse M .
Discharge disposition to skilled nursing facility after emergent general surgery predicts a poor prognosis.
Surgery 2019 Oct;166(4):489-95. doi: 10.1016/j.surg.2019.04.034..
Keywords: Nursing Homes, Hospital Discharge, Elderly, Ambulatory Care and Surgery, Emergency Department, Outcomes, Hospital Readmissions, Outcomes, Risk
Patterson BW, Jacobsohn GC, Shah MN
Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.
This study examined development and validation of a pragmatic natural language processing (NLP) approach to identify fall risk in older adults after emergency department (ED) visits. A single center retrospective review using data from 500 emergency department provider notes on older adults age 65 and older were random selected for analysis. The NLP algorithm successfully identified falls in ED notes with over 90% precision, and looks promising to reduce labor-intensive manual abstraction.
AHRQ-funded; HS024558.
Citation: Patterson BW, Jacobsohn GC, Shah MN .
Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.
BMC Med Inform Decis Mak 2019 Jul 22;19(1):138. doi: 10.1186/s12911-019-0843-7..
Keywords: Adverse Events, Elderly, Emergency Department, Falls, Risk, Patient Safety
Pang PS, Fermann GJ, Hunter BR
TACIT (High Sensitivity Troponin T Rules Out Acute Cardiac Insufficiency Trial).
This study examined the use of high-sensitivity troponin assays to determine whether a patient presenting in the emergency department with chest pains is safe for discharge. An observational study called High Sensitivity Troponin T Rules Out Acute Cardiac Insufficiency Trial (TACIT) explored whether serial high-sensitivity troponin (hsTnT) might aid in making diagnosis of acute heart failure faster. The presence of hsTnT above the 99th percentile usually indicates acute heart failure. Patients in the cohort with hsTnT at or above the 99th percentile were older, more often male, less often black, and more likely to have chronic kidney disease. The study found no difference in risk for 90-day death or rehospitalization or return ED visits in the group with hsTnT above the 99th percentile than those with levels below the 99th percentile so hsTnT would not be considered useful.
AHRQ-funded; HS025411.
Citation: Pang PS, Fermann GJ, Hunter BR .
TACIT (High Sensitivity Troponin T Rules Out Acute Cardiac Insufficiency Trial).
Circ Heart Fail 2019 Jul;12(7):e005931. doi: 10.1161/circheartfailure.119.005931..
Keywords: Cardiovascular Conditions, Heart Disease and Health, Emergency Department, Risk, Shared Decision Making
Patterson BW, Engstrom CJ, Sah V
Training and interpreting machine learning algorithms to evaluate fall risk after emergency department visits.
This study examined the potential of using machine learning algorithms to evaluate fall risk after an emergency department (ED) visit. They compared several machine learning methodologies for creation of a risk stratification algorithm to predict the outcome of a return visit for a fall within 6 months of an ED visit.
AHRQ-funded; HS024558; HS024342.
Citation: Patterson BW, Engstrom CJ, Sah V .
Training and interpreting machine learning algorithms to evaluate fall risk after emergency department visits.
Med Care 2019 Jul;57(7):560-66. doi: 10.1097/mlr.0000000000001140..
Keywords: Adverse Events, Elderly, Emergency Department, Falls, Risk, Patient Safety
Griffey RT, Schneider RM, Todorov AA
Critical review, development, and testing of a taxonomy for adverse events and near misses in the emergency department.
Researchers created and tested a taxonomy for adverse events (AEs) and near misses for use in the emergency department (ED). This taxonomy is patient-centered, as opposed to most taxonomies which fail to describe harm experienced by patients and focus instead on errors and uses too broad categorizations. The authors reviewed candidate taxonomies using an iterative process and selected the Adventist Health Systems AE taxonomy and modified it for use in the ED. After testing with reviewers, agreement with the criterion standard was 92% at the category level and 88% at the subcategory level. Performance from individual raters ranged from very good (88%) to near perfect (98%) at the main category level.
AHRQ-funded; HS025052.
Citation: Griffey RT, Schneider RM, Todorov AA .
Critical review, development, and testing of a taxonomy for adverse events and near misses in the emergency department.
Acad Emerg Med 2019 Jun;26(6):670-79. doi: 10.1111/acem.13724..
Keywords: Adverse Events, Emergency Department, Medical Errors, Patient Safety, Risk
Hirayama A, Goto T, Shimada YJ
Acute exacerbation of chronic obstructive pulmonary disease and subsequent risk of emergency department visits and hospitalizations for atrial fibrillation.
Although emerging evidence has suggested the relationship of chronic obstructive pulmonary disease with atrial fibrillation (AF), little is known about whether acute exacerbation of chronic obstructive pulmonary disease (AECOPD) increases the risk of repeated AF-related healthcare utilization. The investigators found that among patients with existing AF, AECOPD was associated with a higher risk of AF-related ED visit or hospitalization in the first 90-day post-AECOPD period.
AHRQ-funded; HS023305.
Citation: Hirayama A, Goto T, Shimada YJ .
Acute exacerbation of chronic obstructive pulmonary disease and subsequent risk of emergency department visits and hospitalizations for atrial fibrillation.
Circ Arrhythm Electrophysiol 2018 Sep;11(9):e006322. doi: 10.1161/circep.118.006322..
Keywords: Healthcare Cost and Utilization Project (HCUP), Emergency Department, Respiratory Conditions, Heart Disease and Health, Cardiovascular Conditions, Chronic Conditions, Hospitalization, Risk, Healthcare Utilization
Koziatek CA, Simon E, Horwitz LI
Automated pulmonary embolism risk classification and guideline adherence for computed tomography pulmonary angiography ordering.
The objective of this study was to measure the performance of automated, structured data-only versions of the Wells and revised Geneva risk scores in emergency department encounters during which a computed tomography pulmonary angiography was ordered. The hypothesis was that such an automated method would classify a patient's pulmonary embolism risk with high accuracy compared to manual chart review.
AHRQ-funded; HS024376.
Citation: Koziatek CA, Simon E, Horwitz LI .
Automated pulmonary embolism risk classification and guideline adherence for computed tomography pulmonary angiography ordering.
Acad Emerg Med 2018 Sep;25(9):1053-61. doi: 10.1111/acem.13442..
Keywords: Respiratory Conditions, Risk, Diagnostic Safety and Quality, Emergency Department, Imaging, Guidelines
Chaaban MR, Zhang D, Resto V
Factors influencing recurrent emergency department visits for epistaxis in the elderly.
The objective of the study was to determine the risk factors associated with recurrent epistaxis requiring emergency department (ED) visits in the elderly. The investigators concluded that additional ED visits for epistaxis were more common in the elderly and in males. Congestive heart failure, diabetes mellitus and obstructive sleep apnea were found to be independent risk factors.
AHRQ-funded; HS022134.
Citation: Chaaban MR, Zhang D, Resto V .
Factors influencing recurrent emergency department visits for epistaxis in the elderly.
Auris Nasus Larynx 2018 Aug;45(4):760-64. doi: 10.1016/j.anl.2017.11.010..
Keywords: Elderly, Emergency Department, Risk, Respiratory Conditions, Healthcare Utilization