National Healthcare Quality and Disparities Report
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- Adverse Drug Events (ADE) (3)
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- Electronic Health Records (EHRs) (6)
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- Falls (1)
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- Home Healthcare (6)
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- (-) Hospitalization (54)
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- (-) Risk (54)
- Sepsis (1)
- Stroke (1)
- Substance Abuse (1)
- Surgery (5)
- Transitions of Care (1)
- Women (3)
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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 54 Research Studies DisplayedSong 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
Herzig SJ, Anderson TS, Urman RD
Risk factors for opioid-related adverse drug events among older adults after hospitalization for major orthopedic procedures.
The purpose of this retrospective cohort study was to identify risk factors for opioid-related adverse drug events (ORADEs) after hospital discharge following orthopedic procedures. The participants of this study included a national sample of Medicare beneficiaries who underwent major orthopedic surgery during hospitalization in 2016 and had an opioid prescription filled within 2 days of discharge. The study found that among 30,514 hospitalizations with a major orthopedic procedure and an opioid claim, a potential ORADE requiring hospital revisit occurred in 2.5%. After adjustment for patient characteristics, prior opioid use, co-prescribed sedating medications, and opioid prescription characteristics were not related with ORADEs. Independent risk factors did include age of 80 years or older, female sex, and clinical conditions, including heart failure, respiratory illness, kidney disease, dementia/delirium, anxiety disorder, and musculoskeletal/nervous system injuries.
AHRQ-funded; HS026215.
Citation: Herzig SJ, Anderson TS, Urman RD .
Risk factors for opioid-related adverse drug events among older adults after hospitalization for major orthopedic procedures.
J Patient Saf 2023 Oct 1; 19(6):379-85. doi: 10.1097/pts.0000000000001144..
Keywords: Elderly, Opioids, Adverse Drug Events (ADE), Adverse Events, Hospitalization, Orthopedics, Surgery, Medication, Risk, Medication: Safety, Patient Safety
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
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
Hobensack M, Ojo M, Barrón Y
Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians.
The objectives of this study were to identify risk factors that home healthcare clinicians associate with patient deterioration and to understand clinicians’ response to and documentation of these risk factors. The authors interviewed multidisciplinary home healthcare clinicians and used directed content analysis to identify risk factors for deterioration. A total of 79 risk factors were identified by the clinicians, who responded most often by communicating with the prescribing provider or following up with patients and caregivers. Clinicians also acknowledged that social factors played a role in deterioration risk. The authors noted that, since most risk factors were documented in clinical notes, methods such as natural language processing are needed to extract them. They concluded that by providing a comprehensive list of risk factors grounded in clinician expertise and mapped to standardized terminologies, the results of their study supported the development of an early warning system for patient deterioration.
AHRQ-funded; HS027742.
Citation: Hobensack M, Ojo M, Barrón Y .
Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians.
J Am Med Inform Assoc 2022 Apr 13;29(5):805-12. doi: 10.1093/jamia/ocac023..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Home Healthcare, Risk, Hospitalization
Khodneva Y, Goyal P, Levitan EB
Depressive symptoms and incident hospitalization for heart failure: findings From the REGARDS Study.
The purpose of this study was to determine whether depressive symptoms are associated with incident heart failure (HF), including hospitalization for HF overall or by subtype: HF with preserved (HFpEF) or reduced ejection fraction (HFrEF). The study found that over a median of 9.2 years of follow-up, there were 872 incident HF hospitalizations, 526 among those without CHD and 334 among those with CHD. The age-adjusted HF hospitalization incidence rates per 1000 person-years were 4.9 for participants with depressive symptoms compared with 3.2 for participants without depressive symptoms. For overall HF, the elevated risk lessened after controlling for covariates. Among those without baseline CHD, when HFpEF was evaluated separately, after controlling for all covariates, depressive symptoms were related with incident hospitalization. In contrast, depressive symptoms were not related with incident HFrEF hospitalizations. The researchers concluded that among individuals without CHD at baseline, depressive symptoms were related with incident hospitalization for HFpEF, but not for those with baseline CHD or HFrEF.
AHRQ-funded; HS013852.
Citation: Khodneva Y, Goyal P, Levitan EB .
Depressive symptoms and incident hospitalization for heart failure: findings From the REGARDS Study.
J Am Heart Assoc 2022 Apr 5;11(7):e022818. doi: 10.1161/jaha.121.022818..
Keywords: Depression, Behavioral Health, Heart Disease and Health, Cardiovascular Conditions, Hospitalization, Risk
Kamran F, Tang S, Otles E
Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study.
The authors sought to create and validate a simple and transferable machine learning model from electronic health record data to accurately predict clinical deterioration in patients with COVID-19 across institutions, through use of a novel paradigm for model development and code sharing. They determined that a model to predict clinical deterioration was developed rapidly in response to the COVID-19 pandemic at a single hospital, was applied externally without the sharing of data, and performed well across multiple medical centers, patient subgroups, and time periods, showing its potential as a tool for use in optimizing healthcare resources.
AHRQ-funded; HS028038.
Citation: Kamran F, Tang S, Otles E .
Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study.
BMJ 2022 Feb 17;376:e068576. doi: 10.1136/bmj-2021-068576..
Keywords: COVID-19, Hospitalization, Risk, Electronic Health Records (EHRs), Health Information Technology (HIT)
Williams D, Stout MJ, Rosenbloom JI
Preeclampsia predicts risk of hospitalization for heart failure with preserved ejection fraction.
Preeclampsia is associated with increased risk of future heart failure (HF), but the relationship between preeclampsia and HF subtypes are not well-established. The objective of this analysis was to identify the risk of HF with preserved ejection fraction (HFpEF) following a delivery complicated by preeclampsia/eclampsia. The investigators concluded that preeclampsia/eclampsia was an independent risk factor for future hospitalizations for HFpEF.
AHRQ-funded; HS019455.
Citation: Williams D, Stout MJ, Rosenbloom JI .
Preeclampsia predicts risk of hospitalization for heart failure with preserved ejection fraction.
J Am Coll Cardiol 2021 Dec 7;78(23):2281-90. doi: 10.1016/j.jacc.2021.09.1360..
Keywords: Healthcare Cost and Utilization Project (HCUP), Heart Disease and Health, Cardiovascular Conditions, Hospitalization, Risk, Labor and Delivery, Pregnancy, Women
Klein IA, Rosenberg SM, Reynolds KL
Impact of cancer history on outcomes among hospitalized patients with COVID-19.
Researchers investigated whether a current cancer diagnosis or cancer history is an independent risk factor for death in hospitalized patients with COVID-19. They found that patients with a history of cancer hospitalized for COVID-19 had similar mortality to matched hospitalized patients with COVID-19 without cancer, and a lower risk of complications, while patients with active cancer or recent cancer treatment had a similar risk for adverse outcomes compared with survivors of cancer. They concluded that active cancer, systemic cancer therapy, and a cancer history are not independent risk factors for death from COVID-19 among hospitalized patients, and hospitalized patients without cancer are more likely to have severe COVID-19.
AHRQ-funded; HS023680.
Citation: Klein IA, Rosenberg SM, Reynolds KL .
Impact of cancer history on outcomes among hospitalized patients with COVID-19.
Oncologist 2021 Aug;26(8):685-93. doi: 10.1002/onco.13794..
Keywords: COVID-19, Cancer, Risk, Mortality, Hospitalization, Outcomes
Song J, Woo K, Shang J
Predictive risk models for wound infection-related hospitalization or ED visits in home health care using machine-learning algorithms.
Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds in HHC have used data from clinical notes. Therefore, in this paper, the authors created a more accurate description of a patient's condition by extracting risk factors from clinical notes to build predictive models to identify a patient's risk of wound infection in HHC.
AHRQ-funded; HS024915.
Citation: Song J, Woo K, Shang J .
Predictive risk models for wound infection-related hospitalization or ED visits in home health care using machine-learning algorithms.
Adv Skin Wound Care 2021 Aug;34(8):1-12. doi: 10.1097/01.Asw.0000755928.30524.22..
Keywords: Home Healthcare, Injuries and Wounds, Risk, Hospitalization
Pollack LM, Lowder JL, Keller M
Racial/ethnic differences in the risk of surgical complications and posthysterectomy hospitalization among women undergoing hysterectomy for benign conditions.
The objective of this retrospective cohort study was to evaluate whether 30- and 90-day surgical complication and postoperative hospitalization rates after hysterectomy for benign conditions differed by race/ethnicity and whether the differences remained after controlling for patient, hospital, and surgical characteristics. The investigators concluded that Black and Asian/Pacific Islander women had higher risk of some 30- and 90-day surgical complications after hysterectomy than white women. Black and Hispanic women had higher risk of posthysterectomy hospitalization.
AHRQ-funded; HS019455.
Citation: Pollack LM, Lowder JL, Keller M .
Racial/ethnic differences in the risk of surgical complications and posthysterectomy hospitalization among women undergoing hysterectomy for benign conditions.
J Minim Invasive Gynecol 2021 May;28(5):1022-32.e12. doi: 10.1016/j.jmig.2020.12.032..
Keywords: Surgery, Risk, Racial and Ethnic Minorities, Adverse Events, Hospitalization, Women
Baillargeon J, Polychronopoulou E, Kuo YF
The impact of substance use disorder on COVID-19 outcomes.
The goal of this study was to examine the impact of substance use disorder on the risk of hospitalization, complications, and mortality among adult patients diagnosed as having COVID-19. Using data from the TriNetX Research Network database, primary analysis showed that substance use disorder was associated with an increased risk of hospitalization, ventilator use, and mortality. These findings suggest that COVID-19 patients with substance use disorders are at increased risk for adverse outcomes.
AHRQ-funded; HS026133.
Citation: Baillargeon J, Polychronopoulou E, Kuo YF .
The impact of substance use disorder on COVID-19 outcomes.
Psychiatr Serv 2021 May;72(5):578-81. doi: 10.1176/appi.ps.202000534..
Keywords: COVID-19, Substance Abuse, Hospitalization, Mortality, 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
Ye S, Hiura G, Fleck E
Hospital readmissions after implementation of a discharge care program for patients with COVID-19 illness.
The surge of coronavirus 2019 (COVID-19) hospitalizations in New York City required rapid discharges to maintain hospital capacity. The objective of this study was to determine whether lenient provisional discharge guidelines with remote monitoring after discharge resulted in safe discharges home for patients hospitalized with COVID-19 illness. The investigators found that lenient discharge criteria in conjunction with remote monitoring after discharge were associated with a rate of early readmissions after COVID-related hospitalizations that was comparable to the rate of readmissions after other reasons for hospitalization before the COVID pandemic.
AHRQ-funded; HS024262; HS025198.
Citation: Ye S, Hiura G, Fleck E .
Hospital readmissions after implementation of a discharge care program for patients with COVID-19 illness.
J Gen Intern Med 2021 Mar;36(3):722-29. doi: 10.1007/s11606-020-06340-w..
Keywords: COVID-19, Hospital Discharge, Hospital Readmissions, Hospitals, Public Health, Hospitalization, Risk
Bramante CT, Ingraham NE, Murray TA
Metformin and risk of mortality in patients hospitalised with COVID-19: a retrospective cohort analysis.
This study examined whether metformin use by patients with diagnosed with type 2 diabetes had reduced mortality when hospitalized for COVID-19. Pharmacy claims data from UnitedHealth Group’s Clinical Discovery Claims Database was used. Patient data were included if they were aged 18 years or older; had type 2 diabetes or obesity (defined based on claims); at least 6 months of continuous enrolment in 2019; and admission to hospital for COVID-19 confirmed by PCR; manual chart review by UHG; or reported from the hospital to UHG. Metformin was not associated with significant reduction in mortality among men, but there was an association with decreased mortality in women.
AHRQ-funded; HS026379.
Citation: Bramante CT, Ingraham NE, Murray TA .
Metformin and risk of mortality in patients hospitalised with COVID-19: a retrospective cohort analysis.
Lancet Healthy Longev 2021 Jan;2(1):e34-e41. doi: 10.1016/s2666-7568(20)30033-7..
Keywords: COVID-19, Hospitalization, Medication, Mortality, Risk, Diabetes, Chronic Conditions, Public Health, Infectious Diseases
Guglielminotti J, Li G
Exposure to general anesthesia for cesarean delivery and odds of severe postpartum depression requiring hospitalization.
This retrospective cohort study evaluated the risk of general anesthesia use in cesarean delivery versus neuraxial anesthesia on maternal mental health. Cesarean deliveries performed in New York State hospitals between 2006 and 2013 were included. Exclusion criteria included having more than 1 cesarean delivery during the study period, residing outside of New York State, and having a general anesthetic for other surgery or delivery in the year before or after the index case. The primary outcome looked at was severe postpartum depression (PPD), and secondary outcomes were suicidal ideation, anxiety disorders, and posttraumatic stress disorder (PTSD). The majority of cesareans used neuraxial anesthesia and only 8% (34,356) had general anesthesia. Severe PPD requiring hospitalization occurred in 1158 women with 60% identified during readmission. General anesthesia was found to be associated with a 54% increased odds of PPD, and a 91% increased odds of suicidal ideation or self-inflicted injury. There was insufficient evidence for increased risk of anxiety orders.
AHRQ-funded; HS025787.
Citation: Guglielminotti J, Li G .
Exposure to general anesthesia for cesarean delivery and odds of severe postpartum depression requiring hospitalization.
Anesth Analg 2020 Nov;131(5):1421-29. doi: 10.1213/ane.0000000000004663..
Keywords: Labor and Delivery, Pregnancy, Women, Depression, Behavioral Health, Surgery, Risk, Hospitalization, Medication, Adverse Drug Events (ADE), Adverse Events
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)
Wu SS, Bellantoni m, Weiner JP
Geriatric syndrome risk factors among hospitalized postacute Medicare patients.
The purpose of this study was to assess the association of geriatric syndrome risk factors with postacute utilization among hospitalized Medicare patients (both Medicare Advantage [MA] and fee-for-service [FFS] cohorts) and to examine patterns of postacute care for MA and FFS cohorts with high geriatric syndrome risk. The investigators found that geriatric syndrome risk factors not only play a role in postacute care and inpatient utilization in MA and FFS cohorts but also explain different utilizations between MA and FFS cohorts.
AHRQ-funded; HS000029.
Citation: Wu SS, Bellantoni m, Weiner JP .
Geriatric syndrome risk factors among hospitalized postacute Medicare patients.
Am J Manag Care 2020 Oct;26(10):e319-e26. doi: 10.37765/ajmc.2020.88505..
Keywords: Healthcare Cost and Utilization Project (HCUP), Elderly, Medicare, Risk, Healthcare Utilization, Hospitalization
Wehbe RM, Khan SS, Shah SJ
Predicting high-risk patients and high-risk outcomes in heart failure.
Identifying patients with heart failure at high risk for poor outcomes is important for patient care, resource allocation, and process improvement. Although numerous risk models exist to predict mortality, hospitalization, and patient-reported health status, they are infrequently used for several reasons, including modest performance, lack of evidence to support routine clinical use, and barriers to implementation. The authors discuss the potential of artificial to enhance the performance of risk prediction models.
AHRQ-funded; HS026385.
Citation: Wehbe RM, Khan SS, Shah SJ .
Predicting high-risk patients and high-risk outcomes in heart failure.
Heart Fail Clin 2020 Oct;16(4):387-407. doi: 10.1016/j.hfc.2020.05.002..
Keywords: Heart Disease and Health, Cardiovascular Conditions, Risk, Hospitalization
Hoffman GJ, Tinetti ME, Ha J
Prehospital and posthospital fall injuries in older US adults.
Investigators estimated the risk of older adult fall injury within and across discrete periods during a 12-month care episode anchored by an acute hospitalization using national data from 2006 to 2014. Participants in this cohort study included Medicare fee-for-service beneficiaries aged 65 and older from the Health and Retirement Study. The investigators found that an episode-based assessment of fall injury illustrated substantial variability in period-specific risks over an extended period including an anchor hospitalization. Risk transitions between periods included sizable increases just before hospitalization that do not fully subside after hospital discharge. Financial incentives to coordinate hospital and posthospital care for patients at risk for fall injury are needed.
AHRQ-funded; HS025838.
Citation: Hoffman GJ, Tinetti ME, Ha J .
Prehospital and posthospital fall injuries in older US adults.
JAMA Netw Open 2020 Aug 3;3(8):e2013243. doi: 10.1001/jamanetworkopen.2020.13243..
Keywords: Elderly, Falls, Injuries and Wounds, Risk, Hospitalization, Medicare
Lindell RB, Nishisaki A, Weiss SL
Risk of mortality in immunocompromised children with severe sepsis and septic shock.
This study’s objective was to assess the risk of mortality for immunocompromised children admitted to the hospital with septic shock or sepsis. This retrospective multicenter cohort study used eighty-three centers in the Virtual Pediatric systems database. The cohort included children admitted to the pediatric intensive care unit (PICU) with severe sepsis or septic shock from 2012-2016. Across 83 centers, 10,768 PICU admissions with an International Classification of Diseases, 9th Revision, Clinical Modification code for severe sepsis or septic shock were identified; with 3,021 of these patients (28%) having an immunocompromised diagnosis. PICU mortality rates varied widely by center, and those centers with a higher mean number of sepsis patients per month in a center had a lower PICU mortality rate. Multiple prior malignancies, hemophagocytic lymphohistiocytosis, congenital immunodeficiency, and hematopoietic cell transplant are conditions independently associated with an increased odds of PICU mortality in children with severe sepsis or septic shock.
AHRQ-funded; HS024511; HS026939; HS021583; HS022464.
Citation: Lindell RB, Nishisaki A, Weiss SL .
Risk of mortality in immunocompromised children with severe sepsis and septic shock.
Crit Care Med 2020 Jul;48(7):1026-33. doi: 10.1097/ccm.0000000000004329..
Keywords: Children/Adolescents, Mortality, Sepsis, Risk, Intensive Care Unit (ICU), Hospitalization, Hospitals
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
Basciotta M, Zhou W, Ngo L
Antipsychotics and the risk of mortality or cardiopulmonary arrest in hospitalized adults.
Investigators sought to evaluate the risk of death or nonfatal cardiopulmonary arrest in hospitalized adults exposed to antipsychotics. They found that, in hospitalized adults, typical antipsychotics were associated with increased mortality or cardiopulmonary arrest, whereas atypical antipsychotics were only associated with increased risk among adults age 65 years and older. They recommended that providers be thoughtful when prescribing antipsychotic medications, especially to older adults in settings where data regarding benefit are lacking.
AHRQ-funded; HS026215.
Citation: Basciotta M, Zhou W, Ngo L .
Antipsychotics and the risk of mortality or cardiopulmonary arrest in hospitalized adults.
J Am Geriatr Soc 2020 Mar;68(3):544-50. doi: 10.1111/jgs.16246..
Keywords: Medication, Risk, Hospitalization, Cardiovascular Conditions, Mortality, Elderly
Herzig SJ, Stefan MS, Pekow PS
Risk factors for severe opioid-related adverse events in a national cohort of medical hospitalizations.
The objective of this study was to identify independent risk factors for severe opioid-related adverse drug events (ORADEs) in hospitalized patients. This retrospective cohort study used data from medical patients hospitalized at US non-federal and acute care facilities with at least one pharmacy charge. They excluded patients with metastatic, hospice, or palliative care billing codes. Out of 731,208 hospitalizations there was a severe ORADE in 2727 (0.4%) of patients. Independent risk factors included advanced age, female gender, comorbidities, organ failures on admission, medication co-administrations, and characteristics of the opioids themselves. These risk factors can be used to inform physician decision-making and conversations with patients about risk.
AHRQ-funded; HS026215.
Citation: Herzig SJ, Stefan MS, Pekow PS .
Risk factors for severe opioid-related adverse events in a national cohort of medical hospitalizations.
J Gen Intern Med 2020 Feb;35(2):538-45. doi: 10.1007/s11606-019-05490-w..
Keywords: Opioids, Medication, Adverse Drug Events (ADE), Adverse Events, Risk, Hospitalization
Angraal S, Mortazavi BJ, Gupta A
Machine learning prediction of mortality and hospitalization in heart failure with preserved ejection fraction.
This study developed models to predict the risk of death and hospitalization in patients with heart failure (HF) with preserved ejection fraction (HFpEF). Data was used from the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist) clinical trial. Five methods: logistic regression with a forward selection of variables; logistic regression with a lasso regularization for variable selection; random forest (RF); gradient descent boosting; and support vector machine, were used to train models for assessing risks of mortality and HF hospitalization through 3 years of follow-up and were validated using 5-fold cross-validation. RF was found to be the best performing model for predicting mortality and HF hospitalization. Blood urea nitrogen levels, body mass index, and Kansas City Cardiomyopathy Questionnaire (KCCQ) subscale scores were strongly associated with mortality, while hemoglobin level, blood urea nitrogen, time since previous HF hospitalization, and KCCQ scores were the most significant predictors of HF hospitalization.
AHRQ-funded; HS023000.
Citation: Angraal S, Mortazavi BJ, Gupta A .
Machine learning prediction of mortality and hospitalization in heart failure with preserved ejection fraction.
JACC Heart Fail 2020 Jan;8(1):12-21. doi: 10.1016/j.jchf.2019.06.013..
Keywords: Heart Disease and Health, Cardiovascular Conditions, Mortality, Hospitalization, Risk, Health Status, Health Information Technology (HIT)