All Patient Refined Diagnosis Related Groups Research Articles

Call for Action to target interhospital Variation in Cardiovascular Mortality, Readmissions, and Length-of-Stay: Results of A National Population Analysis.

Excessive interhospital variation threatens healthcare quality. Data on variation in patient outcomes across the whole cardiovascular spectrum are lacking. We aimed to examine interhospital variability for 28 cardiovascular All Patient Refined-Diagnosis-related Groups (APR-DRGs). We studied 103,299 cardiovascular admissions in 99 (98%) Belgian acute-care hospitals between 2012 and 2018. Using generalized linear mixed models, we estimated hospital-specific and APR-DRG-specific risk-standardized rates for in-hospital mortality, 30-day readmissions, and length-of-stay above the APR-DRG-specific 90th percentile. Interhospital variation was assessed based on estimated variance components and time trends between the 2012-2014 and 2016-2018 periods were examined. There was strong evidence of interhospital variation, with statistically significant variation across the 3 outcomes for 5 APR-DRGs after accounting for patient and hospital factors: percutaneous cardiovascular procedures with acute myocardial infarction, heart failure, hypertension, angina pectoris, and arrhythmia. Medical diagnoses, with in particular hypertension, heart failure, angina pectoris, and cardiac arrest, showed strongest variability, with hypertension displaying the largest median odds ratio for mortality (2.51). Overall, hospitals performing at the upper-quartile level should achieve improvements to the median level, and an annual 633 deaths, 322 readmissions, and 1578 extended hospital stays could potentially be avoided. Analysis of interhospital variation highlights important outcome differences that are not explained by known patient or hospital characteristics. Targeting variation is therefore a promising strategy to improve cardiovascular care. Considering their treatment in multidisciplinary teams, policy makers, and managers should prioritize heart failure, hypertension, cardiac arrest, and angina pectoris improvements by targeting guideline implementation outside the cardiology department.

Impact of Medicaid Expansion on Trauma Patients at Extreme Risk of Mortality: A Time-Series Analysis.

The 2014 expansion of Medicaid under the Affordable Care Act (ACA) reshaped healthcare delivery in the United States. This study assessed how Medicaid expansion affected in-hospital mortality in patients with extreme risk of mortality (EROM) from traumatic injuries. Data from inpatients aged 18-64 years, registered in the National Inpatient Sample between 2007 and 2020, and identified with trauma-related All-Patient Refined Diagnosis Related Groups (APRDRG) codes, were analyzed. Within this group, a subset of patients was selected based on the APRDRG classification identifying them as at EROM for the principal unit of analysis. The cohort was divided into high-implementation (HIR) and low-implementation (LIR) regions based on Medicaid expansion coverage. In-hospital mortality was assessed using interrupted time-series analysis. Sensitivity analyses considered seasonality, autocorrelation, and exogenous events. Analysis encompassed 70381 trauma inpatient stays, corresponding to 346659 patients based on National Inpatient Sample weighting. There was a consistent monthly decline in in-hospital mortality of .08% (95% CI: -.103 to -.048; P < .001) prior to Medicaid expansion, a trend unaffected by expansion. This pattern persisted across both LIR and HIR Medicaid implementation regions. Although Medicaid enrollment increased in HIR, that in LIR remained unchanged. Over the study period, the in-hospital mortality among severely injured patients consistently decreased, and this trend was not influenced by Medicaid expansion. The statistical models and results from this study can offer valuable guidance to policymakers and healthcare leaders as they formulate more efficient and effective policies.

Assessment of risk-adjusted mortality ratio (RAMR) in bloodstream infections using all-patient refined diagnosis-related groups (APR-DRGs).

To calculate a risk-adjusted mortality ratio (RAMR) for bloodstream infections (BSIs) using all-patient refined diagnosis-related groups (APR-DRGs) and compare it with the crude mortality rate (CMR). Retrospective observational study of prevalent BSI at our institution from January 2019 to December 2022. In-hospital mortality was adjusted with a binary logistic regression model adjusting for sex, age, admission type and mortality risk for the hospitalization episode according to the four severity levels of APR DRGs. The RAMR was calculated as the ratio of observed to expected in-hospital mortality, and the CMR was calculated as the proportion of deaths among all bacteraemia episodes. Of 2939 BSIs, 2541 were included: Escherichia coli (n = 1310), Klebsiella pneumoniae (n = 428), Pseudomonas aeruginosa (n = 209), Staphylococcus aureus (n = 498) and candidaemia (n = 96). A total of 436 (17.2%) patients died during hospitalization and 279 died within the first 14 days after the onset of BSI. Throughout the period, all BSI cases had a mortality rate above the expected adjusted mortality (RAMR value greater than 1), except for Escherichia coli (1.03; 95% CI 0.86-1.21). The highest overall RAMR values were observed for P. aeruginosa, Candida and S. aureus with 2.06 (95% CI 1.57-2.62), 1.99 (95% CI 1.3-2.81) and 1.8 (95% CI 1.47-2.16), respectively. The temporal evolution of CMR may differ from RAMR, especially in E. coli, where it was reversed. RAMR showed higher than expected mortality for all BSIs studied except E. coli and provides complementary to and more clinically comprehensive information than CMR, the currently recommended antibiotic stewardship programme mortality indicator.

Rates, Outcomes, and Resource Burden of Extracorporeal Membrane Oxygenation Use in Hospitalizations in the United States During the Pandemic.

Extracorporeal membrane oxygenation (ECMO) is a lifesaving medical intervention for patients with severe refractory cardiopulmonary dysfunction. This study aims to characterize hospitalizations and resource use burdens associated with ECMO use during the onset of the pandemic. We performed a retrospective analysis of ECMO use in United States (US) hospitals between 2019 and 2020, utilizing data from the National Inpatient Sample database. Patient demographics, comorbidities, admission characteristics, inpatient mortality, length of hospital stay (LOS), healthcare costs, and ECMO utilization trends were assessed. Of the 17,520 hospitalizations analyzed, the most common reasons for admission were diseases and disorders of the circulatory system (40.5%) and diseases and disorders of the respiratory system (31.2%). The average patient age was 52.5 years, with a male predominance (64.2%). Hospitalizations were predominantly for White Americans (59.5%), followed by Blacks (16.3%) and Hispanics (14.8%). Nearly 88.2% of cases were at an extremely high risk of mortality without intervention. Inpatient mortality was significantly associated with Hispanic descent, a higher Charlson Comorbidity Index (CCI) score, age >60 years, and a higher All Patients Refined Diagnosis Related Groups (APRDRG) risk of mortality. Hospitalizations involving ECMO had a significantly higher inpatient mortality rate compared to non-ECMO hospitalizations (43.1% vs. 2.1%, p<0.0001). The mean LOS was 26 days for ECMO hospitalizations, with ECMO initiation occurring approximately five days from admission. ECMO-related hospitalizations often involve over 10 unique procedures, resulting in an average healthcare cost of US$967,647 per hospitalization, totaling US$16.7 billion. Comparatively, non-ECMO hospitalizations had shorter LOS and lower mean costs (mean LOS, 4.7 days, and US$52,659, respectively). ECMO utilization increased significantly from 2019 to 2020, reflecting rising demand for this life-saving therapy. Compared to non-ECMO hospitalizations, ECMO patients had higher inpatient mortality, associated with Hispanic descent, higher CCI scores, an age >60 years, and a higher APRDRG risk. ECMO hospitalizations had longer stays (26 days) and higher costs (US$967,647 per case, US$16.7 billion total) compared to pre-pandemic levels. ECMO use increased significantly from 2019 to 2020, reflecting rising demand.

Severity of illness and risk of mortality in Mayo Clinic’s virtual hybrid advanced care at home program: a retrospective cohort study

BackgroundIn July 2020, Mayo Clinic launched Advanced Care at Home (ACH), a high-acuity virtual hybrid hospital-at-home model (HaH) of care at Mayo Clinic Florida and Northwest Wisconsin, an urban destination medical center and a rural community practice respectively. This study aims to describe demographic characteristics of ACH patients as well as their acuity of illness using severity of illness (SOI) and risk of mortality (ROM), to illustrate the complexity of patients in the program, taking into account the different diagnostic related groups.MethodsMayo Clinic uses All Patient Refined-Diagnosis Related Groups (APR-DRG) to calculate SOI and ROM on hospitalized patients. APR-DRG data, including SOI and ROM, were gathered from individual chart reviews from July 6, 2020, to March 31, 2022.Results Out of 923 patients discharged from ACH, the average APR-DRG SOI was 2.89 (SD 0.81) and ROM was 2.73. (SD 0.92). Mean age was 70.88 (SD 14.46) years, 54.6% were male patients and the average length of stay was 4.10 days. The most frequent diagnosis was COVID-19 infection with 162 patients (17.6%), followed by heart failure exacerbation (12.7%) and septicemia (10.9%). The 30-day readmission rate after discharge from ACH was 11.2% (n = 103) and the 30-day mortality rate was 1.8% (n = 17). There were no in-program patient deaths.ConclusionsSOI and ROM from patients at the ACH program have been shown to be in the range of “moderate/major” according to the APR-DRG classification. The ACH program is capable of accepting and managing highly complex patients that require advanced therapeutic means. Furthermore, the ACH program has an in-program mortality rate of 0 to date. Therefore, ACH is rising as a capable alternative to the brick-and-mortar hospital.

Implementation of a virtual and in-person hybrid hospital-at-home model in two geographically separate regions utilizing a single command center: a descriptive cohort study

BackgroundAs providers look to scale high-acuity care in the patient home setting, hospital-at-home is becoming more prevalent. The traditional model of hospital-at-home usually relies on care delivery by in-home providers, caring for patients in urban communities through academic medical centers. Our objective is to describe the process and outcomes of Mayo Clinic’s Advanced Care at Home (ACH) program, a hybrid virtual and in-person hospital-at-home model combining a single, virtual provider-staffed command center with a vendor-mediated in-person medical supply chain to simultaneously deliver care to patients living near an urban hospital-at-home command center and patients living in a rural region in a different US state and time zone.MethodsA descriptive, retrospective medical records review of all patients admitted to ACH between July 6, 2020, and December 31, 2021. Patients were admitted to ACH from an urban academic medical center in Florida and a rural community hospital in Wisconsin. We collected patient volumes, age, sex, race, ethnicity, insurance type, primary hospital diagnosis, 30-day mortality rate, in-program mortality, 30-day readmission rate, rate of return to hospital during acute phase, All Patient Refined-Diagnosis Related Groups (APR-DRG) Severity of Illness (SOI), and length of stay (LOS) in both the inpatient-equivalent acute phase and post-acute equivalent restorative phase.ResultsSix hundred and eighty-six patients were admitted to the ACH program, 408 in Florida and 278 in Wisconsin. The most common diagnosis seen were infectious pneumonia (27.0%), septicemia / bacteremia (11.5%), congestive heart failure exacerbation (11.5%), and skin and soft tissue infections (6.3%). Median LOS in the acute phase was 3 days (IQR 2–5) and median stay in the restorative phase was 22 days (IQR 11–26). In-program mortality rate was 0% and 30-day mortality was 0.6%. The mean APR-DRG SOI was 2.9 (SD 0.79) and the 30-day readmission rate was 9.7%.ConclusionsThe ACH hospital-at-home model was able to provide both high-acuity inpatient-level care and post-acute care to patients in their homes through a single command center to patients in urban and rural settings in two different geographical locations with favorable outcomes of low mortality and hospital readmissions.

The need for blood transfusion therapy is associated with increased mortality in children with traumatic brain injury.

Blood transfusion therapy (BTT) is widely used in trauma patients. However, the adverse effects of BTT in pediatric trauma patients with traumatic brain injury (TBI) were poorly studied. The objective of this study is to evaluate the effect of BTT on mortality in children with severe TBI. In this retrospective cohort analysis, we analyzed 2012 and 2016 Kids' Inpatient Databases and used a weighted sample to obtain national outcome estimates. We included children aged 1 month to 21 years with TBI who were mechanically ventilated, considered severe TBI; we then compared the demographics, comorbidities, and mortality rates of those patients who had undergone BTT to those who did not. Statistical analysis was performed using the chi-squared test and regression models. In addition, in a correlative propensity score matched analysis, cases (BTT) were matched 1:1 with controls (non-BTT) based on age, gender, hospital region, income quartiles, race, and All Patients Refined Diagnosis Related Groups (APRDRG) severity of illness scores to minimize the effect of confounding variables between the groups. Out of 87,980 children with a diagnosis of TBI, 17,199 (19.5%) with severe TBI were included in the analysis. BTT was documented in 3184 (18.5%) children. Among BTT group, the mortality was higher compared to non-BTT group [31.6% (29.7-33.5%) vs. 14.4 (13.7-15.1%), (OR 2.2, 95% CI 1.9-2.6; p<0.05)]. In the BTT group, infants and adolescents, white race, APRDRG severity of illness, cardiac arrest, platelet, and coagulation factor transfusions were associated with higher mortality. In a propensity-matched analysis, BTT associated with a higher risk of mortality (32.1% [30.1-34.2] vs. 17.4% [15.8-19.1], p<0.05; OR: 2.2, 95% CI: 1.9-2.6). In children with severe TBI, blood transfusion therapy is associated with higher mortality.

Deep neural networks and association with inpatient survival for patients admitted to the hospital with colon cancer undergoing open colectomy.

e15537 Background: During hospitalization for colectomy patients with colon cancer may be at risk for mortality due to several reasons including underlying cancer, other comorbidities or age. Our aim was to develop a machine learning algorithm to predict end of admission mortality in patients undergoing colectomy for their cancer. We hypothesized that machine learning could be applied to patients undergoing open colectomy as part of their colon cancer treatment. Methods: All adult patients (&gt; 18 years) for the National in-patient Services (NIS) database 2014 was used to develop our algorithm. We extracted all patients with a diagnosis of cancer using the ICD-9 codes and all patients that underwent colectomy. We conducted a multivariate analysis to look at the risk factors that dictate mortality in these patients. We also developed a linear regression model and a deep learning algorithm to predict mortality in these patients. Results: We identified a total of 4120 patients that underwent open colectomy with colon cancer in the NIS 2014. We observed that several clinical and lab-based parameters were statistically significant for multivariate analyses while others were not. With most significant being all patients refined diagnosis related groups (APRDRG) risk mortality (HR = 6.20, 95%CI = 4.10-9.36), APRDRG severity (HR = 4.78, 95%CI = 3.27-7.00), chronic anemia (HR = 0.61, 95%CI = 0.40-0.94), coagulation disorders (HR = 2.32, 95%CI = 1.31-4.10), chronic electrolytes disorders (HR = 2.12, 95%CI = 1.39-3.24), neurological disorders (HR = 1.92, 95%CI = 1.11-3.32), underweight (low BMI) (HR = 2.40, 95%CI = 1.05-5.48), Hyperkalemia (HR = 2.40, 95%CI = 1.28-4.50), Acidosis (HR = 4.04, 95%CI = 2.64-6.19). In the machine learning analysis, we found out that our proposed DNN outperformed the RF with test set accuracy of 91.1%, sensitivity of 88.5%, specificity 91.2%, PPV of 24.7, NPV of 99.5% and AUROC of 0.968 [95%CI = 0.08-.014]. Conclusions: Our novel DNN model outperformed RF classifier models. The model is easy to implement, user friendly and with good accuracy. However, further external validation of the model is required.

Variability in HSV Testing and Empiric Treatment in Febrile Infants

Source: Treasure JD, Shah SS, Hall M, et al for the Pediatric Research in Inpatient Settings Network and the Collaborative Antiviral Study Group. Variation in diagnostic testing and empiric acyclovir use for HSV infection in febrile infants. Hospital Pediatrics. 2021;11(9):922–930; doi.10.1542/hpeds.2020-003129Investigators from multiple institutions conducted a retrospective study to describe testing for herpes simplex virus (HSV) in febrile infants <60 days old, assess variation in testing and treatment across hospitals, and evaluate the effect of HSV testing on length of hospital stay (LOS) in these patients. For the study, data in the Pediatric Health Information System (PHIS) database were reviewed. PHIS includes administrative data such as demographics, diagnostic and procedure codes, and laboratory and pharmacy orders from encounters at pediatric hospitals. For the current study, data from 44 hospitals in 26 states and the District of Columbia were reviewed. Study participants were children ≤60 days old evaluated in the ED with an ICD-9 or ICD-10 code indicative of fever. Data abstracted on these children included use of HSV testing (culture or PCR), imaging and other diagnostic evaluations, hospital, demographics, orders for acyclovir, LOS, ICD-9 or ICD-10 codes for HSV infection, and severity of illness, as estimated in All Patient Refined-Diagnosis Related Groups (APR-DRG). The primary study outcome was rate of HSV testing, measured at the patient and hospital level. The hospital-level rates of acyclovir orders were also assessed. Secondary outcomes included rate of HSV infection in study patients. LOS was compared in study patients tested for HSV and those not tested using regression analyses and accounting for confounding variables such as age, hospital and APR-DRG estimated illness severity. Analyses were stratified by age (<22 days and 22–60 days).Data were analyzed on 24,534 ED encounters, including 6,027 (24.6%) patients <22 days old and 18,508 (75.4%) 22 to 60 days old. There were 108 children (0.44%) with a diagnostic code indicative of HSV infection, yielding rates of HSV disease of 1.08% for those <22 days old, and 0.23% for those 22 to 60 days of age. Rates of HSV testing were 39.4% and 12.0%, respectively, for children <22 and 22 to 60 days old. At the hospital level, the rate of HSV testing was 35.6% (interquartile range [IQR], 28% to 53%) for the younger age cohort, and 12% (IQR, 9% to 16%) for those 22 to 60 days old. There also was substantial variation in hospital-level rates of empiric acyclovir use (IQR, 68% to 90% for children <22 days old and 44% to 73% for those 22 to 60 days of age). The prevalence of additional testing also varied by age group and hospital. After adjusting for age, severity of illness and hospital, LOS was significantly longer in patients with HSV testing than in those not tested (mean LOS, 2.6 and 1.9 days, respectively; P <0.001).The authors conclude that substantial variation in diagnostic use of HSV testing in febrile infants ≤60 days old.Dr Winer has disclosed no financial relationship relevant to this commentary. This commentary does not contain a discussion of an unapproved/investigative use of a commercial product/device.The diagnosis and care of potential meningitis/encephalitis in young infants with fever has continually evolved over time (See AAP Grand Rounds. 2010;24[2]:17). As hospitals have moved away from HSV culture and toward HSV PCR testing and the delay in obtaining results has shortened, the safety and cost-effectiveness calculations leading to optimal strategy continue to change.1Although the current investigators were limited in their ability to evaluate duration of empiric acyclovir in children for whom HSV testing is negative, this likely has shortened over time. The LOS was longer for patients who had HSV testing performed, likely related to clinical concern by the physicians that led to the decision to test in the first place.HSV testing continues to evolve, with many hospitals starting to use multiplex PCR array panels which test for multiple viral (including HSV), bacterial, and even fungal pathogens.2 Some evidence exists that initial CSF results are not sensitive enough to preclude a meningitis/encephalitis panel,3 but concerns also exist about overdiagnosis and overtreatment with universal use of these panels.Significant variability exists in the testing and empiric acyclovir usage in febrile infants. Patients tested for HSV have longer LOS than those for whom no test is performed.Fever in young infants is relatively common; neonatal HSV infection, relatively rare. Unfortunately, the results of the current study underscore the need for guidance to allow informed HSV diagnostic and therapeutic decisions. (See AAP Grand Rounds. 2018;39(5):56.)4

Unwarranted Between-hospital Variation in Mortality, Readmission, and Length of Stay of Urological Admissions: An Important Trigger for Prioritising Quality Targets

BackgroundUnwarranted between-hospital variation is a persistent health care quality issue. It is unknown whether urology patients are prone to this variation. ObjectiveTo examine between-hospital variation in mortality, readmission, and length of stay for all 22 urological All Patient Refined Diagnosis Related Groups (APR-DRGs). Design, setting, and participantsThis study included administrative data from 320640 urological admissions in 99 (98%) Belgian acute-care hospitals between 2016 and 2018. Outcome measurements and statistical analysisWe used hierarchical mixed-effect logistic regression models to estimate hospital-specific and APR-DRG–specific risk-standardised rates for in-hospital mortality, 30-d readmission, and length of stay above the APR-DRG–specific 90th percentile. Between-hospital variation was assessed based on the estimated variance components. Associations of outcomes with patient and hospital characteristics and time trends were examined. Results and limitationsOur analysis revealed important between-hospital variation in mortality, readmission, and length of stay for urological pathologies, particularly for medical diagnoses. Significant variation was shown in all three outcomes for kidney and urinary tract infections; other kidney and urinary tract diagnoses, signs, and symptoms; urinary stones and acquired upper urinary tract obstruction; and kidney and urinary tract procedures for nonmalignancy. Lowering of mortality rates in upper-quartile hospitals to the median could potentially save 41.5% of deaths in these hospitals, with the largest absolute gain for kidney and urinary tract infections and kidney and urinary tract malignancy. Limitations included a likely underestimation of readmission rates. ConclusionsUrological patient outcomes are characterised by unwarranted between-hospital variation. We recommend improvement initiatives to prioritise kidney and urinary tract infections because of significant variation across the three outcomes and the largest potential gain in lives saved. Patient summaryWe found notable between-hospital variation in mortality, readmission, and length of stay for urological hospital admissions in Belgium. As much as 41.5% of deaths could potentially be avoided if underperforming hospitals improved. Targeting kidney and urinary tract infections could help reduce variation.

Demographics and Risk Factors of Pediatric Pulmonary Hypertension Readmissions

Background and Objectives: Pulmonary hypertension (PH) leads to significant morbidity and mortality in pediatric patients and increases the readmission rates for hospitalizations. This study evaluates the risk factors and comorbidities associated with an increase in 30-day readmissions among pediatric PH patients.Methods: National Readmission Database (NRD) 2017 was searched for patients less than 18 years of age who were diagnosed with PH based on the International Classification of Diseases, 10th Revision (ICD-10). Statistical Package for the Social Sciences (SPSS) software v25.0 (IBM Corp., Armonk, NY) was used for statistical analysis.Results: Of 5.52 million pediatric encounters, 10,501 patients met the selection criteria. The 30-day readmission rate of 14.43% (p < 0.001) was higher than hospitalizations from other causes {Odds Ratio (OR) 4.02 (3.84-4.20), p < 0.001}. The comorbidities of sepsis {OR 0.75 (0.64-0.89), p < 0.02} and respiratory infections {OR 0.75 (0.67-0.85), p < 0.001} were observed to be associated with lower 30-day readmissions. Patients who required invasive mechanical ventilation via endotracheal tube {OR 1.66 (1.4-1.96), p < 0.001} or tracheostomy tube {OR 1.35 (1.15-1.6), p < 0.001} had increased unplanned readmissions. Patients with higher severity of illness based on All Patients Refined Diagnosis Related Groups (APR-DRG) were more likely to get readmitted {OR 7.66 (3.13-18.76), p < 0.001}.Conclusion: PH was associated with increased readmission rates compared to the other pediatric diagnoses, but the readmission rate in this study was lower than one previous pediatric study. Invasive mechanical ventilation, Medicaid insurance, higher severity of illness, and female gender were associated with a higher likelihood of readmission within 30 days.

Association of the All-Patient Refined Diagnosis-Related Groups Severity of Illness and Risk of Mortality Classification with Outcomes.

Diagnosis-related groups (DRGs) is a patient classification system used to characterize the types of patients that the hospital manages and to compare the resources needed during hospitalization. The DRG classification is based on International Classification of Diseases diagnoses, procedures, demographics, discharge status, and complications or comorbidities and compares hospital resources and outcomes used to determine how much Medicare pays the hospital for each "product/medical condition." The All-Patient Refined DRG (APR-DRG) incorporated severity of illness (SOI) and risk of mortality (ROM) into the DRG system to adjust for patient complexity to compare resource utilization, complication rates, and lengths of stay. This study included 18,478 adult patients admitted to a tertiary care center in Lubbock, Texas during a 1-year period. We recorded the APR-DRG SOI and ROM and some clinical information on these patients, including age, sex, admission shock index, admission glucose and lactate levels, diagnoses based on International Classification of Diseases, Tenth Revision discharge coding, length of stay, and mortality. We compared the levels of SOI and ROM across this clinical information. As the levels of SOI and ROM increase (which indicates increased disease severity and risk of mortality), age, glucose levels, lactate levels, shock index, length of stay, and mortality increased significantly (P < 0.001). Multiple logistic regression analysis demonstrated that each unit increase in ROM and SOI level was significantly associated with an 11.45 and a 10.37 times increase in the odds of in-hospital mortality, respectively. The C-statistics for the corresponding models are 0.947 and 0.929, respectively. When both ROM and SOI were included in the model, the magnitudes of increase in odds of in-hospital mortality were 5.61 and 1.17 times for ROM and SOI, respectively. The C-statistic is 0.949. This study indicates that the APR-DRG SOI and ROM scores provide a classification system that is associated with mortality and correlates with other clinical variables, such as the shock index and lactate levels, which are available on admission.

Inpatient Sinus Surgery Patient Morbidity and Outcomes: A National Analysis.

To investigate the morbidity and mortality of patients undergoing endoscopic sinus surgery (ESS) in the inpatient setting. Retrospective database review. The Nationwide Inpatient Sample was queried for all ESS between 2008 and 2014. Using All Patients Refined Diagnosis Related Groups (APR-DRG) codes, cases with APR-DRG codes under Major Diagnostic Category 3 (Diseases and Disorders of the Ear, Nose, Mouth, and Throat) were designated as patients with primary otolaryngology diagnoses undergoing ESS (ORL), and all other codes were designated as patients with non-otolaryngology pathologies as their primary reason for admission but undergoing ESS (non-ORL). A univariate analysis and a logistic regression were used to compare patient demographics, comorbidities, disease severity, and mortality. There were 8,305 ORL patients and 6,342 non-ORL patients. ORL patients were more likely to be elective admissions (61.3% vs. 48.5%, P< .001), have a deviated nasal septum (17.9% vs. 12.3%, P< .001), nasal polyps (15.8% vs. 5.0%, P< .001), obstructive sleep apnea (10.7% vs. 5.2%, P< .001), and pulmonary disease (15.9% vs. 10.5%, P< .001). Non-ORL patients had a higher likelihood of in-hospital mortality (odds ratio [OR] 6.22, 95% confidence interval [CI] 3.29-11.78, P < .001), length of stay in the highest quartile (OR 2.43, 95% CI 2.16-2.74, P < .001), and a higher proportion had APR-DRG subclasses indicating extreme severity of illness (19.3% vs. 4.3%, P < .001) or extreme risk of mortality (12.5% vs. 2.0%, P < .001). Patients undergoing ESS in the inpatient setting have a higher than expected mortality rate which can be associated with a non-otolaryngology pathology as the primary reason for their admission. 4 Laryngoscope, 132:1523-1529, 2022.

Thirty-Day Hospital Readmissions for Acute Gout in the United States: Analysis of the Nationwide Readmission Database.

The aims of this study were to describe the rates and characteristics of nonelective 30-day readmission among adult patients hospitalized for acute gout and to assess predictors of readmission. We analyzed the 2017 Nationwide Readmission Database. Gout hospitalizations were identified using the International Classification of Diseases, Tenth Revision, Clinical Modification code. Hospitalizations for adult patients were included. We excluded planned or elective readmissions. We utilized χ2 tests to compare baseline characteristics between readmissions and index hospitalizations. We used multivariate Cox regression to identify independent predictors of readmissions. A total of 11,727 index adult hospitalizations with acute gout listed as the principal diagnosis were discharged alive and included. One thousand five hundred ninety-four (13.6%) readmissions occurred within 30 days. Acute gout was the most common reason for readmission. Readmissions had higher inpatient mortality (2.4% vs 0.1%, p < 0.0001), greater mean age (68.1 vs 67.0 years, p = 0.021), and longer hospital length of stay (5.9 vs 3.8 days, p < 0.0001) compared with index hospitalizations. Charlson Comorbidity Index scores of ≥2 (score 2: adjusted hazards ratio [AHR], 1.67; p = 0.001; score ≥3: AHR, 2.08; p < 0.0001), APR-DRG (All Patients Refined Diagnosis Related Groups) severity levels ≥2 (level 2: AHR, 1.43; p = 0.044; level 3: AHR, 1.83; p = 0.002; level 4: AHR, 2.38; p = 0.002), admission to metropolitan hospital (AHR, 1.83; p = 0.012), atrial fibrillation (AHR, 1.31; p = 0.004), and anemia (AHR, 1.30; p = 0.001) were significantly associated with 30-day readmissions. Acute gout readmissions were associated with worse outcomes compared with index hospitalizations. Charlson Comorbidity Index scores ≥2, APR-DRG severity levels ≥2, admission to metropolitan hospital, atrial fibrillation, and anemia were significant predictors of readmission.

Inpatient Use and Outcomes at Children's Hospitals During the Early COVID-19 Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has led to changes in health care use, including decreased emergency department visits for children. In this study, we sought to describe the impact of the COVID-19 pandemic on inpatient use within children's hospitals. We performed a retrospective study using the Pediatric Health Information System. We compared inpatient use and clinical outcomes for children 0 to 18 years of age during the COVID-19 period (March 15 to August 29, 2020) to the same time frame in the previous 3 years (pre-COVID-19 period). Adjusted generalized linear mixed models were used to examine the association of the pandemic period with inpatient use. We assessed trends overall and for a subgroup of 15 medical All Patient Refined Diagnosis Related Groups (APR-DRGs). We identified 424 856 hospitalizations (mean: 141 619 hospitalizations per year) in the pre-COVID-19 period and 91 532 in the COVID-19 period. Compared with the median number of hospitalizations in the pre-COVID-19 period, we observed declines in hospitalizations overall (35.1%), and by APR-DRG (range: 8.5%-81.3%) with asthma (81.3%), bronchiolitis (80.1%), and pneumonia (71.4%) experiencing the greatest declines. Overall readmission rates were lower during the COVID-19 period; however, other outcomes, including length of stay, cost, ICU use, and mortality remained similar to the pre-COVID-19 period with some variability by APR-DRGs. US children's hospitals observed substantial reductions in inpatient admissions with largely unchanged hospital-level outcomes during the COVID-19 pandemic. Although the impact on use varied by condition, the most notable declines were related to inpatient admissions for respiratory conditions, including asthma, bronchiolitis, and pneumonia.

Abstract P249: Rates of Adverse Events and Outcomes Among Ischemic Stroke Patients Admitted to Thrombectomy Capable Stroke Centers

Background: To identify the beneficial effects of thrombectomy capable hospitals (TCHs), we compared the rates of in-hospital adverse events and discharge outcomes among ischemic stroke patients admitted to thrombectomy capable and non-thrombectomy capable hospitals in the United States. Methods: We obtained the data from the Nationwide Inpatient Sample from 2012 and 2017. Thrombectomy capable hospitals were identified based on number of thrombectomy procedures performed by hospital per year among ischemic stroke patients. If an hospital performed ten or more thrombectomy procedures, it was labelled as thrombecotomy capable hospital. The analysis was limited to patients (age ≥18 years) discharged with a principal diagnosis of ischemic stroke (International Classification of Disease 433.x1-434.x1 (ICD-9) or I63 (ICD-10). The impact of TCHs admissions on in-hospital outcomes was assessed in a comparative analysis of propensity-matched groups of patients. Results: We identified a total of 2,826,335 patients with primary ischemic stroke patients. After adjusting for age, gender, race or ethnicity, comorbidities, All Patients Refined Diagnosis Related Groups (APR-DRG)-based disease severity, and hospital teaching status, patients admitted to TCHs were at lower risk of in-hospital adverse events complications: pneumonia (odds ratio [OR], 0.86; 95% confidence interval [CI], 0.80-0.93), urinary tract infection (OR, 0.87; 95% CI, 0.84-0.91)and sepsis (OR, 0.92; 95% CI, 0.84-1.00). Patients admitted to TCH were more likely to receive thrombolysis (OR, 1.29; 95% CI, 1.30-1.36). The mean cost of hospitalization of the patients was significantly higher in patients admitted at TCHs compared with those admitted at non-thrombectomy capable $74765 vs $60530, P &lt; .0001). The patients admitted to TCHs had lower inpatient mortality (OR, 0.82; 95% CI, 0.78-.88) and were more likely to be discharged with none to minimal disability (OR, 1.09; 95% CI, 1.06-1.12). Conclusions: Compared with non-thrombectomy capable admissions, patients admitted to TCHs are less likely to experience hospital adverse events and more likely to experience better discharge outcomes.

1348. Indirect Standardization to Improve Comparison of Children’s Hospitals’ Antimicrobial Use

BackgroundAntimicrobial use (AU) measured by days of therapy per 1000 patient-days (DOT/1000pd), the most established metric, varies widely between children’s hospitals despite robust adoption of antimicrobial stewardship. Differences in diagnoses and procedures (case mix) between hospitals are a source of AU variation not included in adjustment methods such as the Standardized Antimicrobial Administration Ratio. In this study, we evaluated an indirect standardization method to adjust children’s hospital AU for case mix.MethodsThis multicenter retrospective cohort study included 51 children’s hospitals participating in the Pediatric Health Information System database from 2016-2018. All inpatient, observation, and neonatal admissions were included, with a total of 2,558,948 discharges. Hospitalizations were grouped into 83 strata defined based on All Patients Refined Diagnosis Related Groups (APR-DRGs). Observed to expected (O:E) ratios were calculated by indirect standardization of mean antibiotic DOT per case, with expected values from 2016-2018 and observed values from 2018, and compared to DOT/1000pd. Outlier hospitals were defined by O:E z-scores corresponding to below 10th percentile (low outlier) and above 90th percentile (high outlier).ResultsAntibacterial DOT/1000pd ranged from 345 to 776 (2.2-fold variation from lowest to highest), whereas O:E ratios ranged from 0.8 to 1.14 (1.4-fold variation from lowest to highest) (Figure 1). O:E ratios were moderately correlated with DOT/1000pd (correlation estimate 0.45; 95% CI 0.19-0.64; p=0.0008). Three high outlier hospitals and 6 low outlier hospitals were identified. Examining hospitals with comparably high DOT/1000pd but discordant O:E ratios, differences could be explained by variation in both case mix and condition-specific AU within strata defined by APR-DRGs.Figure 1. Individual hospitals labeled on the X-axis, ordered by level of antibacterial DOT/1000pd (left axis), represented by bars. Diamonds represent O:E ratios derived by indirect standardization (right axis). Outlier hospitals (low and high) are highlighted in yellow. Dashed horizontal lines represent 10th percentile (lower) and 90th percentile (upper) limits of the O:E ratio distribution. ConclusionThe observed variation in DOT/1000pd between hospitals is reduced when indirect standardization is applied to account for case mix differences. This approach can be adapted for more specific uses including clinical conditions, patient populations, or antimicrobial agents. Indirect standardization may enhance stewardship efforts by providing adjusted comparisons that incorporate case mix differences between hospitals.Disclosures All Authors: No reported disclosures

Disparities Associated with Sepsis Mortality in Critically Ill Children.

Disparities in health care related to socioeconomic status and race/ethnicity are well documented in adult and neonatal sepsis, but they are less characterized in the critically ill pediatric population. This study investigated whether socioeconomic status and/or race/ethnicity is associated with mortality among children treated for sepsis in the pediatric intensive care unit (PICU). A retrospective cohort study was conducted using information from 48 children's hospitals included in the Pediatric Health Information System database. We included visits by children ≤ 21 years with All Patients Refined Diagnosis-Related Groups (APR-DRG) diagnosis codes of septicemia and disseminated infections that resulted in PICU admission from 2010 to 2016. Multivariable logistic regression was used to measure the effect of race/ethnicity and socioeconomic status (insurance status and median household income for zip code) on mortality after adjustment for age, gender, illness severity, and presence of complex chronic condition. Among the 14,276 patients with sepsis, the mortality rate was 6.8%. In multivariable analysis, socioeconomic status, but not race/ethnicity, was associated with mortality. In comparison to privately insured children, nonprivately insured children had increased odds of mortality (public: adjusted odds ratio [aOR]: 1.2 [1.0, 1.5]; uninsured: aOR: 2.1 [1.2, 3.7]). Similarly, children living in zip codes with the lowest quartile of annual household income had higher odds of mortality than those in the highest quartile (aOR: 1.5 [1.0, 2.2]). These data suggest the presence of socioeconomic, but not racial/ethnic, disparities in mortality among children treated for sepsis. Further research is warranted to understand why such differences exist and how they may be addressed.

Associations Between Obesity and Use for Pediatric Hospitalizations.

Obesity is associated with poor outcomes for specific clinical groups of hospitalized children, but few data exist on outcomes of children with obesity on a larger scale during hospitalization. Therefore, we aimed to determine if use outcomes differ between hospitalized children with obesity and hospitalized children without obesity. We performed a retrospective longitudinal cohort study of all children aged 2 to 19 years hospitalized at a single academic institution between January 1, 2009, and December 31, 2016. BMI was calculated from documented height and weight; obesity was defined by using age- and sex-specific BMI percentile guidelines from the Centers for Disease Control and Prevention. Only All Patient Refined Diagnosis-Related Groups (APR-DRGs) with >100 admissions during the study period were included. Primary outcome measures included hospital length of stay, hospital cost, and 14-day readmission. Generalized linear and logistic models were used to determine adjusted differences for outcome measures between patients with and without obesity. Of 78 756 included hospitalizations, obesity rates increased from 16.5% in 2009-2010 to 17.3% in 2015-2016 (P = .002). Only 6 (4.7%) of the 128 APR-DRGs examined were associated with increased use for patients with obesity: spinal procedures, tonsil and adenoid procedures, major respiratory procedures, peptic ulcer and gastritis, other musculoskeletal diagnoses, and other kidney and urinary tract diagnoses. There were no APR-DRGs with increased length of stay for children with obesity. Obesity is associated with increased hospitalization cost and readmission rates for a minority of diagnosis groups. Some groups of hospitalized children with obesity may benefit from targeted interventions to reduce obesity-specific risks. Future research should be focused on disparities in other relevant clinical outcomes.

Author response: Readmission to a different hospital following acute stroke is associated with worse outcomes.

We would like to thank Chen et al.1 for their interest in our study. We agree that it is important to consider stroke severity and the possibility that quality of care was suboptimal during the index admission. Indeed, we specifically designed our analyses to minimize the likelihood that readmissions were related to higher stroke severity or to unsatisfactory treatment at the first hospital. Although the Nationwide Readmissions Database does not include data on stroke severity, we used the All Patient Refined Diagnosis Related Groups (APRDRG) severity of illness and risk of mortality measures as a measure of overall illness severity. Our fully adjusted models account for both APRDRG severity and mortality. To minimize the likelihood that unsatisfactory treatment at the first hospital contributed to readmission, we excluded patients transferred to a higher level of care during index hospitalization. Finally, Table 2 reports the length of hospital stay and total charges of hospitalization during the index admission. In addition to demographics, vascular risk factors, insurance, discharge disposition, and APRDRG severity or mortality, our fully adjusted model also included adjustment for hospital characteristics, length of stay, and total charges during the index hospitalization.