Identification of patients at a high risk of potentially avoidable readmission allows hospitals to efficiently direct additional care transitions services to the patients most likely to benefit.
To ...externally validate the HOSPITAL score in an international multicenter study to assess its generalizability.
International retrospective cohort study of 117 065 adult patients consecutively discharged alive from the medical department of 9 large hospitals across 4 different countries between January 2011 and December 2011. Patients transferred to another acute care facility were excluded.
The HOSPITAL score includes the following predictors at discharge: hemoglobin, discharge from an oncology service, sodium level, procedure during the index admission, index type of admission (urgent), number of admissions during the last 12 months, and length of stay.
30-day potentially avoidable readmission to the index hospital using the SQLape algorithm.
Overall, 117 065 adults consecutively discharged alive from a medical department between January 2011 and December 2011 were studied. Of all medical discharges, 16 992 of 117 065 (14.5%) were followed by a 30-day readmission, and 11 307 (9.7%) were followed by a 30-day potentially avoidable readmission. The discriminatory power of the HOSPITAL score to predict potentially avoidable readmission was good, with a C statistic of 0.72 (95% CI, 0.72-0.72). As in the derivation study, patients were classified into 3 risk categories: low (n = 73 031 62.4%), intermediate (n = 27 612 23.6%), and high risk (n = 16 422 14.0%). The estimated proportions of potentially avoidable readmission for each risk category matched the observed proportion, resulting in an excellent calibration (Pearson χ2 test P = .89).
The HOSPITAL score identified patients at high risk of 30-day potentially avoidable readmission with moderately high discrimination and excellent calibration when applied to a large international multicenter cohort of medical patients. This score has the potential to easily identify patients in need of more intensive transitional care interventions to prevent avoidable hospital readmissions.
1) To identify predictors of one-year mortality in hospitalized medical patients using factors available during their hospital stay. 2) To evaluate whether healthcare system use within 30 days of ...hospital discharge is associated with one-year mortality.
This prospective, observational study included adult patients from four mid-sized hospital general internal medicine units. During index hospitalization, we retrieved patient characteristics, including demographic and socioeconomic indicators, diagnoses, and early simplified HOSPITAL scores from electronic health records and patient interviews. Data on healthcare system use was collected using telephone interviews 30 days after discharge. Survival status at one year was collected by telephone and from health records. We used a univariable analysis including variables available from the hospitalization and 30-day post-discharge periods. We then performed multivariable analyses with one model using index hospitalization data and one using 30-day post-discharge data.
Of 934 patients, 123 (13.2%; 95% CI 11.0-15.4%) were readmitted or died within 30 days. Of 814 patients whose primary outcome was available, 108 died (13.3%) within one year. Using factors obtained during hospitalization, the early simplified HOSPITAL score (OR 1.50; 95% CI 1.31-1.71; P < 0.001) and not living at home (OR 4.0; 95% CI 1.8-8.3; P < 0.001) were predictors of one-year mortality. Using 30-day post-discharge predictors, hospital readmission was significantly associated with one-year mortality (OR 4.81; 95% CI 2.77-8.33; P < 0.001).
Factors predicting one-year mortality were a high early simplified HOSPITAL score, not living at home, and a 30-day unplanned readmission.
Abstract Objective The study objective was to compare the 30-day readmission rate and mortality between patients with heart failure who have persistent hyponatremia during hospitalization and ...patients who have their admission hyponatremia corrected before discharge. Methods This large retrospective cohort study included all adult patients admitted with a diagnosis of congestive heart failure to a tertiary-care hospital between July 2003 and October 2009. We compared the readmission rate and mortality 30 days after discharge between patients with persistent hyponatremia (ie, low sodium level at both admission and discharge) and patients with hyponatremia correction during hospitalization. Results Among the 4295 eligible patients with hyponatremia at admission, 1799 (41.9%) did not have their sodium level corrected at discharge. Overall, 1269 patients (29.5%) had a 30-day unplanned readmission or died. In a multivariable logistic regression analysis, the absence of hyponatremia correction was associated with a 45% increase in the odds of having a 30-day unplanned readmission or death (odds ratio, 1.45; 95% confidence interval, 1.27-1.67). Among patients with persistent hyponatremia, those with more severe hyponatremia at discharge (<130 mm/L) had a higher odds (odds ratio, 1.68; 95% confidence interval, 1.32-2.14) of having a 30-day readmission or death than those with less severe hyponatremia at discharge (130-134 mm/L). Conclusions The absence of correction of hyponatremia over the course of hospitalization was frequent and independently associated with an increase of approximately 50% in the odds of having a 30-day unplanned readmission or death. This association appeared to be independent of heart failure severity.
Background
The simplified HOSPITAL score is an easy-to-use prediction model to identify patients at high risk of 30-day readmission before hospital discharge. An earlier stratification of this risk ...would allow more preparation time for transitional care interventions.
Objective
To assess whether the simplified HOSPITAL score would perform similarly by using hemoglobin and sodium level at the time of admission instead of discharge.
Design
Prospective national multicentric cohort study.
Participants
In total, 934 consecutively discharged medical inpatients from internal general services.
Main Measures
We measured the composite of the first unplanned readmission or death within 30 days after discharge of index admission and compared the performance of the simplified score with lab at discharge (simplified HOSPITAL score) and lab at admission (early HOSPITAL score) according to their discriminatory power (Area Under the Receiver Operating characteristic Curve (AUROC)) and the Net Reclassification Improvement (NRI).
Key Results
During the study period, a total of 3239 patients were screened and 934 included. In total, 122 (13.2%) of them had a 30-day unplanned readmission or death. The simplified and the early versions of the HOSPITAL score both showed very good accuracy (Brier score 0.11, 95%CI 0.10–0.13). Their AUROC were 0.66 (95%CI 0.60–0.71), and 0.66 (95%CI 0.61–0.71), respectively, without a statistical difference (
p
value 0.79). Compared with the model at discharge, the model with lab at admission showed improvement in classification based on the continuous NRI (0.28; 95%CI 0.08 to 0.48;
p
value 0.004).
Conclusion
The early HOSPITAL score performs, at least similarly, in identifying patients at high risk for 30-day unplanned readmission and allows a readmission risk stratification early during the hospital stay. Therefore, this new version offers a timely preparation of transition care interventions to the patients who may benefit the most.
Objectives To evaluate the impact of preoperative sepsis on risk of postoperative arterial and venous thromboses. Design Prospective cohort study using the National Surgical Quality Improvement ...Program database of the American College of Surgeons (ACS-NSQIP). Setting Inpatient and outpatient procedures in 374 hospitals of all types across the United States, 2005-12. Participants 2 305 380 adults who underwent surgical procedures. Main outcome measures Arterial thrombosis (myocardial infarction or stroke) and venous thrombosis (deep venous thrombosis or pulmonary embolism) in the 30 days after surgery. Results Among all surgical procedures, patients with preoperative systemic inflammatory response syndrome or any sepsis had three times the odds of having an arterial or venous postoperative thrombosis (odds ratio 3.1, 95% confidence interval 3.0 to 3.1). The adjusted odds ratios were 2.7 (2.5 to 2.8) for arterial thrombosis and 3.3 (3.2 to 3.4) for venous thrombosis. The adjusted odds ratios for thrombosis were 2.5 (2.4 to 2.6) in patients with systemic inflammatory response syndrome, 3.3 (3.1 to 3.4) in patients with sepsis, and 5.7 (5.4 to 6.1) in patients with severe sepsis, compared with patients without any systemic inflammation. In patients with preoperative sepsis, both emergency and elective surgical procedures had a twofold increased odds of thrombosis. Conclusions Preoperative sepsis represents an important independent risk factor for both arterial and venous thromboses. The risk of thrombosis increases with the severity of the inflammatory response and is higher in both emergent and elective surgical procedures. Suspicion of thrombosis should be higher in patients with sepsis who undergo surgery.
ObjectiveWe aimed to develop and validate a score to assess inpatient complexity and compare its performance with two currently used but not validated tools to estimate complexity (ie, Charlson ...Comorbidity Index (CCI), patient clinical complexity level (PCCL)).MethodsConsecutive patients discharged from the department of medicine of a tertiary care hospital were prospectively included into a derivation cohort from 1 October 2016 to 16 February 2017 (n=1407), and a temporal validation cohort from 17 February 2017 to 31 March 2017 (n=482). The physician in charge assessed complexity. Potential predictors comprised 52 parameters from the electronic health record such as health factors and hospital care usage. We fit a logistic regression model with backward selection to develop a prediction model and derive a score. We assessed and compared performance of model and score in internal and external validation using measures of discrimination and calibration.ResultsOverall, 447 of 1407 patients (32%) in the derivation cohort, and 116 of 482 patients (24%) in the validation cohort were identified as complex. Eleven variables independently associated with complexity were included in the score. Using a cut-off of ≥24 score points to define high-risk patients, specificity was 81% and sensitivity 57% in the validation cohort. The score’s area under the receiver operating characteristic (AUROC) curve was 0.78 in both the derivation and validation cohort. In comparison, the CCI had an AUROC between 0.58 and 0.61, and the PCCL between 0.64 and 0.69, respectively.ConclusionsWe derived and internally and externally validated a score that reflects patient complexity in the hospital setting, performed better than other tools and could help monitoring complex patients.
The HOSPITAL score has been widely validated and accurately identifies high-risk patients who may mostly benefit from transition care interventions. Although this score is easy to use, it has the ...potential to be simplified without impacting its performance. We aimed to validate a simplified version of the HOSPITAL score for predicting patients likely to be readmitted.
Retrospective study in 9 large hospitals across 4 countries, from January through December 2011.
We included all consecutively discharged medical patients. We excluded patients who died before discharge or were transferred to another acute care facility.
The primary outcome was any 30-day potentially avoidable readmission. We simplified the score as follows: (1) 'discharge from an oncology division' was replaced by 'cancer diagnosis or discharge from an oncology division'; (2) 'any procedure' was left out; (3) patients were categorised into two risk groups (unlikely and likely to be readmitted). The performance of the simplified HOSPITAL score was evaluated according to its overall accuracy, its discriminatory power and its calibration.
Thirty-day potentially avoidable readmission rate was 9.7% (n=11 307/117 065 patients discharged). Median of the simplified HOSPITAL score was 3 points (IQR 2-5). Overall accuracy was very good with a Brier score of 0.08 and discriminatory power remained good with a C-statistic of 0.69 (95% CI 0.68 to 0.69). The calibration was excellent when comparing the expected with the observed risk in the two risk categories.
The simplified HOSPITAL score has good performance for predicting 30-day readmission. Prognostic accuracy was similar to the original version, while its use is even easier. This simplified score may provide a good alternative to the original score depending on the setting.
BACKGROUND/OBJECTIVES:New tools to accurately identify potentially preventable 30-day readmissions are needed. The HOSPITAL score has been internationally validated for medical inpatients, but its ...performance in select conditions targeted by the Hospital Readmission Reduction Program (HRRP) is unknown.
DESIGN:Retrospective cohort study.
SETTING:Six geographically diverse medical centers.
PARTICIPANTS/EXPOSURES:All consecutive adult medical patients discharged alive in 2011 with 1 of the 4 medical conditions targeted by the HRRP (acute myocardial infarction, chronic obstructive pulmonary disease, pneumonia, and heart failure) were included. Potentially preventable 30-day readmissions were identified using the SQLape algorithm. The HOSPITAL score was calculated for all patients.
MEASUREMENTS:A multivariable logistic regression model accounting for hospital effects was used to evaluate the accuracy (Brier score), discrimination (c-statistic), and calibration (Pearson goodness-of-fit) of the HOSPITAL score for each 4 medical conditions.
RESULTS:Among the 9181 patients included, the overall 30-day potentially preventable readmission rate was 13.6%. Across all 4 diagnoses, the HOSPITAL score had very good accuracy (Brier score of 0.11), good discrimination (c-statistic of 0.68), and excellent calibration (Hosmer-Lemeshow goodness-of-fit test, P=0.77). Within each diagnosis, performance was similar. In sensitivity analyses, performance was similar for all readmissions (not just potentially preventable) and when restricted to patients age 65 and above.
CONCLUSIONS:The HOSPITAL score identifies a high-risk cohort for potentially preventable readmissions in a variety of practice settings, including conditions targeted by the HRRP. It may be a valuable tool when included in interventions to reduce readmissions within or across these conditions.
Importance The most appropriate therapy for older adults with multimorbidity may depend on life expectancy (ie, mortality risk), and several scores have been developed to predict 1-year mortality ...risk. However, often, these mortality risk scores have not been externally validated in large sample sizes, and a head-to-head comparison in a prospective contemporary cohort is lacking. Objective To prospectively compare the performance of 6 scores in predicting the 1-year mortality risk in hospitalized older adults with multimorbidity. Design, Setting, and Participants This prognostic study analyzed data of participants in the OPERAM (Optimising Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older People) trial, which was conducted between December 1, 2016, and October 31, 2018, in surgical and nonsurgical departments of 4 university-based hospitals in Louvain, Belgium; Utrecht, the Netherlands; Cork, Republic of Ireland; and Bern, Switzerland. Eligible participants in the OPERAM trial had multimorbidity (≥3 coexisting chronic diseases), were aged 70 years or older, had polypharmacy (≥5 long-term medications), and were admitted to a participating ward. Data were analyzed from April 1 to September 30, 2020. Main Outcomes and Measures The outcome of interest was any-cause death occurring in the first year of inclusion in the OPERAM trial. Overall performance, discrimination, and calibration of the following 6 scores were assessed: Burden of Illness Score for Elderly Persons, CARING (Cancer, Admissions ≥2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, ≥2 Noncancer hospice guidelines) Criteria, Charlson Comorbidity Index, Gagné Index, Levine Index, and Walter Index. These scores were assessed using the following measures: Brier score (0 indicates perfect overall performance and 0.25 indicates a noninformative model); C-statistic and 95% CI; Hosmer-Lemeshow goodness-of-fit test and calibration plots; and sensitivity, specificity, and positive and negative predictive values. Results The 1879 patients in the study had a median (IQR) age of 79 (74-84) years and 835 were women (44.4%). The median (IQR) number of chronic diseases was 11 (8-16). Within 1 year, 375 participants (20.0%) died. Brier scores ranged from 0.16 (Gagné Index) to 0.24 (Burden of Illness Score for Elderly Persons). C-statistic values ranged from 0.62 (95% CI, 0.59-0.65) for Charlson Comorbidity Index to 0.69 (95% CI, 0.66-0.72) for the Walter Index. Calibration was good for the Gagné Index and moderate for other mortality risk scores. Conclusions and Relevance Results of this prognostic study suggest that all 6 of the 1-year mortality risk scores examined had moderate prognostic performance, discriminatory power, and calibration in a large cohort of hospitalized older adults with multimorbidity. Overall, none of these mortality risk scores outperformed the others, and thus none could be recommended for use in daily clinical practice.
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