Acute hospital-community hospital care bundle for elderly orthopedic surgery patients:A propensity score-matched economic analysis

BACKGROUND While Singapore attains good health outcomes,Singapore’s healthcare system is confronted with bed shortages and prolonged stays for elderly people recovering from surgery in acute hospitals.An Acute Hospital-Community Hospital(AHCH)care bundle has been developed to assist patients in postoperative rehabilitation.The core concept is to transfer patients out of AHs when clinically recommended and into CHs,where they can receive more beneficial dedicated care to aid in their recovery,while freeing up bed capacities in AHs.AIM To analyze the AH length of stay(LOS),costs,and savings associated with the AH-CH care bundle intervention initiated and implemented in elderly patients aged 75 years and above undergoing elective orthopedic surgery.METHODS A total of 8621:1 propensity score-matched patients aged 75 years and above who underwent elective orthopedic surgery in Singapore General Hospital(SGH)before(2017-2018)and after(2019-2021)the care bundle intervention period was analyzed.Outcome measures were AH LOS,CH LOS,hospitalization metrics,postoperative 30-d mortality,and modified Barthel Index(MBI)scores.The costs of AH inpatient hospital stay in the matched cohorts were compared using cost data in Singapore dollars.RESULTS Of the 862 matched elderly patients undergoing elective orthopedic surgery before and after the care bundle intervention,the age distribution,sex,American Society of Anesthesiologists classification,Charlson Comorbidity Index,and surgical approach were comparable between both groups.Patients transferred to CHs after the surgery had a shorter median AH LOS(7 d vs 9 d,P<0.001).The mean total AH inpatient cost per patient was 14.9%less for the elderly group transferred to CHs(S$24497.3 vs S$28772.8,P<0.001).The overall AH U-turn rates for elderly patients within the care bundle were low,with a 0%mortality rate following orthopedic surgery.When elderly patients were discharged from CHs,their MBI scores increased significantly(50.9 vs 71.9,P<0.001).CONCLUSION The AH-CH care bundle initiated and implemented in the Department of Orthopedic Surgery appears to be effective and cost-saving for SGH.Our results indicate that transitioning care between acute and community hospitals using this care bundle effectively reduces AH LOS in elderly patients receiving orthopedic surgery.Collaboration between acute and community care providers can assist in closing the care delivery gap and enhancing service quality.

Lessons learned from the hospital to home community care program in Singapore and the supporting AI multiple readmissions prediction model

In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home(H2H)program that has been operating since 2017.In this follow on practice and policy article,we further elaborate on Singapore's H2H program and care model,and its supporting AI model for multiple readmission prediction,in the following ways:(1)by providing updates on the AI and supporting information systems,(2)by reporting on customer engagement and related service delivery outcomes including staff‐related time savings and patient benefits in terms of bed days saved,(3)by sharing lessons learned with respect to(i)analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants,(ii)balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables,and(iii)the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems,(4)by highlighting how this H2H effort supported broader Covid‐19 response efforts across Singapore's public healthcare system,and finally(5)by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards.For the convenience of the reader,some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.

Elderly patients over 80 years undergoing colorectal cancer resection: Development and validation of a predictive nomogram for survival

BACKGROUND Surgery remains the primary treatment for localized colorectal cancer(CRC).Improving surgical decision-making for elderly CRC patients necessitates an accurate predictive tool.AIM To build a nomogram to predict the overall survival of elderly patients over 80 years undergoing CRC resection.METHODS Two hundred and ninety-five elderly CRC patients over 80 years undergoing surgery at Singapore General Hospital between 2018 and 2021 were identified from the American College of Surgeons–National Surgical Quality Improvement Program(ACS-NSQIP)database.Prognostic variables were selected using univariate Cox regression,and clinical feature selection was performed by the least absolute shrinkage and selection operator regression.A nomogram for 1-and 3-year overall survival was constructed based on 60%of the study cohort and tested on the remaining 40%.The performance of the nomogram was evaluated using the concordance index(C-index),area under the receiver operating characteristic curve(AUC),and calibration plots.Risk groups were stratified using the total risk points derived from the nomogram and the optimal cut-off point.Survival curves were compared between the high-and low-risk groups.RESULTS Eight predictors:Age,Charlson comorbidity index,body mass index,serum albumin level,distant metastasis,emergency surgery,postoperative pneumonia,and postoperative myocardial infarction,were included in the nomogram.The AUC values for the 1-year survival were 0.843 and 0.826 for the training and validation cohorts,respectively.The AUC values for the 3-year survival were 0.788 and 0.750 for the training and validation cohorts,respectively.C-index values of the training cohort(0.845)and validation cohort(0.793)suggested the excellent discriminative ability of the nomogram.Calibration curves demonstrated a good consistency between the predictions and actual observations of overall survival in both training and validation cohorts.A significant difference in overall survival was seen between elderly patients stratified into low-and high-risk groups(P<0.001).CONCLUSION We constructed and validated a nomogram predicting 1-and 3-year survival probability in elderly patients over 80 years undergoing CRC resection,thereby facilitating holistic and informed decision-making among these patients.