Risk Factors for Hospital Readmission and Death After Discharge of Older Adults from Acute Geriatric Units: Taking the Rank of Admission into Account

Identifying specific subgroups of older patients at risk of repeated hospital readmissions and death after discharge in a prospective multicentre cohort in France

OBJECTIVE

To identify specific subgroups of older patients at risk of repeated hospital readmissions and death.

DESIGN

Prospective, multicentre, DAMAGE (Patient Outcomes After Hospitalization in Acute Geriatric Unit) cohort of adults aged 75 and over, discharged from an acute geriatric unit (AGU) and followed up for 12 months.

SETTING

Six recruiting hospital centres in the Hauts-de-France and Normandie regions of France.

MAIN OUTCOME MEASURES

We performed a latent class analysis to identify subgroups at risk of repeated hospital readmissions and death, followed by a logistic regression analysis to determine the characteristics associated with the identified subgroups.

RESULTS

3081 patients were included (mean (SD) age: 86.4 (5.5)) and two subgroups were identified. In subgroup 1 (n=2169, 70.4%), only 619 (28.5%) patients were readmitted to hospital once during the follow-up, and 495 (22.5%) died. In subgroup 2 (n=912, 29.6%), all patients were readmitted to hospital at least twice, and 523 (57.8%) died. Subgroup 2 accounted for 29.6% of patients but 74.4% of hospital readmissions, with longer lengths of stay, and 51.6% of deaths. A multivariate logistic regression analysis identified only four characteristics weakly associated with the risk of being in subgroup 2 (at least one hospital admission in the 6 months preceding the index hospital admission, cancer, polymedication and weight changes (gain or loss) during the index hospital admission). The area under the receiver operating characteristic curve was 63%.

CONCLUSION

A latent class analysis showed that a population of older adults hospitalised in an AGU is divided into two subgroups with regard to the postdischarge outcomes: one subgroup (70% of the individuals) will have a low rate of hospital readmission and a moderate death rate, whereas the other will have a high rate of hospital readmission and a very high death rate. There is a need for predictive scores for both events, with a view to better targeting at-risk patients.

TRIAL REGISTRATION NUMBER

Trial registration number was approved by the local independent ethics committee (CPP Nord-Ouest IV, Lille, France) on 13 February 2015, with an amendment approved on 21 January 2016 (reference: IDRCB 2014 A01670 47, CNIL bxA15352514).

Elevating care: assessing the impact of telemonitoring on diabetes management at a cutting-edge quaternary hospital

OBJECTIVE

To assess whether post-discharge telemonitoring reduces hospital readmission in patients participating in the diabetes care program.

METHODS

This retrospective cohort study was conducted from June 2021 to December 2022 and included patients who were enrolled in the Diabetes Program under a hyperglycemia treatment protocol and eligible for post-discharge telemonitoring. The variables included age, sex, diagnosis, hospital stay, LACE Score, and readmission rate.

RESULTS

Among 165 patients who underwent telemonitoring, significant differences emerged in hospital readmission rates between those with and without telemonitoring (p=0.015), with a 15.4% lower readmission rate in the telemonitoring group (95%CI= 3.0-27.9%). Subgroup analyses revealed higher readmission rates in men without telemonitoring (15.2% difference; 95%CI= 0.4-30.0%; p=0.045), and in age groups ≤60 and ≥75 years without telemonitoring (24.2% difference; 95%CI= 4.5-43.9%; p=0.016 for ≤60 years; 37.1% difference; 95%CI= 9.9% to 64.2%; p=0.007 for ≥75 years). Additionally, patients with prolonged hospital stays (>7 days) without telemonitoring had higher readmission rates (19.5% difference; 95%CI= 4.5%-34.5%; p=0.011).

CONCLUSION

This study suggests that post-discharge telemonitoring can effectively lower hospital readmission rates in diabetes management programs, potentially offering improved health outcomes, cost savings, and enhanced healthcare delivery to patients.

Application of machine learning algorithms to predict 30-day hospital readmission following cement augmentation for osteoporotic vertebral compression fractures

Objective

Osteoporosis is a common skeletal disease that greatly increases the risk of pathologic fractures and accounts for approximately 700,000 vertebral compression fractures (VCFs) annually in the United States. Cement augmentation procedures such as balloon kyphoplasty (KP) and percutaneous vertebroplasty (VP) have demonstrated efficacy in the treatment of VCFs, however, some studies report rates of readmission as high as 10.8% following such procedures. The purpose of this study was to employ Machine Learning (ML) algorithms to predict 30-day hospital readmission following cement augmentation procedures for the treatment of VCFs using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database.

Methods

ACS-NSQIP was queried to identify patients undergoing either KP or VP from 2011 to 2014. Three ML algorithms were constructed and tasked with predicting post-operative readmissions within this cohort of patients. Results: Postoperative pneumonia, ASA Class 2 designation, age, partially-dependent functional status, and a history of smoking were independently identified as highly predictive of readmission by all ML algorithms. Among these variables postoperative pneumonia (p < 0.01), ASA Class 2 designation (p < 0.01), age (p = 0.002), and partially-dependent functional status (p < 0.01) were found to be statistically significant. Predictions were generated with an average AUC value of 0.757 and an average accuracy of 80.5%.

Conclusions

Postoperative pneumonia, ASA Class 2 designation, partially-dependent functional status, and age are perioperative variables associated with 30-day readmission following cement augmentation procedures. The use of ML allows for quantification of the relative contributions of these variables toward producing readmission.

The risk of rehospitalization within 30 days of discharge in older adults with malnutrition: A meta-analysis

INTRODUCTION

Malnutrition is a global health problem associated with higher rehospitalization risk, subsequently increasing the risks of adverse complications, and mortality in older individuals. Nevertheless, studies investigating this are still scarce, and even fewer reviewed and aggregated. A number of studies have recently assessed the correlation of malnourishment with rehospitalization among older adults.

OBJECTIVE/AIM

This systematic review and meta-analysis aimed to elaborate the correlation between malnutrition and 30-day rehospitalization in older adults.

METHODS

Systematic review was conducted on literatures from Cochrane, ScienceDirect, SpringerLink, Oxford Academic, and MEDLINE according to PRISMA Guideline, investigating the correlation of malnutrition in older adults with rehospitalization, using Malnutrition, Older Adults, and Rehospitalization as keywords. Meta-analysis was done using RevMan, with random-effect analysis model. P values of ≤0.05 were considered statistically significant with results reported as risk ratios (RR), mean differences (MD), 95 % confidence intervals (CI) and I2 statistics.

RESULTS

Seven literatures were analysed, consisting of 19,340 patients aged 65 or older undergoing hospitalization. Subjects were assessed with screening tools to identify malnutrition. Malnourished subjects are compared to others with normal nutrition; in cohort studies with follow-up period ranging from 3 to 16 months. Malnutrition significantly increased the risks of rehospitalization within 30 days (RR 1.73 [95 % CI 1.10-2.72], p = 0.02, I2 = 56 %), overall rehospitalization at all times (RR 1.33 [95 % CI 1.16-1.52], p < 0.0001, I2 = 75 %), and overall mortality (RR 2.66 [95 % CI 1.09-6.50], p = 0.03, I2 = 94 %).

CONCLUSION

Malnutrition exhibited significant consequences in older patients regarding the rate of rehospitalization and mortality based on this meta-analysis. Further research is highly encouraged to verify this finding.

Challenges and solutions for discharge support of elderly people in the acute care ward: Interviews with community-based integrated care supporters and patients in Tokyo, Japan

Japan, which has become the country with the longest-living people in the world due to rapid population aging, has an insurer function for each local government and socialized long-term care under a public system. Japan aims to build a Community-based Integrated Care System (CICS) for each municipality with the goal of integrating medical care and long-term care. However, despite the policy and management studies, the challenges and solutions for discharge support by the parties have not yet been clarified. This study aimed to obtain suggestions on challenges and solutions for discharge support in the acute care wards for the elderly for community-based integrated care support providers and patients in Kita Ward, Tokyo. Semi-structured interviews were conducted, and the obtained data were a priori analyzed by a deductive thematic analysis using a conceptual framework for integrated care based on the integrative functions of primary care. The challenges were found to include: i) disparity between medical and lifestyle perspectives, ii) competencies of medical and care workers at homes, iii) discharge support challenges related to the elderly themselves, iv) nursing care dependent on family; and v) the impact of payment of medical service in the health insurance system and payment of long-term care services. The solution that can be applied at the local government level was community connection. While aiming to build a CICS for each local government, there was a contradiction in that the challenges and solutions required examination at the national and prefectural levels.

Predictors of hospital readmission rate in geriatric patients

BACKGROUND

Hospital readmissions among older adults are associated with progressive functional worsening, increased institutionalization and mortality.

AIM

Identify the main predictors of readmission in older adults.

METHODS

We examined readmission predictors in 777 hospitalized subjects (mean age 84.40 ± 6.77 years) assessed with Comprehensive Geriatric Assessment (CGA), clinical, anthropometric and biochemical evaluations. Comorbidity burden was estimated by Charlson Comorbidity Index (CCI). Median follow-up was 365 days.

RESULTS

358 patients (46.1%) had a second admission within 365 days of discharge. Estimated probability of having a second admission was 0.119 (95%C.I. 0.095-0.141), 0.158 (95%C.I. 0.131-0.183), and 0.496 (95%C.I. 0.458-0.532) at 21, 30 and 356 days, respectively. Main predictors of readmission at 1 year were length of stay (LOS) > 14 days (p < 0.001), albumin level < 30 g/l (p 0.018), values of glomerular filtration rate (eGFR) < 40 ml/min (p < 0.001), systolic blood pressure < 115 mmHg (p < 0.001), CCI ≥ 6 (p < 0.001), and cardiovascular diagnoses. When the joint effects of selected prognostic variables were accounted for, LOS > 14 days, worse renal function, systolic blood pressure < 115 mmHg, higher comorbidity burden remained independently associated with higher readmission risk.

DISCUSSION

Selected predictors are associated with higher readmission risk, and the relationship evolves with time.

CONCLUSIONS

This study highlights the importance of performing an accurate CGA, since defined domains and variables contained in the CGA (i.e., LOS, lower albumin and systolic blood pressure, poor renal function, and greater comorbidity burden), when combined altogether, may offer a valid tool to identify the most fragile patients with clinical and functional impairment enhancing their risk of unplanned early and late readmission.

Multi-Year Retrospective Analysis of Mortality and Readmissions Correlated with STOPP/START and the American Geriatric Society Beers Criteria Applied to Calgary Hospital Admissions

Introduction: The goals of this retrospective cohort study of 129,443 persons admitted to Calgary acute care hospitals from 2013 to 2021 were to ascertain correlations of "potentially inappropriate medications" (PIMs), "potential prescribing omissions" (PPOs), and other risk factors with readmissions and mortality. Methods: Processing and analysis codes were built in Oracle Database 19c (PL/SQL), R, and Excel. Results: The percentage of patients dying during their hospital stay rose from 3.03% during the first admission to 7.2% during the sixth admission. The percentage of patients dying within 6 months of discharge rose from 9.4% after the first admission to 24.9% after the sixth admission. Odds ratios were adjusted for age, gender, and comorbidities, and for readmission, they were the post-admission number of medications (1.16; 1.12-1.12), STOPP PIMs (1.16; 1.15-1.16), AGS Beers PIMs (1.11; 1.11-1.11), and START omissions not corrected with a prescription (1.39; 1.35-1.42). The odds ratios for readmissions for the second to thirty-ninth admission were consistently higher if START PPOs were not corrected for the second (1.41; 1.36-1.46), third (1.41;1.35-1.48), fourth (1.35; 1.28-1.44), fifth (1.38; 1.28-1.49), sixth (1.47; 1.34-1.62), and seventh admission to thirty-ninth admission (1.23; 1.14-1.34). The odds ratios for mortality were post-admission number of medications (1.04; 1.04-1.05), STOPP PIMs (0.99; 0.96-1.00), AGS Beers PIMs (1.08; 1.07-1.08), and START omissions not corrected with a prescription (1.56; 1.50-1.63). START omissions for all admissions corrected with a prescription by a hospital physician correlated with a dramatic reduction in mortality (0.51; 0.49-0.53) within six months of discharge. This was also true for the second (0.52; 0.50-0.55), fourth (0.56; 0.52-0.61), fifth (0.63; 0.57-0.68), sixth (0.68; 0.61-0.76), and seventh admission to thirty-ninth admission (0.71; 0.65-0.78). Conclusions: "Potential prescribing omissions" (PPOs) consisted mostly of needed cardiac medications. These omissions occurred before the first admission of this cohort, and many persisted through their readmissions and discharges. Therefore, these omissions should be corrected in the community before admission by family physicians, in the hospital by hospital physicians, and if they continue after discharge by teams of family physicians, pharmacists, and nurses. These community teams should also meet with patients and focus on patients' understanding of their illnesses, medications, PPOs, and ability for self-care.

Readmission and adverse outcomes after percutaneous coronary intervention in patients with dementia

BACKGROUND

As the population ages, clinicians increasingly encounter ischemic heart disease in patients with underlying dementia. Therefore, we quantified differences in inhospital adverse events and 30-day readmission rates among patients with and without dementia undergoing percutaneous coronary intervention (PCI).

METHODS

Using the National Readmissions Database 2017-2018, we identified 755,406 index hospitalizations in which PCI was performed, of which 17,309 (2.3%) had a diagnosis of dementia. After propensity score matching patients with and without dementia, we assessed 30-day readmission and inhospital adverse events by Cox proportional hazards and logistic regression modeling and compared them with those of other common cardiac (pacemaker placement [PP]) and noncardiac (hip replacement surgery [HRS]) procedures.

RESULTS

Thirty-day readmission was significantly higher in patients with dementia than patients without dementia (hazard ratio [HR] 1.67, 95% confidence interval [CI] 1.60-1.74). Patients with dementia also experienced higher odds of delirium (odds ratio [OR] 4.37, CI 3.69-5.16), inhospital mortality (OR 1.15, CI 1.01-1.30), cardiac arrest (OR 1.19, CI 1.01-1.39), acute kidney injury (OR 1.30, CI 1.21-1.39), and fall (OR 2.51, CI 2.06-3.07). On multivariable Cox modeling, dementia independently predicted 30-day readmission (HR 1.14, CI 1.07-1.20). The higher readmission risk with PCI (11%) among those with dementia was similar to that of patients undergoing PP (10%), but lower than in those undergoing HRS (41%).

CONCLUSION

Patients with dementia who undergo PCI experience significantly increased rates of inhospital delirium, mortality, kidney injury, falls, and 30-day readmission. These adverse outcomes should be considered during shared decision-making with patients and their families.

The prognostic impacts of frailty on clinical and patient-reported outcomes in patients undergoing coronary artery or valvular surgeries/procedures: A systematic review and meta-analysis

BACKGROUND

Frailty is emerging as an important prognostic indicator for patients undergoing cardiac surgeries/procedures. We sought to evaluate the prognostic and differential impacts of frailty on patients undergoing coronary artery or valvular surgical procedures of different levels of invasiveness, and to explore the differential predictability of various frailty measurement models.

METHODS

Eight databases were searched for prospective cohort studies that have adopted validated measure(s) of frailty and reported clinical, healthcare service utilization, or patient-reported outcomes in patients undergoing coronary artery or valvular surgeries/procedures.

RESULTS

Sixty-two articles were included (N = 16,679). Frailty significantly predicted mortality (short-term [≤ 30 days]: odds ratio [OR]: 2.33, 95% confidence interval [CI]: 1.28-4.26; midterm [6 months to 1 year]: OR: 3.93, 95%CI: 2.65-5.83; long-term [>1 year]: HR: 2.23, 95%CI: 1.60-3.11), postoperative complications (ORs: 2.54-3.57), discharge to care facilities (OR: 5.52, 95%CI: 3.84-7.94), hospital readmission (OR: 2.00, 95%CI: 1.15-3.50), and reduced health-related quality of life (HRQoL; standardized mean difference: -0.74, 95%CI: -1.30 to -0.18). Subgroup analyses showed that frailty exerted a greater impact on short-term mortality in patients undergoing open-heart surgeries than those receiving transcatheter procedures. Multidimensional and physical-aspect-focused frailty measurements performed equally in predicting mortality, but multidimensional measurements were more predictive of hospital readmission than physical-aspect-focused measurements.

CONCLUSION

Frailty was predictive of postoperative mortality, complications, increased healthcare service utilization, and reduced HRQoL. The impact of frailty on short-term mortality was more prominent in patients undergoing open-heart surgeries than those receiving transcatheter procedures. Multidimensional measures of frailty enhanced prognostic risk estimation, especially for hospital readmission.

The Effectiveness of Family Medicine-Driven Interprofessional Collaboration on the Readmission Rate of Older Patients

Interprofessional collaboration (IPC) for older patient care among family physicians, dentists, therapists, nutritionists, nurses, and pharmacists in the rural hospital care of older patients could improve the hospital readmission rate. However, there is a lack of interventional studies on IPC for improving the readmission rate among Japanese older patients in rural hospitals. This quasi-experimental study was performed on patients >65 years who were discharged from a rural community hospital. The intervention was IPC implementation with effective information sharing and comprehensive management of older patients’ conditions for effective discharge and readmission prevention; implementation started on 1 April 2021. The study lasted 2 years, from 1 April 2021 to 31 March 2022 for the intervention group and from 1 April 2020 to 31 March 2021 for the comparison group. The average participant age was 79.86 (standard deviation = 15.38) years and the proportion of men was 45.0%. The Cox hazard model revealed that IPC intervention could reduce the readmission rate after adjustment for sex, serum albumin, polypharmacy, dependent condition, and Charlson Comorbidity Index score (hazard ratio = 0.66, 95% confidence interval: 0.54−0.81). Rural IPC intervention can improve inpatient care for older patients and decrease readmission rates. Thus, for effective rural IPC interventions, family physicians in hospitals should proactively collaborate with various medical professionals to improve inpatient health outcomes.

Association between metabolic obesity phenotypes and multiple myeloma hospitalization burden: A national retrospective study

Background & purpose

Obesity and metabolic disorders were associated with increased risk of MM, a disease characterized by high risk of relapsing and require frequent hospitalizations. In this study, we conducted a retrospective cohort study to explore the association of metabolic obesity phenotypes with the readmission risk of MM.

Patients & methods

We analyzed 34,852 patients diagnosed with MM from the Nationwide Readmissions Database (NRD), a nationally representative database from US. Hospitalization diagnosis of patients were obtained using ICD-10 diagnosis codes. According to obesity and metabolic status, the population was divided into four phenotypes: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). The patients with different phenotypes were observed for hospital readmission at days 30-day, 60-day, 90-day and 180-day. Multivariate cox regression model was used to estimate the relationship between obesity metabolic phenotypes and readmissions risk.

Results

There were 5,400 (15.5%), 7,255 (22.4%), 8,025 (27.0%) and 7,839 (35.6%) unplanned readmissions within 30-day, 60-day, 90-day and 180-day follow-up, respectively. For 90-day and 180-day follow-up, compared with patients with the MHNO phenotype, those with metabolic unhealthy phenotypes MUNO (90-day: P = 0.004; 180-day: P = < 0.001) and MUO (90-day: P = 0.049; 180-day: P = 0.004) showed higher risk of readmission, while patients with only obesity phenotypes MHO (90-day: P = 0.170; 180-day: P = 0.090) experienced no higher risk. However, similar associations were not observed for 30-day and 60-day. Further analysis in 90-day follow-up revealed that, readmission risk elevated with the increase of the combined factor numbers, with aHR of 1.068 (CI: 1.002-1.137, P = 0.043, with one metabolic risk factor), 1.109 (CI: 1.038-1.184, P = 0.002, with two metabolic risk factors) and 1.125 (95% CI: 1.04-1.216, P = 0.003, with three metabolic risk factors), respectively.

Conclusion

Metabolic disorders, rather than obesity, were independently associated with higher readmission risk in patients with MM, whereas the risk elevated with the increase of the number of combined metabolic factors. However, the effect of metabolic disorders on MM readmission seems to be time-dependent. For MM patient combined with metabolic disorders, more attention should be paid to advance directives to reduce readmission rate and hospitalization burden.

Prediction of 30-Day Readmission in Hospitalized Older Adults Using Comprehensive Geriatric Assessment and LACE Index and HOSPITAL Score

(1) Background: Elders have higher rates of rehospitalization, especially those with functional decline. We aimed to investigate potential predictors of 30-day readmission risk by comprehensive geriatric assessment (CGA) in hospitalized patients aged 65 years or older and to examine the predictive ability of the LACE index and HOSPITAL score in older patients with a combination of malnutrition and physical dysfunction. (2) Methods: We included patients admitted to a geriatric ward in a tertiary hospital from July 2012 to August 2018. CGA components including cognitive, functional, nutritional, and social parameters were assessed at admission and recorded, as well as clinical information. The association factors with 30-day hospital readmission were analyzed by multivariate logistic regression analysis. The predictive ability of the LACE and HOSPITAL score was assessed using receiver operator characteristic curve analysis. (3) Results: During the study period, 1509 patients admitted to a ward were recorded. Of these patients, 233 (15.4%) were readmitted within 30 days. Those who were readmitted presented with higher comorbidity numbers and poorer performance of CGA, including gait ability, activities of daily living (ADL), and nutritional status. Multivariate regression analysis showed that male gender and moderately impaired gait ability were independently correlated with 30-day hospital readmissions, while other components such as functional impairment (as ADL) and nutritional status were not associated with 30-day rehospitalization. The receiver operating characteristics for the LACE index and HOSPITAL score showed that both predicting scores performed poorly at predicting 30-day hospital readmission (C-statistic = 0.59) and did not perform better in any of the subgroups. (4) Conclusions: Our study showed that only some components of CGA, mobile disability, and gender were independently associated with increased risk of readmission. However, the LACE index and HOSPITAL score had a poor discriminating ability for predicting 30-day hospitalization in all and subgroup patients. Further identifiers are required to better estimate the 30-day readmission rates in this patient population.