Determinants of hospital readmissions in older people with dementia: a narrative review

INTRODUCTION

Over 50% of hospitalised older people with dementia have multimorbidity, and are at an increased risk of hospital readmissions within 30 days of their discharge. Between 20-40% of these readmissions may be preventable. Current research focuses on the physical causes of hospital readmissions. However, older people with dementia have additional psychosocial factors that are likely to increase their risk of readmissions. This narrative review aimed to identify psychosocial determinants of hospital readmissions, within the context of known physical factors.

METHODS

Electronic databases MEDLINE, EMBASE, CINAHL and PsychInfo were searched from inception until July 2022 and followed up in February 2024. Quantitative and qualitative studies in English including adults aged 65 years and over with dementia, their care workers and informal carers were considered if they investigated hospital readmissions. An inductive approach was adopted to map the determinants of readmissions. Identified themes were described as narrative categories.

RESULTS

Seventeen studies including 7,194,878 participants met our inclusion criteria from a total of 6369 articles. Sixteen quantitative studies included observational cohort and randomised controlled trial designs, and one study was qualitative. Ten studies were based in the USA, and one study each from Taiwan, Australia, Canada, Sweden, Japan, Denmark, and The Netherlands. Large hospital and insurance records provided data on over 2 million patients in one American study. Physical determinants included reduced mobility and accumulation of long-term conditions. Psychosocial determinants included inadequate hospital discharge planning, limited interdisciplinary collaboration, socioeconomic inequalities among ethnic minorities, and behavioural and psychological symptoms. Other important psychosocial factors such as loneliness, poverty and mental well-being, were not included in the studies.

CONCLUSION

Poorly defined roles and responsibilities of health and social care professionals and poor communication during care transitions, increase the risk of readmission in older people with dementia. These identified psychosocial determinants are likely to significantly contribute to readmissions. However, future research should focus on the understanding of the interaction between a host of psychosocial and physical determinants, and multidisciplinary interventions across care settings to reduce hospital readmissions.

Multimodal Machine Learning for Prediction of 30-day Readmission Risk in Elderly Population

BACKGROUND

Readmission within 30 days is a prevalent issue among elderly patients, linked to unfavorable health outcomes. Our objective was to develop and validate multimodal machine learning models for predicting 30-day readmission risk in elderly patients discharged from internal medicine departments.

METHODS

This was a retrospective cohort study which included elderly patients aged 75 or older, who were hospitalized at the Hadassah Medical Center internal medicine departments between 2014 and 2020. Three machine learning algorithms were developed and employed to predict 30-day readmission risk. The primary measures were predictive model performance scores, specifically area under the receiver operator curve (AUROC), and average precision.

RESULTS

This study included 19,569 admissions. Of them, 3,258 (16.65%) resulted in 30-day readmission. Our three proposed models demonstrated high accuracy and precision on an unseen test set, with AUROC values of 0.87, 0.89, and 0.93, respectively, and average precision values of 0.76, 0.78, and 0.81. Feature importance analysis revealed that the number of admissions in the past year, history of 30-day readmission, Charlson score, and admission length were the most influential variables. Notably, the natural language processing score, representing the probability of readmission according to a textual-based model trained on social workers assessment letters during hospitalization, ranked among the top 10 contributing factors.

CONCLUSIONS

Leveraging multimodal machine learning offers a promising strategy for identifying elderly patients who are at high risk for 30-day readmission. By identifying these patients, machine learning models may facilitate the effective execution of preventive actions to reduce avoidable readmission incidents.

Multifactorial risk factors for hospital readmissions among patients with symptoms of advanced heart failure

AIMS

Economic burden of heart failure is attributed to hospital readmissions. Previous studies assessing risk factors for readmissions have focused on single group of risk factors, were limited to 30-day readmissions, or did not account for competing risk of mortality. This study investigates the biological, socio-economic, and behavioural risk factors predicting hospital readmissions while accounting for the competing risk of mortality.

METHODS AND RESULTS

In this prospective cohort study, we recruited 250 patients hospitalized with symptoms of advanced heart failure [New York Heart Association (NYHA) Class III and IV] between July 2017 and April 2019. We analysed their baseline survey data and their hospitalization records over the next 4.5 years (July 2017 to January 2022). We used a joint-frailty model to determine the multifactorial risk factors for all-cause and unplanned hospital readmissions and mortality. At the time of recruitment, patients' mean (SD) age was 66 (12) years, majority being male (72%) and NYHA class IV (68%) with reduced ejection fraction (72%). 87% of the patients had poor self-care behaviours, 51% had diabetes and 56% had weak grip strength. Within 2 years of a hospital admission, 74% of the patients had at least one readmission. Among all readmissions during follow-up, 68% were unplanned. Results from the multivariable regression analysis shows that the independent risk factors for hospital readmissions were biologic-weak grip strength [hazard ratio (95% CI): 1.59 (1.06, 2.13)], poor functional status [1.79 (0.98, 2.61)], diabetes [1.42 (0.97, 1.86)]; behavioural-poor self-care [1.66 (0.84, 2.49)], and socio-economic-preference for maximal life extension at high cost for those with high education [1.98 (1.17, 2.80)]. Risk factors for unplanned hospital readmissions were similar. A higher hospital readmission rate increased the risk of mortality [1.86 (1.23, 2.50)]. Other risk factors for mortality were biologic-weak grip strength [3.65 (0.57, 6.73)], diabetes [2.52 (0.62, 4.42)], socio-economic-lower education [2.45 (0.37, 4.53)], and being married [2.53 (0.37, 4.69)]. Having a private health insurance [0.40 (0.08, 0.73)] lowered the risk for mortality.

CONCLUSIONS

Risk factors for hospital readmissions and mortality are multifactorial. Many of these factors, such as weak grip strength, diabetes, poor self-care behaviours, are potentially modifiable and should be routinely assessed and managed in cardiac clinics and hospital admissions.

Examining emergency department utilization following bariatric surgery

BACKGROUND

Emergency department (ED) utilization following surgery is poorly understood and places immense strain on the healthcare system, being responsible for up to $38 billion in wasteful spending annually. The aim of this study was to quantify ED utilization following bariatric procedures to identify causes and areas of improvement.

MATERIALS AND METHODS

A retrospective review of a prospectively maintained database was conducted for all patients who underwent metabolic bariatric surgery (MBS) between November 2006 and June 2019. The study includes 4703 patients across 8 hospitals in a single health system. Patients who returned to the ED within 30 and 90 days were analyzed for relation to surgery and preventability.

RESULTS

Of the 4703 patients that underwent MBS, 907 (19.3%) visited the ED at least once within 90 days and 350 (7.4%) required hospital readmission. The most common bariatric procedure performed was the Roux-en-Y Gastric Bypass (RYGB) (3716/4703) with an average BMI of 43.8. The median length between discharge and ED visit was 19 days. Under 50% of patients called prior to ED presentation and 61% of these ED visits resulted in discharge.

CONCLUSION

While hospital readmissions following MBS have been scrutinized in literature, investigation of ED utilization remains scarce. Our study is one of few to investigate postoperative ED utilization up to 90 days following bariatric intervention. A clear opportunity exists to improve discharge education and early post-discharge communication. This would additionally alleviate burden to allow focus on the acutely ill.

Telehealth care and remote monitoring strategies in heart failure patients: A systematic review and meta-analysis

BACKGROUND

Heart failure (HF) is a cardiac clinical syndrome that involves complex pathological aetiologies. It represents a growing public health issue and affects a significant number of people worldwide.

OBJECTIVES

To synthesize evidence related to the impact of telemonitoring strategies on mortality and hospital readmissions of heart failure patients.

METHODS

A systematic literature review was conducted using PubMed, Scopus, CINAHL, IEEE Xplore Digital Library, Engineering Source, and INSPEC. To be included, studies had to be in English or Italian and involve heart failure patients of any NYHA class, receiving care through any telecare, remote monitoring, telemonitoring, or telehealth programmes. Articles had to contain data on both mortality and number of patients who underwent rehospitalizations during follow-ups. To explore the effectiveness of telemonitoring strategies in reducing both one-year all-cause mortality and one-year rehospitalizations, studies were synthesized through meta-analyses, while those excluded from meta-analyses were summarized narratively.

RESULTS

Sixty-one studies were included in the review. Narrative synthesis of data suggests a trend towards a reduction in deaths among monitored patients, but the number of rehospitalized patients was higher in this group. Meta-analysis of studies reporting one-year all-cause mortality outlined the protective power of care models based on telemonitoring in reducing one-year all-cause mortality. Meta-analysis of studies reporting the number of rehospitalized patients in one-year outlined that telemonitoring is effective in reducing the number of rehospitalized patients when compared with usual care strategies.

CONCLUSION

Evidence from this review confirms the benefits of telemonitoring in reducing mortality and rehospitalizations of HF patients. Further research is needed to reduce the heterogeneity of the studies.

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.

Discharge planning and resource utilization for minimizing readmissions in acute exacerbation of chronic heart failure: Insights from an observational study in a community hospital

This cross-sectional study analyzed discharge disposition in 1,584 readmitted patients aged 65 or older with acute exacerbation of chronic heart failure (AECHF) in a large community hospital from April 2021 to April 2022. The study aimed to explore the relationship between age (65-74, 75-85, and 85 or older) and gender (male, female) with discharge disposition. Results revealed that 55.6 % were discharged for home self-care, 27.3 % with external home health support, and 17.1 % to skilled nursing facilities. Logistic regression showed no significant differences in discharge between age groups. Gender also had no statistically significant effect on discharge disposition. Effective discharge planning emerged as a key factor in reducing readmissions for AECHF. Gender did not significantly impact disposition, suggesting other variables played a more pivotal role. Comprehensive discharge planning and resource allocation, tailored to patient needs, are recommended to enhance patient outcomes and lower AECHF readmission rates.

A state-level analysis of macro-level factors associated with hospital readmissions

Investigation of the factors that contribute to hospital readmissions has focused largely on individual level factors. We extend the knowledge base by exploring macrolevel factors that may contribute to readmissions. We point to environmental, behavioral, and socioeconomic factors that are emerging as correlates to readmissions. Data were taken from publicly available reports provided by multiple agencies. Partial Least Squares-Structural Equation Modeling was used to test the association between economic stability and environmental factors on opioid use which was in turn tested for a direct association with hospital readmissions. We also tested whether hospital access as measured by the proportion of people per hospital moderates the relationship between opioid use and hospital readmissions. We found significant associations between Negative Economic Factors and Opioid Use, between Environmental Factors and Opioid Use, and between Opioid Use and Hospital Readmissions. We found that Hospital Access positively moderates the relationship between Opioid Use and Readmissions. A priori assumptions about factors that influence hospital readmissions must extend beyond just individualistic factors and must incorporate a holistic approach that also considers the impact of macrolevel environmental factors.

Utilization of a multidisciplinary hospital-based approach to reduce readmission rates

Background

Hospital readmissions remain a significant and pressing issue in our healthcare system. In 2010, the Affordable Care Act helped establish the Hospital Readmissions Reduction Program, which incentivized reducing readmission rates by instituting penalties. Hospital readmission, specifically unplanned, refers to a patient returning to the hospital shortly after discharge due to the same or a related medical condition, signaling potential issues in initial care, discharge processes, or post-hospitalization management. For this study, we defined readmission as a return to the hospital within 30 days. In 2018, Staten Island University Hospital started a multidisciplinary and coordinated initiative to reduce patient readmissions. The approach involved the departments of emergency medicine, medicine, cardiology, case management, nursing, pharmacy, and transitional care management. This study aimed to determine if this approach reduced 30-day readmissions.

Methods

This case-control retrospective study reviewed electronic health records between January 2018 and November 2019. Readmission rates within 30 days of index discharge were compared between patients who received transitional care management before and after establishing a multidisciplinary communication of transitional care. Readmission rates were unadjusted and adjusted for patient demographics and predisposed risk for readmission and compared across demographics and select clinical characteristics.

Results

A total of 772 patients were included in the analyses; 323 were in the control group (41.8%), and 449 were in the intervention group (58.2%). After the hospital adopted the workflow for multidisciplinary communication of transitional care, there was 45.2% less adjusted incidence of readmission, or approximately seven fewer overall readmissions per 100 patients (16.4% readmission vs 9.0% readmission; incident rate ratio, 0.55; 95% CI: 0.34-0.88).

Conclusions

Multidisciplinary communication approaches led by emergency medicine can help reduce readmissions significantly. Adopting a structured communication workflow can enhance co-managing patients with a high risk of readmission between the emergency department and hospital medicine teams.

Healthcare and economic burden of heart failure with amyloidosis: An insight from National Readmission Database

INTRODUCTION

We analyzed trends, causes and predictors of 30-days readmission in cardiac amyloidosis and inspected the impact of these readmissions on mortality, morbidity, and utilization of healthcare resources.

METHODS

Heart Failure with cardiac amyloidosis patients were selected from National readmission Database (NRD) using ICD-10 CM codes. Patients younger than 18 years, elective readmissions, readmissions due to trauma, patients with missing data and December 2018 admissions were excluded. Primary outcome was all-cause 30-day readmissions rate, secondary outcomes were factors associated with 30-days readmissions and their effect on morbidity, mortality, and healthcare resource utilization.

RESULTS

Out of 4123 total heart failure with cardiac amyloidosis index admissions in 2018, 3374 patients were included in final analysis. 19.6% were readmitted within 30 days. Readmitted patients were younger, sicker, admitted to small or large hospital. Hypertensive heart and Chronic Kidney Disease (CKD Stage I-IV) with Congestive Heart Failure (CHF), hypertensive heart and CKD (Stage V) or End Stage Renal Disease (ESRD) with CHF, hypertensive heart disease with CHF, acute kidney failure, and sepsis were the most common causes of readmissions. Young age, admission to small and large size hospitals were independent predictors of 30-day readmissions. Readmissions had higher mortality, costed 6.6 extra in hospital days to patients and $16380 per admission to healthcare system.

CONCLUSIONS

Cardiac amyloidosis readmissions were associated with increased morbidity and mortality of patients and extra burden on the healthcare system. There is a need to identify patients at risk for readmissions to improve patient outcomes and decrease healthcare cost.

Multimorbidity and prior falls correlate with risk of 30-day hospital readmission in aged 80+: A prospective cohort study

BACKGROUND/PURPOSE

Thirty-day hospital readmission rate significantly raised with advanced age. The performance of existing predictive models for readmission risk remained uncertain in the oldest population. We aimed to examine the effect of geriatric conditions and multimorbidity on readmission risk among older adults aged 80 and over.

METHODS

This prospective cohort study enrolled patients aged 80 and older discharged from a geriatric ward at a tertiary hospital, with phone follow-up for 12 months. Demographics, multimorbidity, and geriatric conditions were assessed before hospital discharge. Logistic regression models were conducted to analyse risk factors for 30-day readmission.

RESULTS

Patients readmitted had higher Charlson comorbidity index scores, and were more likely to have falls, frailty, and longer hospital stay, compared to those without 30-day readmission. Multivariate analysis revealed that higher Charlson comorbidity index score was associated with readmission risk. Older patients with a fall history within 12 months had a near 4-fold increase in readmission risk. Severe frailty status before index admission was associated with a higher 30-day readmission risk. Functional status at discharge was not associated with readmission risk.

CONCLUSION

In addition to multimorbidity, history of falls and frailty were associated with higher hospital readmission risk in the oldest.

Mortality Rate Among Patients with Alcohol Use Disorder with Two or More Readmissions to the Hospital

Background

Alcohol use disorder is associated with high morbidity and mortality rates, leading to a significant burden worldwide. Increased hazardous alcohol consumption has been reported during the COVID-19 pandemic raising concerns for greater impact of this already prevalent serious medical condition.

Methods

We conducted chart reviews and described demographic and clinical data for patients with two or more hospital readmissions from June 2020 to July 2021 and followed survival status through June 2022.

Results

We found a high mortality rate of 10.3%. Most patients had psychiatric conditions listed in the chart (n = 70, 80%). Only 34% (n = 24) of living patients and 6% (n = 1) of deceased patients were under psychiatric care. Rates of the utilization of medications for alcohol use disorder were low (n = 23, 26%).

Interpretation

We found high mortality rates in patients with two or more hospital readmissions with low rates of utilization of medications for alcohol use disorder and psychiatric care, thus identifying areas of potential improvement.

Disparities in transitions of acute stroke care: The transitions of care stroke disparities study methodological report

OBJECTIVE

The Transitions of Stroke Care Disparities Study (TCSD-S) is an observational study designed to determine race-ethnic and sex disparities in post-hospital discharge transitions of stroke care and stroke outcomes and to develop hospital-level initiatives to reduce these disparities to improve stroke outcomes.

MATERIALS AND METHODS

Here, we present the study rationale, describe the methodology, report preliminary outcomes, and discuss a critical need for the development, implementation, and dissemination of interventions for successful post-hospital transition of stroke care. The preliminary outcomes describe the demographic, stroke risk factor, socioeconomic, and acute care characteristics of eligible participants by race-ethnicity and sex. We also report on all-cause and vascular-related death, readmissions, and hospital/emergency room representations at 30- and 90-days after hospital discharge.

RESULTS

The preliminary sample included data from 1048 ischemic stroke and intracerebral hemorrhage discharged from 10 comprehensive stroke centers across the state of Florida. The overall sample was 45% female, 22% Non-Hispanic Black and 21% Hispanic participants, with an average age of 64 ± 14 years. All cause death, readmissions, or hospital/emergency room representations are 10% and 19% at 30 and 90 days, respectively. One in 5 outcomes was vascular-related.

CONCLUSIONS

This study highlights the transition from stroke hospitalization as an area in need for considerable improvement in systems of care for stroke patients discharged from hospital. Results from our preliminary analysis highlight the importance of investigating race-ethnic and sex differences in post-stroke outcomes.

Preoperative low handgrip strength (HGS) with HGS asymmetry is associated with adverse outcomes among older adults with gastric cancer

INTRODUCTION

This study aimed to explore the associations of low hand grip strength (HGS), HGS asymmetry, their combinations, and frailty on hospital readmissions, total complications, and prolonged length of stay (PLOS) among older adults with gastric cancer.

MATERIALS AND METHODS

This study included 342 patients with gastric cancer aged ≥60 years who were scheduled to undergo radical surgery. The Tilburg Frailty Indicator (TFI) was used to collect information on frailty. HGS was measured twice for each hand using an electronic handgrip dynamometer. The highest HGS readings on each hand were used for calculating the HGS asymmetry ratio: non-dominant HGS (kg)/dominant HGS (kg). The Fine and Gray proportional subdistribution hazard model and the logistic regression model were used for the analyses, with covariates adjusted.

RESULTS

Low HGS (subdistribution hazard ratios [SHR] = 2.10, 95% confidence interval [CI] = 1.05-3.93, P = 0.036) and low HGS with HGS asymmetry (SHR = 3.95, 95% CI = 1.50-10.36, P = 0.005) were significantly associated with hospital readmissions. Frailty was associated with total complications (odds ratio [OR] = 2.87, 95% CI = 1.61-5.13, P < 0.001) and PLOS (OR = 1.98, 95% CI = 1.19-3.29, P < 0.001). Low HGS, HGS asymmetry, and their combinations were not significantly associated with total complications and PLOS.

DISCUSSION

Preoperative low HGS and low HGS with HGS asymmetry were associated with hospital readmissions, while frailty was associated with total complications and PLOS among older adults with gastric cancer. In the future, more rigorously designed studies are needed to verify our results further to improve preoperative clinical assessment and frailty evaluation among older adults with gastric cancer.

Associations between source-apportioned PM2.5 and 30-day readmissions in heart failure patients

BACKGROUND

Air pollution exposure is a significant risk factor for morbidity and mortality, especially for those with pre-existing chronic disease. Previous studies highlighted the risks that long-term particulate matter exposure has for readmissions. However, few studies have evaluated source and component specific associations particularly among vulnerable patient populations.

OBJECTIVES

Use electronic health records from 5556 heart failure (HF) patients diagnosed between July 5, 2004 and December 31, 2010 that were part of the EPA CARES resource in conjunction with modeled source-specific fine particulate matter (PM_2.5) to estimate the association between exposure to source and component apportioned PM_2.5 at the time of HF diagnosis and 30-day readmissions.

METHODS

We used zero-inflated mixed effects Poisson models with a random intercept for zip code to model associations while adjusting for age at diagnosis, year of diagnosis, race, sex, smoking status, and neighborhood socioeconomic status. We undertook several sensitivity analyses to explore the impact of geocoding precision and other factors on associations and expressed associations per interquartile range increase in exposures.

RESULTS

We observed associations between 30-day readmissions and an interquartile range increase in gasoline- (16.9% increase; 95% confidence interval = 4.8%, 30.4%) and diesel-derived PM_2.5 (9.9% increase; 95% confidence interval = 1.7%, 18.7%), and the secondary organic carbon component of PM_2.5 (SOC; 20.4% increase; 95% confidence interval = 8.3%, 33.9%). Associations were stable in sensitivity analyses, and most consistently observed among Black study participants, those in lower income areas, and those diagnosed with HF at an earlier age. Concentration-response curves indicated a linear association for diesel and SOC. While there was some non-linearity in the gasoline concentration-response curve, only the linear component was associated with 30-day readmissions.

DISCUSSION

There appear to be source specific associations between PM_2.5 and 30-day readmissions particularly for traffic-related sources, potentially indicating unique toxicity of some sources for readmission risks that should be further explored.

Randomized intervention and outpatient follow-up lowers 30-d readmissions for patients with hepatic encephalopathy, decompensated cirrhosis

BACKGROUND

We previously reported national 30-d readmission rates of 27% in patients with decompensated cirrhosis (DC).

AIM

To study prospective interventions to reduce early readmissions in DC at our tertiary center.

METHODS

Adults with DC admitted July 2019 to December 2020 were enrolled and randomized into the intervention (INT) or standard of care (SOC) arms. Weekly phone calls for a month were completed. In the INT arm, case managers ensured outpatient follow-up, paracentesis, and medication compliance. Thirty-day readmission rates and reasons were compared.

RESULTS

Calculated sample size was not achieved due to coronavirus disease 2019; 240 patients were randomized into INT and SOC arms. 30-d readmission rate was 33.75%, 35.83% in the INT vs 31.67% in the SOC arm (P = 0.59). The top reason for 30-d readmission was hepatic encephalopathy (HE, 32.10%). There was a lower rate of 30-d readmissions for HE in the INT (21%) vs SOC arm (45%, P = 0.03). There were fewer 30-d readmissions in patients who attended early outpatient follow-up (n = 17, 23.61% vs n = 55, 76.39%, P = 0.04).

CONCLUSION

Our 30-d readmission rate was higher than the national rate but reduced by interventions in patients with DC with HE and early outpatient follow-up. Development of interventions to reduce early readmission in patients with DC is needed.

Stayin' alive: The introduction of municipal in-patient acute care units was associated with reduced mortality and fewer hospital readmissions

BACKGROUND

Integrated care is seen as integral in combating the current and projected resource scarcity in the healthcare systems of developed economies. Previous research finds positive effects from implementing intermediate care but there is a lack of research on how this shift towards care integration has affected traditional quality indicators within healthcare, indicators such as mortality rates and hospital readmissions. We seek to contribute to the discourse by studying how the introduction of intermediate care in the form of municipal acute units (MAUs) in Norway has affected age adjusted mortality rates and hospital readmissions.

DATA AND METHODS

In this retrospective cohort study we utilize yearly population-based registry data from 2010 to 2016, analysed with fixed-effects regressions. Data on the implementation, characteristics and localization of the MAUs were gathered by telephone during the implementation period. Data on mortality rates and hospital readmissions were collected from Statistics Norway and the Norwegian patient registry.

RESULTS

Our analyses finds that the introduction of MAU was associated with a statistically significant reduction in both aggregated mortality rates and hospital readmission rates. In depth analyses finds that our results are contingent upon the age of the patients treated at the MAUs and the clinical characteristics of the medical units themselves.

CONCLUSION

Our findings indicate that the shift towards intermediate care through the introduction of MAUs has increased performance within the public healthcare sector in Norway. Our findings indicate that the introduction of MAU have had a positive public health impact by lowering the mortality and readmission rates for the oldest population cohort in Norway. Our findings suggests that countries with comparatively similar healthcare systems as Norway could achieve similar benefits from implementing intermediate care in the form of somatic medical institutions in the local communities.

Calculating surgical readmission rates in gynecologic oncology: The impact of patient factors

OBJECTIVE

To determine the 30-day surgical readmission rate after major gynecologic oncology surgeries at a high-volume academic institution and correlated risk factors.

METHODS

Retrospective cohort study was conducted of surgical admissions from January 2016 - December 2019 at a single institution. Data were extracted from patient charts, including reason for readmission and length of stay. A readmission rate was calculated. Nested case control design was used to identify correlations between readmission and patient specific risk-factors. Multivariable logistic regression models were used to determine risk factors with readmission.

RESULTS

A total of 2152 patients were included. The readmission rate was 3.5%, most commonly due to GI disturbance and surgical site infection. Average readmission length was 5 days. Prior to adjusting for covariates, insurance status, primary diagnosis, index admission length, and disposition at discharge differed between patients who were and were not readmitted. After adjusting for co-variates, younger patients, index admission >2 days, and higher Charlson co-morbidity index were associated with readmission.

CONCLUSIONS

Our surgical readmission rate was lower than previously reported rates in gynecologic oncology patients. Patient factors associated with readmission included younger age, longer index hospital admission, and higher medical co-morbidity index scores. Provider factors and institutional practice patterns could contribute to the decreased readmission rate. These findings underscore the importance of standardizing how we calculate readmission rate and interpret these data. Varying readmission rates and institutional practice patterns deserve closer scrutiny to inform best practice and future policies.

Revision lumbar fusions have higher rates of reoperation and result in worse clinical outcomes compared to primary lumbar fusions

BACKGROUND CONTEXT

Indications for revision lumbar fusion are variable, but include recurrent stenosis (RS), adjacent segment disease (ASD), and pseudarthrosis. The efficacy of revision lumbar fusion has been well established, but their outcomes compared to primary procedures is not well documented.

PURPOSE

The purpose of this study was to compares surgical and clinical outcomes between (1) revision and primary lumbar fusion, (2) revision lumbar fusion based on indication (ASD, pseudarthrosis, or RS), and (3) revision lumbar fusion based on whether the index procedure included an isolated decompression or decompression with fusion.

STUDY DESIGN/SETTING

Retrospective single-institution cohort study.

PATIENT SAMPLE

Four thousand six hundred seventy-one consecutive lumbar fusions from 2011 to 2021, of which 892 (23.6%) were revision procedures. The indication for revision procedures included 502 (56.3%) for ASD, 153 (17.2%) for pseudarthrosis, and 237 (26.6%) for RS. Of the 892 revision procedures, 694 (77.8%) underwent an index fusion while 198 (22.2%) underwent an index decompression without fusion.

OUTCOME MEASURES

Hospital readmissions, all-cause reoperation, need for subsequent revision and patient reported outcome measures (PROMs) at baseline, 3-months postoperatively, and 1-year postoperatively, including the Mental Health Component score (MCS-12) and Physical Health Component score (PCS-12) of the Short Form 12 survey, the Oswestry Disability Index (ODI), and the Visual Analog Scale (VAS) for Back and Leg pain.

METHODS

Patient demographics, comorbidities, surgical characteristics, and outcomes were collected from electronic medical records. Twenty-eight percent of patients had preoperative and postoperative PROMs. A delta PROM score was calculated for the 3-month and 1-year postoperative timepoints, which was the change from the preoperative to postoperative value. Univariate comparisons were performed to compare revision fusions to primary fusions. Multivariate logistic regression was performed for all-cause reoperation and subsequent revision surgery, while multivariate linear regression was performed for ∆PROMs at 3-months and 1-year. Revision procedures were then separately regrouped based on indication for revision fusion and whether they underwent a fusion for their index procedure. Univariate comparisons and multivariate linear regressions for ∆PROMs were then repeated based on the new groupings.

RESULTS

There was no difference in hospital readmission rate (5.38% vs. 4.60%, p=.372) or length of stay (4.10 days vs. 3.94 days, p=.129) between revision and primary lumbar fusion, but revision fusions had a higher rate of all-cause reoperation (16.1% vs. 11.2%, p<.001) and subsequent revision (13.7% vs. 9.71%, p=.001), which was confirmed on multivariate logistic regression (Odds Ratio (OR): 1.42, p=.001 and OR: 1.37, p=.007, respectively). On multivariate analysis, a revision procedure was an independent risk factor for worse improvement ∆ODI, ∆VAS Back, ∆VAS Leg, and ∆PCS-12 and 1-year postoperatively. Regardless of the indication for revision lumbar fusion, patients significantly improved in the 3-month and 1-year postoperative PCS-12, ODI, VAS Back, and VAS Leg, with the exception of the 3-month PCS-12 for pseudarthrosis (p=.620). Patients undergoing revision for ASD had significantly worse 1-year postoperative PCS-12 (32.3 vs. Pseudarthrosis: 35.6 and RS: 37.0, p=.026), but there were no differences in ∆PROMs. There was no difference in hospital readmission, all-cause reoperation, or subsequent revision based on whether a patient had an index lumbar fusion or isolated decompression. Multivariate linear regression analysis found that a surgical indication of pseudarthrosis was a significant predictor of decreased improvement in 3-month ∆VAS Leg (ref: ASD, β=2.26, p=.036), but having an index fusion did not significantly predict worse improvement in ∆PROMs when compared to isolated decompressions.

CONCLUSIONS

Revision lumbar fusions had a higher rate of reoperation and subsequent revision surgery when compared to primary lumbar fusions, but there were no difference in hospital readmission rates. Patients undergoing revision lumbar fusion experience improvements in all patient reported outcome measures, but their baseline, postoperative, and magnitude of improvement are worse than primary procedures. Regardless of whether the lumbar fusion is a primary or revision procedure, all patients have significant improvements in pain, disability and physical function. Further, the indication for the revision procedure is not correlated with the expected magnitude of improvement in patient reported outcomes. Finally, no differences in baseline, postoperative, and ∆PROMs for revision fusions were identified when stratifying by whether the patient had an index decompression or fusion.

Hospital Readmission Prediction via Keyword Extraction and Sentiment Analysis on Clinical Notes

Unplanned hospital readmission is a problem that affects hospitals worldwide and is due to different factors. The identification of those factors can help determine which patients are at greater risk of hospital readmission for early intervention. Our end goal is to predict and identify patterns to (i) feed a decision support system for efficient management of patients and resources and (ii) detect patients at high risk of 30-days readmission enabling preventive actions to improve management of hospital discharges. This study aims to analyze whether natural language processing and specifically keyword extractions tools and sentiment analysis can support 30-days readmission prediction. Features extracted from medical history notes and discharge reports were used to train a Logistic Regression model. The resulting model obtains an AUC of 0.63 indicating that the sentiment polarity score of the discharge report and several of the extracted keywords are representative features to consider.

Evaluation of a patient-centered integrated care program for individuals with frequent hospital readmissions and multimorbidity

Managing patients with multimorbidity and frequent hospital readmissions is a challenge. Integrated care programs that consider their needs and allow for personalized care are necessary for their early identification and management. This work aims to describe these patients' clinical characteristics and evaluate a program designed to reducing readmissions. This prospective study analyzed all patients with ≥ 3 admissions to a medical department in the previous year who were included in the Internal Medicine Department chronic care program at the Lucus Augusti University Hospital (Lugo, Spain) between April 1, 2019 and April 30, 2021. A multidimensional assessment, personalized care plan, and proactive follow-up with a case manager nurse were provided via an advanced hospital system. Clinical and demographic variables and data on healthcare system use were analyzed at 6 and 12 months before and after inclusion. Descriptive and survival analyses were performed. One hundred sixty-one patients were included. Program participants were elderly (mean 81.4 (SD 11) years), had multimorbidity (10.2 (3) chronic diseases) and polypharmacy (10.6 (3.5) drugs), frequently used the healthcare system, and were highly complex. Most were included for heart failure. The program led to significant reductions in admissions and emergency department visits (p = .0001). A total of 44.7% patients died within 1 year. The PROFUND Index showed good predictive ability (p = .013), with high values associated with mortality (RR 1.15, p = .001). Patients with frequent hospital readmissions are highly complex and need special care. A personalized integrated care program reduced admissions and allowed for individualized decision-making.

Nurse-led health coaching programme to improve hospital-to-home transitional care for stroke survivors: A randomised controlled trial

OBJECTIVE

To evaluate the effects of a nurse-led health coaching programme for stroke survivors and family caregivers in hospital-to-home transition care.

METHODS

A total of 140 dyads of stroke survivors and their family caregivers were recruited and randomly assigned to either the intervention group (received a 12-week nurse-led health coaching programme) or the usual care group. The primary outcome was self-efficacy, and secondary outcomes were quality of life (QoL), stroke-related knowledge, and caregiver-related burden. The outcomes were measured at baseline, 12 and 24 weeks.

RESULTS

Stroke survivors in the intervention group demonstrated a significant improvement in self-efficacy at 12 weeks (x̅: 24.9, 95%CI: 20.2-29.6, p < 0.001) and at 24 weeks (x̅: 23.9, 95%CI: 19.2-28.6, p < 0.001) compared to the usual care group. Findings also demonstrated significant increases in stroke survivors' QoL, stroke-related knowledge, and reduction in unplanned hospital readmissions and caregiver-related burden. There were no statistically significant changes in other outcomes between the two groups.

CONCLUSION

The nurse-led health coaching programme improved health outcomes for both stroke survivors and their caregivers.

PRACTICE IMPACTION

Findings from the study suggest that nurse-led health coaching should be incorporated into routine practice in hospital-to-home transitional care for stroke survivors and their caregivers.

Why did you come back to the hospital? A qualitative analysis of 72-hour readmissions

OBJECTIVES

Readmissions occurring within a few days of discharge are more likely due to a problem from the patient's original admission and may be preventable by interventions in the hospital setting. As part of a quality improvement project intended to reduce readmissions within 72 hours of discharge our objective was to explore patient and physician perspectives of reasons for readmissions and to identify potential indicators of readmission during the index admission.

METHODS

A retrospective chart review of all readmissions within 72 hours between 2/1/2019 and 6/7/2019 in our healthcare system comprised of an academic medical center and 2 smaller community hospitals. As part of a hospital protocol, patients readmitted within 30 days were interviewed by a social worker regarding reasons for readmission and their perspective on what might have prevented it. These answers, physician notes relevant to the reason for readmission and the clinical course of the index admission were abstracted from patient charts. For the subset of patients identified by themselves or their physicians as potentially benefitting from a longer hospitalization, their index admission was reviewed for indicators of readmission. Reasons for readmission, potential preventive measures, and indicators of readmission were independently reviewed by two authors then grouped into common themes by consensus.

RESULTS

One hundred and thirty-one patients readmitted within 72 hours were identified. Most patients were readmitted for infection related, cardiac or pulmonary reasons. Extending the initial admission was the most common factor suggested by both patients and physicians to prevent readmission. Focusing on 70 patients who may have benefited from a longer admission, indicators included patients not returning to their baseline health status, inadequate management of a known issue, or new symptoms developing during the index admission.

CONCLUSIONS

Patients should be evaluated for indicators of readmission, which may help guide decisions to discharge patients and decrease rates of 72-hour readmissions.

Evaluation of health care quality among insured patients in Indonesian mother & child hospital: A secondary data analysis

OBJECTIVE

This study aimed to evaluate the health care quality among insured patients hospitalized in the Indonesian mother and child hospital.

METHOD

A secondary data analysis was performed to evaluate the health care services received by the insured patients hospitalized in the Indonesian mother and child hospital. Data were extracted from the BPJS health insurance e-claim database from January 1 to December 31, 2019 and from January 1 to June 30, 2020. A descriptive and bivariate analysis were used to examine total patients and hospital admissions; INACBGs diagnoses, procedures by severity; types of inpatient wards; length of stay; discharge status; hospital costs; and 30-day readmissions.

RESULTS

Total inpatient unit admissions were 2870 in 2019 and 1533 in 2020. From total hospital admissions in 2019 and 2020, over 50% were admitted to the 3rd class of inpatient units, less than 10% had length of stays more than 5 days, and over 98% were discharged based on physician approval. However, hospital readmissions were also found for about 20.1% in 2019 and 2.9% in 2020 and about 42.9% in 2019 and 61.3% in 2020 were found causing hospital financial losses. Older patients, longer hospital stays, inpatient ward class 1 & 2, high hospital tariff, inadequate clinical pathway implementation, lack of interprofessional collaboration, and ineffective nurse manager supervision were identified as contributing factors to the hospital financial losses.

CONCLUSION

Integrated clinical pathways with interprofessional collaboration that are implemented through professional nursing practice model are suggested for health care quality improvement.

Improving the safety of outpatient parenteral antimicrobial therapy for patients with solid tumors

Background and objectives

Outpatient parenteral antimicrobial therapy (OPAT) for infections has been in use for nearly 40 years, and although it has been found safe and efficacious, its use has been studied primarily among otherwise healthy patients. We aimed to develop and evaluate an OPAT program for patients with cancer, particularly solid tumors.

Methods

We implemented multiple quality improvement interventions between June 2018 and January 2020. We retrospectively and prospectively collected data on demographics, the completeness of infectious diseases (ID) physician consultation notes, rates of laboratory test result monitoring, ID clinic follow-up, and 30-day outcomes, including unplanned OPAT-related readmissions, OPAT-related emergency center visits, and deaths.

Results

Completeness of ID provider notes improved from a baseline of 77 to 100% (p < .0001) for antimicrobial recommendations, 75 to 97% (p < .0001) for follow-up recommendations, and 19 to 98% (p < .0001) for laboratory test result monitoring recommendations. Completion of laboratory tests increased from a baseline rate of 24 to 56% (p = .027). Thirty-day unplanned OPAT-related readmission, ID clinic follow-up, 30-day emergency center visit, and death rates improved without reaching statistical significance.

Conclusions

Sustained efforts, multiple interventions, and multidisciplinary engagement can improve laboratory test result monitoring among solid tumor patients discharged with OPAT. Although demonstrating a decrease in unplanned readmissions through institution of a formal OPAT program among patients with solid malignancies may be more difficult compared with the general population, the program may still result in improved safety.

Hospital readmissions in older adults with epilepsy in the US - A population-based study

OBJECTIVE

Our objective was to determine proportions, causes, and predictors of 30-day readmissions among older adults with epilepsy. Understanding predictors of readmissions may inform future interventions aimed at reducing avoidable hospitalizations in this vulnerable population.

METHODS

Individuals 65 years or older with epilepsy were identified using previously validated ICD-9-CM codes in any diagnostic position in the 2014 Nationwide Readmissions Database. Proportions of 30-day readmissions and causes of readmissions in older adults with epilepsy were compared to both older adults without and younger adults (18-64 years old) with epilepsy. We identified predictors of readmission in older adults with epilepsy using logistic regression.

RESULTS

There were 92,030 older adults with, 3,166,852 older adults without, and 168,622 younger adults with epilepsy. Proportions of readmissions were higher in older adults with (16.2%) than older adults without (12.5%) and younger adults with epilepsy (15.1%). The main cause of readmission for older adults with and without epilepsy was septicemia, and epilepsy/seizure in younger adults with epilepsy. Predictors of 30-day readmissions in older adults with epilepsy were: non-elective admissions (OR 1.37, 95%CI 1.27-1.48), public insurance (Medicaid vs. private insurance OR 1.19, 95%CI 1.02-1.39; Medicare vs. private insurance OR 1.11, 95%CI 1.00-1.22), lower median household income for patient's zip code ($1-$39,999 vs. $66,000 + OR 1.15, 95% CI 1.08-1.22), hospital location in large metropolitan areas (OR 1.22, 95%CI 1.05-1.42), higher Charlson-Deyo comorbidity index (OR 1.11, 95%CI 1.10-1.02), and male sex (OR 1.04, 95%CI 1.00-1.09).

SIGNIFICANCE

Our findings suggest that targeted interventions to reduce the risk of infection may potentially reduce readmission in older people with epilepsy, similarly to those without. Provision of coordinated care and appropriate discharge planning may reduce readmissions particularly in those who are males, are of lower socioeconomic status and with more comorbidities.

Temporal Trends and Patient Characteristics Associated with 30-Day Hospital Readmission Rates after a First Acute Myocardial Infarction

BACKGROUND

Limited data exist about relatively recent trends in the magnitude and characteristics of patients who are re-hospitalized after hospital admission for an acute myocardial infarction. This study examined trends in the frequency and sociodemographic and clinical characteristics of patients readmitted to the hospital within 30 days after an initial acute myocardial infarction.

METHODS

We reviewed the medical records of 3116 individuals who were hospitalized for a validated first acute myocardial infarction in 6 study periods between 2003 and 2015 at the 3 major medical centers in central Massachusetts.

RESULTS

The median age of our population was 67 years, and 42% were women. The risk of being readmitted to the hospital within 30 days after an initial acute myocardial infarction increased slightly during the most recent study years after controlling for potentially confounding factors. Overall, older adults and patients with previously diagnosed atrial fibrillation, heart failure, diabetes, chronic kidney disease, stroke, and peripheral vascular disease were at higher risk for being readmitted to the hospital than respective comparison groups. For those hospitalized in the most recent study years of 2011/2015, a higher risk of rehospitalization was associated with a previous diagnosis of chronic kidney disease, peripheral vascular disease, the presence of 3 or more chronic conditions, and having developed atrial fibrillation or heart failure during the patient's hospitalization for a first acute myocardial infarction.

CONCLUSIONS

We identified several groups at higher risk for hospital readmission in whom enhanced surveillance efforts as well as tailored educational and treatment approaches remain needed.

Does endoscopic intervention prevent subsequent gastrointestinal bleeding in patients with left ventricular assist devices? A retrospective study

BACKGROUND

Patients with left ventricular assist devices (LVADs) are at increased risk for recurrent gastrointestinal bleeding (GIB) and repeat endoscopic procedures. We assessed the frequency of endoscopy for GIB in patients with LVADs and the impact of endoscopic intervention on preventing a subsequent GIB.

AIM

To evaluate for an association between endoscopic intervention and subsequent GIB. Secondary aims were to assess the frequency of GIB in our cohort, describe GIB presentations and sources identified, and determine risk factors for recurrent GIB.

METHODS

We conducted a retrospective cohort study of all patients at a large academic institution who underwent LVAD implantation from January 2011 – December 2018 and assessed all hospital encounters for GIB through December 2019. We performed a descriptive analysis of the GIB burden and the outcome of endoscopic procedures performed. We performed multivariate logistic regression to evaluate the association between endoscopic intervention and subsequent GIB.

RESULTS

In the cohort of 295 patients, 97 (32.9%) had at least one GIB hospital encounter. There were 238 hospital encounters, with 55.4% (132/238) within the first year of LVAD implantation. GIB resolved on its own by discharge in 69.8% (164/235) encounters. Recurrent GIB occurred in 55.5% (54/97) of patients, accounting for 59.2% (141/238) of all encounters. Of the 85.7% (204/238) of encounters that included at least one endoscopic evaluation, an endoscopic intervention was performed in 34.8% (71/204). The adjusted odds ratio for subsequent GIB if an endoscopic intervention was performed during a GIB encounter was not significant (odds ratio 1.18, P = 0.58).

CONCLUSION

Patients implanted with LVADs whom experience recurrent GIB frequently undergo repeat admissions and endoscopic procedures. In this retrospective cohort study, adherence to endoscopic guidelines for performing endoscopic interventions did not significantly decrease the odds of subsequent GIB, thus suggesting the uniqueness of the LVAD population. A prospective study is needed to identify patients with LVAD at risk of recurrent GIB and determine more effective management strategies.

Charlson Comorbidity Index score predicts adverse post-operative outcomes after far lateral lumbar discectomy

INTRODUCTION

The Charlson Comorbidity Index (CCI) score has been shown to predict 10-year all-cause mortality and post-neurosurgical complications but has never been examined in a far lateral disc herniation (FLDH) population. This study aims to correlate CCI score with adverse outcomes following FLDH repair.

PATIENTS AND METHODS

All patients (n = 144) undergoing discectomy for FLDH at a single, multihospital academic medical system (2013-2020) were retrospectively analyzed. CCI scores were determined for all patients. Univariate logistic regression was used to determine the ability of CCI score to predict adverse outcomes.

RESULTS

Mean age of the population was 61.72 ± 11.55 years, 69 (47.9%) were female, and 126 (87.5%) were non-Hispanic white. Patients underwent either open (n = 92) or endoscopic (n = 52) FLDH repair. Average CCI score among the patient population was 2.87 ± 2.42. Each additional point in CCI score was significantly associated with higher rates of readmission (p = 0.022, p = 0.014) in the 30-day and 30-90-day post-surgery window, respectively, and emergency department visits (p = 0.011) within 30-days. CCI score also predicted risk of reoperation of any kind (p = 0.013) within 30 days of the index operation. In addition, CCI score was predictive of risk of reoperation of any kind (p = 0.008, p < 0.001; respectively) and repeat neurosurgical intervention (p = 0.027, p = 0.027) within 30-days and 90-days of the index admission (either during the same admission or after discharge).

CONCLUSIONS

This study suggests that CCI score is a useful metric to predict of numerous adverse postoperative outcomes following discectomy for FLDH.

Predicting patient outcomes after far lateral lumbar discectomy

INTRODUCTION

The LACE+ (Length of Stay, Acuity of Admission, Charlson Comorbidity Index (CCI) Score, Emergency Department (ED) visits within the previous 6 months) index has never been tested in a purely spine surgery population. This study assesses the ability of LACE + to predict adverse patient outcomes following discectomy for far lateral disc herniation (FLDH).

PATIENTS AND METHODS

Data were obtained for patients (n = 144) who underwent far lateral lumbar discectomy at a single, multi-hospital academic medical center (2013-2020). LACE + scores were calculated for all patients with complete information (n = 100). The influence of confounding variables was assessed and controlled with stepwise regression. Logistic regression was used to test the ability of LACE + to predict risk of unplanned hospital readmission, ED visits, outpatient office visits, and reoperation after surgery.

RESULTS

Mean age of the population was 61.72 ± 11.55 years, 69 (47.9 %) were female, and 126 (87.5 %) were non-Hispanic white. Patients underwent either open (n = 92) or endoscopic (n = 52) surgery. Each point increase in LACE + score significantly predicted, in the 30-day (30D) and 30-90-day (30-90D) post-discharge window, higher risk of readmission (p = 0.005, p = 0.009; respectively) and ED visits (p = 0.045). Increasing LACE + also predicted, in the 30D and 90-day (90D) post-discharge window, risk of reoperation (p = 0.022, p = 0.016; respectively), and repeat neurosurgical intervention (p = 0.026, p = 0.026; respectively). Increasing LACE + score also predicted risk of reoperation (p = 0.011) within 30 days of initial surgery.

CONCLUSIONS

LACE + may be suitable for characterizing risk of adverse perioperative events for patients undergoing far lateral discectomy.

Evidence based processes to prevent readmissions: more is better, a ten-site observational study

Background

30-day hospital readmissions are an indicator of quality of care; hospitals are financially penalized by Medicare for high rates. Numerous care transition processes reduce readmissions in clinical trials. The objective of this study was to examine the relationship between the number of evidence-based transitional care processes used and the risk standardized readmission rate (RSRR).

Methods

Design: Mixed method, multi-stepped observational study. Data collection occurred 2014–2018 with data analyses completed in 2021. Setting: Ten VA hospitals, chosen for 5-year trend of improving or worsening RSRR prior to study start plus documented efforts to reduce readmissions. Participants: During five-day site visits, three observers conducted semi-structured interviews (n = 314) with staff responsible for care transition processes and observations of care transitions work (n = 105) in inpatient medicine, geriatrics, and primary care. Exposure: Frequency of use of twenty recommended care transition processes, scored 0–3. Sites’ individual process scores and cumulative total scores were tested for correlation with RSRR. Outcome: best fit predicted RSRR for quarter of site visit based on the 21 months surrounding the site visits.

Results

Total scores: Mean 38.3 (range 24–47). No site performed all 20 processes. Two processes (pre-discharge patient education, medication reconciliation prior to discharge) were performed at all facilities. Five processes were performed at most facilities but inconsistently and the other 13 processes were more varied across facilities. Total care transition process score was correlated with RSRR (R² = 0..61, p < 0.007).

Conclusions

Sites making use of more recommended care transition processes had lower RSRR. Given the variability in implementation and barriers noted by clinicians to consistently perform processes, further reduction of readmissions will likely require new strategies to facilitate implementation of these evidence-based processes, should include consideration of how to better incorporate activities into workflow, and may benefit from more consistent use of some of the more underutilized processes including patient inclusion in discharge planning and increased utilization of community supports. Although all facilities had inpatient social workers and/or dedicated case managers working on transitions, many had none or limited true bridging personnel (following the patient from inpatient to home and even providing home visits). More investment in these roles may also be needed.

Sex Differences in Ischemic Stroke Readmission Rates and Subsequent Outcomes After Coronary Artery Bypass Graft Surgery

BACKGROUND AND PURPOSE

Prior studies examining sex-related risk of readmission for ischemic stroke (IS) after coronary artery bypass grafting (CABG) did not adjust for preoperative comorbidities and used small study samples that were single-center or otherwise poorly generalizable. We assessed risk of readmission for IS after CABG for females compared to males in a nationwide sample.

METHODS

The 2013 Nationwide Readmissions Database contains data on 49% of all U.S. hospitalizations. We used population weighting to determine national estimates. Using all follow-up data up to 1 year after discharge from CABG hospitalization, we estimated Kaplan-Meier cumulative risk of IS, stratified by sex, using the log-rank test for significance. We created Cox proportional hazard models to calculate hazard ratios (HR) and 95% confidence intervals (CI) for IS readmission, with sex as the main independent variable. We ran unadjusted models and models adjusted for age, vascular risk factors, estimated severity of illness and risk of mortality, hospital characteristics, and income quartile of patient's zip code.

RESULTS

An estimated 53,270 females and 147,396 males survived index CABG admission in 2013. There was a consistently elevated cumulative risk of readmission for IS after CABG for females versus males (log-rank p-value = 0.0014). In the unadjusted Cox model, the HR of IS in females vs. males was 1.35 (95% CI 1.12-1.62, p = 0.0015). The elevated risk for females remained after adjusting for severity of illness (1.30 [1.08-1.56], p = 0.0056) and risk of mortality (1.28 [1.07-1.54], p = 0.0086). This elevated risk persisted after adjusting for multiple vascular risk factors, hospital characteristics, and income quartile of patient's zip code (1.23 [1.02-1.48], p = 0.03).

CONCLUSIONS

We found a 23% increased risk of readmission for IS up to 1 year after CABG for females compared to males in a fully adjusted model utilizing a large, contemporary, nationwide database. Further research would clarify mechanisms of this increased risk among women.

Effectiveness of nurse-led peri-discharge interventions for reducing 30-day hospital readmissions: Network meta-analysis

BACKGROUND

Existing systematic reviews have compared the effectiveness of nurse-led peri-discharge interventions comprising different components with usual care on reducing all-cause 30-day hospital readmissions. However, conflicting results were reported.

OBJECTIVE

We conducted a network meta-analysis to evaluate the comparative effectiveness of different nurse-led peri-discharge interventions, compared with usual care, for reducing all-cause 30-day hospital readmissions.

DESIGN

Network meta-analysis.

METHODS

A total of five international databases were searched for systematic reviews of randomized controlled trials. Additional searches for most updated randomized controlled trials published between 2014 to 2019 were conducted. Data from included randomized controlled trials were extracted for random-effect pairwise meta-analyses. Pooled risk ratios with 95% confidence interval were used to quantify impact of nurse-led peri-discharge interventions on all-cause 30-day hospital readmissions. Network meta-analysis was used to evaluate the comparative effectiveness of different interventions.

RESULTS

From two systematic reviews and additional randomized controlled trial searches, 12 eligible randomized controlled trials (n=150,840) assessing 15 different nurse-led peri-discharge interventions were included. For reducing all-cause 30-day hospital readmissions, pairwise meta-analysis showed that there was no significant difference between nurse-led peri-discharge interventions and usual care (pooled risk ratios = 0.86, 95% confidence interval: 0.71-1.04, moderate quality of evidence). Network meta-analysis indicated no significant difference across different interventions despite variation in complexity.

CONCLUSIONS

Our results indicated that nurse-led peri-discharge interventions were not significantly different from usual care for reducing all-cause 30-day hospital readmissions. Simpler nurse-led peri-discharge interventions are on par with more complex interventions in terms of effectiveness. Benefits of nurse-led peri-discharge interventions may vary across health system context. Therefore, careful consideration is required prior to implementation.

REGISTRATION DETAILS

The protocol for this study has been registered in PROSPERO (Registration No. CRD42020186938). Tweetable abstract: This study suggested that nurse-led peri-discharge interventions do not differ from usual care for reducing all-cause 30-day hospital readmissions.

Improving evidence-based grouping of transitional care strategies in hospital implementation using statistical tools and expert review

BACKGROUND

As health systems transition to value-based care, improving transitional care (TC) remains a priority. Hospitals implementing evidence-based TC models often adapt them to local contexts. However, limited research has evaluated which groups of TC strategies, or transitional care activities, commonly implemented by hospitals correspond with improved patient outcomes. In order to identify TC strategy groups for evaluation, we applied a data-driven approach informed by literature review and expert opinion.

METHODS

Based on a review of evidence-based TC models and the literature, focus groups with patients and family caregivers identifying what matters most to them during care transitions, and expert review, the Project ACHIEVE team identified 22 TC strategies to evaluate. Patient exposure to TC strategies was measured through a hospital survey (N = 42) and prospective survey of patients discharged from those hospitals (N = 8080). To define groups of TC strategies for evaluation, we performed a multistep process including: using ACHIEVE'S prior retrospective analysis; performing exploratory factor analysis, latent class analysis, and finite mixture model analysis on hospital and patient survey data; and confirming results through expert review. Machine learning (e.g., random forest) was performed using patient claims data to explore the predictive influence of individual strategies, strategy groups, and key covariates on 30-day hospital readmissions.

RESULTS

The methodological approach identified five groups of TC strategies that were commonly delivered as a bundle by hospitals: 1) Patient Communication and Care Management, 2) Hospital-Based Trust, Plain Language, and Coordination, 3) Home-Based Trust, Plain language, and Coordination, 4) Patient/Family Caregiver Assessment and Information Exchange Among Providers, and 5) Assessment and Teach Back. Each TC strategy group comprises three to six, non-mutually exclusive TC strategies (i.e., some strategies are in multiple TC strategy groups). Results from random forest analyses revealed that TC strategies patients reported receiving were more important in predicting readmissions than TC strategies that hospitals reported delivering, and that other key co-variates, such as patient comorbidities, were the most important variables.

CONCLUSION

Sophisticated statistical tools can help identify underlying patterns of hospitals' TC efforts. Using such tools, this study identified five groups of TC strategies that have potential to improve patient outcomes.

Cognitive impairment in patients hospitalized for congestive heart failure: data from the RICA Registry

The objective of this study is to determine the prevalence of cognitive impairment (CogI) in patients hospitalized for congestive heart failure, and the influence of CogI on mortality and hospital readmission. This is a multicenter cohort study of patients hospitalized for congestive heart failure enrolled in the RICA registry. The patients were divided into 3 groups according to their Short Portable Mental Status Questionnaire score: 0-3 errors (no CogI or mild CogI), 4-7 (moderate CogI) and 8-10 (severe CogI). A total of 3845 patients with a mean (SD) age of 79 (8.6) years were included; 2038 (53%) were women. A total of 550 (14%) patients had moderate CogI and 76 (2%) had severe CogI. Factors independently associated with severe CogI were age (OR 1.09, 95% CI 1.05-1.14 p < 0.001), male sex (OR 0.57, 95% CI 0.34-0.95, p = 0.031), heart rate (OR 1.01, 95% CI 1.00-1.02, p = 0.004), Charlson index (OR 1.16, 95% CI 1.06-1.27, p = 0.002), and history of stroke (OR 2.67, 95% CI 1.60-4.44, p < 0.001). Severe CogI was associated with higher mortality after one year (HR 3.05, 95% CI 2.25-4.14, p < 0.001). The composite variable of death/hospital readmission was higher in patients with CogI (log rank p < 0.001). Patients with heart failure and severe CogI are older and have a higher comorbidity burden, lower survival, and a higher rate of death or readmission at 1 year, compared to patients with no CogI.

Phase angle is associated with length of hospital stay, readmissions, mortality, and falls in patients hospitalized in internal-medicine wards: A retrospective cohort study

OBJECTIVES

The aim of this study was to investigate the predictive value of bioimpedance phase angle (PA) on selected clinical outcomes in patients hospitalized in internal-medicine wards.

METHODS

This was a retrospective observational study of 168 patients admitted to the internalmedicine service (52.9% women, 47.1% men), with a mean (± SD) age of 73.9 ± 15.9 y. Anthropometric examination, laboratory tests, and bioelectrical impedance analysis were performed. Bioimpedance-derived PA was the study's parameter. Length of hospital stay, prospective all-cause hospital readmission, mortality, and falls were the clinical endpoints.

RESULTS

Across the four PA quartile groups, age was incrementally higher (P ≤ 0.001). Multivariate linear regression models showed that PA quartile 1 was significantly associated with length of hospital stay (β, SE) in both crude and adjusted models-respectively, β (SE) = 6.199 (1.625), P ≤ 0.001, and β = 2.193 (1.355), P = 0.033. Over a 9-mo follow-up period, the hazard ratios for readmission, in-hospital falls, and mortality were associated with the lowest phase angle (PA quartile 1 versus quartiles 2-4)-respectively, 2.07 (95% confidence interval [CI], 1.28-3.35), 2.36 (95% CI, 1.05-5.33), and 2.85 (95% CI, 1.01-7.39). Associations between narrow PA and outcomes continued to be significant after adjustments for various confounders.

CONCLUSIONS

In internal-medicine wards, bioimpedance-derived PA emerged as a predictor of length of hospital stay, hospital readmission, falls, and mortality. The present findings suggest that in the hospital setting, PA assessment could be useful in identifying patients at higher risk who need specific nutritional support.

Fracture-related hospitalisations and readmissions of Australian children ≤16 years: A 10-year population-based cohort study

BACKGROUND

Fractures represent the most common injury-related hospitalisations of children. Injured children often miss days from school, may experience ongoing pain and disability, as well as a reduced quality of life. To monitor temporal trends, and to enable targeted strategies to prevent fracture-related hospitalisation, an examination of the characteristics of hospitalisations by fracture-type is needed. The aim of this study was to investigate the characteristics, health outcomes and hospital treatment costs of fracture hospitalisations and readmissions of children aged ≤16 years in Australia across a 10-year period for the five most common types of fractures.

METHOD

Linked Australian hospitalisation and mortality records during 1 July 2002 to 30 June 2012 were analysed. Hospital treatment costs and length of stay were estimated, and the number and causes of hospital readmissions were identified.

RESULTS

There were 287,646 fracture-related hospital admissions in Australia for children ≤16 years. The five most common fracture regions were the forearm (48.1%), shoulder and upper arm (14.1%), lower leg including the ankle (11.3%), wrist and hand (10.4%), and the skull and face (9.0%). There was a decrease in hospitalisation rate for all fractures over the 10-year period. The hospitalisation rate for males was at least double that of females. Falls, particularly those from playground equipment, were the most common injury mechanism. Hospital readmissions within 28 days of hospitalisation were mostly due to further orthopaedic care or rehabilitation. Total treatment costs for fracture-related hospitalisations amounted to over AUD$732 million, with the median cost of readmissions being AUD$2,474.

CONCLUSION

While there is a decline in the rate of hospitalised fractures in Australian children, continued efforts are required if the rate of fractures and their associated economic costs are to be reduced. The identification of the prevalence and causes of various fracture types provides policymakers with evidence to target preventive initiatives.

Diabetic Foot Infection and Select Comorbidities Drive Readmissions in Outpatient Parenteral Antimicrobial Therapy

BACKGROUND

Outpatient parenteral antimicrobial therapy (OPAT) facilitates early patient discharge, but readmissions prior to completion of therapy may offset its advantages. The objective of this study was to evaluate unplanned readmissions of patients undergoing OPAT at our institution and to identify risk factors. We hypothesized that host factors were most relevant.

METHODS

We retrospectively identified all patients discharged to receive OPAT during 2017 who experienced at least one unplanned readmission to the hospital prior to its completion. We determined the proportion of patients readmitted, and the causes for readmission. Using a control group, we identified risk factors through multivariate logistic regression analysis.

RESULTS

Out of 684 patients, 17% had an unplanned readmission while receiving OPAT. Causes included worsening infection in 18%, venous access problems in 11%, acute events unrelated to infection in 19%, treatment intolerance in 19%, progression of underlying comorbidity in 20%, and social and other problems in 13%. In multivariate analysis diabetic foot infection (OR 3.24; 95%CI 1.38-8.31; p = 0.01), the presence of chronic kidney disease, decubitus ulcer or heart failure (OR 2.65; 95% CI 1.51-4.70; p < 0.001), and narcotics prescribed at discharge (OR 1.93; 95% CI 1.06-3.60; p = 0.049) were independent risk factors for readmission.

CONCLUSIONS

Unplanned hospital readmissions were frequent and due to very heterogeneous causes. Diabetic foot infection, selected comorbidities, and discharge on opioids were identified as independent risk factors. In the efforts to decrease readmissions among patients receiving outpatient parenteral antimicrobial a focus on these high-risk groups is a priority.

Index Admission Characteristics and All-Cause Readmissions Analysis in Younger and Older Adults with Intracerebral Hemorrhage

INTRODUCTION

Intracerebral hemorrhage (ICH) comprises 15-20% of all strokes with debilitating consequences. Data regarding characteristics and outcomes of primary ICH in the young are lacking, given its rarity, making comparisons between younger and older cohorts difficult to perform. Nationally representative administrative databases enable analysis of such rare events.

OBJECTIVE

To determine the baseline characteristics, all-cause readmission rates, and reasons for primary ICH in younger and older adults using a nationally representative database.

METHODS

A retrospective cohort analysis was performed using the Nationwide Readmissions Database 2013. Validated ICD-9-CM codes identified index ICH admissions, comorbidities, demographics, behavioral risk factors, procedures, and Elixhauser and Charlson Comorbidity indices. We compared "younger" (age ≤ 45 years) and "older" (age > 45) index ICH admissions by weighted 30-day all-cause readmission rates, primary diagnosis code for 30-day readmissions, most common comorbidities during the index hospitalization, and Kaplan-Meier cumulative risk of readmission up to 1 year.

RESULTS

Older admissions had higher comorbidity scores and mortality, but both groups had similar total comorbidities. Younger admissions exhibited longer length of stay with more procedures performed. Vascular anomalies (aneurysm 7.2 vs. 4.6% and arteriovenous malformation 5.9 vs. 0.8%) and behavioral risk factors (smoking 26.5 vs. 23.0%, alcohol abuse 6.7 vs. 4.6%, and substance use 13.5 vs. 2.9%) were more prevalent in younger admissions, while older patients had more cardiovascular comorbidities. All-cause 30-day readmission rates (13.1 vs. 13.0%) and 1-year cumulative risk of readmission (log-rank p value 0.7209) were similar. Readmissions in the younger cohort were primarily for neurological conditions, and those in the older cohort were for systemic conditions.

CONCLUSIONS

Adults <45 years with ICH had similar total comorbidities as older adults but more procedures, longer hospital stay, and more behavioral risk factors. Readmission rates were similar though reasons differed; younger patients were more for neurological reasons than for other systemic causes.

Trends in hospital readmissions in Multiple Sclerosis patients between 2009 and 2015

BACKGROUND

Readmission rate is an important healthcare quality metric and remains a problem in Multiple Sclerosis (MS) patients, nonetheless information about this issue is scarce. We present the first study to estimate hospital readmissions in a MS hospital-based European cohort.

METHODS

Retrospective cohort study of patients with at least one hospitalization with a primary discharge of MS from August 1, 2009 and July 31, 2015. The primary outcome was hospitalization within 30 days post-discharge (30-DR). The secondary outcomes included length of stay during index and readmission, total hospital readmissions during the study period, predictors and causes of readmission.

RESULTS

Forty-four (41.5%) patients had a hospital readmission during the six years of this study, 11.3% of them 30-DR, mainly due to infections (58.5%). The two most common comorbidities in these patients were neurogenic bladder (47.7%) and ischemic heart disease (18.1%). Progressive MS subtype was the main predictor of 30-DR, even after adjustment for therapy (OR: 6.29; p = 0.016), with an area under the curve of 0.73.

CONCLUSION

Progressive MS subtypes and "second-line drugs" carry a higher risk of hospital readmission soon after discharge. The impact and cost-effectiveness of strategies to lower readmission rates in MS should be the focus of upcoming studies.

Effect of nutritional interventions on discharged older patients: study protocol for a randomized controlled trial

Background

During hospitalization, many older patients are at nutritional risk or malnourished, and their nutritional condition is often further impaired during hospitalization. After discharge, a “nutrition gap” often occurs in which the patient does not receive enough nutrition to ensure an optimal recovery.

Methods

The study is a randomized controlled study ongoing over 112 days. At discharge, the intervention group receives guidance from a clinical dietitian, and an individualized nutrition plan is made. The dietitian will perform telephone follow-up after 4 and 30 days. It will also be possible for the participant, the participant’s relatives, or the participant’s municipality to contact the dietitian if nutritional questions arise. At the time of discharge, the intervention group will receive a package containing foods and drinks that will cover their nutritional needs on the first day after discharge. They will also receive a goodie bag containing samples of protein-rich, milk-based drinks. Data are collected on quality of life, appetite, physical function, dietary intake, weight, height, energy and protein needs, and experience of discharge and cooperation with the municipality. Information about nutrition status will be sent to the municipality so that the municipality can take over nutritional treatment. The control group receives a standard treatment.

Discussion

This study is the first to combine previously successful single nutritional interventions into a multimodal intervention whose aim is to obtain an effect on patient-related outcomes. We hope that the results will prove beneficial and help to ensure the cross-sector quality of nutritional support to older patients.

Trial registration

ClinicalTrials.gov, NCT03488329. April 5, 2018.

Electrolyte outpatient clinic at a local hospital - experience from diagnostics, treatment and follow-up

Background

Electrolyte imbalances (EI) are common among patients. Many patients have repeated hospitalizations with the same EI without being investigated and treated. We established an electrolyte outpatient clinic (EOC) to diagnose and treat patients with EI to improve symptoms and increase their quality of life (QoL). In addition, we also wanted to reduce the number of admissions with the same EI.

Methods

Uncontrolled before-after study reporting experiences from this outpatient clinic as a quality assurance project. From October 2010 to October 2015, doctors at our local hospital and general practitioners could refer adult patients with EI to the EOC. Ninety patients with EI were referred, of whom 60 were included. Medical history, clinical examination and laboratory tests were performed, and results registered. Admissions with the same EI were recorded 1 year before and 1 year after consultation at the EOC. Patients responded to a questionnaire, composed by the authors, about symptoms before the first consultation, as well as symptom and QoL improvement after the last consultation.

Results

Hyponatremia was the reason for referral in 45/60 patients. The total number of admissions with the same EI 1 year before the first consultation was 71, compared with 20 admissions 1 year after the last consultation. Improvement of symptoms was reported by 60% of patients, and 62% reported improvement in QoL.

Conclusions

An EOC may be an appropriate way to organize the assessment and treatment of patients with EI.

Is obesity a risk factor for readmission after acute myocardial infarction?

INTRODUCTION AND OBJECTIVES

Hospital readmissions are a major concern in terms of both cost and quality of care. The purpose of this study was to determine which patients were more likely to experience hospital readmissions after acute myocardial infarction in order to help develop more targeted programs and policies.

PATIENTS AND MATERIALS AND METHODS

The 2014 Nationwide Readmissions Database was used to calculate the national readmission rate by patient characteristics. All U.S. patients who presented to the hospital with acute myocardial infarction in 2014 and incurred a readmission were included in this analysis. The main outcome of interest was the rate of readmission by obesity. Obesity was measured using the comorbidity indicator found in the dataset. National secondary data of a sample of U.S. hospital discharges was used to measure hospital readmission rates. Bivariate analysis and logistic regression were used to determine if a significant relationship existed between readmissions and the patient characteristics. For this purpose odds ratio (OR) and 95% confidence interval has been calculated.

RESULTS

There were 11.66% hospital readmissions in the database. Non-obese adults were 21% less likely to be readmitted than obese adults. Non-obese patients were 21.2% less likely to be readmitted than obese patients (OR 0.788, CI 0.751-0.827, p-value <.0001). Obese patients with no insurance had significantly higher readmissions compared to obese Medicare patients.

CONCLUSIONS

The Hospital Readmissions Reduction Program has been effective at reducing hospital readmissions. However, greater focus needs to be placed on reducing hospital readmissions for patients with chronic conditions, especially obesity.

Use of psychiatric hospitals and social integration of patients with psychiatric disorders: a prospective cohort study in five European countries

PURPOSE

Long lengths of stay (LoS) in psychiatric hospitals or repeated admission may affect the social integration of patients with psychiatric disorders. So far, however, studies have been inconclusive. This study aimed to analyse whether long LoS or repeated admissions in psychiatric wards were associated in different ways with changes in the social integration of patients.

METHODS

Within a prospective cohort study, data were collected on 2181 patients with a main ICD-10 diagnosis of psychotic, affective, or anxiety disorder, hospitalised in the UK, Italy, Germany, Poland, and Belgium in 2015. Social integration was measured at baseline and 1 year after admission using the SIX index, which includes four dimensions: employment, housing, family situation, and friendship. Regression models were performed to test the association between LoS, the number of admissions, and the change in social integration over the study period, controlling for patients' characteristics (trial registration ISRCTN40256812).

RESULTS

A longer LoS was significantly associated with a decrease in social integration (β = - 0.23, 95%CI - 0.32 to - 0.14, p = 0.03), particularly regarding employment (OR = 2.21, 95%CI 1.18-3.24, p = 0.02), housing (OR = 3.45, 95%CI 1.74-5.16, p < 0.001), and family situation (OR = 1.94, 95%CI 1.10-2.78, p = 0.04). In contrast, repeated admissions were only associated with a decrease in friendship contacts (OR = 1.15, 95CI% 1.08-1.22, p = 0.03).

CONCLUSIONS

Results suggest that a longer hospital LoS is more strongly associated with a decrease in patients' social integration than repeated admissions. Special attention should be paid to helping patients to find and retain housing and employment while hospitalised for long periods.

The heterogeneous health state profiles of high-risk healthcare utilizers and their longitudinal hospital readmission and mortality patterns

BACKGROUND

High-risk patients are most vulnerable during transitions of care. Due to the high burden of resource allocation for such patients, we propose that segmentation of this heterogeneous population into distinct subgroups will enable improved healthcare resource planning. In this study, we segmented a high-risk population with the aim to identify and characterize a patient subgroup with the highest 30-day and 90-day hospital readmission and mortality.

METHODS

We extracted data from our transitional care program (TCP), a Hospital-to-Home program launched by the Singapore Ministry of Health, from June to November 2018. Latent class analysis (LCA) was used to determine the optimal number and characteristics of latent subgroups, assessed based on model fit and clinical interpretability. Regression analysis was performed to assess the association of class membership on 30- and 90-day all-cause readmission and mortality.

RESULTS

Among 752 patients, a 3-class best fit model was selected: Class 1 "Frail, cognitively impaired and physically dependent", Class 2 "Pre-frail, but largely physically independent" and Class 3 "Physically independent". The 3 classes have distinct demographics, medical and socioeconomic characteristics (p <  0.05), 30- and 90-day readmission (p <  0.05) and mortality (p <  0.01). Class 1 patients have the highest age-adjusted 90-day readmission (OR = 2.04, 95%CI: 1.21-3.46, p = 0.008), 30- (OR = 6.92, 95%CI: 1.76-27.21, p = 0.006) and 90-day mortality (OR = 11.51, 95%CI: 4.57-29.02, p <  0.001).

CONCLUSIONS

We identified a subgroup with the highest readmission and mortality risk amongst high-risk patients. We also found a lack of interventions in our TCP that specifically addresses increased frailty and poor cognition, which are prominent features in this subgroup. These findings will help to inform future program modifications and strengthen existing transitional healthcare structures currently utilized in this patient cohort.

Undiagnosed Obstructive Sleep Apnea as Predictor of 90-Day Readmission for Brain Tumor Patients

BACKGROUND

Previously undiagnosed obstructive sleep apnea (OSA) is a known contributor to negative postoperative outcomes. The STOP-Bang questionnaire is a screening tool for OSA that has been validated in both medical and surgical populations. The authors have previously studied this screening tool in a brain tumor population at 30 days. The present study seeks to investigate the effectiveness of this questionnaire, for predicting 90-day readmissions in a population of brain tumor patients with previously undiagnosed OSA.

METHODS

Included for analysis were all patients undergoing craniotomy for supratentorial neoplasm at a multihospital, single academic medical center. Data were collected from supratentorial craniotomy cases for which the patient was alive at 90 days after surgery (n = 238). Simple logistic regression analyses were used to assess the ability of the STOP-Bang questionnaire and subsequent single variables to accurately predict patient outcomes at 90 days.

RESULTS

The sample included 238 brain tumor admissions, of which 50% were female (n = 119). The average STOP-Bang score was 1.95 ± 1.24 (range 0-7). A 1-unit higher increase in STOP-Bang score accurately predicted 90-day readmissions (odds ratio [OR] = 1.65, P = 0.001), 30- to 90-day emergency department visits (OR = 1.85, P < 0.001), and 30- to 90-day reoperation (OR = 2.32, P < 0.001) with fair accuracy as confirmed by the receiver operating characteristic (C-statistic = 0.65-0.76). However, the STOP-Bang questionnaire did not correlate with home discharge (P = 0.315).

CONCLUSIONS

The results of this study suggest that undiagnosed OSA, as evaluated by the STOP-Bang questionnaire, is an effective predictor of readmission risk and health system utilization in a brain tumor craniotomy population with previously undiagnosed OSA.

Design of the patient navigator to Reduce Readmissions (PArTNER) study: A pragmatic clinical effectiveness trial

Previous work indicates the potential for community health workers and peer coaches serving as patient navigators to improve processes of care and health outcomes during care transitions, but have not been sufficiently tested to determine if such programs improve measures of patient experience in minority serving institutions. The objectives of the Patient Navigator to Reduce Readmissions (PArTNER) study was to: 1) conduct a pragmatic clinical effectiveness trial comparing a multi-faceted, stakeholder-supported Navigator intervention (in-person CHW visits in the hospital and after hospital discharge, plus telephone-based peer coaching) versus usual care on the experience of hospital-to-home care transitions in patients hospitalized with heart failure, pneumonia, chronic obstructive pulmonary disease, myocardial infarction, or sickle cell disease; 2) examine the effectiveness of the Navigator intervention in patient subgroups; and 3) understand the barriers and facilitators of successfully implementing the Navigator intervention across patient populations. The co-primary outcomes are the 30-day changes in: 1) Patient Reported Outcomes Measurement Information System (PROMIS) emotional distress-anxiety, and 2) PROMIS informational support. Secondary outcomes at 30 and 60 days include other PROMIS health measures and hospital readmissions. Innovative features of the PArTNER study include early and continuous engagement of patients, their caregivers, clinicians, health system administrators, and other stakeholders to inform the design and implementation of the Navigator intervention. In this report, we describe the design of the PArTNER study.

Evaluating the Connect with Pharmacy web-based intervention to reduce hospital readmission for older people

Background The patient transition from a hospital to a post-discharge healthcare setting has potential to disrupt continuity of medication management and increase the risk of harm. “Connect with Pharmacy” is a new electronic web-based transfer of care initiative employed by Leeds Teaching Hospitals NHS Trust. This allows the sharing of discharge information between the hospital and a patient’s chosen community pharmacy. Objective We investigated whether the timely sharing of discharge information with community pharmacies via “Connect with Pharmacy” reduced hospital readmission rates in older patients. Method To evaluate intervention efficacy, hospital admission data was retrospectively collected. For primary analysis, admission rates were tracked 6-months prior (baseline) and 6-months post-intervention. Secondary measures included effect on total length of stay if readmitted, emergency department attendance and duration, and impact of polypharmacy. Main outcome measure The rate of non-elective hospital readmissions, 6-months post-intervention. Results In the sample (n = 627 patients; Mean age = 81 years), emergency readmission rates following the intervention (M = 1.1, 95% CI [0.98, 1.22]) reduced by 16.16% relative to baseline (M = 1.31, 95% CI [1.21, 1.42]) (W = 54,725; p < 0.001). There was no reduction in total length of stay. Subsidiary analysis revealed a post-intervention reduction in number of days spent in hospital lasting more than three days (χ² = 13.37, df = 1, p < 0 .001). There were no statistically reliable differences in the remaining secondary measures. Conclusion The results showed a reduction in readmissions and potential post-intervention length of stay, indicating there may be further benefits for our older patients’ experiences and hospital flow.

Long-term outcomes among Medicare patients readmitted in the first year of hemodialysis: a retrospective cohort study

Background

Readmission within 30 days of hospital discharge is common and costly among end-stage renal disease (ESRD) patients. Little is known about long-term outcomes after readmission. We estimated the association between hospital admissions and readmissions in the first year of dialysis and outcomes in the second year.

Methods

Data on incident dialysis patients with Medicare coverage were obtained from the United States Renal Data System (USRDS). Readmission patterns were summarized as no admissions in the first year of dialysis (Admit-), at least one admission but no readmissions within 30 days (Admit+/Readmit-), and admissions with at least one readmission within 30 days (Admit+/Readmit+).We used Cox proportional hazards models to estimate the association between readmission pattern and mortality, hospitalization, and kidney transplantation, accounting for demographic and clinical covariates.

Results

Among the 128,593 Medicare ESRD patients included in the study, 18.5% were Admit+/Readmit+, 30.5% were Admit+/Readmit-, and 51.0% were Admit-. Readmit+/Admit+ patients had substantially higher long-term risk of mortality (HR = 3.32 (95% CI, 3.21–3.44)), hospitalization (HR = 4.46 (95% CI, 4.36–4.56)), and lower likelihood of kidney transplantation (HR = 0.52 (95% CI, 0.44–0.62)) compared to Admit- patients; these associations were stronger than those among Admit+/Readmit- patients.

Conclusions

Patients with readmissions in the first year of dialysis were at substantially higher risk of poor outcomes than either patients who had no admissions or patients who had hospital admissions but no readmissions. Identifying strategies to both prevent readmission and mitigate risk among patients who had a readmission may improve outcomes among this substantial, high-risk group of ESRD patients.

Electronic supplementary material

The online version of this article (10.1186/s12882-019-1473-0) contains supplementary material, which is available to authorized users.

Profiling the hospital-dependent patient in a large academic hospital: Observational study

BACKGROUND

In older patients with acute illness, a condition of "hospital-dependence" may arise: patients get adapted to the hospital care and, once discharged, may experience health status decline, requiring repeated readmissions despite appropriate treatments.

AIMS

The objective of this case-series study was to describe the characteristics of 118 patients (72 F) aged ≥75 (mean 83.7 ± 4.9) who were urgently admitted to our institution at least 4 times in 2015.

METHODS

For each patient and admission, data on multimorbidity (Cumulative Illness Rating Scale Comorbidity Score and Severity Index), frailty (Rockwood Clinical Frailty Scale), functional dependence, functional status, polypharmacy, length of stay and interval between admissions were extrapolated from clinical records. Mortality during the years 2015 and 2016 was assessed on the institutional database.

RESULTS

At the first admission, patients had a high burden of polypharmacy (median number of drugs 8.5, IQR 6-11) and multimorbidity (Comorbidity Score 15.8 ± 4.1, Severity Index 2.9 ± 1.1). However, most (55.5%) were fit or pre-frail according to Clinical Frailty Scale (score 1-4). At multivariate models, Severity Index was significantly correlated with the length of stay (β ± SE 2.23 ± 0.89, p = .01) and readmission interval (β ± SE -22.49 ± 9.27, p = .02). Significantly increasing trends of multimorbidity and disability occurred across admissions. By the end of 2016, 66% of patients had died. Frailty (RR 2.005, 95%CI 1.054-3.814, p = .007) and cancer were the only predictors of mortality.

CONCLUSIONS

Hospital-dependent patients had severe multimorbidity, but exhibited an unexpectedly low prevalence of frailty/disability at baseline, though increasing across admissions. Trends of frailty and multimorbidity are paramount for profiling the hospital-dependence risk.