A Novel Risk-Adjusted Metric to Compare Hospitals on Their Antibiotic Prescribing at Hospital Discharge.

BACKGROUND: Antibiotic overuse at hospital discharge is common, but there is no metric to evaluate hospital performance at this transition of care. We built a risk-adjusted metric for comparing hospitals on their overall post-discharge antibiotic use. METHODS: This was a retrospective study across all acute-care admissions within the Veterans Health Administration during 2018-2021. For patients discharged to home, we collected data on antibiotics and relevant covariates. We built a zero-inflated, negative, binomial mixed model with 2 random intercepts for each hospital to predict post-discharge antibiotic exposure and length of therapy (LOT). Data were split into training and testing sets to evaluate model performance using absolute error. Hospital performance was determined by the predicted random intercepts. RESULTS: 1 804 300 patient-admissions across 129 hospitals were included. Antibiotics were prescribed to 41.5% while hospitalized and 19.5% at discharge. Median LOT among those prescribed post-discharge antibiotics was 7 (IQR, 4-10) days. The predictive model detected post-discharge antibiotic use with fidelity, including accurate identification of any exposure (area under the precision-recall curve = 0.97) and reliable prediction of post-discharge LOT (mean absolute error = 1.48). Based on this model, 39 (30.2%) hospitals prescribed antibiotics less often than expected at discharge and used shorter LOT than expected. Twenty-eight (21.7%) hospitals prescribed antibiotics more often at discharge and used longer LOT. CONCLUSIONS: A model using electronically available data was able to predict antibiotic use prescribed at hospital discharge and showed that some hospitals were more successful in reducing antibiotic overuse at this transition of care. This metric may help hospitals identify opportunities for improved antibiotic stewardship at discharge.

A personalized protocol for prescribing opioids after cesarean delivery: leveraging the electronic medical record to reduce outpatient opioid prescriptions.

BACKGROUND: Although cesarean delivery is the most common surgery performed in the United States, prescribing practices for analgesia vary. Strategies to manage postpartum pain have mostly focused on the immediate postpartum period when patients are still admitted to the hospital. At discharge, most providers prescribe a fixed number of opioid tablets. Most patients do not use all the opioids that they are prescribed at hospital discharge. This leads to an excess of opioids in the community, which can ultimately lead to misuse and diversion. OBJECTIVE: This study aimed to determine whether a transition from universal opioid prescribing to a personalized, patient-specific protocol decreases morphine milligram equivalents prescribed at hospital discharge after cesarean delivery while adequately controlling pain. STUDY DESIGN: This was a prospective cohort study of patients undergoing cesarean delivery before and after the implementation of a personalized opioid-prescribing practice at the time of hospital discharge. Each patient was prescribed scheduled ibuprofen and acetaminophen, with a prescription for oxycodone tablets equal to 5 times the morphine milligram equivalents used in the 24 hours before discharge, calculated via an electronic order set. The previous traditional cohorts were routinely prescribed 30 tablets of acetaminophen-codeine 300/30 mg. The primary outcome was morphine milligram equivalents prescribed at discharge. A hotline to address pain control issues after discharge was established, and calls, emergency department visits, and readmissions were examined. Statistical analyses was performed using chi-square and Wilcoxon rank-sum test, with a P value of <.05 considered statistically significant. RESULTS: Overall, 412 patients underwent cesarean delivery in the 6 weeks after initiation of the personalized prescribing protocol and were compared with 367 patients before the change. The median morphine milligram equivalents prescribed at discharge was lower with personalized prescribing (37.5 [interquartile range, 0-75] vs 135 [interquartile range, 135-135]; P<.001). Moreover, 176 patients (43%) were not prescribed opioids at discharge, which was a substantial change as all 367 patients in the traditional cohort received opioids at discharge (P<.001). Of note, 9 hotline phone calls were received; none required additional opioids after a 24-hour trial of scheduled ibuprofen, which none had taken before the call. In addition, 11 patients (2.7%) presented to the emergency department for pain evaluation, of which none required readmission or an outpatient prescription of opioids. CONCLUSION: A personalized protocol for opioid prescriptions after cesarean delivery decreased the total morphine milligram equivalents and the number of opioid tablets at discharge, without hospital readmissions or need for rescue opioid prescriptions after discharge. Opioids released into our community will be reduced by more than 90,000 tablets per year, without demonstrable adverse effect.

Current Status and Influencing Factors of Readiness for Hospital Discharge of Lung Cancer Patients Receiving ERAS-Guided Postoperative Management.

OBJECTIVE: This study ascertained current status and influencing factors of readiness for hospital discharge (RHD) of lung cancer (LC) patients with enhanced recovery after surgery (ERAS) concept-guided postoperative management. METHODS: This study prospectively and consecutively included 217 LC patients who underwent whole-course ERAS concept-guided postoperative management at the Department of Thoracic Surgery of Guangzhou Institute of Cancer Research, the Affiliated Cancer Hospital, Guangzhou Medical University from November 2023 to April 2024. RHD, quality of discharge teaching (QDT), and social support (SS) were evaluated using RHDS, QDTS, and SSRS, followed by correlation analyses of RHD with the other 2 factors. The clinical baseline and pathological data were compared between the high and low RHD groups, and the characteristics showing statistical significance were assigned as independent variables for regression analysis with RHD as the dependent variable. RESULTS: RHD, QDT, and SS were above average among LC patients with ERAS concept-guided postoperative management, and RHD was positively correlated with both QDT and SS. Age, education level, self-care ability, number of admissions, and presence of drainage tubes were independent influence factors for RHD of LC patients with ERAS concept-guided postoperative management. CONCLUSION: In LC patients with ERAS concept-guided postoperative management, RHD may be improved by increasing QDT and SS and intervened by factors such as age, education level, self-care ability, number of admissions, and presence of drainage tubes.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States.

BACKGROUND: Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important. METHODS: We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season. RESULTS: For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods. CONCLUSIONS: Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

A predictive model for readmission within 1-year post-discharge in patients with schizophrenia.

BACKGROUND: Schizophrenia is a pervasive and severe mental disorder characterized by significant disability and high rates of recurrence. The persistently high rates of readmission after discharge present a serious challenge and source of stress in treating this population. Early identification of this risk is critical for implementing targeted interventions. The present study aimed to develop an easy-to-use predictive instrument for identifying the risk of readmission within 1-year post-discharge among schizophrenia patients in China. METHODS: A prediction model, based on static factors, was developed using data from 247 schizophrenia inpatients admitted to the Mental Health Center in Wuxi, China, from July 1 to December 31, 2020. For internal validation, an additional 106 patients were included. Multivariate Cox regression was applied to identify independent predictors and to create a nomogram for predicting the likelihood of readmission within 1-year post-discharge. The model's performance in terms of discrimination and calibration was evaluated using bootstrapping with 1000 resamples. RESULTS: Multivariate cox regression demonstrated that involuntary admission (adjusted hazard ratio [aHR] 4.35, 95% confidence interval [CI] 2.13-8.86), repeat admissions (aHR 3.49, 95% CI 2.08-5.85), the prescription of antipsychotic polypharmacy (aHR 2.16, 95% CI 1.34-3.48), and a course of disease ≥ 20 years (aHR 1.80, 95% CI 1.04-3.12) were independent predictors for the readmission of schizophrenia patients within 1-year post-discharge. The area under the curve (AUC) and concordance index (C-index) of the nomogram constructed from these four factors were 0.820 and 0.780 in the training set, and 0.846 and 0.796 for the validation set, respectively. Furthermore, the calibration curves of the nomogram for both the training and validation sets closely approximated the ideal diagonal line. Additionally, decision curve analyses (DCAs) demonstrated a significantly better net benefit with this model. CONCLUSIONS: A nomogram, developed using pre-discharge static factors, was designed to predict the likelihood of readmission within 1-year post-discharge for patients with schizophrenia. This tool may offer clinicians an accurate and effective way for the timely prediction and early management of psychiatric readmissions.

'You're Just Thinking About Going Home': Exploring Person-Centred Medication Communication With Older Patients at Hospital Discharge.

BACKGROUND: The hospital discharge process poses significant safety risks for older patients due to complexities in communication and coordination among stakeholders, leading to potential drug-related problems post-discharge. Adopting a person-centred care (PCC) approach in medication communication by healthcare professionals (HCPs) is crucial to ensure positive health outcomes. This study aimed to explore the practice of PCC in medication communication between older patients and HCPs during the hospital discharge process. METHODS: We conducted a qualitative study using non-participatory direct observations of patient-HCP consultations during hospital discharge, followed by semi-structured interviews with observed patients and, when applicable, their informal caregivers. Data collection occurred from October 2020 to May 2021 at two Swedish hospitals. We gathered data using an observational form and audio-recorded all consultations and interviews. The data were analysed thematically using the systematic text condensation method. RESULTS: Twenty patients were included (median age: 81 years [range: 65-94]; 9 female) in observations and 13 of them participated in interviews. Two patients were accompanied by an informal caregiver during the interviews. Three main themes were identified: (1) The impact of traditional authoritarian structures, depicts power dynamics between patients and their HCPs, showing how traditional structures influence the practice of PCC in medication communication during hospital discharge; (2) Consultation timing and mode not on patients' terms, describes suboptimal times and settings for consultations, along with the use of complex language that hinders effective communication; and (3) Discrepancy in expectations of self-care ability, illustrates a mismatch between the self-care guidance provided by HCPs during hospital discharge and the actual needs and preferences of patients and informal caregivers. CONCLUSION: Medication communication between older patients and HCPs during hospital discharge is frequently inconsistent with the practice of PCC. Not only must HCPs improve their communication strategies, but patients and their informal caregivers should also be better prepared for discharge communication and encouraged to participate in their care. This involvement would give them relevant knowledge and tailor communication to their individual needs, preventing problems in managing their medications after discharge. PATIENT OR PUBLIC CONTRIBUTION: An advisory group of six patients and/or informal caregiver contributors provided input on the study design, edited the consent forms, and helped develop the interview guide.

The impact of discharge letter content on unplanned hospital readmissions within 30 and 90 days in older adults with chronic illness - a mixed methods study.

BACKGROUND: Care transitions are high-risk processes, especially for people with complex or chronic illness. Discharge letters are an opportunity to provide written information to improve patients' self-management after discharge. The aim of this study is to determine the impact of discharge letter content on unplanned hospital readmissions and self-rated quality of care transitions among patients 60 years of age or older with chronic illness. METHODS: The study had a convergent mixed methods design. Patients with chronic obstructive pulmonary disease or congestive heart failure were recruited from two hospitals in Region Stockholm if they were living at home and Swedish-speaking. Patients with dementia or cognitive impairment, or a "do not resuscitate" statement in their medical record were excluded. Discharge letters from 136 patients recruited to a randomised controlled trial were coded using an assessment matrix and deductive content analysis. The assessment matrix was based on a literature review performed to identify key elements in discharge letters that facilitate a safe care transition to home. The coded key elements were transformed into a quantitative variable of "SAFE-D score". Bivariate correlations between SAFE-D score and quality of care transition as well as unplanned readmissions within 30 and 90 days were calculated. Lastly, a multivariable Cox proportional hazards model was used to investigate associations between SAFE-D score and time to readmission. RESULTS: All discharge letters contained at least five of eleven key elements. In less than two per cent of the discharge letters, all eleven key elements were present. Neither SAFE-D score, nor single key elements correlated with 30-day or 90-day readmission rate. SAFE-D score was not associated with time to readmission when adjusted for a range of patient characteristics and self-rated quality of care transitions. CONCLUSIONS: While written summaries play a role, they may not be sufficient on their own to ensure safe care transitions and effective self-care management post-discharge. TRIAL REGISTRATION: Clinical Trials. giv, NCT02823795, 01/09/2016.

Factors affecting the readiness for hospital discharge of initially treated pulmonary tuberculosis patients in China: a phenomenological study.

BACKGROUND: Despite readiness for hospital discharge widespread popularity since readiness for hospital discharge introduction in 1979 and extensive study, readiness for hospital discharge among pulmonary tuberculosis (PTB) patients has not yet been investigated. Moreover, the factors influencing this process remain unclear. OBJECTIVE: The objective of this study was to investigate the factors influencing readiness for hospital discharge in initially treated PTB patients using the capability, opportunity, motivation-behavior (COM-B) model. METHODS: This phenomenological study was conducted from December 2023 to March 2024. Face-to-face individual interviews were conducted with 18 initially treated patients with PTB according to a semistructured interview guide developed on the basis of the COM-B model. The interview data were subjected to analysis using NVivo 14 software and Colaizzi's method. RESULTS: As a result, 6 themes and 14 subthemes were identified. Physical capability for readiness for hospital discharge (subthemes included poor health status, early acquisition of adequate knowledge about PTB, inadequate knowledge about readiness for hospital discharge), psychological capability for readiness for hospital discharge(subthemes included false perceptions about readiness for hospital discharge, high treatment adherence), physical opportunity for readiness for hospital discharge (subthemes included high continuity of transition healthcare, insufficient financial support, insufficient informational support), social opportunity for readiness for hospital discharge (subthemes included stigmatization, inadequate emotional support), reflective motivation for readiness for hospital discharge (subthemes included lack of reflection on coping with difficulties, intention to develop a readiness for hospital discharge plan), and automatic motivation for readiness for hospital discharge (subthemes included strong desire to be cured, negative emotions). CONCLUSION: We established factors related to readiness for hospital discharge in initially treated PTB patients in terms of capability, opportunity and motivation, which can inform the future development of readiness for hospital discharge plans. To improve patients' readiness for hospital discharge, patients need to be motivated to plan and desire readiness for hospital discharge, patients' knowledge and treatment adherence should be improved, and patients' transition healthcare continuity and emotional support should be focused on. Moreover, the quality of readiness for hospital discharge and discharge education should be assessed in a timely manner to identify impeding factors and provide interventions.

Predictors of length of hospital stay after pediatric Ebstein anomaly corrective surgery: a retrospective cohort study.

BACKGROUND: The remarkable advancements in surgical techniques over recent years have shifted the clinical focus from merely reducing mortality to enhancing the quality of postoperative recovery. The duration of a patient's hospital stay serves as a crucial indicator in evaluating postoperative recovery and surgical outcomes. This study aims to identify predictors of the length of hospital stay for children who have undergone corrective surgery for Ebstein Anomaly (EA). METHODS: We conducted a retrospective cohort study on children (under 18 years of age) diagnosed with EA who were admitted for corrective surgery between January 2009 and November 2021 at Fuwai Hospital. The primary outcome was the Time to Hospital Discharge (THD). Cox proportional hazard models were utilized to identify predictors of THD. In the context of time-to-event analysis, discharge was considered an event. In cases where death occurred before discharge, it was defined as an extended THD, input as 100 days (exceeding the longest observed THD), and considered as a non-event. RESULTS: A total of 270 children were included in this study, out of which three died in the hospital. Following the Cox proportional hazard analysis, six predictors of THD were identified. The hazard ratios and corresponding 95% confidence intervals were as follows: age, 1.030(1.005,1.055); C/R > 0.65, 0.507(0.364,0.707); Carpentier type C or D, 0.578(0.429,0.779); CPB time, 0.995(0.991,0.998); dexamethasone, 1.373(1.051,1.795); and transfusion, 0.680(0.529,0.875). The children were categorized into three groups based on the quartile of THD. Compared to children in the ≤ 6 days group, those in the ≥ 11 days group were associated with a higher incidence of adverse outcomes. Additionally, the duration of mechanical ventilation and ICU stay, as well as hospital costs, were significantly higher in this group. CONCLUSION: We identified six predictors of THD for children undergoing corrective surgery for EA. Clinicians can utilize these variables to optimize perioperative management strategies, reduce adverse complications, improve postoperative recovery, and reduce unnecessary medical expenses.

Measuring the continuing care needs of inpatients in rural China.

BACKGROUND: International experience shows that the suitability of a high-performance healthcare system for its given purposes is reflected in its ability to provide a continuum of services that match the changing health status of the given population. Although many low- and middle-income countries have sought to bring movement away from hospital-centered and towards patient-centered healthcare, such efforts have often had poor results, and one of the major reasons for this is the inability to accurately identify which inpatients need continuing care and what kind of continuing of care is needed. OBJECTIVES: To measure and assess the continuing care needs of discharged patients and its influencing factors in rural China. METHODS: Data were obtained from the hospital database of Medical Center M in County Z from May to July 2022. County Z is a county of 1 million people in central China. The database includes basic patient information, disease-related information, and information on readiness for hospital discharge. Factors related to the need for continuing care were included in the analysis. The Readiness for Hospital Discharge Scale was used to assess the need for continuing care. The statistical data are expressed in terms of both frequency and composition ratio. Finally, linear regression was used to analyze the factors influencing the need for continuing care. RESULTS: The analysis included a total of 3,791 patients, 123 of whom (3.25%) had continuing nursing needs. The need of continuing nursing was related to patients' age group, mode of admission, occupation and major diagnostic categories (P < 0.05). CONCLUSIONS: Developing continuing care is an important initiative for bridging the fragmentation of health services, and an appropriate supply system for continuing care, interconnected with inpatient services, should be established in rural areas in China as soon as possible. And provide more appropriate care for patients in need.

Navigating outpatient care of patients with type 2 diabetes after hospital discharge - a qualitative longitudinal study.

BACKGROUND: The transition from hospital to outpatient care is a particularly vulnerable period for patients as they move from regular health monitoring to self-management. This study aimed to map and investigate the journey of patients with polymorbidities, including type 2 diabetes (T2D), in the 2 months following hospital discharge and examine patients' encounters with healthcare professionals (HCPs). METHODS: Patients discharged with T2D and at least two other comorbidities were recruited during hospitalization. This qualitative longitudinal study consisted of four semi-structured interviews per participant conducted from discharge up to 2 months after discharge. The interviews were based on a guide, transcribed verbatim, and thematically analyzed. Patient journeys through the healthcare system were represented using the patient journey mapping methodology. RESULTS: Seventy-five interviews with 21 participants were conducted from October 2020 to July 2021. The participants had a median of 11 encounters (min-max: 6-28) with HCPs. The patient journey was categorized into six key steps: hospitalization, discharge, dispensing prescribed medications by the community pharmacist, follow-up calls, the first medical appointment, and outpatient care. CONCLUSIONS: The outpatient journey in the 2 months following discharge is a complex and adaptive process. Despite the active role of numerous HCPs, navigation in outpatient care after discharge relies heavily on the involvement and responsibilities of patients. Preparation for discharge, post-hospitalization follow-up, and the first visit to the pharmacy and general practitioner are key moments for carefully considering patient care. Our findings underline the need for clarified roles and a standardized approach to discharge planning and post-discharge care in partnership with patients, family caregivers, and all stakeholders involved.

Evaluation of the nurse-assisted eHealth intervention 'eHealth@Hospital-2-Home' on self-care by patients with heart failure and colorectal cancer post-hospital discharge: protocol for a randomised controlled trial.

BACKGROUND: Patients with heart failure (HF) and colorectal cancer (CRC) are prone to comorbidity, a high rate of readmission, and complex healthcare needs. Self-care for people with HF and CRC after hospitalisation can be challenging, and patients may leave the hospital unprepared to self-manage their disease at home. eHealth solutions may be a beneficial tool to engage patients in self-care. METHODS: A randomised controlled trial with an embedded evaluation of intervention engagement and cost-effectiveness will be conducted to investigate the effect of eHealth intervention after hospital discharge on the self-efficacy of self-care. Eligible patients with HF or CRC will be recruited before discharge from two Norwegian university hospitals. The intervention group will use a nurse-assisted intervention-eHealth@Hospital-2-Home-for six weeks. The intervention includes remote monitoring of vital signs; patients' self-reports of symptoms, health and well-being; secure messaging between patients and hospital-based nurse navigators; and access to specific HF and CRC health-related information. The control group will receive routine care. Data collection will take place before the intervention (baseline), at the end of the intervention (Post-1), and at six months (Post-2). The primary outcome will be self-efficacy in self-care. The secondary outcomes will include measures of burden of treatment, health-related quality of life and 30- and 90-day readmissions. Sub-study analyses are planned in the HF patient population with primary outcomes of self-care behaviour and secondary outcomes of medication adherence, and readmission at 30 days, 90 days and 6 months. Patients' and nurse navigators' engagement and experiences with the eHealth intervention and cost-effectiveness will be investigated. Data will be analysed according to intention-to-treat principles. Qualitative data will be analysed using thematic analysis. DISCUSSION: This protocol will examine the effects of the eHealth@ Hospital-2-Home intervention on self-care in two prevalent patient groups, HF and CRC. It will allow the exploration of a generic framework for an eHealth intervention after hospital discharge, which could be adapted to other patient groups, upscaled, and implemented into clinical practice. TRIAL REGISTRATION: Clinical trials.gov (ID 301472).

Effect of integrated medicines management on quality of discharge medication information - a secondary endpoint in a randomized controlled trial.

BACKGROUND: High-quality discharge information is important to promote patient safety when patients are transferred from hospital to primary care. Patients with multiple long-term conditions are especially vulnerable to insufficient transfer of medication information, as they use many medications and have complex interactions with the healthcare services. The aim of this study was to investigate the effect of integrated medicines management provided to hospitalized multimorbid patients on the quality of the discharge medication information. METHODS: Multimorbid patients ≥18 years, using a minimum of four regular medications from a minimum of two therapeutic medication classes were recruited from the Internal Medicine ward, Oslo University Hospital, Norway, from August 2014 to March 2016 and randomly assigned, 1:1, to the intervention or control group. Intervention patients received integrated medicines management throughout the hospital stay. Control patients received standard care. This paper reports the results of a pre-specified secondary endpoint analysis of a randomized controlled trial; the difference between the intervention and control group in the quality of discharge medication information. RESULTS: The analysis population comprised 384 patients. Integrated medicines management improved the discharge summary quality score of the medication information from 5.8 ± 1.5 to 8.6 ± 2.6 (mean difference 2.7, 95% CI 2.3-3.2, p < 0.001). In total 171 intervention patients (89%) received a patient discharge information letter, compared to 66 control patients (35%), p < 0.001. The quality score of the medication information in the patient discharge information letter was improved from 6.0 ± 1.8 in the control group to 10.0 ± 1.3 in the intervention group (mean difference 4.0, 95% CI 3.6-4.4, p < 0.001). CONCLUSION: Integrated medicines management delivered to multimorbid patients during a hospital stay improved the quality of the medication information in discharge summaries as well as patient discharge information letters and ensured that a discharge information letter in lay language was prepared for almost all patients who were involved in the management of their medications after discharge.

Using a severity threshold to improve occupational injury surveillance: Assessment of a severe traumatic injury-based occupational health indicator across the International Classification of Diseases lexicon transition.

BACKGROUND: Traumatic injury is a leading cause of death and disability among US workers. Severe injuries are less subject to systematic ascertainment bias related to factors such as reporting barriers, inpatient admission criteria, and workers' compensation coverage. A state-based occupational health indicator (OHI #22) was initiated in 2012 to track work-related severe traumatic injury hospitalizations. After 2015, OHI #22 was reformulated to account for the transition from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) to ICD-10-CM. This study describes rates and trends in OHI #22, alongside corresponding metrics for all work-related hospitalizations. METHODS: Seventeen states used hospital discharge data to calculate estimates for calendar years 2012-2019. State-panel fixed-effects regression was used to model linear trends in annual work-related hospitalization rates, OHI #22 rates, and the proportion of work-related hospitalizations resulting from severe injuries. Models included calendar year and pre- to post-ICD-10-CM transition. RESULTS: Work-related hospitalization rates showed a decreasing monotonic trend, with no significant change associated with the ICD-10-CM transition. In contrast, OHI #22 rates showed a monotonic increasing trend from 2012 to 2014, then a significant 50% drop, returning to a near-monotonic increasing trend from 2016 to 2019. On average, OHI #22 accounted for 12.9% of work-related hospitalizations before the ICD-10-CM transition, versus 9.1% post-transition. CONCLUSIONS: Although hospital discharge data suggest decreasing work-related hospitalizations over time, work-related severe traumatic injury hospitalizations are apparently increasing. OHI #22 contributes meaningfully to state occupational health surveillance efforts by reducing the impact of factors that differentially obscure minor injuries; however, OHI #22 trend estimates must account for the ICD-10-CM transition-associated structural break in 2015.

Mediating role of care partner burden among dementia care partners during post-hospital transition.

OBJECTIVES: This study examined the mediating role of care partner burden on the relationship between patient clinical factors (i.e. cognition, physical function, and behavioral and psychological symptoms of dementia [BPSD]) and care partner mental health (i.e. anxiety and depression) among dementia care partners at hospital discharge. METHOD: The sample consisted of 431 patient and care partner dyads enrolled in the Family centered Function-focused Care (Fam-FFC) study; ClinicalTrials.gov identifier NCT03046121. Mediation analyses were conducted to test the role of care partner burden on the associations between patient clinical factors, and care partner anxiety and depression. RESULTS: Mediation models demonstrated that care partner burden partially mediated the relationship between patient physical function and care partner anxiety and depression, as well as patient BPSD and care partner anxiety and depression. CONCLUSION: Findings highlight the need for clinicians and service providers to implement comprehensive strategies that address both patient clinical factors (i.e. physical function and BPSD) and care partner burden, to optimize care partner mental health outcomes during post-hospital transition.

Relationships Between Quality of Discharge Teaching, Readiness for Hospital Discharge, Self-Efficacy and Self-Management in Patients With First-Episode Stroke: A Cross-Sectional Study.

AIMS: The study investigated the influence of quality of discharge teaching (QDT) on readiness for hospital discharge (RHD) and pathways involved in patients with first-episode stroke, aiming to provide a theoretical framework for enhancing RHD levels and reducing readmission rates. DESIGN: Cross-sectional study. METHODS: A total of 372 inpatients completed the Quality of Discharge Teaching Scale, Readiness for Hospital Discharge Scale, Chronic Disease Self-efficacy Scale and Southampton Stroke Self-Management Questionnaire. Structural equation modelling and Pearson's correlation analysis were utilised to elucidate relationships and action pathways among these variables. RESULTS: The correlation analysis demonstrated significant positive pairwise correlations between QDT, RHD, self-efficacy and self-management (r = 0.376-0.678, p < 0.01). The final model exhibited a good fit with the following indices: χ2/df = 3.286, RMSEA = 0.078, SRMR = 0.0303, GFI = 0.984, AGFI = 0.926, CFI = 0.991 and TLI = 0.970. The impact of QDT on RHD in patients with first-episode stroke was observed through one direct and three indirect pathways: (1) QDT exerted a direct influence on RHD (p < 0.001); (2) QDT indirectly influenced RHD via self-efficacy (p < 0.001); (3) QDT indirectly affected RHD through self-management (p < 0.001); and (4) QDT had an indirect effect on RHD via both self-efficacy and self-management (p < 0.05). CONCLUSION: QDT was found to directly influence RHD in patients with first-episode stroke and also exerted indirect effects through self-efficacy and self-management, either independently or in combination. Early screening of RHD levels in patients before discharge is recommended, along with the enhancement of QDT through the development of tailored guidance plans according to different disease stages, ultimately improving RHD levels and facilitating a safer transition from hospital to home or community. RELEVANCE TO CLINICAL PRACTICE: Healthcare professionals should assess both QDT and RHD levels to provide targeted interventions. The establishment of transitional care teams and implementation of long-term poststroke management are essential for reducing stroke recurrence and mortality rates.

Readiness for hospital discharge and its association with post-discharge outcomes among oesophageal cancer patients after oesophagectomy: A prospective observational study.

AIM: To examine the level and influencing factors of discharge readiness among patients with oesophageal cancer following oesophagectomy and to explore its association with post-discharge outcomes (post-discharge coping difficulty and unplanned readmission). BACKGROUND: Oesophageal cancer is common and usually treated via oesophagectomy in China. The assessment of patient's discharge readiness gradually attracts attention as patients tend to be discharged more quickly. DESIGN: Prospective observational study. The STROBE statement was followed. METHODS: In total, 154 participants with oesophageal cancer after oesophagectomy were recruited in a tertiary cancer centre in Southern China from July 2019 to January 2020. The participants completed a demographic and disease-related questionnaire, the Quality of Discharge Teaching Scale and Readiness for Hospital Discharge Scale before discharge. Post-discharge outcomes were investigated on the 21st day (post-discharge coping difficulty) and 30th day (unplanned readmission) after discharge separately. Multiple linear regressions were used for statistical analysis. RESULTS: The mean scores of discharge readiness and quality of discharge teaching were (154.02 ± 31.58) and (138.20 ± 24.20) respectively. The quality of discharge teaching, self-care ability, dysphagia and primary caregiver mainly influenced patient's discharge readiness and explained 63.0% of the variance. The low discharge readiness could predict more risk of post-discharge coping difficulty (r = -0.729, p < 0.01) and unplanned readmission (t = -2.721, p < 0.01). CONCLUSIONS: Discharge readiness among patients with oesophageal cancer following oesophagectomy is influenced by various factors, especially the quality of discharge teaching. A high discharge readiness corresponds to good post-discharge outcomes. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Healthcare professionals should improve the discharge readiness by constructing high-quality discharge teaching, cultivating patients' self-care ability, mobilizing family participation and alleviating dysphagia to decrease adverse post-discharge outcomes among patients with oesophageal cancer. PATIENTS OR PUBLIC CONTRIBUTION: Patients with oesophageal cancer after oesophagectomy who met the inclusion criteria were recruited.

Machine learning prediction of hospital discharge disposition for inpatients with acute ischemic stroke following mechanical thrombectomy in the United States.

BACKGROUND AND PURPOSE: Predicting patient recovery and discharge disposition following mechanical thrombectomy remains a challenge in patients with ischemic stroke. Machine learning offers a promising prognostication approach assisting in personalized post-thrombectomy care plans and resource allocation. As a large national database, National Inpatient Sample (NIS), contain valuable insights amenable to data-mining. The study aimed to develop and evaluate ML models predicting hospital discharge disposition with a focus on demographic, socioeconomic and hospital characteristics. MATERIALS AND METHODS: The NIS dataset (2006-2019) was used, including 4956 patients diagnosed with ischemic stroke who underwent thrombectomy. Demographics, hospital characteristics, and Elixhauser comorbidity indices were recorded. Feature extraction, processing, and selection were performed using Python, with Maximum Relevance - Minimum Redundancy (MRMR) applied for dimensionality reduction. ML models were developed and benchmarked prior to interpretation of the best model using Shapley Additive exPlanations (SHAP). RESULTS: The multilayer perceptron model outperformed others and achieved an AUROC of 0.81, accuracy of 77 %, F1-score of 0.48, precision of 0.64, and recall of 0.54. SHAP analysis identified the most important features for predicting discharge disposition as dysphagia and dysarthria, NIHSS, age, primary payer (Medicare), cerebral edema, fluid and electrolyte disorders, complicated hypertension, primary payer (private insurance), intracranial hemorrhage, and thrombectomy alone. CONCLUSION: Machine learning modeling of NIS database shows potential in predicting hospital discharge disposition for inpatients with acute ischemic stroke following mechanical thrombectomy in the NIS database. Insights gained from SHAP interpretation can inform targeted interventions and care plans, ultimately enhancing patient outcomes and resource allocation.

Preparing safe discharge in a complex practice: A qualitative study of nurses' approach to patients with COPD's hospital discharge from two pulmonary medicinal wards.

INTRODUCTION: It remains unclear why 17% of patients with acute exacerbations of chronic obstructive pulmonary disease (COPD) treated in Danish hospitals are readmitted within 30 days. Hospital discharge is multifaceted. However, the preparation process and nurses' efforts may be essential in ensuring a successful discharge. AIM: To explore the process of preparing discharge for patients with COPD in a hospital setting. METHOD: Using constructivist grounded theory, we observed 11 nurses' work at two pulmonary medical wards using participant observation. Data collection and analysis were conducted using a constant comparative process encompassing three phases: initial, focused and theoretical. RESULTS: We identified important perspectives influencing nurses when patients with COPD are discharged from two pulmonary medical wards. We generated a substantial theory of how nurses integrate various perspectives into their handling of hospital discharge. The theory contains three discharge approaches: co-creating, hesitating and socialising. The co-creating approach focuses on patient and relative involvement and systematic task solution, embedded in a biopsychosocial process, aiming to achieve a safe and sustainable discharge. In contrast, the hesitating approach focuses on discharging patients in line with system requirements and colleagues' expectations. Finally, the socialising approach focuses on creating a pleasant discharge experience for patients and colleagues alike. CONCLUSION: This study illuminates three distinct approaches adopted by nurses when discharging a patient with COPD. The co-creating process encompasses patient involvement and systematic task resolution, incorporating a biopsychosocial process. In contrast, the other approaches are more limited in scope: the hesitating approach aims for harmony and collegial consensus, while the socialising approach focuses on ensuring a pleasant discharge experience for everyone. Nurses should therefore be mindful of the approach they adopt and the values associated with it in order to optimise their management of hospital discharge processes.

Optimising Transitional Care Following a Heart Failure Hospitalisation in Australia.

Hospitalisations for heart failure (HF) are associated with high rates of readmission and death, the most vulnerable period being within the first few weeks post-hospital discharge. Effective transition of care from hospital to community settings for patients with HF can help reduce readmission and mortality over the vulnerable period, and improve long-term outcomes for patients, their family or carers, and the healthcare system. Planning and communication underpin a seamless transition of care, by ensuring that the changes to patients' management initiated in hospital continue to be implemented following discharge and in the long term. This evidence-based guide, developed by a multidisciplinary group of Australian experts in HF, discusses best practice for achieving appropriate and effective transition of patients hospitalised with HF to community care in the Australian setting. It provides guidance on key factors to address before and after hospital discharge, as well as practical tools that can be used to facilitate a smooth transition of care.