Short-term Care Research Articles

Association of pain management and positive expectations with psychological distress and spiritual well‑being among terminally ill cancer patients admitted to a palliative care unit

BackgroundAlthough palliation of psycho-spiritual distress is of great importance in terminally ill cancer patients, there is a little information about screening patients who benefit from palliative care and identifying the cancer care targets. This study explored the relationship of pain management and positive expectations with depression, anxiety and spiritual well-being (SWB) in terminal cancer patients admitted to a palliative care unit.MethodsEighty-four terminal cancer inpatients were recruited from the Hospice Ward, Shengjing Hospital of China Medical University. Optimism and general self-efficacy (GSE) were evaluated at admission. Patients completed self-report questionnaires on SWB, depression, anxiety and pain both on admission and one week later. The repeated designed analysis of variance was used to explore the correlates of depression, anxiety and SWB (meaning, peace, faith).ResultsIn our sample, only cancer pain diminished significantly one week later. For depression (p = 0.041) and faith (p = 0.013), there was a significant pain group (relieved vs. not relieved) × time interaction effect, such that those with satisfied pain control experienced the improved psycho-spiritual outcomes at 1 week. The relationship between positive expectations, peace and faith was also statistically significant, indicating that the improvement of peace or faith was significant in the low group of optimism and GSE.ConclusionsOur findings indicated that pain management lied at the center of depression and SWB, meaning that effective pain management may reduce depression, and improve SWB among terminal cancer patients. Moreover, positive expectations, especially for optimism, may be the new target for SWB-related intervention research. Palliative care nurse should require the identification of terminal cancer patients who may more benefit from short-term palliative care, and target them with effective cancer care.

Machine Learning Models Using Routinely Collected Clinical Data Offer Robust and Interpretable Predictions of 90-Day Unplanned Acute Care Use for Cancer Immunotherapy Patients.

Clinical management of patients receiving immune checkpoint inhibitors (ICIs) could be informed using accurate predictive tools to identify patients at risk of short-term acute care utilization (ACU). We used routinely collected data to develop and assess machine learning (ML) algorithms to predict unplanned ACU within 90 days of ICI treatment initiation. We used aggregated electronic health record data from 7,960 patients receiving ICI treatments to train and assess eight ML algorithms. We developed the models using pre-SARS-COV-19 COVID-19 data generated between January 2016 and February 2020. We validated our algorithms using data collected between March 2020 and June 2022 (peri-COVID-19 sample). We assessed performance using area under the receiver operating characteristic curves (AUROC), sensitivity, specificity, and calibration plots. We derived intuitive explanations of predictions using variable importance and Shapley additive explanation analyses. We assessed the marginal performance of ML models compared with that of univariate and multivariate logistic regression (LR) models. Most algorithms significantly outperformed the univariate and multivariate LR models. The extreme gradient boosting trees (XGBT) algorithm demonstrated the best overall performance (AUROC, 0.70; sensitivity, 0.53; specificity, 0.74) on the peri-COVID-19 sample. The algorithm performance was stable across both pre- and peri-COVID-19 samples, as well as ICI regimen and cancer groups. Type of ICI agents, oxygen saturation, diastolic blood pressure, albumin level, platelet count, immature granulocytes, absolute monocyte, chloride level, red cell distribution width, and alcohol intake were the top 10 key predictors used by the XGBT algorithm. Machine learning algorithms trained using routinely collected data outperformed traditional statistical models when predicting 90-day ACU. The XGBT algorithm has the potential to identify high-ACU risk patients and enable preventive interventions to avoid ACU.

Geographic Disparities in Re-triage Destinations Among Seriously Injured Californians.

To quantify geographic disparities in sub-optimal re-triage of seriously injured patients in California. Re-triage is the emergent transfer of seriously injured patients from the emergency departments of non-trauma and low-level trauma centers to, ideally, high-level trauma centers. Some patients are re-triaged to a second non-trauma or low-level trauma center (sub-optimal) instead of a high-level trauma center (optimal). This was a retrospective observational cohort study of seriously injured patients, defined by an Injury Severity Score > 15, re-triaged in California (2009-2018). Re-triages within one day of presentation to the sending center were considered. The sub-optimal re-triage rate was quantified at the state, regional trauma coordinating committees (RTCC), local emergency medical service agencies, and sending center level. A generalized linear mixed-effects regression quantified the association of sub-optimality with the RTCC of the sending center. Geospatial analyses demonstrated geographic variations in sub-optimal re-triage rates and calculated alternative re-triage destinations. There were 8,882 re-triages of seriously injured patients and 2,680 (30.2 %) were sub-optimal. Sub-optimally re-triaged patients had 1.5 higher odds of transfer to a third short-term acute care hospital and 1.25 increased odds of re-admission within 60 days from discharge. The sub-optimal re-triage rates increased from 29.3 % in 2009 to 38.6 % in 2018. 56.0 % of non-trauma and low-level trauma centers had at least one sub-optimal re-triage. The Southwest RTCC accounted for the largest proportion (39.8 %) of all sub-optimal re-triages in California. High population density geographic areas experienced higher sub-optimal re-triage rates.

Improving Health and Addressing Social Determinants of Health Through Hospital Partnerships.

Hospitals and health systems are forming partnerships to develop an integrated social network of services that better address the needs of their surrounding communities and their social determinants of health (SDOH). There is little research on the association of these partnered services with hospital outcomes. This study examined the association between hospital social need partnerships and activities to improve hospital and community outcomes. A secondary cross-sectional design to analyze 2021 census data of nonfederal short-term acute care hospitals in the United States was utilized. Data were obtained from the American Hospital Association. Four multilevel logistic regression models were used to analyze data from 1005 hospitals. The authors found that hospital partnership type differed in association to social need outcomes. They found that hospitals with a partnership with health insurance providers were more likely to have better health outcomes. Hospitals partnered with health insurance providers, local organizations addressing housing insecurity, local businesses, or chambers of commerce were more likely to have decreased health care costs. Hospitals partnered with health care providers, health insurance providers, local organizations providing legal assistance, or law enforcement/safety forces were more likely to have decreased utilization of hospital services. However, hospitals partnered with other local or state government or social service organizations were less likely to indicate decreased utilization of services. Many hospitals and health systems across the United States are screening for SDOH and are advancing health care delivery and improving the community's overall health and well-being by identifying unmet social needs and partnering with the community to address them.

End-of-life care in intensive care units: A concept analysis

End-of-life care should be considered a part of the nursing profession, specifically in intensive care units [ICUs]. Although various definitions of end-of-life care have been proposed by nursing academies and associations, a clear definition of end-of-life care in ICUs is yet to be determined. Thus, in this concept analysis, we aim to define end-of-life care in the ICU. In this study, we utilized Walker and Avant's concept analysis method, which is designed to identify the structure and definition of a concept like end-of-life care in ICU. In this concept analysis, two antecedents, four attributes, and three consequences of end-of-life care in ICU were extracted, and its definition was thereafter clarified. These results are highly useful and can support critical care nurses, as they are the ones who provide optimal care for dying patients and their families in the ICU; they also form a basis for further research with regard to end-of-life care in the field of critical care nursing. The prominent features of end-of-life care in ICU are as follows: a high dependency on medical equipment, short-term care, and focus on care for families as most patients are unconscious. These features reflect the definition of end-of-life care in ICU. End-of-life care in ICU were defined as intensive and short-term care for patients who are facing imminent death and their families, to help them live out their lives with dignity.

Organización y costes de la atención extrahospitalaria del ictus. Revisión sistemática de la literatura

ObjectiveTo review the bibliography on stroke costs (ICD-10 code I63) in the field of primary care. DesignSystematic review. Data sourcesPubMed/Medline, ClinicalTrials.gov, Cochrane Reviews, EconLit, and Ovid/Embase between 01/01/2012–12/31/2021 with descriptors included in Medical Subject Heading (MeSH). Selection of studiesThose with a description of the costs of activities carried out in the out-of-hospital setting. Systematic reviews were included; prospective and retrospective observational studies; analysis of databases and total or partial costs of stroke as a disease (COI). Articles were added using the snowball method. The studies were excluded because: a) not specifically related to stroke; b) in editorial or commentary format; c) irrelevant after review of the title and abstract; and d) gray literature and non-academic studies were excluded. Data extractionThey were assigned a level of evidence according to the GRADE levels. Direct and indirect cost data were collected. Results and conclusionsThirty studies, of which 14 (46.6%) were related to post-stroke costs and 12 (40%) to cardiovascular prevention costs. The results show that most of them are retrospective analyzes of different databases of short-term hospital care, and do not allow a detailed analysis of the costs by different segments of services. The possibilities for improvement are centered on primary and secondary prevention, selection and pre-hospital transfer, early discharge with support, and social and health care.

Special Report: The Moore Pediatric Surgery Center: An Evolving Model for Pediatric Orthopaedic Surgical Care in a Limited Resource Environment

The authors describe their 11-year experience with 1 model for providing short-term (about 1wk/y in country) pediatric orthopaedic surgical care in a limited resource environment. This paper provides a detailed narrative of 1 team's pediatric orthopaedic work at the Moore Pediatric Surgery Center in Guatemala City, how it has evolved over these 11 years, financial aspects of the model, and examines patient follow-up data for a consecutive 8-year period. The authors have reviewed financial records, case lists, patient charts from 2014 to 2022, and patient photographic records from The Moore Center and as provided via internet by a local contracted Guatemalan pediatric orthopaedic fellowship-trained surgeon to present a complete picture of how the service functions. Specific follow-up data included: last follow-up date, date discharged from follow-up, and major complications including infection, surgical wound dehiscence, return for unplanned surgery, major nerve injury, and recurrent hip dislocation for cases of closed or open reduction of developmental hip dislocation. A total of 297 consecutive pediatric orthopaedic surgical patients were identified from 2014 to 2022. Of these, charts were found for 235 patients (135 female, 110 male), of which 43% were from the urban Guatemala City region. Two hundred sixteen (72%) had at least 1 follow-up clinic visit, and 87 (37%) had at least 1-year follow-up or were discharged. All complications identified by this retrospective chart review included 4 recurrent hip dislocations (3 after closed reduction), 1 femur fracture after implant removal, 1 superficial infection requiring antibiotics, 1 partial dehiscence treated only with dressings, 1 thumb subluxation, and 1 failed graft with internal fixation for congenital pseudoarthrosis of tibia. The Moore Pediatric Surgery Center is a financially viable, sustainable, safe, and effective model for delivering short-term surgical care for many pediatric orthopaedic conditions in a limited resource environment. None (descriptive).

The Predictive Factors of Hospital Bankruptcy-An Exploratory Study.

The United States healthcare industry has witnessed a number of hospitals declare bankruptcy. This has a meaningful impact on local communities with vast implications on access, cost, and quality of care available. In our research, we seek to determine what contemporary structural and operational factors influence a bankruptcy outcome, and craft predictive models to guide healthcare leaders on how to best avoid bankruptcy in the future. In this exploratory study we performed, a single-year cross-sectional analysis of short-term acute care hospitals in the United States and subsequently developed three predictive models: logistic regression, a linear support vector machine (SVM) model with hinge function, and a perceptron neural network. Data sources include Definitive Healthcare and Becker's Hospital Review 2019 report with 3121 observations of 32 variables with 27 observed bankruptcies. The three models consistently indicate that 18 variables have a significant impact on predicting hospital bankruptcy. Currently, there is limited literature concerning financial forecasting models and knowledge detailing the factors associated with hospital bankruptcy. By having tailored knowledge of predictive factors to establish a sound financial structure, healthcare institutions at large can be empowered to take proactive steps to avoid financial distress at the organizational level and ensure long-term financial viability.

Cost Savings and Reduced Health Care Utilization Associated with Participation in a Digital Diabetes Prevention Program in an Adult Workforce Population.

BackgroundThough in-person delivery of the Diabetes Prevention Program (DPP) has demonstrated medical cost savings, the economic impact of digital programs is not as well understood.ObjectiveThis study examines the impact of a digital DPP program on reducing all-cause health care costs and utilization among 2027 adult participants at 12 months.MethodsA longitudinal, observational analysis of health care claims data was conducted on a workforce population who participated in a digital diabetes prevention program. Differences in utilization and costs from the year prior to program delivery through 1 year after enrollment were calculated using medical claims data for digital DPP participants compared to a propensity matched cohort in a differences-in-differences model.ResultsAt 1 year, the digital DPP population had a reduction in all-cause health care spend of US$1169 per participant relative to the comparison group (P = 0.01), with US$699 of that savings coming from reduced inpatient spend (P = 0.001). Cost savings were driven by fewer hospital admissions and shorter length of stay (P < 0.001). No other significant results in cost differences were detected. There was a trend toward savings extending into the second year, but the savings did not reach statistical significance.ConclusionsThese results demonstrated significant short-term health care cost savings at 1 year associated with digital DPP program delivery.

“I will commit to this child as much as I can for the time that they are with me:” A qualitative examination of how foster carer commitment relates to short-term foster care for young children following abuse and neglect

BackgroundFoster carer commitment to the child has been shown to be of paramount importance in young children's recovery and development following abuse and neglect. In Dozier's definition of commitment in the US, there is a focus on both emotional investment in the child and committing to an enduring relationship with the child. How this relates to the routine practice of short-term, temporary, foster care has not been studied. ObjectiveThis is the first qualitative study to explore the drivers of, and barriers to, commitment in short-term foster care within the broader aim of examining whether short-term care is meeting the needs of maltreated young children. Participants & settingFourteen foster carers took part in research interviews and five focus groups were conducted with infant mental health professionals. MethodsInterviews and focus group data were subject to qualitative thematic analysis in order to identify patterns of commonality in relation to our research questions. ResultsThree broad themes pertain to commitment and the meeting of young children's needs in short-term foster care: Influence, Timescales and Choice in the fostering role. These themes were found to house both drivers of, and barriers to, commitment in short-term care, which are influenced by systemic normalisations of fostering practices. ConclusionsThe emotional investment facet of commitment is more alive in the ‘psyche’ of short-term foster care than commitment to an enduring relationship. A long-term outlook for the child may be an undefined facet of commitment that is more akin with short-term placements.

Association between community environment and dependency among the elderly people from a service provision perspective

BackgroundThe incidence of dependency is high among the elderly people worldwide and increases with increasing life expectancy. The purpose of this study was to establish from the perspective of resource demand the association between community environmental resources and dependency among the elderly people.MethodsThis study is a cross-sectional design based on community from 22 locations in China. A multistage sampling method was used to select the study objects. The questionnaires were used to collect the survey data by face-to-face interviews. A total of 950 individuals completed the survey, and 913 individuals were available for this analysis. Dependency and community environment were measured using the standard instruments. Logistic regression analysis was performed to identify the community environment factors associated with dependency. Cluster analysis was used and demonstrated that dependency was mainly associated with community primary preventive care service resources.ResultsIn the group aged under 70 years, the utilization of electronic health records and the need for health assessments, and rehabilitation equipment rentals were significantly associated with the levels of dependency scores: the OR was 2.81, 2.25 and 2.13 (P < 0.05), respectively. In the group aged 70 years and over, a short-term care home was strongly associated with levels of dependency: the OR was 4.01 (P = 0.002). The daycare and nursing service, transportation service, and regular lectures on health knowledge were associated with levels of dependency: the OR was 2.41, 1.86 and 1.93 (P < 0.05). In the group with low social support, an emergency call or monitoring system, transportation services, the need for health assessment, and regular lectures on health knowledge were significantly associated with levels of dependency: the OR was 2.42, 2.19, 1.89 and 1.98 (P < 0.05), respectively.ConclusionsCommunity environment resources were significantly associated with dependency. These results suggest that the dependent on local environment resources may consider as the resource needs among elderly people.

Nursing Home Status Adjustment for Standardized Mortality and Hospitalization in Dialysis Facility Reports

Compared to the original nursing home status (any nursing home stay in the previous calendar year), new nursing home status variables were developed to improve the risk adjustment of Standardized Mortality/Hospitalization Ratio (SMR/SHR) models used in public reporting of dialysis quality of care, such as the Annual Dialysis Facility Report. Retrospective observational study. 625,040 US maintenance dialysis patients with>90 kidney failure days in2019. Nursing home status variables; patient characteristics; comorbid conditions. Mortality/hospitalization. We assigned patients and patient times (SMR/SHR model) to one of 3 mutually exclusive categories: long-term care (≥90 days), short-term care (1-89 days), or non-nursing home, based on nursing home stay during the previous 365 days from the first day of the time period at risk. Nursing home status was derived from the Nursing Home Minimum Data Set. Comparisons of hazard ratios from adjusted models, facility SMR/SHR performance, and model C-statistics between the original/new models were performed. SMR's hazard ratio of original nursing home status (2.09) was lower than both ratios of short-term care (2.38) and long-term care (2.43), whereas SHR's hazard ratio of original nursing home status (1.10) was between the ratios of long-term care (1.01) and short-term care (1.20). There was a difference in hazard ratios between short-term care and long-term care for both measures. Small percentages of facilities changed performance categories: 0.7% for SMR and 0.4% for SHR. The SMR C-statistic improved whereas the SHR C-statistic was relatively unchanged. Limited capture of subacute rehabilitation stays in the nursing home by using a 90-day cutoff for short-term care and long-term care; unable to draw causal inference about nursing home care. Use of a nursing home metric that effectively separates short-term from long-term nursing home utilization results in more meaningful risk adjustment that generally comports with Medicare payment policy, potentially resulting in more interpretable results for dialysis stakeholders.

Financial impact of telehealth: rural chief financial officer perspectives.

To explore the perceived impacts of a variety of telehealth services on hospital finances and assess how hospital administrators make decisions about adopting telehealth programs. From October 2021 to January 2022, we conducted semistructured interviews with chief financial officers (CFOs) of rural hospitals. Recruitment occurred in collaboration with 6 rural health collaboratives and hospital associations that facilitated CFO peer-learning groups. We used inductive and deductive approaches informed by a health care innovation adoption model to identify themes in the qualitative data. Twenty rural hospital CFOs and other hospital administrators from 10 states participated in interviews. Seventeen (85%) represented critical access hospitals and 3 (15%) represented short-term acute care hospitals. Although CFOs believed telehealth has some financial advantages (eg, can help to avoid patient transfers), they did not believe that telehealth improved their hospitals' financial situations. CFOs, rather, seem motivated to implement telehealth services to improve quality of care and address patients' needs. CFOs reported that limited reimbursement, low volumes, preference for in-person care, and insufficient broadband were key challenges to telehealth's financial viability. Understanding how CFOs think about the return on investment of telehealth can inform efforts to promote telehealth utilization in rural communities and to develop policy solutions to make telehealth more sustainable. CFOs may benefit from guidance on promising practices and cost-effective implementation strategies. Policy makers could take steps to improve telehealth's financial attractiveness (eg, through payment parity, subsidies to improve technology infrastructure).

Prediction of total healthcare cost following total shoulder arthroplasty utilizing machine learning.

Given the increase in demand in treatment of glenohumeral arthritis with anatomic total (aTSA) and reverse shoulder arthroplasty (RTSA), it is imperative to improve quality of patient care while controlling costs as private and federal insurers continue its gradual transition toward bundled payment models. Big data analytics with machine learning shows promise in predicting health care costs. This is significant as cost prediction may help control cost by enabling health care systems to appropriately allocate resources that help mitigate the cause of increased cost. The Nationwide Readmissions Database (NRD) was accessed in 2018. The database was queried for all primary aTSA and RTSA by International Classification of Diseases, Tenth Revision (ICD-10) procedure codes: 0RRJ0JZ and 0RRK0JZ for aTSA and 0RRK00Z and 0RRJ00Z for RTSA. Procedures were categorized by diagnoses: osteoarthritis (OA), rheumatoid arthritis (RA), avascular necrosis (AVN), fracture, and rotator cuff arthropathy (RCA). Costs were calculated by utilizing the total hospital charge and each hospital's cost-to-charge ratio. Hospital characteristics were included, such as volume of procedures performed by the respective hospital for the calendar year and wage index, which represents the relative average hospital wage for the respective geographic area. Unplanned readmissions within 90 days were calculated using unique patient identifiers, and cost of readmissions was added to the total admission cost to represent the short-term perioperative health care cost. Machine learning algorithms were used to predict patients with immediate postoperative admission costs greater than 1 standard deviation from the mean, and readmissions. A total of 49,354 patients were isolated for analysis, with an average patient age of 69.9±9.6 years. The average perioperative cost of care was $18,843±$10,165. In total, there were 4279 all-cause readmissions, resulting in an average cost of $13,871.00±$14,301.06 per readmission. Wage index, hospital volume, patient age, readmissions, and diagnosis-related group severity were the factors most correlated with the total cost of care. The logistic regression and random forest algorithms were equivalent in predicting the total cost of care (area under the receiver operating characteristic curve=0.83). After shoulder arthroplasty, there is significant variability in cumulative hospital costs, and this is largely affected by readmissions. Hospital characteristics, such as geographic area and volume, are key determinants of overall health care cost. When accounting for this, machine learning algorithms may predict cases with high likelihood of increased resource utilization and/or readmission.

Stratification of Length of Stay Prediction following Surgical Cytoreduction in Advanced High-Grade Serous Ovarian Cancer Patients Using Artificial Intelligence; the Leeds L-AI-OS Score

(1) Background: Length of stay (LOS) has been suggested as a marker of the effectiveness of short-term care. Artificial Intelligence (AI) technologies could help monitor hospital stays. We developed an AI-based novel predictive LOS score for advanced-stage high-grade serous ovarian cancer (HGSOC) patients following cytoreductive surgery and refined factors significantly affecting LOS. (2) Methods: Machine learning and deep learning methods using artificial neural networks (ANN) were used together with conventional logistic regression to predict continuous and binary LOS outcomes for HGSOC patients. The models were evaluated in a post-hoc internal validation set and a Graphical User Interface (GUI) was developed to demonstrate the clinical feasibility of sophisticated LOS predictions. (3) Results: For binary LOS predictions at differential time points, the accuracy ranged between 70-98%. Feature selection identified surgical complexity, pre-surgery albumin, blood loss, operative time, bowel resection with stoma formation, and severe postoperative complications (CD3-5) as independent LOS predictors. For the GUI numerical LOS score, the ANN model was a good estimator for the standard deviation of the LOS distribution by ± two days. (4) Conclusions: We demonstrated the development and application of both quantitative and qualitative AI models to predict LOS in advanced-stage EOC patients following their cytoreduction. Accurate identification of potentially modifiable factors delaying hospital discharge can further inform services performing root cause analysis of LOS.

Patient-Reported Outcome Measures in Newly Diagnosed Acute Myeloid Leukemia: An Exploratory Analysis of Real-World Data

Background: Patients with acute myeloid leukemia (AML) may experience substantial disease- and treatment-related symptoms. Patient-reported outcome (PRO) assessments are validated tools to evaluate patient symptoms and function, and are associated with improved health-related quality of life (HRQoL), reduced unplanned acute care, and longer overall survival among patients with advanced solid tumors (Basch E et al. JAMA, 2017.318(2):197-198). However, PROs are used infrequently in the AML population outside of clinical trials. Objectives: We assessed the characteristics of baseline PRO measurements in patients with newly diagnosed AML and evaluated their association with short-term acute care utilization and receipt of allogeneic hematopoietic stem cell transplantation (alloHSCT). Methods: We retrospectively identified all patients with non-M3 AML diagnosed between 6/2018 and 3/2020 who were actively receiving therapy at our institution and completed at least one outpatient PRO survey within a period of 1 month preceding to 3 months following AML diagnosis. This assessment period was selected to allow us to assess outpatient PROs, since many patients are admitted at initial presentation and remain inpatient for an extended period at the time of diagnosis. The survey completed at the time closest to the time of diagnosis was defined as baseline PRO. PROs were measured using a 14-question assessment administered before each outpatient encounter using the National Cancer Institute's PRO Version of The Common Terminology Criteria for Adverse Events. The survey addresses 9 symptom scales rated by patients on a scale of 1-5 ranging from no symptom to very severe symptom with higher scores indicating worse symptoms, and 1 QoL scale with higher scores indicating improved QoL. Time to acute care visit (TAC) was defined as the time from baseline PRO measurement to the first unplanned acute care visit (emergency room visit or unplanned hospitalization) and assessed using Kaplan-Meier survival function and log-rank test. Fisher's exact test was used to assess the associations between symptom burden and age, therapy intensity subgroups, and alloHSCT status. Results: Seventy patients with a median age of 63 years (range 22-88) at AML diagnosis were included in the analysis. The median follow-up was 19.2 months. Forty patients (57.1%) underwent intensive induction therapy, i.e., "7+3" and its variations. Thirty patients (42.9%) received non-intensive therapy, primarily venetoclax/azacitidine. The most common (n=52, 75.4%) and most severe symptom reported in our cohort was fatigue, with a mean score of 3.06 (standard deviation (SD) 1.07). Symptom burden did not differ between younger (< 60yrs (n=29, 41.4%)) and older (≥ 60yrs) patients, except for sadness which was reported more frequently in patients < 60yrs (41.4% vs. 19.5%, p=0.043). Patients undergoing non-intensive therapy reported more frequent dyspnea at baseline (61.5% vs. 37.5%, p=0.048) (table 1). Mean QoL score (2.71, SD 1.21) did not differ by age or induction intensity. The median TAC was 16.1 weeks with 60 (85.7%) patients having at least one acute care visit. Patients with moderate to severe baseline fatigue (fatigue score > 2 (n=30, 43.5%) ) had a median TAC of 13.9 weeks and tended to a higher risk of sooner acute care visit initially compared to those with none to mild fatigue (fatigue score ≤ 2) (TAC 20.4 weeks, p=0.282) (figure 1). In patients with intermediate- and adverse-risk disease (n=54), more patients with baseline fatigue score ≤ 2 (n=28, 51.9%) were able to undergo alloHSCT (53.6% vs. 28.0%, p=0.053). Additionally, lower fatigue scores on follow-up PRO survey post-induction were associated with a higher rate of alloHSCT (61.5% for patients with fatigue scores ≤ 2 vs. 24.0% with fatigue scores >2, p=0.007) despite no difference in remission status between the two groups post-first induction cycle (53.6% vs. 31.8%, p=0.182). Conclusions: In patients with newly diagnosed AML, fatigue was the most prominent symptom reported at baseline. Patients with worse baseline fatigue may be at risk for sooner unplanned acute care visits within the first year of diagnosis. Patients with less fatigue post-induction had a higher chance of undergoing alloHSCT. Further investigation is needed to better understand and utilize the real-world PRO data to help provide patient-centered, goal-concordant care to AML patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Motor and non-motor improvements following short-term multidisciplinary day-clinic care in Parkinson´s disease

BackgroundInpatient as well as outpatient care does often not meet PD-patients’ individual needs.IntroductionDay-clinic concepts encompassing a multidisciplinary team as well as therapy adjustments accompanying everyday demands aim at filling this gap.MethodsThis is a retrospective study on short-term effects of a 3 week multidisciplinary rehabilitation program in patients with Parkinson´s disease (PD) embedded in a specialized movement disorder day-clinic. We analyzed short-term outcome of motor and non-motor symptoms (NMS) in 143 PD-patients (mean age 65.3 ± 11.9 years; Hoehn-and-Yahr-score 2.6 ± 0.7) after 3 weeks with 7.4 ± 1.8 active days of interdisciplinary day-care treatment. Participants attended the day-clinic in groups of five patients at a time. Improvements were evaluated by comparison of standardized physical therapy assessments, disease specific scores for motor symptoms (MDS–UPDRS III), mood (BDI), quality of life (PDQ39, SF36), sleep (PDSS, ESS), impulsiveness (QUIP), apathy (SAS), cognition (MMST), as well as change in medication before and directly after the intervention.ResultsMDS–UPDRS motor score improved significantly by 22.9 ± 21.5% (p < 0.001) and was accompanied by a significant reduction of imbalance, immobility, and weakness ranging between 6% and 17% in standardized physical therapy tests. In addition, all disease-specific non-motor scales improved significantly.ConclusionsA multidisciplinary day-clinic approach can support benefit on motor, non-motor symptoms and QoL in PD-patients. Given the increase in PD incidence and prevalence as well as the significant treatment effects shown here, more day-clinic treatment opportunities ought to be implemented to improve PD treatment adapted to everyday challenges while still reducing costs to the health care system.

Health service use before and after dementia diagnosis: a retrospective matched case–control study

ObjectivesThis study investigated patterns in health service usage among older adults with dementia and matched controls over a 10-year span from 5 years before until 5 years after diagnosis.DesignPopulation-based retrospective...

Effects of care burden on the life of caregivers of the elderly: A mixed-method study model.

Determining the care burden of elderly caregivers in the early period allows for early intervention to protect them from the negative physical, social, and psychological effects of care. This mixed-method study aimed to determine the burden levels of caregivers of elderly individuals and evaluate their opinions on the difficulties they experienced while caregiving. This study was conducted with caregivers of 89 elderly people who were determined to need care by visiting the homes of elderly people aged 65 years and over living in Famagusta. While the KATZ index of independence in activities of daily living and the Zarit Burden Interview tool were used to collect quantitative data, face-to-face interviews were conducted with 28 selected participants to collect qualitative data. The mean age of the caregivers was 52 ± 12 years; they were mostly female spouses/children/relatives, and 29.2% had moderate-to-severe care burden perceptions. The perception of caregiver burden levels increased as the level of dependency of elderly individuals and the duration of caregiving increased. Considering that caregiving burden affects every aspect of caregivers' lives, it should be assessed regularly. To reduce care burden, it is recommended to expand home care services and short-term care facilities, use health technologies for continuous distance education and counseling in elderly care, and financially support caregivers who cannot work due to the responsibilities of providing elderly care.

The duration of intervention required to improve the motor function of pre-frail elderly people in a short-term intensive day care service.

The duration of intervention required to improve the motor function of pre-frail elderly people in a short-term intensive day care service.