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The aim of this study was to calculate the average operational cost per sub-type of stroke patient and to investigate cost drivers (e.g. ALoS, NIHSS score, age) correlated to cost.Direct medical costs (diagnostic imaging and clinical laboratory exams, overheads/bed cost, pharmaceuticals, ringers and other non-durables and inpatient rehabilitation) per patient were calculated from the providers' (hospitals') perspective. Resource use data derived from the "SUN4P" web-based registry and unit costs were retrieved from publically available sources and were assigned to resource use.The sample comprised 6,282 inpatient days of 750 patients (mean age: 75.5±13.3 years) admitted from July 2019 to July 2021, in nine public hospitals. Mean length of stay was 8.4±7.6 days and mean total operational cost was calculated to €1,239.4 (from which 45% and 35% related to diagnostic exams and overheads/bed cost respectively). Mean cost related to hemorrhagic stroke patients that were discharged alive was calculated significantly higher compared to mean cost related to ischemic stroke patients who didn't undertake thrombolysis and were also discharged alive from the hospital (€2,155.2 vs. €945.2, p0.001). Linear regression analysis revealed that length of stay was significantly correlated with cost (coefficient beta=232, 95% CI confidence interval = 220-243, p0.001).These findings are in accordance with current evidence and should be thoroughly assessed to rationalize inpatient reimbursement rates in order to achieve improved value of care.

The aim of this study was to present the descriptive characteristics of the Stroke Units Necessity for Patients (SUN4P) registry.The study population derived from the web-based SUN4P registry included 823 patients with first-ever acute stroke. Descriptive statistics were used to present patients' characteristics.The vast majority of patients (80.4%) had an ischemic stroke, whereas 15.4% had a hemorrhagic stroke. Hypertension was the leading risk factor in both patients. The patients with ischemic stroke had higher prevalence of traditional cardiovascular risk factors such as diabetes mellitus, dyslipidemia and smoking and most commonly cryptogenic stroke (39%). National Institutes of Health Stroke Scale (NIHSS) was higher among patients with hemorrhagic in comparison to those with ischemic stroke (10.5 vs 6 respectively). Moreover, all patients had similar rate of disability prior to stroke, as shown by Modified Rankin Scale (mRS=0).These data are in accordance with current evidence and should be thoroughly assessed in order to ensure optimal therapeutic management of stroke patients.

To assess stroke patient-reported experiences and hospital staff experiences, during hospital stay.Stroke patient-reported experiences (n=387) were recorded using the translated and culturally adapted NHS-Stroke Questionnaire into Greek and staff experiences (n=236) were investigated using the Compassion Satisfaction and Burnout subscales of the ProQOL questionnaire.Staff's mean compassion satisfaction score was 39.2 (SD=6.3) and mean burnout score was 24.3 (SD=5.6). Only 38.5% of the staff stated that there is smooth cooperation with healthcare professionals of other specialties/disciplines. Personnel working in an NHS Hospital was more satisfied and less burned-out when compared to personnel working at a University Hospital (p=0.02 and p0.001, respectively). Mean total patient-reported experiences score was 81.9 (SD=9.5). Bivariate analysis revealed statistically significant differences for total patient-reported experiences among the eight study hospitals (p0.001).Health policy planners and decision-makers must take into consideration the results of such self-reported measures to establish innovative techniques to accomplish goals such as staff-specialization, continuous training and applying formal frameworks for efficient cooperation amongst different disciplines.

To assess stroke patient-reported experiences and hospital staff experiences, during hospital stay. Methods: Stroke patient-reported experiences (n=387) were recorded using the translated and culturally adapted NHS-Stroke Questionnaire into Greek and staff experiences (n=236) were investigated using the Compassion Satisfaction and Burnout subscales of the ProQOL questionnaire. Results: Staff’s mean compassion satisfaction score was 39.2 (SD=6.3) and mean burnout score was 24.3 (SD=5.6). Only 38.5% of the staff stated that there is smooth cooperation with healthcare professionals of other specialties/disciplines. Personnel working in an NHS Hospital was more satisfied and less burned-out when compared to personnel working at a University Hospital (p=0.02 and p0.001). Conclusions: Health policy planners and decision-makers must take into consideration the results of such self-reported measures to establish innovative techniques to accomplish goals such as staff-specialization, continuous training and applying formal frameworks for efficient cooperation amongst different disciplines.

The aim of this study was to present the descriptive characteristics of the Stroke Units Necessity for Patients (SUN4P) registry. Methods: The study population derived from the web-based SUN4P registry included 823 patients with first-ever acute stroke. Descriptive statistics were used to present patients’ characteristics. Results: The vast majority of patients (80.4%) had an ischemic stroke, whereas 15.4% had a hemorrhagic stroke. Hypertension was the leading risk factor in both patients. The patients with ischemic stroke had higher prevalence of traditional cardiovascular risk factors such as diabetes mellitus, dyslipidemia and smoking and most commonly cryptogenic stroke (39%). National Institutes of Health Stroke Scale (NIHSS) was higher among patients with hemorrhagic in comparison to those with ischemic stroke (10.5 vs 6 respectively). Moreover, all patients had similar rate of disability prior to stroke, as shown by Modified Rankin Scale (mRS=0). Conclusions: These data are in accordance with current evidence and should be thoroughly assessed in order to ensure optimal therapeutic management of stroke patients.

The aim of this study was to calculate the average operational cost per sub-type of stroke patient and to investigate cost drivers (e.g. ALoS, NIHSS score, age) correlated to cost. Methods: Direct medical costs (diagnostic imaging and clinical laboratory exams, overheads/bed cost, pharmaceuticals, ringers and other non-durables and inpatient rehabilitation) per patient were calculated from the providers’ (hospitals’) perspective. Resource use data derived from the “SUN4P” web-based registry and unit costs were retrieved from publically available sources and were assigned to resource use. Results: The sample comprised 6,282 inpatient days of 750 patients (mean age: 75.5±13.3 years) admitted from July 2019 to July 2021, in nine public hospitals. Mean length of stay was 8.4±7.6 days and mean total operational cost was calculated to €1,239.4 (from which 45% and 35% related to diagnostic exams and overheads/bed cost respectively). Mean cost related to hemorrhagic stroke patients that were discharged alive was calculated significantly higher compared to mean cost related to ischemic stroke patients who didn’t undertake thrombolysis and were also discharged alive from the hospital (€2,155.2 vs. €945.2, p

SUN4Patients is an observational study for the monitoring of patients with first ever acute stroke. For the support of this study, an online platform has been developed which facilitates the collection of various information related to hospital discharge, health services utilization and loss of productivity of the patients. This paper presents the main characteristics of the platform and the methodology followed for its design and implementation.

The aim of this study was to assess stroke patients' experiences in regards to hospital stay and during discharge. A cross-sectional study with retrospective data collection was conducted including patients (n=135) with first-ever acute stroke, who were admitted in seven Public Hospitals in Greece ("Stroke Units Necessity for Patients, SUN4P" registry). The translated version of the NHS-Stroke Questionnaire in the Greek was used. 48.2% of patients rated their overall experience from the care they received as very good/excellent. 66% of patients reported that they participated in decision making about their care and 21.5% reported not having received help from the hospital's social services regarding any benefits/aids, thus lowering their overall patient experience score (p=0.017). Decision and policymakers must consider factors affecting stroke patients 'experiences during their hospitalization. The development of a national stroke patients' experiences database can help prioritize relevant actions and draw up a commonly accepted management and services redesign framework for patients.

The aim of this study was to evaluate accessibility of stroke patients to optimal healthcare technology in Greece. Methods: The study population consisted of 313 first ever stroke patients derived from the "Stroke Units Necessity for Patients, SUN4P" registry. Descriptive statistics were used, to present patients' characteristics and resources utilization Results: The vast majority of patients (91.7%) conducted a CT scan during the acute phase (within the first 24hours). Almost, (65%) were admitted to wards of Internal Medicine Departments, whereas only 21% of patients were admitted to a Stroke Unit. Of note, a total of 6.9% of ischemic stroke patients received intravenous thrombolytic therapy with recombinant tissue plasminogen activator (rtPA). Conclusions: Preliminary results from SUN4P underline the urgent necessity for the re-organization of acute stroke care in Greece, as rates of admissions to stroke units and rtPA treatment during the acute phase are currently below optimal.

Knowledge management has recently received considerable attention in the computer information systems community and is continuously gaining interest from industry, enterprises and government. As we move towards building knowledge organizations, knowledge management in combination with information management will play a fundamental role towards the success of transforming individual knowledge into organizational knowledge. In this framework, this paper discusses the key concepts of human‐computer interaction in knowledge management, identifies new challenges of knowledge management for Web‐based business and proposes a “user agent architecture” for knowledge management in e‐learning environments. User agents use artificial neural network technology and can be used in various e‐learning or e‐training environments, in order to provide them with means of managing information stored, filtering content and enabling better knowledge adoption on behalf of their users.