Measuring the work environment among healthcare professionals:Validation of the Dutch version of the Culture of Care Barometer

Objectives A positive work environment (WE) is paramount for healthcare employees to provide good quality care. To stimulate a positive work environment, employees’ perceptions of the work environment need to be assessed. This study aimed to assess the reliability and validity of the Dutch version of the Culture of Care Barometer (CoCB-NL) survey in hospitals. Methods This longitudinal validation study explored content validity, structural validity, internal consistency, hypothesis testing for construct validity, and responsiveness. The study was conducted at seven departments in two Dutch university hospitals. The departments were included based on their managers’ motivation to better understand their employees’ perception of their WE. All employees of participating departments were invited to complete the survey (n = 1,730). Results The response rate was 63.2%. The content of the CoCB-NL was considered relevant and accessible by the respondents. Two factor models were found. First, confirmative factor analysis of the original four-factor structure showed an acceptable fit (X2 2006.49; df 399; p = &lt;0.001; comparative fit index [CFI] 0.82; Tucker-Lewis index [TLI] 0.80; root mean square error of approximation [RMSEA] 0.09). Second, explanatory factor analysis revealed a five-factor model including ‘organizational support’, ‘leadership’, ‘collegiality and teamwork’, ‘relationship with manager’, and ‘employee influence and development’. This model was confirmed and showed a better fit (X2 1552.93; df 395; p = &lt; 0.00; CFI 0.87; TLI 0.86; RMSEA 0.07). Twelve out of eighteen hypotheses were confirmed. Responsiveness was assumed between the measurements. Conclusions The CoCB-NL is a valid and reliable instrument for identifying areas needing improvement in the WE. Furthermore, the CoCB-NL appears to be responsive and therefore useful for longitudinal evaluations of healthcare employees’ work environments.</p

Measuring the work environment among healthcare professionals:Validation of the Dutch version of the Culture of Care Barometer

Objectives A positive work environment (WE) is paramount for healthcare employees to provide good quality care. To stimulate a positive work environment, employees’ perceptions of the work environment need to be assessed. This study aimed to assess the reliability and validity of the Dutch version of the Culture of Care Barometer (CoCB-NL) survey in hospitals. Methods This longitudinal validation study explored content validity, structural validity, internal consistency, hypothesis testing for construct validity, and responsiveness. The study was conducted at seven departments in two Dutch university hospitals. The departments were included based on their managers’ motivation to better understand their employees’ perception of their WE. All employees of participating departments were invited to complete the survey (n = 1,730). Results The response rate was 63.2%. The content of the CoCB-NL was considered relevant and accessible by the respondents. Two factor models were found. First, confirmative factor analysis of the original four-factor structure showed an acceptable fit (X2 2006.49; df 399; p = &lt;0.001; comparative fit index [CFI] 0.82; Tucker-Lewis index [TLI] 0.80; root mean square error of approximation [RMSEA] 0.09). Second, explanatory factor analysis revealed a five-factor model including ‘organizational support’, ‘leadership’, ‘collegiality and teamwork’, ‘relationship with manager’, and ‘employee influence and development’. This model was confirmed and showed a better fit (X2 1552.93; df 395; p = &lt; 0.00; CFI 0.87; TLI 0.86; RMSEA 0.07). Twelve out of eighteen hypotheses were confirmed. Responsiveness was assumed between the measurements. Conclusions The CoCB-NL is a valid and reliable instrument for identifying areas needing improvement in the WE. Furthermore, the CoCB-NL appears to be responsive and therefore useful for longitudinal evaluations of healthcare employees’ work environments.</p

Mind your data:Privacy and legal matters in eHealth

The health care sector can benefit considerably from developments in digital technology. Consequently, eHealth applications are rapidly increasing in number and sophistication. For successful development and implementation of eHealth, it is paramount to guarantee the privacy and safety of patients and their collected data. At the same time, anonymized data that are collected through eHealth could be used in the development of innovative and personalized diagnostic, prognostic, and treatment tools. To address the needs of researchers, health care providers, and eHealth developers for more information and practical tools to handle privacy and legal matters in eHealth, the Dutch national Digital Society Research Programme organized the "Mind Your Data: Privacy and Legal Matters in eHealth" conference. In this paper, we share the key take home messages from the conference based on the following five tradeoffs: (1) privacy versus independence, (2) informed consent versus convenience, (3) clinical research versus clinical routine data, (4) responsibility and standardization, and (5) privacy versus solidarity

Characterization of tumor heterogeneity using dynamic contrast enhanced CT and FDG-PET in non-small cell lung cancer

AbstractPurposeDynamic contrast-enhanced CT (DCE-CT) quantifies vasculature properties of tumors, whereas static FDG-PET/CT defines metabolic activity. Both imaging modalities are capable of showing intra-tumor heterogeneity. We investigated differences in vasculature properties within primary non-small cell lung cancer (NSCLC) tumors measured by DCE-CT and metabolic activity from FDG-PET/CT.MethodsThirty three NSCLC patients were analyzed prior to treatment. FDG-PET/CT and DCE-CT were co-registered. The tumor was delineated and metabolic activity was segmented on the FDG-PET/CT in two regions: low (<50% maximum SUV) and high (⩾50% maximum SUV) metabolic uptake. Blood flow, blood volume and permeability were calculated using a maximum slope, deconvolution algorithm and a Patlak model. Correlations were assessed between perfusion parameters for the regions of interest.ResultsDCE-CT provided additional information on vasculature and tumor heterogeneity that was not correlated to metabolic tumor activity. There was no significant difference between low and high metabolic active regions for any of the DCE-CT parameters. Furthermore, only moderate correlations between maximum SUV and DCE-CT parameters were observed.ConclusionsNo direct correlation was observed between FDG-uptake and parameters extracted from DCE-CT. DCE-CT may provide complementary information to the characterization of primary NSCLC tumors over FDG-PET/CT imaging

Фінансовий контролінг як інструмент управління діяльністю суб'єкта господарювання

PURPOSE: Multiple imaging techniques are nowadays available for clinical in-vivo visualization of tumour biology. FDG PET/CT identifies increased tumour metabolism, hypoxia PET visualizes tumour oxygenation and dynamic contrast-enhanced (DCE) CT characterizes vasculature and morphology. We explored the relationships among these biological features in patients with non-small-cell lung cancer (NSCLC) at both the patient level and the tumour subvolume level. METHODS: A group of 14 NSCLC patients from two ongoing clinical trials (NCT01024829 and NCT01210378) were scanned using FDG PET/CT, HX4 PET/CT and DCE CT prior to chemoradiotherapy. Standardized uptake values (SUV) in the primary tumour were calculated for the FDG and hypoxia HX4 PET/CT scans. For hypoxia imaging, the hypoxic volume, fraction and tumour-to-blood ratio (TBR) were also defined. Blood flow and blood volume were obtained from DCE CT imaging. A tumour subvolume analysis was used to quantify the spatial overlap between subvolumes. RESULTS: At the patient level, negative correlations were observed between blood flow and the hypoxia parameters (TBR >1.2): hypoxic volume (−0.65, p = 0.014), hypoxic fraction (−0.60, p = 0.025) and TBR (−0.56, p = 0.042). At the tumour subvolume level, hypoxic and metabolically active subvolumes showed an overlap of 53 ± 36 %. Overlap between hypoxic sub-volumes and those with high blood flow and blood volume was smaller: 15 ± 17 % and 28 ± 28 %, respectively. Half of the patients showed a spatial mismatch (overlap <5 %) between increased blood flow and hypoxia. CONCLUSION: The biological imaging features defined in NSCLC tumours showed large interpatient and intratumour variability. There was overlap between hypoxic and metabolically active subvolumes in the majority of tumours, there was spatial mismatch between regions with high blood flow and those with increased hypoxia. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00259-015-3169-4) contains supplementary material, which is available to authorized users

The existence of cranial bone flap displacement during brain radiotherapy

This retrospective study examined bone flap displacement during radiotherapy in 25 post-operative brain tumour patients. Though never exceeding 2.5 mm, the sheer frequency of displacement highlights the need for future research on larger populations to validate its presence and assess the potential clinical impact on planning tumour volume margins.</p

Neurocognition in adults with intracranial tumors:Does location really matter?

OBJECTIVE: As preservation of cognitive functioning increasingly becomes important in the light of ameliorated survival after intracranial tumor treatments, identification of eloquent brain areas would enable optimization of these treatments. METHODS: This cohort study enrolled adult intracranial tumor patients who received neuropsychological assessments pre-irradiation, estimating processing speed, verbal fluency and memory. Anatomical magnetic resonance imaging scans were used for multivariate voxel-wise lesion-symptom predictions of the test scores (corrected for age, gender, educational level, histological subtype, surgery, and tumor volume). Potential effects of histological and molecular subtype and corresponding WHO grades on the risk of cognitive impairment were investigated using Chi square tests. P-values were adjusted for multiple comparisons (p < .001 and p < .05 for voxel- and cluster-level, resp.). RESULTS: A cohort of 179 intracranial tumor patients was included [aged 19-85 years, median age (SD) = 58.46 (14.62), 50% females]. In this cohort, test-specific impairment was detected in 20-30% of patients. Higher WHO grade was associated with lower processing speed, cognitive flexibility and delayed memory in gliomas, while no acute surgery-effects were found. No grading, nor surgery effects were found in meningiomas. The voxel-wise analyses showed that tumor locations in left temporal areas and right temporo-parietal areas were related to verbal memory and processing speed, respectively. INTERPRETATION: Patients with intracranial tumors affecting the left temporal areas and right temporo-parietal areas might specifically be vulnerable for lower verbal memory and processing speed. These specific patients at-risk might benefit from early-stage interventions. Furthermore, based on future validation studies, imaging-informed surgical and radiotherapy planning could further be improved

Nitroglycerin as a radiosensitizer in non-small cell lung cancer: Results of a prospective imaging-based phase II trial

Background: Nitroglycerin is proposed as an agent to reduce tumour hypoxia by improving tumour perfusion. We investigated the potent

'Rapid Learning health care in oncology' – An approach towards decision support systems enabling customised radiotherapy' ☆ ☆☆

AbstractPurposeAn overview of the Rapid Learning methodology, its results, and the potential impact on radiotherapy.Material and resultsRapid Learning methodology is divided into four phases. In the data phase, diverse data are collected about past patients, treatments used, and outcomes. Innovative information technologies that support semantic interoperability enable distributed learning and data sharing without additional burden on health care professionals and without the need for data to leave the hospital. In the knowledge phase, prediction models are developed for new data and treatment outcomes by applying machine learning methods to data. In the application phase, this knowledge is applied in clinical practice via novel decision support systems or via extensions of existing models such as Tumour Control Probability models. In the evaluation phase, the predictability of treatment outcomes allows the new knowledge to be evaluated by comparing predicted and actual outcomes.ConclusionPersonalised or tailored cancer therapy ensures not only that patients receive an optimal treatment, but also that the right resources are being used for the right patients. Rapid Learning approaches combined with evidence based medicine are expected to improve the predictability of outcome and radiotherapy is the ideal field to study the value of Rapid Learning. The next step will be to include patient preferences in the decision making