Editorial: Using Technology to Combat Diseases and Help People With Disabilities

Editorial on the Research Topi

The Impact of Socioeconomic Status, Surgical Resection and Type of Hospital on Survival in Patients with Pancreatic Cancer:A Population-Based Study in The Netherlands

The influence of socioeconomic inequalities in pancreatic cancer patients and especially its effect in patients who had a resection is not known. Hospital type in which resection is performed might also influence outcome. Patients diagnosed with pancreatic cancer from 1989 to 2011 (n = 34,757) were selected from the population-based Netherlands Cancer Registry. Postal code was used to determine SES. Multivariable survival analyses using Cox regression were conducted to discriminate independent risk factors for death. Patients living in a high SES neighborhood more often underwent resection and more often were operated in a university hospital. After adjustment for clinicopathological factors, risk of dying was increased independently for patients with intermediate and low SES compared to patients with high SES. After resection, no survival difference was found among patients in the three SES groups. However, survival was better for patients treated in university hospitals compared to patients treated in non-university hospitals. Low SES was an independent risk factor for poor survival in patients with pancreatic cancer. SES was not an adverse risk factor after resection. Resection in non-university hospitals was associated with a worse prognosis.</p

Sociodemographic and clinical characteristics in child and youth mental health; comparison of routine outcome measurements of an Australian and Dutch outpatient cohort

Routine outcome measurement (ROM) data offer unique opportunities to study treatment outcomes in clinical practice, and can help to assess the real-world impact of mental health services for children and adolescents (youth). This is illustrated by studies using naturalistic data from specialist child and adolescent mental healthcare services (CAMHS), showing the proportion of patients with reliable improvement, recovery or deterioration (Burgess et al., 2015; Wolpert et al., 2016), and revealing specific subgroups of patients with greater risk of poor outcome (Garralda et al., 2000; Lundh et al., 2013; Murphy et al., 2015; Edbrooke-Childs et al., 2017). Naturalistic data are therefore undeniably necessary in addition to data derived from randomised clinical trials, which often have limited generalisability due to strict selection criteria (Rothwell, 2005; Van Noorden et al., 2014).New methods for child psychiatric diagnosis and treatment outcome evaluatio