Hammerhanley3675

Both diagnosis and treatment of neurological emergencies require neurological expertise and are time-sensitive. The lack of fast neurological expertise in regions with underserved infrastructure poses a major barrier for state-of-the-art care of patients with acute neurological diseases and leads to disparity in provision of health care. The main purpose of ANNOTeM (acute neurological care in North East Germany with telemedicine support) is to establish effective and sustainable support structures for evidence based treatments for stroke and other neurological emergencies and to improve outcome for acute neurological diseases in these rural regions.

A "hub-and-spoke" network structure was implemented connecting three academic neurological centres ("hubs") and rural hospitals ("spokes") caring for neurological emergencies. The network structure includes (1) the establishment of a 24/7 telemedicine consultation service, (2) the implementation of standardized operating procedures (SOPs) in the network hospitals, (3) a multiprofessional training scheme, and (4) a quality management program. Data from three major health insurance companies as well as data from the quality management program are being collected and evaluated. Primary outcome is the composite of first time of receiving paid outpatient nursing care, first time of receiving care in a nursing home, or death within 90 days after hospital admission.

Beyond stroke only few studies have assessed the effects of telemedically supported networks on diagnosis and outcome of neurological emergencies. ANNOTeM will provide information whether this approach leads to improved outcome. In addition, a health economic analysis will be performed.

German Clinical Trials Register DRKS00013067, date of registration November 16 th, 2017, URL http//www.drks.de/DRKS00013068.

German Clinical Trials Register DRKS00013067, date of registration November 16 th, 2017, URL http//www.drks.de/DRKS00013068.

Primary insomnia (PI) is characterized by difficulties in initiating sleep or maintaining sleep, which lead to many serious diseases. Acupuncture for PI has drawn attention with its effectiveness and safety. However, the operation of choosing acupoints lacks scientific suggestion. Our trial aims to provide reference and scientific basis for the selection of acupoints and to explore its possible mechanism.

A patient-assessor-blinded, randomized and sham controlled trial was designed to compare the efficacy of 5-weeks acupuncture at a single acupoint, the combination of multi-acupoints, and a sham point. The Pittsburgh sleep quality index and Athens Insomnia Scale questionnaire were used for the primary clinical outcomes, while polysomnography was performed for the secondary clinical outcomes. The resting state functional MRI was employed to detect the cerebral responses to acupuncture. The brain activity in resting state was measured by calculating the fractional amplitude of low-frequency fluctuations (fAClinicalTrials.gov Identifier NCT02448602 . Registered date 14/04/2015.

Advanced cancer affects people's lives, often causing stress, anxiety and depression. Peer mentor interventions are used to address psychosocial concerns, but their outcomes and effect are not known. Our objective was to determine the feasibility of delivering and investigating a novel peer mentor intervention to promote and maintain psychological wellbeing in people with advanced cancer.

A mixed methods design incorporating a two-armed controlled trial (random allocation ratio 11) of a proactive peer mentor intervention plus usual care, vs. usual care alone, and a qualitative process evaluation. Peer mentors were recruited, trained, and matched with people with advanced cancer. Quantitative data assessed quality of life, coping styles, depression, social support and use of healthcare and other supports. Qualitative interviews probed experiences of the study and intervention.

Peer mentor training and numbers (n= 12) met feasibility targets. Patient participants (n = 12, from 181 eligible who received an information pack) were not recruited to feasibility targets. Those who entered the study demonstrated that intervention delivery and data collection were feasible. PIK-III cost Outcome data must be treated with extreme caution due to small numbers, but indicate that the intervention may have a positive effect on quality of life.

Peer mentor interventions are worthy of further study and researchers can learn from these feasibility data in planning participant recruitment and data collection strategies. Pragmatic trials, where the effectiveness of an intervention is tested in real-world routine practice, may be most appropriate. Peer mentor interventions may have merit in enabling survivors with advanced cancer cope with their disease.

The trial was prospectively registered 13.6.2016 ISRCTN10276684 .

The trial was prospectively registered 13.6.2016 ISRCTN10276684 .

Diabetes is a leading cause of Medicare spending; predicting which individuals are likely to be costly is essential for targeting interventions. Current approaches generally focus on composite measures, short time-horizons, or patients who are already high utilizers, whose costs may be harder to modify. Thus, we used data-driven methods to classify unique clusters in Medicare claims who were initially low utilizers by their diabetes spending patterns in subsequent years and used machine learning to predict these patterns.

We identified beneficiaries with type 2 diabetes whose spending was in the bottom 90% of diabetes care spending in a one-year baseline period in Medicare fee-for-service data. We used group-based trajectory modeling to classify unique clusters of patients by diabetes-related spending patterns over a two-year follow-up. Prediction models were estimated with generalized boosted regression, a machine learning method, using sets of all baseline predictors, diabetes predictors, and predictorsterventions, such as medication adherence or interventions that enhance access to care, among patients with type 2 diabetes.

Patients with type 2 diabetes who were initially low spenders exhibit distinct subsequent long-term patterns of diabetes spending; membership in these patterns can be largely predicted with data-driven methods. These findings as well as applications of the overall approach could potentially inform the design and timing of diabetes or cost-containment interventions, such as medication adherence or interventions that enhance access to care, among patients with type 2 diabetes.