The Effects of Levodopa and Deep Brain Stimulation on Subthalamic Local Field Low-Frequency Oscillations in Parkinson's Disease

New adaptive systems for deep brain stimulation (DBS) could in the near future optimize stimulation settings online so as to achieve better control over the clinical fluctuations in Parkinson's disease (PD). Local field potentials (LFPs) recorded from the subthalamic nucleus (STN) in PD patients show that levodopa and DBS modulate STN oscillations. Because previous research has shown that levodopa and DBS variably influence beta LFP activity (8-20 Hz), we designed this study to find out how they affect low-frequency (LF) oscillations (2-7 Hz). STN LFPs were recorded in 19 patients with PD during DBS, after levodopa medication, and during DBS and levodopa intake combined. We investigated the relationship between LF modulations, DBS duration and levodopa intake. We also studied whether LF power depended on disease severity, the patient's clinical condition and whether LF modulations were related to electrode impedances. LF power increased during DBS, after levodopa intake and under both experimental conditions combined. The LF power increase correlated with the levodopa-induced clinical improvement and the higher the electrode impedance, the greater was the LF power change. These data suggest that the LF band could be useful as a control neurosignal for developing novel adaptive DBS systems for patients with PD

Barriers Against Adoption of Electronic Health Record in Italy

This work aims to expose the barriers which work against the satisfactory adoption and utilization of Electronic Health Records (EHRs) in Italy. Experts from six operating areas were involved where barriers associated with practical daily use of EHRs might arise. Experts disclosed different barriers in their operating areas: the low interoperability of healthcare system infrastructures in diagnostic services; the lack of systems able to represent complex processes characterized by uncertainties in hospital wards; the unsatisfactory information exchange between heterogeneous healthcare providers in territorial healthcare; the lack of models and guidelines for administration process management; the lack of Health Information engineers who are recognized as professionals in Italian hospitals; the lack of domain vocabularies and ontologies for conceptual integration in clinical communication. Our findings suggest how future solutions must be designed considering the environment of specific areas

Methodology and workflow to perform the Data Protection Impact Assessment in healthcare information systems

Background: The General Regulation on Data Protection (GDPR) modernizes and harmonizes personal data protection laws across the European Union, affecting all economic sectors including the healthcare industry. The new regulation introduces two specific duties: the Record of Processing Activities (ROPA) and, for each high-risk processing, the Data Protection Impact Assessment (DPIA). Currently, there are no specific DPIA methodologies for the healthcare environment, but only broad methodologies applicable in all economic sectors. Objectives: This work aims to propose a methodology to perform DPIA for healthcare information systems, considering the specific constraints and criticisms posed by the heterogenous and highly sensitive nature of data and software use in hospitals. Methods: We first performed a GDPR analysis and an examination of other sources regarding DPIA.This analysis led to the identification of issues related to GDPR application in the healthcare environment. We then developed a workflow for DPIA execution, and implemented a software to apply it in a real environment. The methodology was applied on 11 softwares and devices already in use in the Trieste area, Italy. Results: The most important issue identified in the analysis is the definition of "processing activity", which was overcome by focusing the methodology on the information system processing the data instead of the processing activity per se. We therefore designed a workflow for the risk assessment of an information system establishing that the DPIA shall be performed after the purchase, usually a bid with strict IT security requirements of the information system, but before its deployment in the real environment. The validation of the developed software to implement the workflow on the 11 softwares showed the ability of the proposed workflow to perform the DPIA, and to uncover some important issues in the examined systems. Conclusions: The proposed methodology can be applied to perform DPIA in the healthcare environment by supporting risk evaluation and management, focusing on each software component added to the healthcare information system

Multi-criteria decision analysis for the assessment of non-clinical hospital services: Methodology and case study

Non-clinical hospital services to support clinical activities, such as the sterilization service and clinical engineering, are an important technology asset in healthcare, and require constant improvement aimed to reduce economic burden and increase quality. The selection of the most effective healthcare service to adopt in a healthcare facility is a multi-criteria decision problem that classical Health Technology Assessment, being mostly focused on medicines, vaccines and medical devices, cannot easily address. Here we present a methodology based on Multi-Criteria Decision Analysis allowing a full assessment of non-clinical hospital services and supporting the selection of the most suitable solution in a certain environment. The methodology involves two different panels of experts: the first one includes international professionals and is aimed at selecting the assessment criteria that are relevant to the target service; the second one is a local panel whose members know the needs and peculiarities of the specific healthcare facility. This approach allows the final decision makers to take into account changes and constraints of their environment, but examining criteria that are internationally recognized as of interest. The proposed methodology, tested in a real context of an Italian Local Health Authority, is versatile and can be applied in any context, even out of the healthcare domain, especially if data in the literature are not sufficient to allow comparisons with similar services in different settings. Abbreviations: HTA, Health Technology Assessment; NCHS, Non-Clinical Hospital Services; CSSD, Central Sterile Services Department; MCDA, Multi-Criteria Decision Analysis; ASM, Local Healt

Amplitude and frequency modulation of subthalamic beta oscillations jointly encode the dopaminergic state in Parkinson's disease.

Brain states in health and disease are classically defined by the power or the spontaneous amplitude modulation (AM) of neuronal oscillations in specific frequency bands. Conversely, the possible role of the spontaneous frequency modulation (FM) in defining pathophysiological brain states remains unclear. As a paradigmatic example of pathophysiological resting states, here we assessed the spontaneous AM and FM dynamics of subthalamic beta oscillations recorded in patients with Parkinson's disease before and after levodopa administration. Even though AM and FM are mathematically independent, they displayed negatively correlated dynamics. First, AM decreased while FM increased with levodopa. Second, instantaneous amplitude and instantaneous frequency were negatively cross-correlated within dopaminergic states, with FM following AM by approximately one beta cycle. Third, AM and FM changes were also negatively correlated between dopaminergic states. Both the slow component of the FM and the fast component (i.e. the phase slips) increased after levodopa, but they differently contributed to the AM-FM correlations within and between states. Finally, AM and FM provided information about whether the patients were OFF vs. ON levodopa, with partial redundancy and with FM being more informative than AM. AM and FM of spontaneous beta oscillations can thus both separately and jointly encode the dopaminergic state in patients with Parkinson's disease. These results suggest that resting brain states are defined not only by AM dynamics but also, and possibly more prominently, by FM dynamics of neuronal oscillations

Advising patients on selecting trustful apps for diabetes self-care

BACKGROUND: There has been a dramatic increase in mobile apps for diabetes self-care. However, their quality is not guaranteed and patients do not have the appropriate tools for careful evaluation. OBJECTIVE: This work aims to propose a tool to help patients with diabetes select an appropriate app for self-care. METHODS: After identifying the conceptual framework of diabetes self-care, we searched Apple US app store and reviewed diabetes self-care apps, considering both generic and diabetes-specific features. Based on an existing tool for representing the benefits and weaknesses of medical apps, we created the pictorial identification schema/Diabetes Self-care tool, which specifically identified medical apps in the diabetes domain. RESULTS: Of the 952 apps retrieved, 67 were for diabetes self-care, while 26 were excluded because they were not updated in the last 12 months. Of the remaining 41, none cost more than 15 USD, and 36 implemented manual data entry. Basic features (data logging, data representation, and data delivery) were implemented in almost all apps, whereas advanced features (e.g., insulin calculator) were implemented in a small percentage of apps. The pictorial identification schema for diabetes was completed by one patient and one software developer for 13 apps. Both users highlighted weaknesses related to the functionalities offered and to their interface, but the patient focused on usability, whereas the software developer focused on technical implementation. CONCLUSIONS: The Pictorial Identification Schema/Diabetes Self-care is a promising graphical tool for perceiving the weaknesses and benefits of a diabetes self-care app that includes multiple user profile perspectives

Integrating home monitoring for transcranial direct current stimulation (tDCS) therapy to professional care environment

Daily management of neurodegenerative diseases is one of the most striking scenarios where an integrated health care system is essential for the continuous assistance to the patient and requires qualification of the caregivers and their training. In particular, patients affected by depression or chronic pain, as well as rehabilitating after stroke, can be treated at home with non-invasive electrical neuromodulation (transcranial Direct Current Stimulation, tDCS) in order to reduce daily travel expenses between home and hospital. Home monitoring of patient undergoing tDCS is essential to (1) optimize the stimulation parameters according to the current health status and to the stimulation outcomes, and (2) assess disease progression. However, monitoring effectiveness depends on the exchange of this information between the patient at home and his/her reference neurologist. Currently, the health IT scenario is composed by two independent environments, one dedicated to healthcare professionals (e.g., Electronic Health Records, EHRs), and one including mobile devices applications dedicated to citizens, caregivers and patients. Safety, communication and interoperability gaps prevented from an effective data exchange between these two environments. The aim of our work is to implement an integrated home monitoring system for tDCS patients, in which a web-based platform for EHR management exchanges data with a patient\u2019s mobile app

A connecting system for cardiological lexicons

The purpose of this paper is to present the approach and the development of a software application ("lexicons connecting" system) to correlate effectively and unambiguously the correspondence between the specialist medical vocabulary and the familiar medical vocabulary for the cardiovascular domain. To investigate the question, the idea, the design, and the implementation of such system will be described. To this end, firstly, a number of research methodologies will be examined including domain ontologies development, database design and implementation. Then, the following implementation methodology and its results are presented. Finally, an example of the application use will be depicted and future work will be briefly described

Transcutaneous Spinal Direct Current Stimulation (tsDCS) Modulates Human Corticospinal System Excitability

This study aimed to assess the effects of thoracic anodal and cathodal transcutaneous spinal direct current stimulation (tsDCS) on upper- and lower-limb corticospinal excitability. Yet, despite studies assessing thoracic tsDCS influences the spinal ascending tract and reflexes, none assessed the effects of this technique over upper- and lower-limb corticomotorneuronal connections. In 14 healthy subjects we recorded motor evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) from abductor hallucis (AH) and hand abductor digiti minimi (ADM) muscles before (baseline, B), and at a different time-points (0 and 30 minutes) after anodal or cathodal tsDCS (2.5 mA, 20 minutes, T9-T11 level). In 8 of the 14 subjects we also tested the soleus H-reflex, the F-waves from AH and ADM before and after tsDCS. Both anodal and cathodal tsDCS left the upper-limb MEPs and F-wave unchanged. Conversely, while leaving lower-limb H-reflex unchanged, they oppositely affected lower-limb MEPs: whereas anodal tsDCS increased resting motor threshold (mean\ub1SEM 107.33 \ub1 3.3%, increase immediately after tsDCS, and 108.37 \ub1 3.2% increase 30 min after tsDCS compared to baseline), and had no effects on MEP area and latency, cathodal tsDCS increased MEP area (139.71 \ub1 12.9% increase immediately after tsDCS and 132.74 \ub122.0% increase 30 min after tsDCS compared to baseline) without affecting resting motor threshold and MEP latency. Our results show that tsDCS induces polarity specific changes in corticospinal excitability that last for more than 30 min after tsDCS offset and selectively affect responses in lower-limb muscles innervated by lumbar and sacral motorneurons

Promoting Health for Chronic Conditions: a Novel Approach that integrates Clinical and Personal Decision Support

Direct and indirect economic costs related to chronic diseases are increasing in Europe due to the aging of population. One of the most challenging goals is to improve the quality of life of patients affected by chronic conditions, and enhance their self-management. In this paper, we propose a novel architecture of a scalable solution, based on mobile tools, aimed to keep patients with chronic diseases away from acute episodes, to improve their quality of life and, consequently, to reduce their economic impact. Our solution aims to provide patients with a personalized tool for improving self-management, and it supports both patients and clinicians in decision-making through the implementation of two different Decision Support Systems. Moreover, the proposed architecture takes into account the interoperability and, particularly, the compliance with data transfer protocols (e.g., BT4/LE, ANT+, ISO/IEEE 11073) to ensure integration with existing devices, and with the semantic web approaches and standards related to the content and structure of the information (e.g., HL7, ICD-10 and openEHR) to ensure correct sharing of information with hospital information systems, and classification of patient behaviors (Coelition). The solution will be implemented and validated in future study