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Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

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Updated: Dec 23, 2025

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

Published on: June 30, 2014

E-health and multiple sclerosis.

Paul M Matthews¹, Valerie J Block², Letizia Leocani^3,4

¹Department of Brain Sciences and UK Dementia Research Institute Centre, Imperial College, London, UK.

Current Opinion in Neurology

|April 24, 2020

Summary

This summary is machine-generated.

E-health data and digital tools are revolutionizing multiple sclerosis (MS) care by enabling better prognosis and treatment insights. These technologies empower patients in managing their MS journey and advance disease understanding.

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The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

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Published on: June 30, 2014

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

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Published on: April 12, 2021

Home-Based Monitor for Gait and Activity Analysis

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Published on: August 8, 2019

Area of Science:

Digital Health
Neuroimmunology
Real-World Data Analysis

Background:

Digitization of clinical data and advancements in technology facilitate the analysis of real-world data.
Real-world data from patient registries and electronic health records (EHR) enhance prognostic accuracy and treatment evaluation for multiple sclerosis (MS).

Purpose of the Study:

To review current applications of e-health data and digital tools in managing multiple sclerosis (MS) care.
To highlight how digital tools are improving patient outcomes and healthcare delivery in MS.

Main Methods:

Analysis of real-world data from patient registries, digital patient-reported outcomes, and EHR.
Integration of data from wearable sensors, telemedicine, and online applications.
Application of machine learning and artificial intelligence for data analysis and decision support.

Main Results:

E-health data provide more confident prognoses and long-term safety/efficacy data for disease-modifying treatments (DMTs) in MS.
Registries facilitate data sharing for improved DMT impact and understanding of comorbidities.
Wearable sensors offer continuous performance monitoring, while telemedicine and apps expand patient self-management capabilities.
Machine learning and AI accelerate advancements in disease understanding, decision support, and self-management.

Conclusions:

E-health approaches and digital tools foster a more patient-centered learning health system for multiple sclerosis (MS).
Both healthcare professionals and patients can leverage these technologies to enhance MS care and management.