10.15452/cejnm.2017.08.0009 OR Problem of fatigue in patients with multiple sclerosis
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INTRODUCTION: In order to estimate the value of interventions in multiple sclerosis (MS) - where lifetime costs and outcomes cannot be observed - outcome data have to be combined with costs. This requires that cost data be regularly updated. OBJECTIVES AND METHODS: This study is part of a cross-sectional retrospective study in 16 countries collecting data on resource consumption and work capacity, health-related quality of life (HRQoL) and prevalent symptoms for patients with MS. Descriptive analyses are presented by level of severity, in the societal perspective, in CZK 2015. RESULTS: A total of 747 patients (mean age 47 years) participated; 86% were below retirement age and of these, 49% were employed. Employment was related to disease severity, and MS affected productivity at work for 82% of those working. Overall, 92% and 66% of patients experienced fatigue and cognitive difficulties as a problem. Mean utility and annual costs were 0.832 and 257,000CZK at Expanded Disability Status Scale (EDSS) 0-3, 0.530 and 425,500CZK at EDSS 4-6.5 and 0.141 and 489,000CZK at EDSS 7-9. The average cost of a relapse was estimated at 12,600CZK. CONCLUSION: This study provides current data on MS in the Czech Republic that are important for the development of health policies.
- Klíčová slova
- Czech Republic, HRQoL, Multiple sclerosis, burden of illness, cognition, costs, fatigue,
- MeSH
- dospělí MeSH
- kvalita života * MeSH
- lidé středního věku MeSH
- lidé MeSH
- náklady na zdravotní péči statistika a číselné údaje MeSH
- osobní újma zaviněná nemocí * MeSH
- průřezové studie MeSH
- roztroušená skleróza * ekonomika epidemiologie patofyziologie terapie MeSH
- senioři MeSH
- stupeň závažnosti nemoci MeSH
- zaměstnanost statistika a číselné údaje MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika epidemiologie MeSH
OBJECTIVE: Long-term physiotherapy is of considerable benefit to patients with multiple sclerosis (MS) who have motor dysfunction or gait impairment. The aim of this study was to determine the effectiveness of a 12-week intensive circuit class therapy for patients with MS, with a wider focus on fatigue and gait ability. METHODS: A total of 46 patients with relapsing-remitting MS were divided randomly into 2 groups: 23 patients (mean Expanded Disability Status Scale (EDSS) 2.33 ± 0.74) participated in an intensive 12-week course of intensive circuit class therapy, and 23 patients (mean EDSS 2.04 ± 0.63) served as a control group. The EDSS, Timed Up and Go (TUG) test and Four-Stage Balance Test (FSBT) made up the physical testing part, supplemented by questionnaires such as the Modified Fatigue Impact Scale (MFIS), 12-Item Multiple Sclerosis Walking Scale (MSWS-12), Beck Depression Inventory (BDI) and 36-Item Short Form Survey (SF-36). RESULTS: Significant improvements were found among intensive circuit class therapy-exercising patients in FSBT (p < 0.05), TUG test (p < 0.01), MFIS (p < 0.01), BDI (p < 0.05), MSWS-12 (p < 0.05) and the 3 subscales of SF-36 after 12 weeks of intensive circuit class therapy, while there were no significant changes in the control group. CONCLUSION: Intensive circuit class therapy is an effective therapeutic approach for improving gait and balance problems in patients with MS. It has also proved to alleviate fatigue and symptoms of depression.
BACKGROUND: Despite the increasing use of remote measurement technologies (RMT) such as wearables or biosensors in health care programs, challenges associated with selecting and implementing these technologies persist. Many health care programs that use RMT rely on commercially available, "off-the-shelf" devices to collect patient data. However, validation of these devices is sparse, the technology landscape is constantly changing, relative benefits between device options are often unclear, and research on patient and health care provider preferences is often lacking. OBJECTIVE: To address these common challenges, we propose a novel device selection framework extrapolated from human-centered design principles, which are commonly used in de novo digital health product design. We then present a case study in which we used the framework to identify, test, select, and implement off-the-shelf devices for the Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) consortium, a research program using RMT to study central nervous system disease progression. METHODS: The RADAR-CNS device selection framework describes a human-centered approach to device selection for mobile health programs. The framework guides study designers through stakeholder engagement, technology landscaping, rapid proof of concept testing, and creative problem solving to develop device selection criteria and a robust implementation strategy. It also describes a method for considering compromises when tensions between stakeholder needs occur. RESULTS: The framework successfully guided device selection for the RADAR-CNS study on relapse in multiple sclerosis. In the initial stage, we engaged a multidisciplinary team of patients, health care professionals, researchers, and technologists to identify our primary device-related goals. We desired regular home-based measurements of gait, balance, fatigue, heart rate, and sleep over the course of the study. However, devices and measurement methods had to be user friendly, secure, and able to produce high quality data. In the second stage, we iteratively refined our strategy and selected devices based on technological and regulatory constraints, user feedback, and research goals. At several points, we used this method to devise compromises that addressed conflicting stakeholder needs. We then implemented a feedback mechanism into the study to gather lessons about devices to improve future versions of the RADAR-CNS program. CONCLUSIONS: The RADAR device selection framework provides a structured yet flexible approach to device selection for health care programs and can be used to systematically approach complex decisions that require teams to consider patient experiences alongside scientific priorities and logistical, technical, or regulatory constraints.
- Klíčová slova
- design thinking, device selection, human-centric design, patient centricity, remote measurement technologies, remote patient monitoring, technology selection,
- MeSH
- lidé MeSH
- technologie MeSH
- telemedicína * MeSH
- zdravotnický personál MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
