Automated Quality Control for Sensor Based Symptom Measurement Performed Outside the Lab

The use of wearable sensing technology for objective, non-invasive and remote clinimetric testing of symptoms has considerable potential. However, the accuracy achievable with such technology is highly reliant on separating the useful from irrelevant sensor data. Monitoring patient symptoms using digital sensors outside of controlled, clinical lab settings creates a variety of practical challenges, such as recording unexpected user behaviors. These behaviors often violate the assumptions of clinimetric testing protocols, where these protocols are designed to probe for specific symptoms. Such violations are frequent outside the lab and affect the accuracy of the subsequent data analysis and scientific conclusions. To address these problems, we report on a unified algorithmic framework for automated sensor data quality control, which can identify those parts of the sensor data that are sufficiently reliable for further analysis. Combining both parametric and nonparametric signal processing and machine learning techniques, we demonstrate that across 100 subjects and 300 clinimetric tests from three different types of behavioral clinimetric protocols, the system shows an average segmentation accuracy of around 90%. By extracting reliable sensor data, it is possible to strip the data of confounding factors in the environment that may threaten reproducibility and replicability

A grounded theory study on the influence of sleep on Parkinson’s symptoms

Contains fulltext : 167717.pdf (publisher's version ) (Open Access)BACKGROUND: Upon awaking, many Parkinson's patients experience an improved mobility, a phenomenon known as 'sleep benefit'. Despite the potential clinical relevance, no objective correlates of sleep benefit exist. The discrepancy between the patients' subjective experience of improvement in absence of objective changes is striking, and raises questions about the nature of sleep benefit. We aimed to clarify what patients reporting subjective sleep benefit, actually experience when waking up. Furthermore, we searched for factors associated with subjective sleep benefit. METHODS: Using a standardized topic list, we interviewed 14 Parkinson patients with unambiguous subjective sleep benefit, selected from a larger questionnaire-based cohort. A grounded theory approach was used to analyse the data. RESULTS: A subset of the participants described a temporary decrease in their Parkinson motor symptoms after sleep. Others did experience beneficial effects which were, however, non-specific for Parkinson's disease (e.g. feeling 'rested'). The last group misinterpreted the selection questionnaire and did not meet the definition of sleep benefit for various reasons. There were no general sleep-related factors that influenced the presence of sleep benefit. Factors mentioned to influence functioning at awakening were mostly stress related. CONCLUSIONS: The group of participants convincingly reporting sleep benefit in the selection questionnaire appeared to be very heterogeneous, with only a portion of them describing sleep benefit on motor symptoms. The group of participants actually experiencing motor sleep benefit may be much smaller than reported in the literature so far. Future studies should employ careful inclusion criteria, which could be based on our reported data

Connectedness of healthcare professionals involved in the treatment of patients with Parkinson's disease: a social networks study

<p>Abstract</p> <p>Background</p> <p>Patients with chronic illness typically receive ambulatory treatment from multiple health professionals. Connectedness between these professionals may influence their clinical decisions and the coordination of patient care. We aimed to describe and analyze connectedness in a regional network of health professionals involved in ambulatory treatment of patients with Parkinson's disease (PD).</p> <p>Methods</p> <p>Observational study with 104 health professionals who had joined a newly established network (ParkinsonNet) were asked to complete a pre-structured form to report on their professional contacts with others in the network. Using social networks methods, network measures were calculated for the total network and for the networks of individual health professionals. We planned to test differences between subgroups of health professionals regarding 12 network measures, using a random permutation method.</p> <p>Results</p> <p>Ninety-six health professionals (92%) provided data on 101 professionals. The reciprocity of reported connections was 0.42 in the network of professional contacts. Measures characterizing the individual networks showed a wide variation; <it>e.g</it>., density varied between 0 and 100% (mean value 28.4%). Health professionals with ≥10 PD patients had higher values on 7 out of 12 network measures compare to those with < 10 PD patients (size, number of connections, two step reach, indegree centrality, outdegree centrality, inreach centrality, betweenness centrality). Primary care professionals had lower values on 11 out of 12 network measures (all but reach efficiency) compared to professionals who were affiliated with a hospital.</p> <p>Conclusions</p> <p>Our measure of professional connectedness proved to be feasible in a regional disease-specific network of health professionals. Network measures describing patterns in the professional contacts showed relevant variation across professionals. A higher caseload and an affiliation with a hospital were associated with stronger connectedness with other health professionals.</p

Personal health communities: A phenomenological study of a new health-care concept

Context: Fragmentation of care, complexity of diseases and the need to involve patients actively in their individual health care led to the development of the personal health community (PHC). In a PHC, patients can -regardless of the nature of their condition- invite all professionals that are involved in their health care process. Once gathered, the patient and health care team can exchange information about the patient's health and communicate through several functionalities, in a secured environment. Objectives: Exploring the use, first experiences and potential consequences of using PHCs in health care. Design: Qualitative phenomenological study. Participants: Eighteen respondents, consisting of women experiencing infertility (n = 5), persons with Parkinson's disease (n = 6), a gynaecologist, a fertility doctor, a fertility nurse, three Parkinson's specialist nurses and a neurologist. Results: First experiences with PHCs showed that patients use their PHC differently, dependending on their condition and people involved. Various (potential) advantages for future health care were mentioned relating to both organizational aspects of care (e.g. continuity of care) and the human side of care (e.g. personal care). Patient involvement in care was facilitated. Disadvantages were the amount of work that it took and technological issues. Conclusions: Using PHCs leads to promising improvements in both the organization of care and care experience, according to the participants in this study. They indicate that patients with different diseases and in different circumstances can benefit from these improvements. The PHC seem to be an online tool that can be applied in a personalized way. When (technically) well facilitated, it could stimulate active involvement of patients in their own health and health care. It warrants further research to study its effect on concrete health outcomes

Design and effects of outcome-based payment models in healthcare: a systematic review

Introduction: Outcome-based payment models (OBPMs) might solve the shortcomings of fee-for-service or diagnostic-related group (DRG) models using financial incentives based on outcome indicators of the provided care. This review provides an analysis of the characteristics and effectiveness of OBPMs, to determine which models lead to favourable effects. Methods: We first developed a definition for OBPMs. Next, we searched four data sources to identify the models: (1) scientific literature databases; (2) websites of relevant governmental and scientific agencies; (3) the reference lists of included articles; (4) experts in the field. We only selected studies that examined the impact of the payment model on quality and/or costs. A narrative evidence synthesis was used to link specific design features to effects on quality of care or healthcare costs. Results: We included 88 articles, describing 12 OBPMs. We identified two groups of models based on differences in design features: narrow OBPMs (financial incentives based on quality indicators) and broad OBPMs (combination of global budgets, risk sharing, and financial incentives based on quality indicators). Most (5 out of 9) of the narrow OBPMs showed positive effects on quality; the others had mixed (2) or negative (2) effects. The effects of narrow OBPMs on healthcare utilization or costs, however, were unfavourable (3) or unknown (6). All broad OBPMs (3) showed positive effects on quality of care, while reducing healthcare cost growth. Discussion: Although strong empirical evidence on the effects of OBPMs on healthcare quality, utilization, and costs is limited, our findings suggest that broad OBPMs may be preferred over narrow OBPMs