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Abstract Background An innovative, integrative care model for people with Parkinson (PRIME Parkinson) has gradually been implemented in a selected region of the Netherlands since 2021. A prospective evaluation of this model (PRIME-NL study) was initiated in parallel, spanning the year prior to implementation (baseline) and the implementation period. Following publication of the original study protocol, the COVID-19 crisis delayed implementation of the full PRIME Parkinson care model by two years and hampered the recruitment of study participants. Objective To describe which methodological adjustments were made to the study protocol because of these developments. Methods We compare various outcomes between a region where PRIME Parkinson care was implemented (innovation region) versus the rest of the Netherlands (usual care region). We use healthcare claims data of virtually all people with Parkinson in the Netherlands and annual questionnaires in a representative subsample of 984 people with Parkinson, 566 caregivers and 192 healthcare professionals. Four major methodological adjustments had to be made since publication of the original protocol. First, we extended the evaluation period by two years. Second, we incorporated annual process measures of the stage of implementation of the new care model. Third, we introduced a real-time iterative feedback loop of interim results to relevant stakeholders. Fourth, we updated the statistical analysis plan. Discussion This manuscript provides transparency in how the design and analyses of the evaluation study had to be adapted to control for external influences in a dynamic environment, including eruption of the COVID-19 crisis. Our solutions could serve as a template for evaluating other complex healthcare interventions in a dynamic environment.

Abstract Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson’s disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant’s own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.

BackgroundPhysiotherapy for persons with Parkinson's disease (PwPD) could benefit from objective and continuous tracking of physical activity and falls in daily life.ObjectivesWe designed a remote monitoring system for this purpose and describe the experiences of PwPD and physiotherapists who used the system in daily clinical practice.MethodsTwenty-one PwPD (15 men) wore a sensor necklace to passively record physical activity and falls for 6 weeks. They also used a smartphone app to self-report daily activities, (near-)falls and medication intake. They discussed those data with their PD-specialized physiotherapist (n = 9) during three regular treatment sessions. User experiences and aspects to be improved were gathered through interviews with PwPD and physiotherapists, resulting in system updates. The system was evaluated in a second pilot with 25 new PwPD (17 men) and eight physiotherapists.ResultsWe applied thematic analysis to the interview data resulting in two main themes: usability and utility. First, the usability of the system was rated positively, with the necklace being easy to use. However, some PwPD with limited digital literacy or cognitive impairments found the app unclear. Second, the perceived utility of the system varied among PwPD. While many PwPD were motivated to increase their activity level, others were not additionally motivated because they perceived their activity level as high. Physiotherapists appreciated the objective recording of physical activity at home and used the monitoring of falls to enlarge awareness of the importance of falls for PwPD. Based on the interview data of all participants, we drafted three user profiles for PwPD regarding the benefits of remote monitoring for physiotherapy: for profile 1, a monitoring system could act as a flagging dashboard to signal the need for renewed treatment; for profile 2, a monitoring system could be a motivational tool to maintain physical activity; for profile 3, a monitoring system could passively track physical activity and falls at home. Finally, for a subgroup of PwPD the burdens of monitoring will outweigh the benefits.ConclusionsOverall, both PwPD and physiotherapists underline the potential of a remote monitoring system to support physiotherapy by targeting physical activity and (near-)falls. Our findings emphasize the importance of personalization in remote monitoring technology, as illustrated by our user profiles.