Devices for remote monitoring of Parkinson’s disease

There is uncertainty about how much remote monitoring devices would affect resource use in the NHS and personal social services. Some impacts may not have been included in the external assessment group's (EAG) model because of a lack of data (see section 3.12), including resource use related to carers (see section 3.13). Adopting the technologies may change how care is provided (see section 3.4) so their effect on resources is hard to estimate without direct data. So, the committee recommended collecting data on how much using the devices affects resource use, to inform cost-effectiveness estimates. Data on time dedicated to training and spent reviewing device results should also be collected. The broader impact on services provided by Parkinson's specialist teams and carers should be considered.

How much using remote monitoring devices to guide decisions about care affects symptoms, and therefore health-related quality of life, is uncertain. How long after using the devices any impact would last is also uncertain. This had a sizeable influence on cost-effectiveness estimates (see section 3.10). Data on this came from studies that did not represent likely NHS practice (see section 3.6), which is itself uncertain (see section 3.3), and from assumptions made by the EAG because of lack of data. For its model, the EAG used a published algorithm from Chandler et al. (2020) to estimate quality-adjusted life years (QALYs) from the Unified Parkinson's Disease Rating Scale (UPDRS) domain scores. The clinical experts said that health-related quality of life questionnaires like the PDQ‑39 are increasingly used in trials to assess health-related quality of life for people with Parkinson's disease. The committee also recognised that the effect of the devices on the health-related quality of life of carers had not been included in the EAG's model because of a lack of data (see section 3.13).

How frequently the remote monitoring devices were modelled as being used substantially affected the cost-effectiveness estimates in the EAG's model (see section 3.9). There are many ways the devices could be used in the NHS (see section 3.3) and no data was available to compare different approaches. So, it is currently not possible to highlight particular approaches that are likely to be more clinically and cost effective. Centres using the devices should therefore collect data on how often they are used and under what circumstances. For example, regularly in advance of scheduled review appointments, to indicate when such appointments are needed, or targeted to people having issues with symptoms. This will help assess the clinical and cost effectiveness of the different uses of the devices in NHS practice.