The Aperio Blog

Implementing Patient Wearables in Clinical Trials:

An Illustration Using Gait Analysis in Parkinson’s Disease

Melissa HancockDirector, eClinical Technology
January 25, 2022

Much has been written about the overall benefits and challenges of implementing patient wearables in clinical trials. It has become one of the latest ‘hot topics’ in an industry that – let’s face it – doesn’t easily embrace change.  But what happens when you take the discussion to the next level and look at the realities of practically and successfully implementing and deploying patient wearables in your clinical trial?

Which comes first, the patient wearable or the clinical trial?

In its publication, The Playbook: Digital Clinical Measures[i], The Digital Medicine Society (DiMe) has described a common issue this way—we attend a conference, see a demonstration for an exciting new patient wearable technology, decide to order several units, and then decide later how we’re going to use it in a trial.

To successfully deploy patient wearables, the clinical trial must come first.  More specifically, you must decide what to measure and why. The main reason is to ensure you’re collecting clinically relevant data, not data just for data’s sake. Data is expensive – both from a technology standpoint and the resources required from multiple stakeholders.  When you’re talking to a site about a new patient wearable they will need to incorporate into their visits, you need to have a better reason for using it than ‘it seems like a cool gadget!’

Clinical Trial Design: The decision-making process

Let’s illustrate the thinking process around the use of patient wearables that might occur during clinical trial design, using gait analysis in a Parkinson’s Disease trial as a potential assessment for wearable use.  Examples of measures for gait analysis could be time between steps on each foot, the period the foot is in contact with the surface, the period when the foot is airborne, the period during which both feet are in contact with the surface, and more.

One traditional method for collecting this data is video recording the action and interpreting the results.  This would typically require patients to travel to an office for assessment, and does include some challenges –  potential for equipment malfunctions, operator error, subjective video interpretation, and the requirement for precise time measures. The interpretation data would then be entered into a database by site data entry staff or sent to a vendor for a centralized evaluation and entry.

So what is an alternative option for collecting this data? Could it be the use of patient wearables? This would allow the patient to remain at home for assessments, potentially allowing for more time points to be collected. With competition for clinical trial participants at an all-time high, this option could improve the ability to recruit and retain patients by reducing on-site visits. It could create efficiencies by eliminating the need for video recording and review, as well as the accompanying subjective interpretation of that video. Many wearables now have cloud-based data portals, with data uploaded in real-time via connections with phones or tablets. This could reduce the drain on staff not only for the video recording/interpretation, but data entry into EDC as well.

Patient Wearable Selection: Considerations

Once it’s decided to use patient wearables in the clinical trial, the next step is to decide which wearable will deliver the needed data.

Parkinson’s Disease is a progressive disease that causes both physical and cognitive impairment, and the patient population may be elderly and/or require caregivers. Taking into consideration a wearable that can increase convenience and comfort but not be so ‘technical’ that it is burdensome in other ways will be important.  Other things to consider include:

Specific measurement: For gait analysis in Parkinson’s Disease, the precise measurement of interest (e.g., amount of pressure on different parts of the feet, the roll of the gait, stumbling or tripping, freezing in place, and more) will determine the patient wearable—whether an off-the-shelf or purpose-built device—that will deliver the precision and consistency of data needed.

Validation: Has the device been validated for the endpoint at hand and confirmed as being suitable for its intended purpose and patient population?

Data upload and integration: Is human intervention needed to upload the data or is it automated? Is a smart device needed to pair to an application to upload and view data in real time, and if so, what are the connectivity requirements and will the device be BYOD or trial-specific? What data security/privacy measures are in place? How is the data integrated into the EDC for reporting and analysis?

Site considerations:  What additional technologies will be required? What are the logistics involved for the site to provide the wearable to the patient and train them for its use?

Data Collection, Management, Reporting, and Analysis

One risk with patient wearables is the potential for a continuous data stream, which could provide more data than is necessary for the endpoint. It is important to identify the specific data required for study endpoint(s) and focus collection and integration on data required to meet your trial objectives – don’t get distracted by the extra noise! In addition to collecting the assessment at hand, the wearable will also need to collect metadata providing context around the assessment (e.g., date and time stamps). The data needs to be consistent, attributable, and machine readable (e.g., ASCII, CSV, EXCEL, JSON, etc.), so it can be integrated with backend data for analysis.

Visibility into the data via centralized and continuous data monitoring is key to confirming data quality and ensuring there are no issues that may impact the validity of the clinical trial. Ensure the clinical operations team and site staff can safely view data and generate reports throughout the clinical trial. An application programming interface (API) can provide a secure way to view the data without compromising the integrity of the data.

Conclusion

Implementing patient wearables into a clinical trial is an important element in the shift toward decentralized clinical trials. To deploy them successfully, it is important to start with the end in mind. With so many factors to consider, working with experienced technology consultants can help you think through all aspects of ever-evolving clinical trial technology and make the decisions that are best for you, your sites and the patients.

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[1] The Playbook: Digital Clinical Measures, Digital Medicine Society, playbook.dimesociety.org, accessed 3 Sept 2021.

Melissa Hancock

Director, eClinical Technologies

If you need technology for your trial, Melissa knows about it. As Aperio’s go-to trial technology expert, Melissa vets technology vendors, evaluates data integration capabilities and provides exciting technology solutions for Aperio’s clinical trials.

Melissa has over 20 years of clinical research experience and has led both Data Management and Project Programming teams. She is an accredited EDC programmer for Medidata (Rave EDC) and IBM Clinical Development. With this extensive knowledge in programming, she is able to collaborate with our clients and study teams on best practices for data collection following the latest standards and maintain CDISC compliant data structures, as well as the complexities of integrating technologies for capturing patient-reported data, vendor data and various clinical trial management systems.

In her free time, Melissa enjoys traveling to far off lands, cheering on the Durham Bulls and Carolina Hurricanes and attending live theater productions.

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