The Parkinson’s disease waiting room of the future: measurements, not magazines

Abstract

Utilizing technology to precisely quantify Parkinson’s disease motor symptoms has evolved over the past 50 years from single point in time assessments using traditional biomechanical approaches to continuous monitoring of performance with wearables. Despite advances in the precision, usability, availability and affordability of technology, the “gold standard” for assessing Parkinson’s motor symptoms continues to be a subjective clinical assessment as none of these technologies have been fully integrated into routine clinical care of Parkinson’s disease patients. To facilitate the integration of technology into routine clinical care, the Develop with Clinical Intent (DCI) model was created. The DCI model takes a unique approach to the development and integration of technology into clinical practice by focusing on the clinical problem to be solved by technology rather than focusing on the technology and then contemplating how it could be integrated into clinical care. The DCI model was successfully used to develop the Parkinson’s disease Waiting Room of the Future (WROTF) within the Center for Neurological Restoration at the Cleveland Clinic. Within the WROTF, Parkinson’s disease patients complete the self-directed PD-Optimize application on an iPad. The PD-Optimize platform contains cognitive and motor assessments to quantify PD symptoms that are difficult and time-consuming to evaluate clinically. PD-Optimize is completed by the patient prior to their medical appointment and the results are immediately integrated into the electronic health record for discussion with the movement disorder neurologist. Insights from the clinical use of PD-Optimize has spurred the development of a virtual reality technology to evaluate instrumental activities of daily living in PD patients. This new technology will undergo rigorous assessment and validation as dictated by the DCI model. The DCI model is intended to serve as a health enablement roadmap to formalize and accelerate the process of bringing the advantages of cutting-edge technology to those who could benefit the most: the patient.

Older adults exhibit declines in instrumental activities of daily living during a virtual grocery shopping task

“…Important factors in scaling the CC-VRS will be the meaningfulness of outcomes to providers and patients and thoughtful integration of the technology into the clinical workflow. Regarding the latter, the CC-VRS was developed from the onset with clinical integration as a goal using the Develop with Clinical Intent model that we have recently published (Alberts, et al, 2023).…”

Smart Waiting Room: A Systematic Literature Review and a Proposal

“…Year Patient Type Health Condition [32] 2009 General - [22] 2013 General - [23] 2014 Women Fertility [30] 2014 Women Diabetes and pregnancy [24] 2017 General - [20] 2019 General - [25] 2019 General Chemotherapy [33] 2019 General Chronic conditions [31] 2020 General Rheumatoid arthritis [21] 2020 General - [26] 2020 Pediatric Dental surgery [27] 2022 General - [28] 2022 Women Abnormal uterine bleeding [34] 2023 65+ aged patients - [35] 2023 General Parkinson disease [29] 2023 General -Most of the papers addressed a general type of patient, i.e., the solutions described in such works are not dedicated to a specific portion of the population (11 papers). However, even if these solutions address a general patient, some of them tackle a specific health condition, impairment, or disability (four works).…”

“…The results of the survey related to technologies are reported in Table 4. [21,23,25,31,[33][34][35], while 3 works provided some sort of recommendation or decision process supported by AI [21,27,33], 3 works foresaw the adoption of patients' EHRs [31,34,35], 3 papers relied on virtual reality applications in different ways [26,28,29,35], and a total of 3 articles adopted technologies to conduct biomedical measurements on patients [30,32,34]. It is also worth observing that IoT technologies are the core of only one work [20].…”

“…Applicative Context [32] 2009 Unspecified waiting room [22] 2013 Primary care waiting room [23] 2014 Specific clinical practice waiting room (family planning) [30] 2014 Specific clinical practice waiting room (obstetric) [24] 2017 Primary care waiting room [20] 2019 Laboratory waiting room (blood testing) [25] 2019 Specific clinical practice waiting room (cancer treatment) [33] 2019 Primary care waiting room [31] 2020 Specific clinical practice waiting room (rheumatic) [21] 2020 Primary care waiting room [26] 2020 Specific clinical practice waiting room (dental) [27] 2022 Emergency room [28] 2022 Specific clinical practice waiting room (gynecological) [34] 2023 Primary care waiting room [35] 2023 Specific clinical practice waiting room (neurologic) [29] 2023 Hospital waiting room…”

“…It is also interesting to observe that those works adopting AI [21,27,33] provide some sort of decision support via the assessment of PROs, taking into account their symptoms. However, none of these smart waiting rooms taps into the potential of EHRs, as this technology is used only as the "destination" for data acquired by the smart solutions [31,34,35]; instead of exploiting patients' health condition summarized in EHRs to provide personalized solutions, EHRs are perceived as the virtual place to store data acquired via tablet applications or sensors.…”