{"doi":"10.1002/mdc3.13135","title":"Toward <scp>e‐Scales</scp>: Digital Administration of the International Parkinson and Movement Disorder Society Rating Scales","abstract":"Medicine is becoming increasingly digital with widespread use of electronic devices including tablets, smartphones, and online platforms for collecting health-related data.1 The digitalization of medicine has the potential to reduce the burden of care and make standard clinical data available in real-time for clinical and research purposes2, 3 while lowering study duration and costs. One consequence of this digitalization is the electronic adaptation of validated paper-based clinical scales (e-scales). The International Parkinson's Disease and Movement Disorders Society (MDS) has led the development of clinical rating scales of movement disorders for both clinical and research settings. Rating scales are standardized instruments that provide a common language to quantify disease severity and progression, measure the response to interventions, and ensure intra- and inter-individual comparability.4 A practical advantage of clinical scales is the integration of multiple manifestations into a single scoring system.5 MDS scales have demonstrated satisfactory clinimetric properties6, 7 and an important example is the MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS).8 Despite the increasing importance of patient-reported outcome measures that reflect the functional status of the patient,9 the MDS-UPDRS has been used as primary endpoint in more than 180 clinical studies on Parkinson disease in the last 5 years (source: clinicaltrials.gov). Digitization of clinical scales must guarantee that the e-scale's output preserves the original clinimetric properties of the paper version. The use of e-scales has many advantages, such as readability, accessibility, scalability, accuracy, and completeness of data collection. Additionally, e-scales may enable easier remote administration, real-time monitoring of the data by clinicians and researchers, as well as prompt feedback to patients and study participants. Certain MDS-owned scales are clinician-rated (eg MDS-UPDRS-III or the MDS-Non-Motor Rating Scale [MDS-NMS]),8, 10 while others are patient-rated (eg MDS-UPDRS Parts 1A and 28 or the autonomic SCales for Outcomes in Parkinson's disease [SCOPA-AUT]).11 The latter category will benefit most from the remote administration of e-scales, facilitating an extension of care and research science into the home, which is also occurring in other areas of medicine.12 The MDS Rating Scales Electronic Development Committee and the MDS Taskforce on Technology have begun to promote and harmonize this “analog-to-digital” transition of rating scales and to provide recommendations for the future use of e-scales owned by the MDS. One of the first steps in the digitalization of medicine was the introduction of the electronic data capture systems (EDC) at the end of the 1960s. At that time, the scarcity of computers and their high costs limited their applicability.13 Additionally, although computers enabled the gathering of information and helped improve medical decisions, concerns that these systems could replace clinicians prevented widespread adoption.14, 15 In the 1990s the presence of more affordable computers and the introduction of online health information set the stage for wide-spread use of EDC.16 In recent years, EDC have been increasingly and efficiently used in clinical practice, industry, and research.17 In clinical settings, the digitization of clinical reports enables the integration of data for and from multi-site longitudinal databases and research studies. Information can be shared almost instantly with multiple health professionals through EDC systems, improving patient care and saving time and money.18 Furthermore, in clinical trials, digital outcome measures have been shown to be reliable and accurate.19 Electronic Case Report Forms have increased data quality and completeness, enhanced database processing, and shortened study duration.18 Further, the benefits of EDC in clinical trials have been documented by using different data coll","journal":"Movement Disorders Clinical Practice","year":2020,"id":109809,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9574,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":523732,"name":"Rebecca Fuller","orcid":"0000-0001-6545-7376","position":1,"is_corresponding":false},{"id":524491,"name":"Esther Cubo","orcid":null,"position":2,"is_corresponding":false},{"id":523733,"name":"Tiago Mestre","orcid":"0000-0002-6973-7479","position":3,"is_corresponding":false},{"id":523734,"name":"Ai Huey Tan","orcid":"0000-0002-2979-3839","position":4,"is_corresponding":false},{"id":523735,"name":"Julie C. Stout","orcid":"0000-0001-9637-8590","position":5,"is_corresponding":false},{"id":524492,"name":"Shazia Ali","orcid":null,"position":6,"is_corresponding":false},{"id":246440,"name":"Lana M. Chahine","orcid":"0000-0003-2521-7196","position":7,"is_corresponding":false},{"id":523736,"name":"Kathy Dujardin","orcid":"0000-0002-0110-574X","position":8,"is_corresponding":false},{"id":523737,"name":"Cheryl Fitzer‐Attas","orcid":"0000-0002-8709-1384","position":9,"is_corresponding":false},{"id":523738,"name":"Jinyoung Youn","orcid":"0000-0003-3350-5032","position":10,"is_corresponding":false},{"id":233022,"name":"Bastiaan R. Bloem","orcid":"0000-0002-6371-3337","position":11,"is_corresponding":false},{"id":286204,"name":"Fay B. Horak","orcid":"0000-0001-7704-5459","position":12,"is_corresponding":false},{"id":373831,"name":"Aristide Merola","orcid":"0000-0002-5587-726X","position":13,"is_corresponding":false},{"id":523739,"name":"Ralf Reilmann","orcid":"0000-0002-5904-9517","position":14,"is_corresponding":false},{"id":523740,"name":"Serene S. Paul","orcid":"0000-0002-3593-1396","position":15,"is_corresponding":false},{"id":110089,"name":"E. Ray Dorsey","orcid":"0000-0002-5140-1248","position":16,"is_corresponding":false},{"id":233023,"name":"Walter Maetzler","orcid":"0000-0002-5945-4694","position":17,"is_corresponding":false},{"id":233015,"name":"Alberto J. Espay","orcid":"0000-0002-3389-136X","position":18,"is_corresponding":false},{"id":92200,"name":"Pablo Martínez‐Martín","orcid":"0000-0003-0837-5280","position":19,"is_corresponding":false},{"id":92181,"name":"Glenn T. Stebbins","orcid":"0000-0001-7905-9336","position":20,"is_corresponding":false},{"id":480534,"name":"Álvaro Sánchez‐Ferro","orcid":"0000-0003-2461-2485","position":21,"is_corresponding":false},{"id":523731,"name":"Mariana H.G. Monje","orcid":"0000-0002-0730-4061","position":0,"is_corresponding":true}],"reference_count":45,"raw_metadata":null,"created_at":"2026-07-18T23:12:54.309019Z","pmid":"33553489","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}