Enhancing clinical information display to improve patient encounters: human-centered design and evaluation of the Parkinson’s Disease-BRIDGE platform (Preprint)

2021 ◽  
Author(s):  
Ethan G Brown ◽  
Erica Schleimer ◽  
Ian O Bledsoe ◽  
William Rowles ◽  
Stephan J Sanders ◽  
...  

BACKGROUND People with Parkinson’s disease (PD) have a variety of complex medical problems that require detailed review at each clinical encounter for appropriate management. Digital health solutions that efficiently integrate and display this information are needed to improve the care for people with PD. OBJECTIVE To improve the efficacy and efficiency of clinical encounters with patients with PD through development of a platform (PD-BRIDGE) with personalized clinical information from both the electronic health record (EHR) and patient-reported outcome data (PROs). METHODS Using Human Centered Design (HCD) processes, we engaged clinician and patient stakeholders in developing PD-BRIDGE through three phases: an inspiration phase involving focus groups and discussions with patients with PD, an ideation phase generating preliminary mockups for feedback, and an implementation phase testing the platform. Movement disorders neurologists and patients with PD were sent surveys asking about the technical validity, usability, and clinical relevance of PD-BRIDGE after their encounter. RESULTS The HCD process led to a platform with four modules: three modules which pulled data from the EHR – (a) a longitudinal module showing motor ratings over time, (b) a display of the most recently collected clinical rating scales, and (c) a display of relevant laboratory values and diagnoses – and (d) one module displaying motor symptom fluctuation based on an at-home diary. In the implementation phase, PD-BRIDGE was used in 17 clinical encounters for patients cared for by one of 11 movement disorders neurologists. Most patients felt that PD-BRIDGE facilitated communication with their clinician (83%) and helped them understand their disease trajectory (65%) and their clinician’s recommendations (65%). Neurologists felt that PD-BRIDGE improved their ability to understand the patient’s disease course (75% of encounters), supported clinical care recommendations (87%), and helped them communicate with their patient (81%). In terms of improvements, neurologists noted that data in PD-BRIDGE were not exhaustive in 62% of encounters. CONCLUSIONS Integrating clinically relevant information from EHR and PRO data into a visually efficient platform (PD-BRIDGE) can facilitate clinical encounters with people with PD. Developing new modules with more disparate information could improve these complex encounters even further.

2009 ◽  
Vol 24 (5) ◽  
pp. 635-646 ◽  
Author(s):  
Marian L. Evatt ◽  
K. Ray Chaudhuri ◽  
Kelvin L. Chou ◽  
Ester Cubo ◽  
Vanessa Hinson ◽  
...  

2010 ◽  
Vol 25 (7) ◽  
pp. 805-822 ◽  
Author(s):  
Joseph H. Friedman ◽  
Guido Alves ◽  
Peter Hagell ◽  
Johan Marinus ◽  
Laura Marsh ◽  
...  

2011 ◽  
Vol 26 (11) ◽  
pp. 1985-1992 ◽  
Author(s):  
Anne Pavy-Le Traon ◽  
Gerard Amarenco ◽  
Susanne Duerr ◽  
Horacio Kaufmann ◽  
Heinz Lahrmann ◽  
...  

2010 ◽  
Vol 8 (1) ◽  
pp. 61 ◽  
Author(s):  
Ida Knutsson ◽  
Helena Rydström ◽  
Jan Reimer ◽  
Per Nyberg ◽  
Peter Hagell

2014 ◽  
Vol 27 (1) ◽  
pp. 33-37 ◽  
Author(s):  
Tuba Özcan ◽  
Erdal Benli ◽  
Esra Yancar Demir ◽  
Feriha Özer ◽  
Yasemin Kaya ◽  
...  

ObjectiveIn this study, we aimed to find out whether sexual dysfunction in patients with Parkinson’s Disease (PD) was associated to PD-related disability and whether this relationship was modulated by depressive and anxiety symptoms.MethodsEighty-nine consecutive patients with idiopathic PD who attended to our movement disorders outpatient clinics between January 2011 and June 2014 were included in this study. The diagnosis of PD was confirmed by a movement disorders specialists in Neurology, according to UK Parkinson’s Disease Society Brain Bank Criteria. The Unified PD Rating Scale (UPDRS) motor was used to assess motor disability and Hoehn and Yahr stage (H&Y) was used to establish disease severity. Cognitive function was assessed by the Mini-Mental State Examination. Patients were also administered the Hamilton depression (HAMD) and anxiety (HAMA) rating scales. The sexual functions of the patients were rated by applying the Turkish version of the Arizona Sexual Experiences Scale (ASEX).ResultsThe mean age at the time of the study visit was 67.74±9.05. Male/female ratio was 1.87. Mean UPDRS total was 29.06±13.96 and mean UPDRS motor was 17.62±9.07. Mean HAMD score was 13.92±10.86, 58.4% of the patients had minor or major depression; and mean HAMA score was 7.94±6.49, 56.2% of the patients had minor or major anxiety. The mean ASEX score was 18.54±7.27 out of a maximum of 30. ASEX total scores were correlated with age, H&Y stage and HAMA scores. Age and also age at onset were correlated with ASEX subdomains except sexual desire. There was no correlation between disease duration and ASEX subdomains. UPDRS motor score was correlated with erection/lubrication. HAMD was only correlated with orgasm satisfaction. HAMA score was correlated with stimulation and orgasm.ConclusionIn patients with PD, there may be a common factor that modulates both depression, anxiety and sexual function. Further studies are needed to clarify the exact relationship.


2019 ◽  
Vol 19 (7) ◽  
pp. 1022-1031 ◽  
Author(s):  
Paula D. Cebrián ◽  
Omar Cauli

Background: Many neurological disorders lead to institutionalization and can be accompanied in their advanced stages by functional impairment, and progressive loss of mobility, and cognitive alterations. Objective: We analyzed the relationship between functional impairment and cognitive performance and its related subdomains in individuals with Parkinson’s disease, Alzheimer’s disease accompanied by motor dysfunction, and with other neurological disorders characterized by both motor and cognitive problems. Methods: All participants lived in nursing homes (Valencia, Spain) and underwent cognitive evaluation with the Mini-Mental State Examination; functional assessment of independence in activities of daily living using the Barthel score and Katz index; and assessment of mobility with the elderly mobility scale. Results: The mean age of the subjects was 82.8 ± 0.6 years, 47% of the sample included individuals with Parkinson’s disease, and 48 % of the sample presented severe cognitive impairment. Direct significant relationships were found between the level of cognitive impairment and functional capacity (p < 0.01) and mobility (p < 0.05). Among the different domains, memory impairment was not associated with altered activities of daily living or mobility. The functional impairment and the risk of severe cognitive impairment were significantly (p<0.05) higher in female compared to male patients. Among comorbidities, overweight/obesity and diabetes were significantly (p < 0.05) associated with poor cognitive performance in those individuals with mild/moderate cognitive impairment. Conclusion: In institutionalized individuals with movement disorders there is an association between functional and cognitive impairment. Reduction of over-weight and proper control of diabetes may represent novel targets for improving cognitive function at such early stages.


2021 ◽  
pp. 1-6
Author(s):  
Matt Landers ◽  
Suchi Saria ◽  
Alberto J. Espay

The use of artificial intelligence (AI) to help diagnose and manage disease is of increasing interest to researchers and clinicians. Volumes of health data are generated from smartphones and ubiquitous inexpensive sensors. By using these data, AI can offer otherwise unobtainable insights about disease burden and patient status in a free-living environment. Moreover, from clinical datasets AI can improve patient symptom monitoring and global epidemiologic efforts. While these applications are exciting, it is necessary to examine both the utility and limitations of these novel analytic methods. The most promising uses of AI remain aspirational. For example, defining the molecular subtypes of Parkinson’s disease will be assisted by future applications of AI to relevant datasets. This will allow clinicians to match patients to molecular therapies and will thus help launch precision medicine. Until AI proves its potential in pushing the frontier of precision medicine, its utility will primarily remain in individualized monitoring, complementing but not replacing movement disorders specialists.


2001 ◽  
Vol 49 (6) ◽  
pp. 821-821
Author(s):  
Ronald F. Pfeiffer

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