How is the Quality of PatientGenerated Health Data Managed in - - PowerPoint PPT Presentation
How is the Quality of PatientGenerated Health Data Managed in Diabetes Remote Monitoring? Robab Abdolkhani Kathleen Gray Ann Borda Ruth DeSouza Health and Biomedical Informatics Centre (HaBIC), The University of Melbourne 05 February
Robab Abdolkhani; Kathleen Gray; Ann Borda; Ruth DeSouza
Health and Biomedical Informatics Centre (HaBIC), The University of Melbourne 05 February 2019
BACKGROUN D
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(age 1899 years)
Global healthcare expenditure on people with diabetes in 2017
Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, Malanda B. IDF Diabetes Atlas: global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes research and clinical practice. 2018 Apr 1;138:271-81.
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Kitsiou S, Paré G, Jaana M, Gerber B. Effectiveness of mHealth interventions for patients with diabetes: an overview of systematic
✓ Better access to healthcare ✓ Improved quality of care ✓ Peace of mind and daily assurance ✓ Improved support, education and feedback
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Ho A, Hao M, Yu X, An T. Business model for glucose monitoring smartwatch. MT5016 Business model for Hi-Tech products. National University of Singapore. 2014
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https://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/HomeHealthandConsumer/ConsumerProducts/ArtificialPancreas/ ucm259548.htm
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https://www.freestylelibre.us
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D A T A M A N A G E M E N T ! ! ! DATA QUALITY!!!
responsible for capturing or recording these data
setting
whom they can share their health data
management process and to ensure PGHD quality
Shapiro M, Johnston D, Wald J, Mon D. Patient-generated Health Data: White Paper Prepared for the Office of the National Coordinator for Health IT by RTI International 2012. Available from: https:// www.healthit.gov/sites/default/files/rti_pghd_whitepaper_april_2012.pdf.
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HIMSS Media. Healthcare coaching: multiplying the value of wearables and patient-generated health data 2018. Available from: https:/ /2nwchq3a3ags2kj7bq20e3qv-wpengine.netdna-ssl.com/wp-content/uploads/FINAL_HIMSS_FitBit_WP_10.01.20181.pdf.
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Accessibility Accuracy Consistency Interpretation Relevancy Timeliness Institutional Environment
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METHODS
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Care Providers (CPs) (at 5 clinical settings)
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Information Professionals (IPs)
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RPM Solution Providers (SPs)
Providers
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RESULTS & DISCUSSIO N
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Data Quality Challenges during PGHD ManagementCPs
Perspectives Institutional Environment Accuracy
entry
body Inaccurate measuring
Interpretation
Complicated data visualisation Lack of PGHD integration with current EMR ( IT infrastructures, health IT staff, guidelines) No access to raw data Difficulty in accessing different portals
Accessibility Interpretation
High volume of information presented
Relevancy
Difficulty in prioritising relevant information
Timeliness
No real-time data access
PEOPLE PROCESS TECHNOLOGY
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Different devices and different data transmission standards Lack of PGHD integration with current EMR ( IT infrastructures, health IT staff, guidelines) Difficulty in accessing different portals
Data Quality Challenges during PGHD ManagementIPs
Perspectives Accessibility Institutional Environment Accessibility
Data access by hackers
Consistency
PEOPLE PROCESS TECHNOLOGY
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Lack of automation in contextual data collection
visualisation
PEOPLE PROCESS TECHNOLOGY
Data Quality Challenges during PGHD ManagementSPs
Perspectives Accuracy
Lack of PGHD integration with current EMR ( IT infrastructures, health IT staff, guidelines)
Institutional Environment Consistency
Difficulty in realising patient’s status due to inconsistent reports
Interpretation
Calibration Lack of motivation
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CONCLUSIO N
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PGHD management protocols (interoperability, terminology standards, etc.) PGHD quality guidelines Digital health literacy Collaboration, collaboration, collaboration
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rabdolkhani@student.unimelb.edu.au
https://www.hisa.org.au/blog/wearehealthinformatics/robab-abdolkhani/