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 2019
BACKGROUN D 2
552 million 451 million by 2030 in 2017 (age 1899 years) USD 850 billion 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 3 estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes research and clinical practice. 2018 Apr 1;138:271-81.
We should bring care to patients instead of patients to care 4
Remote Patient Monitoring ✓ Better access to healthcare ✓ Improved quality of care ✓ Peace of mind and daily assurance ✓ Improved support, education and feedback 5 Kitsiou S, Paré G, Jaana M, Gerber B. Effectiveness of mHealth interventions for patients with diabetes: an overview of systematic reviews. PloS one. 2017 Mar 1;12(3):e0173160.
Ho A, Hao M, Yu X, An T. Business model for glucose monitoring smartwatch. MT5016 Business model for Hi-Tech products. National 6 University of Singapore. 2014
https://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/HomeHealthandConsumer/ConsumerProducts/ArtificialPancreas/ 7 ucm259548.htm
Flash Glucose Monitoring 8 https://www.freestylelibre.us
✓ Wearables used in diabetes RPM are medical-grade devices ✓ They are tested in terms of accuracy and safety ✓ Data is collected automatically D A T A M A N A G E M E N T ! ! ! DATA QUALITY!!! 9
Patient Generated Health Data • Patients, not clinicians, are primarily responsible for capturing or recording these data • Data are collected outside the clinical setting • Patients may choose how and with whom they can share their health data • No guidelines exist to define PGHD 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:// 10 www.healthit.gov/sites/default/files/rti_pghd_whitepaper_april_2012.pdf.
Poor Data Quality Is One of the Main Reasons for Low Adoption of PGHD in Clinical Practices HIMSS Media. Healthcare coaching: multiplying the value of wearables and patient-generated health data 2018. Available from: https:/ 11 /2nwchq3a3ags2kj7bq20e3qv-wpengine.netdna-ssl.com/wp-content/uploads/FINAL_HIMSS_FitBit_WP_10.01.20181.pdf.
Accessibility Accuracy Consistency Interpretation Relevancy Timeliness Institutional Environment 12
METHODS 13
6 • 2 Endocrinologists Care Providers (CPs) • 4 Diabetes Educators (at 5 clinical settings) 16 4 • 2 Chief Information Officers • 1 Health Informaticians Information • 1 IT managers Professionals (IPs) � � � • 1 CGM Manufacturer 6 • 2 PGHD integration Service RPM Solution Providers Providers (SPs) • 3 RPM Consultants 14
Participants asked to: • Describe PGHD management process • Discuss PGHD quality challenges 15
RESULTS & DISCUSSIO N 16
PGHD Management Process in Diabetes Remote Monitoring 17
Data Quality Challenges during PGHD Management CPs Perspectives Accessibility Institutional Accuracy Environment No access to raw data • Calibration • Errors in manual data Lack of PGHD integration Difficulty in accessing entry with current EMR ( IT different portals • Wrong application on infrastructures, health IT body Interpretation staff, guidelines) High volume of Inaccurate measuring information presented Interpretation Relevancy Complicated data Difficulty in prioritising visualisation relevant information PEOPLE Timeliness PROCESS No real-time data access 18 TECHNOLOGY
Data Quality Challenges during PGHD Management IPs Perspectives Institutional Accessibility Accessibility Environment Difficulty in accessing Data access by hackers Lack of PGHD integration different portals with current EMR ( IT Consistency infrastructures, health IT staff, guidelines) Different devices and different data transmission standards PEOPLE PROCESS 19 TECHNOLOGY
Data Quality Challenges during PGHD Management SPs Perspectives Institutional Accuracy Consistency Environment Difficulty in realising Lack of automation in Lack of PGHD integration patient’s status due to contextual data with current EMR ( IT inconsistent reports collection infrastructures, health IT Calibration staff, guidelines) Interpretation Lack of motivation • Complicated data visualisation • Lack of context PEOPLE PROCESS 20 TECHNOLOGY
21
CONCLUSIO N 22
Need for: PGHD management protocols (interoperability, terminology standards, etc.) PGHD quality guidelines Digital health literacy Collaboration, collaboration, collaboration 23
THANK YOU! MAY 2019 rabdolkhani@student.unimelb.edu.au https://www.hisa.org.au/blog/wearehealthinformatics/robab-abdolkhani/
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