TY - GEN
T1 - Mapping the treatment journey for patients with prostate cancer
AU - Kannan, Vaishnavi
AU - Willett, Duwayne L
AU - Goad, Pamela J.
AU - Roehrborn, Claus
AU - Basit, Mujeeb A
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/24
Y1 - 2018/7/24
N2 - For patients with a chronic disease such as prostate cancer, their possible journeys through treatment can be mapped as a state diagram, which now can be implemented as an electronic health record (EHR) Care Path, generating novel data for analysis and visualization. A prostate cancer Problem List form captured treatment path assignment, treatment response, and recurrence. Patients reported their symptom burden via the Expanded Prostate Cancer Index Composite (EPIC) questionnaire, completed by patients at defined intervals either at home via mobile device or computer, or in clinic on a tablet. Patients move through the Care Path via state transitions triggered automatically via rule. New types of EHR data on each patient's journey-pathway sequence and time-in-state-automatically ensue, enabling novel analyses. In the first 3 months after go-live, 408 patients were being actively managed on the Care Path. Data visualizations display not only each individual patient's journey through the system but also (using R) an aggregated view of the patterns of all patients' journeys. Combining a Care Path modeled as a state diagram with a Problem List form and online questionnaire(s) for patient-reported outcomes proves powerful for collecting chronic disease registry data as a byproduct of patient care-including novel state sequence and state dwell time data. Ready access to such data can accelerate the 'Practice-to-Knowledge, Knowledge-to-Practice' cycles crucial to a Learning Health System.
AB - For patients with a chronic disease such as prostate cancer, their possible journeys through treatment can be mapped as a state diagram, which now can be implemented as an electronic health record (EHR) Care Path, generating novel data for analysis and visualization. A prostate cancer Problem List form captured treatment path assignment, treatment response, and recurrence. Patients reported their symptom burden via the Expanded Prostate Cancer Index Composite (EPIC) questionnaire, completed by patients at defined intervals either at home via mobile device or computer, or in clinic on a tablet. Patients move through the Care Path via state transitions triggered automatically via rule. New types of EHR data on each patient's journey-pathway sequence and time-in-state-automatically ensue, enabling novel analyses. In the first 3 months after go-live, 408 patients were being actively managed on the Care Path. Data visualizations display not only each individual patient's journey through the system but also (using R) an aggregated view of the patterns of all patients' journeys. Combining a Care Path modeled as a state diagram with a Problem List form and online questionnaire(s) for patient-reported outcomes proves powerful for collecting chronic disease registry data as a byproduct of patient care-including novel state sequence and state dwell time data. Ready access to such data can accelerate the 'Practice-to-Knowledge, Knowledge-to-Practice' cycles crucial to a Learning Health System.
KW - Biomedical informatics
KW - Clinical decision support
KW - Electronic medical records
KW - Oncology
KW - Systems modeling
UR - http://www.scopus.com/inward/record.url?scp=85051122613&partnerID=8YFLogxK
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U2 - 10.1109/ICHI.2018.00063
DO - 10.1109/ICHI.2018.00063
M3 - Conference contribution
AN - SCOPUS:85051122613
T3 - Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018
SP - 380
EP - 381
BT - Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Healthcare Informatics, ICHI 2018
Y2 - 4 June 2018 through 7 June 2018
ER -