TY - JOUR
T1 - Sharing annotated audio recordings of clinic visits with patients-development of the open recording automated logging system (ORALS)
T2 - Study protocol
AU - Barr, Paul J.
AU - Dannenberg, Michelle D.
AU - Ganoe, Craig H.
AU - Haslett, William
AU - Faill, Rebecca
AU - Hassanpour, Saeed
AU - Das, Amar
AU - Arend, Roger
AU - Masel, Meredith C.
AU - Piper, Sheryl
AU - Reicher, Haley
AU - Ryan, James
AU - Elwyn, Glyn
N1 - Publisher Copyright:
© Paul J Barr, Michelle D Dannenberg, Craig H Ganoe, William Haslett, Rebecca Faill, Saeed Hassanpour, Amar Das, Roger Arend, Meredith C Masel, Sheryl Piper, Haley Reicher, James Ryan, Glyn Elwyn. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 06.07.2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.
PY - 2017/7
Y1 - 2017/7
N2 - Background: Providing patients with recordings of their clinic visits enhances patient and family engagement, yet few organizations routinely offer recordings. Challenges exist for organizations and patients, including data safety and navigating lengthy recordings. A secure system that allows patients to easily navigate recordings may be a solution. Objective: The aim of this project is to develop and test an interoperable system to facilitate routine recording, the Open Recording Automated Logging System (ORALS), with the aim of increasing patient and family engagement. ORALS will consist of (1) technically proficient software using automated machine learning technology to enable accurate and automatic tagging of in-clinic audio recordings (tagging involves identifying elements of the clinic visit most important to patients [eg, treatment plan] on the recording) and (2) a secure, easy-to-use Web interface enabling the upload and accurate linkage of recordings to patients, which can be accessed at home. Methods: We will use a mixed methods approach to develop and formatively test ORALS in 4 iterative stages: case study of pioneer clinics where recordings are currently offered to patients, ORALS design and user experience testing, ORALS software and user interface development, and rapid cycle testing of ORALS in a primary care clinic, assessing impact on patient and family engagement. Dartmouth's Informatics Collaboratory for Design, Development and Dissemination team, patients, patient partners, caregivers, and clinicians will assist in developing ORALS. Results: We will implement a publication plan that includes a final project report and articles for peer-reviewed journals. In addition to this work, we will regularly report on our progress using popular relevant Tweet chats and online using our website, www.openrecordings.org. We will disseminate our work at relevant conferences (eg, Academy Health, Health Datapalooza, and the Institute for Healthcare Improvement Quality Forums). Finally, Iora Health, a US-wide network of primary care practices (www.iorahealth.com), has indicated a willingness to implement ORALS on a larger scale upon completion of this development project. Conclusions: Upon the completion of this project we will have developed a novel recording system that will be ready for large-scale testing. Our long-term goal is for ORALS to seamlessly fit into a clinic's and patient's daily routine, increasing levels of patient engagement and transparency of care.
AB - Background: Providing patients with recordings of their clinic visits enhances patient and family engagement, yet few organizations routinely offer recordings. Challenges exist for organizations and patients, including data safety and navigating lengthy recordings. A secure system that allows patients to easily navigate recordings may be a solution. Objective: The aim of this project is to develop and test an interoperable system to facilitate routine recording, the Open Recording Automated Logging System (ORALS), with the aim of increasing patient and family engagement. ORALS will consist of (1) technically proficient software using automated machine learning technology to enable accurate and automatic tagging of in-clinic audio recordings (tagging involves identifying elements of the clinic visit most important to patients [eg, treatment plan] on the recording) and (2) a secure, easy-to-use Web interface enabling the upload and accurate linkage of recordings to patients, which can be accessed at home. Methods: We will use a mixed methods approach to develop and formatively test ORALS in 4 iterative stages: case study of pioneer clinics where recordings are currently offered to patients, ORALS design and user experience testing, ORALS software and user interface development, and rapid cycle testing of ORALS in a primary care clinic, assessing impact on patient and family engagement. Dartmouth's Informatics Collaboratory for Design, Development and Dissemination team, patients, patient partners, caregivers, and clinicians will assist in developing ORALS. Results: We will implement a publication plan that includes a final project report and articles for peer-reviewed journals. In addition to this work, we will regularly report on our progress using popular relevant Tweet chats and online using our website, www.openrecordings.org. We will disseminate our work at relevant conferences (eg, Academy Health, Health Datapalooza, and the Institute for Healthcare Improvement Quality Forums). Finally, Iora Health, a US-wide network of primary care practices (www.iorahealth.com), has indicated a willingness to implement ORALS on a larger scale upon completion of this development project. Conclusions: Upon the completion of this project we will have developed a novel recording system that will be ready for large-scale testing. Our long-term goal is for ORALS to seamlessly fit into a clinic's and patient's daily routine, increasing levels of patient engagement and transparency of care.
KW - Audiovisual AIDS
KW - Caregivers
KW - Disease management
KW - Machine learning
KW - Patient engagement
KW - Patients
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U2 - 10.2196/resprot.7735
DO - 10.2196/resprot.7735
M3 - Article
AN - SCOPUS:85027840416
SN - 1929-0748
VL - 6
JO - JMIR Research Protocols
JF - JMIR Research Protocols
IS - 7
M1 - e121
ER -