Systems for electronic documentation and sharing of advance care planning preferences: a scoping review

Digital approaches to support advance care planning (ACP) documentation and sharing are increasingly being used, with a lack of research to characterise their design, content, and use. This study aimed to characterise how digital approaches are being used to support ACP documentation and sharing internationally. A scoping review was performed in accordance with the JBI (formerly Joanna Briggs Institute) guidelines and the PRISMA 2020 checklist, prospectively registered on Open Science Framework (https://osf.io/xnrg3). MEDLINE, EMBASE, PsycINFO, ACM Digital, IEEE Xplore and CINAHL were searched in February 2023. Only publications in English, published from 2008 onwards were considered. Eligibility criteria included a focus on ACP and electronic systems. Out of 2,393 records, 34 reports were included, predominantly from the USA (76.5%). ACP documentation is typically stored in electronic health records (EHRs) (67.6%), with a third (32.4%) enabling limited patient access. Non-standard approaches (n = 15;44.1%) were the commonest study design of included reports, with outcome measures focusing on the influence of systems on the documentation (i.e. creation, quantity, quality, frequency or timing) of ACP information (n = 23;67.6%). Digital approaches to support ACP are being implemented and researched internationally with an evidence base dominated by non-standard study designs. Future research is needed to extend outcome measurement to consider aspects of care quality and explore whether the content of existing systems aligns with aspects of care that are valued by patients

POS1596-HPR IMPACT OF THE HEALTH STATUS ON THE WILL TO USE TELEMEDICINE AMONG RHEUMATIC PATIENTS: SECONDARY ANALYSIS OF DATA FROM A GERMAN NATIONWIDE SURVEY

International audienceBackground Telemedicine (TM) is an effective tool to supplement rheumatology care and address staff shortages [1]. A previous study revealed that patients’ willingness to try TM is closely connected to their perceived health status [2]. Yet, it is still unclear which factors are associated with patients’ motivation to use TM according to the perceived health status. Objectives The study aimed to identify factors that determine patients’ willingness to try TM (TM-try) and their wish that their rheumatologists offer TM services (TM-wish) according to their perceived health status. Methods We conducted a secondary analysis of data from a German nationwide cross-sectional survey among patients with rheumatic and musculoskeletal diseases (RMDs) [3]. Bayesian univariate logistic regression analysis was applied to the data in order to determine which factors were associated with TM-try and TM-wish, respectively. Predictor variables (covariates) studied individually included sociodemographic factors (e.g., age, sex) and health characteristics (e.g., health status). All the variables positively and negatively associated with TM-try and TM-wish in the univariate analyses were then considered for Bayesian model averaging analysis (BMA) after a selection based on the variance inflation factor (≤ 2.5) to identify determinants of TM-try and TM-wish, respectively. Results Regarding TM-try, a total of 26 (30.6%) and 45 (27.1%) variables/factors (answers to the 25 questions), out of 85, were found to be positively or negatively associated (ROPE% ≤ 5%) with a perceived okay and bad/very bad health statuses, respectively. Regarding TM-wish, a total of 14 (16.5%) variables/factors (answers to the 25 questions), out of 85, were found to be positively or negatively associated for both a perceived okay and bad/very bad health statuses, respectively. A total of 19 and 13 determinant factors (Figure 1) were identified for TM-try and TM-wish, respectively. Patients with a perceived bad/very bad health status that did not want to try TM were more frequently 60-69 years old, living 10-15 km from the GP’s office, being diagnosed with rheumatoid arthritis and had more often less TM knowledge than patients wanting to try TM. Patients with a perceived bad/very bad health status that did wish that TM services were offered by rheumatologist were more frequently older, not documenting their health status and more being diagnosed with osteoporosis than patients wishing that TM services were offered by RM. Conclusion Our results indicate that RMD knowledge, age, RMD type, health status documentation and access to technical equipment and infrastructure influence RMD patients’ motivation to use telehealth. References [1]Miloslavsky EM, Bolster MB. Addressing the rheumatology workforce shortage: A multifaceted approach. Semin Arthritis Rheum. 2020 Aug;50(4):791-796. doi: 10.1016/j.semarthrit.2020.05.009. [2]Muehlensiepen F, Petit P, Knitza J, Welcker M, Vuillerme N. Factors associated with Telemedicine Factors associated with Telemedicine Usage among Rheumatic Patients: Secondary Analysis of Data from a German Nationwide Survey. J Med Internet Res. 2022 Nov 16. doi: 10.2196/40912 [Epub ahead of print] [3]Muehlensiepen F, Knitza J, Marquardt W, May S, Krusche M, Hueber A, et al. Opportunities and Barriers of Telemedicine in Rheumatology: A Participatory, Mixed-Methods Study. Int. J. Environ. Res. Public Health 2021;18(24):13127. doi: 10.3390/ijerph182413127. Figure 1. Profile of RMD patients motivated to try TM vs. RMD patients not motivated to try TM Acknowledgements FM & PP contributed equally and share the first authorship. The authors would like to thank the participants in the survey and all other supporters of TeleRheumaBB. We also owe special gratitude to KV Consult- und Managementgesellschaft mbH, which initiated the study in the first place. The present work is part of the PhD thesis of F.M. (AGEIS, Université Grenoble Alpes, Grenoble, France). Disclosure of Interests Felix Muehlensiepen Speakers bureau: Novartis, Paid instructor for: Novartis, Consultant of: Novartis, Grant/research support from: AbbVie, Novartis, Pascal Petit: None declared, Johannes Knitza Speakers bureau: Abbvie, Novartis, Medac, Sanofi, Amgen, UCB, Consultant of: Abbvie, Novartis, Lilly, Medac, BMS, Sanofi, Amgen, Gilead, UCB, ABATON, GSK, Werfen, Vila Health, Böhringer Ingelheim, Janssen, Galapagos, Chugai, Grant/research support from: Abbvie, Novartis, Thermo Fisher, UCB, ABATON, Sanofi, DFG, EIT Health, Martin Welcker Shareholder of:/, Speakers bureau: Abbvie, Actelion, Amgen, Biogen,BMS, Berlin Chemie, Celgene, Galapagos, Gilead, GSK, Hexal, Janssen, Medac, MSD, Mundipharma, Mylan, Novartis, Pfizer, Roche, Sanofi, SOBI, UCB, Consultant of: Abbvie, Actelion, Aescu, Amgen, Cel- gene, Hexal, Janssen, Medac, Novartis, Pfizer, Sanofi, UCB, Grant/research support from: Novartis, Abbvie, Nicolas Vuillerme: None declared

AB1597 DETERMINANTS OF TELEMEDICINE ACCEPTANCE AMONG PATIENTS WITH RHEUMATOID ARTHRITIS: SECONDARY ANALYSIS OF DATA FROM A GERMAN NATIONWIDE SURVEY

International audienceBackground Telemedicine (TM) is an effective tool to supplement rheumatology care and address staff shortages [1]. A previous study revealed that patients’ willingness to try TM is closely connected to their rheumatic and musculoskeletal disease (RMD) [2]. Yet, it is still unclear which factors are associated with patients’ willingness to try TM among specific RMD groups, such as the most prevalent rheumatic arthritis (RA). Objectives To identify factors that determine the willingness to try TM (TM-try) among patients diagnosed with RA. Methods We conducted a secondary analysis of data from a German nationwide cross-sectional survey [3] among patients with RA. Bayesian univariate logistic regression analysis was applied to the data in order to determine which factors were associated with TM-try. Predictor variables (covariates) studied individually included sociodemographic factors (e.g., age, sex) and health characteristics (e.g., health status). All the variables positively and negatively associated with TM-try in the univariate analyses were then considered for Bayesian model averaging analysis (BMA) after a selection based on the variance inflation factor (≤ 2.5) to identify determinants of TM-try. Results A total of 22 variables/factors (22/55, 40%) were found to be positively or negatively associated (ROPE% ≤ 5%) with TM-try among 146 RA patients. A total of 9 determinant factors were identified using BMA (Figure 1). Wishing that TM services were offered by a rheumatologist, having prior TM knowledge, living in a town and considering one’s health status as okay were positively associated with TM-try. By contrast, not owning an electronic device, not having internet access at home, considering to have a bad health status and being more than 60 years old were negatively associated with TM-try. Conclusion Our results suggest that health status, TM knowledge, age, and access to technical equipment and infrastructure influence RA patients’ motivation to use telehealth in Germany. Consequently, training programs and targeted support measures in terms of equipment and infrastructure could help ensure that all patients have equal access to telehealth. References [1] Miloslavsky EM, Bolster MB. Addressing the rheumatology workforce shortage: A multifaceted approach. Semin Arthritis Rheum. 2020 Aug;50(4):791-796. doi: 10.1016/j.semarthrit.2020.05.009. [2] Muehlensiepen F, Petit P, Knitza J, Welcker M, Vuillerme N. Factors associated with Telemedicine Factors associated with Telemedicine Usage among Rheumatic Patients: Secondary Analysis of Data from a German Nationwide Survey. J Med Internet Res. 2022 Nov 16. doi: 10.2196/40912 [Epub ahead of print] [3] Muehlensiepen F, Knitza J, Marquardt W, May S, Krusche M, Hueber A, et al. Opportunities and Barriers of Telemedicine in Rheumatology: A Participatory, Mixed-Methods Study. Int. J. Environ. Res. Public Health 2021;18(24):13127. doi: 10.3390/ijerph182413127. Figure 1. Determinants of TM-try in patients with rheumatoid arthritis Acknowledgements FM & PP contributed equally and share the first authorship. The authors would like to thank the participants in the survey and all other supporters of TeleRheumaBB. We also owe special gratitude to KV Consult- und Managementgesellschaft mbH, which initiated the study in the first place. The present work is part of the PhD thesis of F.M. (AGEIS, Université Grenoble Alpes, Grenoble, France). Disclosure of Interests Felix Muehlensiepen Speakers bureau: Novartis Pharma GmbH, Paid instructor for: Novartis Pharma GmbH, Consultant of: Novartis Pharma GmbH, Grant/research support from: AbbVie Deutschland GmbH & Co. KG, Novartis Pharma GmbH, Pascal Petit: None declared, Johannes Knitza Speakers bureau: Abbvie, Novartis, Medac, Sanofi, Amgen, UCB, Consultant of: Abbvie, Novartis, Lilly, Medac, BMS, Sanofi, Amgen, Gilead, UCB, ABATON, GSK, Werfen, Vila Health, Böhringer Ingelheim, Janssen, Galapagos, Chugai, Grant/research support from: Abbvie, Novartis, Thermo Fisher, UCB, ABATON, Sanofi, DFG, EIT Health, Martin Welcker Shareholder of:/, Speakers bureau: Abbvie, Actelion, Amgen, Biogen,BMS, Berlin Chemie, Celgene, Galapagos, Gilead, GSK, Hexal, Janssen, Medac, MSD, Mundipharma, Mylan, Novartis, Pfizer, Roche, Sanofi, SOBI, UCB, Consultant of: Abbvie, Actelion, Aescu, Amgen, Cel- gene, Hexal, Janssen, Medac, Novartis, Pfizer, Sanofi, UCB, Grant/research support from: Novartis, Abbvie, Nicolas Vuillerme: None declared