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dc.contributor.authorFranklin, Patricia D
dc.contributor.authorZheng, Hua
dc.contributor.authorBond, Christina
dc.contributor.authorLavallee, Danielle C.
dc.date2022-08-11T08:08:25.000
dc.date.accessioned2022-08-23T15:54:38Z
dc.date.available2022-08-23T15:54:38Z
dc.date.issued2020-06-19
dc.date.submitted2020-09-22
dc.identifier.citation<p>Franklin PD, Zheng H, Bond C, Lavallee DC. Translating clinical and patient-reported data to tailored shared decision reports with predictive analytics for knee and hip arthritis. Qual Life Res. 2020 Jun 19. doi: 10.1007/s11136-020-02557-8. Epub ahead of print. PMID: 32562194. <a href="https://doi.org/10.1007/s11136-020-02557-8">Link to article on publisher's site</a></p>
dc.identifier.issn0962-9343 (Linking)
dc.identifier.doi10.1007/s11136-020-02557-8
dc.identifier.pmid32562194
dc.identifier.urihttp://hdl.handle.net/20.500.14038/29592
dc.description.abstractINTRODUCTION: New informatics tools can transform evidence-based information to individualized predictive reports to serve shared decisions in clinic. We developed a web-based system to collect patient-reported outcomes (PROs) and medical risk factors and to compare responses to national registry data. The system generates predicted outcomes for individual patients and a report for use in clinic to support decisions. We present the report development, presentation, and early experience implementing this PRO-based, shared decision report for knee and hip arthritis patients seeking orthopedic evaluation. METHODS: Iterative patient and clinician interviews defined report content and visual display. The web-system supports: (a) collection of PROs and risk data at home or in office, (b) automated statistical processing of responses compared to national data, (c) individualized estimates of likely pain relief and functional gain if surgery is elected, and (d) graphical reports to support shared decisions. The system was implemented at 12 sites with 26 surgeons in an ongoing cluster randomized trial. RESULTS: Clinicians and patients recommended that pain and function as well as clinical risk factors (e.g., BMI, smoking) be presented to frame the discussion. Color and graphics support patient understanding. To date, 7891 patients completed the assessment before the visit and 56% consented to study participation. Reports were generated for 98% of patients and 68% of patients recalled reviewing the report with their surgeon. CONCLUSIONS: Informatics solutions can generate timely, tailored office reports including PROs and predictive analytics. Patients successfully complete the pre-visit PRO assessments and clinicians and patients value the report to support shared surgical decisions.
dc.language.isoen_US
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=32562194&dopt=Abstract">Link to Article in PubMed</a></p>
dc.rightsOpen Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectOsteoarthritis
dc.subjectPatient-reported outcomes
dc.subjectPredictive analytics
dc.subjectShared decision-making
dc.subjectTotal joint replacement
dc.subjectBioinformatics
dc.subjectClinical Epidemiology
dc.subjectEpidemiology
dc.subjectHealth Information Technology
dc.subjectHealth Services Administration
dc.subjectHealth Services Research
dc.subjectMusculoskeletal Diseases
dc.subjectRehabilitation and Therapy
dc.subjectTranslational Medical Research
dc.titleTranslating clinical and patient-reported data to tailored shared decision reports with predictive analytics for knee and hip arthritis
dc.typeJournal Article
dc.source.journaltitleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=2824&amp;context=faculty_pubs&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/faculty_pubs/1810
dc.identifier.contextkey19508493
refterms.dateFOA2022-08-23T15:54:38Z
html.description.abstract<p>INTRODUCTION: New informatics tools can transform evidence-based information to individualized predictive reports to serve shared decisions in clinic. We developed a web-based system to collect patient-reported outcomes (PROs) and medical risk factors and to compare responses to national registry data. The system generates predicted outcomes for individual patients and a report for use in clinic to support decisions. We present the report development, presentation, and early experience implementing this PRO-based, shared decision report for knee and hip arthritis patients seeking orthopedic evaluation.</p> <p>METHODS: Iterative patient and clinician interviews defined report content and visual display. The web-system supports: (a) collection of PROs and risk data at home or in office, (b) automated statistical processing of responses compared to national data, (c) individualized estimates of likely pain relief and functional gain if surgery is elected, and (d) graphical reports to support shared decisions. The system was implemented at 12 sites with 26 surgeons in an ongoing cluster randomized trial.</p> <p>RESULTS: Clinicians and patients recommended that pain and function as well as clinical risk factors (e.g., BMI, smoking) be presented to frame the discussion. Color and graphics support patient understanding. To date, 7891 patients completed the assessment before the visit and 56% consented to study participation. Reports were generated for 98% of patients and 68% of patients recalled reviewing the report with their surgeon.</p> <p>CONCLUSIONS: Informatics solutions can generate timely, tailored office reports including PROs and predictive analytics. Patients successfully complete the pre-visit PRO assessments and clinicians and patients value the report to support shared surgical decisions.</p>
dc.identifier.submissionpathfaculty_pubs/1810
dc.contributor.departmentDepartment of Orthopedics and Physical Rehabilitation


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Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's license is described as Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.