--- title: "Integrating Patient-Generated Health Data: Expanded 10-Stage Workflow for Shared Decision-Making" description: Discover a new 10-stage workflow for integrating patient-generated health data into shared decision-making, enhancing patient-provider collaboration in healthcare. image: https://blog.jmir.org/hubfs/StoryTap%20Blog%20-%20Pavithren%20V%20S%20Pakianathan.png --- [![JMIR Publications logo](https://blog.jmir.org/hs-fs/hubfs/JMIR-Publications_logo_2020_original.png?width=550&height=109&name=JMIR-Publications_logo_2020_original.png "JMIR Publications logo")](http://www.jmirpublications.com) Open main menu Close main menu [Research News](https://blog.jmir.org/tag/research-news) # Integrating Patient-Generated Health Data: Expanded 10-Stage Workflow for Shared Decision-Making ![Liana Ramos, Marketing Associate](https://blog.jmir.org/hs-fs/hubfs/Liana%20Ramos.jpeg?width=45&name=Liana%20Ramos.jpeg) [Liana Ramos, Marketing Associate](https://blog.jmir.org/author/liana-ramos) Published Date: 14 October 2026 9:41 a.m. [Share this blog post on Twitter](https://twitter.com/intent/tweet?text=I+found+this+interesting+blog+post&url=https://blog.jmir.org/integrating-patient-generated-health-data-expanded-10-stage-workflow-for-shared-decision-making) [Share this blog post on Facebook](http://www.facebook.com/share.php?u=https://blog.jmir.org/integrating-patient-generated-health-data-expanded-10-stage-workflow-for-shared-decision-making) [Share this blog post on LinkedIn](http://www.linkedin.com/shareArticle?mini=true&url=https://blog.jmir.org/integrating-patient-generated-health-data-expanded-10-stage-workflow-for-shared-decision-making) ![Integrating Patient-Generated Health Data: Expanded 10-Stage Workflow for Shared Decision-Making](https://blog.jmir.org/hubfs/StoryTap%20Blog%20-%20Pavithren%20V%20S%20Pakianathan.png) With consumer wearables, smartphones, and remote monitoring devices becoming mainstream, patient-generated health data (PGHD) offers a continuous lens into daily living. However, translating raw tracking data into actionable clinical insights during time-constrained consultations presents significant challenges for both patients and healthcare providers. | --- **Key Takeaways** | | --- | | Expanded 10-Stage Workflow: The authors expanded existing clinical models into an augmented 10-stage workflow model that captures pre-consultation tracking, clinical co-interpretation, and post-consultation health actions. | | Seven Cross-Cutting Tensions: Key misalignments between stakeholders include data relevance versus data overload, patient emotional connection to numbers versus provider clinical objectivity, and patient autonomy versus provider monitoring accountability. | | Collaborative Sensemaking as the Primary Driver: Shared decision-making succeeds when tools scaffold collaborative sensemaking, allowing providers and patients to co-interpret health trends rather than raw, unformatted data streams. --- | Listen to this blog post 2:24 ---   In a [scoping review](https://mhealth.jmir.org/2026/1/e85197/) published in [JMIR mHealth and uHealth](https://mhealth.jmir.org/), lead researcher Pavithren V S Pakianathan and colleagues at [LMU Munich](https://www.lmu.de/en/) and the [Ludwig Boltzmann Institute for Digital Health and Prevention](https://dhp.lbg.ac.at/?lang=en) synthesized a decade of literature (2013–2023) to examine the barriers, enablers, and cross-cutting tensions surrounding PGHD integration in shared decision-making. ### Aligning Patient Journeys and Clinical Workflows How can digital health systems bridge the gap between daily self-tracking and clinical consultations? By analyzing 53 studies across clinical, technical, and human-computer interaction domains, the scoping review highlights that successful PGHD integration extends far beyond the traditional hospital environment. To optimize shared decision-making, digital health platforms must provide structured data summaries, respect patient autonomy, and streamline electronic health record (EHR) data integration to prevent clinician burnout. Discover how this augmented workflow model can guide the design of digital health tools: - [Read the Full Open-Access Article](https://mhealth.jmir.org/2026/1/e85197/) to explore the complete 10-stage model, thematic heatmaps, and stakeholder alignment strategies. - [Watch the Author Video](https://www.youtube.com/watch?v=zgyvvUX0MSE) to hear Pavithren V S Pakianathan break down the scoping review findings and 10-stage workflow model. | | In this video, Pavithren V S Pakianathan from LMU Munich and the Ludwig Boltzmann Institute for Digital Health and Prevention discusses a scoping review examining how patient-generated health data (PGHD) from wearables and smartphones can be integrated into shared decision-making. | | | --- | --- | --- |   ### In the Author's Words > *"Our scoping review examines this from clinicians' and patients' perspectives and formulates a 10-stage workflow model consisting of pre-consultation, during consultation, and post-consultation stages."* > > > — Pavithren V S Pakianathan, PhD Candidate (Ludwig Boltzmann Institute for Digital Health and Prevention and LMU Munich)   --- V S Pakianathan P, Kumar D, Prabath J, Hussein R, Niebauer J, Schmidt A, Smeddinck J Barriers and Enablers to Integrating Patient-Generated Health Data in Shared Decision-Making From Health Care Professional and Patient Perspectives: Scoping Review JMIR Mhealth Uhealth 2026;14:e85197 URL: [https://mhealth.jmir.org/2026/1/e85197](https://mhealth.jmir.org/2026/1/e85197/) DOI: [10.2196/85197](https://mhealth.jmir.org/2026/1/e85197/) --- JMIR Publications is thrilled to announce that we will be attending the [AMIA 2026 Annual Symposium](https://amia.org/education-events/amia-2026-annual-symposium) this November 7-11, 2026 in Dallas, TX! If you'll be at AMIA, we would love to connect in person. Drop by booth 114 to meet us, discuss your upcoming research, or learn more about publishing open-access.   ![Liana Ramos, Marketing Associate](https://blog.jmir.org/hs-fs/hubfs/Liana%20Ramos.jpeg?width=150&name=Liana%20Ramos.jpeg) #### Liana Ramos, Marketing Associate [Follow me on LinkedIn](https://www.linkedin.com/in/lianaramos/) Liana Ramos is a Marketing Associate at JMIR Publications, dedicated to building data-driven systems that connect scholarly content with the communities that need it most. With five years of experience at the intersection of media, publishing, and audience behaviour, she handles automated lifecycle journeys, author recognition programs, and record-scale digital events for JMIR. Passionate about storytelling and digital strategy, she focuses on making open access digital health research discoverable, scalable, and highly engaging. ### Leave a Comment #### About - Menu Item One - Menu Item Two - Menu Item Three #### Services - Menu Item One - Menu Item Two - Menu Item Three #### News - Menu Item One - Menu Item Two - Menu Item Three Follow us on Facebook Follow us on LinkedIn Follow us on Twitter Follow us on Instagram ```json { "@context" : "https://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Person", "name" : "Liana Ramos, Marketing Associate", "url" : "https://blog.jmir.org/author/liana-ramos" }, "dateModified" : "2026-10-14T13:41:40.672Z", "datePublished" : "2026-10-14T13:41:40.000Z", "headline" : "Integrating Patient-Generated Health Data: Expanded 10-Stage Workflow for Shared Decision-Making", "image" : [ "https://blog.jmir.org/hubfs/StoryTap%20Blog%20-%20Pavithren%20V%20S%20Pakianathan.png" ], "mainEntityOfPage" : { "@id" : "https://blog.jmir.org/integrating-patient-generated-health-data-expanded-10-stage-workflow-for-shared-decision-making", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://blog.jmir.org/hubfs/JMIR-Publications_logo_2020_original.png" }, "name" : "JMIR Publications" } } ```