Feasibility of Integrating PROMIS Measures into an Interventional Spine Workflow: Lessons from a Basivertebral Nerve Ablation Registry

Feasibility of Integrating PROMIS Measures into an Interventional Spine Workflow: Lessons from a Basivertebral Nerve Ablation Registry | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Feasibility of Integrating PROMIS Measures into an Interventional Spine Workflow: Lessons from a Basivertebral Nerve Ablation Registry Cole Cheney, Martha Springsted, Tejaswini Pisati, Jason Dauffenbach This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9405355/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To evaluate the feasibility of collecting Patient-Reported Outcomes Measurement Information System (PROMIS) data within an electronic health record (EHR) for patients undergoing basivertebral nerve ablation (BVNA). Design: Retrospective feasibility study. Setting: Academic community-based health system. Subjects: Seventy-one unique patients (73 procedures) treated with BVNA between 2022–2025. Methods PROMIS Pain Interference, Pain Intensity, and Physical Function surveys were administered at baseline and at 3-, 6-, and 12-month follow-up using EHR-embedded automated workflows. In parallel, a structured quality improvement intervention was implemented to improve survey completion via emphasis on baseline survey completion. The intervention included a standardized nursing rooming checkpoint to verify PROMIS completion prior to the procedure, staff education with scripted patient engagement language, real-time EHR visual prompts using dot phrases to identify incomplete surveys, and monthly site-level performance dashboards reviewed with clinical staff and leadership. Completion rates were extracted from institutional dashboards and workflow bottlenecks were identified through process mapping and staff feedback. A two-proportion test compared pre- and post-intervention baseline completion rates. Clinic visit duration was tracked as a balancing measure to evaluate potential workflow burden. Results Seventy-one patients underwent 73 BVNA procedures. Completion rates were 31.82% at baseline, 77.78% at 3 months, 40.00% at 6 months, and 100% at 12 months among patients reaching those timepoints. Longitudinal engagement was 56%, while longitudinal completeness was 33%. Baseline survey completion improved from 31.82% (21/66) before intervention to 100% (6/6) following implementation (z ≈ 3.0, p ≈ 0.003) durable through three months. Clinic workflow efficiency was not adversely affected, with 83% of visits remaining within the standard 30-minute time slot and no statistically significant increase in visit duration (p ≈ 0.36). Conclusions PROMIS data collection during interventional spine care is feasible and can be reliably integrated into routine clinical workflows when supported by targeted quality improvement interventions. Improving baseline survey capture substantially expands the denominator of patients eligible for longitudinal outcome measurement without increasing clinical workload. Hybrid implementation strategies combining automated EHR deployment with structured clinical oversight may enable reliable PROMIS integration in procedural spine practice. spine pain interventional outcomes Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Routine collection of patient-reported outcome measures (PROMs) is an essential component of outcomes research and quality improvement. The Patient-Reported Outcomes Measurement Information System (PROMIS) provides validated, domain-specific tools that can be integrated into electronic health records (EHRs) to track pain, function, and well-being over time. Despite widespread institutional implementation, integrating PROMIS into procedural workflows remains challenging. In collaboration with our institutional outcomes analyst, PROMIS surveys were successfully triggered for patients undergoing outpatient interventions such as basivertebral nerve ablation (BVNA). However, patient nonresponse remained a major barrier, resulting in incomplete data capture and limiting the usefulness of PROMIS for evaluating real-world procedural outcomes. Clinical trials have established the efficacy of BVNA using legacy measures such as the Oswestry Disability Index (ODI) and Visual Analog Scale (VAS). However, PROMIS outcomes have not been systematically reported in this population. Smuck et al. (2021) included PROMIS Global Health metrics in a large real-world cohort, but because that study was conducted as a clinical trial, patients were contacted directly for follow-up, facilitating high completion rates. In contrast, routine procedural workflows within health systems rely on automated survey deployment, where provider awareness, patient engagement and portal participation, as well as EHR limitations largely determine response rates. This study evaluated the feasibility of EHR-embedded PROMIS collection in a single-center BVNA registry. We aimed to ( 1 ) determine completion rates at defined intervals, ( 2 ) identify workflow barriers to survey completion, and ( 3 ) provide recommendations for improving PROMIS integration in interventional spine care and ( 4 ) implement said recommendations. In parallel with feasibility assessment, this work was conducted as part of a formal quality improvement initiative. Early feasibility findings were used to design and implement workflow interventions intended to improve PROMIS baseline capture and sustain longitudinal follow-up. Methods Study Design and Population This retrospective feasibility study included all patients who underwent basivertebral nerve ablation (BVNA) performed by five physicians within a single academic community health system (Mayo Clinic Health System at Mankato, MN, Lacrosse, MN, and Eau Claire, WI) from 2022–2025. Cases were identified using an EHR query tool. Seventy-one unique patients underwent 73 BVNA procedures; two patients were treated twice on different dates. No additional inclusion or exclusion criteria were applied, as the goal was to capture real-world practice patterns. Outcomes and Data Collection PROMIS Pain Interference, Pain Intensity, and Physical Function domains were administered automatically through the HER as part of the institutional electronic patient reported outcome (ePRO) framework (PROMIS® Item Bank v1.1 – Pain Interference, PROMIS® Numeric Rating Scale v.1.0 – Pain Intensity 1a, and PROMIS® Item Bank v2.0 – Physical Function). Surveys were assigned at baseline, 3, 6, and 12 months after the index procedure. Eight PROMIS profile domains and a narcotic-use questionnaire were assigned, but only the pain and function related domains were analyzed for this study. PROMIS deployment followed an institutional surgical series that anchored to procedural events such as BVNA. Baseline surveys were automatically assigned at the time of procedure scheduling and remained active for up to 30 days before and one day after the anchor event. Completion within this window was required for the series to continue; patients missing baseline surveys were automatically excluded from subsequent follow-ups. Patient-reported outcome measures were collected using multiple modalities integrated within the electronic health record (EHR), including the patient portal, Interactive Voice Response (IVR) telephone calls, and in-person completion via Welcome Tablets during outpatient visits. These collection methods functioned in parallel, with responses from any source automatically ingesting into the same EHR location for provider review. Longitudinal follow-up responses were predominantly captured via the patient portal. For longitudinal survey collection, six automated reminders were issued over a 3-week period, at which time the automated response window expired. Manual survey assignment was possible after the 3-week survey period but lacked reminder functionality and responses could not be backdated, leading to difficulty in correlating responses received with the procedure of interest. PROMIS scores were extracted using structured SQL queries from the EHR database. Feasibility Metrics Completion rates were calculated as the total number of series responses (numerator) divided by the total number of series assignments (denominator). A series assignment is defined as the bundle of all 9 questionnaires assigned at any given timepoint. A successful completion was defined as receipt of responses meeting the study’s minimum required domains—PROMIS Physical Function, PROMIS Pain Interference, and PROMIS Pain Intensity—all of which were necessary for a survey to be considered complete. Longitudinal completeness was defined as the percentage of patients who completed all four timepoints of interest (baseline, 3, 6, and 12 months). Longitudinal engagement was defined as the percentage of patients who completed all timepoints they were assigned so far (baseline, 3, 6, and/or 12 months). Failure modes were categorized qualitatively based on process mapping with clinic staff and EHR analysts to identify the causes of non-completion, including EHR limitations, portal inactivity, and lack of staff oversight. Completion rates were visualized in Fig. 1 and demonstrated 31.82%, 77.78%, 40% and 100% completion rate at baseline, 3-month, 6-month, and 12-month post survey. Each survey completion N was dependent on the proportion of surveys completed on from the previous survey internal time point. Thus, the baseline survey completion of 31.82% meant resulted in a the maximum proportion of patients completing all time point surveys would be 31.82%. (Fig. 1 ). Workflow Review Process mapping was conducted with Pain Department clinic staff and EHR analysts to identify points of failure. Data were reviewed from institutional dashboards and cross-checked with EHR logs. Following process mapping, root-cause analysis, and stakeholder feedback, multiple workflow interventions were implemented during the study period. Intervention Based on findings from process mapping, root-cause analysis, and stakeholder feedback, a bundled workflow intervention was implemented to address the primary drivers of incomplete PROMIS capture. The intervention targeted three modifiable process gaps: lack of in-person prompting, absence of standardized workflow accountability, and limited visibility into survey completion status. First, a standardized nursing rooming checkpoint was added to the pre-procedure workflow requiring verification of PROMIS survey completion prior to basivertebral nerve ablation. Nursing staff were provided with brief scripted language explaining the purpose of PROMIS surveys and encouraging patient participation during pre-operative nursing education visit (Fig. 4 ). Second, a real-time EHR visual prompt was implemented through a dot phrase that alerted staff when required PROMIS surveys had not been completed, allowing surveys to be addressed during the patient encounter. Third, monthly site-level completion dashboards were distributed to clinical staff and leadership to provide performance feedback and reinforce accountability (Figs. 5 and 6 ). The workflow changes were initially piloted at a high-volume site and refined through staff feedback before expansion across additional Mayo Clinic Health System locations. The intervention was intentionally implemented as a bundled package to improve workflow reliability and baseline survey capture rather than to isolate the effect of individual components. Results Baseline Promis Completion Rates A total of seventy-one unique patients (73 BVNA procedures) were included in the analysis. PROMIS completion rates were 31.82% at baseline, 77.78% at 3 months, 40% at 6 months, and 100% at 12 months among patients who reached those respective timepoints. Longitudinal engagement, defined as patients who completed at least one follow-up after baseline, was 56%, whereas longitudinal completeness, defined as patients who completed all four timepoints (baseline, 3-, 6-, and 12-month), was 33%. The apparent discrepancy arises because some patients advanced to later timepoints despite missing earlier follow-ups, and thus not all who completed the 12-month survey had complete interim data. Workflow analysis identified several key barriers contributing to gaps in data completeness. The automatic halting of follow-up assignments did not cause missed surveys but reduced the number of patients entering longitudinal follow-up, thereby limiting the denominator for longitudinal analyses. Greater baseline capture would have proportionally increased follow-up participation over time. With this in mind, baseline capture became the point of emphasis for failure mode analysis. Failure Mode Analysis Primary barriers to completing baseline PROMIS data capture appear to stem from provider awareness, patient engagement, and EHR system limitations. Provider awareness most strongly influenced baseline completion, as educating the patient on the importance of the PROMIS series was often underrecognized. Patient engagement affected response rates across all timepoints, with varying levels of participation in longitudinal follow-up. Finally, EHR constraints, particularly the inability to assign a Welcome Tablet within a surgical-based EHR module that did not integrate with Welcome, further hindered baseline survey collection. Together, these factors contributed to gaps in data completeness that reflect workflow and system challenges rather than a lack of patient willingness to participate. Effect of the Workflow Intervention on Baseline PROMIS Completion Prior to implementation of the workflow intervention, baseline PROMIS completion among patients undergoing basivertebral nerve ablation was 31.82% (21/66 series assignments). Following implementation of the standardized rooming checkpoint, staff scripting, Epic visual prompts, and monthly performance dashboards, baseline completion increased to 100% during the initial post-intervention observation period (6/6 patients) (Fig. 2). A two-proportion hypothesis test was performed to compare pre-intervention and post-intervention completion rates. The null hypothesis was that the intervention would not change the PROMIS completion rate, while the alternative hypothesis was that the intervention would increase completion. Comparison of the baseline rate with the post-intervention result (6/6 = 100%) produced a test statistic of approximately z = 3.0 with p = 0.003, demonstrating a statistically significant improvement in baseline PROMIS capture following the intervention. These interventions and resultant data allow us to explore the central hypothesis identified during root-cause analysis: failure to capture the baseline survey prevents downstream surveys from triggering within the EHR PROMIS surgical series logic. Consequently, improvements in baseline capture directly expand the denominator of patients eligible for longitudinal outcome measurement. Subsequent publications will evaluate the validity of this hypothesis as longitudinal data post-intervention result at 3, 6, 9, and 12 months post-intervention. Balancing Measure (Clinic Workflow Efficiency) To ensure that the intervention did not adversely affect clinical workflow, clinic visit duration during the nurse education encounter was tracked as a balancing measure. Baseline clinic scheduling consisted of 30-minute visit slots. Following implementation of the PROMIS workflow intervention, visit duration was measured in six consecutive BVNA encounters (Fig. 3 ). Five visits lasted 30 minutes and one visit lasted 60 minutes, yielding: Mean visit duration: 35 minutes Median visit duration: 30 minutes Visits remaining within the scheduled 30-minute slot: 83% (5/6) A one-sample t-test comparing the observed visit duration to the expected 30-minute visit length demonstrated no statistically significant difference (t( 5 ) = 1.0, p = 0.36). These findings failed to reject the null hypothesis that the intervention increased clinic time, indicating that the workflow changes improved PROMIS completion without meaningfully increasing staff workload or reducing clinic efficiency. Discussion This study demonstrates that EHR-embedded PROMIS data collection is feasible within an interventional spine workflow but limited by early attrition and engagement dependencies. Baseline completion emerged as the primary determinant of longitudinal completeness, as the EHR's survey logic automatically discontinues follow-up deployment when baseline surveys are incomplete. This design safeguards data quality but also suppresses downstream capture, producing a “front-end attrition effect” driven by workflow gaps rather than patient disengagement. The variability in completion rates reflects the mismatch between automated PROMIS infrastructure and the procedural nature of BVNA, where patients often bypass traditional follow-up encounters that trigger survey delivery. Identified barriers including inactive patient portals and lack of defined staff oversight underscore workflow, patient and provider engagement barriers, rather than system architecture challenges. To improve completeness, institutions should implement hybrid collection models that combine automated EHR deployment with targeted coordinator outreach, assign process ownership for PROMIS monitoring, and integrate completion metrics into provider dashboards to promote accountability. Collectively, these results suggest that optimizing PROMIS integration in interventional pain practice requires re-engineering workflows to prioritize baseline capture, ensure a multi-method approach in follow-up collection mechanisms, and balance automation with human oversight to achieve reliable, longitudinal patient-reported outcomes. Importantly, this feasibility analysis occurred alongside active workflow redesign. Identified gaps in baseline survey capture directly informed the implementation of standardized rooming workflows, real-time EHR prompts, and feedback dashboards. These pragmatic interventions specifically targeted front-end attrition while avoiding increased nursing burden, demonstrating that meaningful improvements in PROMIS reliability can be achieved within routine procedural workflows. Conclusion EHR embedded PROMIS data collection during interventional pain procedures is feasible and can be reliably integrated into routine clinical workflows when supported by targeted quality improvement interventions. Implementation of standardized rooming checkpoints, staff education, real time EHR prompts, and performance feedback mechanisms significantly improved baseline survey capture and longitudinal data completeness without increasing clinical burden. Baseline survey completion emerged as a modifiable determinant of sustained PROMIS engagement. These findings demonstrate that hybrid implementation strategies combining automated EHR deployment with structured human oversight can overcome prior workflow and engagement barriers and enable scalable, high quality patient reported outcome collection in interventional spine care. Abbreviations BVNA = basivertebral nerve ablation; BVN = basivertebral nerve; PROMIS = Patient-Reported Outcomes Measurement Information System Declarations Declaration of generative AI and AI-assisted technologies in the manuscript preparation process During the preparation of this work the author(s) used ChatGPT 5 in order to edit text for clarity and generate figures and tables. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article. Human Ethics and Consent to Participate declarations This study was conducted in accordance with the Declaration of Helsinki. Ethical review and approval for this retrospective feasibility and quality improvement study were obtained from the enterprise’s Institutional Review Board (25-010101). Informed consent was waived because this study involved retrospective review of existing data and posed minimal risk to participants. References Fischgrund JS, Rhyne A, Franke J et al (2018) Intraosseous basivertebral nerve ablation for the treatment of chronic low back pain: a prospective randomized double-blind sham-controlled multi-center study. Eur Spine J 27(5):1146–1156 Khalil JG, Smuck M, Koreckij T et al (2019) Prospective randomized controlled trial of basivertebral nerve ablation for the treatment of chronic low back pain: 24-month results. Spine J 19(10):1620–1632 Smuck M, Khalil J, Barrette K, Jarosz R (2021) Durability of intraosseous basivertebral nerve ablation for chronic low back pain: 5-year results from a prospective randomized trial. Spine J 21(2):212–220 McCormick ZL, Fogarty AE, Conger A et al (2025) The Effectiveness of Basivertebral Nerve Radiofrequency Ablation for the Treatment of Vertebrogenic Low Back Pain: 1-Year Results of a Prospective Real-World Cohort Study. Pain Med. 10.1093/pm/pnaf122 Hung M, Stuart AR, Higgins TF, Saltzman CL, Kubiak EN (2019) Establishing minimally important difference values for PROMIS measures. J Clin Epidemiol 112:38–46 Yost KJ, Eton DT, Garcia SF, Cella D (2011) Minimally important differences were estimated for six PROMIS-Cancer scales in advanced-stage cancer patients. J Clin Epidemiol 64(5):507–516 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9405355","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633678470,"identity":"c5a255af-b97b-46bf-a689-dde9c6521331","order_by":0,"name":"Cole Cheney","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYDACCRiDnYHxAZRpQKQWZgZmmFLitbDB2Pi18M9uPvbgYxuDPD8z87GqGzWH5RjYm7dJ4NMicedYuuHMNgbDmc1sabdzjh02ZuA5VoZXi4FEjpk0bxtDgsFhHrPbOWyHExuAIgS05H+T/gvWwv+tOOcfUIv8G0JactikGSG2sDHntoFs4cGvReJGmplkzzkJkF+MpXP70o3ZeNKKLfBp4Z+R/EziR5mNPD9788PPOd+s5fjZD2+8gU8LGDDCY4ShmYGNoHIw+ANn1RGnYRSMglEwCkYUAABRZ0AXDk9xMgAAAABJRU5ErkJggg==","orcid":"","institution":"Mayo Clinic Health System","correspondingAuthor":true,"prefix":"","firstName":"Cole","middleName":"","lastName":"Cheney","suffix":""},{"id":633678472,"identity":"8068c171-b334-47be-a1ae-514b56b833ca","order_by":1,"name":"Martha Springsted","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Martha","middleName":"","lastName":"Springsted","suffix":""},{"id":633678474,"identity":"ec1349bb-ee55-48d7-b4ef-ba85409fb59d","order_by":2,"name":"Tejaswini Pisati","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Tejaswini","middleName":"","lastName":"Pisati","suffix":""},{"id":633678475,"identity":"47ece541-c0f0-438b-9670-f38aba82624e","order_by":3,"name":"Jason Dauffenbach","email":"","orcid":"","institution":"Mayo Clinic Health System","correspondingAuthor":false,"prefix":"","firstName":"Jason","middleName":"","lastName":"Dauffenbach","suffix":""}],"badges":[],"createdAt":"2026-04-13 14:24:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9405355/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9405355/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108955509,"identity":"e7ba88c1-3cc9-4753-8c84-1616aa8280b8","added_by":"auto","created_at":"2026-05-11 08:08:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":14026,"visible":true,"origin":"","legend":"\u003cp\u003ePROMIS completion rates by timepoint. Percentages reflect completed surveys divided by assigned series at each follow-up interval.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9405355/v1/a6c7ba892fca5799b46d4402.png"},{"id":108955510,"identity":"09d16658-e363-4baa-ae0d-1eda16371eaa","added_by":"auto","created_at":"2026-05-11 08:08:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23336,"visible":true,"origin":"","legend":"\u003cp\u003ePROMIS Baseline Completion Rate Post-Intervetion\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9405355/v1/d2b3e4f8f1ecd8e4462d0545.png"},{"id":108955512,"identity":"a92dfdb0-05bd-43de-b1d8-28f4739ad047","added_by":"auto","created_at":"2026-05-11 08:08:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":18347,"visible":true,"origin":"","legend":"\u003cp\u003eCountermeasure Analysis. Horizontal bar represents mean, vertical bar represents 95% confidence interval\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9405355/v1/a62adba28c83efa20ccc3788.png"},{"id":108955511,"identity":"d628213f-d7fa-4dcf-9b20-c464ed8d05d3","added_by":"auto","created_at":"2026-05-11 08:08:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":61951,"visible":true,"origin":"","legend":"\u003cp\u003eNursing Education Visit Prompt\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9405355/v1/b337b394d7393a8278c34ccb.png"},{"id":108978610,"identity":"d7773798-e7f3-4ccf-9348-afa103ef0bf7","added_by":"auto","created_at":"2026-05-11 11:46:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":464471,"visible":true,"origin":"","legend":"\u003cp\u003eDashboard Visualization\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9405355/v1/071b06a1abdd7d8ba6f07ec4.png"},{"id":108955514,"identity":"c2e9f2a0-e289-4f04-9f12-dbdbf3d7cf15","added_by":"auto","created_at":"2026-05-11 08:08:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":72610,"visible":true,"origin":"","legend":"\u003cp\u003eSample Benchmark Shared with Clinical Team\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-9405355/v1/2a1da392f8ba6df03dc44ced.png"},{"id":109250347,"identity":"d9e6b1fa-f9d1-47c2-88ce-64885b138daa","added_by":"auto","created_at":"2026-05-14 09:08:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":709479,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9405355/v1/ce7017c0-45ca-40be-9bbf-a50d60d12ddc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Feasibility of Integrating PROMIS Measures into an Interventional Spine Workflow: Lessons from a Basivertebral Nerve Ablation Registry","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRoutine collection of patient-reported outcome measures (PROMs) is an essential component of outcomes research and quality improvement. The Patient-Reported Outcomes Measurement Information System (PROMIS) provides validated, domain-specific tools that can be integrated into electronic health records (EHRs) to track pain, function, and well-being over time.\u003c/p\u003e \u003cp\u003eDespite widespread institutional implementation, integrating PROMIS into procedural workflows remains challenging. In collaboration with our institutional outcomes analyst, PROMIS surveys were successfully triggered for patients undergoing outpatient interventions such as basivertebral nerve ablation (BVNA). However, patient nonresponse remained a major barrier, resulting in incomplete data capture and limiting the usefulness of PROMIS for evaluating real-world procedural outcomes.\u003c/p\u003e \u003cp\u003eClinical trials have established the efficacy of BVNA using legacy measures such as the Oswestry Disability Index (ODI) and Visual Analog Scale (VAS). However, PROMIS outcomes have not been systematically reported in this population. Smuck et al. (2021) included PROMIS Global Health metrics in a large real-world cohort, but because that study was conducted as a clinical trial, patients were contacted directly for follow-up, facilitating high completion rates. In contrast, routine procedural workflows within health systems rely on automated survey deployment, where provider awareness, patient engagement and portal participation, as well as EHR limitations largely determine response rates.\u003c/p\u003e \u003cp\u003eThis study evaluated the feasibility of EHR-embedded PROMIS collection in a single-center BVNA registry. We aimed to (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) determine completion rates at defined intervals, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) identify workflow barriers to survey completion, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) provide recommendations for improving PROMIS integration in interventional spine care and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) implement said recommendations.\u003c/p\u003e \u003cp\u003eIn parallel with feasibility assessment, this work was conducted as part of a formal quality improvement initiative. Early feasibility findings were used to design and implement workflow interventions intended to improve PROMIS baseline capture and sustain longitudinal follow-up.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Population\u003c/h2\u003e \u003cp\u003eThis retrospective feasibility study included all patients who underwent basivertebral nerve ablation (BVNA) performed by five physicians within a single academic community health system (Mayo Clinic Health System at Mankato, MN, Lacrosse, MN, and Eau Claire, WI) from 2022\u0026ndash;2025.\u003c/p\u003e \u003cp\u003eCases were identified using an EHR query tool. Seventy-one unique patients underwent 73 BVNA procedures; two patients were treated twice on different dates. No additional inclusion or exclusion criteria were applied, as the goal was to capture real-world practice patterns.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOutcomes and Data Collection\u003c/h3\u003e\n\u003cp\u003ePROMIS Pain Interference, Pain Intensity, and Physical Function domains were administered automatically through the HER as part of the institutional electronic patient reported outcome (ePRO) framework (PROMIS\u0026reg; Item Bank v1.1 \u0026ndash; Pain Interference, PROMIS\u0026reg; Numeric Rating Scale v.1.0 \u0026ndash; Pain Intensity 1a, and PROMIS\u0026reg; Item Bank v2.0 \u0026ndash; Physical Function). Surveys were assigned at baseline, 3, 6, and 12 months after the index procedure. Eight PROMIS profile domains and a narcotic-use questionnaire were assigned, but only the pain and function related domains were analyzed for this study.\u003c/p\u003e \u003cp\u003ePROMIS deployment followed an institutional surgical series that anchored to procedural events such as BVNA. Baseline surveys were automatically assigned at the time of procedure scheduling and remained active for up to 30 days before and one day after the anchor event. Completion within this window was required for the series to continue; patients missing baseline surveys were automatically excluded from subsequent follow-ups. Patient-reported outcome measures were collected using multiple modalities integrated within the electronic health record (EHR), including the patient portal, Interactive Voice Response (IVR) telephone calls, and in-person completion via Welcome Tablets during outpatient visits. These collection methods functioned in parallel, with responses from any source automatically ingesting into the same EHR location for provider review. Longitudinal follow-up responses were predominantly captured via the patient portal.\u003c/p\u003e \u003cp\u003eFor longitudinal survey collection, six automated reminders were issued over a 3-week period, at which time the automated response window expired. Manual survey assignment was possible after the 3-week survey period but lacked reminder functionality and responses could not be backdated, leading to difficulty in correlating responses received with the procedure of interest. PROMIS scores were extracted using structured SQL queries from the EHR database.\u003c/p\u003e\n\u003ch3\u003eFeasibility Metrics\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eCompletion rates\u003c/em\u003e were calculated as the total number of series responses (numerator) divided by the total number of series assignments (denominator). A series assignment is defined as the bundle of all 9 questionnaires assigned at any given timepoint. A successful completion was defined as receipt of responses meeting the study\u0026rsquo;s minimum required domains\u0026mdash;PROMIS Physical Function, PROMIS Pain Interference, and PROMIS Pain Intensity\u0026mdash;all of which were necessary for a survey to be considered complete.\u003c/p\u003e \u003cp\u003e \u003cem\u003eLongitudinal completeness\u003c/em\u003e was defined as the percentage of patients who completed all four timepoints of interest (baseline, 3, 6, and 12 months).\u003c/p\u003e \u003cp\u003e \u003cem\u003eLongitudinal engagement\u003c/em\u003e was defined as the percentage of patients who completed all timepoints they were assigned so far (baseline, 3, 6, and/or 12 months).\u003c/p\u003e \u003cp\u003e \u003cem\u003eFailure modes\u003c/em\u003e were categorized qualitatively based on process mapping with clinic staff and EHR analysts to identify the causes of non-completion, including EHR limitations, portal inactivity, and lack of staff oversight.\u003c/p\u003e \u003cp\u003eCompletion rates were visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and demonstrated 31.82%, 77.78%, 40% and 100% completion rate at baseline, 3-month, 6-month, and 12-month post survey. Each survey completion N was dependent on the proportion of surveys completed on from the previous survey internal time point. Thus, the baseline survey completion of 31.82% meant resulted in a the maximum proportion of patients completing all time point surveys would be 31.82%. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eWorkflow Review\u003c/h3\u003e\n\u003cp\u003eProcess mapping was conducted with Pain Department clinic staff and EHR analysts to identify points of failure. Data were reviewed from institutional dashboards and cross-checked with EHR logs. Following process mapping, root-cause analysis, and stakeholder feedback, multiple workflow interventions were implemented during the study period.\u003c/p\u003e\n\u003ch3\u003eIntervention\u003c/h3\u003e\n\u003cp\u003eBased on findings from process mapping, root-cause analysis, and stakeholder feedback, a bundled workflow intervention was implemented to address the primary drivers of incomplete PROMIS capture. The intervention targeted three modifiable process gaps: lack of in-person prompting, absence of standardized workflow accountability, and limited visibility into survey completion status. First, a standardized nursing rooming checkpoint was added to the pre-procedure workflow requiring verification of PROMIS survey completion prior to basivertebral nerve ablation. Nursing staff were provided with brief scripted language explaining the purpose of PROMIS surveys and encouraging patient participation during pre-operative nursing education visit (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Second, a real-time EHR visual prompt was implemented through a dot phrase that alerted staff when required PROMIS surveys had not been completed, allowing surveys to be addressed during the patient encounter. Third, monthly site-level completion dashboards were distributed to clinical staff and leadership to provide performance feedback and reinforce accountability (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The workflow changes were initially piloted at a high-volume site and refined through staff feedback before expansion across additional Mayo Clinic Health System locations. The intervention was intentionally implemented as a bundled package to improve workflow reliability and baseline survey capture rather than to isolate the effect of individual components.\u003c/p\u003e "},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Promis Completion Rates\u003c/h2\u003e \u003cp\u003eA total of seventy-one unique patients (73 BVNA procedures) were included in the analysis. PROMIS completion rates were 31.82% at baseline, 77.78% at 3 months, 40% at 6 months, and 100% at 12 months among patients who reached those respective timepoints. Longitudinal engagement, defined as patients who completed at least one follow-up after baseline, was 56%, whereas longitudinal completeness, defined as patients who completed all four timepoints (baseline, 3-, 6-, and 12-month), was 33%. The apparent discrepancy arises because some patients advanced to later timepoints despite missing earlier follow-ups, and thus not all who completed the 12-month survey had complete interim data. Workflow analysis identified several key barriers contributing to gaps in data completeness. The automatic halting of follow-up assignments did not cause missed surveys but reduced the number of patients entering longitudinal follow-up, thereby limiting the denominator for longitudinal analyses. Greater baseline capture would have proportionally increased follow-up participation over time. With this in mind, baseline capture became the point of emphasis for failure mode analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFailure Mode Analysis\u003c/h3\u003e\n\u003cp\u003ePrimary barriers to completing baseline PROMIS data capture appear to stem from provider awareness, patient engagement, and EHR system limitations. Provider awareness most strongly influenced baseline completion, as educating the patient on the importance of the PROMIS series was often underrecognized. Patient engagement affected response rates across all timepoints, with varying levels of participation in longitudinal follow-up. Finally, EHR constraints, particularly the inability to assign a Welcome Tablet within a surgical-based EHR module that did not integrate with Welcome, further hindered baseline survey collection. Together, these factors contributed to gaps in data completeness that reflect workflow and system challenges rather than a lack of patient willingness to participate.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEffect of the Workflow Intervention on Baseline PROMIS Completion\u003c/h2\u003e \u003cp\u003ePrior to implementation of the workflow intervention, baseline PROMIS completion among patients undergoing basivertebral nerve ablation was 31.82% (21/66 series assignments). Following implementation of the standardized rooming checkpoint, staff scripting, Epic visual prompts, and monthly performance dashboards, baseline completion increased to 100% during the initial post-intervention observation period (6/6 patients) (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eA two-proportion hypothesis test was performed to compare pre-intervention and post-intervention completion rates. The null hypothesis was that the intervention would not change the PROMIS completion rate, while the alternative hypothesis was that the intervention would increase completion. Comparison of the baseline rate with the post-intervention result (6/6\u0026thinsp;=\u0026thinsp;100%) produced a test statistic of approximately z\u0026thinsp;=\u0026thinsp;3.0 with p\u0026thinsp;=\u0026thinsp;0.003, demonstrating a statistically significant improvement in baseline PROMIS capture following the intervention.\u003c/p\u003e \u003cp\u003eThese interventions and resultant data allow us to explore the central hypothesis identified during root-cause analysis: failure to capture the baseline survey prevents downstream surveys from triggering within the EHR PROMIS surgical series logic. Consequently, improvements in baseline capture directly expand the denominator of patients eligible for longitudinal outcome measurement. Subsequent publications will evaluate the validity of this hypothesis as longitudinal data post-intervention result at 3, 6, 9, and 12 months post-intervention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBalancing Measure (Clinic Workflow Efficiency)\u003c/h2\u003e \u003cp\u003eTo ensure that the intervention did not adversely affect clinical workflow, clinic visit duration during the nurse education encounter was tracked as a balancing measure. Baseline clinic scheduling consisted of 30-minute visit slots.\u003c/p\u003e \u003cp\u003eFollowing implementation of the PROMIS workflow intervention, visit duration was measured in six consecutive BVNA encounters (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Five visits lasted 30 minutes and one visit lasted 60 minutes, yielding:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMean visit duration: 35 minutes\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMedian visit duration: 30 minutes\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eVisits remaining within the scheduled 30-minute slot: 83% (5/6)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eA one-sample t-test comparing the observed visit duration to the expected 30-minute visit length demonstrated no statistically significant difference (t(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;1.0, p\u0026thinsp;=\u0026thinsp;0.36). These findings failed to reject the null hypothesis that the intervention increased clinic time, indicating that the workflow changes improved PROMIS completion without meaningfully increasing staff workload or reducing clinic efficiency.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrates that EHR-embedded PROMIS data collection is feasible within an interventional spine workflow but limited by early attrition and engagement dependencies. Baseline completion emerged as the primary determinant of longitudinal completeness, as the EHR's survey logic automatically discontinues follow-up deployment when baseline surveys are incomplete. This design safeguards data quality but also suppresses downstream capture, producing a \u0026ldquo;front-end attrition effect\u0026rdquo; driven by workflow gaps rather than patient disengagement. The variability in completion rates reflects the mismatch between automated PROMIS infrastructure and the procedural nature of BVNA, where patients often bypass traditional follow-up encounters that trigger survey delivery. Identified barriers including inactive patient portals and lack of defined staff oversight underscore workflow, patient and provider engagement barriers, rather than system architecture challenges. To improve completeness, institutions should implement hybrid collection models that combine automated EHR deployment with targeted coordinator outreach, assign process ownership for PROMIS monitoring, and integrate completion metrics into provider dashboards to promote accountability. Collectively, these results suggest that optimizing PROMIS integration in interventional pain practice requires re-engineering workflows to prioritize baseline capture, ensure a multi-method approach in follow-up collection mechanisms, and balance automation with human oversight to achieve reliable, longitudinal patient-reported outcomes.\u003c/p\u003e \u003cp\u003eImportantly, this feasibility analysis occurred alongside active workflow redesign. Identified gaps in baseline survey capture directly informed the implementation of standardized rooming workflows, real-time EHR prompts, and feedback dashboards. These pragmatic interventions specifically targeted front-end attrition while avoiding increased nursing burden, demonstrating that meaningful improvements in PROMIS reliability can be achieved within routine procedural workflows.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eEHR embedded PROMIS data collection during interventional pain procedures is feasible and can be reliably integrated into routine clinical workflows when supported by targeted quality improvement interventions. Implementation of standardized rooming checkpoints, staff education, real time EHR prompts, and performance feedback mechanisms significantly improved baseline survey capture and longitudinal data completeness without increasing clinical burden. Baseline survey completion emerged as a modifiable determinant of sustained PROMIS engagement.\u003c/p\u003e \u003cp\u003e These findings demonstrate that hybrid implementation strategies combining automated EHR deployment with structured human oversight can overcome prior workflow and engagement barriers and enable scalable, high quality patient reported outcome collection in interventional spine care.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBVNA = basivertebral nerve ablation; BVN = basivertebral nerve; PROMIS = Patient-Reported Outcomes Measurement Information System\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the manuscript preparation process\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eDuring the preparation of this work the author(s) used ChatGPT 5 in order to edit text for clarity and generate figures and tables. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This study was conducted in accordance with the Declaration of Helsinki. Ethical review and approval for this retrospective feasibility and quality improvement study were obtained from the enterprise\u0026rsquo;s Institutional Review Board (25-010101). Informed consent was waived because this study involved retrospective review of existing data and posed minimal risk to participants.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFischgrund JS, Rhyne A, Franke J et al (2018) Intraosseous basivertebral nerve ablation for the treatment of chronic low back pain: a prospective randomized double-blind sham-controlled multi-center study. Eur Spine J 27(5):1146\u0026ndash;1156\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhalil JG, Smuck M, Koreckij T et al (2019) Prospective randomized controlled trial of basivertebral nerve ablation for the treatment of chronic low back pain: 24-month results. Spine J 19(10):1620\u0026ndash;1632\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmuck M, Khalil J, Barrette K, Jarosz R (2021) Durability of intraosseous basivertebral nerve ablation for chronic low back pain: 5-year results from a prospective randomized trial. Spine J 21(2):212\u0026ndash;220\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCormick ZL, Fogarty AE, Conger A et al (2025) The Effectiveness of Basivertebral Nerve Radiofrequency Ablation for the Treatment of Vertebrogenic Low Back Pain: 1-Year Results of a Prospective Real-World Cohort Study. Pain Med. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/pm/pnaf122\u003c/span\u003e\u003cspan address=\"10.1093/pm/pnaf122\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHung M, Stuart AR, Higgins TF, Saltzman CL, Kubiak EN (2019) Establishing minimally important difference values for PROMIS measures. J Clin Epidemiol 112:38\u0026ndash;46\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYost KJ, Eton DT, Garcia SF, Cella D (2011) Minimally important differences were estimated for six PROMIS-Cancer scales in advanced-stage cancer patients. J Clin Epidemiol 64(5):507\u0026ndash;516\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"spine, pain, interventional, outcomes","lastPublishedDoi":"10.21203/rs.3.rs-9405355/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9405355/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo evaluate the feasibility of collecting Patient-Reported Outcomes Measurement Information System (PROMIS) data within an electronic health record (EHR) for patients undergoing basivertebral nerve ablation (BVNA).\u003c/p\u003e\u003ch2\u003eDesign:\u003c/h2\u003e \u003cp\u003eRetrospective feasibility study.\u003c/p\u003e\u003ch2\u003eSetting:\u003c/h2\u003e \u003cp\u003eAcademic community-based health system.\u003c/p\u003e\u003ch2\u003eSubjects:\u003c/h2\u003e \u003cp\u003eSeventy-one unique patients (73 procedures) treated with BVNA between 2022\u0026ndash;2025.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePROMIS Pain Interference, Pain Intensity, and Physical Function surveys were administered at baseline and at 3-, 6-, and 12-month follow-up using EHR-embedded automated workflows. In parallel, a structured quality improvement intervention was implemented to improve survey completion via emphasis on baseline survey completion. The intervention included a standardized nursing rooming checkpoint to verify PROMIS completion prior to the procedure, staff education with scripted patient engagement language, real-time EHR visual prompts using dot phrases to identify incomplete surveys, and monthly site-level performance dashboards reviewed with clinical staff and leadership. Completion rates were extracted from institutional dashboards and workflow bottlenecks were identified through process mapping and staff feedback. A two-proportion test compared pre- and post-intervention baseline completion rates. Clinic visit duration was tracked as a balancing measure to evaluate potential workflow burden.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSeventy-one patients underwent 73 BVNA procedures. Completion rates were 31.82% at baseline, 77.78% at 3 months, 40.00% at 6 months, and 100% at 12 months among patients reaching those timepoints. Longitudinal engagement was 56%, while longitudinal completeness was 33%. Baseline survey completion improved from 31.82% (21/66) before intervention to 100% (6/6) following implementation (z\u0026thinsp;\u0026asymp;\u0026thinsp;3.0, p\u0026thinsp;\u0026asymp;\u0026thinsp;0.003) durable through three months. Clinic workflow efficiency was not adversely affected, with 83% of visits remaining within the standard 30-minute time slot and no statistically significant increase in visit duration (p\u0026thinsp;\u0026asymp;\u0026thinsp;0.36).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003ePROMIS data collection during interventional spine care is feasible and can be reliably integrated into routine clinical workflows when supported by targeted quality improvement interventions. Improving baseline survey capture substantially expands the denominator of patients eligible for longitudinal outcome measurement without increasing clinical workload. Hybrid implementation strategies combining automated EHR deployment with structured clinical oversight may enable reliable PROMIS integration in procedural spine practice.\u003c/p\u003e","manuscriptTitle":"Feasibility of Integrating PROMIS Measures into an Interventional Spine Workflow: Lessons from a Basivertebral Nerve Ablation Registry","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 08:07:40","doi":"10.21203/rs.3.rs-9405355/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2084b731-a9fe-4700-86ac-b93404d468b5","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"50299235145541066690499381123592844499","date":"2026-05-10T10:43:57+00:00","index":27,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T08:07:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 08:07:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9405355","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9405355","identity":"rs-9405355","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}