Symptom Management Implementation of Patient Reported Outcomes in Oncology (SIMPRO)

SIMPRO Research Center: Integration and Implementation of PROs for Symptom Management in Oncology Practice

Deficits in the management of common symptoms cause substantial morbidity for cancer patients.Because the health care delivery system is structured to be reactive and not proactive, there are missed opportunities to optimize symptom control. Growth in Internet access and proliferation of smartphones has created an opportunity to re-engineer cancer care delivery. Electronic symptom tracking and feedback is a promising strategy to improve symptom control. Electronic patient reported outcome (ePRO) monitoring of cancer symptoms has been shown to decrease symptom burden, improve quality of life, reduce acute care and even extend survival. SIMPRO will use functioning ePRO prototypes to create and refine the electronic symptom management system eSyM

Study Overview

• Status: Completed
• Conditions: Gynecologic Cancer; Thoracic Cancer; Gastrointestinal Cancer; Other Cancer
• Intervention / Treatment: Other: Stakeholder Survey (Control Period); Other: Stakeholder Survey (Intervention Period); Other: SASS Questionnaire; Other: Qualitative Interview; Other: eSyM

Detailed Description

A multi-disciplinary team of investigators from 6 health systems have formed the Symptom Management IMplementation of Patient Reported Outcomes in Oncology (SIMPRO) Research Center. SIMPRO will use functioning ePRO prototypes to create and refine the electronic symptom management system eSyM. eSyM is the name of the platform the team will refine, integrate, implement and evaluate. eSyM addresses each of the 4 evidence gaps by:

• Implementing eSyM in cancer centers in small, rural or community-based systems.
• Integrating eSyM into the EHR (electronic health record) of the predominant vendor used nationwide.
• Leveraging evidence-based tools, patient engagement, and population management.
• Executing this work using the Consolidated Framework for Implementation Research across all phases to maximize the chances that eSyM and similar systems achieve their intended goals and decrease the morbidity of cancer treatment at a population level.

This project contains 5 activities:

1. Obtain stakeholder feedback
2. Build and deploy eSyM
3. Pilot test eSyM
4. Pragmatic stepped-wedge cluster randomized trial
5. Integration of eSyM data to develop algorithms to estimate the risk of experiencing an outcome, including, but not limited to, ED usage and hospitalization among cancer patients

• Study Type: Interventional
• Enrollment (Actual): 42808
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Maine
    • Portland, Maine, United States, 04101
      • Maine Medical Center
  • Massachusetts
    • Boston, Massachusetts, United States, 02115
      • Dana Farber Cancer Institute
  • New Hampshire
    • Lebanon, New Hampshire, United States, 03756
      • Dartmouth-Hitchcock Medical Center
  • Rhode Island
    • Providence, Rhode Island, United States, 02905
      • Brown University Health (formerly Lifespan Cancer Institute)
  • Tennessee
    • Memphis, Tennessee, United States, 38120
      • Baptist Memoiral HealthCare
  • West Virginia
    • Morgantown, West Virginia, United States, 26506
      • West Virginia University Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

Stakeholder Feedback and Stakeholder Qualitative Interviews Population:

• Age ≥ 18 years
• The potential stakeholders are: patient advisory council members, health system leaders, clinicians, clinic support staff/administration, IT/Informatics staff

Cluster Randomized Trial, Patient QualitativeInterviews, Pilot Testing & SASS Questionnaire Population:

• Age ≥ 18 years

• Priority population will be patients who meet one of the following:

  • Suspected thoracic cancer [lung or bronchus] AND is inpatient following thoracic surgery.
  • Suspected gastrointestinal cancer [colorectal, pancreas, liver/biliary, esophagus,or gastric] AND is inpatient following gastrointestinal surgery.
  • Suspected gynecologic cancer [ovary, uterus, or cervix] AND is inpatient following gynecologic surgery.
  • Diagnosis of thoracic cancer [lung or bronchus] AND scheduled to start a new treatment plan for thoracic cancer.
  • Diagnosis of gastrointestinal cancer [colorectal, pancreas, liver/biliary, esophagus,or gastric] AND scheduled to start a new treatment plan for gastrointestinal cancer.
  • Diagnosis of gynecologic cancer [ovary, uterus, or cervix] AND scheduled to start a new treatment plan for gynecologic cancer.

• Total population allowed to use eSyM:

  • Any patient at any participating site.

Exclusion Criteria:

- Participants not meeting the inclusion critera above.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

9

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Other: Stakeholder Feedback (Control Period); Eligible stakeholders at each SIMPRO site were invited to provide feedback through focus groups, team meetings, and surveys before the trial rollout of eSyM to inform development and implementation. Stakeholders included: patient advisory councils; health system leaders; clinicians; clinic support staff/administration; IT/Informatics	Other: Stakeholder Survey (Control Period); Before eSyM go-live, study team members from each site will solicit input via emailed survey, remote meetings and/or in-person meeting on the use of ePROs in oncology from stakeholders to obtain input regarding adaptation, anticipated challenges, and implementation.
Other: Stakeholder Feedback (Intervention Period); Eligible stakeholders at each SIMPRO site were invited to provide feedback through surveys after the trial rollout of eSyM to inform intervention normalization and sustainability. Stakeholders included: health system leaders; clinicians; clinic support staff/administration; IT/Informatics	Other: Stakeholder Survey (Intervention Period); After eSyM go-live and on an ongoing basis, we will evaluate the implementation process at each of the sites with a focus on adoption, appropriateness, acceptability, sustainability, penetration, and scalability. We will do so through emailed surveys and/or discussions with health system leadership, clinicians, clinic support staff, and informatics/IT staff.
Other: SASS Questionnaire Participants (Control Period); A subset of trial control patients were asked to complete a research questionnaire called the SASS Questionnaire before the roll-out of eSyM to assess patient outcomes including self-efficacy, attainment of informational needs, symptom burden, and satisfaction with care.	Other: SASS Questionnaire; A subset of control and intervention patients will be asked to complete a research questionnaire called the "SASS Questionnaire" asking about their Self-efficacy, Attainment of information needs, Symptom burden, and Satisfaction with care.
Other: SASS Questionnaire Participants (Intervention Period); A subset of trial intervention patients were asked to complete a research questionnaire called the SASS Questionnaire after the roll-out of eSyM to assess patient outcomes including self-efficacy, attainment of informational needs, symptom burden, and satisfaction with care.	Other: SASS Questionnaire; A subset of control and intervention patients will be asked to complete a research questionnaire called the "SASS Questionnaire" asking about their Self-efficacy, Attainment of information needs, Symptom burden, and Satisfaction with care.
Other: Patient Qualitative Interviews; A subset of trial intervention patients were asked to participate in a one-time patient interview to provide feedback on facilitators and barriers to eSyM implementation and adoption after the roll-out of eSyM.	Other: Qualitative Interview; A small subset of patients and stakeholders were invited to take part in qualitative interviews after the eSyM trial rollout.
Other: Stakeholder Qualitative Interviews; A subset of eligible stakeholders at each site were asked to participate in a one-time interview to provide feedback on facilitators and barriers to eSyM implementation and adoption after the roll-out of eSyM.	Other: Qualitative Interview; A small subset of patients and stakeholders were invited to take part in qualitative interviews after the eSyM trial rollout.
Other: Pilot Testing; A subset of control patients at each site were selected to pilot test the eSyM intervention prior to trial start.	Other: eSyM; The electronic symptom management (eSyM) program is the EHR-integrated ePRO program being evaluated through this trial.
No Intervention: Cluster Randomized Trial (Control Patients); These patients (and/or proxy) were seen at a participating site prior to the trial rollout of eSyM and were not exposed to the eSyM intervention.
Experimental: Cluster Randomized Trial (Intervention Patients); These patients (and/or proxy) were seen at a participating site after the trial rollout of eSyM and were exposed to the eSyM intervention.	Other: eSyM; The electronic symptom management (eSyM) program is the EHR-integrated ePRO program being evaluated through this trial.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Emergency Department Treat/Release [EDTR] Event Occurrence Status at Day 30	The primary study outcome of the stepped wedge cluster RCT (randomized controlled trial) is the EDTR rate. This outcome will be defined in relation to the date of discharge from hospital (surgical cohort) or the initiation date of a new intravenous chemo regimen (medical oncology cohort). This is a binary outcome and we will analyze the absolute difference and odds ratio for the medical oncology and surgical cohorts combined and independently.	30 days

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Emergency Department Treat/Release [EDTR] Event Occurrence Status at Day 90	This outcome will be defined in relation to the date of discharge from hospital (surgical cohort) or the initiation date of a new intravenous chemo regimen (medical oncology cohort). This is a binary outcome and we will analyze the absolute difference and odds ratio for the medical oncology and surgical cohorts combined and independently.	90 days
Admissions Event Occurrence Status at Day 30	This outcome will be defined in relation to the date of discharge from hospital (surgical cohort) or the initiation date of a new intravenous chemo regimen (medical oncology cohort). This is a binary outcome and we will analyze the absolute difference and odds ratio for the medical oncology and surgical cohorts combined and independently.	30 Days
Admissions Event Occurrence Status at Day 90	This outcome will be defined in relation to the date of discharge from hospital (surgical cohort) or the initiation date of a new intravenous chemo regimen (medical oncology cohort). This is a binary outcome and we will analyze the absolute difference and odds ratio for the medical oncology and surgical cohorts combined and independently.	90 Days
Difference in Fatigue PROMIS Scores Reported by Participants Before and After eSyM Exposure	Difference in PROMIS fatigue scores between the pre-live and post-live eSyM cohorts. Since the two cohorts were comprised of different patients, comparisons were performed at the population level using mean T-scores. Fatigue was assessed using the PROMIS Fatigue 4-item short form with responses converted to T-scores (score range: 50 indicates the population mean with a standard deviation of 10; decrease in score indicates a positive change). All PROMIS items were scored using the standardized scoring tool kit. The differences in mean T-scores and the corresponding 95% confidence intervals (CI) were calculated for each PROMIS item, comparing the post-live versus pre-live cohort. When comparing group-level change in PROMIS scores, even trivial differences can be statistically significant if the sample size is large enough. The threshold to evaluate within-group change or to make a between-group comparison generally ranges between 2 and 6 T-score points (Terwee et al., 2021).	30-90 days before and after eSyM go-live
Difference in Depression PROMIS Scores Reported by Participants Before and After eSyM Exposure	Difference in PROMIS depression scores between the pre-live and post-live eSyM cohorts. Since the two cohorts were comprised of different patients, comparisons were performed at the population level using mean T-scores. Depression was assessed using the PROMIS Emotional Distress-Depression 4-item short form with responses converted to T-scores (score range: 50 indicates the population mean with a standard deviation of 10; decrease in score indicates a positive change). All PROMIS items were scored using the standardized scoring tool kit. The differences in mean T-scores and the corresponding 95% confidence intervals (CI) were calculated for each PROMIS item, comparing the post-live versus pre-live cohort. When comparing group-level change in PROMIS scores, even trivial differences can be statistically significant if the sample size is large enough. The threshold to evaluate within-group change or to make a between-group comparison generally ranges between 2 and 6 T-score points.	30-90 days before and after eSyM go-live
Difference in Anxiety PROMIS Scores Reported by Participants Before and After eSyM Exposure	Difference in PROMIS anxiety scores between the pre-live and post-live eSyM cohorts. Since the two cohorts were comprised of different patients, comparisons were performed at the population level using mean T-scores. Anxiety was assessed using the PROMIS Emotional Distress-Anxiety 4-item short form with responses converted to T-scores (score range: 50 indicates the population mean with a standard deviation of 10; decrease in score indicates a positive change). All PROMIS items were scored using the standardized scoring tool kit. The differences in mean T-scores and the corresponding 95% confidence intervals (CI) were calculated for each PROMIS item, comparing the post-live versus pre-live cohort. When comparing group-level change in PROMIS scores, even trivial differences can be statistically significant if the sample size is large enough. The threshold to evaluate within-group change or to make a between-group comparison generally ranges between 2 and 6 T-score points.	30-90 days before and after eSyM go-live
Difference in Pain Interference PROMIS Scores Reported by Participants Before and After eSyM Exposure	Difference in PROMIS pain interference scores between the pre-live and post-live eSyM cohorts. Since the two cohorts were comprised of different patients, comparisons were performed at the population level using mean T-scores. Pain interference was assessed using the PROMIS Pain Interference 4-item short form with responses converted to T-scores (score range: 50 indicates the population mean with a standard deviation of 10; decrease in score indicates a positive change). All PROMIS items were scored using the standardized scoring tool kit. The differences in mean T-scores and the corresponding 95% confidence intervals (CI) were calculated for each PROMIS item, comparing the post-live versus pre-live cohort. When comparing group-level change in PROMIS scores, even trivial differences can be statistically significant if the sample size is large enough. The threshold to evaluate within-group change or to make a between-group comparison generally ranges between 2 and 6 T-score points.	30-90 days before and after eSyM go-live
Difference in Self-Efficacy PROMIS Scores Reported by Participants Before and After eSyM Exposure	Difference in PROMIS self-efficacy scores between pre-live and post-live eSyM cohorts. Since the two cohorts were comprised of different patients, comparisons were performed at the population level using mean T-scores. Self-efficacy was assessed using the PROMIS Self-Efficacy for Managing Symptoms 8-item short form with responses converted to T-scores (score range: 50 indicates the population mean with a standard deviation of 10; decrease in score indicates a positive change). All PROMIS items were scored using the standardized scoring tool kit. The differences in mean T-scores and the corresponding 95% confidence intervals were calculated for each PROMIS item, comparing the post-live versus pre-live cohort. When comparing group-level change in PROMIS scores, even trivial differences can be statistically significant if the sample size is large enough. The threshold to evaluate within-group change or to make a between-group comparison generally ranges between 2 and 6 T-score points.	30-90 days before and after eSyM go-live
Difference in Physical Function PROMIS Scores Reported by Participants Before and After eSyM Exposure	Difference in PROMIS physical function scores between the pre-live and post-live eSyM cohorts. Since the two cohorts were comprised of different patients, comparisons were performed at the population level using mean T-scores. Physical function was assessed using the PROMIS Physical Function 4-item short form with responses converted to T-scores (score range: 50 indicates the population mean with a standard deviation of 10; decrease in score indicates a positive change). All PROMIS items were scored using the standardized scoring tool kit. The differences in mean T-scores and the corresponding 95% confidence intervals (CI) were calculated for each PROMIS item, comparing the post-live versus pre-live cohort. When comparing group-level change in PROMIS scores, even trivial differences can be statistically significant if the sample size is large enough. The threshold to evaluate within-group change or to make a between-group comparison generally ranges between 2 and 6 T-score points).	30-90 days before and after eSyM go-live
Emergency Department Treat/Release [EDTR] Event Occurrence Status at Day 30 (Comparing eSyM Intervention Responders Versus Non-Responders)	The secondary study outcome of the stepped wedge cluster RCT (randomized controlled trial) is the difference in the EDTR rate between eSyM responders and non-responders. This outcome will be defined in relation to the date of discharge from hospital (surgical cohort) or the initiation date of a new intravenous chemo regimen (medical oncology cohort). This is a binary outcome and we will analyze the absolute difference and odds ratio for the medical oncology and surgical cohorts combined and independently. NOTE: The total number of intervention participants in this analysis is greater than the number of intervention participants included in the primary analyses (outcomes 1-4). For outcomes outcomes 1-4, we used the patient's first event during the entire study period. To conduct this analysis of eSyM responders, we used the patient's first event during the intervention period. Approximately 10% of patients in this analysis were counted as a control event in the prior analyses.	30 days
Emergency Department Treat/Release [EDTR] Event Occurrence Status at Day 90 (Comparing eSyM Intervention Responders Versus Non-Responders)	This outcome will be defined in relation to the date of discharge from hospital (surgical cohort) or the initiation date of a new intravenous chemo regimen (medical oncology cohort). This is a binary outcome and we will analyze the absolute difference and odds ratio for the medical oncology and surgical cohorts combined and independently. NOTE: The total number of intervention participants in this analysis is greater than the number of intervention participants included in the primary analyses (outcomes 1-4). For outcomes outcomes 1-4, we used the patient's first event during the entire study period. To conduct this analysis of eSyM responders, we used the patient's first event during the intervention period. Approximately 10% of patients in this analysis were counted as a control event in the prior analyses.	90 days
Admissions Event Occurrence Status at Day 30 (Comparing eSyM Intervention Responders Versus Non-Responders)	This outcome will be defined in relation to the date of discharge from hospital (surgical cohort) or the initiation date of a new intravenous chemo regimen (medical oncology cohort). This is a binary outcome and we will analyze the absolute difference and odds ratio for the medical oncology and surgical cohorts combined and independently. NOTE: The total number of intervention participants in this analysis is greater than the number of intervention participants included in the primary analyses (outcomes 1-4). For outcomes outcomes 1-4, we used the patient's first event during the entire study period. To conduct this analysis of eSyM responders, we used the patient's first event during the intervention period. Approximately 10% of patients in this analysis were counted as a control event in the prior analyses.	30 Days
Admissions Event Occurrence Status at Day 90 (Comparing eSyM Intervention Responders Versus Non-Responders)	This outcome will be defined in relation to the date of discharge from hospital (surgical cohort) or the initiation date of a new intravenous chemo regimen (medical oncology cohort). This is a binary outcome and we will analyze the absolute difference and odds ratio for the medical oncology and surgical cohorts combined and independently. NOTE: The total number of intervention participants in this analysis is greater than the number of intervention participants included in the primary analyses (outcomes 1-4). For outcomes outcomes 1-4, we used the patient's first event during the entire study period. To conduct this analysis of eSyM responders, we used the patient's first event during the intervention period. Approximately 10% of patients in this analysis were counted as a control event in the prior analyses.	90 Days

Collaborators and Investigators

• Sponsor: Dana-Farber Cancer Institute
• Collaborators: National Cancer Institute (NCI); Dartmouth-Hitchcock Medical Center; West Virginia University; RTI International; MaineHealth; Lifespan; Baptist Memorial Health Care Corporation
• Investigators: Principal Investigator: Michael Hassett, MD, Dana-Farber Cancer Institute

Publications and helpful links

General Publications

• Teunissen SC, Wesker W, Kruitwagen C, de Haes HC, Voest EE, de Graeff A. Symptom prevalence in patients with incurable cancer: a systematic review. J Pain Symptom Manage. 2007 Jul;34(1):94-104. doi: 10.1016/j.jpainsymman.2006.10.015. Epub 2007 May 23.
• Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin. 2017 Jan;67(1):7-30. doi: 10.3322/caac.21387. Epub 2017 Jan 5.
• Hernandez-Boussard T, Graham LA, Desai K, Wahl TS, Aucoin E, Richman JS, Morris MS, Itani KM, Telford GL, Hawn MT. The Fifth Vital Sign: Postoperative Pain Predicts 30-day Readmissions and Subsequent Emergency Department Visits. Ann Surg. 2017 Sep;266(3):516-524. doi: 10.1097/SLA.0000000000002372.
• Cleeland CS. Symptom burden: multiple symptoms and their impact as patient-reported outcomes. J Natl Cancer Inst Monogr. 2007;(37):16-21. doi: 10.1093/jncimonographs/lgm005.
• Hofman M, Ryan JL, Figueroa-Moseley CD, Jean-Pierre P, Morrow GR. Cancer-related fatigue: the scale of the problem. Oncologist. 2007;12 Suppl 1:4-10. doi: 10.1634/theoncologist.12-S1-4.
• Temel JS, Pirl WF, Lynch TJ. Comprehensive symptom management in patients with advanced-stage non-small-cell lung cancer. Clin Lung Cancer. 2006 Jan;7(4):241-9. doi: 10.3816/CLC.2006.n.001.
• Janjan N. Palliation and supportive care in radiation medicine. Hematol Oncol Clin North Am. 2006 Feb;20(1):187-211. doi: 10.1016/j.hoc.2006.01.010.
• Fleishman SB. Treatment of symptom clusters: pain, depression, and fatigue. J Natl Cancer Inst Monogr. 2004;(32):119-23. doi: 10.1093/jncimonographs/lgh028.
• Kenzik KM, Ganz PA, Martin MY, Petersen L, Hays RD, Arora N, Pisu M. How much do cancer-related symptoms contribute to health-related quality of life in lung and colorectal cancer patients? A report from the Cancer Care Outcomes Research and Surveillance (CanCORS) Consortium. Cancer. 2015 Aug 15;121(16):2831-9. doi: 10.1002/cncr.29415. Epub 2015 Apr 17.
• Hassett MJ, Wong S, Osarogiagbon RU, Bian J, Dizon DS, Jenkins HH, Uno H, Cronin C, Schrag D; SIMPRO Co-Investigators. Implementation of patient-reported outcomes for symptom management in oncology practice through the SIMPRO research consortium: a protocol for a pragmatic type II hybrid effectiveness-implementation multi-center cluster-randomized stepped wedge trial. Trials. 2022 Jun 16;23(1):506. doi: 10.1186/s13063-022-06435-1.
• Hassett MJ, Cronin C, Tsou TC, Wedge J, Bian J, Dizon DS, Hazard-Jenkins H, Osarogiagbon RU, Wong S, Basch E, Austin T, McCleary N, Schrag D. eSyM: An Electronic Health Record-Integrated Patient-Reported Outcomes-Based Cancer Symptom Management Program Used by Six Diverse Health Systems. JCO Clin Cancer Inform. 2022 Jan;6:e2100137. doi: 10.1200/CCI.21.00137.
• Paudel R, Enzinger AC, Uno H, Cronin C, Wong SL, Dizon DS, Hazard Jenkins H, Bian J, Osarogiagbon RU, Jensen RE, Mitchell SA, Schrag D, Hassett MJ. Effects of a change in recall period on reporting severe symptoms: an analysis of a pragmatic multisite trial. J Natl Cancer Inst. 2024 Jul 1;116(7):1137-1144. doi: 10.1093/jnci/djae049.
• Paudel R, Tramontano AC, Cronin C, Wong SL, Dizon DS, Jenkins HH, Bian J, Osarogiagbon RU, Schrag D, Hassett MJ. Assessing Patient Readiness for an Electronic Patient-Reported Outcome-Based Symptom Management Intervention in a Multisite Study. JCO Oncol Pract. 2024 Jan;20(1):77-84. doi: 10.1200/OP.23.00339. Epub 2023 Nov 27.
• Ivatury SJ, Hazard-Jenkins HW, Brooks GA, McCleary NJ, Wong SL, Schrag D. Translation of Patient-Reported Outcomes in Oncology Clinical Trials to Everyday Practice. Ann Surg Oncol. 2020 Jan;27(1):65-72. doi: 10.1245/s10434-019-07749-2. Epub 2019 Aug 26.
• Phillips JD, Wong SL. Patient-Reported Outcomes in Surgical Oncology: An Overview of Instruments and Scores. Ann Surg Oncol. 2020 Jan;27(1):45-53. doi: 10.1245/s10434-019-07752-7. Epub 2019 Aug 28.
• Hassett M, Dias S, Cronin C, Schrag D, McCleary N, Simpson J, Poirier-Shelton T, Bian J, Reich J, Dizon D, Begnoche M, Jenkins HH, Tasker L, Wong S, Pearson L, Paudel R, Osarogiagbon RU. Strategies for implementing an electronic patient-reported outcomes-based symptom management program across six cancer centers. BMC Health Serv Res. 2024 Nov 12;24(1):1386. doi: 10.1186/s12913-024-11536-5.
• Paudel R, Dias S, Wade CG, Cronin C, Hassett MJ. Use of Patient-Reported Outcomes in Risk Prediction Model Development to Support Cancer Care Delivery: A Scoping Review. JCO Clin Cancer Inform. 2024 Nov;8:e2400145. doi: 10.1200/CCI-24-00145. Epub 2024 Nov 1.
• Mallow J, Bailey A, Tasker L, Hazard H, Hassett M, Cronin C, Paudel R, Bian J, Dizon DS, Osarogiagbon RU, Schrag D, Wong SL. Perceptions of an Electronic Patient Symptom Reporting Tool by Clinicians. Comput Inform Nurs. 2025 Apr 21. doi: 10.1097/CIN.0000000000001313. Online ahead of print.
• Beqari J, Hurd J, Tramontano AC, Cronin C, Potter A, Wong S, Schrag D, Dizon DS, Bian J, Osarogiagbon RU, Hazard-Jenkins H, Phillips JD, Abbas AE, Warikoo IM, Anderson M, Seastedt KP, Lanuti M, Colson YL, Wright CD, Hassett M, Jeffrey Yang CF. The implementation of an electronic symptom management system to monitor postoperative pain in thoracic surgery patients: A multicenter evaluation. JTCVS Open. 2025 Feb 25;25:485-499. doi: 10.1016/j.xjon.2025.02.010. eCollection 2025 Jun.
• Cronin, C., Barrett, F., Dias, S., Wong, S. L., Pearson, L., Hazard-Jenkins, H., Bian, J. J., Dizon, D. S., Osarogiagbon, R. U., Schrag, D., & Hassett, M. J. (2024). Electronic Patient-Reported Outcomes in Oncology: Lessons from Six Cancer Centers. NEJM Catalyst Innovations in Care Delivery, 5(2). https://doi.org/10.1056/cat.23.0331
• Kuharic M, Merle JL, Cella D, Mitchell SA, DiMartino L, Ridgeway JL, Dizon DS, Paudel R, Austin JD, Wong SL, Flores AM, Cheville AL, Smith JD; IMPACT Consortium. Psychometric evaluation of the NoMAD instrument in cancer care settings: assessing factorial validity, measurement invariance, and differential item functioning. Implement Sci Commun. 2025 Jun 16;6(1):72. doi: 10.1186/s43058-025-00756-3.

Study record dates

Study Major Dates

• Study Start (Actual): July 25, 2019
• Primary Completion (Actual): March 31, 2023
• Study Completion (Actual): June 9, 2025

Study Registration Dates

• First Submitted: February 20, 2019
• First Submitted That Met QC Criteria: February 21, 2019
• First Posted (Actual): February 22, 2019

Study Record Updates

• Last Update Posted (Estimated): August 27, 2025
• Last Update Submitted That Met QC Criteria: August 8, 2025
• Last Verified: August 1, 2025

More Information

Terms related to this study

• Keywords: Patient reported outcomes; Symptom management; Other Cancer; Digital health
• Additional Relevant MeSH Terms: Neoplasms by Site; Neoplasms; Digestive System Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Gastrointestinal Neoplasms
• Other Study ID Numbers: 18-734; 1UM1CA233080-01 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: The Dana-Farber / Harvard Cancer Center encourages and supports the responsible and ethical sharing of data from clinical trials. De-identified participant data from the final research data set used in the published manuscript may only be shared under the terms of a Data Use Agreement. Requests may be directed to: [contact information for Sponsor Investigator or designee]. The protocol and statistical analysis plan will be made available on Clinicaltrials.gov only as required by federal regulation or as a condition of awards and agreements supporting the research
• IPD Sharing Time Frame: Data can be shared no earlier than 1 year following the date of publication
• IPD Sharing Access Criteria: DFCI (Dana-Farber Cancer Institute) - Contact the Belfer Office for Dana-Farber Innovations (BODFI) at innovation@dfci.harvard.edu
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ICF

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No