Back to Authors

Smith, Ashley Wilder

https://orcid.org/0000-0001-9674-5717

Mayo Clinic

National Institutes of Health

Citations 13

Predictors of electronic health record (EHR) portal registration and frequency of portal use among patients with cancer prior to engagement in the IMPACT Consortium symptom management trials.
Yanez, Betina R. , Flores, Ann Marie , Bian, Jessica , Hassett, Michael J. , Griffin, Joan M. , Wong, Sandra L. , Kroner, Barbara, Preiss, Liliana , Jensen, Roxanne E. , Smith, Ashley Wilder , Popovic, Jennifer R. , Austin, Jessica D. , Mitchell, Sandra A , Osarogiagbon, Raymond U. , Cheville, Andrea

Journal of Clinical Oncology | September 30, 2022 | Volume: 40 | Issue: 28_suppl | Pages: 419-419

10.1200/jco.2022.40.28_suppl.419 Get It

419 Background: The patient portal is part of an electronic health record (EHR) that allows patients to communicate with their healthcare team. The portal also provides a platform for patients to receive and complete symptom surveys that can be directly integrated into the EHR, allowing clinical care teams to monitor symptoms and provide cancer symptom management. The Improving Management of symPtoms during And following Cancer Treatment (IMPACT) consortium, supported by the National Cancer Institute’s Cancer MoonshotSM, aims to improve symptom control for cancer patients through assessment and symptom management interventions deployed via the EHR. This initiative presents an opportunity to examine portal enrollment and variation in use, factors critical to successful implementation, especially among groups that have high cancer symptom burden. To this end, we examine: 1) relationships between portal enrollment prior to the launch of IMPACT interventions and neighborhood broadband access, demographic, and social characteristics; and 2) frequency of pre-intervention portal use for any purpose among enrollees. Methods: Data are derived from two of three IMPACT research centers. Enrollment in and frequency of portal use, mode of accessing the portal (web vs. phone), social, demographic, and cultural factors were extracted from the EHR. Rural Urban Commuting Area (RUCA) codes were used to classify population density and degree of rurality. Broadband access was estimated using 2015-2019 American Community Survey estimates matched to zip codes from enrolled IMPACT patients and classified as a patient’s residence being in a community with high (≥85% of households) or low (< 85% of households) access. Bivariate comparisons and adjusted odds ratios were used to describe all associations. Results: Forty-seven percent of patients (22,596/48,034) were enrolled in the portal prior to the intervention. Patients in zip codes with low broadband access and those who were men, > 65 years old, not White, of Hispanic ethnicity, or disabled or not employed had significantly lower odds of being enrolled in the portal. If enrolled, 21% (n = 4825) used the portal at least once a week. Less variation was found in the average frequency of portal use, but patients younger than 40, and those who were Black, disabled, unemployed, or those who used a mobile device to access the portal had the lowest odds of accessing it at least once a week. Conclusions: Significant disparities in portal enrollment exist across demographic groups and among those with limited broadband access. Among those enrolled, most used the portal less than once a week. Fewer differences in frequency of use were observed by sociodemographic factors. Improving portal enrollment and frequency of use may be critical for symptom management interventions deployed via patient portals.
Moving forward toward standardizing analysis of quality of life data in randomized cancer clinical trials
Bottomley, Andrew , Pe, Madeline , Sloan, Jeff A. , Basch, Ethan , Bonnetain, Franck, Calvert, Melanie , Campbell, Alicyn, Cleeland, Charles S. , Cocks, Kim , Collette, Laurence , Dueck, Amylou C. , Flechtner, Hans‐Henning , Gotay, Carolyn , Greimel, Eva , Griebsch, Ingolf , Grøenvold, Mogens , Hamel, Jean-François, King, Madeleine , Koller, Michael , Malone, Daniel C. , Martinelli, Francesca , Moinpour, Carol M. , Musoro, Jammbe , O’Connor, Daniel , Oliver, Kathy , Piault‐Louis, Elisabeth, Piccart, Martine , Pimentel, Francisco , Quinten, Chantal , Reijneveld, Jaap C. , Soltys, Katherine M, Sridhara, Rajeshwari , Taphoorn, Martin , Velikova, Galina , Coens, Corneel , Sloan, Jeff, Flechtner, Hans-Henning , Dueck, A. C. , Basch, Ethan , Devlin, Nancy J. , Kluetz, Paul Gustav , Mitchell, Sandra A , Schürmann, Christoph, Smith, Ashley Wilder

Clinical Trials | August 24, 2018 | Volume: 15 | Issue: 6 | Pages: 624-630

10.1177/1740774518795637 Get It

Background There is currently a lack of consensus on how health-related quality of life and other patient-reported outcome measures in cancer randomized clinical trials are analyzed and interpreted. This makes it difficult to compare results across randomized controlled trials (RCTs) synthesize scientific research, and use that evidence to inform product labeling, clinical guidelines, and health policy. The Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints Data for Cancer Clinical Trials (SISAQOL) Consortium aims to develop guidelines and recommendations to standardize analyses of patient-reported outcome data in cancer RCTs. Methods and Results Members from the SISAQOL Consortium met in January 2017 to discuss relevant issues. Data from systematic reviews of the current state of published research in patient-reported outcomes in cancer RCTs indicated a lack of clear reporting of research hypothesis and analytic strategies, and inconsistency in definitions of terms, including “missing data,”“health-related quality of life,” and “patient-reported outcome.” Based on the meeting proceedings, the Consortium will focus on three key priorities in the coming year: developing a taxonomy of research objectives, identifying appropriate statistical methods to analyze patient-reported outcome data, and determining best practices to evaluate and deal with missing data. Conclusion The quality of the Consortium guidelines and recommendations are informed and enhanced by the broad Consortium membership which includes regulators, patients, clinicians, and academics.
Responsiveness of 8 Patient‐Reported Outcomes Measurement Information System (PROMIS) measures in a large, community‐based cancer study cohort
Moinpour, Carol M. , Potosky, Arnold L. , Lobo, Tania , Hahn, Elizabeth A. , Hays, Ron D. , Cella, David , Keegan, Theresa H.M. , Paddock, Lisa E. , Stroup, Antoinette M. , Eton, David T. , Jensen, Roxanne E. , Smith, Ashley Wilder , Wu, Xiao‐Cheng

Cancer | October 11, 2016 | Volume: 123 | Issue: 2 | Pages: 327-335

10.1002/cncr.30354 Get It

BACKGROUND The Patient‐Reported Outcomes Measurement Information System (PROMIS) was a National Institutes of Health‐funded initiative to develop measures of symptoms and function. Responsiveness is the degree to which a measure can detect underlying changes over time. The objective of the current study was to document the responsiveness of 8 PROMIS measures in a large, population‐based cancer cohort. METHODS The Measuring Your Health study recruited 2968 patients who were diagnosed with 1 of 7 cancers between 2010 and 2012 through 4 Surveillance, Epidemiology, and End Results registries. Participants completed a baseline survey (6‐13 months after diagnosis) and a 6‐month follow‐up survey. Changes in 8 PROMIS scores were compared with global ratings of transition, changes in performance status, and clinical events. RESULTS Measures were responsive to 6‐month declines and improvements in performance status with small to large effect sizes (ES) (Cohen d = 0.34‐0.71; P < .01). Mean changes and effect sizes were larger for participants who reported declines compared with those who reported improvements. Small‐to‐medium ES were observed in patients who reported being “a little” worse (d = 0.31‐0.56), and medium‐to‐large ES were observed in those who reported being “a lot” worse (d = 0.53‐0.72). Hospitalized participants reported significant score increases, resulting in worsening of pain (d = 0.51), fatigue (d = 0.35), and depression (d = 0.57; all P < .01). Cancer recurrence and progression were associated with smaller increases in pain, fatigue, and sleep disturbance (d = 0.22‐0.27). CONCLUSIONS The current results indicated that all 8 PROMIS measures were sensitive to patient‐perceived worsening and improvement and to major clinical events. These findings will be able to inform the design and interpretation of future research studies and clinical initiatives administering PROMIS measures. Cancer 2017;123:327–335. © 2016 American Cancer Society .