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Swirsky ES, Boyd AD, Gu C, Burke LA, Doorenbos AZ, Ezenwa MO, Knisely MR, Leigh JW, Li H, Mandernach MW, Molokie RE, Patil CL, Steffen AD, Shah N, deMartelly VA, Staman KL, Schlaeger JM. Monitoring and responding to signals of suicidal ideation in pragmatic clinical trials: Lessons from the GRACE trial for Chronic Sickle Cell Disease Pain. Contemp Clin Trials Commun 2023; 36:101218. [PMID: 37842321 PMCID: PMC10569945 DOI: 10.1016/j.conctc.2023.101218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 09/11/2023] [Accepted: 10/01/2023] [Indexed: 10/17/2023] Open
Abstract
Sickle cell disease (SCD) is a hemoglobin disorder and the most common genetic disorder that affects 100,000 Americans and millions worldwide. Adults living with SCD have pain so severe that it often requires opioids to keep it in control. Depression is a major global public health concern associated with an increased risk in chronic medical disorders, including in adults living with sickle cell disease (SCD). A strong relationship exists between suicidal ideation, suicide attempts, and depression. Researchers enrolling adults living with SCD in pragmatic clinical trials are obligated to design their methods to deliberately monitor and respond to symptoms related to depression and suicidal ideation. This will offer increased protection for their participants and help clinical investigators meet their fiduciary duties. This article presents a review of this sociotechnical milieu that highlights, analyzes, and offers recommendations to address ethical considerations in the development of protocols, procedures, and monitoring activities related to suicidality in depressed patients in a pragmatic clinical trial.
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Affiliation(s)
| | | | - Carol Gu
- University of Illinois Chicago, Chicago, IL, USA
| | | | | | | | | | | | - Hongjin Li
- University of Illinois Chicago, Chicago, IL, USA
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Boyd AD, Gonzalez-Guarda R, Lawrence K, Patil CL, Ezenwa MO, O’Brien EC, Paek H, Braciszewski JM, Adeyemi O, Cuthel AM, Darby JE, Zigler CK, Ho PM, Faurot KR, Staman KL, Leigh JW, Dailey DL, Cheville A, Del Fiol G, Knisely MR, Grudzen CR, Marsolo K, Richesson RL, Schlaeger JM. Potential bias and lack of generalizability in electronic health record data: reflections on health equity from the National Institutes of Health Pragmatic Trials Collaboratory. J Am Med Inform Assoc 2023; 30:1561-1566. [PMID: 37364017 PMCID: PMC10436149 DOI: 10.1093/jamia/ocad115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/07/2023] [Accepted: 06/13/2023] [Indexed: 06/28/2023] Open
Abstract
Embedded pragmatic clinical trials (ePCTs) play a vital role in addressing current population health problems, and their use of electronic health record (EHR) systems promises efficiencies that will increase the speed and volume of relevant and generalizable research. However, as the number of ePCTs using EHR-derived data grows, so does the risk that research will become more vulnerable to biases due to differences in data capture and access to care for different subsets of the population, thereby propagating inequities in health and the healthcare system. We identify 3 challenges-incomplete and variable capture of data on social determinants of health, lack of representation of vulnerable populations that do not access or receive treatment, and data loss due to variable use of technology-that exacerbate bias when working with EHR data and offer recommendations and examples of ways to actively mitigate bias.
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Affiliation(s)
- Andrew D Boyd
- Department of Biomedical and Health Information Sciences, University of Illinois Chicago, Chicago, Illinois, USA
| | | | - Katharine Lawrence
- Department of Population Health, New York University Grossman School of Medicine, New York City, New York, USA
| | - Crystal L Patil
- College of Nursing, University of Illinois Chicago, Chicago, Illinois, USA
| | - Miriam O Ezenwa
- University of Florida College of Nursing, Gainesville, Florida, USA
| | - Emily C O’Brien
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
| | - Hyung Paek
- Biostatistics (Health Informatics), Yale University, New Haven, Connecticut, USA
| | | | - Oluwaseun Adeyemi
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York City, New York, USA
| | - Allison M Cuthel
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York City, New York, USA
| | - Juanita E Darby
- College of Nursing, University of Illinois Chicago, Chicago, Illinois, USA
| | | | - P Michael Ho
- Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Keturah R Faurot
- Department of Physical Medicine and Rehabilitation, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Karen L Staman
- Duke University School of Medicine, Durham, North Carolina, USA
| | - Jonathan W Leigh
- College of Nursing, University of Illinois Chicago, Chicago, Illinois, USA
| | - Dana L Dailey
- Physical Therapy, St. Ambrose University, Davenport, Iowa, USA
- Department of Physical Therapy and Rehabilitation Science Department, University of Iowa, Iowa City, Iowa, USA
| | - Andrea Cheville
- Mayo Clinic Comprehensive Cancer Center, Rochester, Minnesota, USA
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | | | - Corita R Grudzen
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
| | - Keith Marsolo
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
| | - Rachel L Richesson
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Judith M Schlaeger
- College of Nursing, University of Illinois Chicago, Chicago, Illinois, USA
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Boyd AD, Gonzalez-Guarda R, Lawrence K, Patil CL, Ezenwa MO, O'Brien EC, Paek H, Braciszewski JM, Adeyemi O, Cuthel AM, Darby JE, Zigler CK, Ho PM, Faurot KR, Staman K, Leigh JW, Dailey DL, Cheville A, Del Fiol G, Knisely MR, Marsolo K, Richesson RL, Schlaeger JM. Equity and bias in electronic health records data. Contemp Clin Trials 2023; 130:107238. [PMID: 37225122 PMCID: PMC10330606 DOI: 10.1016/j.cct.2023.107238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/20/2023] [Accepted: 05/19/2023] [Indexed: 05/26/2023]
Abstract
Embedded pragmatic clinical trials (ePCTs) are conducted during routine clinical care and have the potential to increase knowledge about the effectiveness of interventions under real world conditions. However, many pragmatic trials rely on data from the electronic health record (EHR) data, which are subject to bias from incomplete data, poor data quality, lack of representation from people who are medically underserved, and implicit bias in EHR design. This commentary examines how the use of EHR data might exacerbate bias and potentially increase health inequities. We offer recommendations for how to increase generalizability of ePCT results and begin to mitigate bias to promote health equity.
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Affiliation(s)
- Andrew D Boyd
- Department of Biomedical and Health Information Sciences, University of Illinois Chicago, Chicago, IL, United States of America.
| | | | - Katharine Lawrence
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States of America
| | - Crystal L Patil
- University of Illinois Chicago, College of Nursing, Chicago, IL, United States of America
| | - Miriam O Ezenwa
- University of Florida College of Nursing, Gainesville, FL, United States of America
| | - Emily C O'Brien
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States of America
| | - Hyung Paek
- Yale University, New Haven, CT, United States of America
| | | | - Oluwaseun Adeyemi
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, NY, United States of America
| | - Allison M Cuthel
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, NY, United States of America
| | - Juanita E Darby
- University of Illinois Chicago, College of Nursing, Chicago, IL, United States of America
| | - Christina K Zigler
- Duke University School of Medicine, Durham, NC, United States of America
| | - P Michael Ho
- Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Keturah R Faurot
- Department of Physical Medicine and Rehabilitation, University of North Carolina School of Medicine, Chapel Hill, NC, United States of America
| | - Karen Staman
- Duke University School of Medicine, Durham, NC, United States of America
| | - Jonathan W Leigh
- University of Illinois Chicago, College of Nursing, Chicago, IL, United States of America
| | - Dana L Dailey
- St. Ambrose University, Davenport, IA, United States of America; University of Iowa, Iowa City, IA, United States of America
| | - Andrea Cheville
- Mayo Clinic Comprehensive Cancer Center, Rochester, MN, United States of America
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | | | - Keith Marsolo
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States of America
| | - Rachel L Richesson
- Department of Learning Health Sciences, University of Michigan Medical School
| | - Judith M Schlaeger
- University of Illinois Chicago, College of Nursing, Chicago, IL, United States of America
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Doorenbos AZ, Schlaeger JM, deMartelly VA, Burke LA, Boyd AD, Knisely MR, Leigh JW, Li H, Mandernach MW, Molokie RE, Patil CL, Steffen AD, Shah N, Ezenwa MO. Hybrid effectiveness-implementation trial of guided relaxation and acupuncture for chronic sickle cell disease pain (GRACE): A protocol. Contemp Clin Trials Commun 2023; 32:101076. [PMID: 36852100 PMCID: PMC9958255 DOI: 10.1016/j.conctc.2023.101076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 11/09/2022] [Accepted: 01/14/2023] [Indexed: 01/20/2023] Open
Abstract
Background People with sickle cell disease frequently use complementary and integrative therapies to cope with their pain, yet few studies have evaluated their effectiveness. The 3-arm, 3-site pragmatic Hybrid Effectiveness-implementation Trial of Guided Relaxation and Acupuncture for Chronic Sickle Cell Disease Pain (GRACE) has 3 priorities: (1) evaluate guided relaxation and acupuncture to improve pain control; (2) determine the most appropriate and effective treatment sequence for any given patient based on their unique characteristics; and (3) describe the processes and structures required to implement guided relaxation and acupuncture within health care systems. Methods Participants (N = 366) are being recruited and randomized 1:1:1 to one of 2 intervention groups or usual care. The acupuncture intervention group receives 10 sessions over approximately 5 weeks. The guided relaxation intervention group receives access to video sessions ranging from 2 to 20 min each viewed daily over 5 weeks. The usual care group receives the standard of clinical care for sickle cell disease. Participants are re-randomized at 6 weeks depending on their pain impact score. Assessments occur at 6 weeks, 12 weeks, and 24 weeks. The primary outcome is the change in pain impact score and secondary measures include opioid use, anxiety, depression, sleep, pain catastrophizing, substance use, global impression of change, constipation, and hospitalizations. The GRACE study uses the Consolidated Framework for Implementation Research to plan, execute, and evaluate the associated implementation processes. Conclusion The results from GRACE will represent a critical step toward improving management of pain affecting patients with sickle cell disease.ClinicalTrials.gov Identifier: NCT04906447.
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Affiliation(s)
- Ardith Z. Doorenbos
- College of Nursing, University of Illinois Chicago, 845 S. Damen, Chicago, IL, 60612, USA
| | - Judith M. Schlaeger
- College of Nursing, University of Illinois Chicago, 845 S. Damen, Chicago, IL, 60612, USA
| | - Victoria A. deMartelly
- College of Nursing, University of Illinois Chicago, 845 S. Damen, Chicago, IL, 60612, USA
| | - Larisa A. Burke
- College of Nursing, University of Illinois Chicago, 845 S. Damen, Chicago, IL, 60612, USA
| | - Andrew D. Boyd
- College of Applied Health Sciences, 1919 W Taylor St, Chicago, IL, 60612, USA
| | | | - Jonathan W. Leigh
- College of Nursing, University of Illinois Chicago, 845 S. Damen, Chicago, IL, 60612, USA
| | - Hongjin Li
- College of Nursing, University of Illinois Chicago, 845 S. Damen, Chicago, IL, 60612, USA
| | - Molly W. Mandernach
- Department of Medicine, UF Health, PO Box 100278, Gainesville, FL, 32610, USA
| | - Robert E. Molokie
- College of Applied Health Sciences, 1919 W Taylor St, Chicago, IL, 60612, USA
- Jesse Brown VA Medical Center, Chicago, IL, 60612, USA
| | - Crystal L. Patil
- College of Nursing, University of Illinois Chicago, 845 S. Damen, Chicago, IL, 60612, USA
| | - Alana D. Steffen
- College of Nursing, University of Illinois Chicago, 845 S. Damen, Chicago, IL, 60612, USA
| | - Nirmish Shah
- Department of Medicine, Duke University, 40 Medicine Circle, Durham, NC, 27710, USA
| | - Miriam O. Ezenwa
- College of Nursing, University of Florida, 1225 Center Drive, PO Box 100197, Gainesville, FL, 32610-0197, USA
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Leigh JW, Gerber BS, Gans CP, Kansal MM, Kitsiou S. Smartphone Ownership and Interest in Mobile Health Technologies for Self-care Among Patients With Chronic Heart Failure: Cross-sectional Survey Study. JMIR Cardio 2022; 6:e31982. [PMID: 35029533 PMCID: PMC8800088 DOI: 10.2196/31982] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 10/18/2021] [Accepted: 11/21/2021] [Indexed: 12/26/2022] Open
Abstract
Background Heart failure (HF) is a highly prevalent chronic condition that places a substantial burden on patients, families, and health care systems worldwide. Recent advances in mobile health (mHealth) technologies offer great opportunities for supporting many aspects of HF self-care. There is a need to better understand patients’ adoption of and interest in using mHealth for self-monitoring and management of HF symptoms. Objective The purpose of this study is to assess smartphone ownership and patient attitudes toward using mHealth technologies for HF self-care in a predominantly minority population in an urban clinical setting. Methods We conducted a cross-sectional survey of adult outpatients (aged ≥18 years) at an academic outpatient HF clinic in the Midwest. The survey comprised 34 questions assessing patient demographics, ownership of smartphones and other mHealth devices, frequently used smartphone features, use of mHealth apps, and interest in using mHealth technologies for vital sign and HF symptom self-monitoring and management. Results A total of 144 patients were approached, of which 100 (69.4%) participated in the study (63/100, 63% women). The participants had a mean age of 61.3 (SD 12.25) years and were predominantly Black or African American (61/100, 61%) and Hispanic or Latino (18/100, 18%). Almost all participants (93/100, 93%) owned a cell phone. The share of patients who owned a smartphone was 68% (68/100). Racial and ethnic minorities that identified as Black or African American or Hispanic or Latino reported higher smartphone ownership rates compared with White patients with HF (45/61, 74% Black or African American and 11/18, 61% Hispanic or Latino vs 9/17, 53% White). There was a moderate and statistically significant association between smartphone ownership and age (Cramér V [ΦC]=0.35; P<.001), education (ΦC=0.29; P=.001), and employment status (ΦC=0.3; P=.01). The most common smartphone features used by the participants were SMS text messaging (51/68, 75%), internet browsing (43/68, 63%), and mobile apps (41/68, 60%). The use of mHealth apps and wearable activity trackers (eg, Fitbits) for self-monitoring of HF-related parameters was low (15/68, 22% and 15/100, 15%, respectively). The most popular HF-related self-care measures participants would like to monitor using mHealth technologies were physical activity (46/68, 68%), blood pressure (44/68, 65%), and medication use (40/68, 59%). Conclusions Most patients with HF have smartphones and are interested in using commercial mHealth apps and connected health devices to self-monitor their condition. Thus, there is a great opportunity to capitalize on the high smartphone ownership among racial and ethnic minority patients to increase reach and enhance HF self-management through mHealth interventions.
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Affiliation(s)
- Jonathan W Leigh
- Department of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, IL, United States.,Division of Cardiology, Department of Medicine, University of Illinois at Chicago, Chicago, IL, United States
| | - Ben S Gerber
- Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worchester, MA, United States
| | - Christopher P Gans
- Division of Cardiology, Department of Medicine, University of Illinois at Chicago, Chicago, IL, United States
| | - Mayank M Kansal
- Division of Cardiology, Department of Medicine, University of Illinois at Chicago, Chicago, IL, United States
| | - Spyros Kitsiou
- Department of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, IL, United States
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