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Mehta SJ, Rhodes C, Linn KA, Reitz C, McDonald C, Okorie E, Williams K, Resnick D, Arostegui A, McAuliffe T, Wollack C, Snider CK, Peifer MK, Weinstein SP. Behavioral Interventions to Improve Breast Cancer Screening Outreach: Two Randomized Clinical Trials. JAMA Intern Med 2024:2818196. [PMID: 38709509 DOI: 10.1001/jamainternmed.2024.0495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
Importance Despite public health efforts, breast cancer screening rates remain below national goals. Objective To evaluate whether bulk ordering, text messaging, and clinician endorsement increase breast cancer screening rates. Design, Setting, and Participants Two concurrent, pragmatic, randomized clinical trials, each with a 2-by-2 factorial design, were conducted between October 25, 2021, and April 25, 2022, in 2 primary care regions of an academic health system. The trials included women aged 40 to 74 years with at least 1 primary care visit in the past 2 years who were eligible for breast cancer screening. Interventions Patients in trial A were randomized in a 1:1 ratio to receive a signed bulk order for mammogram or no order; in a factorial design, patients were concurrently randomized in a 1:1 ratio to receive or not receive text message reminders. Patients in trial B were randomized in a 1:1 ratio to receive a message signed by their primary care clinician (clinician endorsement) or from the organization (standard messaging); in a factorial design, patients were concurrently randomized in a 1:1 ratio to receive or not receive text message reminders. Main Outcomes and Measures The primary outcome was the proportion of patients who completed a screening mammogram within 3 months. Results Among 24 632 patients included, the mean (SD) age was 60.4 (7.5) years. In trial A, at 3 months, 15.4% (95% CI, 14.6%-16.1%) of patients in the bulk order arm and 12.7% (95% CI, 12.1%-13.4%) in the no order arm completed a mammogram, showing a significant increase (absolute difference, 2.7%; 95% CI, 1.6%-3.6%; P < .001). In the text messaging comparison arms, 15.1% (95% CI, 14.3%-15.8%) of patients receiving a text message completed a mammogram compared with 13.0% (95% CI, 12.4%-13.7%) of those in the no text messaging arm, a significant increase (absolute difference of 2.1%; 95% CI, 1.0%-3.0%; P < .001). In trial B, at 3 months, 12.5% (95% CI, 11.3%-13.7%) of patients in the clinician endorsement arm completed a mammogram compared with 11.4% (95% CI, 10.3%-12.5%) of those in the standard messaging arm, which was not significant (absolute difference, 1.1%; 95% CI, -0.5% to 2.7%; P = .18). In the text messaging comparison arms, 13.2% (95% CI, 12.0%-14.4%) of patients receiving a text message completed a mammogram compared with 10.7% (95% CI, 9.7%-11.8%) of those in the no text messaging arm, a significant increase (absolute difference, 2.5%; 95% CI, 0.8%-4.0%; P = .003). Conclusions and Relevance These findings show that text messaging women after initial breast cancer screening outreach via either electronic portal or mailings, as well as bulk ordering with or without text messaging, can increase mammogram completion rates. Trial Registration ClinicalTrials.gov Identifier: NCT05089903.
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Affiliation(s)
- Shivan J Mehta
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Corinne Rhodes
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Medicine, University of Pennsylvania, Philadelphia
| | - Kristin A Linn
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Catherine Reitz
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Caitlin McDonald
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Evelyn Okorie
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Keyirah Williams
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - David Resnick
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | | | - Timothy McAuliffe
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Colin Wollack
- Penn Medicine, University of Pennsylvania, Philadelphia
| | | | - MaryAnne K Peifer
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Medicine, University of Pennsylvania, Philadelphia
| | - Susan P Weinstein
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
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Mehta SJ, Palat S, McDonald C, Reitz C, Okorie E, Williams K, Tao J, Shaw PA, Glanz K, Asch DA. A Randomized Trial of Choice Architecture and Mailed Colorectal Cancer Screening Outreach in a Community Health Setting. Clin Gastroenterol Hepatol 2024:S1542-3565(24)00390-2. [PMID: 38697235 DOI: 10.1016/j.cgh.2024.04.003] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 04/03/2024] [Accepted: 04/05/2024] [Indexed: 05/04/2024]
Abstract
BACKGROUND & AIMS Mailed outreach for CRC screening increases uptake but it is unclear how to offer the choice of testing. We evaluated if the active choice between colonoscopy and fecal immunochemical test (FIT), or FIT alone, increased response compared to colonoscopy alone. METHODS This pragmatic randomized controlled trial at a community health center included patients between ages 50-74 who were not up to date with CRC screening. Patients were randomized 1:1:1 to: (1) Colonoscopy Only, (2) Active Choice of Colonoscopy or FIT, or (3) FIT Only. Patients received an outreach letter with instructions for testing (colonoscopy referral and/ or enclosed FIT kit), a reminder letter at 2 months, and another reminder at 3-5 months via text message or automated voice recording. The primary outcome was CRC screening completion within 6 months. RESULTS Among 738 patients in the final analysis, the mean age was 58.7 (SD 6.2); 48.6% were insured by Medicaid and 24.3% by Medicare; 71.7% were White, 16.9% were Black, and 7.3% were Hispanic/ Latino. At 6 months, 5.6% (95% CI, 2.8 to 8.5) completed screening in the Colonoscopy Only arm, 12.8% (95% CI, 8.6 to 17.0) in the Active Choice arm, and 11.3% (95% CI, 7.4 to 15.3) in the FIT Only arm. Compared to Colonoscopy Only, there was a significant increase in screening in Active Choice (absolute difference of 7.1%; 95% CI, 2.0 to 12.2; p=0.006) and FIT Only (absolute difference of 5.7%; 95% CI, 0.8 to 10.6; p=0.02). CONCLUSION Both choice of testing and FIT alone increased response and may align with patient preferences.
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Affiliation(s)
- Shivan J Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania; Center for Health Care Innovation, University of Pennsylvania.
| | - Sanjay Palat
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania; Center for Health Care Innovation, University of Pennsylvania
| | - Caitlin McDonald
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania; Center for Health Care Innovation, University of Pennsylvania
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania; Center for Health Care Innovation, University of Pennsylvania
| | - Evelyn Okorie
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania; Center for Health Care Innovation, University of Pennsylvania
| | - Keyirah Williams
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania; Center for Health Care Innovation, University of Pennsylvania
| | - Jinming Tao
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania; Center for Health Care Innovation, University of Pennsylvania
| | - Pamela A Shaw
- Biostatistics Division, Kaiser Permanente Washington Health Research Institute; Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
| | - Karen Glanz
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
| | - David A Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania
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Waddell KJ, Goel K, Park SH, Linn KA, Navathe AS, Liao JM, McDonald C, Reitz C, Moore J, Hyland S, Mehta SJ. Association of Electronic Self-Scheduling and Screening Mammogram Completion. Am J Prev Med 2024; 66:399-407. [PMID: 38085196 PMCID: PMC10922640 DOI: 10.1016/j.amepre.2023.11.002] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 11/02/2023] [Accepted: 11/02/2023] [Indexed: 01/29/2024]
Abstract
INTRODUCTION The purpose of this study was to evaluate if an electronic health record (EHR) self-scheduling function was associated with changes in mammogram completion for primary care patients who were eligible for a screening mammogram using U.S. Preventive Service Task Force recommendations. METHODS This was a retrospective cohort study (September 1, 2014-August 31, 2019, analyses completed in 2022) using a difference-in-differences design to examine mammogram completion before versus after the implementation of self-scheduling. The difference-in-differences estimate was the interaction between time (pre-versus post-implementation) and group (active EHR patient portal versus inactive EHR patient portal). The primary outcome was mammogram completion among all eligible patients, with completion defined as receiving a mammogram within 6 months post-visit. The secondary outcome was mammogram completion among patients who received a clinician order during their visit. RESULTS The primary analysis included 35,257 patient visits. The overall mammogram completion rate in the pre-period was 22.2% and 49.7% in the post-period. EHR self-scheduling was significantly associated with increased mammogram completion among those with an active EHR portal, relative to patients with an inactive portal (adjusted difference 13.2 percentage points [95% CI 10.6-15.8]). For patients who received a clinician mammogram order at their eligible visit, self-scheduling was significantly associated with increased mammogram completion among patients with an active EHR portal account (adjusted difference 14.7 percentage points, [95% CI 10.9-18.5]). CONCLUSIONS EHR-based self-scheduling was associated with a significant increase in mammogram completion among primary care patients. Self-scheduling can be a low-cost, scalable function for increasing preventive cancer screenings.
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Affiliation(s)
- Kimberly J Waddell
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Corporal Michael J. Cresencz VA Medical Center, Philadelphia, PA.
| | - Keshav Goel
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Sae-Hwan Park
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA
| | - Kristin A Linn
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania
| | - Amol S Navathe
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Corporal Michael J. Cresencz VA Medical Center, Philadelphia, PA
| | - Joshua M Liao
- Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Department of Medicine, University of Washington, Seattle, WA
| | - Caitlin McDonald
- Center for Health Care Transformation and Innovation, University of Pennsylvania, Philadelphia, PA
| | - Catherine Reitz
- Center for Health Care Transformation and Innovation, University of Pennsylvania, Philadelphia, PA
| | - Jake Moore
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Steve Hyland
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Shivan J Mehta
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Center for Health Care Transformation and Innovation, University of Pennsylvania, Philadelphia, PA
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Mehta SJ, McDonald C, Reitz C, Kastuar S, Snider CK, Okorie E, McNelis K, Shaikh H, Cook TS, Goldberg DS, Rothstein K. A randomized trial of mailed outreach with behavioral economic interventions to improve liver cancer surveillance. Hepatol Commun 2024; 8:e0349. [PMID: 38099859 PMCID: PMC10727671 DOI: 10.1097/hc9.0000000000000349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 11/08/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Surveillance rates for HCC remain limited in patients with cirrhosis. We evaluated whether opt-out mailed outreach increased uptake with or without a $20 unconditional incentive. METHODS This was a pragmatic randomized controlled trial in an urban academic health system including adult patients with cirrhosis or advanced fibrosis, at least 1 visit to a specialty practice in the past 2 years and no surveillance in the last 7 months. Patients were randomized in a 1:2:2 ratio to (1) usual care, (2) a mailed letter with a signed order for an ultrasound, or (3) a mailed letter with an order and a $20 unconditional incentive. The main outcome was the proportion with completion of ultrasound within 6 months. RESULTS Among the 562 patients included, the mean age was 62.1 (SD 11.1); 56.8% were male, 51.1% had Medicare, and 40.6% were Black. At 6 months, 27.6% (95% CI: 19.5-35.7) completed ultrasound in the Usual care arm, 54.5% (95% CI: 47.9-61.0) in the Letter + Order arm, and 54.1% (95% CI: 47.5-60.6) in the Letter + Order + Incentive arm. There was a significant increase in the Letter + Order arm compared to Usual care (absolute difference of 26.9%; 95% CI: 16.5-37.3; p<0.001), but no significant increase in the Letter + Order + Incentive arm compared to Letter + Order (absolute difference of -0.4; 95% CI: -9.7 to 8.8; p=0.93). CONCLUSIONS There was an increase in HCC surveillance from mailed outreach with opt-out framing and a signed order slip, but no increase in response to the financial incentive.
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Affiliation(s)
- Shivan J. Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, USA
| | - Caitlin McDonald
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, USA
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, USA
| | - Shivani Kastuar
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | | | - Evelyn Okorie
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, USA
| | - Kiernan McNelis
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, USA
| | - Hamzah Shaikh
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Tessa S. Cook
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - David S. Goldberg
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Kenneth Rothstein
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
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Mehta SJ, Mallozzi C, Shaw PA, Reitz C, McDonald C, Vandertuyn M, Balachandran M, Kopinsky M, Sevinc C, Johnson A, Ward R, Park SH, Snider CK, Rosin R, Asch DA. Effect of Text Messaging and Behavioral Interventions on COVID-19 Vaccination Uptake: A Randomized Clinical Trial. JAMA Netw Open 2022; 5:e2216649. [PMID: 35696165 PMCID: PMC9194662 DOI: 10.1001/jamanetworkopen.2022.16649] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
IMPORTANCE COVID-19 vaccine uptake among urban populations remains low. OBJECTIVE To evaluate whether text messaging with outbound or inbound scheduling and behaviorally informed content might increase COVID-19 vaccine uptake. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial with a factorial design was conducted from April 29 to July 6, 2021, in an urban academic health system. The trial comprised 16 045 patients at least 18 years of age in Philadelphia, Pennsylvania, with at least 1 primary care visit in the past 5 years, or a future scheduled primary care visit within the next 3 months, who were unresponsive to prior outreach. The study was prespecified in the trial protocol, and data were obtained from the intent-to-treat population. INTERVENTIONS Eligible patients were randomly assigned in a 1:20:20 ratio to (1) outbound telephone call only by call center, (2) text message and outbound telephone call by call center to those who respond, or (3) text message, with patients instructed to make an inbound telephone call to a hotline. Patients in groups 2 and 3 were concurrently randomly assigned in a 1:1:1:1 ratio to receive different content: standard messaging, clinician endorsement (eg, "Dr. XXX recommends"), scarcity ("limited supply available"), or endowment framing ("We have reserved a COVID-19 vaccine appointment for you"). MAIN OUTCOMES AND MEASURES The primary outcome was the proportion of patients who completed the first dose of the COVID-19 vaccine within 1 month, according to the electronic health record. Secondary outcomes were the completion of the first dose within 2 months and completion of the vaccination series within 2 months of initial outreach. Additional outcomes included the percentage of patients with invalid cell phone numbers (wrong number or nontextable), no response to text messaging, the percentage of patients scheduled for the vaccine, text message responses, and the number of telephone calls made by the access center. Analysis was on an intention-to-treat basis. RESULTS Among the 16 045 patients included, the mean (SD) age was 36.9 (11.1) years; 9418 (58.7%) were women; 12 869 (80.2%) had commercial insurance, and 2283 (14.2%) were insured by Medicaid; 8345 (52.0%) were White, 4706 (29.3%) were Black, and 967 (6.0%) were Hispanic or Latino. At 1 month, 14 of 390 patients (3.6% [95% CI, 1.7%-5.4%]) in the outbound telephone call-only group completed 1 vaccine dose, as did 243 of 7890 patients (3.1% [95% CI, 2.7%-3.5%]) in the text plus outbound call group (absolute difference, -0.5% [95% CI, -2.4% to 1.4%]; P = .57) and 253 of 7765 patients (3.3% [95% CI, 2.9%-3.7%]) in the text plus inbound call group (absolute difference, -0.3% [95% CI, -2.2% to 1.6%]; P = .72). Among the 15 655 patients receiving text messaging, 118 of 3889 patients (3.0% [95% CI, 2.5%-3.6%]) in the standard messaging group completed 1 vaccine dose, as did 135 of 3920 patients (3.4% [95% CI, 2.9%-4.0%]) in the clinician endorsement group (absolute difference, 0.4% [95% CI, -0.4% to 1.2%]; P = .31), 100 of 3911 patients (2.6% [95% CI, 2.1%-3.1%]) in the scarcity group (absolute difference, -0.5% [95% CI, -1.2% to 0.3%]; P = .20), and 143 of 3935 patients (3.6% [95% CI, 3.0%-4.2%]) in the endowment group (absolute difference, 0.6% [95% CI, -0.2% to 1.4%]; P = .14). CONCLUSIONS AND RELEVANCE There was no detectable increase in vaccination uptake among patients receiving text messaging compared with telephone calls only or behaviorally informed message content. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT04834726.
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Affiliation(s)
- Shivan J. Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | | | - Pamela A. Shaw
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Caitlin McDonald
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Matthew Vandertuyn
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Mohan Balachandran
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Michael Kopinsky
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Christianne Sevinc
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Aaron Johnson
- Penn Medicine, University of Pennsylvania, Philadelphia
| | - Robin Ward
- Penn Medicine, University of Pennsylvania, Philadelphia
| | - Sae-Hwan Park
- Penn Medicine, University of Pennsylvania, Philadelphia
| | | | - Roy Rosin
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - David A. Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
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Mehta SJ, Palat S, Reitz C, Okorie E, McDonald C, Shaw PA, Glanz K, Asch DA. YIA22-005: A Randomized Trial of Choice Architecture and Mailed Colorectal Cancer Screening Outreach in a Community Health Setting. J Natl Compr Canc Netw 2022. [DOI: 10.6004/jnccn.2021.7150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Shivan J. Mehta
- 1 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- 2 Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA
| | - Sanjay Palat
- 1 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- 2 Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA
| | - Catherine Reitz
- 1 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- 2 Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA
| | - Evelyn Okorie
- 1 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- 2 Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA
| | - Caitlin McDonald
- 1 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- 2 Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA
| | | | - Karen Glanz
- 3 University of Pennsylvania, Philadelphia, PA
| | - David A Asch
- 1 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- 2 Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA
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Lee NS, Anastos-Wallen R, Chaiyachati KH, Reitz C, Asch DA, Mehta SJ. Clinician Decisions After Notification of Elevated Blood Pressure Measurements From Patients in a Remote Monitoring Program. JAMA Netw Open 2022; 5:e2143590. [PMID: 35029664 PMCID: PMC8760617 DOI: 10.1001/jamanetworkopen.2021.43590] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
IMPORTANCE Guidelines recommend using telehealth for hypertension management, but insufficient evidence is available to guide strategies for incorporating telehealth data into clinical practice. OBJECTIVE To describe how primary care teams responded to elevated remote blood pressure (BP) alerts in the electronic health record (EHR) in a randomized clinical trial of BP telemonitoring conducted in routine practice settings. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study reviewed EHR documentation from May 8, 2018, to August 9, 2019, in a single urban academic family practice site. Primary care teams comprising 28 attending physicians and nurse practitioners, residents, and nurses cared for 162 patients in a text-based clinical trial of remote BP monitoring remote BP monitoring. Data were analyzed from October 21, 2019, to April 30, 2021. EXPOSURES Clinicians received a direct message in their EHR inbox when patients submitted at least 3 elevated BP readings. MAIN OUTCOMES AND MEASURES Categories and frequencies of clinician action, created via review of EHR-documented clinician responses to EHR alerts by 2 physicians. RESULTS Patients in this study (n = 162) were predominantly female (111 [68.5%]) and Black or African American (146 [90.1%]), whereas attending physicians (n = 21) were predominantly female (13 [61.9%]) and non-Hispanic White (19 [90.5%]) with a mean (SD) age of 51.6 (11.1) years. Five hundred fifty-two alerts fell into 12 categories of clinical actions. Clinicians acted on 343 alerts (62.1%). Common remote activities were to reconcile medications and assess adherence (120 of 552 alerts [21.7%]) and verify BP measurement technique (65 of 552 alerts [11.8%]). Clinicians also commonly requested appointments (120 of 552 alerts [21.7%]) and/or saw the patient in a subsequent office visit (114 of 552 alerts [20.7%]). Ninety-six alerts (17.4%) resulted in medication changes; half of these changes were remote (48 of 96 [50.0%]), and the other half were visit-based. For 209 of 552 alerts (37.9%), no changes were made to the care plan, typically without documenting clinical rationale (196 of 209 instances [93.8%]). Exploratory EHR review was used to infer potential clinical rationale for 106 (54.1%) of such cases, but there was insufficient information for the remaining 90 (45.9%). CONCLUSIONS AND RELEVANCE These findings suggest that EHR alerts for elevated BP during remote monitoring were effective in prompting a mix of remote and office-based management. It was also common for the plan of care to remain unchanged, possibly suggesting need for more refined alerts and improved clinician support.
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Affiliation(s)
- Natalie S. Lee
- Division of General Internal Medicine, The Ohio State University Wexner Medical Center, Columbus
| | - Rebecca Anastos-Wallen
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Krisda H. Chaiyachati
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Healthcare Innovation, University of Pennsylvania, Philadelphia
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Healthcare Innovation, University of Pennsylvania, Philadelphia
| | - David A. Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Healthcare Innovation, University of Pennsylvania, Philadelphia
| | - Shivan J. Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Healthcare Innovation, University of Pennsylvania, Philadelphia
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Mehta SJ, Reitz C, Niewood T, Volpp KG, Asch DA. Effect of Behavioral Economic Incentives for Colorectal Cancer Screening in a Randomized Trial. Clin Gastroenterol Hepatol 2021; 19:1635-1641.e1. [PMID: 32623005 PMCID: PMC7775888 DOI: 10.1016/j.cgh.2020.06.047] [Citation(s) in RCA: 3] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 06/15/2020] [Accepted: 06/21/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Financial incentives might increase participation in prevention such as screening colonoscopy. We studied whether incentives informed by behavioral economics increase participation in risk assessment for colorectal cancer (CRC) and completion of colonoscopy for eligible adults. METHODS Employees of a large academic health system (50-64 y old; n = 1977) were randomly assigned to groups that underwent risk assessment for CRC screening and direct access colonoscopy scheduling (control), or risk assessment, direct access colonoscopy scheduling, a $10 loss-framed incentive to complete risk assessment, and a $25 unconditional incentive for colonoscopy completion (incentive). The primary outcome was the percentage of participants who completed screening colonoscopy within 3 months of initial outreach. Secondary outcomes included the percentage of participants who scheduled colonoscopy and the percentage who completed the risk assessment. RESULTS At 3 months, risk assessment was completed by 19.5% of participants in the control group (95% CI, 17.0-21.9%) and 31.9% of participants in the incentive group (95% CI, 29.0-34.8%) (P < .001). At 3 months, 0.7% of controls had completed a colonoscopy (95% CI, .2%-1.2%) compared with 1.2% of subjects in the incentive group (95% CI, .5%-1.9%) (P = .25). CONCLUSIONS In a randomized trial of participants who underwent risk assessment for CRC with vs without financial incentive, the financial incentive increased CRC risk assessment completion but did not result in a greater completion of screening colonoscopy. Clinicaltrials.gov no: NCT03068052.
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Affiliation(s)
- Shivan J. Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania,Center for Health Care Innovation, University of Pennsylvania,Center for Health Incentives and Behavioral Economics, University of Pennsylvania
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania,Center for Health Care Innovation, University of Pennsylvania,Center for Health Incentives and Behavioral Economics, University of Pennsylvania
| | - Tess Niewood
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania
| | - Kevin G. Volpp
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania,Center for Health Care Innovation, University of Pennsylvania,Center for Health Incentives and Behavioral Economics, University of Pennsylvania,Center for Health Equity Research and Promotion, Philadelphia VA Medical Center
| | - David A. Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania,Center for Health Care Innovation, University of Pennsylvania,Center for Health Incentives and Behavioral Economics, University of Pennsylvania,Center for Health Equity Research and Promotion, Philadelphia VA Medical Center
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9
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Huf SW, Asch DA, Volpp KG, Reitz C, Mehta SJ. Text Messaging and Opt-out Mailed Outreach in Colorectal Cancer Screening: a Randomized Clinical Trial. J Gen Intern Med 2021; 36:1958-1964. [PMID: 33511567 PMCID: PMC8298623 DOI: 10.1007/s11606-020-06415-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 12/08/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND Routine screening reduces colorectal cancer mortality, but screening rates fall below national targets and are particularly low in underserved populations. OBJECTIVE To compare the effectiveness of a single text message outreach to serial text messaging and mailed fecal home test kits on colorectal cancer screening rates. DESIGN A two-armed randomized clinical trial. PARTICIPANTS An urban community health center in Philadelphia. Adults aged 50-74 who were due for colorectal cancer screening had at least one visit to the practice in the previously year, and had a cell phone number recorded. INTERVENTIONS Participants were randomized (1:1 ratio). Individuals in the control arm were sent a simple text message reminder as per usual practice. Those in the intervention arm were sent a pre-alert text message offering the options to opt-out of receiving a mailed fecal immunochemical test (FIT) kit, followed by up to three behaviorally informed text message reminders. MAIN MEASURES The primary outcome was participation in colorectal cancer screening at 12 weeks. The secondary outcome was the FIT kit return rate at 12 weeks. KEY RESULTS Four hundred forty participants were included. The mean age was 57.4 years (SD ± 6.1). 63.4% were women, 87.7% were Black, 19.1% were uninsured, and 49.6% were Medicaid beneficiaries. At 12 weeks, there was an absolute 17.3 percentage point increase in colorectal cancer screening in the intervention arm (19.6%), compared to the control arm (2.3%, p < 0.001). There was an absolute 17.7 percentage point increase in FIT kit return in the intervention arm (19.1%) compared to the control arm (1.4%, p < 0.001). CONCLUSIONS Serial text messaging with opt-out mailed FIT kit outreach can substantially improve colorectal cancer screening rates in an underserved population. TRIAL REGISTRATION clinicaltrials.gov ( https://clinicaltrials.gov/ct2/show/NCT03479645 ).
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Affiliation(s)
- Sarah W Huf
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. .,The Commonwealth Fund, Harkness Fellowship, New York City, NY, USA. .,Department of Surgery and Cancer, Imperial College London, London, UK. .,Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
| | - David A Asch
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA.,Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Kevin G Volpp
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA.,Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Catherine Reitz
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA.,Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Shivan J Mehta
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA.,Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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10
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Mehta SJ, Day SC, Norris AH, Sung J, Reitz C, Wollack C, Snider CK, Shaw PA, Asch DA. Behavioral interventions to improve population health outreach for hepatitis C screening: randomized clinical trial. BMJ 2021; 373:n1022. [PMID: 34006604 PMCID: PMC8129827 DOI: 10.1136/bmj.n1022] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
OBJECTIVE To evaluate whether opt out framing, messaging incorporating behavioral science concepts, or electronic communication increases the uptake of hepatitis C virus (HCV) screening in patients born between 1945 and 1965. DESIGN Pragmatic randomized controlled trial. SETTING 43 primary care practices from one academic health system (Philadelphia, PA, USA) between April 2019 and May 2020. PARTICIPANTS Patients born between 1945 and 1965 with no history of screening and at least two primary care visits in the two years before the enrollment period. INTERVENTIONS This multilevel trial was divided into two studies. Substudy A included 1656 eligible patients of 17 primary care clinicians who were randomized in a 1:1 ratio to a mailed letter about HCV screening (letter only), or a similar letter with a laboratory order for HCV screening (letter+order). Substudy B included the remaining 19 837 eligible patients followed by 417 clinicians. Active electronic patient portal users were randomized 1:5 to receive a mailed letter about HCV screening (letter), or an electronic patient portal message with similar content (patient portal); inactive patient portal users were mailed a letter. In a factorial design, patients in substudy B were also randomized 1:1 to receive standard content (usual care), or content based on principles of social norming, anticipated regret, reciprocity, and commitment (behavioral content). MAIN OUTCOME MEASURES Proportion of patients who completed HCV testing within four months. RESULTS 21 303 patients were included in the intention-to-treat analysis. Among the 1642 patients in substudy A, 19.2% (95% confidence interval 16.5% to 21.9%) completed screening in the letter only arm and 43.1% (39.7% to 46.4%) in the letter+order arm (P<0.001). Among the 19 661 patients in substudy B, 14.6% (13.9% to 15.3%) completed screening with usual care content and 13.6% (13.0% to 14.3%) with behavioral science content (P=0.06). Among active patient portal users, 17.8% (16.0% to 19.5%) completed screening after receiving a letter and 13.8% (13.1% to 14.5%) after receiving a patient portal message (P<0.001). CONCLUSIONS Opt out framing and effort reduction by including a signed laboratory order with outreach increased screening for HCV. Behavioral science messaging content did not increase uptake, and mailed letters achieved a greater response rate than patient portal messages. TRIAL REGISTRATION ClinicalTrials.gov NCT03712553.
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Affiliation(s)
- Shivan J Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA
| | - Susan C Day
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anne H Norris
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jessica Sung
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA
| | - Colin Wollack
- Information Services, Penn Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher K Snider
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA
| | - Pamela A Shaw
- Department of Clinical Epidemiology, Biostatistics, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA
- Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
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11
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Mahmud N, Asch DA, Sung J, Reitz C, Coniglio MS, McDonald C, Bernard D, Mehta SJ. Effect of Text Messaging on Bowel Preparation and Appointment Attendance for Outpatient Colonoscopy: A Randomized Clinical Trial. JAMA Netw Open 2021; 4:e2034553. [PMID: 33492374 PMCID: PMC7835713 DOI: 10.1001/jamanetworkopen.2020.34553] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
IMPORTANCE Outpatient colonoscopy is important for colorectal cancer screening. However, nonadherence and poor bowel preparation are common. OBJECTIVE To determine if an automated text messaging intervention with a focus on informational and reminder functions could improve attendance rates and bowel preparation quality for outpatient colonoscopy. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial was conducted in an endoscopy center at an urban academic medical center. Adult patients scheduled for outpatient colonoscopy between January and September 2019 were enrolled by telephone call (early phase) or by automated text message (late phase). Data were analyzed from October 2019 to January 2020. INTERVENTIONS After enrollment, patients were randomized in a 1:1 ratio to usual care (ie, written instructions and nurse telephone call) or to the intervention (ie, usual care plus an automated series of 9 educational or reminder text messages in the week prior to scheduled colonoscopy). MAIN OUTCOMES AND MEASURES The primary outcome was appointment attendance rate with good or excellent bowel preparation. Secondary outcomes included appointment attendance rate, bowel preparation quality (poor or inadequate, fair or adequate, and good or excellent), and cancellation lead time (in days). RESULTS Among 753 patients included and randomized in the trial (median [interquartile range] age, 56 [49-64] years; 364 [48.3%] men; 429 [57.2%] Black), 367 patients were randomized to the intervention group and 386 patients were randomized to the control group. There was no significant difference in the primary outcome between groups (patients attending appointments with good or excellent bowel preparation: intervention, 195 patients [53.1%]; control, 210 patients [54.4%]; P = .73), including when stratified by early or late phase enrollment groups. Similarly, there were no significant differences in secondary outcomes. CONCLUSIONS AND RELEVANCE This randomized clinical trial found no significant difference in appointment attendance or bowel preparation quality with an automated text messaging intervention compared with the usual care control. Future work could optimize the content and delivery of text message interventions or identify patient subgroups that may benefit from this approach. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03710213.
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Affiliation(s)
- Nadim Mahmud
- Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Leonard David Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - David A. Asch
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Jessica Sung
- Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Catherine Reitz
- Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Mary S. Coniglio
- Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Caitlin McDonald
- Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Donna Bernard
- Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Shivan J. Mehta
- Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Leonard David Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
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12
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Davoudi A, Lee NS, Chivers C, Delaney T, Asch EL, Reitz C, Mehta SJ, Chaiyachati KH, Mowery DL. Patient Interaction Phenotypes With an Automated Remote Hypertension Monitoring Program and Their Association With Blood Pressure Control: Observational Study. J Med Internet Res 2020; 22:e22493. [PMID: 33270032 PMCID: PMC7746494 DOI: 10.2196/22493] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 10/12/2020] [Accepted: 10/24/2020] [Indexed: 01/26/2023] Open
Abstract
Background Automated texting platforms have emerged as a tool to facilitate communication between patients and health care providers with variable effects on achieving target blood pressure (BP). Understanding differences in the way patients interact with these communication platforms can inform their use and design for hypertension management. Objective Our primary aim was to explore the unique phenotypes of patient interactions with an automated text messaging platform for BP monitoring. Our secondary aim was to estimate associations between interaction phenotypes and BP control. Methods This study was a secondary analysis of data from a randomized controlled trial for adults with poorly controlled hypertension. A total of 201 patients with established primary care were assigned to the automated texting platform; messages exchanged throughout the 4-month program were analyzed. We used the k-means clustering algorithm to characterize two different interaction phenotypes: program conformity and engagement style. First, we identified unique clusters signifying differences in program conformity based on the frequency over time of error alerts, which were generated to patients when they deviated from the requested text message format (eg, ###/## for BP). Second, we explored overall engagement styles, defined by error alerts and responsiveness to text prompts, unprompted messages, and word count averages. Finally, we applied the chi-square test to identify associations between each interaction phenotype and achieving the target BP. Results We observed 3 categories of program conformity based on their frequency of error alerts: those who immediately and consistently submitted texts without system errors (perfect users, 51/201), those who did so after an initial learning period (adaptive users, 66/201), and those who consistently submitted messages generating errors to the platform (nonadaptive users, 38/201). Next, we observed 3 categories of engagement style: the enthusiast, who tended to submit unprompted messages with high word counts (17/155); the student, who inconsistently engaged (35/155); and the minimalist, who engaged only when prompted (103/155). Of all 6 phenotypes, we observed a statistically significant association between patients demonstrating the minimalist communication style (high adherence, few unprompted messages, limited information sharing) and achieving target BP (P<.001). Conclusions We identified unique interaction phenotypes among patients engaging with an automated text message platform for remote BP monitoring. Only the minimalist communication style was associated with achieving target BP. Identifying and understanding interaction phenotypes may be useful for tailoring future automated texting interactions and designing future interventions to achieve better BP control.
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Affiliation(s)
- Anahita Davoudi
- Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, PA, United States
| | - Natalie S Lee
- National Clinician Scholars Program, University of Pennsylvania, Philadelphia, PA, United States.,Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.,Corporal Michael J Crescenz Veterans Affairs Medical Center, Philadelphia, PA, United States
| | - Corey Chivers
- Penn Medicine Predictive Healthcare, University of Pennsylvania Health System, Philadelphia, PA, United States
| | - Timothy Delaney
- Center for Healthcare Innovation, University of Pennsylvania, Philadelphia, PA, United States
| | - Elizabeth L Asch
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States
| | - Catherine Reitz
- Center for Healthcare Innovation, University of Pennsylvania, Philadelphia, PA, United States.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Shivan J Mehta
- Center for Healthcare Innovation, University of Pennsylvania, Philadelphia, PA, United States.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Krisda H Chaiyachati
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.,Center for Healthcare Innovation, University of Pennsylvania, Philadelphia, PA, United States.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Danielle L Mowery
- Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, PA, United States.,Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, United States
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13
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Mehta SJ, Hume E, Troxel AB, Reitz C, Norton L, Lacko H, McDonald C, Freeman J, Marcus N, Volpp KG, Asch DA. Effect of Remote Monitoring on Discharge to Home, Return to Activity, and Rehospitalization After Hip and Knee Arthroplasty: A Randomized Clinical Trial. JAMA Netw Open 2020; 3:e2028328. [PMID: 33346847 PMCID: PMC7753899 DOI: 10.1001/jamanetworkopen.2020.28328] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 10/10/2020] [Indexed: 12/13/2022] Open
Abstract
Importance Hip and knee arthroplasty are the most common inpatient surgical procedures for Medicare beneficiaries in the US, with substantial variation in cost and quality. Whether remote monitoring incorporating insights from behavioral science might help improve outcomes and increase value of care remains unknown. Objective To evaluate the effect of activity monitoring and bidirectional text messaging on the rate of discharge to home and clinical outcomes in patients receiving hip or knee arthroplasty. Design, Setting, and Participants Randomized clinical trial conducted between February 7, 2018, and April 15, 2019. The setting was 2 urban hospitals at an academic health system. Participants were patients aged 18 to 85 years scheduled to undergo hip or knee arthroplasty with a Risk Assessment and Prediction Tool score of 6 to 8. Interventions Eligible patients were randomized evenly to receive usual care (n = 153) or remote monitoring (n = 147). Those in the intervention arm who agreed received a wearable activity monitor to track step count, messaging about postoperative goals and milestones, pain score tracking, and connection to clinicians as needed. Patients assigned to receive monitoring were further randomized evenly to remote monitoring alone or remote monitoring with gamification and social support. Remote monitoring was offered before surgery, began at hospital discharge, and continued for 45 days postdischarge. Main Outcomes and Measures The primary outcome was discharge status (home vs skilled nursing facility or inpatient rehabilitation). Prespecified secondary outcomes included change in average daily step count and rehospitalizations. Results A total of 242 patients were analyzed (124 usual care, 118 intervention); median age was 66 years (interquartile range, 58-73 years); 78.1% were women, 45.5% were White, 43.4% were Black; and 81.4% in the intervention arm agreed to receive monitoring. There was no significant difference in the rate of discharge to home between the usual care arm (57.3%; 95% CI, 48.5%-65.9%) and the intervention arm (56.8%; 95% CI, 47.9%-65.7%) and no significant increase in step count in those receiving remote monitoring plus gamification and social support compared with remote monitoring alone. There was a statistically significant reduction in rehospitalization rate in the intervention arm (3.4%; 95% CI, 0.1%-6.7%) compared with the usual care arm (12.2%; 95% CI, 6.4%-18.0%) (P = .01). Conclusions and Relevance In this study, the remote monitoring program did not increase rate of discharge to home after hip or knee arthroplasty, and gamification and social support did not increase activity levels. There was a significant reduction in rehospitalizations among those receiving the intervention, which may have resulted from goal setting and connection to the care team. Trial Registration ClinicalTrials.gov Identifier: NCT03435549.
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Affiliation(s)
- Shivan J. Mehta
- Perelman School of Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, Philadelphia, Pennsylvania
| | - Eric Hume
- Department of Orthopaedic Surgery, University of Pennsylvania, Philadelphia
| | - Andrea B. Troxel
- Division of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, New York, New York
| | - Catherine Reitz
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, Philadelphia, Pennsylvania
| | - Laurie Norton
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
| | - Hannah Lacko
- Department of Orthopaedic Surgery, University of Pennsylvania, Philadelphia
| | - Caitlin McDonald
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, Philadelphia, Pennsylvania
| | - Jason Freeman
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
| | - Noora Marcus
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
| | - Kevin G. Volpp
- Perelman School of Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, Philadelphia, Pennsylvania
- Center for Health Equity Research and Promotion, Philadelphia Veterans Affairs Medical Center, Philadelphia, Pennsylvania
| | - David A. Asch
- Perelman School of Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, Philadelphia, Pennsylvania
- Center for Health Equity Research and Promotion, Philadelphia Veterans Affairs Medical Center, Philadelphia, Pennsylvania
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14
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Mehta SJ, Oyalowo A, Reitz C, Dean O, McAuliffe T, Asch DA, Doubeni CA. Text messaging and lottery incentive to improve colorectal cancer screening outreach at a community health center: A randomized controlled trial. Prev Med Rep 2020; 19:101114. [PMID: 32477853 PMCID: PMC7251946 DOI: 10.1016/j.pmedr.2020.101114] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [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: 07/05/2019] [Revised: 04/28/2020] [Accepted: 05/03/2020] [Indexed: 12/11/2022] Open
Abstract
Efforts to boost colorectal cancer (CRC) screening rates in underserved populations have been limited by effectiveness and scalability. We evaluate the impact of adding a lottery-based financial incentive to a text messaging program that asks patients to opt-in to receive mailed fecal immunochemical testing (FIT). This is a two-arm pragmatic randomized controlled trial at a community health center in Southwest Philadelphia from April to July 2017. We included CRC screening-eligible patients between ages 50-74 years who had a mobile phone, active health insurance, and at least one visit to the clinic in the past 12 months. Patients received a text message about CRC screening with the opportunity to opt-in to receive mailed FIT. They were randomized 1:1 to the following: (1) text messaging outreach alone (text), or (2) text messaging with lottery for a 1-in-5 chance of winning $100 after FIT completion (text + lottery). The primary outcome was the percentage of patients completing the mailed FIT within 3 months of initial outreach. 281 patients were included in the intent-to-treat analysis. The FIT completion rate was 12.1% (95% CI, 6.7%-17.5%) in the text message arm and 12.1% (95% CI, 6.7%-17.5%) in the lottery arm, with no statistical difference between arms. The majority of post-intervention interview respondents found text messaging to be acceptable and convenient. Opt-in text messaging is a feasible option to promote the uptake of mailed FIT screening, but the addition of a lottery-based incentive did not improve completion rates. Trial Registration: clinicaltrials.gov (NCT03072095).
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Affiliation(s)
- Shivan J. Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, United States
- Center for Health Care Innovation, University of Pennsylvania, United States
| | - Akinbowale Oyalowo
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, United States
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, United States
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, United States
| | - Owen Dean
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, United States
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, United States
| | - Timothy McAuliffe
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, United States
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, United States
| | - David A. Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, United States
- Center for Health Care Innovation, University of Pennsylvania, United States
- Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, United States
| | - Chyke A. Doubeni
- Center for Health Equity and Community Engagement Research, Mayo Clinic, United States
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15
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Mehta S, Hume E, Troxel A, Reitz C, Norton L, Lacko H, McDonald C, Freeman J, Marcus N, Volpp K, Asch D. DIGITAL TECHNOLOGIES, DATA, AND ANALYTICS. Health Serv Res 2020. [DOI: 10.1111/1475-6773.13381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Affiliation(s)
- S. Mehta
- Perelman School of Medicine University of Pennsylvania Philadelphia PA United States
- Penn Medicine Center for Health Care Innovation Philadelphia PA United States
| | - E. Hume
- Perelman School of Medicine University of Pennsylvania Philadelphia PA United States
| | - A. Troxel
- New York University School of Medicine New York City NY United States
| | - C. Reitz
- Penn Medicine Center for Health Care Innovation Philadelphia PA United States
| | - L. Norton
- Center for Health Incentives and Behavioral Economics Philadelphia PA United States
| | - H. Lacko
- Perelman School of Medicine University of Pennsylvania Philadelphia PA United States
| | - C. McDonald
- Penn Medicine Center for Health Care Innovation Philadelphia PA United States
| | - J. Freeman
- Center for Health Incentives and Behavioral Economics Philadelphia PA United States
| | - N. Marcus
- Center for Health Incentives and Behavioral Economics Philadelphia PA United States
| | - K. Volpp
- Center for Health Incentives and Behavioral Economics Philadelphia PA United States
- Center for Health Equity Research and Promotion Philadelphia VA Medical Center Philadelphia PA United States
| | - D. Asch
- Penn Medicine Center for Health Care Innovation Philadelphia PA United States
- Center for Health Equity Research and Promotion Philadelphia VA Medical Center Philadelphia PA United States
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Mahmud N, Doshi SD, Coniglio MS, Clermont M, Bernard D, Reitz C, Khungar V, Asch DA, Mehta SJ. An Automated Text Message Navigation Program Improves the Show Rate for Outpatient Colonoscopy. Health Educ Behav 2019; 46:942-946. [PMID: 31431077 DOI: 10.1177/1090198119869964] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background. Numerous barriers to outpatient colonoscopy completion exist, causing undue procedure cancellations and poor bowel preparation. We piloted a text message navigation program to improve colonoscopy adherence. Method. We conducted a prospective study of patients aged 18 to 75 years scheduled for outpatient colonoscopy at an urban endoscopy center in April 2018. An intervention arm consisting of bidirectional, automated text messages prior to the procedure was compared with a usual care arm. We enrolled 21 intervention patients by phone and randomly selected 50 controls. Outcomes included colonoscopy appointment adherence, bowel preparation quality, and colonoscopy completion. Results. The arms had similar demographics and comorbidities. Intervention patients had higher colonoscopy appointment adherence (90% vs. 62%, p = 0.049). There were no significant differences in preparation quality or procedure completeness. Poststudy surveys indicated high patient satisfaction and perceived usefulness of the program. Conclusion. A bidirectional, automated texting navigation program improved colonoscopy adherence rates as compared with usual care.
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Affiliation(s)
- Nadim Mahmud
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | - David A Asch
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
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Mehta SJ, Induru V, Santos D, Reitz C, McAuliffe T, Orellana C, Volpp KG, Asch DA, Doubeni CA. Effect of Sequential or Active Choice for Colorectal Cancer Screening Outreach: A Randomized Clinical Trial. JAMA Netw Open 2019; 2:e1910305. [PMID: 31469393 PMCID: PMC6724166 DOI: 10.1001/jamanetworkopen.2019.10305] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 07/11/2019] [Indexed: 12/26/2022] Open
Abstract
Importance Colonoscopy and fecal immunochemical testing (FIT) are considered top-tier tests for colorectal cancer (CRC) screening. Behavioral economic insights about "choice architecture" suggest that participation could be influenced by how people are presented test options. Objective To investigate response rates for offering colonoscopy only compared with sequential choice (colonoscopy and then FIT) or active choice (colonoscopy or FIT) through mailed outreach. Design, Setting, and Participants Three-arm pragmatic randomized clinical trial conducted between November 14, 2017, and May 14, 2018. The setting was primary care practices at an academic health system. Patients aged 50 to 74 years with at least 2 primary care visits in the 2-year preenrollment period were included if they were eligible but not up to date on CRC screening. Interventions Eligible patients received mailed outreach about CRC screening. Equal numbers of eligible patients were randomly assigned to 3 outreach groups to receive mailings about CRC screening with the following options: (1) direct phone number to call for scheduling colonoscopy (colonoscopy only), (2) direct phone number to call for colonoscopy and a mailed FIT kit if no response within 4 weeks (sequential choice), or (3) direct phone number to call for colonoscopy and a mailed FIT kit offered at the same time (active choice). Main Outcomes and Measures The primary outcome was CRC screening completion (FIT or colonoscopy) within 4 months of initial outreach. The secondary outcomes were CRC screening completion within 6 months of outreach and the choice of colonoscopy as a screening test. Results In total, 438 patients were included in the intent-to-treat analysis, with a median age of 56 years (interquartile range, 52-63 years); 55.0% were women. At 4 months, the CRC screening completion rates were 14.4% (95% CI, 8.7%-20.1%) in the colonoscopy-only arm, 17.1% (95% CI, 11.0%-23.2%) in the sequential choice arm, and 19.9% (95% CI, 13.4%-26.4%) in the active choice arm. Neither choice arm achieved a screening rate statistically greater than that in the colonoscopy-alone arm. Among those who completed CRC screening at 4 months, 90.5% (95% CI, 78.0%-103.0%) chose colonoscopy in the colonoscopy-only arm, which was significantly higher than the 52.0% (95% CI, 32.4%-71.6%; P = .005) and 37.9% (95% CI, 20.2%-55.6%; P < .001) in the sequential choice and active choice arms, respectively. Conclusions and Relevance There was no significant increase in CRC screening when offering sequential or active choice, but there was a lower rate of colonoscopy in the choice arms than in the colonoscopy-only arm. Subtle changes in sequencing or defaults can alter patient decision making related to preventive health. Trial Registration ClinicalTrials.gov identifier: NCT03246438.
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Affiliation(s)
- Shivan J. Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Vikranth Induru
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - David Santos
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Timothy McAuliffe
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Charles Orellana
- Clinical Care Associates, University of Pennsylvania, Philadelphia
| | - Kevin G. Volpp
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
- Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, Pennsylvania
| | - David A. Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Health Care Innovation, University of Pennsylvania, Philadelphia
- Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, Pennsylvania
| | - Chyke A. Doubeni
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
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Mehta SJ, Pepe RS, Gabler NB, Kanneganti M, Reitz C, Saia C, Teel J, Asch DA, Volpp KG, Doubeni CA. Effect of Financial Incentives on Patient Use of Mailed Colorectal Cancer Screening Tests: A Randomized Clinical Trial. JAMA Netw Open 2019; 2:e191156. [PMID: 30901053 PMCID: PMC6583304 DOI: 10.1001/jamanetworkopen.2019.1156] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 02/03/2019] [Indexed: 12/26/2022] Open
Abstract
Importance Mailing fecal immunochemical test (FIT) kits to patients' homes has been shown to boost colorectal cancer screening rates, but response rates remain limited, and organized programs typically require repeated outreach attempts. Behavioral economics has shown that offering salient financial incentives to patients may increase participation in preventive health. Objective To compare the impact of different financial incentives for mailed FIT outreach. Design, Setting, and Participants This 4-parallel-arm randomized clinical trial included patients aged 50 to 75 years who had an established primary care clinician, at least 2 visits in the prior 2 years, and were eligible for colorectal cancer screening and not up-to-date. This study was conducted at urban primary care practices at an academic health system from December 2015 to February 2018. Data analysis was conducted from March 2018 to September 2018. Interventions Eligible patients received a letter from their primary care clinician that included a mailed FIT kit and instructions for use. They were randomized in a 1:1:1:1 ratio to receive (1) no financial incentive; (2) an unconditional $10 incentive included with the mailing; (3) a $10 incentive conditional on FIT completion; or (4) a conditional lottery with a 1-in-10 chance of winning $100 after FIT completion. Main Outcomes and Measures Fecal immunochemical test completion within 2 and 6 months of initial outreach. Results A total of 897 participants were randomized, with a median age of 57 years (interquartile range, 52-62 years); 56% were women, and 69% were black. The overall completion rate across all arms was 23.5% at 2 months. The completion rate at 2 months was 26.0% (95% CI, 20.4%-32.3%) in the no incentive arm, 27.2% (95% CI, 21.5%-33.6%) in the unconditional incentive arm, 23.2% (95% CI, 17.9%-29.3%) in the conditional incentive arm, and 17.7% (95% CI, 13.0%-23.3%) in the lottery incentive arm. None of the arms with an incentive were statistically superior to the arm without incentive. The overall FIT completion rate across all arms was 28.9% at 6 months, and there was also no difference by arm. The completion rate at 6 months was 32.7% (95% CI, 26.6%-39.3%) in the no incentive arm, 31.7% (95% CI, 25.7%-38.2%) in the unconditional incentive arm, 26.8% (95% CI, 21.1%-33.1%) in the conditional incentive arm, and 24.3% (95% CI, 18.9%-30.5%) in the lottery incentive arm. Conclusions and Relevance Mailed FIT resulted in high colorectal cancer screening response rates in this population, but different forms of financial incentives of the same expected value ($10) did not incrementally increase FIT completion rates. The incentive value may have been too small or financial incentives may not be effective in this context. Trial Registration ClinicalTrials.gov Identifier: NCT02594150.
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Affiliation(s)
- Shivan J. Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia
| | - Rebecca S. Pepe
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Nicole B. Gabler
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Mounika Kanneganti
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Chelsea Saia
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Joseph Teel
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - David A. Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, Pennsylvania
| | - Kevin G. Volpp
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, Pennsylvania
| | - Chyke A. Doubeni
- Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia
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19
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Mehta SJ, Khan T, Guerra C, Reitz C, McAuliffe T, Volpp KG, Asch DA, Doubeni CA. A Randomized Controlled Trial of Opt-in Versus Opt-Out Colorectal Cancer Screening Outreach. Am J Gastroenterol 2018; 113:1848-1854. [PMID: 29925915 PMCID: PMC6768589 DOI: 10.1038/s41395-018-0151-3] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Accepted: 05/14/2018] [Indexed: 12/11/2022]
Abstract
OBJECTIVES METHODS:: RESULTS:: Patients randomized to opt-in agreed to participate 23.1% of the time, and only 2.5% of those in opt-out chose not to participate. FIT kits were mailed to 22.4% and 93% of patients in opt-in and opt-out arms, respectively. In intention-to-screen analysis, patients in the opt-out arm had a higher FIT completion rate (29.1%) than in the opt-in arm (9.6%) (absolute difference 19.5%; 95% confidence interval, 10.9-27.9%; P < .001). Results were similar in subgroup analysis of those sent initial messaging through the EHR portal (9.5% opt-in versus 37.5% in opt-out). CONCLUSIONS .
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Affiliation(s)
- Shivan J Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Tanya Khan
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Carmen Guerra
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Timothy McAuliffe
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Kevin G Volpp
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - David A Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Chyke A Doubeni
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
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Chouraki V, De Bruijn RFAG, Chapuis J, Bis JC, Reitz C, Schraen S, Ibrahim-Verbaas CA, Grenier-Boley B, Delay C, Rogers R, Demiautte F, Mounier A, Fitzpatrick AL, Berr C, Dartigues JF, Uitterlinden AG, Hofman A, Breteler M, Becker JT, Lathrop M, Schupf N, Alpérovitch A, Mayeux R, van Duijn CM, Buée L, Amouyel P, Lopez OL, Ikram MA, Tzourio C, Lambert JC. A genome-wide association meta-analysis of plasma Aβ peptides concentrations in the elderly. Mol Psychiatry 2014; 19:1326-35. [PMID: 24535457 PMCID: PMC4418478 DOI: 10.1038/mp.2013.185] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2013] [Revised: 10/08/2013] [Accepted: 10/31/2013] [Indexed: 11/09/2022]
Abstract
Amyloid beta (Aβ) peptides are the major components of senile plaques, one of the main pathological hallmarks of Alzheimer disease (AD). However, Aβ peptides' functions are not fully understood and seem to be highly pleiotropic. We hypothesized that plasma Aβ peptides concentrations could be a suitable endophenotype for a genome-wide association study (GWAS) designed to (i) identify novel genetic factors involved in amyloid precursor protein metabolism and (ii) highlight relevant Aβ-related physiological and pathophysiological processes. Hence, we performed a genome-wide association meta-analysis of four studies totaling 3 528 healthy individuals of European descent and for whom plasma Aβ1-40 and Aβ1-42 peptides levels had been quantified. Although we did not observe any genome-wide significant locus, we identified 18 suggestive loci (P<1 × 10(-)(5)). Enrichment-pathway analyses revealed canonical pathways mainly involved in neuronal functions, for example, axonal guidance signaling. We also assessed the biological impact of the gene most strongly associated with plasma Aβ1-42 levels (cortexin 3, CTXN3) on APP metabolism in vitro and found that the gene protein was able to modulate Aβ1-42 secretion. In conclusion, our study results suggest that plasma Aβ peptides levels are valid endophenotypes in GWASs and can be used to characterize the metabolism and functions of APP and its metabolites.
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Affiliation(s)
- V Chouraki
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - RFAG De Bruijn
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Department of Neurology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands
| | - J Chapuis
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - JC Bis
- Cardiovascular Health Resarch Unit and Department of Medicine,
University of Washington, Seattle, WA, USA
| | - C Reitz
- The Taub Institute for Research on Alzheimer’s Disease and
the Aging Brain, Columbia University, New York, NY, USA,The Gertrude H. Sergievsky Center, Columbia University, New York,
NY, USA,The Department of Neurology, College of Physicians and Surgeons,
Columbia University, New York, NY, USA
| | - S Schraen
- Université Lille-Nord de France, Lille, France,Inserm U837, Jean-Pierre Aubert Research Centre, Lille,
France,Centre Hospitalier Régional Universitaire de Lille, Lille,
France
| | - CA Ibrahim-Verbaas
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Department of Neurology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands
| | - B Grenier-Boley
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - C Delay
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - R Rogers
- The Taub Institute for Research on Alzheimer’s Disease and
the Aging Brain, Columbia University, New York, NY, USA
| | - F Demiautte
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - A Mounier
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - AL Fitzpatrick
- Cardiovascular Health Resarch Unit and Department of Medicine,
University of Washington, Seattle, WA, USA
| | | | - C Berr
- INSERM U888, Hôpital La Colombière, Montpellier,
France
| | - J-F Dartigues
- INSERM U593, Victor Segalen University, Bordeaux, France
| | - AG Uitterlinden
- Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands,Department of Internal medicine, Leiden, Erasmus MC University
Medical Center, Rotterdam, The Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands
| | - M Breteler
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,DZNE, German Center for Neurodegenerative Diseases, Bonn,
Germany
| | - JT Becker
- Alzheimer’s Disease Research Center, Departments of
Neurology, Psychiatry and Psychology, University of Pittsburgh School of Medicine,
Pittsburgh, PA, USA
| | - M Lathrop
- Fondation Jean Dausset—Centre d’Etude du
Polymorphisme Humain, Paris, France,Centre National de Genotypage, Institut Genomique, Commissariat
à l’énergie Atomique, Evry, France
| | - N Schupf
- The Gertrude H. Sergievsky Center, Columbia University, New York,
NY, USA
| | | | - R Mayeux
- The Taub Institute for Research on Alzheimer’s Disease and
the Aging Brain, Columbia University, New York, NY, USA,The Department of Psychiatry, College of Physicians and Surgeons,
Columbia University, New York, NY, USA
| | - CM van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands
| | - L Buée
- Université Lille-Nord de France, Lille, France,Inserm U837, Jean-Pierre Aubert Research Centre, Lille,
France,Centre Hospitalier Régional Universitaire de Lille, Lille,
France
| | - P Amouyel
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France,Centre Hospitalier Régional Universitaire de Lille, Lille,
France
| | - OL Lopez
- Alzheimer’s Disease Research Center, Departments of
Neurology, Psychiatry and Psychology, University of Pittsburgh School of Medicine,
Pittsburgh, PA, USA
| | - MA Ikram
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Department of Neurology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands,Department of Radiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands
| | - C Tzourio
- INSERM U593, Victor Segalen University, Bordeaux, France,INSERM U708, Paris, France
| | - J-C Lambert
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
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Lambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, DeStafano AL, Bis JC, Beecham GW, Grenier-Boley B, Russo G, Thorton-Wells TA, Jones N, Smith AV, Chouraki V, Thomas C, Ikram MA, Zelenika D, Vardarajan BN, Kamatani Y, Lin CF, Gerrish A, Schmidt H, Kunkle B, Dunstan ML, Ruiz A, Bihoreau MT, Choi SH, Reitz C, Pasquier F, Cruchaga C, Craig D, Amin N, Berr C, Lopez OL, De Jager PL, Deramecourt V, Johnston JA, Evans D, Lovestone S, Letenneur L, Morón FJ, Rubinsztein DC, Eiriksdottir G, Sleegers K, Goate AM, Fiévet N, Huentelman MW, Gill M, Brown K, Kamboh MI, Keller L, Barberger-Gateau P, McGuiness B, Larson EB, Green R, Myers AJ, Dufouil C, Todd S, Wallon D, Love S, Rogaeva E, Gallacher J, St George-Hyslop P, Clarimon J, Lleo A, Bayer A, Tsuang DW, Yu L, Tsolaki M, Bossù P, Spalletta G, Proitsi P, Collinge J, Sorbi S, Sanchez-Garcia F, Fox NC, Hardy J, Deniz Naranjo MC, Bosco P, Clarke R, Brayne C, Galimberti D, Mancuso M, Matthews F, Moebus S, Mecocci P, Del Zompo M, Maier W, Hampel H, Pilotto A, Bullido M, Panza F, Caffarra P, Nacmias B, Gilbert JR, Mayhaus M, Lannefelt L, Hakonarson H, Pichler S, Carrasquillo MM, Ingelsson M, Beekly D, Alvarez V, Zou F, Valladares O, Younkin SG, Coto E, Hamilton-Nelson KL, Gu W, Razquin C, Pastor P, Mateo I, Owen MJ, Faber KM, Jonsson PV, Combarros O, O'Donovan MC, Cantwell LB, Soininen H, Blacker D, Mead S, Mosley TH, Bennett DA, Harris TB, Fratiglioni L, Holmes C, de Bruijn RF, Passmore P, Montine TJ, Bettens K, Rotter JI, Brice A, Morgan K, Foroud TM, Kukull WA, Hannequin D, Powell JF, Nalls MA, Ritchie K, Lunetta KL, Kauwe JS, Boerwinkle E, Riemenschneider M, Boada M, Hiltuenen M, Martin ER, Schmidt R, Rujescu D, Wang LS, Dartigues JF, Mayeux R, Tzourio C, Hofman A, Nöthen MM, Graff C, Psaty BM, Jones L, Haines JL, Holmans PA, Lathrop M, Pericak-Vance MA, Launer LJ, Farrer LA, van Duijn CM, Van Broeckhoven C, Moskvina V, Seshadri S, Williams J, Schellenberg GD, Amouyel P. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet 2013; 45:1452-8. [PMID: 24162737 PMCID: PMC3896259 DOI: 10.1038/ng.2802] [Citation(s) in RCA: 2947] [Impact Index Per Article: 267.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2013] [Accepted: 09/27/2013] [Indexed: 12/12/2022]
Abstract
Eleven susceptibility loci for late-onset Alzheimer's disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer's disease cases and 37,154 controls. In stage 2, 11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10(-8)) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.
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23
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Reitz C, Tosto G, Vardarajan B, Rogaeva E, Ghani M, Rogers RS, Conrad C, Haines JL, Pericak-Vance MA, Fallin MD, Foroud T, Farrer LA, Schellenberg GD, George-Hyslop PS, Mayeux R. Independent and epistatic effects of variants in VPS10-d receptors on Alzheimer disease risk and processing of the amyloid precursor protein (APP). Transl Psychiatry 2013; 3:e256. [PMID: 23673467 PMCID: PMC3669917 DOI: 10.1038/tp.2013.13] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Genetic variants in the sortilin-related receptor (SORL1) and the sortilin-related vacuolar protein sorting 10 (VPS10) domain-containing receptor 1 (SORCS1) are associated with increased risk of Alzheimer's disease (AD), declining cognitive function and altered amyloid precursor protein (APP) processing. We explored whether other members of the (VPS10) domain-containing receptor protein family (the sortilin-related VPS10 domain-containing receptors 2 and 3 (SORCS2 and SORCS3) and sortilin (SORT1)) would have similar effects either independently or together. We conducted the analyses in a large Caucasian case control data set (n=11,840 cases, 10,931 controls) to determine the associations between single nucleotide polymorphisms (SNPs) in all the five homologous genes and AD risk. Evidence for interactions between SNPs in the five VPS10 domain receptor family genes was determined in epistatic statistical models. We also compared expression levels of SORCS2, SORCS3 and SORT1 in AD and control brains using microarray gene expression analyses and assessed the effects of these genes on γ-secretase processing of APP. Several SNPs in SORL1, SORCS1, SORCS2 and SORCS3 were associated with AD. In addition, four specific linkage disequilibrium blocks in SORCS1, SORCS2 and SORCS3 showed additive epistatic effects on the risk of AD (P≤0.0006). SORCS3, but not SORCS2 or SORT1, showed reduced expression in AD compared with control brains, but knockdown of all the three genes using short hairpin RNAs in HEK293 cells caused a significant threefold increase in APP processing (from P<0.001 to P<0.05). These findings indicate that in addition to SORL1 and SORCS1, variants in other members of the VPS10 domain receptor family (that is, SORCS1, SORCS2, SORCS3) are associated with AD risk and alter APP processing. More importantly, the results indicate that variants within these genes have epistatic effects on AD risk.
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Affiliation(s)
- C Reitz
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA,The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA,Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - G Tosto
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - B Vardarajan
- Department of Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - E Rogaeva
- Centre for Research in Neurodegenerative Diseases, University of Toronto, Ontario, Canada
| | - M Ghani
- Centre for Research in Neurodegenerative Diseases, University of Toronto, Ontario, Canada
| | - R S Rogers
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - C Conrad
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - J L Haines
- Center for Human Genetics Research and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - M A Pericak-Vance
- Miami Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA
| | - M D Fallin
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - T Foroud
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA
| | - L A Farrer
- Department of Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA,Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine and Public Health, Boston, MA, USA,Department of Neurology, Boston University Schools of Medicine and Public Health, Boston, MA, USA,Department of Ophthalmology, Boston University Schools of Medicine and Public Health, Boston, MA, USA,Department of Genetics and Genomics, Boston University Schools of Medicine and Public Health, Boston, MA, USA,Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - G D Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - P S George-Hyslop
- Centre for Research in Neurodegenerative Diseases, University of Toronto, Ontario, Canada,Department of Medicine, University Health Network, Toronto, Ontario, Canada,Department of Clinical Neurosciences, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | - R Mayeux
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA,The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA,Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA,Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY, USA,Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY, USA,Department of Epidemiology, School of Public Health, Columbia University, New York, NY, USA,Gertrude H. Sergievsky Center, Columbia University, 630 West 168th Street, New York, NY 10032, USA. E-mail:
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Luchsinger JA, Brickman AM, Reitz C, Cho SJ, Schupf N, Manly JJ, Tang MX, Small SA, Mayeux R, DeCarli C, Brown TR. Subclinical cerebrovascular disease in mild cognitive impairment. Neurology 2009; 73:450-6. [PMID: 19667320 DOI: 10.1212/wnl.0b013e3181b1636a] [Citation(s) in RCA: 71] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Cerebrovascular disease (CVD) may contribute to mild cognitive impairment (MCI). We sought to determine the relation of white matter hyperintensity (WMH) volume and infarcts in brain MRI to MCI in a community-based sample. METHODS A total of 679 elderly persons without dementia underwent brain MRI. WMH and infarcts were quantified using research methods. WMH was adjusted for total cranial volume. The Petersen criteria were used to define MCI. MCI was further subclassified into amnestic and non-amnestic. We used logistic regression to relate WMH and infarcts to prevalent MCI. RESULTS WMH were associated with amnestic MCI (odds ratio [OR] = 1.9; 95% confidence interval [CI] 1.1, 3.4) but not non-amnestic MCI (OR = 1.2; 95% CI 0.4, 1.6) after adjusting for age, gender, ethnic group, education, and APOE-epsilon4. Infarcts were more strongly associated with non-amnestic MCI (OR = 2.7; 95% CI 1.5, 4.8) than amnestic MCI (OR = 1.4; 95% CI 0.9, 2.3). In secondary analyses using continuous cognitive scores as outcomes, WMH, but not infarcts, were related to memory, while infarcts were more strongly related with non-amnestic domains. CONCLUSION White matter hyperintensity (WMH) is more strongly related to amnestic mild cognitive impairment (MCI). Infarcts are more strongly related to non-amnestic MCI. The nature of WMH in amnestic MCI requires further study.
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Affiliation(s)
- J A Luchsinger
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.
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Abstract
OBJECTIVE To determine the relation of amyloid and tau pathology in the hippocampal formation to decline in memory and other cognitive functions in Alzheimer's disease (AD). METHODS Regression models were used to relate semiquantitative measurements of amyloid plaques, neurofibrillary tangles (NFTs) and neuropil threads (NTs) at autopsy with antemortem performance in memory, abstract/visuospatial and language domains in two independent samples (n = 41, n = 66) that had repeated neuropsychological measurements before death. RESULTS In both groups, the number of NFTs in the entorhinal cortex, subiculum and CA1 region was inversely associated with memory performance at the last visit before death. However, the number of amyloid plaques and NTs in the entorhinal cortex was also inversely related to poor memory function. Moreover, as the number of plaques or NTs increased in any region of the hippocampal formation, there was a more rapid decline in memory performance over time; a similar decline was associated with increasing numbers of NFTs in the CA1 or subiculum. In contrast, there was no association between amyloid plaques, NFTs or NTs in the frontal or parietal lobe and performance in memory, nor was there an association between plaques, NFTs or NTs in the hippocampal formation and cognitive functions unrelated to memory. DISCUSSION This study implicates both amyloid deposition and tau pathology in the hippocampus as an early and late cause of decline in memory function over time in AD. Memory performance appears to be specifically related to the amount of amyloid plaques, NFTs and NTs in the entorhinal cortex and hippocampus.
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Affiliation(s)
- C Reitz
- Gertrude H Sergievsky Center/Taub Institute for Research on the Aging Brain, 630 West 168 Street, Columbia University, New York, NY 10032, USA.
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Reitz C, Mayeux R. Endophenotypes in normal brain morphology and Alzheimer's disease: a review. Neuroscience 2009; 164:174-90. [PMID: 19362127 DOI: 10.1016/j.neuroscience.2009.04.006] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2008] [Revised: 04/03/2009] [Accepted: 04/06/2009] [Indexed: 01/27/2023]
Abstract
Late-onset Alzheimer's disease is a common complex disorder of old age. Though these types of disorders can be highly heritable, they differ from single-gene (Mendelian) diseases in that their causes are often multifactorial with both genetic and environmental components. Genetic risk factors that have been firmly implicated in the cause are mutations in the amyloid precursor protein (APP), presenilin 1 (PSEN1) and presenilin 2 (PSEN2) genes, which are found in large multi-generational families with an autosomal dominant pattern of disease inheritance, the apolipoprotein E (APOE)epsilon4 allele and the sortilin-related receptor (SORL1) gene. Environmental factors that have been associated with late-onset Alzheimer's disease include depressive illness, various vascular risk factors, level of education, head trauma and estrogen replacement therapy. This complexity may help explain their high prevalence from an evolutionary perspective, but the etiologic complexity makes identification of disease-related genes much more difficult. The "endophenotype" approach is an alternative method for measuring phenotypic variation that may facilitate the identification of susceptibility genes for complexly inherited traits. The usefulness of endophenotypes in genetic analyses of normal brain morphology and, in particular for Alzheimer's disease will be reviewed as will the implications of these findings for models of disease causation. Given that the pathways from genotypes to end-stage phenotypes are circuitous at best, identifying endophenotypes more proximal to the effects of genetic variation may expedite the attempts to link genetic variants to disorders.
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Affiliation(s)
- C Reitz
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA
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Abstract
BACKGROUND AND OBJECTIVE Previous studies relating smoking with the risk of dementia have been inconsistent and limited in their validity by short follow-up times, large intervals between baseline and follow-up assessments, and unspecific determination of dementia diagnosis. We re-assessed after longer follow-up time in the large population-based cohort of the Rotterdam Study whether smoking habits and pack-years of smoking are associated with the risk of dementia, Alzheimer disease (AD), and vascular dementia (VaD). METHODS Prospective population-based cohort study in 6,868 participants, 55 years or older and free of dementia at baseline. First, Cox proportional hazard models were used to relate smoking status at baseline with the risks of incident dementia, VaD, and AD, using never smokers as the reference category in all analyses. Then Cox proportional hazard models were used to relate pack-years of smoking with the risks of incident dementia, VaD, and AD. To explore the impact of the APOEepsilon4 allele, sex, and age on the association between smoking status and dementia, we repeated all analyses stratifying, in separate models, by APOEepsilon4 genotype, sex, and median of age. RESULTS After a mean follow-up time of 7.1 years, current smoking at baseline was associated with an increased risk of dementia (HR 1.47, 95% CI 1.18 to 1.86) and AD (HR 1.56, 95% CI 1.21 to 2.02). This increase in disease risk was restricted to persons without the APOEepsilon4 allele. There was no association between current smoking and risk of VaD, and there was no association between past smoking and risk of dementia, AD, or VaD. CONCLUSION Current smoking increases the risk of dementia. This effect is more pronounced in persons without the APOEepsilon4 allele than APOEepsilon4 carriers.
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Affiliation(s)
- C Reitz
- Department of Epidemiology & Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlands
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Abstract
BACKGROUND The prevalence of Alzheimer disease (AD) is increasing in the elderly, and vascular risk factors may increase its risk. OBJECTIVE To explore the association of the aggregation of vascular risk factors with AD. METHODS The authors followed 1,138 individuals without dementia at baseline (mean age 76.2) for a mean of 5.5 years. The presence of vascular risk factors was related to incident possible and probable AD. RESULTS Four risk factors (diabetes, hypertension, heart disease, and current smoking) were associated with a higher risk of AD (p < 0.10) when analyzed individually. The risk of AD increased with the number of risk factors (diabetes + hypertension + heart disease + current smoking). The adjusted hazards ratio of probable AD for the presence of three or more risk factors was 3.4 (95% CI: 1.8, 6.3; p for trend < 0.0001) compared with no risk factors. Diabetes and current smoking were the strongest risk factors in isolation or in clusters, but hypertension and heart disease were also related to a higher risk of AD when clustered with diabetes, smoking, or each other. CONCLUSIONS The risk of Alzheimer disease (AD) increased with the number of vascular risk factors. Diabetes and current smoking were the strongest risk factors, but clusters including hypertension and heart disease also increased the risk of AD. These associations are unlikely to be explained by misclassification of the outcome, given strong associations when only probable AD is considered.
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Affiliation(s)
- J A Luchsinger
- Taub Institute for Research of Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.
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Abstract
OBJECTIVE To examine the association of plasma lipid levels to changes in cognitive function in elderly subjects without dementia. METHODS The authors examined changes in performance in tests of memory, visuospatial/cognitive, and language abilities in 1,147 elderly individuals without dementia or cognitive impairment at baseline followed for 7 years using generalized estimating equations. RESULTS Performance in all cognitive domains declined significantly over time, while there was no association between levels of any plasma lipid or lipid lowering treatment and memory, cognitive/visuospatial, or language performance at any interval. Higher age at baseline was related to lower scores in all three domains at each interval, while higher education and white ethnicity were associated with higher scores in all domains. Analyses relating plasma lipids to performance in color trails tests using proportional hazards regression showed no association. In subsequent analyses excluding subjects with incident dementia, memory performance declined over time, while cognitive/visuospatial and language performance did not. Higher plasma high density lipoprotein and total cholesterol were associated with higher scores in language performance at baseline; this domain declined faster among individuals with higher total cholesterol, but this result was not significant after taking multiple comparisons into account. Plasma triglycerides, low density lipoprotein, or treatment with lipid lowering agents were not associated with changes in cognitive performance. CONCLUSIONS Plasma lipid levels or treatment with lipid lowering agents in the elderly were not associated with changes in cognitive function.
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Affiliation(s)
- C Reitz
- Gertrude H. Sergievsky Center, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA
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Lecerf JM, Reitz C, de Chasteigner A. [Evaluation of discomfort and complications in a population of 18,102 patients overweight or obese patients]. Presse Med 2003; 32:689-95. [PMID: 12754449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2023] Open
Abstract
AIMS The burden of disorders associated with overweight and obesity is a major public health problem. It is therefore important to better identify these concomitant disorders and how their frequencies vary with sex and age. METHODS A survey was carried out during a 5 month-period from September 2001 to January 2002) among 4 727 general practitioners distributed throughout France in 18 102 patients with a body mass index (BMI)>25 kg/m2. The practitioners evaluated the presence of concomitant disorders using a closed questionnaire. The patients assessed global discomfort linked to overweight using an analog visual scale. Univariate and multivariate analyses of the concomitant disorders and self-reported discomfort depending on age, gender and BMI were performed. RESULTS The survey population comprised 66.8% of women (W) and 33.2% of men (M). Mean age was 48.0 +/- 13.2 years and mean BMI was 34.6 +/- 6.1, with no differences between the two sexes. The most frequent concomitant disorders were back pain (44.6%), hypertension (44.2%), dyslipidemia (39.9%), knee osteoarthritis (30.8%), lower limb edema (24.3%), hypersudation (23.8%), skin fold mycosis (22.8%) and type 2 diabetes (21.6%). In multivariate analyses, the distribution of these disorders varied with sex: hypertension, type 2 diabetes, dyslipidemia, and hypersudation were more frequent in men, whereas knee osteoarthritis, back pain, and skin fold mycosis were more frequent in women. The prevalence (odd ratio, OR) of back pain and dyslipidemia did not increase with higher BMI and the prevalence of back pain did not increase with age. Overall discomfort related to overweight was rated as 61.3 +/- 19.9 mm on a 0 to 100-mm scale. Discomfort was less marked in men, decreased with age and increased with BMI (and with the consultations in the Paris area). CONCLUSIONS This study shows the complexity of relationships between concomitant diseases, overall discomfort, BMI, age and sex (in the population of overweight and obese patients) and should improve the management of such patients and their complications.
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Affiliation(s)
- J-M Lecerf
- Service de nutrition, Institut Pasteur de Lille, Lille (59).
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Weber P, Filipecki J, Bingen E, Fitoussi F, Goldfarb G, Chauvin JP, Reitz C, Portier H. Genetic and phenotypic characterization of macrolide resistance in group A streptococci isolated from adults with pharyngo-tonsillitis in France. J Antimicrob Chemother 2001; 48:291-4. [PMID: 11481304 DOI: 10.1093/jac/48.2.291] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Three hundred and three strains of group A streptococci (GAS) isolated from adults with pharyngitis were tested to evaluate their phenotype of resistance to macrolides-lincosamides and to search for macrolide resistance genes. MICs of clarithromycin were determined. The overall rate of resistance to both erythromycin and clarithromycin was 9.6%. Constitutive, inducible and M phenotypes of resistance were detected in 4.3, 2 and 3.3% of strains, respectively. All constitutive phenotypes harboured ermB genes, whereas inducible phenotypes had the ermTR gene and M phenotypes had the mefA gene. In France, the current resistance rate of GAS to erythromycin and clarithromycin remains low.
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Affiliation(s)
- P Weber
- Laboratoire de Biologie Médicale BIO VSM, 10 rue de la Gare, F-77360 Vaires-sur-Marne, France.
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Serment G, Rossi D, Reitz C, Boumendil O. [Patterns of use of terazosine in current medical practice in ambulatory patients with obstructive and irritative obstructive disorders of urination]. Prog Urol 2000; 10:254-60. [PMID: 10857143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
OBJECTIVES To evaluate the efficacy and to describe the modalities of use of terazosin hydrochloride dihydrate, prescribed under conditions of routine clinical practice to a vast population of patients with benign prostatic hyperplasia (BPH). MATERIAL AND METHODS 1,624 patients suffering from BPH and requiring medical treatment were included in this multicentre open clinical trial performed by 983 general practitioners. After a one-week titration phase, terazosin was administered for 4 weeks at the dosage of 5 mg per day as a single dose in the evening at bedtime. The efficacy of treatment was assessed by the variation of the IPSS score between inclusion and the end of treatment, the treatment response rate (at least 3 point reduction of the IPSS score) and the course of the quality of life score. The safety of treatment was evaluated by clinical interview and physical examination at each visit and by analysis of all adverse events occurring during the trial. RESULTS A mean 45.8% improvement of the IPSS score (corresponding to a mean decrease of 8.81 points) was demonstrated between D0 and D35 (p < 0.001). The treatment response rate was 91.8%. A mean improvement of 2.11 points (p < 0.001) of the quality of life score was obtained. Complementary subgroup analysis (moderate dysuria n = 775 and severe BPH n = 702) showed that the efficacy of treatment was independent of the initial severity of the voiding disorders. The clinical safety of treatment was considered to be good in 92.5% of cases by the investigators. The incidence of adverse events attributable to treatment and related to a fall in blood pressure was 2.6%. Less than half (20/43, i.e. 1.25% of the population) of the patients experiencing this type of adverse event had to discontinue treatment. The ease of use of treatment was considered to be good in 85.2% of cases. CONCLUSION Terazosin constitutes an effective symptomatic treatment for BPH when surgery is not indicated, whether the initial disorders are moderate or severe. The safety of treatment appears to be perfectly satisfactory, in a patient series representative of the general practice outpatient population concerned by BPH (age, state of health, concomitant treatments). The one-week progressive dose regimen allows cautious introduction of treatment and generally does not raise any problems of acceptability.
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Affiliation(s)
- G Serment
- Service d'Urologie, Hôpital Salvator, Marseille, France
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Pessey JJ, Reitz C, Los F. [Acute rhinosinusitis in the adult: national survey of general practice management]. Rev Laryngol Otol Rhinol (Bord) 2000; 121:237-41. [PMID: 11233706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/16/2023]
Abstract
Between the 17/1/2000 and the 31/3/2000 a study was carried out in 5000 general practitioners in the management of patients with acute maxillary sinusitis. The general practitioners filled out a questionnaire in 2 parts: the first part about their management (diagnosis-treatment) and the second part included 1 case study. According to the results of the first part, acute maxillary sinusitis occurred frequently during the winter months adding further complications. The second part of the study confirmed the finding of the first part. Analysis of case study demonstrates that this pathology affected men at the median age 37.6. The incidence of bilateral sinusitis is (61.4%) maxillary (61.1%), frontal (31.7%), ethmoidomaxillary (9.4%) or sphenoidal (1.7%). One quarter of patients participated in further medical investigations that included regular X rays of sinus and 14% patients in anterior rhinoscopy. In the older patients, on the patients with unilateral sinusitis, or sphenoidal sinusitis, the investigations were more frequent and these patients appealed for the specialist frequently (Ear Nose and Throat specialist mainly). The first line of treatment included 3.2 products of which antibiotics 98.5%, vasoconstrictors 55%, anti-inflammatory 55% (corticosteroids 46.8%, non corticosteroids 8.7%), mucolytics 41.6%. In total, general practitioners confirmed their pragmatic management in the treatment of acute sinusitis based on clinical diagnosis.
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Affiliation(s)
- J J Pessey
- C.H.U. Rangueil, Clinique Universitaire O.R.L., 1 avenue Jean Poulhes, F-31408, Toulouse, France
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Reitz C, Breipohl W, Augustin A, Bours J. Analysis of tear proteins by one- and two-dimensional thin-layer iosoelectric focusing, sodium dodecyl sulfate electrophoresis and lectin blotting. Detection of a new component: cystatin C. Graefes Arch Clin Exp Ophthalmol 1998; 236:894-9. [PMID: 9865619 DOI: 10.1007/s004170050177] [Citation(s) in RCA: 39] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
Abstract
BACKGROUND Isoelectric focusing (IEF) of tear proteins has not yet been carried out in a satisfactory way. Two-dimensional (2D) electrophoresis, especially in the combination of IEF with SDS, is able to differentiate between proteins in detail. The purpose of this study was therefore to analyze tear proteins by 1D IEF alone and in combination with a 2D pattern, and by IEF followed by lectin staining. METHODS Ampholines, covering a broad range from pH 3 to pH 10, were applied. After IEF, semi-dry blotting and incubation with a group II lectin and two group V lectins was performed. RESULTS Tear proteins could be separated into 31 single bands. Tear-specific pre-albumin (TSPA), lactoferrin, sIgA, IgG and lysozyme were found to be main components. Isoelectric points (IEPs, pls) of all proteins separated were determined by comparison with IEF standards. 2D patterns of IEF and SDS electrophoresis were obtained for the main subunit components of lactoferrin, sIgA, TSPA, and lysozyme. An additional new component of considerable concentration was focused at pI 8.6 with a subunit MW of 14 kDa. With s-WGA a component at an IEP of 5.2 was visualized, representing transferrin. With SNA, lactoferrin stained as a sharp main band at pI 5.1 with three additional weaker bands at IEPs from 4.8 to 4.9. At IEPs between 4.4 and 6.1, multiple components of sIgA were stained with MAA. The sugar specificity of transferrin at pI 5.2 was beta-GlcNAc. Lactoferrin showed glycation with NANA-alpha-2-6-Gal or NANA-alpha-2-6-GalNAc, whereas the sugar specificity of sIgA was NANA-alpha-2-3-Gal. CONCLUSIONS The investigative strategy applied here, including IEF alone, in combination with SDS-electrophoresis, and SDS-electrophoresis followed by lectin staining proved to be a reproducible method for tear protein analysis of hitherto unexperienced capacity. Lectin-stained bands of native tear proteins are not uniformly glycated by one sugar residue, but show various sugar specificities. IgA as a whole molecule is specifically glycated with NANA-alpha-2-3-Gal.
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Affiliation(s)
- C Reitz
- Institute for Experimental Ophthalmology, University of Bonn, Germany
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Schröder J, Geider FJ, Binkert M, Reitz C, Jauss M, Sauer H. Subsyndromes in chronic schizophrenia: do their psychopathological characteristics correspond to cerebral alterations? Psychiatry Res 1992; 42:209-20. [PMID: 1496053 DOI: 10.1016/0165-1781(92)90113-h] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
This article examines the relationship between psychopathological subsyndromes in schizophrenia and cerebral alterations. A factor analysis of the psychopathological characteristics of 50 DSM-III schizophrenic patients revealed four subsyndromes. On the basis of these subsyndromes, four corresponding clusters of patients--remitted, chronic delusional, chronic asthenic, and chronic disorganized--were identified. These clusters were then compared with respect to negative symptoms, treatment response, neurological soft signs (NSS), and computed tomographic findings, such as the ventricle-brain ratio (VBR), using a discriminant analysis. The first discriminant function consisted of negative symptoms and significantly differentiated the remitted cluster from the three chronic clusters. Within the chronic clusters, the disorganized cluster was clearly identified by the second discriminant function (VBR and NSS). The third function (width of the interhemispheric fissure) provided only a tentative differentiation between the chronic delusional cluster and the chronic asthenic cluster. Although the subsyndromes of chronic schizophrenia share negative symptoms as a common feature, they appear to differ somewhat with regard to their morphological sites. These findings indicate that negative symptoms may arise from different psychopathological states and corroborate the existence of three subsyndromes in chronic schizophrenia.
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Affiliation(s)
- J Schröder
- Department of Psychiatry, University of Heidelberg, Germany
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Abstract
A new scale for neurological soft signs (NSS) was constructed and consists of 17 items compiled from the literature. The scale was found to have a high internal reliability (Cronbach's alpha 0.83) and a high interrater reliability (0.88). According to the results of a factor analysis, NSS are covered by five factors: 'motor coordination', 'integrative functions', 'complex motor tasks', 'righ/left and spatial orientation' and 'hard signs'. Using this scale, the associations of NSS with clinical course and brain alterations were investigated. NSS varied with the clinical course and were significantly correlated with some BPRS subscales, in particular 'thought disorder'. In addition, the 'motor coordination' soft signs were found to correlate with morphological alterations in the basal ganglia.
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Affiliation(s)
- J Schröder
- Department of Psychiatry, University of Heidelberg, F.R.G
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Abstract
Caripito itch, a pruritic dermatosis rarely seen in the United States, is caused by contact with moths of the genus Hylesia--specifically, with urticating abdominal hairs of the adult female moth. The purpose of this study was to investigate an outbreak of Caripito itch that occurred in thirty-four of thirty-five crew members of a British oil tanker who were exposed to Hylesia moths at the port of Caripito, Venezuela. Methods of investigation included general history and physical examination of all crew members, complete inspection of the ship, transparent-tape slide preparations from involved skin, cutaneous histopathologic studies, and entomologic examination of the moths. The patients had a typical papulourticarial eruption, primarily on exposed surfaces. Although Hylesia moths do not occur in the United States, primary care physicians and dermatologists, especially those located in port cities, should be aware of cutaneous lepidopterism caused by Hylesia moths.
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