Devon Check

Overview:

Devon Check, PhD is a health services researcher focused on understanding and overcoming barriers to the delivery of equitable, high-quality care for patients with cancer and other potentially life-limiting conditions.

Dr. Check received her PhD in Health Policy and Management from the Gillings School of Global Public Health at UNC-Chapel Hill. Prior to joining the Department of Population Health Sciences at Duke, she completed a postdoctoral fellowship in Delivery Science at Kaiser Permanente Northern California.

Areas of Expertise: Implementation Science and Health Services Research

Positions:

Assistant Professor in Population Health Sciences

Population Health Sciences
School of Medicine

Member of the

Duke Cancer Institute
School of Medicine

Education:

Ph.D. 2016

University of North Carolina - Chapel Hill

Grants:

Collaboratory Resource Coordinating Center for Pragmatic and Implementation Studies for the Management of Pain (PRISM) (U24)

Administered By
Duke Clinical Research Institute
Awarded By
National Institutes of Health
Role
Co Investigator
Start Date
End Date

Promotion of Prostate Cancer Screening Equity: A Quality Improvement Education Initiative

Administered By
Population Health Sciences
Awarded By
National Minority Quality Forum
Role
Principal Investigator
Start Date
End Date

Publications:

Integration of Improvement and Implementation Science in Practice-Based Research Networks: a Longitudinal, Comparative Case Study.

BACKGROUND: Implementation science (IS) and quality improvement (QI) inhabit distinct areas of scholarly literature, but are often blended in practice. Because practice-based research networks (PBRNs) draw from both traditions, their experience could inform opportunities for strategic IS-QI alignment. OBJECTIVE: To systematically examine IS, QI, and IS/QI projects conducted within a PBRN over time to identify similarities, differences, and synergies. DESIGN: Longitudinal, comparative case study of projects conducted in the Oregon Rural Practice-based Research Network (ORPRN) from January 2007 to January 2019. APPROACH: We reviewed documents and conducted staff interviews. We classified projects as IS, QI, IS/QI, or other using established criteria. We abstracted project details (e.g., objective, setting, theoretical framework) and used qualitative synthesis to compare projects by classification and to identify the contributions of IS and QI within the same project. KEY RESULTS: Almost 30% (26/99) of ORPRN's projects included IS or QI elements; 54% (14/26) were classified as IS/QI. All 26 projects used an evidence-based intervention and shared many similarities in relation to objective and setting. Over half of the IS and IS/QI projects used randomized designs and theoretical frameworks, while no QI projects did. Projects displayed an upward trend in complexity over time. Project used a similar number of practice change strategies; however, projects classified as IS predominantly employed education/training while all IS/QI and most QI projects used practice facilitation. Projects including IS/QI elements demonstrated the following contributions: QI provides the mechanism by which the principles of IS are operationalized in order to support local practice change and IS in turn provides theories to inform implementation and evaluation to produce generalizable knowledge. CONCLUSIONS: Our review of projects conducted over a 12-year period in one PBRN demonstrates key synergies for IS and QI. Strategic alignment of IS/QI within projects may help improve care quality and bridge the research-practice gap.
Authors
Davis, MM; Gunn, R; Kenzie, E; Dickinson, C; Conway, C; Chau, A; Michaels, L; Brantley, S; Check, DK; Elder, N
MLA Citation
Davis, Melinda M., et al. “Integration of Improvement and Implementation Science in Practice-Based Research Networks: a Longitudinal, Comparative Case Study.J Gen Intern Med, Apr. 2021. Pubmed, doi:10.1007/s11606-021-06610-1.
URI
https://scholars.duke.edu/individual/pub1478721
PMID
33852140
Source
pubmed
Published In
J Gen Intern Med
Published Date
DOI
10.1007/s11606-021-06610-1

Opioid Use Disorder and Overdose in Older Adults With Breast, Colorectal, or Prostate Cancer.

BACKGROUND: Despite high rates of opioid therapy, evidence about the risk of preventable opioid harms among cancer survivors is underdeveloped. Our objective was to estimate the odds of opioid use disorder (OUD) and overdose following breast, colorectal, or prostate cancer diagnosis among Medicare beneficiaries. METHODS: We conducted a retrospective cohort study using 2007-2014 Surveillance, Epidemiology, and End Results-Medicare data for cancer survivors with a first cancer diagnosis of stage 0-III breast, colorectal, or prostate cancer at age 66-89 years between 2008 and 2013. Cancer survivors were matched to up to 2 noncancer controls on age, sex, and Surveillance, Epidemiology, and End Results region. Using Firth logistic regression, we estimated adjusted 1-year odds of OUD or nonfatal opioid overdose associated with a cancer diagnosis. We also estimated adjusted odds of OUD and overdose separately and by cancer stage, prior opioid use, and follow-up time. RESULTS: Among 69 889 cancer survivors and 125 007 controls, the unadjusted rates of OUD or nonfatal overdose were 25.2, 27.1, 38.9, and 12.4 events per 10 000 patients in the noncancer, breast, colorectal, and prostate samples, respectively. There was no association between cancer and OUD. Colorectal survivors had 2.3 times higher odds of opioid overdose compared with matched controls (adjusted odds ratio = 2.33, 95% confidence interval  = 1.49 to 3.67). Additionally, overdose risk was greater in those with more advanced disease, no prior opioid use, and preexisting mental health conditions. CONCLUSIONS: Opioid overdose was a rare, but statistically significant, outcome following stage II-III colorectal cancer diagnosis, particularly among previously opioid-naïve patients. These patients may require heightened screening and intervention to prevent inadvertent adverse opioid harms.
Authors
Roberts, AW; Eiffert, S; Wulff-Burchfield, EM; Dusetzina, SB; Check, DK
MLA Citation
Roberts, Andrew W., et al. “Opioid Use Disorder and Overdose in Older Adults With Breast, Colorectal, or Prostate Cancer.J Natl Cancer Inst, vol. 113, no. 4, Apr. 2021, pp. 425–33. Pubmed, doi:10.1093/jnci/djaa122.
URI
https://scholars.duke.edu/individual/pub1456578
PMID
32805032
Source
pubmed
Published In
J Natl Cancer Inst
Volume
113
Published Date
Start Page
425
End Page
433
DOI
10.1093/jnci/djaa122

Implementation and Impact of a Risk-Stratified Prostate Cancer Screening Algorithm as a Clinical Decision Support Tool in a Primary Care Network.

BACKGROUND: Implementation methods of risk-stratified cancer screening guidance throughout a health care system remains understudied. OBJECTIVE: Conduct a preliminary analysis of the implementation of a risk-stratified prostate cancer screening algorithm in a single health care system. DESIGN: Comparison of men seen pre-implementation (2/1/2016-2/1/2017) vs. post-implementation (2/2/2017-2/21/2018). PARTICIPANTS: Men, aged 40-75 years, without a history of prostate cancer, who were seen by a primary care provider. INTERVENTIONS: The algorithm was integrated into two components in the electronic health record (EHR): in Health Maintenance as a personalized screening reminder and in tailored messages to providers that accompanied prostate-specific antigen (PSA) results. MAIN MEASURES: Primary outcomes: percent of men who met screening algorithm criteria; percent of men with a PSA result. Logistic repeated measures mixed models were used to test for differences in the proportion of individuals that met screening criteria in the pre- and post-implementation periods with age, race, family history, and PSA level included as covariates. KEY RESULTS: During the pre- and post-implementation periods, 49,053 and 49,980 men, respectively, were seen across 26 clinics (20.6% African American). The proportion of men who met screening algorithm criteria increased from 49.3% (pre-implementation) to 68.0% (post-implementation) (p < 0.001); this increase was observed across all races, age groups, and primary care clinics. Importantly, the percent of men who had a PSA did not change: 55.3% pre-implementation, 55.0% post-implementation. The adjusted odds of meeting algorithm-based screening was 6.5-times higher in the post-implementation period than in the pre-implementation period (95% confidence interval, 5.97 to 7.05). CONCLUSIONS: In this preliminary analysis, following implementation of an EHR-based algorithm, we observed a rapid change in practice with an increase in screening in higher-risk groups balanced with a decrease in screening in low-risk groups. Future efforts will evaluate costs and downstream outcomes of this strategy.
Authors
Shah, A; Polascik, TJ; George, DJ; Anderson, J; Hyslop, T; Ellis, AM; Armstrong, AJ; Ferrandino, M; Preminger, GM; Gupta, RT; Lee, WR; Barrett, NJ; Ragsdale, J; Mills, C; Check, DK; Aminsharifi, A; Schulman, A; Sze, C; Tsivian, E; Tay, KJ; Patierno, S; Oeffinger, KC; Shah, K
MLA Citation
Shah, Anand, et al. “Implementation and Impact of a Risk-Stratified Prostate Cancer Screening Algorithm as a Clinical Decision Support Tool in a Primary Care Network.J Gen Intern Med, vol. 36, no. 1, 2021, pp. 92–99. Pubmed, doi:10.1007/s11606-020-06124-2.
URI
https://scholars.duke.edu/individual/pub1441099
PMID
32875501
Source
pubmed
Published In
J Gen Intern Med
Volume
36
Published Date
Start Page
92
End Page
99
DOI
10.1007/s11606-020-06124-2

Associations of Patient Characteristics and Care Setting with Complexity of Specialty Palliative Care Visits.

Background: Information routinely collected during a palliative care consultation request may help predict the level of complexity of that patient encounter. Objectives: We examined whether patient and consultation characteristics, as captured in consultation requests, are associated with the number of unmet palliative care needs that emerge during consultation, as an indicator of complexity. Design: We performed a retrospective cohort analysis of palliative care consultations. Setting: We analyzed quality-of-care data from specialty palliative care consultations contained in the Quality Data Collection Tool of the Global Palliative Care Quality Alliance from 2012 to 2017. Measurements: Using 13 point-of-care assessments of quality of life, symptoms, advance care planning, and prognosis, we created a complexity score ranging from 0 (not complex) to 13 (highest complexity). Using multivariable linear regression, we examined the relationships of consultation setting and patient characteristics with complexity score. Results: Patients in our cohort (N = 3121) had an average complexity score of 6.7 (standard deviation = 3.7). Female gender, nonwhite race, and neurological (e.g., dementia) and noncancer primary diagnosis were associated with increased complexity score. The hospital intensive care unit, compared with the general floor, was associated with higher complexity scores. In contrast, outpatient and residence, compared with the general floor, were associated with lower complexity scores. Conclusion: Patient, disease, and care setting factors known at the time of specialty palliative care consultation request are associated with level of complexity, and they may inform teams about the right service provisions, including time and expertise, required to meet patient needs.
Authors
Kamal, AH; Check, DK; Bull, J; Wolf, S; Troy, J; Samsa, G; Nicolla, JM; Harker, M; Taylor, DH
MLA Citation
Kamal, Arif H., et al. “Associations of Patient Characteristics and Care Setting with Complexity of Specialty Palliative Care Visits.J Palliat Med, vol. 24, no. 1, Jan. 2021, pp. 83–90. Pubmed, doi:10.1089/jpm.2020.0149.
URI
https://scholars.duke.edu/individual/pub1450796
PMID
32634037
Source
pubmed
Published In
Journal of Palliative Medicine
Volume
24
Published Date
Start Page
83
End Page
90
DOI
10.1089/jpm.2020.0149

Improvement Science and Implementation Science in Cancer Care: Identifying Areas of Synergy and Opportunities for Further Integration.

Efforts to improve cancer care primarily come from two fields: improvement science and implementation science. The two fields have developed independently, yet they have potential for synergy. Leveraging that synergy to enhance alignment could both reduce duplication and, more importantly, enhance the potential of both fields to improve care. To better understand potential for alignment, we examined 20 highly cited cancer-related improvement science and implementation science studies published in the past 5 years, characterizing and comparing their objectives, methods, and approaches to practice change. We categorized studies as improvement science or implementation science based on authors' descriptions when possible; otherwise, we categorized studies as improvement science if they evaluated efforts to improve the quality, value, or safety of care, or implementation science if they evaluated efforts to promote the implementation of evidence-based interventions into practice. All implementation studies (10/10) and most improvement science studies (6/10) sought to improve uptake of evidence-based interventions. Improvement science and implementation science studies employed similar approaches to change practice. For example, training was employed in 8/10 implementation science studies and 4/10 improvement science studies. However, improvement science and implementation science studies used different terminology to describe similar concepts and emphasized different methodological aspects in reporting. Only 4/20 studies (2 from each category) described using a formal theory or conceptual framework to guide program development. Most studies were multi-site (10/10 implementation science and 6/10 improvement science) and a minority (2 from each category) used a randomized design. Based on our review, cancer-related improvement science and implementation science studies use different terminology and emphasize different methodological aspects in reporting but share similarities in purpose, scope, and methods, and are at similar levels of scientific development. The fields are well-positioned for alignment. We propose that next steps include harmonizing language and cross-fertilizing methods of program development and evaluation.
Authors
Check, DK; Zullig, LL; Davis, MM; Davies, L; Chambers, D; Fleisher, L; Kaplan, SJ; Proctor, E; Ramanadhan, S; Schroeck, FR; Stover, AM; Koczwara, B
MLA Citation
Check, Devon K., et al. “Improvement Science and Implementation Science in Cancer Care: Identifying Areas of Synergy and Opportunities for Further Integration.J Gen Intern Med, vol. 36, no. 1, Jan. 2021, pp. 186–95. Pubmed, doi:10.1007/s11606-020-06138-w.
URI
https://scholars.duke.edu/individual/pub1459324
PMID
32869193
Source
pubmed
Published In
J Gen Intern Med
Volume
36
Published Date
Start Page
186
End Page
195
DOI
10.1007/s11606-020-06138-w

Research Areas:

Cancer
Communication
Decision Making
Delivery of Health Care
Diffusion of Innovation
Guideline Adherence
Health Services Research
Healthcare Disparities
Implementation Science
Palliative Care
Quality of Health Care
Survivorship