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Article ; Online: Association of a Medicare Mandate for Shared Decision-Making With Cardiac Device Utilization.

Rager, Joshua B / Hou, Hechuan / Caverly, Tanner / Thompson, Michael P

2024 Volume 184, Issue 4, Page(s) 439–440

MeSH term(s)	Aged ; Humans ; United States ; Defibrillators, Implantable ; Medicare ; Electric Countershock ; Risk Factors ; Death, Sudden, Cardiac
Language	English
Publishing date	2024-02-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	2699338-7
ISSN	2168-6114 ; 2168-6106
ISSN (online)	2168-6114
ISSN	2168-6106
DOI	10.1001/jamainternmed.2023.8532
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Article ; Online: Re: Inaccuracies in electronic health records smoking data and a potential approach to address resulting underestimation in determining lung cancer screening eligibility.

Kukhareva, Polina / Caverly, Tanner / Kawamoto, Kensaku

Journal of the American Medical Informatics Association : JAMIA

2022 Volume 29, Issue 9, Page(s) 1655

MeSH term(s)	Early Detection of Cancer/methods ; Electronic Health Records ; Eligibility Determination ; Humans ; Lung Neoplasms/diagnosis ; Mass Screening ; Smoking
Language	English
Publishing date	2022-07-12
Publishing country	England
Document type	Letter ; Comment
ZDB-ID	1205156-1
ISSN	1527-974X ; 1067-5027
ISSN (online)	1527-974X
ISSN	1067-5027
DOI	10.1093/jamia/ocac119
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Article ; Online: Selecting the best candidates for lung cancer screening.

Caverly, Tanner

JAMA internal medicine

2015 Volume 175, Issue 6, Page(s) 898–900

MeSH term(s)	Contraindications ; Decision Making ; Early Detection of Cancer ; Humans ; Lung Neoplasms/diagnosis ; Patient Education as Topic ; Patient Selection ; Risk Assessment ; Unnecessary Procedures
Language	English
Publishing date	2015-06
Publishing country	United States
Document type	Editorial
ZDB-ID	2699338-7
ISSN	2168-6114 ; 2168-6106
ISSN (online)	2168-6114
ISSN	2168-6106
DOI	10.1001/jamainternmed.2015.1235
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Article ; Online: Dealing with the Lack of Time for Detailed Shared Decision-making in Primary Care: Everyday Shared Decision-making.

Caverly, Tanner J / Hayward, Rodney A

Journal of general internal medicine

2020 Volume 35, Issue 10, Page(s) 3045–3049

Abstract: Policymakers and researchers are strongly encouraging clinicians to support patient autonomy through shared decision-making (SDM). In setting policies for clinical care, decision-makers need to understand that current models of SDM have tended to focus ... ...

Abstract	Policymakers and researchers are strongly encouraging clinicians to support patient autonomy through shared decision-making (SDM). In setting policies for clinical care, decision-makers need to understand that current models of SDM have tended to focus on major decisions (e.g., surgeries and chemotherapy) and focused less on everyday primary care decisions. Most decisions in primary care are substantive everyday decisions: intermediate-stakes decisions that occur dozens of times every day, yet are non-trivial for patients, such as whether routine mammography should start at age 40, 45, or 50. Expectations that busy clinicians use current models of SDM (here referred to as "detailed" SDM) for these decisions can feel overwhelming to clinicians. Evidence indicates that detailed SDM is simply not realistic for most of these decisions and without a feasible alternative, clinicians usually default to a decision-making approach with little to no personalization. We propose, for discussion and refinement, a compromise approach to personalizing these decisions (everyday SDM). Everyday SDM is based on a feasible process for supporting patient autonomy that also allows clinicians to continue being respectful health advocates for their patients. We propose that alternatives to detailed SDM are needed to make progress toward more patient-centered care.
MeSH term(s)	Adult ; Decision Making ; Decision Making, Shared ; Humans ; Patient Participation ; Patient-Centered Care ; Primary Health Care
Language	English
Publishing date	2020-08-10
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	639008-0
ISSN	1525-1497 ; 0884-8734
ISSN (online)	1525-1497
ISSN	0884-8734
DOI	10.1007/s11606-020-06043-2
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Article ; Online: Using Risk Models to Make Lung Cancer Screening Decisions: Evidence-Based and Getting Better.

Caverly, Tanner J / Meza, Rafael

Annals of internal medicine

2019 Volume 171, Issue 9, Page(s) 669–670

MeSH term(s)	Decision Making ; Early Detection of Cancer ; Humans ; Lung Neoplasms ; Mass Screening ; Smokers
Language	English
Publishing date	2019-10-22
Publishing country	United States
Document type	Editorial ; Comment
ZDB-ID	336-0
ISSN	1539-3704 ; 0003-4819
ISSN (online)	1539-3704
ISSN	0003-4819
DOI	10.7326/M19-2869
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Article ; Online: Tackling Guideline Non-concordance: Primary Care Barriers to Incorporating Life Expectancy into Lung Cancer Screening Decision-Making-A Qualitative Study.

Kearney, Lauren / Bolton, Rendelle E / Núñez, Eduardo R / Boudreau, Jacqueline H / Sliwinski, Samantha / Herbst, Abigail N / Caverly, Tanner J / Wiener, Renda Soylemez

Journal of general internal medicine

2024

Abstract: Background: Primary care providers (PCPs) are often the first point of contact for discussing lung cancer screening (LCS) with patients. While guidelines recommend against screening people with limited life expectancy (LLE) who are less likely to ... ...

Abstract	Background: Primary care providers (PCPs) are often the first point of contact for discussing lung cancer screening (LCS) with patients. While guidelines recommend against screening people with limited life expectancy (LLE) who are less likely to benefit, these patients are regularly referred for LCS. Objective: We sought to understand barriers PCPs face to incorporating life expectancy into LCS decision-making for patients who otherwise meet eligibility criteria, and how a hypothetical point-of-care tool could support patient selection. Design: Qualitative study based on semi-structured telephone interviews. Participants: Thirty-one PCPs who refer patients for LCS, from six Veterans Health Administration facilities. Approach: We thematically analyzed interviews to understand how PCPs incorporated life expectancy into LCS decision-making and PCPs' receptivity to a point-of-care tool to support patient selection. Final themes were organized according to the Cabana et al. framework Why Don't Physicians Follow Clinical Practice Guidelines, capturing the influence of clinician knowledge, attitudes, and behavior on LCS appropriateness determinations. Key results: PCP referrals to LCS for patients with LLE were influenced by limited knowledge of the life expectancy threshold at which patients are less likely to benefit from LCS, discomfort estimating life expectancy, fear of missing cancer at the point of early detection, and prioritization of factors such as quality of life, patient values, clinician-patient relationship, and family support. PCPs were receptive to a decision support tool to inform and communicate LCS appropriateness decisions if easy to use and integrated into clinical workflows. Conclusions: Our study suggests knowledge gaps and attitudes may drive decisions to offer screening despite LLE, a behavior counter to guideline recommendations. Integrating a LCS decision support tool that incorporates life expectancy within the electronic medical record and existing clinical workflows may be one acceptable solution to improve guideline concordance and increase confidence in selecting high benefit patients for LCS.
Language	English
Publishing date	2024-03-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	639008-0
ISSN	1525-1497 ; 0884-8734
ISSN (online)	1525-1497
ISSN	0884-8734
DOI	10.1007/s11606-024-08705-x
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Article ; Online: "It Can't Hurt!": Why Many Patients With Limited Life Expectancy Decide to Accept Lung Cancer Screening.

Núñez, Eduardo R / Bolton, Rendelle E / Boudreau, Jacqueline H / Sliwinski, Samantha K / Herbst, Abigail N / Kearney, Lauren E / Caverly, Tanner J / Wiener, Renda Soylemez

Annals of family medicine

2024 Volume 22, Issue 2, Page(s) 95–102

Abstract: Purpose: Lung cancer screening (LCS) has less benefit and greater potential for iatrogenic harm among people with multiple comorbidities and limited life expectancy. Yet, such individuals are more likely to undergo screening than healthier LCS-eligible ... ...

Abstract	Purpose: Lung cancer screening (LCS) has less benefit and greater potential for iatrogenic harm among people with multiple comorbidities and limited life expectancy. Yet, such individuals are more likely to undergo screening than healthier LCS-eligible people. We sought to understand how patients with marginal LCS benefit conceptualize their health and make decisions regarding LCS. Methods: We interviewed 40 people with multimorbidity and limited life expectancy, as determined by high Care Assessment Need scores, which predict 1-year risk of hospitalization or death. Patients were recruited from 6 Veterans Health Administration facilities after discussing LCS with their clinician. We conducted a thematic analysis using constant comparison to explore factors that influence LCS decision making. Results: Patients commonly held positive beliefs about screening and perceived LCS to be noninvasive. When posed with hypothetical scenarios of limited benefit, patients emphasized the nonlongevity benefits of LCS (eg, peace of mind, planning for the future) and generally did not consider their health status or life expectancy when making decisions regarding LCS. Most patients were unaware of possible additional evaluations or treatment of screen-detected findings, but when probed further, many expressed concerns about the potential need for multiple evaluations, referrals, or invasive procedures. Conclusions: Patients in this study with multimorbidity and limited life expectancy were unaware of their greater risk of potential harm when accepting LCS. Given patient trust in clinician recommendations, it is important that clinicians engage patients with marginal LCS benefit in shared decision making, ensuring that their values of desiring more information about their health are weighed against potential harms from further evaluations.
MeSH term(s)	Humans ; Lung Neoplasms/diagnosis ; Decision Making ; Early Detection of Cancer/methods ; Comorbidity ; Life Expectancy ; Mass Screening
Language	English
Publishing date	2024-03-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	2171425-3
ISSN	1544-1717 ; 1544-1709
ISSN (online)	1544-1717
ISSN	1544-1709
DOI	10.1370/afm.3081
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Article ; Online: Identify Patients Likely to Benefit from Lung Cancer Screening.

Begnaud, Abbie / Leishman, Joseph / Caverly, Tanner J

American family physician

2020 Volume 101, Issue 2, Page(s) 69–70

MeSH term(s)	Early Detection of Cancer ; Humans ; Lung Neoplasms ; Mass Screening ; Tomography, X-Ray Computed
Language	English
Publishing date	2020-01-14
Publishing country	United States
Document type	Letter ; Research Support, Non-U.S. Gov't ; Comment
ZDB-ID	412694-4
ISSN	1532-0650 ; 0002-838X ; 0572-3612
ISSN (online)	1532-0650
ISSN	0002-838X ; 0572-3612
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Article ; Online: Implementation of a Web-Based Tool for Shared Decision-making in Lung Cancer Screening: Mixed Methods Quality Improvement Evaluation.

Lowery, Julie / Fagerlin, Angela / Larkin, Angela R / Wiener, Renda S / Skurla, Sarah E / Caverly, Tanner J

JMIR human factors

2022 Volume 9, Issue 2, Page(s) e32399

Abstract: Background: Lung cancer risk and life expectancy vary substantially across patients eligible for low-dose computed tomography lung cancer screening (LCS), which has important consequences for optimizing LCS decisions for different patients. To account ... ...

Abstract	Background: Lung cancer risk and life expectancy vary substantially across patients eligible for low-dose computed tomography lung cancer screening (LCS), which has important consequences for optimizing LCS decisions for different patients. To account for this heterogeneity during decision-making, web-based decision support tools are needed to enable quick calculations and streamline the process of obtaining individualized information that more accurately informs patient-clinician LCS discussions. We created DecisionPrecision, a clinician-facing web-based decision support tool, to help tailor the LCS discussion to a patient's individualized lung cancer risk and estimated net benefit. Objective: The objective of our study is to test two strategies for implementing DecisionPrecision in primary care at eight Veterans Affairs medical centers: a quality improvement (QI) training approach and academic detailing (AD). Methods: Phase 1 comprised a multisite, cluster randomized trial comparing the effectiveness of standard implementation (adding a link to DecisionPrecision in the electronic health record vs standard implementation plus the Learn, Engage, Act, and Process [LEAP] QI training program). The primary outcome measure was the use of DecisionPrecision at each site before versus after LEAP QI training. The second phase of the study examined the potential effectiveness of AD as an implementation strategy for DecisionPrecision at all 8 medical centers. Outcomes were assessed by comparing absolute tool use before and after AD visits and conducting semistructured interviews with a subset of primary care physicians (PCPs) following the AD visits. Results: Phase 1 findings showed that sites that participated in the LEAP QI training program used DecisionPrecision significantly more often than the standard implementation sites (tool used 190.3, SD 174.8 times on average over 6 months at LEAP sites vs 3.5 SD 3.7 at standard sites; P<.001). However, this finding was confounded by the lack of screening coordinators at standard implementation sites. In phase 2, there was no difference in the 6-month tool use between before and after AD (95% CI -5.06 to 6.40; P=.82). Follow-up interviews with PCPs indicated that the AD strategy increased provider awareness and appreciation for the benefits of the tool. However, other priorities and limited time prevented PCPs from using them during routine clinical visits. Conclusions: The phase 1 findings did not provide conclusive evidence of the benefit of a QI training approach for implementing a decision support tool for LCS among PCPs. In addition, phase 2 findings showed that our light-touch, single-visit AD strategy did not increase tool use. To enable tool use by PCPs, prediction-based tools must be fully automated and integrated into electronic health records, thereby helping providers personalize LCS discussions among their many competing demands. PCPs also need more time to engage in shared decision-making discussions with their patients. Trial registration: ClinicalTrials.gov NCT02765412; https://clinicaltrials.gov/ct2/show/NCT02765412.
Language	English
Publishing date	2022-04-01
Publishing country	Canada
Document type	Journal Article
ISSN	2292-9495
ISSN (online)	2292-9495
DOI	10.2196/32399
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Article ; Online: Considerations for using predictive models that include race as an input variable: The case study of lung cancer screening.

Stevens, Elizabeth R / Caverly, Tanner / Butler, Jorie M / Kukhareva, Polina / Richardson, Safiya / Mann, Devin M / Kawamoto, Kensaku

Journal of biomedical informatics

2023 Volume 147, Page(s) 104525

Abstract: Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from ... ...

Abstract	Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. Thus, there is a need for a pragmatic framework to help model users think through how to include race in their chosen model so as to avoid inadvertently exacerbating disparities. In this paper, we use the case study of lung cancer screening to propose a simple framework to guide how model users can approach the use (or non-use) of race inputs in the predictive models they are tasked with leveraging in electronic health records and clinical workflows.
MeSH term(s)	Humans ; United States ; Early Detection of Cancer ; Lung Neoplasms/diagnosis ; Electronic Health Records
Language	English
Publishing date	2023-10-14
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, P.H.S. ; Research Support, N.I.H., Extramural
ZDB-ID	2057141-0
ISSN	1532-0480 ; 1532-0464
ISSN (online)	1532-0480
ISSN	1532-0464
DOI	10.1016/j.jbi.2023.104525
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