[Skip to Content]
[Skip to Content Landing]
Figure.
Flow Diagram Describing Included and Excluded Physician-Patient Conversations
Flow Diagram Describing Included and Excluded Physician-Patient Conversations
Table 1.  
Characteristics of Conversations in the Analytic Sample and Conversations Matching Search Term Key Words
Characteristics of Conversations in the Analytic Sample and Conversations Matching Search Term Key Words
Table 2.  
Presence of Shared Decision Making Communication Behaviors in Lung Cancer Screening Conversationsa
Presence of Shared Decision Making Communication Behaviors in Lung Cancer Screening Conversationsa
Table 3.  
Illustrative Lung Cancer Screening Conversations
Illustrative Lung Cancer Screening Conversations
1.
Moyer  VA; US Preventive Services Task Force.  Screening for lung cancer: US Preventive Services Task Force recommendation statement.  Ann Intern Med. 2014;160(5):330-338. doi:10.7326/M13-2771PubMedGoogle ScholarCrossref
2.
Ma  J, Ward  EM, Smith  R, Jemal  A.  Annual number of lung cancer deaths potentially avertable by screening in the United States.  Cancer. 2013;119(7):1381-1385. doi:10.1002/cncr.27813PubMedGoogle ScholarCrossref
3.
Bach  PB, Mirkin  JN, Oliver  TK,  et al.  Benefits and harms of CT screening for lung cancer: a systematic review.  JAMA. 2012;307(22):2418-2429. doi:10.1001/jama.2012.5521PubMedGoogle ScholarCrossref
4.
Harris  RP, Sheridan  SL, Lewis  CL,  et al.  The harms of screening: a proposed taxonomy and application to lung cancer screening.  JAMA Intern Med. 2014;174(2):281-285. doi:10.1001/jamainternmed.2013.12745PubMedGoogle ScholarCrossref
5.
Patz  EFJ  Jr, Pinsky  P, Gatsonis  C,  et al; NLST Overdiagnosis Manuscript Writing Team.  Overdiagnosis in low-dose computed tomography screening for lung cancer.  JAMA Intern Med. 2014;174(2):269-274. doi:10.1001/jamainternmed.2013.12738PubMedGoogle ScholarCrossref
6.
Wood  DE.  The importance of lung cancer screening with low-dose computed tomography for Medicare beneficiaries.  JAMA Intern Med. 2014;174(12):2016-2018. doi:10.1001/jamainternmed.2014.5623PubMedGoogle ScholarCrossref
7.
Woolf  SH, Harris  RP, Campos-Outcalt  D.  Low-dose computed tomography screening for lung cancer: how strong is the evidence?  JAMA Intern Med. 2014;174(12):2019-2022. doi:10.1001/jamainternmed.2014.5626PubMedGoogle ScholarCrossref
8.
Centers for Medicare & Medicaid Services. Decision memo for screening for lung cancer with low dose computed tomography (LDCT) (CAG-00439N). https://www.cms.gov/medicare-coverage-database/details/nca-decision-memo.aspx?NCAId=274. Published February 5, 2015. Accessed April 16, 2018.
9.
Goff  SL, Mazor  KM, Ting  HH, Kleppel  R, Rothberg  MB.  How cardiologists present the benefits of percutaneous coronary interventions to patients with stable angina: a qualitative analysis.  JAMA Intern Med. 2014;174(10):1614-1621. doi:10.1001/jamainternmed.2014.3328PubMedGoogle ScholarCrossref
10.
Elwyn  G, Hutchings  H, Edwards  A,  et al.  The OPTION scale: measuring the extent that clinicians involve patients in decision-making tasks.  Health Expect. 2005;8(1):34-42. doi:10.1111/j.1369-7625.2004.00311.xPubMedGoogle ScholarCrossref
11.
Elwyn  G, Edwards  A, Wensing  M, Grol  R. OPTION rater manual. http://www.optioninstrument.org/uploads/2/4/0/4/24040341/option_12_rater_manual.pdf. Accessed April 14, 2018.
12.
Rapport  F, Wainwright  P, Elwyn  G.  “Of the edgelands”: broadening the scope of qualitative methodology.  Med Humanit. 2005;31(1):37-42. doi:10.1136/jmh.2004.000190PubMedGoogle ScholarCrossref
13.
Hoffman  RM, Couper  MP, Zikmund-Fisher  BJ,  et al.  Prostate cancer screening decisions: results from the National Survey of Medical Decisions (DECISIONS study).  Arch Intern Med. 2009;169(17):1611-1618. doi:10.1001/archinternmed.2009.262PubMedGoogle ScholarCrossref
14.
Hoffmann  TC, Del Mar  C.  Patients’ expectations of the benefits and harms of treatments, screening, and tests: a systematic review.  JAMA Intern Med. 2015;175(2):274-286. doi:10.1001/jamainternmed.2014.6016PubMedGoogle ScholarCrossref
15.
Hoffmann  TC, Del Mar  C.  Clinicians’ expectations of the benefits and harms of treatments, screening, and tests: a systematic review.  JAMA Intern Med. 2017;177(3):407-419. doi:10.1001/jamainternmed.2016.8254PubMedGoogle ScholarCrossref
16.
Couët  N, Desroches  S, Robitaille  H,  et al.  Assessments of the extent to which health-care providers involve patients in decision making: a systematic review of studies using the OPTION instrument.  Health Expect. 2015;18(4):542-561. doi:10.1111/hex.12054PubMedGoogle ScholarCrossref
17.
Légaré  F, Stacey  D, Turcotte  S,  et al.  Interventions for improving the adoption of shared decision making by healthcare professionals.  Cochrane Database Syst Rev. 2014;(9):CD006732.PubMedGoogle Scholar
18.
Reuland  DS, Cubillos  L, Brenner  AT, Harris  RP, Minish  B, Pignone  MP.  A pre-post study testing a lung cancer screening decision aid in primary care.  BMC Med Inform Decis Mak. 2018;18(1):5. doi:10.1186/s12911-018-0582-1PubMedGoogle ScholarCrossref
19.
Volk  RJ, Linder  SK, Leal  VB,  et al.  Feasibility of a patient decision aid about lung cancer screening with low-dose computed tomography.  Prev Med. 2014;62:60-63. doi:10.1016/j.ypmed.2014.02.006PubMedGoogle ScholarCrossref
20.
Lau  YK, Caverly  TJ, Cao  P,  et al.  Evaluation of a personalized, web-based decision aid for lung cancer screening.  Am J Prev Med. 2015;49(6):e125-e129. doi:10.1016/j.amepre.2015.07.027PubMedGoogle ScholarCrossref
21.
Jimbo  M, Rana  GK, Hawley  S,  et al.  What is lacking in current decision aids on cancer screening?  CA Cancer J Clin. 2013;63(3):193-214. doi:10.3322/caac.21180PubMedGoogle ScholarCrossref
22.
Mazzone  PJ, Tenenbaum  A, Seeley  M,  et al.  Impact of a lung cancer screening counseling and shared decision-making visit.  Chest. 2017;151(3):572-578. doi:10.1016/j.chest.2016.10.027PubMedGoogle ScholarCrossref
23.
Mazzone  PJ, Silvestri  GA, Patel  S,  et al.  Screening for lung cancer: CHEST guideline and expert panel report.  Chest. 2018;153(4):954-985. doi:10.1016/j.chest.2018.01.016PubMedGoogle ScholarCrossref
Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words
    Original Investigation
    Less Is More
    October 2018

    Evaluating Shared Decision Making for Lung Cancer Screening

    Author Affiliations
    • 1Division of General Medicine and Clinical Epidemiology, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill
    • 2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill
    • 3Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
    • 4Department of Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill
    • 5Center for Health Promotion and Disease Prevention, University of North Carolina at Chapel Hill
    JAMA Intern Med. 2018;178(10):1311-1316. doi:10.1001/jamainternmed.2018.3054
    Key Points

    Question  What is the quality of guideline-recommended shared decision making about lung cancer screening in clinical practice?

    Findings  In this qualitative content analysis of 14 recorded and transcribed outpatient clinical encounters, the quality of shared decision making about lung cancer screening was poor, as rated by 2 independent observers using a validated shared decision making scale. Potential harms of screening were not adequately explained, and decision aids were not used.

    Meaning  Despite recommendations, shared decision making for lung cancer screening in practice may be far from what is intended by guidelines.

    Abstract

    Importance  The US Preventive Services Task Force recommends that shared decision making (SDM) involving a thorough discussion of benefits and harms should occur between clinicians and patients before initiating lung cancer screening (LCS) with low-dose computed tomography. The Centers for Medicare & Medicaid Services require an SDM visit using a decision aid as a prerequisite for LCS coverage. However, little is known about how SDM about LCS occurs in practice.

    Objective  To assess the quality of SDM about the initiation of LCS in clinical practice.

    Design, Setting, and Participants  A qualitative content analysis was performed of transcribed conversations between primary care or pulmonary care physicians and 14 patients presumed to be eligible for LCS, recorded between April 1, 2014, and March 1, 2018, that were identified within a large database.

    Main Outcomes and Measures  Independent observer ratings of communication behaviors of physicians using the OPTION (Observing Patient Involvement in Decision Making) scale, a validated 12-item measure of SDM (total score, 0-100 points, where 0 indicates no evidence of SDM and 100 indicates evidence of SDM at the highest skill level); time spent discussing LCS during visits; and evidence of decision aid use.

    Results  A total of 14 conversations about initiating LCS were identified; 9 patients were women, and 5 patients were men; the mean (SD) patient age was 63.9 (5.1) years; 7 patients had Medicare, and 8 patients were current smokers. Half the conversations were conducted by primary care physicians. The mean total OPTION score for the 14 LCS conversations was 6 on a scale of 0 to 100 (range, 0-17). None of the conversations met the minimum skill criteria for 8 of the 12 SDM behaviors. Physicians universally recommended LCS. Discussion of harms (such as false positives and their sequelae or overdiagnosis) was virtually absent. The mean total visit length of a discussion was 13:07 minutes (range, 3:48-27:09 minutes). The mean time spent discussing LCS was 0:59 minute (range, 0:16-2:19 minutes), or 8% of the total visit time (range, 1%-18%). There was no evidence that decision aids or other patient education materials for LCS were used.

    Conclusions and Relevance  In this small sample of recorded encounters about initiating LCS, the observed quality of SDM was poor and explanation of potential harms of screening was virtually nonexistent. Time spent discussing LCS was minimal, and there was no evidence that decision aids were used. Although these findings are preliminary, they raise concerns that SDM for LCS in practice may be far from what is intended by guidelines.

    Introduction

    In 2013, the US Preventive Services Task Force (USPSTF) recommended lung cancer screening (LCS) using annual low-dose computed tomography (CT) for current and former smokers at high risk for lung cancer.1 More than 6 million individuals in the United States are eligible for LCS, including more than 4 million Medicare beneficiaries.2 However, although LCS can reduce the chances of death from lung cancer, LCS also causes harms. For example, because most lung nodules detected by screening are benign, many individuals who complete LCS then undergo follow-up procedures, some of which are invasive, that do not find cancer.3,4 Screening can also lead to the diagnosis and treatment of cancer that would not have affected the individual during his or her lifetime (overdiagnosis), with attendant physical, psychological, and financial harms.5

    Although experts disagree on how well the existing evidence suggests an overall net benefit of LCS,6,7 consensus has emerged on the importance of shared decision making (SDM). The USPSTF recommends that LCS should not be initiated without SDM that involves a thorough discussion of its benefits and harms. Furthermore, in 2015, the Centers for Medicare & Medicaid Services (CMS) issued requirements for an SDM visit using a decision aid prior to covering LCS.8 However, how (or if) SDM occurs in clinical practice is unknown. We used content analysis to assess SDM for LCS in a sample of existing audio-recorded encounters between patients and physicians from community practice.

    Methods

    We identified conversations about initiating LCS in the Verilogue database. Detailed data collection methods are published elsewhere.9 In brief, the Verilogue database contains more than 135 000 recordings from more than 2150 US health care professionals, mainly in private solo or group practices. The Verilogue analyst electronically searched the database of transcribed outpatient encounters collected between April 1, 2014, and March 1, 2018, to identify encounters that: (1) were between primary care physicians (PCPs) or pulmonologists and patients who were eligible for LCS based on age (ie, 55-80 years of age) and (2) contained key words relevant to LCS: (scan OR screen OR CT) AND (lungs OR chest OR smoke OR low-dose OR lung cancer). Two of us (A.T.B. and T.L.M.) manually reviewed transcripts to identify encounters with discussions about initiating LCS. This study was determined to not be human subjects research by the University of North Carolina Institutional Review Board. Participating patients provided written consent to be recorded, with the knowledge that all protected health information will be redacted from the recordings and transcripts.

    Analyses

    Two of us (T.L.M. and M.M.) independently reviewed and coded transcripts using OPTION (Observing Patient Involvement in Decision Making), a validated scale designed to measure the extent to which clinicians involve patients in decisions within consultations. The scale assesses 12 SDM clinician communication behaviors, such as “explains the pros and cons of options to the patient.”10-12 The authors rated each behavior along the following scale, as specified in the OPTION rater manual11: 0, no attempt to perform the behavior; 1, perfunctory or unclear attempt to perform the behavior; 2, behavior performed at minimum or baseline skill level; 3, behavior performed to a good standard; and 4; behavior performed to a high standard. Coding discrepancies were resolved by group consensus. For each item, we calculated the mean item score for conversations and the proportion of conversations with a rating of 2 (minimum or baseline skill level) or better. We calculated a standard total OPTION score by summing individual item scores for each conversation and scaling to 100 points. Coders also agreed on the presence or absence of references to decision aids or other informational material and measured total visit and LCS conversation times.

    Results

    We identified 5385 conversations involving age-eligible patients occurring between April 1, 2014, and March 1, 2018 (Figure). Of these, 137 met the key word criteria. Manual review of these transcripts yielded 14 conversations about initiation of LCS. Most conversations were excluded because they involved discussion of chest imaging conducted for nonscreening (eg, diagnostic or unclear) indications, previously completed CT scans, or other unrelated discussions that included the key words.

    Patients’ mean (SD) age was 63.9 (5.1) years; 9 (64.3%) were female, 7 (50.0%) had Medicare, and 8 (57.1%) were current smokers (Table 1). The 14 conversations involved 10 unique physicians (5 pulmonologists and 5 PCPs). All physicians were in office-based group or solo private practice.

    Analyses of SDM

    Mean SDM behavior item scores ranged from 0 to 0.79 on the scale of 0 to 4 (Table 2). Two conversations met baseline skill criteria (level 2) for 1 behavior each, 2 met baseline skill criteria for 2 behaviors each, and no conversations met baseline skill criteria for the remaining 8 of 12 communication behaviors, including explaining the pros and cons of LCS. No physician adequately explained false positives or their sequelae (eg, the need for additional imaging or invasive diagnostic procedures). No physician discussed overdiagnosis.

    The mean total OPTION score for the 14 LCS conversations was 6 on the scale of 0 to 100 (range, 0-17). The mean score was 5 of 100 (range, 0-17) for pulmonologists and 7 of 100 (range, 0-15) for primary care physicians. The mean score was 6 of 100 (range, 0-15) for Medicare patients and 6 of 100 (range, 0-17) for patients with other payers. Table 3 shows example conversations along with OPTION item scores. The mean total visit length was 13:07 minutes (range, 3:48-27:09 minutes). The mean time spent discussing LCS was 0:59 minute (range, 0:16-2:19 minutes), or 8% of the total visit time (range, 1%-18%). We found no reference to decision aids or other patient education materials.

    Discussion

    In a small sample of recorded clinical encounters between patients and physicians, we found that physicians’ efforts to engage patients in SDM about initiating LCS were cursory at best. Despite guidelines from organizations including the USPSTF and CMS, no conversations met even basic skill criteria for explaining the pros and cons of LCS. Although the sample is small and these findings are clearly preliminary, they raise concerns that SDM in practice may be far from what is intended by guidelines.

    The fact that the main drivers of harms from LCS (false positives and their sequelae, as well as overdiagnosis) were not adequately explained by physicians is troubling. However, these findings are consistent with other evidence that discussions between patients and physicians regarding preference-sensitive cancer screening decisions are imbalanced with respect to explaining the pros and cons. For example, in a national survey about prostate cancer screening, US men reported that their health care professionals emphasized the pros of screening substantially more than the cons.13 More broadly, our findings are consistent with increasingly robust evidence that patients, members of the public, and clinicians tend to overestimate the benefits and underestimate the harms of medical interventions, including treatments, tests, or screening tests.14,15

    We are unaware of other studies using the OPTION scale to evaluate discussions about the initiation of LCS. However, a systematic review by Couët et al16 identified 29 studies using the OPTION scale and found that clinicians generally performed poorly (mean, 23 of 100) across a variety of other decisions and clinical contexts. The review identified 2 factors associated with higher OPTION scores; 1 factor was duration of the encounter. This finding is not surprising because explaining equipoise, listing options, explaining pros and cons, checking understanding, and then integrating preferences into a shared decision requires time. In our study, physicians spent less than 1 minute, on average, discussing LCS. It seems doubtful that meaningful deliberation about a decision as complex and consequential as initiating yearly CT scanning can occur as an ad hoc addition to a brief outpatient visit.

    A second factor associated with higher OPTION scores in the review by Couët et al16 was “SDM interventions,” which were primarily decision aids and/or clinician training. This finding is consistent with a review of interventions to improve adoption of SDM, which also suggested that interventions directed at both patients and clinicians were the most promising.17 Decision aids delivered before an encounter between the patient and clinician could help address physician time constraints, and several LCS decision aids have been tested.18-20 However, decision aid use in practice is rare.21

    The 2016 CMS coverage decision policy recognized the time and effort needed for LCS SDM by establishing reimbursement criteria for an SDM visit, which was required before covering an initial CT scan for LCS.8 Specifically, CMS requires that an SDM visit involve use of 1 or more decision aids and a documented discussion of the “benefits and harms of screening, follow-up diagnostic testing, overdiagnosis, false-positive rate, and total radiation exposure.” None of the 7 encounters involving Medicare patients in our study met these criteria. Although we do not know whether CT scans were completed or reimbursed by Medicare, these findings raise concerns about whether practicing physicians are actually meeting these requirements.

    Although it is tempting to conclude that SDM for LCS should be conducted at dedicated referral LCS centers, such a paradigm does not fully acknowledge what is known about how and when patients actually make decisions about screening. For example, a study recently found that 50% of patients eligible for screening who received LCS decision support (a video decision aid) in a primary care practice preferred to be screened.18 In contrast, in a recent study of patients attending a tertiary LCS program who received robust decision support (including a decision aid), 95% chose to be screened.22 We suspect that patients referred to LCS programs will presume that the purpose of referral is to complete screening, rather than to decide about screening. We believe that current evidence suggests that true patient-centered solutions will require a robust and flexible primary care–based decision support infrastructure that allows meaningful decision support to be provided when and where the issue of LCS is first raised.

    Limitations

    The major limitation of this study is its small sample from private community practices and the limitations inherent in qualitative studies. Larger studies are needed to fully describe current practice and the challenges associated with SDM for LCS.

    Conclusions

    We believe these preliminary findings should engender a more pressing discussion among clinical leaders, policy makers, and researchers about how to meaningfully involve patients in LCS decisions. Until more is known, we believe that guideline and policy makers should not assume that recommending SDM for cancer screening decisions with a “tenuous balance of benefits and harms,”23(p971) like LCS, will protect patients who would value avoiding screening harms.

    Back to top
    Article Information

    Accepted for Publication: June 15, 2018.

    Corresponding Author: Daniel S. Reuland, MD, MPH, Division of General Medicine and Clinical Epidemiology, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, 101 E Weaver St, Campus Box 7923, Carrboro, NC 27510 (dreuland@med.unc.edu).

    Published Online: August 13, 2018. doi:10.1001/jamainternmed.2018.3054

    Author Contributions: Dr Brenner had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Brenner, Elston Lafata, Reuland.

    Acquisition, analysis, or interpretation of data: Brenner, Malo, Margolis, James, Vu, Reuland.

    Drafting of the manuscript: Brenner, Malo, James, Reuland.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Brenner, Margolis.

    Obtained funding: Brenner, Elston Lafata, Reuland.

    Administrative, technical, or material support: Margolis, James.

    Supervision: Brenner, Reuland.

    Conflict of Interest Disclosures: None reported.

    Funding/Support: This study was primarily supported by pilot grant 550KR151604 from the North Carolina Translational and Clinical Sciences Institute. The Connected Health Applications and Interventions (CHAI) Core, which provided the graphical design features with this article, was supported by grant P30-CA16086 from the National Cancer Institute to the Lineberger Comprehensive Cancer Center.

    Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Additional Contributions: Dmytro Byelmac, BA, Verilogue, assisted with data searches. He received no compensation for his contributions beyond that received in the normal course of his employment.

    References
    1.
    Moyer  VA; US Preventive Services Task Force.  Screening for lung cancer: US Preventive Services Task Force recommendation statement.  Ann Intern Med. 2014;160(5):330-338. doi:10.7326/M13-2771PubMedGoogle ScholarCrossref
    2.
    Ma  J, Ward  EM, Smith  R, Jemal  A.  Annual number of lung cancer deaths potentially avertable by screening in the United States.  Cancer. 2013;119(7):1381-1385. doi:10.1002/cncr.27813PubMedGoogle ScholarCrossref
    3.
    Bach  PB, Mirkin  JN, Oliver  TK,  et al.  Benefits and harms of CT screening for lung cancer: a systematic review.  JAMA. 2012;307(22):2418-2429. doi:10.1001/jama.2012.5521PubMedGoogle ScholarCrossref
    4.
    Harris  RP, Sheridan  SL, Lewis  CL,  et al.  The harms of screening: a proposed taxonomy and application to lung cancer screening.  JAMA Intern Med. 2014;174(2):281-285. doi:10.1001/jamainternmed.2013.12745PubMedGoogle ScholarCrossref
    5.
    Patz  EFJ  Jr, Pinsky  P, Gatsonis  C,  et al; NLST Overdiagnosis Manuscript Writing Team.  Overdiagnosis in low-dose computed tomography screening for lung cancer.  JAMA Intern Med. 2014;174(2):269-274. doi:10.1001/jamainternmed.2013.12738PubMedGoogle ScholarCrossref
    6.
    Wood  DE.  The importance of lung cancer screening with low-dose computed tomography for Medicare beneficiaries.  JAMA Intern Med. 2014;174(12):2016-2018. doi:10.1001/jamainternmed.2014.5623PubMedGoogle ScholarCrossref
    7.
    Woolf  SH, Harris  RP, Campos-Outcalt  D.  Low-dose computed tomography screening for lung cancer: how strong is the evidence?  JAMA Intern Med. 2014;174(12):2019-2022. doi:10.1001/jamainternmed.2014.5626PubMedGoogle ScholarCrossref
    8.
    Centers for Medicare & Medicaid Services. Decision memo for screening for lung cancer with low dose computed tomography (LDCT) (CAG-00439N). https://www.cms.gov/medicare-coverage-database/details/nca-decision-memo.aspx?NCAId=274. Published February 5, 2015. Accessed April 16, 2018.
    9.
    Goff  SL, Mazor  KM, Ting  HH, Kleppel  R, Rothberg  MB.  How cardiologists present the benefits of percutaneous coronary interventions to patients with stable angina: a qualitative analysis.  JAMA Intern Med. 2014;174(10):1614-1621. doi:10.1001/jamainternmed.2014.3328PubMedGoogle ScholarCrossref
    10.
    Elwyn  G, Hutchings  H, Edwards  A,  et al.  The OPTION scale: measuring the extent that clinicians involve patients in decision-making tasks.  Health Expect. 2005;8(1):34-42. doi:10.1111/j.1369-7625.2004.00311.xPubMedGoogle ScholarCrossref
    11.
    Elwyn  G, Edwards  A, Wensing  M, Grol  R. OPTION rater manual. http://www.optioninstrument.org/uploads/2/4/0/4/24040341/option_12_rater_manual.pdf. Accessed April 14, 2018.
    12.
    Rapport  F, Wainwright  P, Elwyn  G.  “Of the edgelands”: broadening the scope of qualitative methodology.  Med Humanit. 2005;31(1):37-42. doi:10.1136/jmh.2004.000190PubMedGoogle ScholarCrossref
    13.
    Hoffman  RM, Couper  MP, Zikmund-Fisher  BJ,  et al.  Prostate cancer screening decisions: results from the National Survey of Medical Decisions (DECISIONS study).  Arch Intern Med. 2009;169(17):1611-1618. doi:10.1001/archinternmed.2009.262PubMedGoogle ScholarCrossref
    14.
    Hoffmann  TC, Del Mar  C.  Patients’ expectations of the benefits and harms of treatments, screening, and tests: a systematic review.  JAMA Intern Med. 2015;175(2):274-286. doi:10.1001/jamainternmed.2014.6016PubMedGoogle ScholarCrossref
    15.
    Hoffmann  TC, Del Mar  C.  Clinicians’ expectations of the benefits and harms of treatments, screening, and tests: a systematic review.  JAMA Intern Med. 2017;177(3):407-419. doi:10.1001/jamainternmed.2016.8254PubMedGoogle ScholarCrossref
    16.
    Couët  N, Desroches  S, Robitaille  H,  et al.  Assessments of the extent to which health-care providers involve patients in decision making: a systematic review of studies using the OPTION instrument.  Health Expect. 2015;18(4):542-561. doi:10.1111/hex.12054PubMedGoogle ScholarCrossref
    17.
    Légaré  F, Stacey  D, Turcotte  S,  et al.  Interventions for improving the adoption of shared decision making by healthcare professionals.  Cochrane Database Syst Rev. 2014;(9):CD006732.PubMedGoogle Scholar
    18.
    Reuland  DS, Cubillos  L, Brenner  AT, Harris  RP, Minish  B, Pignone  MP.  A pre-post study testing a lung cancer screening decision aid in primary care.  BMC Med Inform Decis Mak. 2018;18(1):5. doi:10.1186/s12911-018-0582-1PubMedGoogle ScholarCrossref
    19.
    Volk  RJ, Linder  SK, Leal  VB,  et al.  Feasibility of a patient decision aid about lung cancer screening with low-dose computed tomography.  Prev Med. 2014;62:60-63. doi:10.1016/j.ypmed.2014.02.006PubMedGoogle ScholarCrossref
    20.
    Lau  YK, Caverly  TJ, Cao  P,  et al.  Evaluation of a personalized, web-based decision aid for lung cancer screening.  Am J Prev Med. 2015;49(6):e125-e129. doi:10.1016/j.amepre.2015.07.027PubMedGoogle ScholarCrossref
    21.
    Jimbo  M, Rana  GK, Hawley  S,  et al.  What is lacking in current decision aids on cancer screening?  CA Cancer J Clin. 2013;63(3):193-214. doi:10.3322/caac.21180PubMedGoogle ScholarCrossref
    22.
    Mazzone  PJ, Tenenbaum  A, Seeley  M,  et al.  Impact of a lung cancer screening counseling and shared decision-making visit.  Chest. 2017;151(3):572-578. doi:10.1016/j.chest.2016.10.027PubMedGoogle ScholarCrossref
    23.
    Mazzone  PJ, Silvestri  GA, Patel  S,  et al.  Screening for lung cancer: CHEST guideline and expert panel report.  Chest. 2018;153(4):954-985. doi:10.1016/j.chest.2018.01.016PubMedGoogle ScholarCrossref
    ×