Applying User-Centered Design to Develop Practical Strategies that Address Overuse in Primary Care.

INTRODUCTION: Engaging patients and frontline clinicians in re-designing clinical care is essential for improving care delivery in a complex clinical environment. This study sought to assess an innovative user-centered design approach to improving clinical care quality, focusing on the use cases of de-intensifying non-beneficial care within the following areas: (1) de-intensifying diabetes treatment in high-risk patients; (2) stopping screening for carotid artery stenosis in asymptomatic patients; and (3) stopping colorectal cancer screening in average-risk, older adults. METHODS: The user-centered design approach, consisting of patient and patient-clinician charrettes (defined as intensive workshops where key stakeholders collaborate to develop creative solutions to a specific problem) and participant surveys, has been described previously. Following the charrettes, we used inductive coding to identify and categorize themes emerging from the de-intensification ideas prioritized by participants as well as facilitator notes and audio recordings from the charrettes. RESULTS: Thirty-five patients participated in the patient design charrettes, generating 134 unique de-intensification ideas and prioritizing 32, which were then distilled into six patient-generated principles of de-intensification by the study team. These principles provided a starting point for a subsequent patient-clinician charrette. In this follow-up charrette, 9 patients who had participated in an earlier patient design charrette collaborated with 7 clinicians to generate 63 potential de-intensification solutions. Six of these potential solutions were developed into multi-faceted, fully operationalized de-intensification strategies. DISCUSSION: The de-intensification strategies that patients and clinicians prioritized and operationalized during the co-design charrette process were detailed and multi-faceted. Each component of a strategy had a rationale based on feasibility, practical considerations, and ways of overcoming barriers. The charrette-based process may be a useful way to engage clinicians and patients in developing the complex and multi-faceted strategies needed to improve care delivery.

Long-term follow-up of smokers following lung and colorectal cancer diagnosis.

BACKGROUND: Continued smoking after a cancer diagnosis limits the effectiveness of treatment, increases the risk of cancer recurrence or secondary malignancies, and is associated with poorer quality of life and survival. A cancer diagnosis may provide a meaningful timepoint for quitting, but the prevalence and characteristics of continued smoking through survivorship are poorly understood. METHODS: In the multi-regional Cancer Care Outcomes Research and Surveillance (CanCORS) cohort, we examined smoking rates and factors associated with continued smoking at long-term follow-up among lung and colorectal cancer patients. This paper builds upon previous CanCORS participant data addressing quit rates and associated characteristics at baseline and 5 months post-diagnosis. RESULTS: At long-term follow-up (median 7.3 years post-diagnosis [IQR = 5.9-8.7]), 16.7% of lung cancer and 11.6% of colorectal cancer survivors continued to smoke combustible cigarettes. Factors independently associated with continued smoking at long-term follow-up included being male, younger, not married or partnered, having Medicare, Medicaid/other public or no insurance, more depression symptoms, smoking more cigarettes per day, and having a history of lung disease (p < .05). Continued smoking did not vary by lung vs. colorectal cancer diagnosis. CONCLUSION: Of active smokers at the time of diagnosis, an important minority of lung and colorectal cancer survivors continued to smoke well into survivorship. Understanding characteristics associated with continued smoking after a cancer diagnosis may help inform the development of tobacco treatment programs for cancer patients and survivors. IMPLICATIONS FOR SURVIVORS: While addressing smoking cessation at the time of diagnosis is critical to ensure better long-term treatment outcomes and quality of life, it is essential to continue smoking cessation discussions and efforts throughout care and survivorship.

Perceptions of somatic and affective symptoms and psychosocial care utilization in younger and older survivors of lung cancer.

OBJECTIVE: Rates of depression identification in oncology settings and referral to psychosocial services remain low. Patients with lung cancer face an elevated risk of depression relative to patients with other cancers. This study explored perceptions of somatic and affective symptoms and psychosocial care utilization among younger and older lung cancer survivors. METHODS: We conducted in-depth interviews with 20 adults at two academic medical centers in Boston, MA, who had received a lung cancer diagnosis in the past 24 months. A semi-structured interview guide was used to assess experiences with, and perceptions of, depression symptoms and psychosocial services. Interviews were audio-recorded, transcribed, and coded to identify themes. We also explored differences between younger (<65years; N=9) and older (>65years; N=11) patients. RESULTS: Participants commonly described somatic symptoms (i.e., changes in appetite, sleep, or energy levels) and affective symptoms (i.e., worry, fear, sadness) as side effects of cancer treatment. Older participants more commonly contextualized these symptoms with information about how they impacted daily life. Both younger and older participants faced barriers to accessing psychosocial services, with older adults more commonly referencing stigma of service referral and utilization. DISCUSSION: Patients with lung cancer associated both somatic and affective symptoms with their cancer and its treatment, with age differences in how symptoms were described and how psychosocial referrals may be perceived. More systematic integration of psychosocial care into cancer care may help to increase the identification of depression in lung cancer and reduce barriers to psychosocial service utilization.

Planning and Reporting Effective Web-Based RAND/UCLA Appropriateness Method Panels: Literature Review and Preliminary Recommendations.

BACKGROUND: The RAND/UCLA Appropriateness Method (RAM), a variant of the Delphi Method, was developed to synthesize existing evidence and elicit the clinical judgement of medical experts on the appropriate treatment of specific clinical presentations. Technological advances now allow researchers to conduct expert panels on the internet, offering a cost-effective and convenient alternative to the traditional RAM. For example, the Department of Veterans Affairs recently used a web-based RAM to validate clinical recommendations for de-intensifying routine primary care services. A substantial literature describes and tests various aspects of the traditional RAM in health research; yet we know comparatively less about how researchers implement web-based expert panels. OBJECTIVE: The objectives of this study are twofold: (1) to understand how the web-based RAM process is currently used and reported in health research and (2) to provide preliminary reporting guidance for researchers to improve the transparency and reproducibility of reporting practices. METHODS: The PubMed database was searched to identify studies published between 2009 and 2019 that used a web-based RAM to measure the appropriateness of medical care. Methodological data from each article were abstracted. The following categories were assessed: composition and characteristics of the web-based expert panels, characteristics of panel procedures, results, and panel satisfaction and engagement. RESULTS: Of the 12 studies meeting the eligibility criteria and reviewed, only 42% (5/12) implemented the full RAM process with the remaining studies opting for a partial approach. Among those studies reporting, the median number of participants at first rating was 42. While 92% (11/12) of studies involved clinicians, 50% (6/12) involved multiple stakeholder types. Our review revealed that the studies failed to report on critical aspects of the RAM process. For example, no studies reported response rates with the denominator of previous rounds, 42% (5/12) did not provide panelists with feedback between rating periods, 50% (6/12) either did not have or did not report on the panel discussion period, and 25% (3/12) did not report on quality measures to assess aspects of the panel process (eg, satisfaction with the process). CONCLUSIONS: Conducting web-based RAM panels will continue to be an appealing option for researchers seeking a safe, efficient, and democratic process of expert agreement. Our literature review uncovered inconsistent reporting frameworks and insufficient detail to evaluate study outcomes. We provide preliminary recommendations for reporting that are both timely and important for producing replicable, high-quality findings. The need for reporting standards is especially critical given that more people may prefer to participate in web-based rather than in-person panels due to the ongoing COVID-19 pandemic.

Clinician Perceptions on Using Decision Tools to Support Prediction-Based Shared Decision Making for Lung Cancer Screening.

Background: Considering a patient's full risk factor profile can promote personalized shared decision making (SDM). One way to accomplish this is through encounter tools that incorporate prediction models, but little is known about clinicians' perceptions of the feasibility of using these tools in practice. We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS). Design: We conducted a qualitative study based on field notes from academic detailing visits during a multisite quality improvement program. The detailer engaged one-on-one with 96 primary care clinicians across multiple Veterans Affairs sites (7 medical centers and 6 outlying clinics) to get feedback on 1) the rationale for prediction-based LCS and 2) how to use the DecisionPrecision (DP) encounter tool with eligible patients to personalize LCS discussions. Results: Thematic content analysis from detailing visit data identified 6 categories of clinician willingness to use the DP tool to personalize SDM for LCS (adoption potential), varying from "Enthusiastic Potential Adopter" (n = 18) to "Definite Non-Adopter" (n = 16). Many clinicians (n = 52) articulated how they found the concept of prediction-based SDM highly appealing. However, to varying degrees, nearly all clinicians identified challenges to incorporating such an approach in routine practice. Limitations: The results are based on the clinician's initial reactions rather than longitudinal experience. Conclusions: While many primary care clinicians saw real value in using prediction to personalize LCS decisions, more support is needed to overcome barriers to using encounter tools in practice. Based on these findings, we propose several strategies that may facilitate the adoption of prediction-based SDM in contexts such as LCS. Highlights: Encounter tools that incorporate prediction models promote personalized shared decision making (SDM), but little is known about clinicians' perceptions of the feasibility of using these tools in practice.We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS).While many clinicians found the concept of prediction-based SDM highly appealing, nearly all clinicians identified challenges to incorporating such an approach in routine practice.We propose several strategies to overcome adoption barriers and facilitate the use of prediction-based SDM in contexts such as LCS.

Refining a Framework to Enhance Communication in the Emergency Department During the Diagnostic Process: An eDelphi Approach.

BACKGROUND: Emergency departments (EDs) are susceptible to diagnostic error. Suboptimal communication between the patient and the interdisciplinary care team increases risk to diagnostic safety. The role of communication remains underrepresented in existing diagnostic decision-making conceptual models. METHODS: The authors used eDelphi methodology, whereby data are collected electronically, to achieve consensus among an expert panel of 18 clinicians, patients, family members, and other participants on a refined ED-based diagnostic decision-making framework that integrates several potential opportunities for communication to enhance diagnostic quality. This study examined the entire diagnostic process in the ED, from prehospital to discharge or transfer to inpatient care, and identified where communication breakdowns could occur. After four iterative rounds of the eDelphi process, including a final validation round by all participants, the project's a priori consensus threshold of 80% agreement was reached. RESULTS: The authors developed a final framework that positions communication more prominently in the diagnostic process in the ED and enhances the original National Academies of Sciences, Engineering, and Medicine (NASEM) and ED-adapted NASEM frameworks. Specific points in the ED journey were identified where more attention to communication might be helpful. Two specific types of communication-information exchange and shared understanding-were identified as high priority for optimal outcomes. Ideas for communication-focused interventions to prevent diagnostic error in the ED fell into three categories: patient-facing, clinician-facing, and system-facing interventions. CONCLUSION: This project's refinement of the NASEM framework adapted to the ED can be used to develop communications-focused interventions to reduce diagnostic error in this highly complex and error-prone setting.

Implementation of a Web-Based Tool for Shared Decision-making in Lung Cancer Screening: Mixed Methods Quality Improvement Evaluation.

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.

Corrigendum to "Examining the effects of stress and psychological distress on smoking abstinence in cancer patients" [Prev. Med. Rep. 23 (2021) 101402].

[This corrects the article DOI: 10.1016/j.pmedr.2021.101402.].

The Need for Brevity During Shared Decision Making (SDM) for Cancer Screening: Veterans' Perspectives on an "Everyday SDM" Compromise.

Introduction. Detailed or "full" shared decision making (SDM) about cancer screening is difficult in the primary care setting. Time spent discussing cancer screening is time not spent on other important issues. Given time constraints, brief SDM that is incomplete but addresses key elements may be feasible and acceptable. However, little is known about how patients feel about abbreviated SDM. This study assessed patient perspectives on a compromise solution ("everyday SDM"): 1) primary care provided makes a tailored recommendation, 2) briefly presents qualitative information on key tradeoffs, and 3) conveys full support for decisional autonomy and desires for more information. Methods. We recruited a stratified random sample of Veterans from an academic Veterans Affairs medical center who were eligible for lung cancer screening, oversampling women and minority patients, to attend a 6-hour deliberative focus group. Experts informed participants about cancer screening, factors that influence screening benefits, and the role of patient preferences. Then, facilitator-led small groups elicited patient questions and informed opinions about the everyday SDM proposal, its acceptability, and their recommendations for improvement. Results. Thirty-six Veterans with a heavy smoking history participated (50% male, 83% white). There was a strong consensus that everyday SDM was acceptable if patients were the final deciders and could get more information on request. Participants broadly recommended that clinicians only mention downsides directly related to screening and avoid discussion of potential downstream harms (such as biopsies). Discussion. Although further testing in more diverse populations and different conditions is needed, these patients found the everyday SDM approach to be acceptable for routine lung cancer screening discussions, despite its use of an explicit recommendation and presentation of only qualitative information.

Examining the effects of stress and psychological distress on smoking abstinence in cancer patients.

INTRODUCTION: Cancer patients who smoke report more stress and psychological distress than patients who do not smoke. It is unclear how these emotional symptoms may modify smoking behavior in cancer patients. We examined the influence of a smoking cessation intervention for cancer patients on stress and distress, and the effects of these symptoms on smoking abstinence. METHODS: Mixed-methods secondary analysis of data from the Smokefree Support Study, a two-site randomized controlled trial examining the efficacy of Intensive (IT; n = 153) vs. Standard Treatment (ST; n = 150) for smoking cessation in newly diagnosed cancer patients. Stress coping, perceived stress, distress, and anxiety were self-reported at baseline, 3, and 6 months. Abstinence was biochemically-confirmed at 6 months. A subset of patients (n = 72) completed qualitative exit-interviews. RESULTS: Patients were on average, 58 years old, 56% female, and smoked a median of 10 cigarettes/day. There were no significant treatment group × time interactions or main effects of treatment group on stress or distress measures (p's > 0.05), however there were significant main effects of time suggesting symptom improvements on each measure in both study groups (p's < 0.05). In adjusted logistic regression models, lower levels anxiety at 3 months predicted confirmed smoking abstinence at 6 months (p = .03). Qualitatively, at 6 months, patients reported their stress and smoking were connected and that the cessation counseling was helpful. CONCLUSIONS: Cancer patients enrolled in a smoking cessation trial report decreases in stress, distress and anxiety over time, and anxiety symptoms may impact smoking cessation success at follow-up resulting in an important intervention target.

Using Democratic Deliberation to Engage Veterans in Complex Policy Making for the Veterans Health Administration.

A democratic deliberation panel of veterans providing insight into veteran perspectives on resource allocation and the Veterans Choice Act showed the importance and feasibility of engaging veterans in the policy-making process.

Identifying Recommendations for Stopping or Scaling Back Unnecessary Routine Services in Primary Care.

Importance: Much of health care involves established, routine use of medical services for chronic conditions or prevention. Stopping these services when the evidence changes or if the benefits no longer outweigh the risks is essential. Yet, most guidelines focus on escalating care and provide few explicit recommendations to stop or scale back (ie, deintensify) treatment and testing. Objective: To develop a systematic, transparent, and reproducible approach for identifying, specifying, and validating deintensification recommendations associated with routine adult primary care. Design, Setting, and Participants: A focused review of existing guidelines and recommendations was completed to identify and prioritize potential deintensification indications. Then, 2 modified virtual Delphi expert panels examined the synthesized evidence, suggested ways that the candidate recommendations could be improved, and assessed the validity of the recommendations using the RAND/UCLA Appropriateness Method. Twenty-five physicians from Veterans Affairs and US academic institutions with knowledge in relevant clinical areas (eg, geriatrics, primary care, women's health, cardiology, and endocrinology) served as panel members. Main Outcomes and Measures: Validity of the recommendations, defined as high-quality evidence that deintensification is likely to improve patient outcomes, evidence that intense testing and/or treatment could cause harm in some patients, absence of evidence on the benefit of continued or repeated intense treatment or testing, and evidence that deintensification is consistent with high-quality care. Results: A total of 409 individual recommendations were identified representing 178 unique opportunities to stop or scale back routine services (eg, stopping population-based screening for vitamin D deficiency and decreasing concurrent use of opioids and benzodiazepines). Thirty-seven recommendations were prioritized and forwarded to the expert panels. Panelists reviewed the evidence and suggested modifications, resulting in 44 recommendations being rated. Overall, 37 recommendations (84%) were considered to be valid, as assessed by the RAND/UCLA Appropriateness Method. Conclusions and Relevance: In this study, a total of 178 unique opportunities to deintensify routine primary care services were identified, and 37 of these were validated as high-priority deintensification recommendations. To date, this is the first study to develop a model for identifying, specifying, and validating deintensification recommendations that can be implemented and tracked in clinical practice.

Developing Strategies to Reduce Unnecessary Services in Primary Care: Protocol for User-Centered Design Charrettes.

BACKGROUND: Overtreatment and overtesting expose patients to unnecessary, wasteful, and potentially harmful care. Reducing overtreatment or overtesting that has become ingrained in current clinical practices and is being delivered on a routine basis will require solutions that incorporate a deep understanding of multiple perspectives, particularly those on the front lines of clinical care: patients and their clinicians. Design approaches are a promising and innovative way to incorporate stakeholder needs, desires, and challenges to develop solutions to complex problems. OBJECTIVE: This study aimed (1) to engage patients in a design process to develop high-level deintensification strategies for primary care (ie, strategies for scaling back or stopping routine medical services that more recent evidence reveals are not beneficial) and (2) to engage both patients and primary care providers in further co-design to develop and refine the broad deintensification strategies identified in phase 1. METHODS: We engaged stakeholders in design charrettes-intensive workshops in which key stakeholders are brought together to develop creative solutions to a specific problem-focused on deintensification of routine overuse in primary care. We conducted the study in 2 phases: a 6.5-hour design charrette with 2 different groups of patients (phase 1) and a subsequent 4-hour charrette with clinicians and a subgroup of phase 1 patients (phase 2). Both phases included surveys and educational presentations related to deintensification. Phase 1 involved several design activities (mind mapping, business origami, and empathy mapping) to help patients gain a deeper understanding of the individuals involved in deintensification. Following that, we asked participants to review hypothetical scenarios where patients, clinicians, or the broader health system context posed a barrier to deintensification and then to brainstorm solutions. The deintensification themes identified in phase 1 were used to guide phase 2. This second phase primarily involved 1 design activity (WhoDo). In this activity, patients and clinicians worked together to develop concrete actions that specific stakeholders could take to support deintensification efforts. This activity included identifying barriers to the actions and approaches to overcoming those barriers. RESULTS: A total of 35 patients participated in phase 1, and 9 patients and 7 clinicians participated in phase 2. The analysis of the deintensification strategies and survey data is currently underway. The results are expected to be submitted for publication in early 2020. CONCLUSIONS: Health care interventions are frequently developed without input from the people who are most affected. The exclusion of these stakeholders in the design process often influences and limits the impact of the intervention. This study employed design charrettes, guided by a flexible user-centered design model, to bring clinicians and patients with differing backgrounds and with different expectations together to cocreate real-world solutions to the complex issue of deintensifying medical services. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/15618.