Primary care clinicians' opinions before and after implementation of cancer screening and prevention clinical decision support in a clinic cluster-randomized control trial: a survey research study.

BACKGROUND: Electronic health record (EHR)-linked clinical decision support (CDS) may impact primary care clinicians' (PCCs') clinical care opinions. As part of a clinic cluster-randomized control trial (RCT) testing a cancer prevention and screening CDS system with patient and PCC printouts (with or without shared decision-making tools [SDMT]) for patients due for breast, cervical, colorectal, and lung cancer screening and/or human papillomavirus (HPV) vaccination compared to usual care (UC), we surveyed PCCs at study clinics pre- and post-CDS implementation. Our primary aim was to learn if PCCs' opinions changed over time within study arms. Secondary aims including examining whether PCCs' opinions in study arms differed both pre- and post-implementation, and gauging PCCs' opinions on the CDS in the two intervention arms. METHODS: This study was conducted within a healthcare system serving an upper Midwestern population. We administered pre-implementation (11/2/2017-1/24/2018) and post-implementation (2/2/2020-4/9/2020) cross-sectional electronic surveys to PCCs practicing within a RCT arm: UC; CDS; or CDS + SDMT. Bivariate analyses compared responses between study arms at both time periods and longitudinally within study arms. RESULTS: Pre-implementation (53%, n = 166) and post-implementation (57%, n = 172) response rates were similar. No significant differences in PCC responses were seen between study arms on cancer prevention and screening questions pre-implementation, with few significant differences found between study arms post-implementation. However, significantly fewer intervention arm clinic PCCs reported being very comfortable with discussing breast cancer screening options with patients compared to UC post-implementation, as well as compared to the same intervention arms pre-implementation. Other significant differences were noted within arms longitudinally. For intervention arms, these differences related to CDS areas like EHR alerts, risk calculators, and ordering screening. Most intervention arm PCCs noted the CDS provided overdue screening alerts to which they were unaware. Few PCCs reported using the CDS, but most would recommend it to colleagues, expressed high CDS satisfaction rates, and thought patients liked the CDS's information and utility. CONCLUSIONS: While appreciated by PCCs with high satisfaction rates, the CDS may lower PCCs' confidence regarding discussing patients' breast cancer screening options and may be used irregularly. Future research will evaluate the impact of the CDS on cancer prevention and screening rates. TRIAL REGISTRATION: clinicaltrials.gov , NCT02986230, December 6, 2016.

Assessing the implementation of a clinical decision support tool in primary care for diabetes prevention: a qualitative interview study using the Consolidated Framework for Implementation Science.

BACKGROUND: In this paper we describe the use of the Consolidated Framework for Implementation Research (CFIR) to study implementation of a web-based, point-of-care, EHR-linked clinical decision support (CDS) tool designed to identify and provide care recommendations for adults with prediabetes (Pre-D CDS). METHODS: As part of a large NIH-funded clinic-randomized trial, we identified a convenience sample of interview participants from 22 primary care clinics in Minnesota, North Dakota, and Wisconsin that were randomly allocated to receive or not receive a web-based EHR-integrated prediabetes CDS intervention. Participants included 11 clinicians, 6 rooming staff, and 7 nurse or clinic managers recruited by study staff to participate in telephone interviews conducted by an expert in qualitative methods. Interviews were recorded and transcribed, and data analysis was conducted using a constructivist version of grounded theory. RESULTS: Implementing a prediabetes CDS tool into primary care clinics was useful and well received. The intervention was integrated with clinic workflows, supported primary care clinicians in clearly communicating prediabetes risk and management options with patients, and in identifying actionable care opportunities. The main barriers to CDS use were time and competing priorities. Finally, while the implementation process worked well, opportunities remain in engaging the care team more broadly in CDS use. CONCLUSIONS: The use of CDS tools for engaging patients and providers in care improvement opportunities for prediabetes is a promising and potentially effective strategy in primary care settings. A workflow that incorporates the whole care team in the use of such tools may optimize the implementation of CDS tools like these in primary care settings. Trial registration Name of the registry: Clinicaltrial.gov. TRIAL REGISTRATION NUMBER: NCT02759055. Date of registration: 05/03/2016. URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT02759055 Prospectively registered.

Clinician perceptions of a clinical decision support system to reduce cardiovascular risk among prediabetes patients in a predominantly rural healthcare system.

BACKGROUND: The early detection and management of uncontrolled cardiovascular risk factors among prediabetes patients can prevent cardiovascular disease (CVD). Prediabetes increases the risk of CVD, which is a leading cause of death in the United States. CVD clinical decision support (CDS) in primary care settings has the potential to reduce cardiovascular risk in patients with prediabetes while potentially saving clinicians time. The objective of this study is to understand primary care clinician (PCC) perceptions of a CDS system designed to reduce CVD risk in adults with prediabetes. METHODS: We administered pre-CDS implementation (6/30/2016 to 8/25/2016) (n = 183, 61% response rate) and post-CDS implementation (6/12/2019 to 8/7/2019) (n = 131, 44.5% response rate) independent cross-sectional electronic surveys to PCCs at 36 randomized primary care clinics participating in a federally funded study of a CVD risk reduction CDS tool. Surveys assessed PCC demographics, experiences in delivering prediabetes care, perceptions of CDS impact on shared decision making, perception of CDS impact on control of major CVD risk factors, and overall perceptions of the CDS tool when managing cardiovascular risk. RESULTS: We found few significant differences when comparing pre- and post-implementation responses across CDS intervention and usual care (UC) clinics. A majority of PCCs felt well-prepared to discuss CVD risk factor control with patients both pre- and post-implementation. About 73% of PCCs at CDS intervention clinics agreed that the CDS helped improve risk control, 68% reported the CDS added value to patient clinic visits, and 72% reported they would recommend use of this CDS system to colleagues. However, most PCCs disagreed that the CDS saves time talking about preventing diabetes or CVD, and most PCCs also did not find the clinical domains useful, nor did PCCs believe that the clinical domains were useful in getting patients to take action. Finally, only about 38% reported they were satisfied with the CDS. CONCLUSIONS: These results improve our understanding of CDS user experience and can be used to guide iterative improvement of the CDS. While most PCCs agreed the CDS improves CVD and diabetes risk factor control, they were generally not satisfied with the CDS. Moreover, only 40-50% agreed that specific suggestions on clinical domains helped patients to take action. In spite of this, an overwhelming majority reported they would recommend the CDS to colleagues, pointing for the need to improve upon the current CDS. TRIAL REGISTRATION: NCT02759055 03/05/2016.

The impact of personalized clinical decision support on primary care patients' views of cancer prevention and screening: a cross-sectional survey.

BACKGROUND: Few studies have assessed the impact of clinical decision support (CDS), with or without shared decision-making tools (SDMTs), on patients' perceptions of cancer screening or prevention in primary care settings. This cross-sectional survey was conducted to understand primary care patient's perceptions on cancer screening or prevention. METHODS: We mailed surveys (10/2018-1/2019) to 749 patients aged 18 to 75 years within 15 days after an index clinical encounter at 36 primary care clinics participating in a clinic-randomized control trial of a CDS system for cancer prevention. All patients were overdue for cancer screening or human papillomavirus vaccination. The survey compared respondents' answers by study arm: usual care; CDS; or CDS + SDMT. RESULTS: Of 387 respondents (52% response rate), 73% reported having enough time to discuss cancer prevention options with their primary care provider (PCP), 64% reported their PCP explained the benefits of the cancer screening choice very well, and 32% of obese patients reported discussing weight management, with two-thirds reporting selecting a weight management intervention. Usual care respondents were significantly more likely to decide on colorectal cancer screening than CDS respondents (p < 0.01), and on tobacco cessation than CDS + SDMT respondents (p = 0.02) and both CDS and CDS + SDMT respondents (p < 0.001). CONCLUSIONS: Most patients reported discussing cancer prevention needs with PCPs, with few significant differences between the three study arms in patient-reported cancer prevention care. Upcoming research will assess differences in screening and vaccination rates between study arms during the post-intervention follow-up period. TRIAL REGISTRATION: clinicaltrials.gov , NCT02986230 , December 6, 2016.

Pre-implementation adaptation of primary care cancer prevention clinical decision support in a predominantly rural healthcare system.

BACKGROUND: Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system's goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. METHODS: In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. RESULTS: Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. CONCLUSIONS: Pre-implementation changes to CDS may help meet healthcare systems' evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. TRIAL REGISTRATION: NCT02986230.

Understanding primary care providers' perceptions of cancer prevention and screening in a predominantly rural healthcare system in the upper Midwest.

BACKGROUND: Cancer is the leading cause of death in the United States, with the burden expected to rise in the coming decades, increasing the need for effective cancer prevention and screening options. The United States Preventive Services Task Force has suggested that a shared decision-making process be used when clinicians and patients discuss cancer screening. The electronic medical record (EMR) often provides only reminders or alerts to primary care providers (PCPs) when screenings are due, a strategy with limited efficacy. METHODS: We administered a cross-sectional electronic survey to PCPs (n = 165, 53% response rate) at 36 Essentia Health primary care clinics participating in a large, National Cancer Institute-funded study on a cancer prevention clinical decision support (CDS) tool. The survey assessed PCP demographics, perceptions of the EMR's ability to help assess and manage patients' cancer risk, and experience and comfort level discussing cancer screening and prevention with patients. RESULTS: In these predominantly rural clinics, only 49% of PCPs thought the EMR was well integrated to help assess and manage cancer risk. Both advanced care practitioners and physicians agreed that cancer screening and informed discussion of cancer risks are important; however, only 53% reported their patients gave cancer screening a high priority relative to other health issues. CONCLUSIONS: The impact of EMR-linked CDS delivered to both patients and PCPs may improve cancer screening, but only if it is easy to use and saves PCPs time.

Barriers and facilitators to implementing cancer prevention clinical decision support in primary care: a qualitative study.

BACKGROUND: In the United States, primary care providers (PCPs) routinely balance acute, chronic, and preventive patient care delivery, including cancer prevention and screening, in time-limited visits. Clinical decision support (CDS) may help PCPs prioritize cancer prevention and screening with other patient needs. In a three-arm, pragmatic, clinic-randomized control trial, we are studying cancer prevention CDS in a large, upper Midwestern healthcare system. The web-based, electronic health record (EHR)-linked CDS integrates evidence-based primary and secondary cancer prevention and screening recommendations into an existing cardiovascular risk management CDS system. Our objective with this study was to identify adoption barriers and facilitators before implementation in primary care. METHODS: We conducted semi-structured interviews guided by the Consolidated Framework for Implementation Research (CFIR) with 28 key informants employed by the healthcare organization in either leadership roles or the direct provision of clinical care. Transcribed interviews were analyzed using qualitative content analysis. RESULTS: EHR, CDS workflow, CDS users (providers and patients), training, and organizational barriers and facilitators were identified related to Intervention Characteristics, Outer Setting, Inner Setting, and Characteristics of Individuals CFIR domains. CONCLUSION: Identifying and addressing key informant-identified barriers and facilitators before implementing cancer prevention CDS in primary care may support a successful implementation and sustained use. The CFIR is a useful framework for understanding pre-implementation barriers and facilitators. Based on our findings, the research team developed and instituted specialized training, pilot testing, implementation plans, and post-implementation efforts to maximize identified facilitators and address barriers. TRIAL REGISTRATION: clinicaltrials.gov , NCT02986230 , December 6, 2016.

Understanding Primary Care Provider Attitudes and Behaviors Regarding Cardiovascular Disease Risk and Diabetes Prevention in the Northern Midwest.

IN BRIEF We sought to fill critical gaps in understanding primary care providers' (PCPs') beliefs regarding diabetes prevention and cardiovascular disease risk in the prediabetes population, including through comparison of attitudes between rural and non-rural PCPs. We used data from a 2016 cross-sectional survey sent to 299 PCPs practicing in 36 primary clinics that are part of a randomized control trial in a predominately rural northern Midwestern integrated health care system. Results showed a few significant, but clinically marginal, differences between rural and non-rural PCPs. Generally, PCPs agreed with the importance of screening for prediabetes and thoroughly and clearly discussing CV risk with high-risk patients.

The potential impact of clinical decision support on nonwaivered primary care clinicians' prescribing of buprenorphine.

Elimination of the X-waiver increased potential buprenorphine prescribers 13-fold, but growth in prescribing will likely be much lower. We explored self-assessments of nonwaivered primary care clinicians (PCCs) for factors affecting their likelihood to prescribe buprenorphine were the X-waiver eliminated (since realized January 2023) and the potential impacts of a clinical decision-support (CDS) tool for opioid use disorder (OUD). Cross-sectional survey data were obtained between January 2021 and March 2022 from 305 nonwaivered PCCs at 3 health systems. Factors explored were patient requests for buprenorphine, PCC access to an OUD-CDS, and PCC confidence and abilities for 5 OUD-care activities. Relationships were described using descriptive statistics and odds ratios. Only 26% of PCCs were more likely to prescribe buprenorphine upon patient request, whereas 63% were more likely to prescribe with the OUD-CDS. PCC confidence and abilities for some OUD-care activities were associated with increased prescribing likelihood from patient requests, but none were associated with the OUD-CDS. The OUD-CDS may increase buprenorphine prescribing for PCCs less likely to prescribe upon patient request. Future research is needed to develop interventions that increase PCC buprenorphine prescribing. Clinical trial registration: ClinicalTrials.gov. Identifier: NCT04198428. Clinical trial name: Clinical Decision Support for Opioid Use Disorders in Medical Settings (Compute 2.0).

Adapting a clinical decision support system to improve identification of pediatric hypertension in a rural health system: Design of a pragmatic trial.

BACKGROUND: Identifying hypertension (HTN) early is crucial in preventing and lowering the long-term risk of heart disease, yet HTN in children often goes undiagnosed. An electronic health record linked, web-based clinical decision support (CDS) called PedsBP can help address this care gap and has been previously shown to increase recognition of HTN by primary care clinicians. OBJECTIVES: To adapt the PedsBP tool for use in a mostly rural health system and then to evaluate the effectiveness of PedsBP for repeat of hypertensive level blood pressure (BP) measurements and HTN recognition among youth 6-17 years of age in primary care settings, comparing low-intensity and high-intensity implementation approaches. METHODS AND DESIGN: PedsBP was evaluated through a pragmatic, clinic-randomized trial. The tool was piloted in 2 primary care clinics and modified prior to the full trial. Forty community-based, primary care clinics (or clusters of clinics) were randomly allocated in a 1:1:1 ratio to usual care, low-intensity implementation (CDS only), or high-intensity implementation (CDS plus in-person training, monthly use reports, and ongoing communication between study staff and clinics). Accrual of eligible patients started on August 1, 2022 and will continue for 18 months. Primary outcomes include repeating hypertensive level BP measurements at office visits and clinical recognition of HTN. Secondary outcomes include lifestyle counseling, dietician referral, and BP at follow-up. CONCLUSION: This report focuses on the design and feasibility of adapting and implementing PedsBP in a rural primary care setting. The trial and analysis are ongoing with main results expected in mid-2024.

Design of a pragmatic clinical trial to improve screening and treatment for opioid use disorder in primary care.

BACKGROUND: Opioid-related deaths continue to rise in the U.S. A shared decision-making (SDM) system to help primary care clinicians (PCCs) identify and treat patients with opioid use disorder (OUD) could help address this crisis. METHODS: In this cluster-randomized trial, primary care clinics in three healthcare systems were randomized to receive or not receive access to an OUD-SDM system. The OUD-SDM system alerts PCCs and patients to elevated risk of OUD and supports OUD screening and treatment. It includes guidance on OUD screening and diagnosis, treatment selection, starting and maintaining patients on buprenorphine for waivered clinicians, and screening for common comorbid conditions. The primary study outcome is, of patients at high risk for OUD, the percentage receiving an OUD diagnosis within 30 days of index visit. Additional outcomes are, of patients at high risk for or with a diagnosis of OUD, (a) the percentage receiving a naloxone prescription, or (b) the percentage receiving a medication for OUD (MOUD) prescription or referral to specialty care within 30 days of an index visit, and (c) total days covered by a MOUD prescription within 90 days of an index visit. RESULTS: The intervention started in April 2021 and continues through December 2023. PCCs and patients in 90 clinics are included; study results are expected in 2024. CONCLUSION: This protocol paper describes the design of a multi-site trial to help PCCs recognize and treat OUD. If effective, this OUD-SDM intervention could improve screening of at-risk patients and rates of OUD treatment for people with OUD.

Implementing a prediabetes clinical decision support system in a large primary care system: Design, methods, and pre-implementation results.

BACKGROUND: Early detection of prediabetes and management of cardiovascular (CV) risk factors to prevent CV disease is essential, but clinicians are often slow to address this risk. Clinical decision support (CDS) systems, with appropriate implementation, can potentially improve prediabetes identification and treatment. METHODS/DESIGN: 34 Midwestern primary care clinics were randomized to receive or not receive access to a prediabetes (PreD) CDS tool. Between October 2016 and December 2019, primary care clinicians (PCPs) received Pre-D CDS alerts during visits with adult patients identified with prediabetes and who met minimal inclusion criteria and had at least one CV risk factor not at goal. The PCP Pre-D CDS included a summary of six modifiable CV risk factors and patient-specific treatment recommendations. Study outcomes included total modifiable CV risk, six modifiable CV risk factors, use of CV medications, and referrals. The Consolidated Framework for Implementation Research was used to examine CDS implementation processes. DISCUSSION: This cluster-randomized pragmatic trial allowed PCPs the opportunity to improve CV risk in a timely manner for patients with prediabetes. Effectiveness will be assessed using an intent-to-treat analysis. Implementation processes and outcomes will be assessed through interviews, surveys, and electronic health record data harvested by the CDS tool itself. Pre-implementation interviews and activities identified key strategies to incorporate as part of the Pre-D CDS implementation process to ensure acceptability and high use rates. Analyses are ongoing and trial results are expected in mid-2021.

Human Papillomavirus vaccination clinical decision support for young adults in an upper midwestern healthcare system: a clinic cluster-randomized control trial.

INTRODUCTION: Human papillomavirus (HPV) vaccination rates are low in young adults. Clinical decision support (CDS) in primary care may increase HPV vaccination. We tested the treatment effect of algorithm-driven, web-based, and electronic health record-linked CDS with or without shared decision-making tools (SDMT) on HPV vaccination rates compared to usual care (UC). METHODS: In a clinic cluster-randomized control trial conducted in a healthcare system serving a largely rural population, we randomized 34 primary care clinic clusters (with three clinics sharing clinicians randomized together) to: CDS; CDS+SDMT; UC. The sample included young adults aged 18-26 due for HPV vaccination with a study index visit from 08/01/2018-03/15/2019 in a study clinic. Generalized linear mixed models tested differences in HPV vaccination status 12 months after index visits by study arm. RESULTS: Among 10,253 patients, 6,876 (65.2%) were due for HPV vaccination, and 5,054 met study eligibility criteria. In adjusted analyses, the HPV vaccination series was completed by 12 months in 2.3% (95% CI: 1.6%-3.2%) of CDS, 1.6% (95% CI: 1.1%-2.3%) of CDS+SDMT, and 2.2% (95% CI: 1.6%-3.0%) of UC patients, and at least one HPV vaccine was received by 12 months in 13.1% (95% CI: 10.6%-16.1%) of CDS, 9.2% (95% CI: 7.3%-11.6%) of CDS+SDMT, and 11.2% (95% CI: 9.1%-13.7%) of UC patients. Differences were not significant between arms. Females, those with prior HPV vaccinations, and those seen at urban clinics had significantly higher odds of HPV vaccination in adjusted models. DISCUSSION: CDS may require optimization for young adults to significantly impact HPV vaccination. TRIAL REGISTRATION: clinicaltrials.gov NCT02986230, 12/6/2016.

Clinical Decision Support with or without Shared Decision Making to Improve Preventive Cancer Care: A Cluster-Randomized Trial.

BACKGROUND: Innovative interventions are needed to address gaps in preventive cancer care, especially in rural areas. This study evaluated the impact of clinical decision support (CDS) with and without shared decision making (SDM) on cancer-screening completion. METHODS: In this 3-arm, parallel-group, cluster-randomized trial conducted at a predominantly rural medical group, 34 primary care clinics were randomized to clinical decision support (CDS), CDS plus shared decision making (CDS+SDM), or usual care (UC). The CDS applied web-based clinical algorithms identifying patients overdue for United States Preventive Services Task Force-recommended preventive cancer care and presented evidence-based recommendations to patients and providers on printouts and on the electronic health record interface. Patients in the CDS+SDM clinic also received shared decision-making tools (SDMTs). The primary outcome was a composite indicator of the proportion of patients overdue for breast, cervical, or colorectal cancer screening at index who were up to date on these 1 y later. RESULTS: From August 1, 2018, to March 15, 2019, 69,405 patients aged 21 to 74 y had visits at study clinics and 25,198 were overdue for 1 or more cancer screening tests at an index visit. At 12-mo follow-up, 9,543 of these (37.9%) were up to date on the composite endpoint. The adjusted, model-derived percentage of patients up to date was 36.5% (95% confidence interval [CI]: 34.0-39.1) in the UC group, 38.1% (95% CI: 35.5-40.9) in the CDS group, and 34.4% (95% CI: 31.8-37.2) in the CDS+SDM group. For all comparisons, the screening rates were higher than UC in the CDS group and lower than UC in the CDS+SDM group, although these differences did not reach statistical significance. CONCLUSION: The CDS did not significantly increase cancer-screening rates. Exploratory analyses suggest a deeper understanding of how SDM and CDS interact to affect cancer prevention decisions is needed. Trial registration: ClinicalTrials.gov ID: NCT02986230, December 6, 2016.

Patient Perceptions of Using Clinical Decision Support for Cancer Screening and Prevention: "I wouldn't have thought about getting screened without it."

PURPOSE: We sought to gain an understanding of cancer prevention and screening perspectives among patients exposed to a clinical decision support (CDS) tool because they were due or overdue for certain cancer screenings or prevention. METHODS: Semi-structured qualitative interviews were conducted with 37 adult patients due or overdue for cancer prevention services in 10 primary care clinics within the same health system. Data were thematically segmented and coded using qualitative content analysis. RESULTS: We identified three themes: 1) The CDS tool had more strengths than weaknesses, with areas for improvement; 2) Many facilitators and barriers to cancer prevention and screening exist; and 3) Discussions and decision-making varied by type of cancer prevention and screening. Almost all participants made positive comments regarding the CDS. Some participants learned new information, reporting the CDS helped them make a decision they otherwise would not have made. Participants who used the tool with their provider had higher self-reported rates of deciding to be screened than those who did not. CONCLUSIONS: Learning about patients' perceptions of a CDS tool may increase understanding of how patient-tailored CDS impacts cancer screening and prevention rates. Participants found a personalized CDS tool for cancer screening and prevention in primary care useful and a welcome addition to their visit. However, many providers were not using the tool with eligible patients.

Design and rationale of an intervention to improve cancer prevention using clinical decision support and shared decision making: A clinic-randomized trial.

BACKGROUND: Despite decades of research the gap in primary and secondary cancer prevention services in the U. S. remains unacceptably wide. Innovative interventions are needed to address this persistent challenge. Electronic health records linked with Web-based clinical decision support may close this gap, especially if delivered to both patients and their providers. OBJECTIVES: The Cancer Prevention Wizard (CPW) study is an implementation, clinic-randomized trial designed to achieve these aims: 1) assess impact of the Cancer Prevention Wizard-Clinical Decision Support (CPW-CDS) alone and CPW-CDS plus Shared Decision Making Tools (CPW + SDMTs) compared to usual care (UC) on tobacco cessation counseling and drugs, HPV vaccinations, and screening tests for breast, cervical, colorectal, or lung cancer; 2) assess cost of the CPW-CDS intervention; and 3) describe critical facilitators and barriers for CPW-CDS implementation, use, and clinical impact using a mixed-methods approach supported by the CFIR and RE-AIM frameworks. METHODS: 34 predominantly rural, primary care clinics were randomized to CPW-CDS, CPW + SMDTs, or UC. Between August 2018 and October 2020, primary care providers and their patients who met inclusion criteria in intervention clinics were exposed to the CPW-CDS with or without SDMTs. Study outcomes at 12 months post index visit include patients up to date on screening tests and HPV vaccinations, overall healthcare costs, and diagnostic codes and billing levels for cancer prevention services. CONCLUSIONS: We will test in rural primary care settings whether CPW-CDS with or without SDMTs can improve delivery of primary and secondary cancer prevention services. The trial and analyses are ongoing with results expected in 2021.

Decision analysis defining optimal management of clinical stage 1 high-risk nonseminomatous germ cell testicular cancer with lymphovascular invasion.

BACKGROUND: Risk of recurrent disease for men with clinical stage 1 high-risk nonseminomatous germ cell testicular cancer (CS1 NSGCT) with lymphovascular invasion (LVI) after orchiectomy is 50% and current treatment options (surveillance [S], retroperitoneal lymph node dissection [RPLND], or 1 cycle of BEP [BEP ×1]) are associated with a 99% disease specific survival, therefore practice patterns vary. We performed a decision analysis using updated data of long-term complications for men with CS1 NSGCT with LVI to quantify and assess relative treatment values. METHODS: Decision analysis included previously defined utilities (via standard gamble) for posttreatment states of living from 0 (death from disease) to 1 (alive in perfect health) and updated morbidity probabilities. We quantified the values of S, RPLND, and BEP ×1 via the rollback method. Sensitivity analyses including a range of orchiectomy cure rates and utility values were performed. RESULTS: Estimated probabilities favoring treatment with RPLND (0.97) or BEP ×1 (0.97) were equivalent and superior to surveillance (0.88). Sensitivity analysis of orchiectomy cure rates (50%-100%) failed to find a cure rate that favored S over BEP ×1 or RPLND. Varying utility values for cure after S from 0.92 (previously defined utility) to 1 (perfect health), failed to find a viable utility state favoring S over BEP ×1 or RPLND. An orchiectomy cure rate of ≥82% would be required for S to equal treatment of either type. CONCLUSIONS: We demonstrate that for surveillance to be superior to treatment with BEP ×1 or RPLND, the orchiectomy cure rate must be at least 82%, which is not expected in a patient population with high-risk CS1 NSGCT.