Neoplasms

Respiratory Tract (Lung and Bronchial) Diseases

All Conditions

Lung Neoplasms

Respiratory Tract Neoplasms

Thoracic Neoplasms

Lung Diseases

Respiratory Tract Diseases

This population will consist of patients eligible for, or potentially eligible for, LDCT lung cancer screening according to USPSTF guidelines, who are seen by a pilot user of the intervention. The inclusion criteria are (i) \>= 55 years and \<= 80 years old at the time of the visit; (ii) does not already have lung cancer; and (iii) meets USPSTF smoking criteria for LDCT screening (30+ pack-year smoking history and current smoker or quit in the past 15 years) or may meet the criteria if a complete smoking history were taken.

USPSTF guidelines may change during the study. In particular, it is anticipated that the guidelines may update during the study whereby the minimum age is reduced to 50 (from 55) and the minimum smoking history is reduced to 20 years (from 30). In the event that the USPSTF guidelines change, the intervention will be updated to match the change to the guidelines. We may also update the study evaluation to match the updated USPSTF guidelines.

The intervention will consist of the following core items:

* An EHR-integrated shared decision making (SDM) tool for providing information on the risks and benefits of lung cancer screening through low-dose computed tomography (LDCT) testing. This intervention is referred to as Decision Precision+.
* Suggestions in the EHR to offer SDM for LDCT for patients eligible for lung cancer screening according to USPSTF guidelines. These suggestions include those provided by the EHR's "Health Maintenance" module as well as an EHR-integrated "Disease Manager" system for disease management and health maintenance.

Improvements may also be introduced based on user feedback. All major enhancements will be introduced with the support and approval of the appropriate governance group.

Following roll-out, clinic leaders may also receive periodic feedback on use of the intervention and LDCT screening rates, as well as advice on how to improve intervention adoption.

EHR-integrated Shared Decision Making Tool and Clinical Decision Support for Lung Cancer Screening

Kensaku Kawamoto, MD, PhD, MHS

The purpose of this project is to increase appropriate low-dose computed tomography (LDCT) lung cancer screening through the development and wide dissemination of patient-centered clinical decision support (CDS) tools that (1) are integrated with the electronic health record (EHR) and clinical workflows, (2) prompt for shared decision making (SDM) when patients meet screening criteria, and (3) enable effective SDM using individually-tailored information on the potential benefits and harms of screening. The study will promote standard of care that is endorsed by the Centers for Medicare \& Medicaid Services (CMS) and the US Preventive Services Task Force (USPSTF).

The purpose of this project is to increase appropriate low-dose computed tomography (LDCT) lung cancer screening through the development and wide dissemination of patient-centered clinical decision support (CDS) tools that (1) are integrated with the electronic health record (EHR) and clinical workflows, (2) prompt for shared decision making (SDM) when patients meet screening criteria, and (3) enable effective SDM using individually-tailored information on the potential benefits and harms of screening. The study will promote standard of care that is endorsed by the Centers for Medicare \& Medicaid Services (CMS) and the US Preventive Services Task Force (USPSTF). This project is supported both operationally and by an Agency for Healthcare Research and Quality (AHRQ) R18 grant.

This project will leverage Decision Precision, a validated Web-based tool for LDCT SDM developed at the Veterans Health Administration, as well as an initial version of Decision Precision+, an EHR-integrated version of the tool which can be accessed directly in the EHR and auto-populate relevant patient data in the tool instead of requiring manual data entry.

This study will be an 18-month interrupted time series study conducted at the University of Utah Health primary care clinics.

no masking due to the nature of the intervention

Evaluation of a Scalable Decision Support and Shared Decision Making Tool for Lung Cancer Screening

We are not planning to make individual participant data (IPD) available to other researchers.

The rate of usage of the intervention will be measured. The usage will be measured through system logs and data from the enterprise data warehouse. We will also seek to model patient, clinical user, and context predictors of tool usage.

Usability of the intervention will be solicited during the study to support the implementation and make adjustments to the intervention as needed. Towards the end of the evaluation period, usability will be measured though the System Usability Scale survey.

We will report whether investment in a program to promote appropriate screening for lung cancer can lead to a positive financial return on investment. If so, the number of years before such an investment can break even will be reported.

Change in proportion of patients eligible for LDCT screening per USPSTF guidelines receiving LDCT screening

Estimated number of lung cancer deaths prevented given the risk profiles of individuals screened with LDCT

Estimated number of major complications given the risk profiles of individuals screened with LDCT

University of Utah

Associate Chief Medical Information Officer

Nutritional and Metabolic Diseases

Gland and Hormone Related Diseases

Heart and Blood Diseases

Diabetes Mellitus

Heart Diseases

MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to patients as clinical decision support.

MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to providers as clinical decision support.

Software program collecting family health history and generating clinical decision support for risk-based preventive care

MeTree

Geoffrey S Ginsburg, MD PHD

Lori Orlando, MD

The outcome of this research will be a demonstration that family health history (FHH) risk data can be used efficiently to deliver more effective healthcare in geographically and ethnically diverse clinical care environments. Although FHH is a standard component of the medical interview its widespread adoption is hindered by three major barriers: (1) a dearth of standard collection methods; (2) the absence of health care provider access to complete FHH information; and (3) the need for clinical guidance for the interpretation and use of FHH. In addition, the time constraints of the busy provider and poor integration of FHH with paper medical records or electronic medical records (EMR) impede its widespread use. The investigators hypothesize that patient-driven and electronic collection of FHH for risk stratification will promote more informed decision-making by patients and providers, and improves adherence to risk-stratified preventive care guidelines. The study team will use an implementation sciences approach to integrate an innovative FHH system that collects FHH from patients. Intermountain Healthcare will provide the information technology expertise with EMR design to develop an innovative solution to a storage model standard for FHH data as well as a centralized standards-compliant open clinical decision support (OpenCDS) rule development architecture to analyze FHH and to generate evidence-based, individualized, disease risk, preventive care recommendations for both patients and providers.

Five health care delivery organizations will participate in this demonstration project: Duke University, the Medical College of Wisconsin, the Air Force, Essentia Health, and the University of North Texas Health Science Center. The study will take place in 'real world' clinical, socio-cultural, and demographically diverse (rural, underserved, academic, family medicine) care clinics (n=34) in 5 states (CA, MN, NC, WI, TX) that include genomic medicine 'early adopter' and 'naïve' sites, as well as those that are EMR-enabled and others that are not. The study team will recruit a minimum of 7000 English or Spanish speaking adults over a 3-year period and will capture process metrics and outcomes that are measured in the course of usual care. The goals are: 1) To optimize the collection of patient entered FHH in diverse clinical environments for coronary heart disease, thrombosis, and selected cancers, 2) to export FHH data to an OpenCDS platform and return CDS results to providers and patients (and to EMRs where relevant) and to explore the integration of genetic risk and FHH data at selected sites, 3) to assess the clinical and personal utility of FHH using a pragmatic observational study design to assess reach, adoption, integrity, exposure, and sustainability, and to capture, analyze, and report effectiveness outcomes at each stakeholder level: patient, provider, and clinic/system, and 4) to take a leadership role in the dissemination of guidelines for FHH intervention across in diverse practice settings.

Family Health History in Diverse Care Settings (FHH)

Family Health History in Diverse Care Settings

How many patients identified as meeting criteria for genetic counseling, how many providers ordered genetic counseling, and how many patients adhere to the provider recommendation at 1 year.

The study will assess satisfaction associated with using the MeTree tool via 3 months survey after completing the family health history collection. The participant were asked their level of satisfaction with their experience using the web-based portal to enter information for their provider before their appointment

The study will assess comfort associated with using the MeTree tool via 3 months survey after completing the family health history collection. The participant were asked if the MeTree program was easy to use

The study will assess anxiety associated with using the MeTree tool via 3 months survey after completing the family health history collection. The participant were asked if answering the questions made them anxious

The study will assess preparedness associated with using the MeTree tool via 3 months survey after completing the family health history collection. The participants were asked if they had enough information about some people in their family when completing MeTree

Evaluate physicians' perceptions of satisfaction, the MeTree tool's impact on work load and its effectiveness via survey and informal interviews at 3 months.

Evaluate which providers were successfully using MeTree in their clinical work flow and which patients are successfully using MeTree for their care. (surveys, monitoring of clinical workflow, patient recruitment reflects underlying clinic population)

Duke University

All-Cause Mortality and Serious Adverse Events were not monitored/assessed for either Arm/Group

MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to patients as clinical decision support.

MeTree: Software program collecting family health history and generating clinical decision support for risk-based preventive care

MeTree - Patients

MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to providers as clinical decision support.

MeTree: Software program collecting family health history and generating clinical decision support for risk-based preventive care

MeTree - Providers

MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to Providers as clinical decision support.

MeTree: Software program collecting family health history and generating clinical decision support for risk-based preventive care

Total

Age, Categorical

Age, Continuous

Sex: Female, Male

Ethnicity (NIH/OMB)

Race (NIH/OMB)

United States

Region of Enrollment

12 mo survey ended early w/ approved by Duke IRB. Sufficient data obtained to perform the scientific analysis; the overall status of the study is still active, not recruiting. Participant contact completed.

Dr. Lori A. Orlando, Director Program in Precision Medicine

Patients who met genetic counseling criteria

Patients who received Genetic Counseling Order

Patients adhered to provider's recommendation-1yr

Providers who placed Genetic counseling order

Patients who completed intervention and meeting criteria for genetic counseling

Number of Participants With Uptake of Genetic Counseling for Those at Risk of Hereditary Conditions at 1 Year

Superior

Above Average

Very Satisfactory

Somewhat unsatisfactory

Very Poor

Not Answered

Patients who completed 3 months post survey and reported their level of satisfaction

Number of Participants Reporting Satisfaction When Using the MeTree Tool

Do not know

did not answer

Patients who completed 3 months post survey and reported on their level of comfort

Number of Participants Reporting Comfort When Using the MeTree Tool

Did not answer

Patients who completed 3 months post survey and reported on anxiety with answering the questions

Number of Participants Reporting Anxiety When Using the MeTree Tool

Patients who completed 3 months post survey and reported on preparedness

Number of Participants Reporting Preparedness When Using the MeTree Tool

Consented providers who completed provider post implementation survey

Number of Physicians Who Gave Their Perceptions of Satisfaction and the MeTree Tool's Impact on Work Load

Number of Providers Who Were Successfully Using MeTree in Their Clinical Work Flow

MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to patients and providers as clinical decision support.

MeTree: Software program collecting family health history and generating clinical decision support for risk-based preventive care

Providers using MeTree risk assessment program for clinical decision support

Overall Study

The CP-CDS group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services.

The CP-CDS + SDMT group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services. The CP-CDS + SDMT arm also provides shared decision making tools to patient and provider at the time of the visit.

The usual care group will have no access to the CP-CDS, or the CP-CDS + SDMT.

The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

CP-CDS

Thomas E Elliott, MD

The objective of this project is to implement and evaluate the effectiveness of a sophisticated Web-based, electronic health record (EHR)-linked clinical decision support (CDS) system designed to improve primary and secondary cancer preventive care.

This project will engage a rural population with substantial healthcare disparities and gaps in the receipt of primary and secondary cancer prevention. Results will advance dissemination and implementation research methods that can reduce health disparities and improve healthcare for millions in medically under-served areas.

The objective of this project is to implement and evaluate the effectiveness of a sophisticated Web-based, electronic health record (EHR)-linked clinical decision support (CDS) system designed to improve primary and secondary cancer preventive care. To achieve this objective, EHR data is sent to evidence-based cancer prevention algorithms, housed on a secure Web site. The algorithms: (a) identify at the point of care all eligible patients not up to date on their cancer prevention interventions; and (b) present to both patient and primary care provider (PCP), appropriate evidence-based primary cancer prevention interventions and cancer screening options at the point of care. The cancer prevention (CP)-CDS will focus on breast cancer screening in women aged 50-74, colorectal cancer screening for both sexes aged 50-75, cervical cancer screening for women aged 21-65, human papilloma virus (HPV) vaccination for both sexes aged 11-26, and referrals for weight management and smoking cessation in all adults aged 18 and older. Effectiveness is assessed by cluster-randomizing 30 primary care clinics with roughly 285 PCPs and 153,000 study-eligible patients into one of three experimental conditions: Group 1: CP-CDS intervention in which the decision support is printed for the PCP and patient, designed to engage patients in discussions about appropriate cancer prevention strategies. Group 2: CP-CDS + shared decision making tools (SDMT) intervention in which the CP-CDS is printed along with additional shared decision making tools. Group 3: clinics provide usual care (UC) with no intervention-related activity related to cancer prevention.

With 10 clinics, 95 PCPs, and 51,000 potentially eligible patients per study arm, this study will formally test the hypothesis that Groups 1 and 2 are superior to Group 3 over an 12-month follow-up period with respect to: (a) significantly higher rates of appropriate screening for breast, cervix, and colorectal cancer, as defined by the United States Preventive Services Task Force; and (b) significantly higher rates of human papillomavirus (HPV) vaccination in males and females aged 11-26 years. Secondary analysis will evaluate the impact of the intervention on lung cancer screening. The investigators further posit that Groups 1 and 2 will have higher short-term health care costs but better long-term cost-effectiveness than Group 3. The Consolidated Framework for Implementation Research (CFIR) and Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) conceptual frameworks will be used to guide implementation planning, organization, conduct, and impact evaluation of the intervention in a large rural healthcare system.

This project will engage a rural population with substantial healthcare disparities and gaps in the receipt of primary and secondary cancer prevention. Results will advance dissemination and implementation research methods that can reduce health disparities and improve healthcare for millions in medically under-served areas.

Cancer Prevention Clinical Decision Support

Implementing Cancer Prevention Using Patient-Provider Clinical Decision Support

Participants up to date on composite endpoint of breast, cervical, and colorectal cancer screening at 1 year post index date.

Participants up to date on HPV vaccination at 1 year post index date.

Participants up to date on lung cancer screening at 1 year post index date.

HealthPartners Institute

This is a minimal risk study designed to improve cancer screening rates. Feedback from providers on the CDS tool was monitored and printing rates for the CDS interface were monitored.

Providers in the PCP-focused group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services.

CP-CDS: The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

Providers in the SDMT-focused group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services. The SDMT-focused arm also provides shared decision making tools to patient and provider at the time of the visit.

CP-CDS: The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

CP-CDS + SDMT

Providers practicing at clinics assigned to the usual care arm will have no access to the CP Wizard.

Usual Care

Providers practicing in the PCP-focused group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services.

CP-CDS: The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

Providers practicing in the SDMT-focused group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services. The SDMT-focused arm also provides shared decision making tools to patient and provider at the time of the visit.

CP-CDS: The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

Analysis population included patients not up to date on one or more composite screening for breast, cervical, or colorectal cancer, HPV vaccine, or lung cancer screening.

The study was conducted at one relatively high-performing predominantly rural healthcare system, and generalizability of results to other care systems or patient populations is uncertain. The intervention was delivered during clinic encounters with primary care providers; the impact of the clinical decision support delivered in other clinical venues or directly to patients using mobile health technologies may be greater or less than what we observed.

Dr. Tom Elliott

Generalized linear mixed models with logit link and binomial error distribution were used to test the effect of the intervention on the composite of cancer screening by 1 year post-index for breast, cervical, and colorectal cancer. The model included two primary contrasts: CP-CDS vs. UC and CP-CDS+SDMT vs. UC and included pre-specified covariates and variables used in the randomization process. Tests of the two contrasts were 2-sided with P-values \< 0.025 considered statistically significant.

Generalized linear mixed models with a logit link and binomial error distribution were used to test the effect of the intervention on the composite of cancer screening by 1 year post-index date for breast, cervical, and colorectal cancer. Model included two primary contrasts: CP-CDS vs. UC and CP-CDS+SDMT vs. UC and included pre-specified covariates and variables used in randomization process. Tests of the planned contrasts were 2-sided with P-values \< 0.025 considered statistically significant.

The PCP-focused group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services.

CP-CDS: The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

The SDMT-focused group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services. The SDMT-focused arm also provides shared decision making tools to patient and provider at the time of the visit.

CP-CDS: The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

Analysis population included adult patients ages 21-75 who had a visit at a study clinic over the accrual period, and who were due for one or more breast, cervical, or colorectal cancer screening test.

Composite Cancer Screening Tests up to Date

Generalized linear mixed models with a logit link and binomial error distribution were used to test the effect of the intervention on completion of the HPV vaccination series by 12 months post-index date. The model included two primary contrasts: CP-CDS vs. UC and CP-CDS+SDMT vs. UC and included pre-specified covariates and variables used in the randomization process. Tests of the two planned contrasts were 2-sided with P-values less than 0.025 considered statistically significant.

Young adults ages 18-26 with a visit at a study clinic during the accrual period, and not up to date on HPV vaccination.

HPV Vaccination up to Date

Generalized linear mixed models with a logit link and binomial error distribution were used to test the effect of the intervention on completion of lung cancer screening by 12 months post-index date. The model included two primary contrasts: CP-CDS vs. UC and CP-CDS+SDMT vs. UC and included pre-specified covariates and variables used in the randomization process. Tests of the two planned contrasts were 2-sided with P-values less than 0.025 considered statistically significant.

Generalized linear mixed models with a logit link and binomial error distribution were used to test the intervention effect on the completion of lung cancer screening by 12 months post-index. The model included two primary contrasts: CP-CDS vs. UC and CP-CDS+SDMT vs. UC and included pre-specified covariates and variables used in the randomization process. Tests of the two planned contrasts were 2-sided with P-values less than 0.025 considered statistically significant.

Adult patients with a visit at a study clinic and not up to date for lung cancer screening at index date.

Lung Cancer Screening up to Date

The CP-CDS group will receive a point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services.

CP-CDS: The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

The SDMT-focused group will receive the point of care clinical decision support tool called cancer prevention wizard (CP Wizard) that is integrated into the EHR. The CP Wizard provides evidenced- based recommendations to the provider and patient related to overdue cancer prevention screening services. The SDMT-focused arm also provides shared decision making tools to patient and provider at the time of the visit.

CP-CDS: The cancer prevention wizard is a point of care clinical decision support system designed to identify patients that are due for preventative cancer services and provides evidenced-based recommendations to the patient and provider.

Patients of providers practicing at clinics assigned to the usual care arm will have no access to the CP-CDS or CP-CDS + SDMTs.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Evaluation of a Scalable Decision Support and Shared Decision Making Tool for Lung Cancer Screening	NCT04498052	Early Detection... Lung Neoplasms	EHR-integrated ...	55 Years - 80 Years	University of Utah
Family Health History in Diverse Care Settings (FHH)	NCT01956773	Diabetes Heart Disease Cancer	MeTree	18 Years -	Duke University
Cancer Prevention Clinical Decision Support	NCT02986230	Cancer Preventi...	CP-CDS	18 Years - 80 Years	HealthPartners Institute

Spots Global Cancer Trial Database for clinical decision support