Nutritional and Metabolic Diseases

Gland and Hormone Related Diseases

All Conditions

Heart and Blood Diseases

Diabetes Mellitus

Hypertension

Metabolic Diseases

Glucose Metabolism Disorders

Endocrine System Diseases

Health Information

Preventive Services

Computer tailored information

Christopher N Sciamanna, MD

To test whether or not giving patients information before their doctor visits changes the care they receive and what type of information is best to give before the doctor visit.

Patients are randomized into one of three groups. Before a single visit with diabetes care provider, the patient is called to answer interview questions about their health, diabetic care and behavior habits. After a patient visits with their doctor, they are called again to answer question about the visit they just had. If a patient is place into group A or B, based on their answers to the questions they are mailed a printed report before their doctor visit. The report will indicate how things are going the patient's diabetic care and recommended questions to ask his/her health care provided about diabetes. Group A feedback report will emphasize the risks from diabetes and the feedback reports for Group B will emphasize things to do to protect oneself from problems from having diabetes. Participants randomized to Group C will only receive printed reports after a doctors visit. No extra visit will be scheduled with the participants doctor, no travel is required, no blood tests are required and ther doctor will not be involved in the study unless the study participant chooses to discuss it with his/her doctor.

Computer-Assisted Cancer Risk Behavior Counseling

National Cancer Institute (NCI)

Thomas Jefferson University

Intervention practices will implement an interactive preventive health record in addition to their standard personal health record functionality.

Control practices will continue to field their existing personal health record

The interactive preventive healthcare record (IPHR) is a patient-centered application that links patients to their clinician's record, explains information in lay language, displays tailored recommendations and educational resources, and makes preventive care actionable.

Interactive Preventive Health Record

Alexander H Krist, MD, MPH

Cancer screening can improve the length and quality of life, yet the average American receives only half of recommended services. Patient-centered personal health records with higher levels of functionality, combined with practice redesign to make use of these functions, can help patients obtain recommended cancer screening tests by linking them to their doctor's records, explaining information in lay language, displaying tailored recommendations and educational resources, providing logistical support and tools to stimulate action, and generating reminders. This project will measure whether making these resources available to primary care practices and patients promotes shared decision-making and increases the delivery of cancer screening compared to existing information systems.

We developed a theory-driven interactive Patient Health Record (PHR) that uses higher functionality to more deeply engage patients in health promotion. The model defines five levels of PHR functionality: (1) collecting patient information, (2) integrating with electronic health records (EHRs), (3) translating information into lay language, (4) providing individualized, guideline-based clinical recommendations, and (5) facilitating patient action. We hypothesize that implementing PHRs with these higher levels of functionality will inform and activate patients in ways that simpler PHRs cannot achieve and will increase uptake of preventive services. In Phase 1, we will randomize 46 practices from three practice-based research networks in eight states to implement a PHR with advanced versus simpler functionality. Control practices will use their existing PHR. Intervention practices will upgrade their PHR to feature an interactive preventive health record (IPHR) that we have previously developed and tested. Intervention practices will locally tailor the IPHR content and learn how to integrate new functions into practice. Phase 1 will feature an implementation assessment in intervention practices, based on the RE-AIM model, to measure Reach (creation of IPHR accounts by patients), Adoption (practice decision to use the IPHR), Implementation (consistency, fidelity, barriers, and facilitators of use), and Maintenance (sustained use). The randomized comparison of intervention and control practices will measure the incremental effect of the IPHR on shared decision-making and receipt of cancer screening tests compared to traditional PHRs (Effectiveness). Data sources will include the EHR/PHR/IPHR databases, patient and practice surveys, recruitment field notes, practice learning collaborative transcripts, practice diaries, and patient phone interviews. This study will inform future efforts to use patient-centered information technology to promote cancer prevention and the feasibility of national dissemination.

Implementing Personal Health Records to Promote Evidence-Based Cancer Screening

The percent of eligible patients who are up-to-date with all indicated cancer screenings (all-or-none measure).

To assess shared decision making a composite score based on the following measures will be calculated.

* Knowledge gained will be measured by using the IPHR, we will use questions from NCI's Health Information National Trends Survey (HINTS).
* To assess whether the IPHR helps patients weigh values regarding risks and benefits 2 measures will be used: (a) process (patient-clinician communication) and (b) patient perception (decisional conflict).

  1. Communication will be measured by using questions from AHRQ's Consumer Assessment of HealthCare Providers and Systems (CAHPS) survey.
  2. O'Connor's low literacy decisional conflict scale will be used to measure decisional conflict.
* To assess whether the IPHR fosters decision-making engagement at the desired level, Degner's locus of control metric will be used.

The difference in delivery of preventive services (Effectiveness) will be calculated for disadvantaged patients and the general population, using a two-level mixed-effects logistic regression for the all-or-none, composite, and individual screening tests.

To assess shared decision making a composite score based on the following measures will be calculated.

* Knowledge gained will be measured by using the IPHR, we will use questions from NCI's Health Information National Trends Survey (HINTS).
* To assess whether the IPHR helps patients weigh values regarding risks and benefits 2 measures will be used: (a) process (patient-clinician communication) and (b) patient perception (decisional conflict).

  1. Communication will be measured by using questions from AHRQ's Consumer Assessment of HealthCare Providers and Systems (CAHPS) survey.
  2. O'Connor's low literacy decisional conflict scale will be used to measure decisional conflict.
* To assess whether the IPHR fosters decision-making engagement at the desired level, Degner's locus of control metric will be used.

These scores will be calculated for disadvantaged patients (minorities and Medicaid patients) and the general population that use the IPHR, then compared.

Post-implementation patient phone interviews will be conducted then analyzed using grounded-theory approach to understand disadvantaged patients' perceptions of and experience with the IPHR. These results will be compared to the phone interviews done with patients from the general population.

Virginia Commonwealth University

Patients receiving care in community health centers in states that expanded Medicaid (intervention group)

Patients receiving care in community health centers in states that did not expand Medicaid (control group)

There will be no direct intervention, but rather an observation of change based on whether a state expanded Medicaid or not

Medicaid Expansion

This innovative and timely study will measure the impact of Affordable Care Act (ACA) Medicaid expansions on cancer screenings and preventive services. To assess this natural policy experiment, the investigators will use electronic health record data from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) clinical data research network (CDRN) of the National Patient-Centered Clinical Research Network (PCORnet).

Cancer morbidity and mortality is greatly reduced through screening and prevention, but uninsured patients are much less likely than insured patients to receive these evidence-based services as recommended. In addition, uninsured cancer survivors receive fewer primary and preventive care services than those with health insurance. Thus, it is hypothesized that Affordable Care Act (ACA) Medicaid expansions could substantially improve access to essential cancer preventive and screening services for previously uninsured patients, and facilitate better care for cancer survivors who gain health insurance. In 2012, the United States (US) Supreme Court ruled that states were not legally required to implement ACA Medicaid expansions, creating a unique natural experiment to test this hypothesis. By April 1, 2015, 30 states and the District of Columbia had implemented expansions, and 20 states had not. This led to increased Medicaid enrollment by 26% in expansion states, compared to 8% in non-expansion states. Previous single-state Medicaid expansions led to increased utilization of healthcare services and improved health outcomes post-expansion. For example, in Oregon, cervical cancer screening rates were 18-19% higher among women who gained Medicaid in 2008, compared to those who remained uninsured. However, no previous assessments of state-specific expansions had concurrent control (non-expansion) states for comparison. Further, little is known about how Medicaid expansion impacts the delivery of recommended primary and preventive care services to cancer survivors, termed 'survivor care.'

The investigators propose to use the ACA Medicaid expansion natural experiment to study the effect of state-level Medicaid expansion on rates of cancer screening and preventive services ('cancer prevention') and survivor care. Many patients likely to gain coverage through ACA Medicaid expansions receive primary care in community health centers (CHCs), our nation's healthcare 'safety net;' thus, the proposed analyses will use electronic health record (EHR) data from the ADVANCE clinical data research network (CDRN) of CHCs (ADVANCE is one of 11 CDRNs in the national PCORnet data network). The ADVANCE CDRN has patient-level data from 476 CHCs in 13 Medicaid expansion states (n=576,711 patients) and 242 CHCs in 8 non-expansion states (n=361,421 patients). This nationally unique data resource will allow us to measure outcomes in expansion versus non-expansion states, illuminating the impact of increased Medicaid opportunities on rates of cancer prevention and survivor care within the safety net. The investigators will also assess whether disparities in delivery of this care are reduced. Our specific aims for this study, titled "Assessing Community Cancer care after insurance ExpanSionS (ACCESS)," are to:

Aim 1. Compare pre-post receipt of cancer prevention and screening among vulnerable CHC patients in Medicaid expansion versus non-expansion states.

Hypothesis 1a: Cancer prevention and screening will significantly increase among CHC patients in expansion states, compared to those in non-expansion states.

Hypothesis 1b: Racial/ethnic disparities in cancer prevention and screening will be significantly reduced in expansion states versus no change in non-expansion states.

Aim 2. Compare pre-post insurance status, visits, and receipt of routine, recommended primary and preventive care among cancer survivors seen in CHCs in expansion versus non-expansion states.

Hypothesis 2a: A higher percentage of uninsured cancer survivors will have gained insurance coverage in expansion states, compared to those in non-expansion states.

Hypothesis 2b: Cancer survivors who are CHC patients in expansion states will have a significant increase in visits, visits paid by Medicaid, and survivor care relative to no change among patients in non-expansion states.

Assessing Community Cancer Care After Insurance ExpanSionS

Preventive services and screenings for cervical, colorectal, and breast cancers, HPV vaccinations, smoking screening ad interventions, and obesity screening and interventions.

Preventive services and screenings for cervical, colorectal, and breast cancers, HPV vaccinations, smoking screening ad interventions, and obesity screening and interventions

Health insurance status derived from EHR data and is primarily based on information collected at each visit

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Computer-Assisted Cancer Risk Behavior Counseling	NCT00242645	Diabetes Diabetes Mellit... Hypertension	Health Informat... Preventive Serv... Computer tailor...	21 Years - 70 Years	Thomas Jefferson University
Implementing Personal Health Records to Promote Evidence-Based Cancer Screening	NCT02138448	Cancer Health Promotio...	Interactive Pre...	18 Years - 75 Years	Virginia Commonwealth University
Assessing Community Cancer Care After Insurance ExpanSionS	NCT02936609	Cancer	Medicaid Expans...	19 Years - 64 Years	OHSU Knight Cancer Institute

Spots Global Cancer Trial Database for preventive services