Messaging and advance directive distribution. All arms receive physician advance care planning education at the clinic level.

Messaging and advance directive distribution plus introduction to the Prepare For Your Care website. All arms receive physician advance care planning education at the clinic level.

Messaging and advance directive distribution, introduction to the Prepare For Your Care website, plus patient engagement from a trained facilitator who also can interact with the primary care physician. All arms receive physician advance care planning education at the clinic level.

Patient receives a health system-specific advance directive along with a message crafted with input from a broad group of stakeholders at the clinical sites and external advisors. Messaging introduces advance care planning, the purpose of the advance directive and contains instructions for completing it and turning it in, as well as a prompt to discuss the document with the patient's primary care physician.

Advance directive

Patient invited to use the Prepare For Your Care website (www.prepareforyourcare.org) that will introduce and facilitate advance care planning and guide completion of an advance directive.

Prepare

Facilitator engages patient to activate advance care planning and to carry out navigation and facilitation aspects of advance care planning. Facilitator can tee up advance care planning activities with the primary care physician.

Facilitator

Neil S Wenger, MD

Using a cluster randomized design at the clinic level, this project will implement and test three real-world, scalable advance care planning interventions among primary care clinics across three University of California health systems. Seriously ill patients identified using data from the electronic health record will receive (1) an advance directive with targeted messaging, (2) intervention 1 plus prompting to engage with the Prepare For Your Care website, or (3) intervention 2 plus engagement from a clinic-based facilitator. A Research cohort of patients will provide complete surveys at baseline, 12 and 24 months. The main outcomes are advance directive completion among the population cohort and goal concordant care among the Research cohort at 12 months.

The goal of the project is to test, implement, and disseminate real-world, scalable advance care planning (ACP) interventions among busy, primary care clinics across three UC Health systems. The study aims are as follows:

Aim 1: With the input of primary care stakeholders (i.e., adults with serious illness, caregivers and clinical staff) at each site, determine the barriers, facilitators and best workflow plans to implement the three ACP interventions.

Aim 2: Implement the three ACP interventions across primary care clinics using a cluster randomized design across three UC Health systems: distribution of an advance directive (AD) (arm 1), distribution of the AD plus prompting the patient to engage with the Prepare For Your Care website (arm 2), and the AD plus engagement with the Prepare For Your Care website plus a Care coordinator intervention to engage clinicians (arm 3).

Aim 3: Compare the effectiveness of the three interventions on documentation of ACP (represented by an AD, POLST or out-of-hospital DNR form available in the medical record) on a population-based primary care cohort of seriously ill patients across three UC Health systems, and assess ACP engagement, quality of communication and goal-concordant care among a Research cohort subset of these patients.

The investigators hypothesize that there will be a dose response of additive improvement from arm 1 to arm 2 to arm 3 on AD completion (primary outcome) at the population level and receipt of goal-concordant treatment at the Research cohort level.

Seriously ill patients commonly receive treatments at the end of life that are inconsistent with or not guided by their values and goals. People with serious illness bear a considerable burden of suffering, and complexity of illness is strongly associated with increased hospitalization and healthcare utilization. Families of patients with serious illness who die often sustain substantial financial and emotional injury. Yet, this is not an irremediable result of advanced technology and an enlarging older population: ACP - the process of discussion of end of life care, clarification of values and goals, and embodiment of preferences through written documents and medical orders - is associated with less aggressive medical care near death and earlier hospice referral, which is then associated with better quality of life for patients and better bereavement adjustment for loved ones.

Experimental evidence supports the premise that ACP improves the treatment choices made by and for people with serious illness. A systematic review concluded that ACP interventions increase completion of ADs, increase the frequency of discussions about care preferences and increase concordance between patient's preferences and end-of-life care received. An earlier review found that multicomponent interventions were more likely to result in AD completion, yet much of this work focused on hospitalized patients and patients with cancer. A systematic review of the effects of 113 ACP interventions found decreased use of life-sustaining treatment and increased hospice and palliative care, but concluded that more experimental designs and community studies are needed. Many of these reviews noted a lack of head-to-head comparison of ACP interventions and a need for structures to implement ACP in standard care. The Institute of Medicine IOM critiqued studied ACP interventions for being targeted as one-time decisions rather than being conceptualized as incorporated into the routine of care.

A fundamental gap exists in whether and how ACP interventions can be implemented at a healthcare system level. Although ACP has shown the potential to help patients and clinicians achieve the "triple aim" of improving quality of care and patient satisfaction, improving population health and lowering costs by honoring patients' wishes, it has been slow to be prioritized in healthcare systems. Even among seriously ill patients, ACP remains uncommon. Although quality and efficiency are increasingly emphasized and several health systems are in early phases of adopting programs to improve ACP, few programs have successfully implemented ACP across their healthcare system. Implementing a system-wide program among a diverse patient population with primary care physicians (PCPs) who are already overburdened with the complex management of seriously ill patients remains a challenge.

This project will implement three system-wide advance care planning interventions and compare their effect. This quality improvement project will be implemented at the level of the health system with no direct patient contact and collection of only deidentified data for evaluation of the effect of the interventions. A second project nested in the population-based quality improvement project will enroll and evaluate a Research cohort that will provide patient and caregiver level information about the effect of the three ACP interventions. These components will be conducted in an identical fashion at UCLA, UCSF and UCI.

Using a computer algorithm developed and validated for this project, data from the electronic health record will be used to delineate a group of seriously ill patients cared for in primary care that require ACP and also identify whether these patients have ADs in the electronic health record in the past 3 years. All patients receiving primary care in the health system are eligible to be identified as seriously ill patients.

The project will implement 3 real-world ACP intervention comparators using a clustered randomized trial design. The interventions are: (arm 1) distribution of an AD with a tailored message via MyChart in the electronic health record and/or postal mail, (arm 2) arm 1 plus access to the Prepare For Your Care website that is a publicly available decision support tool for ACP, and (arm 3) arm 2 plus patient engagement by a clinic-based facilitator who will tee up AD completion, Prepare website use and coordinate patient ACP interactions with primary care physicians. The interventions will continue over a 24-month period, with an evaluation at 12 and 24 months.

Comparison of the 3 intervention arms will occur at the population level by collecting deidentified data from the electronic health record reflecting AD completion (existence of an AD or POLST or outpatient DNR order and the date of the document), vital status, and healthcare utilization (hospitalization, ICU use, ED use, and location of death).

A Research cohort will be enrolled from the seriously ill population-based cohort that do not have an AD or POLST within the past three years by asking patients via mail, telephone, or in person whether they are willing to participate in an observational survey study. Interested patients will be asked to provide written informed consent to participate in up to 3 surveys: baseline, 12 months and 24 months. The surveys may be completed on a paper-and-pencil hard copy, completed by interview over the telephone, completed in person or completed over a secure web link, depending on patient preference. The surveys will ask about experience with and readiness for ACP, health status, preferences for healthcare and decision making, and demographics. If a patient is unable to be surveyed at month 12 or month 24, a caregiver will be approached for survey. If the patient dies, a caregiver will be asked to complete a survey about goal-concordant treatment, perceptions about care and satisfaction with care and communication. Patients will also be asked to consent to medical record review to evaluate documentation about ACP and measure goal concordant care. The principle outcome is AD completion at the population level using administrative data from the electronic health record.

Cluster randomized trial at the primary care clinic level

UC Health Care Planning Study

Population-based Comparison of Evidence-based, Patient-centered Advance Care Planning Interventions on Advance Directive Completion, Goal Concordant Care and Caregiver Outcomes for Patients With Advanced Illness

Hospitalization, ICU care and ER visits within 30 days of death will be compared among decedents of the three study arms using regression models to account for patients clustered within clinics including covariates of patient age, gender, race/ethnicity, serious illness category, clinic baseline advance directive completion rate, study site, time, study arm, and study arm-time interaction.

Advance care planning level of engagement and conversations based on survey (Sudore RL, Stewart AL, Knight SJ, McMahan RD, Feuz M, Miao Y, Barnes DE. Development and validation of a questionnaire to detect behavior change in multiple advance care planning behaviors. PLoS One. 2013;8(9):e72465).

Advance care planning level of engagement and conversations based on validated survey (Sudore RL, Stewart AL, Knight SJ, McMahan RD, Feuz M, Miao Y, Barnes DE. Development and validation of a questionnaire to detect behavior change in multiple advance care planning behaviors. PLoS One. 2013;8(9):e72465).

Proportion of patients that have advance care planning documentation (enduring advance directive, POLST or out-of-hospital DNR form in the electronic health record) at 12 months (or death) compared to baseline. Baseline date defined as the clinic intervention start date. Intention to treat analysis will use logistic regression models to account for patients clustered within clinics including covariates of patient age, gender, race/ethnicity, serious illness category, clinic baseline advance directive completion rate, study site, time, study arm, and study arm-time interaction.

Goal concordant care measured by patient/caregiver reports of receipt of preference concordant care based on questions from SUPPORT (Teno JM, Fisher ES, Hamel MB, Coppola K, Dawson NV. Medical Care Inconsistent with Patients' Treatment Goals: Association with 1-Year Medicare Resource Use and Survival. J Am Geriatr Soc. 2002;50(3):496-500. doi:10.1046/j.1532-5415.2002.50116.)

Advance care planning documentation (enduring advance directive, POLST or out-of-hospital DNR form in the electronic health record) among patients with no advance care planning documentation in the past three years. Baseline date defined as receipt of intervention. "As treated" analysis will use logistic regression models to account for patients clustered within clinics including covariates of patient age, gender, race/ethnicity, serious illness category, clinic baseline advance directive completion rate, study site, time, study arm, and study arm-time interaction.

Caregiver report of quality of end of life care among decedents based on the modified Bereaved Family Survey

Proportion of patients that have advance care planning documentation

Goal concordant care measured as match of care receipt to future care preference based on survey

Goal concordant care measured as caregiver post-mortem report goal concordant care (Teno JM, Freedman VA, Kasper JD, Gozalo P, Mor V. Is care for the dying improving in the United States? J Palliat Med. 2015;18(8):662-6).

University of California, San Francisco

University of California, Irvine

University of California, Los Angeles

Professor

Neoplasms

Skin and Connective Tissue Diseases

All Conditions

Breast Neoplasms

Breast Diseases

Skin Diseases

A mammogram order will be placed using bulk order technology in the EHR in advance of outreach for all patients.

Bulk Order

In addition to outreach, patients will receive text messaging with information regarding the importance of screening, how to schedule a mammogram, and locations available for mammography.

Texting

Outreach informing patients that they are overdue for a mammogram will be signed by the patient's primary care provider.

Clinician Endorsement

The outreach will ask patients to contact their PCP's office in order to have a mammogram order placed on their behalf.

No Bulk Order

Patient's will receive outreach from the practice informing them that they are overdue for a mammogram.

Standard Endorsement

Shivan Mehta, MD

This project aims to evaluate different approaches to increase breast cancer screening among primary care patients at Penn Medicine through a centralized screening outreach program. In a pragmatic trial, the investigators will evaluate different approaches to increase completion of screening among eligible patients, including ordering mammograms in bulk prior to outreach, sending personalized text reminders, and endorsing of the communication by the primary care provider.

While mammograms are recommended by guidelines for early detection of breast cancer, mammogram rates are significantly lower now than they were prior to the initial COVID-19 pandemic surge in early 2020. In this project, the investigators will evaluate different ways of reaching out to eligible patients to encourage them to participate in breast cancer screening. Through letters, texting, and the electronic health record portal (MyPennMedicine (MPM)), the investigators will compare mammogram bulk orders, text messaging, and primary care provider endorsement to traditional outreach messaging with the goal of increasing breast cancer screening uptake.

Breast Cancer Outreach Among Primary Care Patients

Percent of mammograms that have positive results

Percent of patients that complete a mammogram by age groups

Percent of patients that complete a mammogram by race/ethnicity

Percent of patients that complete a mammogram by insurance type

Percent of patients that complete a mammogram by Median Household Income by zip code

Percent of patients with a positive mammogram that receive subsequent care

Percent of patients that complete a mammogram by electronic patient portal status

Percent of patients that complete a mammogram

Abramson Cancer Center at Penn Medicine

Principal Investigator

The wellness landscape intervention (Wellscapes) will establish a multi-level system infrastructure (Community Hub, Organization Wellness Teams, Activity Setting/Leaders) and provide training and support for population health quality improvement cycle processes targeting two evidence-based practices (EBPs): (1) stacking time segments of PA episodes within an organization's daily routine, and (2) improving the quality of PA episodes (% time in PA).

The standard collective impact public health practice intervention will establish a multi-level system infrastructure and provide training on community development.

Community and organization systems intervention targeting youth population physical activity

Wellness Landscape Intervention

Standard Practice

David A Dzewaltowski, PhD

This study will evaluate the impact of a whole-of-community multi-level adaptive systems intervention on implementation of community change and youth population physical activity. Building on local health department partnerships, the investigators will conduct a two-wave staggered-start community randomized trial with four volunteer rural communities (each having nested school, after-school, scouting/4-H club, youth sport organizations) randomly assigned to intervention or standard public health practice.

The underlying conditions where youth live are associated with population health outcomes, with rural communities facing under-studied challenges. Youth physical activity (PA), a key risk factor linked to later cancer occurrence, is an outcome of community conditions. The proposed work will address a critical public health need by evaluating the impact of a whole-of-community multi-level adaptive systems intervention on implementation of community change and youth population PA. The intervention, Wellscapes, is based on a hierarchical patch dynamics paradigm, given that communities are "wellness landscapes" of spatially heterogeneous geographic areas, characterized by a patchwork of interacting organization and activity settings. The intervention will establish a multi-level system infrastructure (Community Hub, Organization Wellness Teams, Activity Setting/Leaders) and provide training and support for population health quality improvement cycle processes targeting two evidence-based practices (EBPs): (1) stacking time segments of PA episodes within an organization's daily routine, and (2) improving the quality of PA episodes (% time in PA). The omnibus hypothesis is that intervention communities (plus organizations and leaders nested within) will have synergy and capacity to implement EBPs, adapting to continuously changing local system drivers to create a whole-of-community ecosystem of diverse and equitable youth PA opportunities. Building on local health department partnerships, the investigators will conduct a two-wave staggered-start community randomized trial with four volunteer rural communities (each having nested school, after-school, scouting/4-H club, youth sport organizations) randomly assigned to intervention or standard public health practice. For baseline and intervention years, one day per month in the fall (3 days) and spring (3 days), organization activity settings (e.g., classrooms, teams) that house 480 children in 3rd through 6th grades will be assessed, resulting in observed community condition data, PA accelerometer data, and setting reach data (children % attendance by gender, ethnicity, free/reduced lunch status, and grade). The investigators will also obtain estimates of population level PA with the use of the calibrated Youth Activity Profile, as well as community system qualitative data. The specific aims are to: (1) Determine the impact of the intervention on multi-level community system outcomes; and (2) Determine the implementation system drivers of multi-level youth population PA. The investigators will use "big data" multi- level modeling methods for this effectiveness-implementation hybrid design, because there is a dual focus on testing an implementation strategy while simultaneously evaluating youth population PA impact. The research is significant because it evaluates a method for improving population health, theory-based systems, and behavior change processes in low-resource rural communities. The proposed research is novel because the adaptive patch dynamics approach builds capacity for both equitable collaboration and EBPs implementation across multiple local systems that are individually and collectively, dynamic and unpredictable.

This design can be described as a staggered-start, stepped-wedge, community randomized trial. The design includes two sequential intervention waves.

Whole-of-Community Youth Population Physical Activity

Whole-of-Community Systems Intervention for Youth Population Physical Activity

De-identified data for all primary and secondary outcome measures will be made available.

Average of school class, after-school class, youth club meeting, and youth sport practice physical activity

Average of observed frequency of implemented physical activity episodes in school class, after-school class, youth club meeting, and youth sport practices

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
UC Health Care Planning Study	NCT04012749	Advance Care Pl... Advance Directi... Advanced Cancer	Advance directi... Prepare Facilitator	18 Years -	University of California, Los Angeles
Breast Cancer Outreach Among Primary Care Patients	NCT05089903	Breast Cancer	Bulk Order Texting Clinician Endor... No Bulk Order Standard Endors...	40 Years - 74 Years	Abramson Cancer Center at Penn Medicine
Whole-of-Community Youth Population Physical Activity	NCT03380143	Physical Activi...	Wellness Landsc... Standard Practi...	7 Years - 12 Years	University of Nebraska
Breast Cancer Outreach Among Primary Care Patients	NCT05089903	Breast Cancer	Bulk Order Texting Clinician Endor... No Bulk Order Standard Endors...	40 Years - 74 Years	Abramson Cancer Center at Penn Medicine
Whole-of-Community Youth Population Physical Activity	NCT03380143	Physical Activi...	Wellness Landsc... Standard Practi...	7 Years - 12 Years	University of Nebraska
UC Health Care Planning Study	NCT04012749	Advance Care Pl... Advance Directi... Advanced Cancer	Advance directi... Prepare Facilitator	18 Years -	University of California, Los Angeles

Spots Global Cancer Trial Database for population health