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Patient decision aids help people choose between two or more healthcare options based on what is most important to them. Involving users, such as patients and clinicians, in developing decision aids may make them more useful.

User-centered design is a way to get users involved in creating products. Learning from projects that apply user-centered design may suggest ways to involve users more in developing patient decision aids. In this study, the research team reviewed studies about developing decision aids and studies about user-centered design.

For people with serious chronic conditions, healthcare that defaults to all available treatments without considering patient preferences risks harms that may exceed benefits. Advance care planning (ACP) has the potential to align healthcare with what is important to patients and maximize quality of life. While primary care is where most people receive most of their care, engaging patients in ACP is not routine in primary care given competing demands and limited resources. Primary care clinicians, patients, and families agree that it is preferred to make plans before there is a medical crisis. The research team's goal was to make ACP routine in primary care and to "move it upstream" so that it included improving the quality of the last years of life as well as respecting wishes for end of life care.

This study included a comparative effectiveness trial of team-based versus individual clinician-focused ACP in primary care practices. The research team adapted Ariadne Labs' Serious Illness Care Program (SICP) and aimed to determine if a team approach produces better patient outcomes and explore factors influencing implementation of ACP across practices.

Seven practice-based research networks (PBRNs) in the United States and Canada randomized their primary care practices to team-based or individual clinician-focused versions of SICP. Team members and clinicians completed training, and implementation was supported through practice facilitation. Consented patient participants completed a baseline survey after initial conversations and follow-up surveys at 6 and 12 months later. Forty practices (21 team, 19 clinician) completed training and referred patients to the study. Half of the practices were rural, 80 percent were family medicine, and 33 percent were medical residency training sites. 535 healthcare staff completed training. Both arms trained primary care providers; the team arm also trained nurses, medical assistants, and other roles. 1,321 patients and care partners were referred; and 917 consented and were enrolled (455 from team practices, 462 from clinician). Data from 802 patients were included in the primary analyses. Qualitative implementation data was collected during practice facilitation and from practice interviews.

This collection includes quantitative data collected from primary care practices (DS1) and team members and clinicians (DS2) from study sites located in the United States.

The Comprehensive Post-Acute Stroke Services (COMPASS) Study is a pragmatic cluster-randomized clinical trial that evaluated the real-world effectiveness of the COMPASS transitional care (COMPASS-TC) model compared to usual care among adult stroke and transient ischemic attack (TIA) patients discharged home between 2016 and 2018. In Phase 1, 40 North Carolina hospital units were randomized 1:1 to the COMPASS-TC intervention or usual care, stratified by stroke patient volume and stroke center certification. In Phase 2, hospitals randomized to usual care crossed over to implement COMPASS-TC, and hospitals randomized to the intervention sustained COMPASS-TC. The intervention was patient-centered and assessed social and functional determinates of health to inform individualized care plans for secondary prevention, recovery, and referrals to services and community-based resources. COMPASS-TC was consistent with Centers for Medicare and Medicaid Services (CMS) TC management reimbursement requirements.

The primary outcome was functional status (Stroke Impact Scale-16; SIS-16) at 90 days; secondary outcomes were mortality, disability, medication adherence, depression, cognition, self-rated health, fatigue, care satisfaction, home blood pressure monitoring, falls, and caregiver strain. Telephone interviewers, blinded to treatment assignment, assessed these outcomes at 90 days.

Community-engaged research is an umbrella term for forms of research that have community and stakeholder engagement as a core principle, for example, patient-centered outcomes research (PCOR), participatory action research, and community-based participatory research. However, the implementation and category of community engagement can vary across a spectrum from minimal engagement to fully collaborative engagement. A major methodological gap is the assessment of stakeholder engagement from a stakeholder perspective. Evaluation of the impact of stakeholder engagement on research development, implementation, and outcomes requires the development and validation of tools that assess engagement. This study's objective was to develop and validate comprehensive and condensed versions of a survey instrument that will be completed by stakeholders and used to assess engagement in research studies from a stakeholder perspective.

Patient-reported outcome measures, or PROMs, ask patients how they feel and what activities they can do in daily life. Patients receiving cancer treatment, such as chemotherapy, often have side effects. PROMs can help cancer centers know if patients are getting high-quality care that helps manage their side effects.

In this study, the research team wanted to

• Learn from patients and clinicians, like doctors and nurses, what side effects are important to track during chemotherapy
• Create PROMs that can measure important side effects of chemotherapy

The research team also wanted to test the PROMs to see

• If patients find them easy to complete
• If the PROMs can detect differences in how well cancer centers control patients' treatment side effects

The way doctors communicate with patients during office visits can affect the quality of care. Studying conversations between doctors and patients can help doctors improve their communication skills.

To study conversations, researchers rely on written records, or transcripts, of office visits. They read the transcripts and give each conversation topic a label. For example, topics may include smoking or pain. But labeling topics in this way may take a lot of time.

In this project, the research team created and tested a new method to make this work easier using natural language processing, or NLP. With NLP, computer programs interpret written language. NLP methods use a process called machine learning, where computer programs use data to learn how to perform different tasks with little or no human input.

During the COVID-19 pandemic, telemedicine emerged as the primary method of providing outpatient care in many regions with shelter-in-place and social distancing policies. This study aimed understand the impact of this rapid and widespread transition from in-person to remote visits on disparities in access to primary care, especially in chronic disease where ongoing communication between providers and patients is essential.

The newly developed or expanded telemedicine programs varied widely, raising questions about the effect of these differences on uptake of telemedicine among different patient populations and on patient-centered outcomes. Leveraging a natural experiment approach, this study examined rapidly changing telemedicine and in-person models of care during and after the COVID-19 crisis to determine whether certain patients could safely choose to continue telemedicine or telemedicine-supplemented care, rather than return to in-person care.

A patient's preference for a treatment may affect how well the treatment works. For example, if patients prefer a specific medicine, they may be more likely to take that medicine.

Traditional randomized clinical trials can't tell how much patient preferences affect how well a treatment works. But a two-stage clinical trial might. In a two-stage trial, researchers assign patients by chance to one of two groups. In the first group, researchers assign patients by chance to get a specific treatment, regardless of their preference. In the second group, patients choose their treatment. In a two-stage trial, researchers can compare health outcomes for patients who choose their treatment with patients who don't. But few methods exist for researchers to design and analyze this type of trial.

In this project, the research team developed new statistical methods for two-stage trials. The team wanted to find out how many patients are needed for two-stage trials to provide accurate results. They also wanted to learn how to measure whether patient preference for a specific treatment affects patients' health outcomes.

To access the software, methods and R package, please visit the preference CRAN webpage and preference GitHub.

A learning health system, or LHS, is a health system that constantly looks for new ways to improve patient care. At an LHS, doctors and other hospital staff use learning activities to improve care, put what they've learned into practice, and share findings with other hospitals. Activities may include doing studies that compare treatments to see which one works better for which patients.

Governance refers to the way LHSs oversee learning activities. Governance includes people, committees, and policies that regulate learning activities. Including patients as partners in governance helps make sure learning activities address what's important to patients and protect patients' rights and interests. But LHSs don't always include patients in governance.

In this study, the research team wanted to learn how LHSs include patient partners in governance. The team interviewed patients and health system leaders to answer this question.

During care transitions, patients move from one care setting to another, such as from the hospital to home. If not done well, these care transitions can result in health problems for patients and the need for them to return to the hospital.

Healthcare organizations can use patient surveys to measure the success of care transitions. One survey about the quality of care transitions already exists. The survey was created with input from patients but with no input from caregivers and healthcare providers. In addition, the survey doesn't ask about topics that patients may find important, such as caregiver involvement and the time after care transitions.

In this study, the research team created and tested a new survey. To create the survey, the team asked for input from patients, caregivers, and healthcare providers. The team tested whether the survey was

• Valid, or able to correctly capture what it intends to measure
• Reliable, or able to get consistent answers

The BRITE study (Brain Injury Rehabilitation: Improving the Transition Experience) was a six-center, 1:1 randomized controlled pragmatic trial with masked outcome assessment that compared the effectiveness of two established approaches to managing transition from inpatient rehabilitation facility discharge to the next phase of care for individuals with moderate-to-severe traumatic brain injury (TBI). The two established transition methods were (1) a standardized version of existing discharge procedures used at all six sites and (2) a standardized remotely-delivered case management approach that extended beyond the point of discharge, based on the protocol used within the Veteran's Health Administration and enhanced with input from patient and family stakeholders. The sample was stratified by site and discharge location (skilled nursing facility vs. discharge to home/community) based on the relatively lower frequency of discharge to facility (22 percent across all six study sites in 2015) and the expectation of high impact of discharge destination on outcomes. When a caregiver was available for an enrolled patient, they were also approached for consent to be surveyed, with some patients having up to two caregivers enrolled to account for changes in primary caregiver.

The following key outcome domains were assessed: (1) ability of patients to participate in the home and community as independently as possible, (2) health-related quality of life, (3) access to appropriate healthcare and reduced emergent or urgent healthcare, and (4) caregiver outcomes. These outcomes were assessed at 3, 6, 9 and 12 months after discharge from inpatient care. Participants were also given the standard TBI Model Systems follow-up assessment one-year post-injury. Types of medical insurance coverage and satisfaction with healthcare were examined at 6 and 12 months post-discharge.

Imaging tests, such as X-rays and MRIs, can help find health problems. When assessing how well the tests work, accuracy is important. But other benefits and harms, such as having pain from the test or relieving worry by knowing test results, may also matter to patients.

In this study, the research team wanted to learn what effects of imaging tests matter to patients.

Black and Latinx patients bear a disproportionate burden of asthma. Efforts to reduce the disproportionate morbidity have been mostly unsuccessful, and guideline recommendations have not been based on studies in these populations. PREPARE (PESRAMHIP) is a pragmatic, open-label trial of 1201 randomly assigned African American/Black and Hispanic/Latinx adults with moderate-to-severe asthma to use a patient-activated, reliever-triggered inhaled corticosteroid strategy (PARTICS) plus usual care (intervention) or to continue usual care.

Participants had one in-person visit to consent, randomize and collect baseline data followed by 15 monthly questionnaires. The primary end point of this study was the annualized rate of severe asthma exacerbations. Secondary end points included monthly asthma control as measured with the Asthma Control Test (ACT; range, 5 [poor] to 25 [complete control]), quality of life as measured with the Asthma Symptom Utility Index (ASUI; range, 0 to 1, with lower scores indicating greater impairment), and participant-reported missed days of work, school, or usual activities. Safety was also assessed.

Patients treated for metastatic cancer, or cancer that has spread to another part of the body, often have symptoms from cancer and its treatment. They may feel tired, depressed, or nauseated. They may find it hard to do their usual activities. Better symptom tracking may help improve patients' care. For example, symptom tracking could quickly alert doctors when a patient may need a different medicine. In this study, the research team compared use of a weekly electronic symptom tracking system versus usual care for patients with cancer. Patients receiving usual care could report their symptoms to their care team during regular clinic visits. The research team wanted to see if the tracking system helped patients live longer, have better quality of life, or go to the hospital or emergency room less often. The aims of this study were as follows:

1. Determine whether integrating electronic patient-reported outcomes (ePRO) in cancer care improves patient-centered outcomes;
2. Elicit perspectives about benefit burden tradeoffs for integrating patient-reported outcomes into clinical workflow; and
3. Identify barriers, facilitators, and strategies used by practices to integrate patient-reported outcomes into clinical workflow.

A total of 1,191 patients were enrolled from 52 U.S.-based community oncology practices. Randomization into intervention and control conditions occurred at the site level. Data collected as part of this study included patient clinical information; weekly symptom surveys, quality of life surveys, and cancer care surveys completed by patients; feedback on the ePRO intervention from patients, clinical research associates, nurses, and physicians; and symptom alerts sent to nursing staff. Please note that while qualitative data were collected as part of this study, they are not available.

This study consists of a two-group, randomized, controlled comparative effectiveness trial with 300 individuals from Appalachian Kentucky who do not have a primary care provider (and thus are not able to receive the standard of care without intercession) and who are at risk for CVD (cardiovascular disease) by virtue of having two or more modifiable CVD risk factors. The researchers compared (1) the standard of care alone, referral to a primary care provider for management of CVD risk factors, with (2) standard of care supplemented by patient-centered, culturally appropriate, self-care CVD risk reduction intervention (HeartHealth) designed to improve multiple CVD risk factors while overcoming barriers to success.

The researchers compared the 4 month (short-term) and 1 year (long-term) impact of the interventions on: 1) CVD risk factors selected by patients (i.e., tobacco use, blood pressure, lipid profile, HgA1c for diabetics, body mass index, waist circumference, depressive symptoms, or physical activity level); 2) all CVD risk factors for each patient; 3) quality of life; 4) patient and healthcare provider satisfaction; 5) desirability and adoptability by assessing adherence to recommended CVD risk reduction protocols, and retention of recruited individuals.

Demographic variables include gender, age, ethnicity, marital status, employment status, and level of education.

Organizations that fund research often seek input on which topics are important to study. Patients can take part in setting priorities for research to help make sure that future studies focus on the topics that matter most to them. Researchers can collect patients' views on which research topics are most important in different ways.

In this study, the research team compared three methods of research priority setting:

• Online crowd voting, where patients submit, discuss, and vote on ideas online
• Focus groups with nominal group technique, where patients come up with ideas on their own and then discuss those ideas in a group with a moderator
• Modified Delphi method, where patients give input through a series of mailed surveys

The research team looked at research topic rankings and experiences with each method among patients with low back pain.

Electronic health records, or EHRs, have information about a patient's health such as test results, diagnoses, and treatments. EHRs also have clinical notes that doctors and patients can use to track goals and decisions.

Clinical notes may be useful for research or to help improve care. But it's hard to get information from these notes across large groups of patients. The notes may use different ways to describe the same thing. For example, high blood pressure may be called hypertension. Also, the notes may use abbreviations or have spelling mistakes.

In this project, the research team designed and built a search engine to make EHR notes easier to search and use for patient care and research.

Researchers can use data on patient traits such as age, health problems, and treatment preferences, to create personalized treatment rules, or PTRs. PTRs provide doctors with guidance on how to treat patients' health problems based on their traits. But PTRs based on a single data source may not apply to all patients. For example, if researchers create a PTR using data from older people with heart failure, it may not apply to younger people with heart failure.

To avoid this problem, researchers can create PTRs by combining data from many sources. PTRs based on many data sources can help guide treatment for patients with different traits.

In this study, the research team created and tested a new method for creating PTRs using data from multiple sources.