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The University of Pennsylvania Health System (Penn Medicine) developed COVID Watch, an automated text message-based, remote monitoring program with 24/7 clinical support. Remote outpatient monitoring of patients with COVID-19 became needed because patients with SARS-CoV-2 infection can decline rapidly and unpredictably, and because of their own limited capacity to manage acute symptoms and concerns about staff safety, office-based outpatient practices often redirect patients with confirmed or suspected COVID-19 to hospitals. As a result, emergency departments (EDs) and hospitals became overwhelmed during surge periods of high community incidence rates and prevalence. Remote monitoring has the potential to facilitate ED- and hospital-level care for patients who require it while supporting access to care for patients who can safely remain at home.

This study compared outcomes for patients enrolled in COVID Watch with those of patients who were eligible to enroll but received usual care, with the hypothesis that enrollment in COVID Watch was associated with reduced mortality. The present research examined whether patients with COVID-19 who were enrolled in COVID Watch experienced better health outcomes compared with usual care (Aim 1) and whether augmenting COVID Watch with at-home monitoring of SpO2 (blood-oxygen saturation) improves patient outcomes (Aim 2).

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 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.

In the United States, tobacco smoking is associated with significant morbidity and premature mortality for individuals with serious mental illness (SMI) (e.g., schizophrenia, post-traumatic stress disorder, bipolar disorder, major depressive disorder). While many smokers with SMI wish to quit smoking, few are offered advice or treatments with demonstrated effectiveness in reducing tobacco dependence, primarily medication-assisted treatments. The overall aim of this randomized controlled trial was to test the effects of provider education (PE) (i.e. provider-level educational intervention focused on evidence-based smoking cessation treatment for those with SMI) and community health worker (CHW) support on the provision and utilization of smoking cessation treatment to those with SMI, and cessation rates for adults with SMI who smoke or use tobacco over a 2-year period. The objectives of this trial were to:

1. Examine whether an intervention combining PE and CHW support would increase prescriber provision of advice and assistance to quit smoking, and improve tobacco cessation rates in smokers with SMI compared to usual care/treatment as usual (TAU) and compared to PE-only treatment
2. Determine the effect of the combined PE+CHW intervention on patient-reported overall health compared to TAU and PE-only treatment

Eligible individuals were recruited from two outpatient psychiatric service providers in the Boston, Massachusetts metropolitan area. Clinics where individuals received services were randomized into either the TAU condition or into the PE condition, where health care providers would receive additional education on first-line medications used to treat tobacco use disorder. Within clinics in the PE arm, individuals were further randomized into the community health worker (CHW) support condition (PE+CHW), where CHWs would assist participants with smoking cessation care access and provide community outreach and education, or no CHW support (PE-only). Enrolled participants (n=1,010) completed surveys on smoking/tobacco use at 3 timepoints: study baseline, 1 year post-randomization, and 2 years post-randomization.

A mixed-methods evaluation of the trial was also conducted post-intervention, using an interactive convergent design. The aims of the evaluation were to identify barriers and facilitators to effective implementation; examine how primary care providers differed by performance and engagement level, and how experiences with the intervention compared across these groups; and identify anticipated barriers to implementing the intervention as discussed by stakeholders. Quantitative outcome and visit data from the trial were used in the evaluation. For the evaluation's qualitative component, interviews were conducted with purposively sampled community health workers, smoker participants, primary care providers, and other stakeholders in policy, payor, and clinical administration. Please note that the qualitative evaluation data are not available for this collection.

Using a pragmatic trial design to limit exclusions, the investigators conducted a 36-month multi-center randomized effectiveness trial to compare the impact of an enhanced usual care (control) intervention, with exercise coaching (exercise), on fragility fractures and serious fall-related injuries (FF/SFRI) in patients with a previous fragility fracture. Specifically, the investigators examined the impact of the intervention on social loneliness, physical function, and bone strength. 1,139 individuals over 65 with a history of fragility fractures and/or osteoporosis were recruited over two years across three regions of Pennsylvania and randomized into either the enhanced usual care control group or exercise with coaching treatment group, where in-person exercise activities were led by trained volunteers.

Dataset (DS) 1 contains the following data used for analysis: participant characteristics at baseline by study group (referred to as Table 5 in the documentation), intervention participant characteristics at baseline based on exercise session type (referred to as Table 6), cumulative incidences of first serious fall-related injury compared by study group (referred to as Figure 3), cumulative incidence for first serious fall-related injury by age, gender, race, and osteoporosis medication (referred to as Table 8 and Figure 4), and cumulative incidence for first series fall-related injury by tertile of average intervention sessions per month (referred to as Figure 5). Other datasets used for analysis are fall injury data (DS2), monthly workout sessions data (DS3), secondary outcomes data (DS4, referred to as Table 7), and adverse events data (DS5, referred to as Table 9). DS6 includes markers designating before and after the start of the COVID-19 pandemic (March 11, 2020), allowing for analyses of participants who experienced fall-related injuries relative to COVID-19.

Datasets labeled "Miscellaneous" were not used in any analysis. These datasets contain extra measures from screening (DS7), baseline assessments (DS8), 4-month check-in visits (DS9), participant's distance to study site (DS10), coaching check-ins for weeks 1-12 (DS11), exercise sessions by month (DS12), adverse events (DS13), and end of study information (DS14).

Comparative effectiveness research, or CER, compares two or more treatments. In some CER studies, researchers use patient data from electronic health records, or EHRs, to compare treatments. But patient traits like age may affect doctors' and patients' choice of treatments, which can bias results. Using EHR systems to identify eligible patients and assign them to treatments by chance could improve results of CER studies that use EHR data.

In this study, the research team explored the views of patients, clinic staff, and clinicians, such as doctors or nurses, on doing CER studies in clinics. The team also tested software with a widely used EHR system. The software finds patients who qualify for a study. During a clinic visit, the software prompts doctors to invite patients to take part in the study. If patients agree, the software assigns patients by chance to a treatment.

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.

This study addressed whether it is better to expand the scope of collaborative care programs to treat patients with more complex psychiatric disorders or to facilitate successful referrals to specialty mental health care. The primary objective of this study is to compare Telepsychiatry Collaborative Care (TCC) and Telepsychiatry Enhanced Referral (TER) from the patient and provider perspective. The secondary objective is to determine whether patients not engaging and responding to TER, improve with Phone-Psychiatry Enhanced Referral (PER). There are four specific aims.

Aim #1: To quantitatively compare the treatment experience, engagement, self-reported clinical outcomes, and recovery-oriented outcomes of patients initially randomized to TCC and TER.

Aim #2: For the subset of patients randomized to TER who do not engage in treatment and are still symptomatic at 6 months, quantitatively compare treatment experience, treatment engagement, self-reported clinical outcomes and recovery-oriented outcomes of patients randomized to continued-TER or PER.

Aim #3: To gain an in-depth understanding of patients' and providers' treatment experience, qualitatively compare those randomized to TCC, TER and PER.

Aim #4: To examine treatment heterogeneity among subgroups of patients randomized to TCC and TER based on race/ethnicity, age and clinical severity.