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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).

Research that focuses on what's most important to patients can inform health decisions. Researchers use different methods to identify what's most important to patients.

In this study, the research team compared two methods for identifying what's most important to patients: one-on-one interviews and group concept mapping, or GCM. GCM is a three-round process that helps researchers get input from a group. In the first round, people brainstorm topics that are important to them. Next, people sort the topics into clusters based on similar ideas. Finally, researchers create a map to display and discuss the topics. Researchers can use the complete GCM process or the brainstorming round only.

The research team looked at one-on-one interviews versus GCM and compared the number of topics patients named and the amount of time and money required.

Amplification is an evidence-based front-line treatment for those with impaired communication secondary to Age Related Hearing Loss (ARHL). ARHL is the most prevalent cause of communication impairment among older adults and multiple existing evidence-based care models exist to address it. This study compared the two most common models of care (defined below) for ARHL provided to adults in assisted living/personal care communities.

• The Consult Model (i.e., usual care) was an acute care strategy, relying on a monthly Audiologist visit to the facility.
• The Engage Model was a chronic care approach to supportive hearing loss self-management of ARHL. Engage includes (a) hearing screening for all residents, (b) an individualized communication plan for those with an identified hearing loss (e.g., one-to-one, group, telephone, television plans, hearing aid trouble shooting, communication strategies, etc.), (c) provision of simple, non-custom amplifiers, (d) referral to audiology if needed, and (e) ongoing support provided by trained personnel (Communication Facilitator) under the supervision of the audiologist.

This study included three separate sample populations at 10 medical facilities. The staff at the medical facilities were selected to measure job satisfaction (DS1). Residents of the medical facilities were sampled to collect measures related to the impact of hearing on an individual's life and general demographics (DS2 and DS3). And the family of the residents were sampled to measure caregiver burden (DS4).

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).

Medical devices, such as pacemakers or stents, can help diagnose, treat, or prevent health problems. Companies that make medical devices label them with unique device identifiers, or UDIs. UDIs contain data about a device, such as the make, model, and expiration date. Healthcare providers can scan UDIs when they use the devices and record UDI data in patients' health records.

Right now, UDI data can only be accessed by the health systems that use the devices. Having the UDI data in insurance claim forms, instead of only in patients' health records, would mean that researchers could look at data over time and across health systems. They could then use these data to help monitor devices for safety or study questions like how well devices are working.

In this study, the research team created ways to send UDI data from health systems to insurance claims forms.

The TARGET (Targeted Interventions to Prevent Chronic Low Back Pain in High-Risk Patients) Trial was a primary care-based, multisite, cluster randomized, pragmatic trial comparing guideline-based care (GBC) to GBC + referral to Psychologically Informed Physical Therapy (PIPT) for patients presenting with acute lower back pain (LBP) and identified as high risk for persistent disabling symptoms. Chronic lower back pain (LBP) is defined as a response of "more than three months" to question 1, and a response of "half the days or more than half the days" in the past 6 months to question 2. See Appendix 1 for the LBP Questionnaire in the Protocol report.

Study sites included primary care clinics within each of four geographical regions in the United States, with clinics randomized to either GBC or GBC+PIPT. Acute LBP patients at all clinics were risk stratified (high, medium, low) using the STarT Back Tool. The primary outcomes were the presence of chronic LBP and LBP-related functional disability determined by the Oswestry Disability Index at 6 months. Secondary outcomes were LBP-related processes of health care and utilization of services over 12 months, determined through electronic medical records.

Study enrollment began in May 2016 and concluded in June 2018. The trial was powered to include at least 1,860 high-risk patients in the cluster-randomized controlled trial cohort. A prospective observational cohort of approximately 6,900 low and medium-risk acute LBP patients was enrolled concurrently.

This data collection contains a single data file with 223 variables and 9,730 cases. The number of respondents at each of the study locations were:

• Boston Medical Center: 997 respondents
• Intermountain Health (Salt Lake City): 2,094 respondents
• Johns Hopkins University (Baltimore): 1,615 respondents
• University of Pittsburg Medical Center: 5,024 respondents