How Pragmatic are Trials in International Nursing Home Settings?

Join us as this presenter discusses this poster live on Tuesday, August 11, 2020 | Track B at 4:35 PM Mountain

PRESENTER
KATE MAGID
Health Science Specialist, Rocky Mountain Regional Veterans Affairs Medical Center
INTRODUCTION
At the 2019 AMDA-The Society for Post-acute and Long-term Care Medicine symposium, researchers discussed the implementation of pragmatic trials in nursing homes. Relatively few pragmatic trials have been conducted in nursing homes. In this abstract, we review the extent to which the design and implementation of trials presented at the AMDA symposium were pragmatic with a goal of describing approaches to improve pragmatic nursing home research study design.
POPULATION
All trials were conducted in nursing homes, with sample sizes ranging from 12- 175 homes.1-6 Trials were conducted Europe and the United States. Participants varied by study and included nursing home residents, nursing home staff, and caregivers.
METHODS
We used the Pragmatic Explanatory Continuum Indicator Summary (PRECIS-2) criteria to rate the pragmatic nature of the trials.7-8 Given that these trials were conducted at the level of the nursing home, reviewers rated recruitment and eligibility for nursing homes and residents separately. Subsequently, the reviewers discussed ratings and came to consensus. A PRECIS wheel was constructed for each trial to visually represent where the trial aligned on the explanatory-pragmatic continuum.
RESULTS
Figure 1 shows the PRECIS-2 wheels summarizing the pragmatic nature of the trials. Using PRECIS-2 criteria, the domains identified as most pragmatic across the trials were setting, primary outcome, and primary analysis. All studies were conducted in nursing homes that resembled usual care, collected primary outcomes relevant to participants, and almost all conducted an intention-to-treat analysis. In contrast, organization, nursing home recruitment, and nursing home eligibility were the least pragmatic. Several trials hired staff for intervention delivery or evaluation, implemented trainings, or provided resources beyond what is available in usual care, thus making the organization domain more explanatory. The eligibility criteria and recruitment for nursing homes were less pragmatic due to excluding homes based on; resident census, location, existing interventions and recruiting homes through advertisements or mailings. Four trials required residents or their legal guardian to provide informed consent to participate, making resident recruitment less pragmatic.
CONCLUSIONS
The application of PRECIS-2 criteria to the trials presented at the AMDA symposium suggests that the implementation of pragmatic trials in nursing homes have pragmatic and explanatory components. Future studies should explore how requiring residents to provide consent might lead to participants not being fully representative of the usual care population, especially given the prevalence of dementia in nursing homes. To better suit cluster pragmatic trials, researchers should rate the eligibility and recruitment of facilities and participants separately.
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EHR Data Mining to Understand Trends in Association of Systemic Health Factors and Tooth Loss

Join us as this presenter discusses this poster live on Tuesday, August 11, 2020 | Track A at 5:45 PM Mountain

PRESENTER
NAYANJOT KAUR RAI
Research Associate, University of Colorado School of Dental Medicine and Clinics
BACKGROUND
Tooth loss is a major contributing factor to oral health quality of life. Retaining at least 20 natural teeth is essential to maintain functional and aesthetic dentition throughout life. Tooth loss has been linked to some systemic diseases including, cardiovascular diseases (CVD) and diabetes and self-reported poor health status. We aim to evaluate the association of systemic health factors, including CVD, diabetes and tobacco use with tooth loss in patients visiting the University of Colorado School of Dental Medicine (SDM) clinics over four years. Also, we aim to analyze the trends in this association for the four consecutive years, 2017, 2018, 2019, and 2020.
METHODS
Data was collected through mining the electronic health records (EHRs) by the firstyear dental students and third-year advanced degree international dental students and 2709 current patients were included (≥55 years of age). The EHRs were reviewed for age, gender, ethnicity, self-reported systemic diseases including, CVD, diabetes, and tobacco use and the number of natural teeth present in the oral cavity(<20: yes/no), which was chosen as the outcome of interest. Univariate and multivariate logistic regression analysis was performed to test the association between patients having <20 natural teeth and self-reported systemic diseases. Also, trends in the odds of having <20 teeth and percentage of <20 teeth in the oral cavity varying by reported systemic health factors were analyzed.
RESULTS
Of the 2709 patients, 37% had <20 natural teeth. The odds of having <20 teeth were higher in patients who reported having CVD (OR=1.3, 95% CI=1.1, 1.5, p=0.0007) and diabetes (OR=1.6, 95% CI=1.4, 2.0, p<0.0001) compared to patients who did not report CVD and diabetes respectively. Similarly, the odds of having <20 teeth were found to be more than two times greater in patients reporting tobacco use (OR=2.4, 95% CI=1.8, 3.0, p=<0.0001) compared to patients who never used tobacco. The trends analysis results demonstrated an increase in the odds of having <20 teeth from the years 2017 to 2019 in the adults who reported having diabetes followed by a decrease in 2020 (Figure 1). The odds of having <20 teeth increased in adults reporting CVD over the four years (Figure 1a). An overall increasing trend in the odds of having <20 teeth was also seen in adults reporting tobacco use.
CONCLUSIONS
The results have shown that patients reporting CVD, diabetes, and tobacco use are more likely to have tooth loss, and the odds have increased since 2017. The results indicate the need for educational programs to educate the SDM patients and students. The knowledge gained can lead to the design and implementation of evidence-based interventions at the school and community levels, thereby benefiting the overall health of the population.
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Acceptability of Sharing Behavioral Risk and Glucose Data Between Patients and Clinicians – A Pilot Study

Join us as this presenter discusses this poster live on Tuessday, August 11, 2020 | Track C at 5:15 PM Mountain

PRESENTER
AMY HUEBSCHMANN
Associate Professor, Clinician-Investigator, Division of General Internal Medicine, University of Colorado Center for Women’s Health Research
BACKGROUND
Medically complex patients with uncontrolled type 2 diabetes face diabetes self-management challenges, including managing blood glucose levels and lifestyle behaviors. Technology packages have improved clinical outcomes by allowing patients to share data with clinic teams on home glucose (Glooko©) and behavioral health risk data (My Own Health Report, MOHR). However, adoption of Glooko and MOHR remains low in primary care. In a pilot study to inform implementation efforts, we evaluated the acceptability of Glooko/MOHR among key stakeholders: patients and clinicians.
POPULATION
We recruited eligible patients with uncontrolled type 2 diabetes mellitus (Hemoglobin A1c >8%) and their treating clinicians from three academic primary care clinics.
METHODS
Participants provided acceptability ratings after a demonstration of the process of sharing Glooko/MOHR data between patients and clinicians. We considered ratings of ≥ 70% in each of the 7 Technology Acceptance Model (TAM) domains as acceptable. All quantitative data are reported as mean ± SD. We considered survey ratings of 70-80% and >80% as moderately and highly acceptable, respectively.
RESULTS
Patients enrolled (n=12) were adults (age = 65.7 ± 12.8 years), 33% non-white, 58% female, and 50% reported use of internet to manage health issues. Clinicians (n=11) had 13.2 ± 9.9 years of practice experience. Patient acceptability for Glooko data sharing: Intention to use (91.5±12%), Perceived usefulness (89.5±8.1%) and Social influence (83±0%). No unacceptable ratings. Patient acceptability for MOHR data sharing: Perceived usefulness (85.5±8.1%), Self-efficacy (83.5±12%) and Social influence (83±0%). One TAM domain was rated as unacceptable: Resistance to change (58.5±12%), including 33% of patients agreeing that s/he did not want MOHR to change how s/he managed diabetes. Clinician (n=11) acceptability of sharing Glooko and MOHR data: Highest ratings were for Perceived usefulness (88.1 ± 4.2%), Facilitators (84.2 ± 8.6%) and Intention to use (82 ± 15.6%). The Subjective Norms/Others’ support was unacceptably rated (50.2 ± 16%), including anticipation of low perceived support among patients (27%), colleagues (55%), and health managers (55%).
CONCLUSIONS
Medically complex patients with diabetes and their clinicians expressed intention to use technology to share glucose and behavioral risk data between visits. However, to reach the promise of using remote technology and patient-reported data to address health challenges, clinics will need to identify and address factors leading to clinicians’ perceptions of limited support from others to use remote data monitoring, particularly patients, and also better discern why some patients are resistant to using MOHR as part of their diabetes management.
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