The National Home-Based Primary Care Learning Network: A Practice-Based Quality Improvement and Research Network

Home-based primary care (HBPC) provides interdisciplinary, comprehensive care at home for homebound older adults and has been largely excluded from the national conversation on care quality and quality improvement. In this Pragmatic Innovations article, we describe the work of the National HBPC Learning Network (LN), which focuses on fostering a continuous learning culture among HBPC practices to improve practice quality, elevate the field of HBPC, and create a community of continuous growth and quality of care accountability. The LN recruits HBPC practices in waves of 9 to 10 practices. It currently comprises 38 HBPC practices that care for 58,000 patients across 25 states (approximately 26% of all patients receiving HBPC in the United States). In a Kickoff meeting, the HBPC practices in each wave are instructed in the basics of quality improvement, develop project aim statements and their first plan-do-study-act cycle, receive an introduction to the LN quality improvement software platform, and review plans for LN engagement. Each month, practices submit updates and receive real-time feedback on their quality improvement work. Monthly virtual workshops are held with all practices that include sharing results of a “1-minute survey” (a monthly 1-to 3-question survey sent to all LN participants on a topic relevant to HBPC practices), a didactic and discussion related to the 1-minute survey topic, and interactive progress updates from LN participants regarding their quality improvement work. Each wave ends with “Moving-up Day,” where practices report on their overall project and reflect on how their practice has changed as a result of the LN. LN practices have addressed and improved performance in multiple HBPC-related quality areas including assessment of functional status and cognitive impairment, falls prevention, advanced care planning, COVID-19 vaccination, and others. We present case studies of 3 LN practices and how LN participation strengthened their practices.     

Nursing Home Resident Admission Characteristics and Potentially Preventable Emergency Department Transfers

ObjectivesTo determine which nursing home (NH) resident-level admission characteristics are associated with potentially preventable emergency department (PPED) transfers.DesignWe conducted a population-level retrospective cohort study on NH resident data collected using the Resident Assessment Instrument-Minimum Data Set Version 2.0 and linked to the National Ambulatory Care Reporting System for ED transfers.SettingWe used all NH resident admission assessments from January 1, 2017, to December 31, 2018, in Ontario.ParticipantsThe cohort included the admission assessment of 56,433 NH residents.MethodsPPED transfers were defined based on the International Classification of Disease, Version 10 (Canadian) We used logistic regression with 10-fold cross-validation and computed average marginal effects to identify the association between resident characteristics at NH admission and PPED transfers within 92 days after admission.ResultsOverall, 6.2% of residents had at least 1 PPED transfer within 92 days of NH admission. After adjustment, variables that had a prevalence of 10% or more that were associated with a 1% or more absolute increase in the risk of a PPED transfer included polypharmacy [of cohort (OC) 84.4%, risk difference (RD) 2.0%], congestive heart failure (OC 29.0%, RD 3.0%), and renal failure (OC 11.6%, RD 1.2%). Female sex (OC 63.2%, RD -1.3%), a do not hospitalize directive (OC 24.4%, RD -2.6%), change in mood (OC 66.9%, RD -1.2%), and Alzheimer's or dementia (OC 62.1%, RD -1.2%) were more than 10% prevalent and associated with a 1% or more absolute decrease in the risk of a PPED.Conclusions and ImplicationsThough many routinely collected resident characteristics were associated with a PPED transfer, the absence of sufficiently discriminating characteristics suggests that emergency department visits by NH residents are multifactorial and difficult to predict. Future studies should assess the clinical utility of risk factor identification to prevent transfers.     

Face Off: 3D-Printed Masks as a Cost-Effective and Reusable Alternative to N95 Respirators: A Feasibility Study

BackgroundOne of the best methods for protection against respiratory diseases is the use of an N95 mask. Supply shortages have demonstrated a significant need for effective alternatives to N95 masks. Benefits of 3D-printed respirators over N95s include reduced cost and ease of production, widespread availability, reusability/sterilizability, and customizability. 3D-printed mask designs have been downloaded thousands of times; however, there is little to no data on the efficacy of these potential alternatives.MethodsThree of the most popular 3D-printed respirator designs were modified to allow for the Occupational Safety and Health Administration (OSHA) quantitative fit testing that disperses saline into the ambient air and determines concentrations within the mask during multiple trials. Five volunteers conducted standardized fit tests of these masks, as well as an N95 and a KN95, and the results were compared.ResultsOne of the 3D-printed respirators, low poly COVID-19 face mask respirator (mask 2), achieved a fit factor greater than 100 in every trial, representing sufficient fit according to OSHA protocols. The N95 mask achieved a sufficient fit in 60% of the trials, and none of the remaining masks provided a suitable fit factor reliably according to the OSHA fit test. Further trials showed no change in fit factor when different 3D-printable plastics are used or when a widely available high efficiency particulate air (HEPA) filter was used.Conclusion3D-printed respirators provide a possible alternative to N95 masks to protect against respiratory pathogens such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Fit testing results demonstrate that certain 3D-printed mask designs may exceed the fit of N95 masks.     

Decline in skeletal muscle mass is associated with cognitive decline in type 2 diabetes mellitus

AimsTo examine the longitudinal association between skeletal muscle mass (SMM) loss and cognitive decline over time in type 2 diabetes mellitus (T2DM).MethodsWe conducted a prospective cohort study of 453 patients from SMART2D cohort with follow-up intervals of 1.6 to 6.4 years. Baseline and follow-up measurements included bio-impedance analysis (BIA) measure of skeletal muscle mass index (SMI) and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) measure of cognitive function. We examined the association between annual rate of SMI and RBANS scores using linear regression, adjusting for demographics, education, depression, clinical co-variables and presence of apolipoprotein E4 (APOE) _?4 allele.ResultsThe mean age of participants was 60.3 ± 7.4 years. Compared to patients with Tertile 1 SMI change, the group with greater SMI decline (Tertile 3 SMI change) experienced 0.30 decline in RBANS total score (95%CI ?0.57 to ?0.03; p = 0.030) in the adjusted analysis. RBANS scores for subdomains in immediate memory and visuo-spatial/construction were lower in Tertile 3 SMI change group with corresponding coefficients ?0.54 (95%CI ?1.01 to ?0.06; p = 0.026), and ?0.71 (95%CI ?1.30 to ?0.12; p = 0.019) respectively.ConclusionIn patients with T2DM, BIA measure of muscle mass loss over time was independently associated with cognitive decline globally and in the domains of memory and visuo-spatial/construction.     

Trends of self-reported non-adherence among type 2 diabetes medication users in the United States across three years using the self-reported Medication Adherence Reasons Scale

Background & aimsTo determine the trends of self-reported non-adherence rates among adults taking Type 2 medicines (T2D) medicines between 2017 and 2019 and to identify the patterns for the frequently reported reasons for non-adherence in the United States.Methods & resultsData from the National Health and Wellness Survey, a self-administered, internet-based cross-sectional survey of US adults from 2017 to 2019 was used. Non-adherence was measured using the self-reported Medication Adherence Reasons Scale (MAR-Scale). Frequencies were used to identify the reasons for non-adherence for insulin and non-insulin therapies for T2D.Data were obtained from 2983 respondents in 2017, 5416 in 2018, and 5268 in 2019. Based on the MAR-Scale, the self-reported medication non-adherence rate was 25% in 2017, 21% in 2018, and 27% in 2019. The most common reason for non-adherence across all the three years was simple forgetfulness, yet patients reported the lowest mean number of days missing medication for that reason. Though less frequently reported, non-adherence lasted longer when patient did not know how to take their medicines, cost was a reason, or had concerns about the long term effects of the medicines.ConclusionsWith no significant improvement in adherence with T2D medicines over time, regardless of better awareness and extensive diabetes education, focus should be on individualized non-adherence reasons-based interventions.     

Effect of recent seasonal influenza vaccination on serum antibody responses to candidate pandemic influenza A/H5N1 vaccines: A meta-analysis

Recent studies have suggested that among those receiving seasonal influenza vaccine (SIV), reduced immunogenicity is observed in recently vaccinated (RV; within the past season or 2) persons when compared with those not recently vaccinated (NRV). We performed a meta-analysis to assess the effect of recent immunization with SIV on serum H5 hemagglutination inhibition (HAI) antibody responses after influenza A/H5N1 vaccination using data from a series of randomized controlled trials. The primary outcome was seroconversion measured by HAI assays following receipt of 2 doses of H5N1 vaccine. The geometric mean titer (GMT) of serum HAI antibody after vaccination was the secondary outcome. Analyses were performed using propensity score (PS) matching. The PS for each individual in the meta-analysis cohort was calculated using logistic regression and covariates included age, gender, race, antigen dose, adjuvant, statin use and vaccine manufacturer. 2015 subjects enrolled in 7 clinical trials were eligible for inclusion in the meta-analysis cohort; among these, 915 (45%) were RV. 901 RV subjects were matched (1:1) with replacement to a subject who was NRV. Subjects who received SIV within the previous season were significantly less likely to seroconvert following H5N1 vaccination (adjusted odds ratio 0.76; 95%CI 0.60–0.96; p = 0.024), and the GMT was 18% higher among NRV subjects (GM ratio of HAI antibody 1.18; 95%CI 1.04–1.33; p = 0.008). Further work is needed to better define the effects of, and mechanisms contributing to, reduced immune responses to H5N1 vaccine among RV subjects.