Patient Perceptions of their COVID-19 Inpatient Hospital Experience: a Survey Exploring Inequities in Healthcare Delivery.

BACKGROUND: Compared with White patients, Black and Latinx patients have higher infection, hospitalization, and mortality rates from COVID-19; yet, little is known about their perspective before, during, and after a COVID-19 hospitalization. The objective of this study conducted in White, Black, and Latinx patients was to assess perceptions of their COVID-19-related hospitalization from onset of symptoms through the post-discharge period to identify disparities in their perceived care. METHODS: A cross-sectional observational study using an online survey from May 19 to June 23, 2021, was conducted by The Harris Poll in 200 White, 200 Black, and 201 Latinx patients hospitalized for COVID-19 in the US. Main measures obtained included baseline demographic variables, socioeconomic status, and social determinants of health. Survey questions were specific to key aspects of the patient experience before, during, and after a COVID-19-related hospitalization. RESULTS: Compared with White patients, Latinx and Black patients faced unique challenges in their healthcare journey including higher likelihood of delaying their hospitalization (10% Black vs. 4% White patients, respectively, P = 0.025), lower perceived satisfaction with care (82% Latinx vs 91% White patients, P = 0.002), and lower trust in providers following their hospitalization (85% White vs. 65% Latinx [P = 0.027] and 73% Black [P = 0.050] patients). CONCLUSIONS: Patient perceptions of their COVID-19 hospitalization experience revealed disparities in perceived quality of care among minority groups. These findings offer insights that health inequities still exist, and strategies need to be taken to make health care delivery more equitable.

Estimating the Gender Distribution of Patients with Wild-Type Transthyretin Amyloid Cardiomyopathy: A Systematic Review and Meta-Analysis.

INTRODUCTION: This study investigates the gender distribution in patients diagnosed with wild-type transthyretin amyloidosis cardiomyopathy (ATTRwt). METHODS: A systematic review and meta-analysis of the male proportion in diagnosed ATTRwt patients were conducted. To avoid overlapping population, pooled estimates in the primary analysis were based on all unique studies. In secondary analyses, we considered predefined subsets of studies based on study sample size, recruitment years, geography, study design, age at diagnosis, and method of diagnosis. Additional meta-regression analyses were tested for potential determinants of gender distribution. RESULTS: Twenty-eight unique studies (2542 patients) were included in the meta-analysis. Male proportion in patients with ATTRwt was 86.9% (95% confidence interval 81.5-91.6%). Studies, including patients older than 80 years at diagnosis, had a 29.1% (p value < 0.001) lower male proportion compared to studies, including younger patients. After adjusting for age, studies using autopsy as a method of diagnosis had a 21.1% (p value 0.002) lower male proportion compared to other studies. CONCLUSIONS: Studies conducted to date suggest ATTRwt disproportionally affects males. The proportion of males was significantly impacted by the age at diagnosis and method diagnosis, which may suggest important gender-based differences in the clinical manifestation and diagnostic challenges of ATTRwt in females that warrant future research.

Provider- and Patient-Related Barriers to and Facilitators of Digital Health Technology Adoption for Hypertension Management: Scoping Review.

BACKGROUND: The uptake of digital health technology (DHT) has been surprisingly low in clinical practice. Despite showing great promise to improve patient outcomes and disease management, there is limited information on the factors that contribute to the limited adoption of DHT, particularly for hypertension management. OBJECTIVE: This scoping review provides a comprehensive summary of barriers to and facilitators of DHT adoption for hypertension management reported in the published literature with a focus on provider- and patient-related barriers and facilitators. METHODS: This review followed the methodological framework developed by Arskey and O'Malley. Systematic literature searches were conducted on PubMed or Medical Literature Analysis and Retrieval System Online, Cumulative Index to Nursing and Allied Health Literature, and Excerpta Medica database. Articles that reported on barriers to and/or facilitators of digital health adoption for hypertension management published in English between 2008 and 2017 were eligible. Studies not reporting on barriers or facilitators to DHT adoption for management of hypertension were excluded. A total of 2299 articles were identified based on the above criteria after removing duplicates, and they were assessed for eligibility. Of these, 2165 references did not meet the inclusion criteria. After assessing 134 studies in full text, 98 studies were excluded (full texts were either unavailable or studies did not fulfill the inclusion criteria), resulting in a final set of 32 articles. In addition, 4 handpicked articles were also included in the review, making it a total of 36 studies. RESULTS: A total of 36 studies were selected for data extraction after abstract and full-text screening by 2 independent reviewers. All conflicts were resolved by a third reviewer. Thematic analysis was conducted to identify major themes pertaining to barriers and facilitators of DHT from both provider and patient perspectives. The key facilitators of DHT adoption by physicians that were identified include ease of integration with clinical workflow, improvement in patient outcomes, and technology usability and technical support. Technology usability and timely technical support improved self-management and patient experience, and positive impact on patient-provider communication were most frequently reported facilitators for patients. Barriers to use of DHTs reported by physicians include lack of integration with clinical workflow, lack of validation of technology, and lack of technology usability and technical support. Finally, lack of technology usability and technical support, interference with patient-provider relationship, and lack of validation of technology were the most commonly reported barriers by patients. CONCLUSIONS: Findings suggest the settings and context in which DHTs are implemented and individuals involved in implementation influence adoption. Finally, to fully realize the potential of digitally enabled hypertension management, there is a greater need to validate these technologies to provide patients and providers with reliable and accurate information on both clinical outcomes and cost effectiveness.

Predictive Modeling of 30-Day Emergency Hospital Transport of Patients Using a Personal Emergency Response System: Prognostic Retrospective Study.

BACKGROUND: Telehealth programs have been successful in reducing 30-day readmissions and emergency department visits. However, such programs often focus on the costliest patients with multiple morbidities and last for only 30 to 60 days postdischarge. Inexpensive monitoring of elderly patients via a personal emergency response system (PERS) to identify those at high risk for emergency hospital transport could be used to target interventions and prevent avoidable use of costly readmissions and emergency department visits after 30 to 60 days of telehealth use. OBJECTIVE: The objectives of this study were to (1) develop and validate a predictive model of 30-day emergency hospital transport based on PERS data; and (2) compare the model's predictions with clinical outcomes derived from the electronic health record (EHR). METHODS: We used deidentified medical alert pattern data from 290,434 subscribers to a PERS service to build a gradient tree boosting-based predictive model of 30-day hospital transport, which included predictors derived from subscriber demographics, self-reported medical conditions, caregiver network information, and up to 2 years of retrospective PERS medical alert data. We evaluated the model's performance on an independent validation cohort (n=289,426). We linked EHR and PERS records for 1815 patients from a home health care program to compare PERS-based risk scores with rates of emergency encounters as recorded in the EHR. RESULTS: In the validation cohort, 2.22% (6411/289,426) of patients had 1 or more emergency transports in 30 days. The performance of the predictive model of emergency hospital transport, as evaluated by the area under the receiver operating characteristic curve, was 0.779 (95% CI 0.774-0.785). Among the top 1% of predicted high-risk patients, 25.5% had 1 or more emergency hospital transports in the next 30 days. Comparison with clinical outcomes from the EHR showed 3.9 times more emergency encounters among predicted high-risk patients than low-risk patients in the year following the prediction date. CONCLUSIONS: Patient data collected remotely via PERS can be used to reliably predict 30-day emergency hospital transport. Clinical observations from the EHR showed that predicted high-risk patients had nearly four times higher rates of emergency encounters than did low-risk patients. Health care providers could benefit from our validated predictive model by targeting timely preventive interventions to high-risk patients. This could lead to overall improved patient experience, higher quality of care, and more efficient resource utilization.

Evaluating the Impact of a Web-Based Risk Assessment System (CareSage) and Tailored Interventions on Health Care Utilization: Protocol for a Randomized Controlled Trial.

BACKGROUND: Soaring health care costs and a rapidly aging population, with multiple comorbidities, necessitates the development of innovative strategies to deliver high-quality, value-based care. OBJECTIVE: The goal of this study is to evaluate the impact of a risk assessment system (CareSage) and targeted interventions on health care utilization. METHODS: This is a two-arm randomized controlled trial recruiting 370 participants from a pool of high-risk patients receiving care at a home health agency. CareSage is a risk assessment system that utilizes both real-time data collected via a Personal Emergency Response Service and historical patient data collected from the electronic medical records. All patients will first be observed for 3 months (observation period) to allow the CareSage algorithm to calibrate based on patient data. During the next 6 months (intervention period), CareSage will use a predictive algorithm to classify patients in the intervention group as "high" or "low" risk for emergency transport every 30 days. All patients flagged as "high risk" by CareSage will receive nurse triage calls to assess their needs and personalized interventions including patient education, home visits, and tele-monitoring. The primary outcome is the number of 180-day emergency department visits. Secondary outcomes include the number of 90-day emergency department visits, total medical expenses, 180-day mortality rates, time to first readmission, total number of readmissions and avoidable readmissions, 30-, 90-, and 180-day readmission rates, as well as cost of intervention per patient. The two study groups will be compared using the Student t test (two-tailed) for normally distributed and Mann Whitney U test for skewed continuous variables, respectively. The chi-square test will be used for categorical variables. Time to event (readmission) and 180-day mortality between the two study groups will be compared by using the Kaplan-Meier survival plots and the log-rank test. Cox proportional hazard regression will be used to compute hazard ratio and compare outcomes between the two groups. RESULTS: We are actively enrolling participants and the study is expected to be completed by end of 2018; results are expected to be published in early 2019. CONCLUSIONS: Innovative solutions for identifying high-risk patients and personalizing interventions based on individual risk and needs may help facilitate the delivery of value-based care, improve long-term patient health outcomes and decrease health care costs. TRIAL REGISTRATION: ClinicalTrials.gov NCT03126565; https://clinicaltrials.gov/ct2/show/NCT03126565 (Archived by WebCite at http://www.webcitation.org/6ymDuAwQA).

Health Care Cost Analyses for Exploring Cost Savings Opportunities in Older Patients: Longitudinal Retrospective Study.

BACKGROUND: Half of Medicare reimbursement goes toward caring for the top 5% of the most expensive patients. However, little is known about these patients prior to reaching the top or how their costs change annually. To address these gaps, we analyzed patient flow and associated health care cost trends over 5 years. OBJECTIVE: To evaluate the cost of health care utilization in older patients by analyzing changes in their long-term expenditures. METHODS: This was a retrospective, longitudinal, multicenter study to evaluate health care costs of 2643 older patients from 2011 to 2015. All patients had at least one episode of home health care during the study period and used a personal emergency response service (PERS) at home for any length of time during the observation period. We segmented all patients into top (5%), middle (6%-50%), and bottom (51%-100%) segments by their annual expenditures and built cost pyramids based thereon. The longitudinal health care expenditure trends of the complete study population and each segment were assessed by linear regression models. Patient flows throughout the segments of the cost acuity pyramids from year to year were modeled by Markov chains. RESULTS: Total health care costs of the study population nearly doubled from US $17.7M in 2011 to US $33.0M in 2015 with an expected annual cost increase of US $3.6M (P=.003). This growth was primarily driven by a significantly higher cost increases in the middle segment (US $2.3M, P=.003). The expected annual cost increases in the top and bottom segments were US $1.2M (P=.008) and US $0.1M (P=.004), respectively. Patient and cost flow analyses showed that 18% of patients moved up the cost acuity pyramid yearly, and their costs increased by 672%. This was in contrast to 22% of patients that moved down with a cost decrease of 86%. The remaining 60% of patients stayed in the same segment from year to year, though their costs also increased by 18%. CONCLUSIONS: Although many health care organizations target intensive and costly interventions to their most expensive patients, this analysis unveiled potential cost savings opportunities by managing the patients in the lower cost segments that are at risk of moving up the cost acuity pyramid. To achieve this, data analytics integrating longitudinal data from electronic health records and home monitoring devices may help health care organizations optimize resources by enabling clinicians to proactively manage patients in their home or community environments beyond institutional settings and 30- and 60-day telehealth services.

Healthcare utilization in older patients using personal emergency response systems: an analysis of electronic health records and medical alert data : Brief Description: A Longitudinal Retrospective Analyses of healthcare utilization rates in older patients using Personal Emergency Response Systems from 2011 to 2015.

BACKGROUND: Personal Emergency Response Systems (PERS) are traditionally used as fall alert systems for older adults, a population that contributes an overwhelming proportion of healthcare costs in the United States. Previous studies focused mainly on qualitative evaluations of PERS without a longitudinal quantitative evaluation of healthcare utilization in users. To address this gap and better understand the needs of older patients on PERS, we analyzed longitudinal healthcare utilization trends in patients using PERS through the home care management service of a large healthcare organization. METHODS: Retrospective, longitudinal analyses of healthcare and PERS utilization records of older patients over a 5-years period from 2011-2015. The primary outcome was to characterize the healthcare utilization of PERS patients. This outcome was assessed by 30-, 90-, and 180-day readmission rates, frequency of principal admitting diagnoses, and prevalence of conditions leading to potentially avoidable admissions based on Centers for Medicare and Medicaid Services classification criteria. RESULTS: The overall 30-day readmission rate was 14.2%, 90-days readmission rate was 34.4%, and 180-days readmission rate was 42.2%. While 30-day readmission rates did not increase significantly (p = 0.16) over the study period, 90-days (p = 0.03) and 180-days (p = 0.04) readmission rates did increase significantly. The top 5 most frequent principal diagnoses for inpatient admissions included congestive heart failure (5.7%), chronic obstructive pulmonary disease (4.6%), dysrhythmias (4.3%), septicemia (4.1%), and pneumonia (4.1%). Additionally, 21% of all admissions were due to conditions leading to potentially avoidable admissions in either institutional or non-institutional settings (16% in institutional settings only). CONCLUSIONS: Chronic medical conditions account for the majority of healthcare utilization in older patients using PERS. Results suggest that PERS data combined with electronic medical records data can provide useful insights that can be used to improve health outcomes in older patients.

Household food insecurity is associated with anemia in adult Mexican women of reproductive age.

BACKGROUND: Anemia is a major cause of maternal mortality. Household food insecurity (HFI) may increase the risk of anemia among women of reproductive age although this hypothesis remains largely untested in representative samples from low- and middle-income countries. OBJECTIVE: Our objective was to investigate the association of HFI with anemia in a nationally representative, cross-sectional sample of Mexican women of reproductive age (12-49 y old). METHODS: We tested the association between HFI and anemia among 16,944 women of reproductive age using the multiple logistic regression among adolescent (12-20 y) and adult women (21-49 y). HFI was measured with the use of the Latin American and Caribbean Food Security Scale. Hemoglobin was measured with capillary hemoglobin with the use of HemoCue photometer (HemoCue, Inc.) and anemia was defined with the use of WHO standards. RESULTS: The association of HFI and anemia was not significant (P > 0.05) for adolescent women (12-20 y), whereas in adult women (21-49 y), the adjusted odds of having anemia were 31-43% higher among those living in mild to severely food insecure households than adult women residing in food secure households (P < 0.05). CONCLUSIONS: HFI is associated with anemia among adult Mexican women. Programs that reduce HFI may also be effective at reducing the risk of anemia among Mexican women.

Identification of genes involved in Listeria monocytogenes biofilm formation by mariner-based transposon mutagenesis.

Listeria monocytogenes is a ubiquitous food-borne pathogen, whose distribution and survival in food-processing environments are associated with the ability to form biofilms. The process of biofilm formation is complex and its molecular mechanism is relatively poorly understood in L. monocytogenes. To better understand the genetics of this process, a mariner-based transposon mutagenesis strategy was used to identify genes involved in biofilm formation of L. monocytogenes. A library of 6,500 mutant colonies was screened for reduced biofilm formation using a microtiter plate biofilm assay. Forty biofilm-deficient mutants of L. monocytogenes were identified based on DNA sequences of the transposon-flanking regions and Southern hybridization with a transposon-based probe. The insertions harbored by these mutants led to the identification of 24 distinct loci, 18 of which, to our knowledge, have not been previously reported to function in the biofilm formation in L. monocytogenes. Genetic complementation confirmed the importance of lmo1386, a gene encoding a putative DNA translocase, for biofilm formation. Molecular analyses of mutants indicated that the majority of the 24 identified genes are related to flagella motility, gene regulation, and cell surface structures.