BackgroundOne in 3 US adults has high blood pressure, or hypertension. As prior projections suggest hypertension is the costliest of all cardiovascular diseases, it is important to define the current state of healthcare expenditures related to hypertension.Methods and ResultsWe used a nationally representative database, the Medical Expenditure Panel Survey, to calculate the estimated annual healthcare expenditure for patients with hypertension and to measure trends in expenditure longitudinally over a 12‐year period. A 2‐part model was used to estimate adjusted incremental expenditures for individuals with hypertension versus those without hypertension. Sex, race/ethnicity, education, insurance status, census region, income, marital status, Charlson Comorbidity Index, and year category were included as covariates. The 2003–2014 pooled data include a total sample of 224 920 adults, of whom 36.9% had hypertension. Unadjusted mean annual medical expenditure attributable to patients with hypertension was $9089. Relative to individuals without hypertension, individuals with hypertension had $1920 higher annual adjusted incremental expenditure, 2.5 times the inpatient cost, almost double the outpatient cost, and nearly triple the prescription medication expenditure. Based on the prevalence of hypertension in the United States, the estimated adjusted annual incremental cost is $131 billion per year higher for the hypertensive adult population compared with the nonhypertensive population.ConclusionsIndividuals with hypertension are estimated to face nearly $2000 higher annual healthcare expenditure compared with their nonhypertensive peers. This trend has been relatively stable over 12 years. Healthcare costs associated with hypertension account for about $131 billion. This warrants intense effort toward hypertension prevention and management.
Aims Across the United States of America, patients are increasingly receiving healthcare using innovative telehealth technologies. As healthcare continues to shift away from traditional office-based visits, providers face new challenges. Telehealth champions are needed to adapt technologies to meet the needs of patients, providers and communities, especially within the realm of primary care specialties. Given these challenges, this intervention aimed to incorporate telemedicine into internal medicine resident training across multiple training years to prepare them for practice in the current and changing healthcare system. Methods Education and telehealth leaders at the Medical University of South Carolina identified key topics relevant to telehealth and the provision of general internal medicine services. With this as a framework, we developed a 3-year longitudinal telehealth curriculum for internal medicine resident physicians, consisting of an introduction to telemedicine equipment in the first year, didactic learning through in-person education and online modules in the second year and experiential learning through remote monitoring of chronic disease in the third year. Participants included approximately 100 internal medicine residents per year (2016–2019). Self-perceived knowledge, comfort and ability to provide telehealth services was assessed via a survey completed before and after participation in the curriculum. Results Resident physicians’ self-reported knowledge of telehealth history, access to care, contributions of telehealth applications and quality of care and communication each improved after completion of the online curriculum. There were also significant improvements in resident comfort and perceived ability to provide telehealth services after participation in the curriculum, as assessed via a survey. Overall, 41% of residents felt their ability to utilize telehealth as part of their current or future practice was greater than average after completion of the online modules compared to only 2% at baseline ( p<0.01). Results also show residents accurately identify barriers to telehealth adoption at the healthcare system level, including the lack of clinical time to implement services (67% post- vs 47% pre-curriculum, p = 0.02), unfamiliarity with concepts (65% post- vs 21% pre-curriculum, p<−0.01) and concerns about consistent provider reimbursement (74% post- vs 39% pre-curriculum, p < 0.01). Conclusion Telemedicine and remote patient monitoring are an increasingly prevalent form of healthcare delivery. Internal medicine residents must be adept in caring for patients utilizing this technology. This curriculum was effective in improving resident comfort and self-efficacy in providing care through telehealth and provided residents with hands-on opportunities through supervised inclusion in remote patient-monitoring services. This curriculum model could be employed and evaluated within other internal medicine residency programmes to determine the feasibility at institutions with and without advanced telehealth centres.
BACKGROUND: National administrative datasets have demonstrated increased risk-adjusted mortality among patients undergoing interhospital transfer (IHT) compared to patients admitted through the emergency department (ED). OBJECTIVE: To investigate the impact of patient-level data not available in larger administrative datasets on the association between IHT status and in-hospital mortality. DESIGN: Retrospective cohort study with logistic regression analyses to examine the association between IHT status and in-hospital mortality, controlling for covariates that were potential confounders. Model 1: IHT status, admit service. Model 2: model 1 and patient demographics. Model 3: model 2 and disease-specific conditions. Model 4: model 3 and vital signs and laboratory data. PARTICIPANTS: Nine thousand three hundred twentyeight adults admitted to Medicine services. MAIN MEASURES: Interhospital transfer status, coded as an unordered categorical variable (IHT vs ED vs clinic), was the independent variable. The primary outcome was in-hospital mortality. Secondary outcomes included unadjusted length of stay and total cost. KEY RESULTS: IHT patients accounted for 180 out of 484 (37%) in-hospital deaths, despite accounting for only 17% of total admissions. Unadjusted mean length of stay was 8.4 days vs 5.6 days (p < 0.0001) and mean total cost was $22,647 vs $12,968 (p < 0.0001) for patients admitted via IHT vs ED respectively. The odds ratios (OR) for inhospital mortality for patients admitted via IHT compared to the ED were as follows: model 1 OR, 2.06 (95% CI 1.66-2.56, p < 0.0001); model 2 OR, 2.07 (95% CI 1.66-2.58, p < 0.0001); model 3 OR, 2.07 (95% CI 1.63-2.61, p < 0.0001); model 4 OR, 1.70 (95% CI 1.31-2.19, p < 0.0001). The AUCs of the models were as follows: model 1, 0.74; model 2, 0.76; model 3, 0.83; model 4, 0.88, consistent with a good prediction model. CONCLUSIONS: Patient-level characteristics affect the association between IHT and in-hospital mortality. After adjusting for patient-level clinical characteristics, IHT status remains associated with in-hospital mortality.
Background: Remote physiological monitoring (RPM) is accessible, convenient, relatively inexpensive, and can improve clinical outcomes. Yet, it is unclear in which clinical setting or target population RPM is maximally effective. Objective: To determine whether patients' demographic characteristics or clinical settings are associated with data transmission and engagement. Methods: This is a prospective cohort study of adults enrolled in a diabetes RPM program for a minimum of 12 months as of April 2020. We developed a multivariable logistic regression model for engagement with age, gender, race, income, and primary care clinic type as variables and a second model to include first-order interactions for all demographic variables by time. The participants included 549 adults (mean age 53 years, 63% female, 54% Black, and 75% very low income) with baseline hemoglobin A1c ‡8.0% and enrolled in a statewide diabetes RPM program. The main measure was the transmission engagement over time, where engagement is defined as a minimum of three distinct days per week in which remote data are transmitted. Results: Significant predictors of transmission engagement included increasing age, academic clinic type, higher annual household income, and shorter time-in-program (p < 0.001 for each). Self-identified race and gender were not significantly associated with transmission engagement (p = 0.729 and 0.237, respectively). Conclusions: RPM appears to be an accessible tool for minority racial groups and for the aging population, yet engagement is impacted by primary care location setting and socioeconomic status. These results should inform implementation of future RPM studies, guide advocacy efforts, and highlight the need to focus efforts on maintaining engagement over time.
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