Abstract
This study provides data on the feasibility and impact of video-enabled telemedicine use among patients and providers and its impact on urgent and nonurgent healthcare delivery from one ...large health system (NYU Langone Health) at the epicenter of the coronavirus disease 2019 (COVID-19) outbreak in the United States. Between March 2nd and April 14th 2020, telemedicine visits increased from 102.4 daily to 801.6 daily. (683% increase) in urgent care after the system-wide expansion of virtual urgent care staff in response to COVID-19. Of all virtual visits post expansion, 56.2% and 17.6% urgent and nonurgent visits, respectively, were COVID-19–related. Telemedicine usage was highest by patients 20 to 44 years of age, particularly for urgent care. The COVID-19 pandemic has driven rapid expansion of telemedicine use for urgent care and nonurgent care visits beyond baseline periods. This reflects an important change in telemedicine that other institutions facing the COVID-19 pandemic should anticipate.
Background:
Nonadherence to statins limits the benefits of this common drug class. Individual studies assessing predictors of nonadherence haue produced inconsistent results.
Objective:
To identify ...reliable predictors of nonadherence to statins through systematic review and meta-analysis.
Methods:
Multiple databases, including MEDLINE, EMBASE, and PsycINFO, were searched (from inception through February 2009) to identify studies that evaluated predictors of nonadherence to statins. Studies were selected using a priori defined criteria, and each study was reviewed by 2 authors who abstracted data on study characteristics and outcomes. Relative risks were then pooled, using an inverse-variance weighted random-effects model.
Results:
Twenty-two cohort studies met inclusion criteria. Age had a U-shaped association with adherence; the oldest (≥70 years) and youngest (<50 years) subjects had lower adherence than the middle-aged (50-69 years) subjects. Women and patients with lower incomes were more likely to be nonadherent than were men (odds of nonadherence 1.07; 95% CI 1.04 to 1.11) and those with higher incomes (odds of nonadherence 1.18:95% CI 1.10 to 1.28), respectively. A history of cardiovascular disease predicted better adherence to statins (odds of nonadherence 0.68; 95% CI 0.66 to 0.78). Similarly, a diagnosis of hypertension or diabetes was associated with better adherence. Although there were too few studies for quantitative pooling, increased testing of lipid levels and lower out-of-pocket costs appeared to be associated with better adherence. There was substantial (l2 range 68.7-96.3%) heterogeneity between studies across factors.
Conclusions:
Several sociodemographic, medical, and health-care utilization characteristics are associated with statin nonadherence. These factors may be useful guides for targeting statin adherence interventions.
Despite the effectiveness of drug therapy in diabetes management high rates of poor adherence persist. The purpose of this study was to identify potentially modifiable patient disease and medication ...beliefs associated with poor medication adherence among people with diabetes. A cohort of patients with diabetes was recruited from an urban primary-care clinic in New York City. Patients were interviewed in English or Spanish about: disease beliefs, medication beliefs, regimen complexity, diabetes knowledge, depression, self-efficacy, and medication adherence (Morisky scale). Logistic regression was used to identify multivariate predictors of poor medication adherence (Morisky > 1). Patients (
n
= 151) had diabetes for an average of 13 years with a mean HgA1C of 7.6 (SD 1.7). One-in-four (28%) were poor adherers to their diabetes medicines. In multivariate analyses, predictors of poor medication adherence were: believing you have diabetes only when your sugar is high (OR = 7.4;2–27.2), saying there was no need to take medicine when the glucose was normal (OR = 3.5;0.9–13.7), worrying about side-effects of diabetes medicines (OR = 3.3;1.3–8.7), lack of self-confidence in controlling diabetes (OR = 2.8;1.1–7.1), and feeling medicines are hard to take (OR = 14.0;4.4–44.6). Disease and medication beliefs inconsistent with a chronic disease model of diabetes were significant predictors of poor medication adherence. These suboptimal beliefs are potentially modifiable and are logical targets for educational interventions to improve diabetes self-management.
Background During the COVID-19 pandemic, acute respiratory infection (ARI) antibiotic prescribing in ambulatory care markedly decreased. It is unclear if antibiotic prescription rates will remain ...lowered. Methods We used trend analyses of antibiotics prescribed during and after the first wave of COVID-19 to determine whether ARI antibiotic prescribing rates in ambulatory care have remained suppressed compared to pre-COVID-19 levels. Retrospective data was used from patients with ARI or UTI diagnosis code(s) for their encounter from 298 primary care and 66 urgent care practices within four academic health systems in New York, Wisconsin, and Utah between January 2017 and June 2022. The primary measures included antibiotic prescriptions per 100 non-COVID ARI encounters, encounter volume, prescribing trends, and change from expected trend. Results At baseline, during and after the first wave, the overall ARI antibiotic prescribing rates were 54.7, 38.5, and 54.7 prescriptions per 100 encounters, respectively. ARI antibiotic prescription rates saw a statistically significant decline after COVID-19 onset (step change -15.2, 95% CI: -19.6 to -4.8). During the first wave, encounter volume decreased 29.4% and, after the first wave, remained decreased by 188%. After the first wave, ARI antibiotic prescription rates were no longer significantly suppressed from baseline (step change 0.01, 95% CI: -6.3 to 6.2). There was no significant difference between UTI antibiotic prescription rates at baseline versus the end of the observation period. Conclusions The decline in ARI antibiotic prescribing observed after the onset of COVID-19 was temporary, not mirrored in UTI antibiotic prescribing, and does not represent a long-term change in clinician prescribing behaviors. During a period of heightened awareness of a viral cause of ARI, a substantial and clinically meaningful decrease in clinician antibiotic prescribing was observed. Future efforts in antibiotic stewardship may benefit from continued study of factors leading to this reduction and rebound in prescribing rates.
Through the coronavirus disease 2019 (COVID-19) pandemic, telemedicine became a necessary entry point into the process of diagnosis, triage, and treatment. Racial and ethnic disparities in healthcare ...have been well documented in COVID-19 with respect to risk of infection and in-hospital outcomes once admitted, and here we assess disparities in those who access healthcare via telemedicine for COVID-19.
Electronic health record data of patients at New York University Langone Health between March 19th and April 30, 2020 were used to conduct descriptive and multilevel regression analyses with respect to visit type (telemedicine or in-person), suspected COVID diagnosis, and COVID test results.
Controlling for individual and community-level attributes, Black patients had 0.6 times the adjusted odds (95% CI: 0.58-0.63) of accessing care through telemedicine compared to white patients, though they are increasingly accessing telemedicine for urgent care, driven by a younger and female population. COVID diagnoses were significantly more likely for Black versus white telemedicine patients.
There are disparities for Black patients accessing telemedicine, however increased uptake by young, female Black patients. Mean income and decreased mean household size of a zip code were also significantly related to telemedicine use.
Telemedicine access disparities reflect those in in-person healthcare access. Roots of disparate use are complex and reflect individual, community, and structural factors, including their intersection-many of which are due to systemic racism. Evidence regarding disparities that manifest through telemedicine can be used to inform tool design and systemic efforts to promote digital health equity.
New clinical practice recommendations include A1C as an alternative to fasting glucose as a diagnostic test for identifying pre-diabetes. The impact of these new recommendations on the diagnosis of ...pre-diabetes is unknown.
Data from the National Health and Nutrition Examination Survey 1999-2006 (n = 7,029) were analyzed to determine the percentage and number of U.S. adults without diabetes classified as having pre-diabetes by the elevated A1C (5.7-6.4%) and by the impaired fasting glucose (IFG) (fasting glucose 100-125 mg/dl) criterion separately. Test characteristics (sensitivity, specificity, and positive and negative predictive values) using IFG as the reference standard were calculated.
The prevalence of pre-diabetes among U.S. adults was 12.6% by the A1C criterion and 28.2% by the fasting glucose criterion. Only 7.7% of U.S. adults, reflecting 61 and 27% of those with pre-diabetes by A1C and fasting glucose, respectively, had pre-diabetes according to both definitions. A1C used alone would reclassify 37.6 million Americans with IFG to not having pre-diabetes and 8.9 million without IFG to having pre-diabetes (46.5 million reclassified). Using IFG as the reference standard, pre-diabetes by the A1C criterion has 27% sensitivity, 93% specificity, 61% positive predictive value, and 77% negative predictive value.
Using A1C as the pre-diabetes criterion would reclassify the pre-diabetes diagnosis of nearly 50 million Americans. It is imperative that clinicians and health systems understand the differences and similarities in using A1C or IFG in diagnosis of pre-diabetes.
Abstract Major depressive disorder (MDD) is prevalent in clinical weight-loss settings and predicts poor weight-loss outcomes. It is unknown whether the severity of depressive symptoms among those ...with MDD is associated with diet quality or physical activity levels. This knowledge is important for improving weight-loss treatment for these patients. It was hypothesized that more severe depression is associated with poorer diet quality and lower physical activity levels among individuals with obesity and MDD. Participants were 161 women with current MDD and obesity enrolled in the baseline phase of a weight-loss trial between 2007 and 2010. Depression severity was measured with the Beck Depression Inventory II. The Alternate Healthy Eating Index was applied to data from three 24-hour diet recalls to capture overall diet quality. Daily metabolic equivalents expended per day were calculated from three 24-hour physical activity recalls. Greater depression severity was associated with poorer overall diet quality (estimate=−0.26, standard error 0.11; P =0.02), but not with physical activity (estimate=0.07, standard error 0.05; P =0.18), in linear regression models controlling for income, education, depression-related appetite change, binge eating disorder, and other potential confounds. Associations with diet quality were primarily driven by greater intake of sugar ( r =0.20; P <0.01), saturated fat ( r =0.21; P <0.01), and sodium ( r =0.22; P <0.01). More severe depression was associated with poorer overall diet quality, but not physical activity, among treatment-seeking women with MDD and obesity. Future studies should identify mechanisms linking depression to diet quality and determine whether diet quality improves with depression treatment.
A validated tool to assess adherence with inhaled corticosteroids (ICS) could help physicians and researchers determine whether poor asthma control is due to poor adherence or severe intrinsic ...asthma.
To assess the performance of the Medication Adherence Report Scale for Asthma (MARS-A), a 10-item, self-reported measure of adherence with ICS.
We interviewed 318 asthmatic adults receiving care at 2 inner-city clinics. Self-reported adherence with ICS was measured by MARS-A at baseline and 1 and 3 months. ICS adherence was measured electronically in 53 patients. Electronic adherence was the percentage of days patients used ICS. Patients with a mean MARS-A score of 4.5 or higher or with electronic adherence of more than 70% were defined as good adherers. We assessed internal validity (Cronbach alpha, test-retest correlations), criterion validity (associations between self-reported adherence and electronic adherence), and construct validity (correlating self-reported adherence with ICS beliefs).
The mean patient age was 47 years; 40% of patients were Hispanic, 40% were black, and 18% were white; 53% had prior asthma hospitalizations; and 70% had prior oral steroid use. Electronic substudy patients were similar to the rest of the cohort in age, sex, race, and asthma severity. MARS-A had good interitem correlation in English and Spanish (Cronbach alpha = 0.85 and 0.86, respectively) and good test-retest reliability (r = 0.65, P < .001). According to electronic measurements, patients used ICS 52% of days. Continuous MARS-A scores correlated with continuous electronic adherence (r = 0.42, P<.001), and dichotomized high self-reported adherence predicted high electronic adherence (odds ratio, 10.6; 95% confidence interval, 2.5-44.5; P < .001). Construct validity was good, with self-reported adherence higher in those saying daily ICS use was important and ICS were controller medications (P = .04).
MARS-A demonstrated good psychometric performance as a self-reported measure of adherence with ICS among English- and Spanish-speaking, low-income, minority patients with asthma.
Cancer genetic testing to assess an individual's cancer risk and to enable genomics-informed cancer treatment has grown exponentially in the past decade. Because of this continued growth and a ...shortage of health care workers, there is a need for automated strategies that provide high-quality genetics services to patients to reduce the clinical demand for genetics providers. Conversational agents have shown promise in managing mental health, pain, and other chronic conditions and are increasingly being used in cancer genetic services. However, research on how patients interact with these agents to satisfy their information needs is limited.
Our primary aim is to assess user interactions with a conversational agent for pretest genetics education.
We conducted a feasibility study of user interactions with a conversational agent who delivers pretest genetics education to primary care patients without cancer who are eligible for cancer genetic evaluation. The conversational agent provided scripted content similar to that delivered in a pretest genetic counseling visit for cancer genetic testing. Outside of a core set of information delivered to all patients, users were able to navigate within the chat to request additional content in their areas of interest. An artificial intelligence-based preprogrammed library was also established to allow users to ask open-ended questions to the conversational agent. Transcripts of the interactions were recorded. Here, we describe the information selected, time spent to complete the chat, and use of the open-ended question feature. Descriptive statistics were used for quantitative measures, and thematic analyses were used for qualitative responses.
We invited 103 patients to participate, of which 88.3% (91/103) were offered access to the conversational agent, 39% (36/91) started the chat, and 32% (30/91) completed the chat. Most users who completed the chat indicated that they wanted to continue with genetic testing (21/30, 70%), few were unsure (9/30, 30%), and no patient declined to move forward with testing. Those who decided to test spent an average of 10 (SD 2.57) minutes on the chat, selected an average of 1.87 (SD 1.2) additional pieces of information, and generally did not ask open-ended questions. Those who were unsure spent 4 more minutes on average (mean 14.1, SD 7.41; P=.03) on the chat, selected an average of 3.67 (SD 2.9) additional pieces of information, and asked at least one open-ended question.
The pretest chat provided enough information for most patients to decide on cancer genetic testing, as indicated by the small number of open-ended questions. A subset of participants were still unsure about receiving genetic testing and may require additional education or interpersonal support before making a testing decision. Conversational agents have the potential to become a scalable alternative for pretest genetics education, reducing the clinical demand on genetics providers.
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