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Predictors of telemedicine use during the COVID-19 pandemic in the United States-an analysis of a national electronic medical record database.

ABSTRACT: Telemedicine utilization increased significantly in the United States during the COVID-19 pandemic. However, there is concern that disadvantaged groups face barriers to access based on single-center studies. Whether there has been equitable access to telemedicine services across the US and during later parts of the pandemic is unclear. This study retrospectively analyzes outpatient medical encounters for patients 18 years of age and older using Healthjump-a national electronic medical record database-from March 1 to December 31, 2020. A mixed effects multivariable logistic regression model was used to assess the association between telemedicine utilization and patient and area-level factors and the odds of having at least one telemedicine encounter during the study period. Among 1,999,534 unique patients 21.6% had a telemedicine encounter during the study period. In the multivariable model, age [OR = 0.995 (95% CI 0.993, 0.997); p<0.001], non-Hispanic Black race [OR = 0.88 (95% CI 0.84, 0.93); p<0.001], and English as primary language [OR = 0.78 (95% CI 0.74, 0.83); p<0.001] were associated with a lower odds of telemedicine utilization. Female gender [OR = 1.24 (95% CI 1.22, 1.27); p<0.001], Hispanic ethnicity or non-Hispanic other race [OR = 1.40 (95% CI 1.33, 1.46);p<0.001 and 1.29 (95% CI 1.20, 1.38); p<0.001, respectively] were associated with a higher odds of telemedicine utilization. During the COVID-19 pandemic, therefore, utilization of telemedicine differed significantly among patient groups, with older and non-Hispanic Black patients less likely to have telemedicine encounters. These findings are relevant for ongoing efforts regarding the nature of telemedicine as the COVID-19 pandemic ends.

SUBMITTER: Khatana SAM

PROVIDER: S-EPMC9242497 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background and objectivesAn unintended consequence of electronic medical record use in the United States is the potential effect on graduate physician training. We assessed educational burdens and benefits of electronic medical record use on United States nephrology fellows by means of a survey.Design, setting, participants, & measurementsWe used an anonymous online opinion survey of all United States nephrology program directors (n=148), their faculty, and fellows. Program directors forwarded survey links to fellows and clinical faculty, indicating to how many they forwarded the link. The three surveys had parallel questions to permit comparisons.ResultsTwenty-two percent of program directors (n=33) forwarded surveys to faculty (n=387) and fellows (n=216; 26% of United States nephrology fellows). Faculty and fellow response rates were 25% and 33%, respectively; 51% of fellows agreed/strongly agreed that the electronic medical record contributed positively to their education. Perceived positive effects included access flexibility and ease of obtaining laboratory/radiology results. Negative effects included copy-forward errors and excessive, irrelevant documentation. Electronic medical record function was reported to be slow, disrupted, or completely lost monthly or more by >40%, and these were significantly less likely to agree that the electronic medical record contributed positively to their education. Electronic medical record completion time demands contributed to fellow reluctance to do procedures (52%), participate in conferences (57%), prolong patient interactions (74%), and do patient-directed reading (55%). Sixty-five percent of fellows reported often/sometimes exceeding work-hours limits due to documentation time demands; 85% of faculty reported often/sometimes observing copy-forward errors. Limitations include potential nonresponse and social desirability bias.ConclusionsRespondents reported that the electronic medical record enhances fellow education with efficient and geographically flexible patient data access, but the time demands of data and order entry reduce engagement in educational activities, contribute to work-hours violations, and diminish direct patient interactions.

Project description:BackgroundAs family caregivers of patients undergoing hematopoietic cell transplantation have multifaceted caregiving responsibilities (such as medical, household, financial) of long duration, they also have multiple physical, social, psychological, and informational needs.ObjectiveThis study explored the prevalence of electronic health record patient portal use by family caregivers for managing both their own and their hematopoietic cell transplantation care recipient's health, as well as potential factors associated with portal use.MethodsAn electronic caregiver health survey, first developed via cognitive interviewing methods of hematopoietic cell transplantation caregivers, was distributed nationally (in the United States) by patient advocacy organizations to family caregivers of hematopoietic cell transplantation patients. It was used to assess self-reported caregiver demographics, caregiving characteristics, depression and anxiety with the Patient Health Questionnaire-4, coping with the Brief COPE, and caregiver portal use to manage care recipient's and their own health.ResultsWe found that 77% of respondents (720/937) accessed electronic health record patient portals for their care recipients, themselves, or both. Multivariate models indicated use of care recipient electronic health record portals by caregivers was more likely with young, White, married, low-income caregivers caring for a parent, residing with the care recipient, and experiencing more caregiver depression. Caregiver use of their own electronic health record portal was more likely with young, White, high-income caregivers caring for a parent and experiencing chronic medical conditions of their own. Partially due to multicollinearity, anxiety and coping did not contribute independently to this model.ConclusionsFindings from the survey could open avenues for future research into caregiver use of technology for informational support or intervention, including wearables and mobile health.International registered report identifier (irrid)RR2-10.2196/4918.

Project description:BackgroundElectronic health record (EHR) databases provide an opportunity to facilitate characterization and trends in patients with COVID-19.MethodsPatients with COVID-19 were identified based on an ICD-10 diagnosis code for COVID-19 (U07.1) and/or a positive SARS-CoV-2 viral lab result from January 2020 to November 2020. Patients were characterized in terms of demographics, healthcare utilization, clinical comorbidities, therapies, laboratory results, and procedures/care received, including critical care, intubation/ventilation, and occurrence of death were described, overall and by month.ResultsThere were 393,773 patients with COVID-19 and 56,996 with a COVID-19 associated hospitalization. A greater percentage of patients hospitalized with COVID-19 relative to all COVID-19 cases were older, male, African American, and lived in the Northeast and South. The most common comorbidities before admission/infection date were hypertension (40.8%), diabetes (29.5%), and obesity (23.8%), and the most common diagnoses during hospitalization were pneumonia (59.6%), acute respiratory failure (44.8%), and dyspnea (28.0%). A total of 85.7% of patients hospitalized with COVID-19 had CRP values > 10 mg/L, 75.5% had fibrinogen values > 400 mg/dL, and 76.8% had D-dimer values > 250 ng/mL. Median values for platelets, CRP, lactate dehydrogenase, D-dimer, and fibrinogen tended to decrease from January-March to November. The use of chloroquine/hydroxychloroquine during hospitalization peaked by March (71.2%) and was used rarely by May (5.1%) and less than 1% afterwards, while the use of remdesivir had increased by May (10.0%) followed by dexamethasone by June (27.7%). All-cause mortality was 3.2% overall and 15.0% among those hospitalized; 21.0% received critical care and 16.0% received intubation/ventilation/ECMO.ConclusionsThis study characterizes US patients with COVID-19 and their management during hospitalization over the first eleven months of this disease pandemic.

Project description:BackgroundAt the beginning of June 2020, there were nearly 7 million reported cases of coronavirus disease 2019 (COVID-19) worldwide and over 400,000 deaths in people with COVID-19. The objective of this study was to determine associations between comorbidities listed in the Charlson comorbidity index and mortality among patients in the United States with COVID-19.Methods and findingsA retrospective cohort study of adults with COVID-19 from 24 healthcare organizations in the US was conducted. The study included adults aged 18-90 years with COVID-19 coded in their electronic medical records between January 20, 2020, and May 26, 2020. Results were also stratified by age groups (<50 years, 50-69 years, or 70-90 years). A total of 31,461 patients were included. Median age was 50 years (interquartile range [IQR], 35-63) and 54.5% (n = 17,155) were female. The most common comorbidities listed in the Charlson comorbidity index were chronic pulmonary disease (17.5%, n = 5,513) and diabetes mellitus (15.0%, n = 4,710). Multivariate logistic regression analyses showed older age (odds ratio [OR] per year 1.06; 95% confidence interval [CI] 1.06-1.07; p < 0.001), male sex (OR 1.75; 95% CI 1.55-1.98; p < 0.001), being black or African American compared to white (OR 1.50; 95% CI 1.31-1.71; p < 0.001), myocardial infarction (OR 1.97; 95% CI 1.64-2.35; p < 0.001), congestive heart failure (OR 1.42; 95% CI 1.21-1.67; p < 0.001), dementia (OR 1.29; 95% CI 1.07-1.56; p = 0.008), chronic pulmonary disease (OR 1.24; 95% CI 1.08-1.43; p = 0.003), mild liver disease (OR 1.26; 95% CI 1.00-1.59; p = 0.046), moderate/severe liver disease (OR 2.62; 95% CI 1.53-4.47; p < 0.001), renal disease (OR 2.13; 95% CI 1.84-2.46; p < 0.001), and metastatic solid tumor (OR 1.70; 95% CI 1.19-2.43; p = 0.004) were associated with higher odds of mortality with COVID-19. Older age, male sex, and being black or African American (compared to being white) remained significantly associated with higher odds of death in age-stratified analyses. There were differences in which comorbidities were significantly associated with mortality between age groups. Limitations include that the data were collected from the healthcare organization electronic medical record databases and some comorbidities may be underreported and ethnicity was unknown for 24% of participants. Deaths during an inpatient or outpatient visit at the participating healthcare organizations were recorded; however, deaths occurring outside of the hospital setting are not well captured.ConclusionsIdentifying patient characteristics and conditions associated with mortality with COVID-19 is important for hypothesis generating for clinical trials and to develop targeted intervention strategies.

Project description:BACKGROUND:High utilizers (HUs) are a small group of patients who impose a disproportionately high burden on the healthcare system due to their elevated resource use. Identification of persistent HUs is pertinent as interventions have not been effective due to regression to the mean in majority of patients. This study will use cost and utilization metrics to segment a hospital-based patient population into HU groups. METHODS:The index visit for each adult patient to an Academic Medical Centre in Singapore during 2006 to 2012 was identified. Cost, length of stay (LOS) and number of specialist outpatient clinic (SOC) visits within 1 year following the index visit were extracted and aggregated. Patients were HUs if they exceeded the 90th percentile of any metric, and Non-HU otherwise. Seven different HU groups and a Non-HU group were constructed. The groups were described in terms of cost and utilization patterns, socio-demographic information, multi-morbidity scores and medical history. Logistic regression compared the groups' persistence as a HU in any group into the subsequent year, adjusting for socio-demographic information and diagnosis history. RESULTS:A total of 388,162 patients above the age of 21 were included in the study. Cost-LOS-SOC HUs had the highest multi-morbidity and persistence into the second year. Common conditions among Cost-LOS and Cost-LOS-SOC HUs were cardiovascular disease, acute cerebrovascular disease and pneumonia, while most LOS and LOS-SOC HUs were diagnosed with at least one mental health condition. Regression analyses revealed that HUs across all groups were more likely to persist compared to Non-HUs, with stronger relationships seen in groups with high SOC utilization. Similar trends remained after further adjustment. CONCLUSION:HUs of healthcare services are a diverse group and can be further segmented into different subgroups based on cost and utilization patterns. Segmentation by these metrics revealed differences in socio-demographic characteristics, disease profile and persistence. Most HUs did not persist in their high utilization, and high SOC users should be prioritized for further longitudinal analyses. Segmentation will enable policy makers to better identify the diverse needs of patients, detect gaps in current care and focus their efforts in delivering care relevant and tailored to each segment.

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Predictors of telemedicine use during the COVID-19 pandemic in the United States-an analysis of a national electronic medical record database.

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