skip to main content
Explore Scholarly Publications and Datasets in the NSF-PAR

Title: Disparities in patient portal access by US adults before and during the COVID-19 pandemic
Abstract Objective

Online patient portals become important during disruptions to in-person health care, like when cases of coronavirus disease 2019 (COVID-19) and other respiratory viruses rise, yet underlying structural inequalities associated with race, socio-economic status, and other socio-demographic characteristics may affect their use. We analyzed a population-based survey to identify disparities within the United States in access to online portals during the early period of COVID-19 in 2020.

 Materials and Methods

The National Cancer Institute fielded the 2020 Health and Information National Trends Survey from February to June 2020. We conducted multivariable analysis to identify socio-demographic characteristics of US patients who were offered and accessed online portals, and reasons for nonuse.

 Results

Less than half of insured adult patients reported accessing an online portal in the prior 12 months, and this was less common among patients who are male, are Hispanic, have less than a college degree, have Medicaid insurance, have no regular provider, or have no internet. Reasons for nonuse include: wanting to speak directly to a provider, not having an online record, concerns about privacy, and discomfort with technology.

 Discussion

Despite the rapid expansion of digital health technologies due to COVID-19, we found persistent socio-demographic disparities in access to patient portals. Ensuring more » that digital health tools are secure, private, and trustworthy would address some patient concerns that are barriers to portal access.

 Conclusion

Expanding the use of online portals requires explicitly addressing fundamental inequities to prevent exacerbating existing disparities, particularly during surges in cases of COVID-19 and other respiratory viruses that tax health care resources.

 « less
Authors:
; ;
Publication Date:
NSF-PAR ID:
10385974
Journal Name:
JAMIA Open
Volume:
5
Issue:
4
ISSN:
2574-2531
Publisher:
Oxford University Press
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ( , BMC Infectious Diseases)
    Abstract Background

    The Mexican Institute of Social Security (IMSS) is the largest health care provider in Mexico, covering about 48% of the Mexican population. In this report, we describe the epidemiological patterns related to confirmed cases, hospitalizations, intubations, and in-hospital mortality due to COVID-19 and associated factors, during five epidemic waves recorded in the IMSS surveillance system.

     Methods

    We analyzed COVID-19 laboratory-confirmed cases from the Online Epidemiological Surveillance System (SINOLAVE) from March 29th, 2020, to August 27th, 2022. We constructed weekly epidemic curves describing temporal patterns of confirmed cases and hospitalizations by age, gender, and wave. We also estimated hospitalization, intubation, and hospital case fatality rates. The mean days of in-hospital stay and hospital admission delay were calculated across five pandemic waves. Logistic regression models were employed to assess the association between demographic factors, comorbidities, wave, and vaccination and the risk of severe disease and in-hospital death.

     Results

    A total of 3,396,375 laboratory-confirmed COVID-19 cases were recorded across the five waves. The introduction of rapid antigen testing at the end of 2020 increased detection and modified epidemiological estimates. Overall, 11% (95% CI 10.9, 11.1) of confirmed cases were hospitalized, 20.6% (95% CI 20.5, 20.7) of the hospitalized cases were intubated, and the hospitalmore »case fatality rate was 45.1% (95% CI 44.9, 45.3). The mean in-hospital stay was 9.11 days, and patients were admitted on average 5.07 days after symptoms onset. The most recent waves dominated by the Omicron variant had the highest incidence. Hospitalization, intubation, and mean hospitalization days decreased during subsequent waves. The in-hospital case fatality rate fluctuated across waves, reaching its highest value during the second wave in winter 2020. A notable decrease in hospitalization was observed primarily among individuals ≥ 60 years. The risk of severe disease and death was positively associated with comorbidities, age, and male gender; and declined with later waves and vaccination status.

     Conclusion

    During the five pandemic waves, we observed an increase in the number of cases and a reduction in severity metrics. During the first three waves, the high in-hospital fatality rate was associated with hospitalization practices for critical patients with comorbidities.

    « less
  2. ; ; ; ; ; ; ; ; ; ; et al ( , Microbiome)
    Abstract Background

    SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity. We set out to test whether specific bacterial communities predict SARS-CoV-2 occurrence in a hospital setting.

     Methods

    We collected 972 samples from hospitalized patients with COVID-19, their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model.

     Results

    Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. The highest prevalence was in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples more closely resembled the patient microbiome compared to floor samples, SARS-CoV-2 RNA was detected less often in bed rail samples (11%). SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity in both human and surface samples and higher biomass in floor samples. 16S microbial community profiles enabled high classifier accuracy for SARS-CoV-2 status in not onlymore »nares, but also forehead, stool, and floor samples. Across these distinct microbial profiles, a single amplicon sequence variant from the genusRothiastrongly predicted SARS-CoV-2 presence across sample types, with greater prevalence in positive surface and human samples, even when compared to samples from patients in other intensive care units prior to the COVID-19 pandemic.

     Conclusions

    These results contextualize the vast diversity of microbial niches where SARS-CoV-2 RNA is detected and identify specific bacterial taxa that associate with the viral RNA prevalence both in the host and hospital environment.

    « less
  3. ; ; ; ; ( , MIS quarterly)
    Hospitalization of patients with chronic diseases poses a significant burden on the healthcare system. Frequent hospitalization can be partially attributed to the failure of healthcare providers to engage effectively with their patients. Recently, patient portals have become popular as information technology (IT) platforms that provide patients with online access to their medical records and help them engage effectively with healthcare providers. Despite the popularity of these portals, there is a paucity of research on the impact of patient–provider engagement on patients’ health outcomes. Drawing on the theory of effective use, we examine the association between portal use and the incidence of subsequent patient hospitalizations, based on a unique, longitudinal dataset of patients’ portal use, across a 12-year period at a large academic medical center in North Texas. Our results indicate that portal use is associated with improvements in patient health outcomes along multiple dimensions, including the frequency of hospital and emergency visits, readmission risk, and length of stay. This is one of the first studies to conduct a large-scale, longitudinal analysis of a health IT system and its effect on individual level health outcomes. Our results highlight the need for technologies that can improve patient–provider engagement and improve overall healthmore »outcomes for chronic disease management.« less
  4. ; ; ; ( , Allergy, Asthma & Clinical Immunology)
    Abstract Background

    COVID-19 disproportionately affects those with preexisting conditions, but little research has determined whether those with chronic diseases view the pandemic itself differently - and whether there are differences between chronic diseases. We theorized that while individuals with respiratory disease or autoimmune disorders would perceive greater threat from COVID-19 and be more supportive of non-pharmaceutical interventions (NPIs), those with autoimmune disorders would be less likely to support vaccination-based interventions.

     Methods

    We conducted a two-wave online survey conducted in February and November 2021 asking respondents their beliefs about COVID-19 risk perception, adoption and support of interventions, willingness to be vaccinated against COVID-19, and reasons for vaccination. Regression analysis was conducted to assess the relationship of respondents reporting a chronic disease and COVID-19 behaviors and attitudes, compared to healthy respondents adjusting for demographic and political factors.

     Results

    In the initial survey, individuals reporting a chronic disease had both stronger feelings of risk from COVID-19 as well as preferences for NPIs than healthy controls. The only NPI that was still practiced significantly more compared to healthy controls in the resample was limiting trips outside of the home. Support for community-level NPIs was higher among individuals reporting a chronic disease than healthy controls and remained highmore »among those with respiratory diseases in sample 2. Vaccine acceptance produced more divergent results: those reporting chronic respiratory diseases were 6% more willing to be vaccinated than healthy controls, while we found no significant difference between individuals with autoimmune diseases and healthy controls. Respondents with chronic respiratory disease and those with autoimmune diseases were more likely to want to be vaccinated to protect themselves from COVID-19, and those with an autoimmune disease were more likely to report fear of a bad vaccine reaction as the reason for vaccine hesitancy. In the resample, neither those with respiratory diseases nor autoimmune diseases reported being more willing to receive a booster vaccine than healthy controls.

     Conclusions

    It is not enough to recognize the importance of health in determining attitudes: nuanced differences between conditions must also be recognized.

    « less
  5. ; ; ; ; ; ; ( , Journal of the American Medical Informatics Association)
    Abstract Objective 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 health care 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 . Materials and Methods 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. 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. Discussion There are disparities for Black patients accessing telemedicine, however increased uptake by young, female Black patients. Mean income and decreased mean household size of Zip code were also significantly related to telemedicine use. Conclusion Telemedicine access disparities reflectmore »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.« less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email