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10.1089/pop.2020.0186

http://scihub22266oqcxt.onion/10.1089/pop.2020.0186
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32816644!?!32816644

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suck abstract from ncbi

pmid32816644      Popul+Health+Manag 2020 ; 23 (5): 368-377
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  • Health Inequalities in the Use of Telehealth in the United States in the Lens of COVID-19 #MMPMID32816644
  • Jaffe DH; Lee L; Huynh S; Haskell TP
  • Popul Health Manag 2020[Oct]; 23 (5): 368-377 PMID32816644show ga
  • The use of remote health care services, or telehealth, is a promising solution for providing health care to those unable to access care in person easily and thus helping to reduce health inequalities. The COVID-19 pandemic and resulting stay-at-home orders in the United States have created an optimal situation for the use of telehealth services for non-life-threatening health care use. A retrospective cohort study was performed using Kantar's Claritis database, which links insurance claims encounters (Komodo Health) with patient-reported data (Kantar Health, National Health & Wellness Survey). Logistic regression models (odds ratios [OR], 95% confidence intervals [CI]) examined predictors of telehealth versus in-person encounters. Adults ages >/=18 years eligible for payer-complete health care encounters in both March 2019 and March 2020 were identified (n = 35,376). Telehealth use increased from 0.2% in 2019 to 1.9% in 2020. In adjusted models of respondents with >/=1 health care encounter (n = 11,614), age, marital status, geographic residence (region; urban/rural), and presence of anxiety or depression were significant predictors of telehealth compared with in-person use in March 2020. For example, adults 45-46 years versus 18-44 years were less likely to use telehealth (OR 0.684, 95% CI: 0.561-0.834), and respondents living in urban versus rural areas were more likely to use telehealth (OR 1.543, 95% CI: 1.153-2.067). Substantial increases in telehealth use were observed during the onset of the COVID-19 pandemic in the United States; however, disparities existed. These inequalities represent the baseline landscape that population health management must monitor and address during this pandemic.
  • |*Health Status Disparities[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |COVID-19[MESH]
  • |Cohort Studies[MESH]
  • |Confidence Intervals[MESH]
  • |Coronavirus Infections/*epidemiology/*therapy[MESH]
  • |Cross-Sectional Studies[MESH]
  • |Female[MESH]
  • |Health Personnel/economics/statistics & numerical data[MESH]
  • |Healthcare Disparities/*economics/ethnology[MESH]
  • |Humans[MESH]
  • |Logistic Models[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Needs Assessment[MESH]
  • |Odds Ratio[MESH]
  • |Pandemics/*prevention & control/statistics & numerical data[MESH]
  • |Pneumonia, Viral/*epidemiology/*therapy[MESH]
  • |Retrospective Studies[MESH]
  • |Socioeconomic Factors[MESH]
  • |Telemedicine/methods/*statistics & numerical data[MESH]
  • |United States[MESH]


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