{"title":"EHR Investments, Relative Bed Allocation for Covid-19 Patients and Local COVID-19 Incidence and Death Rates: A Simulation and An Empirical Study","authors":"P. Patel, M. Tsionas, Srikant Devaraj","doi":"10.2139/ssrn.3793919","DOIUrl":null,"url":null,"abstract":"During the COVID-19 pandemic, raising the hospital bed capacity was essential to ‘flattening the curve.’ However, due to short-run stickiness in hospital bed capacity, operational flexibility in managing the relative bed allocation for COVID-19 and non-COVID-19 patients was the key to hospital supply chain efficacy. The lateral and vertical flows of information, knowledge, and resources facilitated by electronic health record (EHR) systems could improve the efficacy of relative bed allocations on local COVID-19 outcomes through improved coordination. Drawing on the organizational information processing theory (OIPT) we use both simulation and empirical tests. Using a simulation model, we find that under varying levels of relative bed allocations, coordination among local healthcare providers is associated with a flatter SIR (susceptible-infected-recovered) curve. Using weekly hospital data (3,640 hospitals and a total of 73,706 hospital-week observations from July 31st, 2020 to February 12th, 2021), relative allocation of beds under higher EHR was associated with lower 7-, 14-, and 21-day forward-looking COVID-19 case and death rate at the county-level. Our empirical results are robust to a variety of specifications, a contiguous border-county pair analysis, and 2SLS estimates. The findings have implications for policymakers and stakeholders of the local healthcare supply chain.","PeriodicalId":274233,"journal":{"name":"PublicHealthRN: Disease Outbreaks & Public Health (Topic)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PublicHealthRN: Disease Outbreaks & Public Health (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3793919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
During the COVID-19 pandemic, raising the hospital bed capacity was essential to ‘flattening the curve.’ However, due to short-run stickiness in hospital bed capacity, operational flexibility in managing the relative bed allocation for COVID-19 and non-COVID-19 patients was the key to hospital supply chain efficacy. The lateral and vertical flows of information, knowledge, and resources facilitated by electronic health record (EHR) systems could improve the efficacy of relative bed allocations on local COVID-19 outcomes through improved coordination. Drawing on the organizational information processing theory (OIPT) we use both simulation and empirical tests. Using a simulation model, we find that under varying levels of relative bed allocations, coordination among local healthcare providers is associated with a flatter SIR (susceptible-infected-recovered) curve. Using weekly hospital data (3,640 hospitals and a total of 73,706 hospital-week observations from July 31st, 2020 to February 12th, 2021), relative allocation of beds under higher EHR was associated with lower 7-, 14-, and 21-day forward-looking COVID-19 case and death rate at the county-level. Our empirical results are robust to a variety of specifications, a contiguous border-county pair analysis, and 2SLS estimates. The findings have implications for policymakers and stakeholders of the local healthcare supply chain.