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2.
Pan Afr Med J ; 37(Suppl 1): 15, 2020.
Article in English | MEDLINE | ID: covidwho-994229

ABSTRACT

The public health impact of the COVID-19 pandemic cannot be overstated. Its impact on the cost of surgical and obstetric care is significant. More so, in a country like Nigeria, where even before the pandemic, out-of-pocket spending (OOPS) has been the major payment method for healthcare. The increased cost of surgical and obstetric care occasioned by the pandemic has principally been due to the additional burden of ensuring the use of adequate/appropriate personal protective equipment (PPE) during patient care as a disease containment measure. These PPE are not readily available in public hospitals across Nigeria. Patients are therefore compelled to bear the financial burden of procuring scarce PPE for use by health care personnel, further increasing the already high cost of healthcare. In this study, we sought to appraise the impact of the COVID-19 pandemic on the cost of surgical and obstetric care in Nigeria, drawing from the experience from one of the major Nigerian teaching hospitals- the Obafemi Awolowo University Teaching Hospitals Complex (OAUTHC), Ile-Ife, Osun State. The cost of surgical and obstetric care was reviewed and compared pre- and during the COVID-19 pandemic, deriving relevant examples from some commonly performed surgical operations in our centre (OAUTHC). We reviewed patients' hospital bills and receipts of consumables procured for surgery. Our findings revealed that the cost of surgical and obstetric care during the COVID-19 pandemic had significantly increased. We identified gaps and made relevant recommendations on measures to reduce the additional costs of surgical and obstetric care during and beyond pandemic.


Subject(s)
COVID-19 , Hospital Costs/statistics & numerical data , Obstetrics/economics , Surgical Procedures, Operative/economics , Delivery of Health Care/economics , Female , Hospitals, Teaching , Humans , Nigeria , Obstetrics/statistics & numerical data , Personal Protective Equipment/supply & distribution , Pregnancy , Public Health/economics , Surgical Procedures, Operative/statistics & numerical data
5.
Health Aff (Millwood) ; 39(6): 927-935, 2020 06.
Article in English | MEDLINE | ID: covidwho-123936

ABSTRACT

With the coronavirus disease 2019 (COVID-19) pandemic, one of the major concerns is the direct medical cost and resource use burden imposed on the US health care system. We developed a Monte Carlo simulation model that represented the US population and what could happen to each person who got infected. We estimated resource use and direct medical costs per symptomatic infection and at the national level, with various "attack rates" (infection rates), to understand the potential economic benefits of reducing the burden of the disease. A single symptomatic COVID-19 case could incur a median direct medical cost of $3,045 during the course of the infection alone. If 80 percent of the US population were to get infected, the result could be a median of 44.6 million hospitalizations, 10.7 million intensive care unit (ICU) admissions, 6.5 million patients requiring a ventilator, 249.5 million hospital bed days, and $654.0 billion in direct medical costs over the course of the pandemic. If 20 percent of the US population were to get infected, there could be a median of 11.2 million hospitalizations, 2.7 million ICU admissions, 1.6 million patients requiring a ventilator, 62.3 million hospital bed days, and $163.4 billion in direct medical costs over the course of the pandemic.


Subject(s)
Coronavirus Infections/economics , Disease Outbreaks/economics , Health Care Costs/statistics & numerical data , Health Resources/economics , Hospital Costs/statistics & numerical data , Pandemics/economics , Pneumonia, Viral/economics , COVID-19 , Delivery of Health Care/economics , Disease Outbreaks/statistics & numerical data , Female , Health Resources/statistics & numerical data , Humans , Intensive Care Units/economics , Intensive Care Units/statistics & numerical data , Length of Stay/economics , Male , Monte Carlo Method , Pandemics/statistics & numerical data , United States
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