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SPECIAL FEATURE Test sensitivity and specificity


influence cost of pandemic Impact of SARS-COV-2 test on total charges for treating suspected COVID-19


patients in a tertiary academic medical center in Central Texas. By Arundhati Rao, MD, PhD; Briget M da Graca, JD, MS; Nguyen Nguyen, PhD; Alejandro C. Arroliga, MD; William Koss, MD; Eduardo Castro, MD, MPH; Shekhar Ghamande, MD; Alita Risinger; Manohar Mutnal, PhD; and Amin. A. Mohammad, PhD.


Introduction A major concern of the COVID-19 pandemic is the financial burden imposed on the U.S. healthcare system, which has been expressed by elected officials, healthcare economists and health professionals.1,2,3 Monte Carlo simulation analysis suggests that if 20%


of the U.S. population were to be 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 medi- cal costs over the course of the pandemic.4


An analysis per-


formed by Kaiser Family Foundation estimated the average cost of COVID-19 treatment for a patient with employer- based insurance and without complications at $9,763, and this could double or more with complications.5 Laboratory tests help diagnosis multiple diseases, includ- ing COVID-19, such as a positive reverse-transcriptase poly- merase chain reaction (rtPCR) to confirm diagnosis. Based on symptom severity, a patient may go home to self-quarantine for 14 days or may be admitted to a COVID-19 care unit. The rtPCR test results could be true positive (TP), true negative (TN), false positive (FP) or false negative (FN). The probability of each is determined by the test sensitivity and specificity, which has a huge impact on how a patient is treated, a fact often overlooked. The most routinely used rtPCR test has a sensitivity ranging from 60–90%, depending on numer- ous pre-analytic and analytic variables, including when the patient is tested after symptom onset.6 Sensitivity defines the proportion of patients with the


disease who will have a positive result, which is useful in ruling out a disease with a negative test. On the other hand, the specificity of a test is the proportion of people without the disease who will have a negative result, which is use- ful for ruling in a disease if a person tests positive.7


From


a clinician’s perspective, positive and negative predictive values for a given test are the most important parameter. The positive predictive value (PPV) of a test is the proportion of people with a positive test result who actually have the disease. The negative predictive value (NPV) of a test is the proportion of people with a negative test result who do not have the disease. Both PPV and NPV are highly dependent on the prevalence of a disease in the population. A test with good sensitivity will have moderate to low PPV if it is used in locales with low disease prevalence. Responding to the pandemic, the U.S. Food and Drug


Administration (FDA) started issuing emergency use autho- rizations (EUAs) on February 4, 2020,8


4 CLR 2021-2022 • MLO • www.clr-online.com resulting in a plethora


of rtPCR and serological tests flooding the marketplace.9 Since laboratory tests play a pivotal role in triaging patient care, the PPV of the test has a significant impact on over- all cost burden. With such a wide range of tests available for COVID-19, the varying sensitivities and specificities of these tests will affect the overall cost for treating patients in emergency departments suspected of having COVID-19. While many publications discuss the diagnostic impact of test characteristics on a patient’s outcome, the impact of test sensitivity and specificity on overall treatment cost for COVID-19 patients has not yet been addressed.10,11, 12 The emergency department (ED) at our tertiary aca-


demic medical center (Baylor Scott & White Medical Center – Temple, TX) annually treats 102,000 patients, and approximately 40% (40,800) of these patients have symp- toms, per guidelines from the Centers for Disease Control and Prevention (CDC), suspicious for COVID-19. We found


Exhibit 1: Assumptions used for deterministic simulation analysis Number of Patients seen in Emergency Department annually 102,000


Number of Patients with CDC defined symptoms for COVID-19


40,800


Average Charge for True Positive COVID-19 patient per day $7,815 Average Charge for False Positive COVID-19 patient per day $7,815 Average Charge for True Negative COVID-19 patient


$3,208


Average Initial Charge of False Negative COVID-19 patient $3,208 Length of Stay for True Positive COVID-19 Length of Stay for False Positive COVID-19


ED room Length of Stay for True and False Negative patient 1 day Infectivity of False Negative Patient i.e. R0


1


Exhibit 2: Comparing LOS and charges/LOS for COVID-19 and non-COVID- 19 patients


COVID-19 patients Discharged From ED N = 151


Length of Stay


1.3 – 12 h


364.0 - 10130.0


COVID-19 Patients Admitted N = 17


Median 95% CI Median 95% CI 3.3 h


3.4 d Charges / LOS ($) 3208 7815 2.2 – 4.6 d


4596.0 – 8446.0


CI = confidence interval; ED = emergency department; LOS = length of stay


3.4 days 2 days


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