Browsing by Author "Tapaneeyakul, Sasathorn"

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    CDC Case Report Data for COVID-19: Characterizing the Pandemic with Limited Information
    (James A. Baker III Institute for Public Policy, 2021) Ho, Vivian; Short, Marah Noel; Tapaneeyakul, Sasathorn; James A. Baker III Institute for Public Policy
    Nationwide standardized surveillance of COVID-19 using the U.S. Center for Disease Control (CDC)'s COVID-19 case report forms could yield invaluable information on disease burden and the nature of virus transmission. If respondents provided comprehensive responses to the form’s queries, public health officials, policymakers, and business leaders would have a wealth of data when making critical decisions on where to direct testing and treatment resources, and how to conduct safe reopenings. We obtained CDC case reports through July 19, 2020 through an expedited Freedom of Information Act request. We examined data from May 5 through July 19 to determine completeness of CDC case counts relative to more accurate counts reported by the New York Times (NYT). We found that the CDC’s case reports contained surprisingly incomplete information relative to the amount that the agency’s official form was intended to collect. Only seven states had sufficient data to characterize cases by ethnicity or race, or exposure type. People age 20 to 39 accounted for more COVID-19 cases than their share of the population. The most infections for all ages tended to occur during the third time period (June 24 through July 19) in our sample. White people were infected in proportion to their share of the population, while Hispanic cases were overrepresented. The most common sources of exposure were workplaces and households.
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    Using Medicare data to measure vertical integration of hospitals and physicians
    (Springer Nature, 2020) Ho, Vivian; Tapaneeyakul, Sasathorn; Metcalfe, Leanne; Vu, Lan; Short, Marah Noel; James A. Baker III Institute for Public Policy
    Researchers, healthcare providers, and policy makers have become increasingly interested in the cost and quality effects of vertical integration (VI) between hospitals and physicians. However, tracking VI is often financially costly. Because the Medicare Data on Provider Practice and Specialty (MD-PPAS) annual dataset may be more cost-effective for researchers to access than private data sources, we examine the accuracy of MD-PPAS in identifying VI by comparing it to physician and hospital affiliations reported in Blue Cross Blue Shield Texas (BCBSTX) PPO claims data for 2014–2016. The BCBSTX data serve as a gold standard, because physician–hospital affiliations are based on the insurer’s provider contract information. We merged the two datasets using the physician National Provider Identifier (NPI), then determined what percentage of physicians had the same Tax Identification Number (TIN) in both sources, and whether the TIN implied the physician belonged to a physician- or hospital-owned practice. We found that 71.3% of successfully matched NPIs reported the same TIN, and 95.1% of patient-level observations were attributed to organizations with the same ownership type in both datasets, regardless of TIN. We compared regression estimates of patient-level annual spending on an indicator variable for physician versus hospital ownership for the primary attributed physician and found that estimates were within one percentage point whether one determined VI based on the BCBSTX or the MD-PPAS data. The results suggest that MD-PPAS, which costs less to obtain than from a for-profit data source, can be used to reliably track VI between hospitals and physicians.