Background: The demand for cosmetic surgery and services has diminished with recent fluctuations in the economy. To stay ahead, surgeons must appreciate and attend to the fiscal challenges of private practice. A key component of practice economics is knowledge of the common methods of payment.
Objective: To review methods of payment in a five-surgeon group practice in central Texas, USA.
Methods: A retrospective chart review of the financial records of a cosmetic surgery centre in Texas was conducted. Data were collected for the five-year period from 2003 to 2008, and included the method of payment, the item purchased (product, service or surgery) and the dollar amount.
Results: More than 11,000 transactions were reviewed. The most common method of payment used for products and services was credit card, followed by check and cash. For procedures, the most common form of payment was personal check, followed by credit card and financing. Of the credit card purchases for both products and procedures, an overwhelming majority of patients (more than 75%) used either Visa (Visa Inc, USA) or MasterCard (MasterCard Worldwide, USA). If the amount of the individual transaction surpassed US$1,000, the most common method of payment transitioned from credit card to personal check.
Conclusions: In an effort to maximize revenue, surgeons should consider limiting the credit cards accepted by the practice and encourage payment through personal check.
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Int J Clin Pharm
January 2025
Division of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Khon Kaen University, Khon Kaen, 40002, Thailand.
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Department of Preventive Medicine, Gachon University College of Medicine, Incheon, Korea.
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PLoS One
January 2025
Department of Human Sciences, College of Education and Human Ecology, The Ohio State University, Columbus, Ohio, United States of America.
This study focuses on the initial wave of the COVID-19 pandemic in Spring 2020 in the United States to assess how liquidity constraints were related to loneliness among older adults. Data are from the COVID Impact Survey, which was used to collect data in April, May and June 2020 across the U.S.
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Beijing Wuzi University, Beijing, China.
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December 2024
Infineon Technologies, Free Trade Zone, Batu Berendam, Melaka 75350, Malaysia.
Credit card usage has surged, heightening concerns about fraud. To address this, advanced credit card fraud detection (CCFD) technology employs machine learning algorithms to analyze transaction behavior. Credit card data's complexity and imbalance can cause overfitting in conventional models.
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