健保藥價給付之因素分析－以抗微生物製劑為例

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Title:	健保藥價給付之因素分析－以抗微生物製劑為例
Authors:	王家偉;Wang, Chia-Wei
Contributors:	產業經濟研究所在職專班
Keywords:	健保藥價;抗微生物製劑;普通最小平均法(OLS);二階段最小平方法(2SLS);health insurance drug prices;antimicrobial agents;ordinary least averaging (OLS);two stage least square(2SLS)
Date:	2024-05-27
Issue Date:	2024-10-09 16:27:12 (UTC+8)
Publisher:	國立中央大學
Abstract:	台灣全民健保政策自民國86年開辦以來嘉惠國民，不僅照顧到經濟弱勢民眾，更讓台灣醫療愈加普及，使得國民平均壽命日漸增加。但相對的也帶來了全民健保沉重的財務虧損，有鑑於此，衛生福利部中央健康保險署逐步調整健保給付藥物價格，實施健保藥物保險給付調整機制，以減少全民健保財務虧損之衝擊。故本文探討抗微生物製劑歷年來健保藥價給付之因素，試圖以特徵價格分析健保藥價給付之決定因素，研究方法以衛生福利部中央健康保險署民國106年~111年公告健保用藥品項之藥價給付所記載藥品之類型設立虛擬變數，以普通最小平均法(OLS)建立價格給付模型分析影響現行整體抗微生物製劑之顯著因素，探討相較控制組之原因及差異；另外，本研究也試圖分析健保藥價在不同藥品分類樣本對健保藥品使用量之影響，以二階段最小平方法(2SLS)估計需求分析模型，探討二者變化之原因。依價格給付模型特徵實證結果顯示，年度使用量具有顯著負相關性。適應症方面，抗腫瘤藥和免疫抑制劑對藥價給付影響最高，依序為消化系統和代謝用藥、泌尿生殖系統用藥和性荷爾蒙相關用藥及全身性抗感染藥呈現顯著正相關性；抗蟲藥、痔瘡用藥及荷爾蒙類用藥則呈現顯著負相關性。學名藥、第一線藥品、單方藥品及口服藥品亦具顯著正相關性；注射藥品則呈現顯著負相關性。需求分析模型區分不同藥品分類樣本中，抗腫瘤藥和免疫抑制劑、全身性抗感染藥及後線藥品需求彈性小於1，其餘藥品則無此情形；注射藥品則因缺藥影響，且無替代性造成需求彈性呈現正數，顯示藥品的特殊性及使用的急迫性的確會影響藥品的需求彈性。;Since its inception in 1997, Taiwan′s National Health Insurance (NHI) policy has benefited the populace by not only catering to economically disadvantaged individuals but also by promoting widespread access to healthcare services, leading to a gradual increase in the average life expectancy of citizens. However, this expansion of coverage has also resulted in significant financial deficits for the NHI system. In response to these challenges, the National Health Insurance Administration (NHIA) under the Ministry of Health and Welfare has gradually adjusted the drug prices and implemented medication insurance payment mechanism covered by the NHI scheme to mitigate the financial burden on the system. Therefore, this study aims to examine the factors influencing the reimbursement of antimicrobial agents under the NHI scheme over the years. It seeks to analyze the determinants of NHI drug reimbursement using hedonic price analysis. The research methodology involves establishing virtual variables based on the types of drugs listed in the NHIA′s announcements of reimbursable drug items from 2017 to 2022. Ordinary Least Squares (OLS) regression analysis is then employed to construct a price reimbursement model and analyze the significant factors affecting the overall reimbursement of antimicrobial agents, comparing them to control groups and identifying differences. Moreover, this research attempts to analyze the impact of NHI drug prices on the usage of antimicrobial agents across different drug categories. It establishes a demand analysis model using two-stage least squares methods (2SLS) to investigate the reasons for changes in both variables. Therefore, this study aims to examine the factors influencing the factor of reimbursement for antimicrobial agents under the NHI over the years. It seeks to analyze the determinants of reimbursement factor for these medications. The research methodology involves establishing dummy variables based on the types of medications listed in the NHIA′s announcements of reimbursable drug items from 2016 to 2022. Ordinary Least Squares (OLS) regression analysis is then employed to identify significant factors affecting the overall reimbursement of antimicrobial agents. Moreover, the study investigates the reasons for compared to the control group and identifies any differences therein. According to the empirical results of the price reimbursement model, annual usage exhibits a significant negative correlation. Regarding indications, antineoplastic drugs and immunosuppressants have the highest impact on drug reimbursement, followed by medications for the digestive system and metabolism, medications for the genitourinary system and hormonal-related medications, and systemic anti-infective agents, which show significant positive correlations. Conversely, anthelmintic drugs, medications for hemorrhoids, and hormonal medications exhibit significant negative correlations. Generic drugs, first-line medications, single-ingredient medications, and oral medications also show significant positive correlations, whereas injectable medications show significant negative correlations. In the demand analysis model, among different drug categories, the demand elasticity for antineoplastic drugs, immunosuppressants, systemic anti-infective agents, and second-line medications is less than 1, while other medications do not exhibit this pattern. Injectable medications, on the other hand, show positive demand elasticity due to drug shortages and lack of alternatives, indicating that the uniqueness and urgency of medication usage can indeed influence demand elasticity.
Appears in Collections:	[Executive Master of Industrial Economics] Electronic Thesis & Dissertation

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