Doctor Shopping Behavior Among Cancer Patients: A Nationwide Population-based Study in Taiwan

Hsien-Chang Li, Yu-Ling Shiao, Chao Hsiun Tang, Wen Shan Jian, Nae-Fang Miao

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Objective: In this study, we used a nationwide population-based dataset in Taiwan to explore the clinical doctor shopping behavior (DSB) phenomenon and possible contributing factors that influence the choice to engage in DSB among cancer patients. Methods: A five-year nationwide population-based dataset was used. Of 62,155 cancer patients with DSB, 52,165 patients were included as our study sample. Results: The distribution rate of DSB was 83.93%, which was much higher than the rate reported in other questionnaire-designed research. The regression analysis showed strong associations between DSB and age, monthly income, residence area, urbanization level, and hospital type. Older patients were less likely (p

Original languageEnglish
Pages (from-to)172-176
Number of pages5
JournalJournal of Experimental and Clinical Medicine(Taiwan)
Volume5
Issue number5
DOIs
Publication statusPublished - Oct 2013

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Taiwan
Population
Neoplasms
Urbanization
Regression Analysis
Research
Datasets

Keywords

  • Cancer patient
  • Doctor shopping behavior
  • National Health Insurance
  • Nationwide population-based dataset

ASJC Scopus subject areas

  • Medicine(all)

Cite this

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abstract = "Objective: In this study, we used a nationwide population-based dataset in Taiwan to explore the clinical doctor shopping behavior (DSB) phenomenon and possible contributing factors that influence the choice to engage in DSB among cancer patients. Methods: A five-year nationwide population-based dataset was used. Of 62,155 cancer patients with DSB, 52,165 patients were included as our study sample. Results: The distribution rate of DSB was 83.93{\%}, which was much higher than the rate reported in other questionnaire-designed research. The regression analysis showed strong associations between DSB and age, monthly income, residence area, urbanization level, and hospital type. Older patients were less likely (p",
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AU - Jian, Wen Shan

AU - Miao, Nae-Fang

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