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Decoding a Doctor’s Prescription: A Study

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  • Cedric Thomas Silveira

Abstract

Doctors today have very little time to listen to a medical representative. They have become patient-centric and feel that listening to a medical representative is a waste of their time. Wishing to learn what could make a doctor prescribe a drug when visited by the medical representative, I drew up a questionnaire consisting of product-centric variables and non-product-based variables. The questionnaire had six variables, which had to be ranked from 1 to 6, with 1 being the most important and 6 being the least important. The variables were easy availability, economical drugs, company name, sponsorships, medical representative’s dedication, and samples among the non-product-based variables and safety, efficacy, tried and tested, less drug interactions, good reviews of the drug, and less adverse effects among the product-based factors. A total of 100 doctors were interviewed. A personal interview was conducted wherein the questionnaire was direct and structured. The results were such that in Thurstone Case V Scaling, economical drugs were considered as the most effective way to get doctors to prescribe, followed by easy availability, company name, medical rep dedication, samples, and sponsorships among the non-product-centric factors, whereas in the product-centric factors, it included efficacy, followed by time tested, less adverse effects, safety, less drug interactions, and good drug reviews. In Karl Pearson’s coefficient of correlation, it was found that a high, positive correlation existed between economical drugs and efficacious drugs and a medium, positive correlation existed between economical drugs and safe drugs. Similarly, a medium–high correlation existed between company name and time-tested drugs.

Suggested Citation

  • Cedric Thomas Silveira, 2023. "Decoding a Doctor’s Prescription: A Study," Jindal Journal of Business Research, , vol. 12(1), pages 73-84, June.
    • Handle: RePEc:sae:jjlobr:v:12:y:2023:i:1:p:73-84
    DOI: 10.1177/22786821231161247
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    References listed on IDEAS

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    1. Bhuvanesh Pareek & Qiang Liu & Pulak Ghosh, 2019. "Ask your doctor whether this product is right for you: a Bayesian joint model for patient drug requests and physician prescriptions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(1), pages 197-223, January.
    2. Farzana Elahi & Shamsad Ahmed & Mahbubul Haque & Nazreen Chowdhury, 2016. "An Empirical Investigation into Physician Preferences in Drug Prescription: An Integrated Methodology of AHP and QFD," International Journal of Marketing Studies, Canadian Center of Science and Education, vol. 8(5), pages 81-89, October.
    3. G Michael Allan & Joel Lexchin & Natasha Wiebe, 2007. "Physician Awareness of Drug Cost: A Systematic Review," PLOS Medicine, Public Library of Science, vol. 4(9), pages 1-11, September.
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