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| Author: | Bhatia, T. Wang, L. |
| Title: | Identifying physician peer-to-peer effects using patient movement data |
| Journal: | International Journal of Research in Marketing
2011 : MAR, VOL. 28:1, p. 51-61 |
| Index terms: | USA pharmaceutical industry medical care opinion leadership models |
| Freeterms: | patient movement data medical practice prescription behaviour social interactions social multiplier peer effects contagion |
| Language: | eng |
| Abstract: | This paper identifies and quantifies peer-to-peer effects using physician prescription data and patient movement data btw. physicians. The movements are classified into three types: 1. primary care physician (PCP) to specialist and back, 2. specialist to specialist (S-to-S), and 3. PCP to PCP. Using of in-depth physician interviews and surveys, there are found different reasons for these movements: PCP to PCP is purely patient-generated (herein as: pt-gen.), PCP to specialist is mostly physician-generated (as: phs-gen.), and specialist to specialist is a mix of patient- and physician-generated (as: pt+phs-gen.) movements. A simultaneous equations model is estimated on these three types of movements. It is found that in the purely pt-gen. movement sample (PCP to PCP), the physicians have a significantly negative effect on each other's prescription behaviour due to observational learning and congestion effects. In contrast, in the PCP to specialist sample and the specialist to PCP sample, the specialist is found to have a significantly positive effect on the PCP but not vice versa. Based on this result, there is suggested an opinion leader effect. S-to-S. movement is a mixed case, and the effect is insignificant in most cases etc. |
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