Week12- Reading Summary- Leting Zhang
Bhargava, H. K., & Mishra, A. N. (2014). Electronic medical records and physician productivity: Evidence from panel data analysis. Management Science, 60(10), 2543-2562.
This paper examines the impact of EMRs on physician productivity. There are two specific questions: 1. Does physician productivity change over time as a result of EMR implementation? 2. Does this impact differ for physicians of different specialties?
The conceptual foundations for this study mainly based on three streams of literature. The first is physician productivity, WRVUs are used to measure it. they are relative value units generated for clinical activities; the second stream is IT- Enabled productivity, extant research shows there may be significant differences between IT’s impact during short-term and long-term; the third stream is Task-Technology Fit, the paper points out the two main functions of EMRs are information review and information entry, given that physicians of different specialities have different demand for the EMRs, the productivity impacts of EMRs on them are likely to vary.
This study uses data includes monthly physician schedule and production in a healthcare system from 2003 to 2006, in the period, EMR system was implemented across clinics. Some exploratory data analyses show EMR’s impacts on productivity are significantly different in first months and after six months, then they estimated the learning period empirically. Next, they use OLS to estimate the model which accounts for the heterogeneous in physicians and clinics. Lastly, they use Arellano- Bond system GMM estimation which eliminates bias from unobserved heterogeneity by first-differencing and from endogeneity by using instrumental variables of available lags and levels.
Results show 1. FPs and Peds are less productive in the stable phase in comparison to IMs. The net impact of EMRs is better on IM than FPs and Peds. 2. FPs and Peds experience a decrease in productivity compared to IMs in the learning phase.