Study Reveals Low EMR Adoption Rates despite the HITECH Act


In an effort to streamline patient data acquisition and management and decrease healthcare costs, the US congress passed the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act- a subsidy program that provides up to $27 billion to motivate hospitals to adopt the Electronic Medical Records (EMR) system. However, results from a recent study indicate that the incentive program may be only marginally successful in its goal of integrating EMR in hospitals. The study was conducted by David Dravone and colleagues at the Kellogg School of Management and published by the National Bureau of Economic Research.

What is EMR?

EMR is an electronic (as opposed to paper-based) repository of patient or population data that promises to transform the healthcare industry by decreasing costs, reducing errors, increasing data quality, and facilitating data storage and management. EMRs can be categorized as either basic or advanced (also see Box 1). Basic EMR includes applications such as Clinical Decision Support and Clinical Data Repository that are easy to implement and have been widely adopted even before the advent of the HITECH act. Advanced EMRs such as Physician Documentation and Computerized Physician Order Entry are more expensive and complicated. Adopting advanced EMRs can cost hospitals $10 million or more, depending on the hospital size and complexity of the applications. Thus, it is of no surprise that hospitals have been reluctant in integrating advanced EMRs with their system.


The 2009 subsidiary act has allocated Medicare and Medicaid payments of up to $27 billion for clinicians and hospitals that use EMRs in their daily practices. To qualify, providers should own an EMR system and demonstrate an integral use in patient data collection and storage.

The Study

In their study, the researchers sought to determine the extent to which the HITECH incentive program increased EMR adoption. To do so, a baseline was determined with EMR adoption rates from 2006- 2008. Compared to baseline, the team found that adoption rate increased from 48% in 2008 to 77% in 2011. Using statistical analyses, the team also determined that without the HITECH incentives, the adoption rate for 2011 would have been 67% and 77% by 2013. Thus, the authors concluded that only 10% of hospitals adopted the EMR system as a result of the HITECH act.[i]

The Good News

The study findings prognosticate a general upward trend in hospital adoption of EMR, given that only 10% of the total adoption rate in 2011 was attributed to the HITECH incentive program. Interestingly, according to a 2013 CDC report, 69% of office-based physicians surveyed intended to apply to the HITECH program to incorporate EMR in their practices, indicating a generally positive buzz about the program among providers.[ii] Nevertheless, the news is good for patients, given the fact that quality of care is indeed better in hospitals using EMR.[iii]

BOX 1: Types of EMR[iv]

  1. Physician- Hosted System: An EMR system where the data is stored in the provider’s own server. The provider holds the responsibility of purchasing all relevant hardware and software and storing, securing, and maintaining the data.

2: Remotely-Hosted system: An EMR system where the data is stored with an independent vendor’s servers. The independent vendor holds the responsibility of maintaining and storing the data. The vendor also controls the data.

[i] Dravone et al. Investment Subsidies and the Adoption of Electronic Medical Records in Hospitals. NBER Working Paper Series. 20553: Oct 2014

[ii] Hsiao CJ and Hing E. Use and characteristics of electronic health records systems among office-based physician practices: United States 2001-2013. NCHS Data Brief. 2013

[iii] Cebul, Randall D.; Love, Thomas E.; Jain, Anil K.; Hebert, Christopher J. (2011). “Electronic Health Records and Quality of Diabetes Care”. New England Journal of Medicine 365 (9): 825–33

[iv] Neal D. Choosing an Electronic Health Records System. Innovations in clinical neuroscience 8:6 2011 Jun pg 43-45


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