How are Electronic Health Records Associated with Provider Productivity and Billing in Orthopaedic Surgery?
Authors: Dandu Navya , Zmistowski Benjamin , Chen Antonia F. , Chapman Talia , Howley Michael 
Published: August 2019

Abstract

Background
Electronic health records (EHRs) have become ubiquitous in orthopaedics. Although they offer certain benefits, they have been cited as a factor that can contribute to provider burnout. Little is known about the degree to which EHR adoption is associated with provider and practice characteristics or outpatient and surgical volume.

Questions/purposes
(1) What was the rate of EHR adoption in orthopaedics and how are physician and practice characteristics associated with adoption? (2) How is EHR adoption related to outpatient productivity? (3) How is EHR adoption associated with surgical volume?

Methods
We conducted this retrospective analysis by linking three publicly available Medicare databases, which we chose for their reliability in reporting because they are provided by a government-funded entity. We included providers in the 2016 Physician Compare dataset who reported a primary specialty of orthopaedic surgery. The EHR adoption status for these providers between 2011 and 2016 was determined using the Meaningful Use Eligible Professional public use files, which we chose to standardize both adoption and usage of EHRs. Provider characteristics, from the Physician Compare dataset, were compared between non-adopters, early adopters (who adopted EHR in 2011 and 2012), and late adopters (2016) using a multivariate logistic analysis, due to the binary nature of the dependent variable (adoption). To measure productivity and billing, we used the 2012 and 2016 Medicare Utilization and Payment datasets. To measure productivity before and after EHR adoption, we compared the number of services for select Current Procedural Terminology codes between 2012 and 2016 for providers who first adopted EHR in 2013, and performed the same comparison for non-adopters for the same years. Paired t-tests were used where volume in 2012 and 2016 were being compared, and multivariate analysis was performed.

Results
By 2016, 10,904 of 21,484 orthopaedic providers (51%) had adopted EHRs, with an increase from 8% to 46% during the incentive phase (2011 to 2014) and an increase from 44% to 51% during the penalty phase (2015 to 2016). After analyzing factors associated with adoption, it was most notable that for every additional year since graduation, the odds of adopting EHR later increased by 4.14 (95% confidence interval 4.00 to 4.33; p < 0.001). After adoption, providers who adopted EHRs increased the mean number of Medicare outpatient visits per year from 439 to 470 (mean difference, increase of 31 procedures [95% CI 24 to 39]; p < 0.001), and providers who did not use EHRs decreased from 378 to 368 visits per year (median difference, decrease of 10 procedures [95% CI 8.0 to 12.0]; p < 0.001). EHR was not associated with billing for Level 4-5 visits, after adjusting for practice size and pre-adoption volumes (p = 0.32; R2 = 0.51). EHR adoption was not associated with surgical volume for 10 of 11 common orthopaedic procedures. However, two additional TKA procedures annually could be attributed to EHR adoption, when compared with non-adopters (p = 0.03; R2 = 0.65). After adoption, orthopaedic surgeons increased their annual TKA volume from 42 to 48 (mean difference, increase of 6 [95% CI 4.0 to 7.0]; p < 0.001), while non-adopting orthopaedic surgeons increased their annual surgical volume for TKA from 28 to 30 (median difference, increase of 2 [95% CI 2.0 to 4.0]; p < 0.001).

Conclusions
In orthopaedics, the Health Information Technology for Economic and Clinical Health (HITECH) Act resulted in approximately half of self-reported orthopaedic surgeons adopting EHR from 2011 to 2016. Considering the high cost of most EHRs and the substantial investment in adoption incentives, this adoption rate may not be sufficient to fully realize the objectives of the HITECH Act. Diffusion of technology is a vast field of study within social theory. Prominent sociologist Everett M. Rogers details its complexity in Diffusion of Innovations. Diffusion of technology is impacted by factors such as the possibility to sample the innovation without commitment, opinion leadership, and observability of results in a peer network, to name a few. Incorporating these principles, where appropriate, into a more focused action plan may facilitate technological diffusion for future innovations. Lastly, EHR adoption was not associated with higher-level billing or surgical volume. This might suggest that EHRs have not had a meaningful clinical benefit, but this needs to be further investigated by relating these trends to patient outcomes or other quality measures.

Level of Evidence
Level III, therapeutic study.