The Impact of Electronic Health Record Use on Physician Productivity
Published Online: November 25, 2013
Julia Adler-Milstein, PhD; and Robert S. Huckman, PhD
The centerpiece of the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act is $27 billion in incentives for providers who demonstrate “meaningful use” of electronic health records (EHRs).1 The legislation was motivated by the belief that EHRs used in specific ways (eg, medication order entry with alerts for drug-drug interactions) would make care safer, more effective, and more efficient. The meaningful use measures specify the activities that must be performed using an EHR,2 leaving ambulatory practices and hospitals to determine how to structure their work to accomplish them.
A major concern among physicians is that EHR adoption will hamper their productivity.3 This concern is not without merit—several studies have shown that physicians spend extra time entering data into the EHR, which cuts into time with patients and can extend the length of the workday.4,5 One strategy for dealing with this productivity loss is to rely on support staff to perform EHR-related tasks. However, when work is interdependent, delegation has its own costs; it increases the need for coordination, which may require additional physician time.6 Because scope-of-practice regulations prevent support staff from performing many clinical activities autonomously, physicians who successfully delegate must still spend time reviewing and authorizing staff activities.
For example, a physician who uses support staff to enter orders into an EHR must review and sign them before they are submitted. It is unclear whether (or under what conditions) efficiency gains from delegation exceed the time required to communicate the orders that need to be entered, reviewed, and in some cases, corrected. Across all clinical activities, there is little empirical evidence to guide physicians about whether it is optimal to off-load EHR-related tasks to support staff, or whether doing so would make them less efficient due to costs of oversight and coordination.7
Our study used monthly EHR task-log data from more than 40 primary care practices to examine the relationship between physician productivity, the degree of EHR use, and the delegation of EHR tasks. We first examined the independent effects of EHR use and delegation on productivity, and then assessed their joint impact on productivity to shed light on whether delegation and EHR use operate as complements or substitutes. Finally, we explored whether these relationships differ by practice size. Our findings offer insight into how primary care practices can structure their work after adopting an EHR to ensure that EHR use does not harm productivity.
Sample, Data and Measures
We obtained panel data for all of the primary care and internal medicine practices (n = 42) that use both a web-based EHR and a billing and practice management system from athenahealth Inc (Watertown, Massachusetts). Practices were distributed throughout the country and had on average 4 clinicians (range, 1-14). The average length of time that practices used the EHR was 17 months, with a minimum of 6 months. All practices in our sample employed at least 1 clinical support staff member and therefore had the ability to delegate from clinicians (those who can bill for clinical services, predominantly physicians but also including nurse practitioners and physician assistants) to clinical support staff (eg, registered nurse, licensed practical nurse, medical assistant). Our data included monthly measures at the practice level from May 2006 through May 2009. Observations were included for each practice with at least 6 months of experience, beginning in the first full month after it adopted the EHR and ending in May 2009, when athenahealth created the data set (n = 695 practice-month observations).
We relied on data from 2 sources: (1) the billing and practice management software and (2) the EHR. The billing and practice management software captures practice and staff demographics, monthly appointment volume, and monthly billing data. The EHR tracks each of hundreds of discrete, time-stamped actions associated with patient care. These actions are best thought of as changes to fields within the EHR. For descriptive purposes, they are grouped into a more meaningful and manageable list of 32 clinical tasks. For example, the task “collect vitals” includes 30 fields (eg, height, weight) and a change to any field is captured as a distinct action (eAppendix Table 1, available at www.ajmc.com). The vendor then generated a data set with a count of the number of actions, grouped by task, performed by each staff member per month. We used these 2 data sources to create the measures of productivity, EHR use, and delegation described below.
Productivity. Physician efficiency and productivity have been defined and studied in a number of ways.8-16 In the context of EHRs, physician productivity is most commonly used to refer to throughput—the number of services delivered in a given period of time. Physicians carefully weigh whether to make practice changes (eg, EHR adoption) based on their perception of whether the change affects this dimension of productivity. We measured monthly productivity at the practice level using work relative value units (RVUs), standardized units of production in healthcare that reflect the volume and intensity of services provided, and serve as the basis for fee-for-service reimbursement. Work RVUs are captured in the billing and practice management system, and include all work RVUs for which the practice billed, regardless of whether they were reimbursed by the specific payer. For each practice, we divided total work RVUs per month by the number of clinician workdays in the month. We then log transformed this variable to approximate a normal distribution. (We ran all our models with the untransformed version of the dependent variable to confirm that no results were driven by the transformation.)
PDF is available on the last page.