Trends in Inpatient Admission Comorbidity and Electronic Health Data: Implications for Resident Workload Intensity

This retrospective, observational study shows that patient comorbidity and EHR data burden have increased over time, both of which impact resident workload at the time of admission. These findings, combined with the duty hour regulations, suggest that resident workload intensity at the time of admission may be increasing over time.

Patient comorbidity has likely increased due to a combination of factors. Elective admissions have decreased, and demographics have changed consistent with an aging population. Trainee admissions patterns also have changed over time, with less-acute admissions often admitted to nonacademic providers. Additionally, there are more stringent requirements for inpatient admissions, resulting in higher acuity and comorbidity.

As EHRs have matured and documentation requirements have expanded, the amount of electronic data has grown per patient, substantially increasing the time required to review a patient’s medical record.^5,10 In our evaluation, all EHR metrics increased between 2003 and 2011. The only metric that did not increase between 2011 and 2015 was the mean number of medications. The number of notes per patient has shown a dramatic increase. Even in an EHR that has reached maturity (in use more than 10 years), the number of notes per patient still increased by greater than 50% between 2011 and 2015. The VA EHR has been in use for more than 15 years, making it an ideal resource to study data trends. As many EHRs are in their infancy in comparison, these data may serve as a predictor of how other EHRs will mature. While all notes are not reviewed at every admission, this illustrates how increasing data burden combined with poor usability can be time consuming and promote inefficient patient care.¹¹ Moreover, many argue that poor EHR usability also affects cognitive workflow and clinical decision making, a task that is of utmost value to patient quality and safety as well as resident education.¹²Common program requirements for internal medicine as set forth by the ACGME state that residency programs should give adequate attention to scheduling, work intensity, and work compression to optimize resident well-being and prevent burnout.¹³ Resident workload intensity is multifaceted and encompasses many elements, including patient census and acuity, EHR data assessment, components of patient complexity such as comorbidity and psychosocial situation, and time.¹³ The work intensity increases with increase in the overall patient census, complexity, acuity, or data burden. Similarly, work intensity increases with time restrictions for patient care (in the form of duty hours). In addition, work intensity is affected by the time allotted for nonclinical responsibilities, such as morning reports and conferences, as these decrease the amount of time a resident can spend providing patient care.

Many programs have responded to the duty hour restrictions by decreasing patient caps.¹⁴ Our data suggest that decreasing patient census alone may not adequately mitigate the workload intensity of residents. There are other alternatives to prevent the increasing workload intensity that may have already been employed by some institutions. One such method is that programs can take into account patient complexity or acuity when allocating patients to teaching teams.¹⁴ Another method is to adjust the time spent on ancillary tasks such as obtaining outside hospital records, transporting patients, and scheduling follow-up appointments. Foregoing routine conferences such as morning reports or noon conferences would decrease work intensity, although obviously at the expense of resident education. Geographic rounding can encourage more efficient use of clinical time. One of the most difficult, but potentially impactful strategies would be to streamline EHRs to simplify and speed documentation, refocus regulations, and support and build based on the view of clinicians.¹⁵

The main limitations of this study include its retrospective design, single-center site, and focus on the internal medicine admissions to a VA hospital. Therefore, these findings may not be generalizable to other patient populations and training programs. Another potential limitation may be that changes in documentation practices have led to “upcoding” of patient comorbidy within the EHR. In addition, in this study, we looked only at the data available at the time of admission. To get a more complete picture of true workload intensity, understanding the day-to-day metrics of inpatient care would be crucial.

Our study demonstrates that components of resident workload (patient comorbidity and EHR data burden), specifically at the time of admission, have increased over time. These findings, combined with the duty hour regulations, suggest resident workload intensity at the time of admission has increased over time. This can have significant implications regarding graduate medical education, patient safety, and burnout. To optimize resident workload, innovation will be required in the areas of workflow, informatics, and curriculum. Future studies to assess the workload and intensity of the course of the entire patient hospitalization are needed.