In private practice, physician-lead practice groups, and academic medical centers alike, there is often an emphasis placed on productivity. How many cases are completed per day, what is the turnover time, and how has patient census changed over time? In smaller practices, it is more feasible to directly see the effects of individual productivity on the practice at-large. However, in more dispersed large group practices, or more largely in academic medical centers, it can become opaque to specifically elucidate the relationship between clinical productivity and outcomes. By effectively measuring productivity in the field, clinicians, departmental leadership, and policy-makers can access the tools to employ interventions for change.
In the field of anesthesiology, it can be complex to discern clinical productivity in terms of individual anesthesiologist performance, as compared to the perioperative outcomes more broadly. Historically, it was thought that productivity could be measured by benchmarking individual physicians to accepted standards through timely evaluations by trained staff[1]. In this way, it was conceived that the total productivity of the practice could be thought of the sum of its parts, the parts referring to individual clinician performance. However, in recent years this ideology has experienced a challenge from the health economics community, due to the notion that a per-physician measurement may represent an oversimplification of the issue.
In lieu of measuring on a per-physician basis, Dr. Amr Abouleish, MD, MBA, an anesthesiologist and health economics researcher, has advocated for measuring productivity on a per-operating room (OR) basis[2]. The primary reason for this perspective, is that Dr. Abouleish’s research suggests that global analysis metrics related to turnover may actually impact clinical productivity outcomes more so than individual performance. Delay is one salient example. The research has shown that a perioperative delay of more than 40 minutes may detrimentally impact clinical workflow and census throughout the day, providing a viable limit to an oft-measured productivity metric. It is thus suggested that by reducing delays to 40 minutes, at an optimal of 35 minutes, significant time and costs can be saved.
To address this line of discussion, how can delays be reduced, particularly in cases that include visits to the pharmacy alongside the OR? Abouleish suggests modeling as one viable solution, providing examples of time-dependent schematics that advised physician trainees on the most timely and cost-effective pathways for delivering care in one institution. Undoubtedly, a variety of solutions exist to reduce delay-time, and may serve as a subject for future research. Yet, the underlying objective is to establish that by addressing per-OR metrics, change at the facility level can be made. Hence in this way, facilities could focus on either, increasing caseload, or alternatively, ensuring revenue whilst saving time for providers, depending on the model of that institution.
Measuring
productivity is primarily about data input. A hospital or healthcare site must
have the infrastructure to rapidly, and with ease, collect a large amount of
data related to patient flow, census, and outcomes. Yet, perhaps more important
than the collection of data, is the analysis of said data in order to form an
accurate measurement of the site’s clinical productivity. To achieve this
objective will require the share of knowledge between researchers and
providers, practice leaders and policy-makers, each of whom carry diverse and
distinct perspectives. By measuring productivity in the field of
anesthesiology, it allows for the establishment of interventions, thereby
continuing to improve the quality and delivery of care for all patients.
[1] Amr E. Abouleish, Mark H. Zornow, Ronald S. Levy, James Abate, Donald S. Prough; Measurement of Individual Clinical Productivity in an Academic Anesthesiology Department. Anesthesiology 2000;93(6):1509-1516.
[2] Amr E. Abouleish, Mark E. Hudson, Charles W. Whitten; Measuring Clinical Productivity of Anesthesiology Groups: Surgical Anesthesia at the Facility Level. Anesthesiology 2019;130(2):336-348. doi: 10.1097/ALN.0000000000002398.