Physicians prescribe fewer analgesics during night shifts than day shifts.

Adequate pain management is one of the biggest challenges of the modern healthcare system. Physician perception of patient subjective pain, which is crucial to pain management, is susceptible to a host of potential biases. Here we explore the timing of physicians' work as a previously unrecognized source of systematic bias in pain management. We hypothesized that during night shifts, sleep deprivation, fatigue, and stress would reduce physicians' empathy for others' pain, leading to underprescription of analgesics for patient pain relief. In study 1, 67 resident physicians, either following a night shift or not, performed empathy for pain assessment tasks and simulated patient scenarios in laboratory conditions. As predicted, following a night shift, physicians showed reduced empathy for pain. In study 2, we explored this phenomenon in medical decisions in the field. We analyzed three emergency department datasets from Israel and the United States that included discharge notes of patients arriving with pain complaints during 2013 to 2020 (n = 13,482). Across all datasets, physicians were less likely to prescribe an analgesic during night shifts (compared to daytime shifts) and prescribed fewer analgesics than generally recommended by the World Health Organization. This effect remained significant after adjusting for patient, physician, type of complaint, and emergency department characteristics. Underprescription for pain during night shifts was particularly prominent for opioids. We conclude that night shift work is an important and previously unrecognized source of bias in pain management, likely stemming from impaired perception of pain. We consider the implications for hospitals and other organizations employing night shifts.

A review of verbal order policies in acute care hospitals.

BACKGROUND: Although verbal and telephone orders (VOs) are commonly used in the patient care process, there has been little examination of the strategies and tactics used to ensure their appropriate use or how to ensure that they are accurately communicated, correctly understood, initially documented, and subsequently transcribed into the medical record and ultimately carried out as intended. A systematic review was conducted of hospital verbal and telephone order policies in acute care settings. METHODS: A stratified random sample of hospital verbal and telephone order policy documents were abstracted from critical access, rural, rural referral, and urban hospitals located in Iowa and Missouri and from academic medical centers from across the United States. FINDINGS: Substantial differences were found across 40 acute care settings in terms of who is authorized to give (including nonlicensed personnel) and take VOs and in terms of time allowed for the prescriber to cosign the VO. When a nonphysician or other licensed prescriber was allowed to communicate VOs, there was no discussion of the process to review the VO before it was communicated in turn to the hospital personnel receiving the order. Policies within several of the same hospitals were inconsistent in terms of the periods specified for prescriber cosignature. Few hospitals required authentication of the identity of the person making telephone VOs, nor the use of practices to improve communication reliability. CONCLUSION: Careful review and updating of hospital VO policies is necessary to ensure that they are internally consistent and optimize patient safety. The implementation of computerized medical records and ordering systems can reduce but not eliminate the need for VOs.

A framework for analyzing data from the electronic health record: verbal orders as a case in point.

BACKGROUND: Investment in health care information technology is resulting in a large amount of data electronically captured during patient care. These databases offer the opportunity to implement ongoing monitoring and analysis of processes with important patient care quality and safety implications to an extent that was previously not feasible with paper-based records. Thus, there is a growing need for analytic frameworks to efficiently support both ongoing monitoring and as-needed periodic detailed analyses to explore particular issues. One patient care process-the use of verbal orders-is used as a case in point to present a framework for analyzing data pulled from electronic health record (EHR) and computerized provider order entry systems. METHODS: Longitudinal and cross-sectional data on verbal orders (VOs) were analyzed at University of Missouri Health Care, Columbia, an academic medical center composed of five specialty hospitals and other care settings. RESULTS: A variety of verbal order analyses were conducted, addressing longitudinal-order patterns, provider-specific patterns, order content and urgency, associated computer-generated alerts, and compliance with institutional policy of a provider cosignature within 48 hours. For example, at the individual prescriber level, in July 2011 there were 14 physicians with 50 or more VOs, with the top 2 having 253 and 233 individual VOs, respectively. CONCLUSIONS: Taking advantage of the automatic data-capture features associated with health information technologies now being incorporated into clinical work flows offers new opportunities to expand the ability to analyze care processes. Health care organizations can now study and statistically model, understand, and improve complex patient care processes.