Original Research
Steroid-Induced Sleep Disturbance and Delirium: A Focused Review for Critically Ill Patients
Steroid use is a modifiable risk factor in intensive care unit patients; however, reported mechanisms are often lacking.
Background
VA Directive 1082 on Patient Care Data requires the capture of all outpatient and inpatient billable encounter data.10 Accurate capture of workload informs budget allocation models and is necessary for health care provider (HCP) productivity metrics. These data points help identify staff shortages relative to the generated workload. The Veterans Equitable Resource Allocation (VERA) model is used to allocate general purpose funds to the Veterans Integrated Service Networks (VISNs) regional network of VHA facilities. The underlying data components of the VERA model rely on comprehensive data systems that track and analyze the many management information systems used in VHA. Historically, at least 90% of the funds allocated by the VERA model have been attributed directly to patient care. All workload that is appropriately documented is accounted for in the VERA patient classification process, which is the official data source for funding patient care in VHA.
VA medical facilities use Stop Codes (formerly known as Decision Support System Identifiers) to identify workload for all outpatient encounters and inpatient professional services. Each code is composed of a 6-character descriptor that includes a primary Stop Code and a credit (secondary) Stop Code. Primary Stop Codes—the first 3 numbers in the sequence—designate the main clinical group responsible for patient care, such as sleep medicine or neurology. Secondary Stop Codes—the last 3 numbers in the sequence—further define the primary workgroup, such as the type of services provided (eg, telehealth) or the type of HCP (eg, nurse practitioner). These codes help ensure that workload and generated revenue are allocated or credited to the proper specialty care service.11 An example of how changes or inaccuracies in Stop Code reporting can affect VHA clinical workload assessment and resource allocation is provided by the VHA sleep medicine program.
The prevalence of sleep disorders—particularly apnea and insomnia—among US military service members and veterans has increased dramatically over the past 2 decades and continues to rise.12-14 Consequently, demand for sleep care services at VHA facilities also has increased substantially (Figure 1). Unfortunately, this demand has outpaced the VHA’s staffing models, sometimes resulting in long wait times for appointments.15 In fact, sleep medicine remains one of the most backlogged services in the VHA, despite significant improvements in program efficiency achieved by incorporating telehealth modalities.16 Untreated sleep disorders are associated with increased risk of depression, anxiety, impaired neurocognitive functions, cardiovascular disease, motor vehicle accidents, and premature death.17-23
A major contributor to understaffing of VHA sleep medicine programs is the CBD system’s historical inability to accurately track sleep resources and demand for sleep care services. For many years, Stop Codes attributed sleep workload credit primarily to pulmonary medicine, neurology, and internal medicine workgroups. Within these workgroups, few individuals contributed to sleep care, but the entire workgroup received credit for these services, masking the workload of sleep care providers. Additional barriers to accurate sleep medicine workload capture within the VHA included (1) inability to centrally identify personnel, including physicians, as providers of sleep care; (2) limited and variable understanding among VA sleep physicians of the importance of proper encounter form completion (the mechanism by which the cost of a service is calculated); and (3) a lack of awareness that encounter closure is directly linked to productivity measures such as relative value units (RVUs) that support sleep medicine programs and the salaries of those who provide care.