In Part I of this series, we explored why the traditional utilization management (UM) model is no longer sufficient to meet today’s regulatory and operational healthcare demands. The proposed removal of the Medicare Inpatient-Only (IPO) List, continued expansion of Medicare Advantage (MA), and increasing payer scrutiny have shifted the UM process from a retrospective review function to one that must proactively support level-of-care decisions and denials prevention.
Typically, hospital UM programs assign utilization review (UR) specialists by nursing unit or service line, creating workflows in which clinicians spend much of their day moving from one patient to the next based solely on location, operating off a patient list. While this model is familiar and operationally comfortable, it often obscures the actual work requiring attention at any given time. It also assumes that every hospitalized patient requires the same level of UR intervention each day, which is rarely the case.
An adaptive UR model organizes staff according to the work being performed, rather than the physical location of the patient. Specialized teams focus on distinct operational responsibilities, such as pre-admission surgical review, emergency department and direct admission reviews, observation management, concurrent inpatient reviews, and post-discharge prebill denial and authorization reconciliation. Each function requires different clinical expertise, review cadence, and workflow priorities, allowing staff to develop greater proficiency while creating standardized processes across the organization.
One area where this redesign becomes particularly valuable is the surgical population. As reliance on the IPO List diminishes, UR will need to start shifting towards evaluating patients with significant medical complexity before surgery occurs, not just immediately after. A dedicated preoperative work queue, reviewed approximately two weeks before scheduled procedures, allows UR specialists to identify patients who may require inpatient hospitalization based on clinical factors, rather than procedure alone. Early collaboration with surgeons, physician advisors, and scheduling staff supports more accurate patient status decisions, timely MA authorizations, and stronger clinical documentation – before the patient ever enters the operating room.
Observation management represents another opportunity for specialization. Observation patients often require a much higher level of monitoring than traditional inpatients, because progression-of-care needs and conversion decisions frequently occur within hours. Assigning dedicated staff to observation services creates a simulation of an observation unit without having to necessarily collocate patients in the hospital. This works well, especially for hospitals where it is physically impossible to create a dedicated observation unit. Historically, observation workflows have focused heavily on identifying patients approaching the second midnight to determine whether inpatient conversion is appropriate. However, this represents only one component of observation management. Dedicated observation specialists can proactively address progression-of-care barriers, reduce unnecessary delays, help facilitate timely discharges, and improve patient throughput. This team is also well-positioned to oversee extended recovery patients and other outpatient-in-a-bed (OPIB) populations, creating consistency across bedded outpatient services.
Emergency department UR similarly benefits from a specialized approach. Evaluating patients at the point of entry allows medical necessity concerns, physician advisor consultations, and level-of-care determinations to occur before avoidable denials develop. Traditional models often delay these reviews, because staff believe that insufficient clinical information exists early in the encounter. However, advances in clinical decision support, artificial intelligence (AI), and real-time electronic documentation have made earlier intervention both practical and beneficial. Today’s UR specialist is no longer simply applying medical necessity criteria; they are serving as a real-time clinical resource, educating providers, collaborating with emergency physicians, and supporting accurate admission decisions before patient status becomes difficult to correct.
Building an adaptive model requires organizations to reconsider who performs the work. UR specialists should spend the majority of their time applying their clinical expertise, collaborating with physicians, physician advisors, and addressing complex medical necessity issues. Many administrative activities, such as authorization tracking, payer portal updates, fax management, scheduling peer-to-peer discussions, and post-discharge authorization reconciliation can often be delegated to trained UR technicians or other non-licensed professionals. This top-of-license approach allows the seasoned clinicians to focus on activities that require professional expertise while improving overall operational efficiency.
Technology serves as the foundation that connects these specialized workflows. Electronic medical records (EMRs) and UR technology are quickly replacing manual tracking spreadsheets with automated work queues and methods for prioritization that identify patients requiring review, notify physician advisors of escalation requests, monitor pending authorizations, and alert staff when status changes or payer requirements require action. Rather than relying on emails or secure chats, UR teams can build transparent electronic workflows for which each step of the review process is visible to case management, revenue cycle, clinical documentation integrity (CDI), and physician advisors. This level of visibility not only improves communication, but also creates valuable operational data that organizations can use to identify trends in denials, authorization delays, outpatient and observation utilization, physician advisor interventions, and throughput opportunities.
Healthcare delivery continues to evolve rapidly, and UM programs must be designed to evolve alongside it. Staffing models should reflect review demand, rather than traditional Monday-through-Friday schedules; incorporate remote and hybrid work environments, where appropriate; and adjust productivity expectations based on the complexity of each review function, rather than applying a single productivity standard across all roles. Success should be measured by meaningful outcomes such as reduced denials, improved authorization performance, shorter observation and bedded outpatient stays, cleaner claims, and stronger physician engagement.
