A new look at observation units: evidence-based approach

Abstract

Background: Observation patient classification and billing are an important focus area for recovery audit contractors (RACs) and creation of a centralized observation unit (COU) could be a good strategy for Academic Medical Centers (AMCs) to improve care and fiscal management of a growing observation/patient volume. Objective: To define and investigate the feasibility of a dual purpose COU at an AMC. Methods: Retrospective data analysis and domain expertise were utilized to define potential observation patients. A pre/post study design was used to test the effects of three strategies. These strategies included: 1) all observation patients; 2) all observation patients except Emergency Department (ED) sourced patients; and 3) only post-procedural and post-surgical observation patients measured on unit efficiency metrics (i.e., bed placement wait time and occupancy rate), through simulation modeling. In addition, domain experts determined operational feasibility of each strategy based on multiple criteria. Results:Results of the simulation model demonstrated two feasible strategies that included COUs focusing on non-ED sourced observation patients on inpatient units (wait time ≤ 1 minute; occupancy rate = 8.26 ± 3.8 beds) and post-surgical and postprocedural observation patients only (wait time ≤ 1 minute; occupancy rate = 5.15 ± 3.04 beds). Conclusions: A multi-purpose COU with clear definitions and patient care protocols for observation patients allows efficient medical care to be delivered, facilitates correct documentation and billing to third-party payers, and frees capacity on inpatient care units. Additional hospital revenue and reimbursement with modest investment given clinical feasibility bolster financial viability of a COU.

Accounting for capacity: A real‐time optimization approach to managing observation unit utilization

“…Hospitals measure OU performance along multiple dimensions, including LOS, rate of conversion to inpatient status, patient volume, patient satisfaction, and costs (Shah et al, 2015;Peacock et al, 2014). Best operational practices follow evidence-based protocols and staffing models for decreasing variability in care, providing higher quality at a lower cost, and decreasing the LOS (Baugh et al, 2019;Conley, Bohan, & Baugh, 2017;Leykum, Huerta, & Mortensen, 2010;Mace et al, 2003).…”