Due to the complex and ever-changing regulatory landscape of contemporary healthcare, it is essential that hospitals and health systems have an efficient and finely tuned utilization review (UR) process in place.
Ongoing checks of this review process are necessary to ensure compliance with the Medicare Conditions of Participation and contractual obligations with commercial payers.
By effectively examining a hospital’s data, the UR committee can predict compliance risk areas in the event of an audit.
Observation service metrics and inpatient status rates can be calculated in different ways to find the most appropriate measurement value. For starters, the most important areas to evaluate are:
- Consistency and quality of the facility’s review process;
- Cases at risk for audit (especially short-stay cases); and
- Observation or inpatient metrics that fall outside of normal range.
When evaluating an observation rate, it is critical to perform the “correct” calculation. Data for this measurement can be drawn from case management/quality data, hospital census information and/or claims data.
The best metric by which to evaluate Medicare audit preparation is a facility’s Medicare FFS medical observation rate. There is no one set national standard, as the rate can vary from facility to facility based on patient profiles, physician practice patterns and hospital location. However, if a facility’s rate is too low, it could imply an overuse of inpatient status, which creates a greater risk for a government audit (by RACs, MACs, the OIG, the DOJ, etc).
If a facility’s observation rate is too high, it could be representative of an inconsistent or incomplete review process. A high observation rate also could affect quality and reporting data as well as impact patient financial responsibility.
When evaluating observation rates, it can be helpful to do so by diagnosis (medical back, cardiac, endocrine/metabolic, gastrointestinal, gastric ulcer renal, hematology/oncology, infectious disease, neurological, orthopedic, pulmonary, vascular, etc.). As an example, a higher observation rate for medical back cases would be expected when compared to the rate for chest pain. Separating the diagnoses into categories helps identify specific problem areas. If an overall observation rate is normal, high or low, evaluating specific areas can determine where internal audits and additional resources should be directed.
Commercial payers’ metrics should be evaluated separately since benchmarks and norms can vary from payer to payer, depending on contracts. Commercial payers may include private companies, Medicare managed care and Medicaid managed care. This is where it becomes important to understand the specifics of each payer contract. All patients should be treated the same, clinically speaking. However, facilities must follow the specific billing and claims requirements of each contract. For example, one contract may mandate that hospital stays are billed as observation, based on the number of hours spent in the hospital, regardless of medical necessity. Surgical procedures also commonly are directed to be billed one way or another regardless of medical necessity, urgency or specific procedure. Again, this is why understanding the specifics of every contract is of paramount importance.
After reviewing observation rates, it is also useful to check for the consistent application of screening criteria. This evaluation can be measured by case management inter-rater reliability (IRR), with calculations made through a statistical analysis or by clinical review. Clinically, this evaluation entails providing a clinical scenario to a group of case managers (CMs), then having them apply screening criteria and determine whether they achieved the desired result. A statistical method to measure whether IRR occurs involves comparing the number of cases that do not meet the criteria for each reviewer to the overall number of cases reviewed. Ideally, the failure or pass rates will be similar across all of the case management staff when looking at different medical departments (i.e., OB, pediatrics, medicine floor, observation unit, time of day or week, etc.). For example, the percentage of inpatients on the OB ward would be different from the percentage in the ICU.
If IRR rates are inconsistent, then ensure that you are measuring all staff by the same ruler. First, determine if the patient population is different for each case manager. For example, the ICU generally will have a higher number of high-acuity cases than the hospital floor. Another example is if one case manager only specializes in cardiac cases while another reviews cases across all disease states. If, after controlling for variables, the results are still inconsistent across your staff, education and training should be considered. All parties involved in the UR process (the UM committee, CM staff, physician advisors) should regularly attend thorough training sessions focusing on the updates and trends of rules and regulations. Staff members cannot be expected to perform to the best of their abilities if they are not updated routinely on contracts and the regulatory landscape.
Data analysis can prove to be a highly effective tool when evaluating a hospital’s utilization review process. The data and statistics collected can serve as a strong indicator as to where a facility is excelling and where improvements are needed. Most importantly, data analysis is an ongoing process used to enhance compliance and to help determine how to make adjustments as needed.
About the Author
Ralph Wuebker, MD, MBA, currently serves as Vice President of Executive Health Resources’ (EHR) ACE (Audit, Compliance and Education) Team. This group of physicians conducts audits and regular visits to EHR’s client hospitals to provide ongoing education on a variety of topics including Medicare and Medicaid compliance and regulations, medical necessity, Recovery Audit Contractors, utilization review, denials management and length of stay.
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