Does Your Utilization Management Measure Up?

//Does Your Utilization Management Measure Up?

Does Your Utilization Management Measure Up?

DOES YOUR UTILIZATION MANAGEMENT MEASURE UP?
Patient Specific Normative Data May Provide the Answer

Almost one-third of health care dollars go to inpatient hospital care. That’s almost three times the amount spent on prescription drugs. Utilization Management (UM) programs geared toward
inpatient care have been around for more than a 20 years and have been accepted as an effective prospective and concurrent management tool.

The initial UM programs, as well as many today, focus on avoiding unnecessary admissions and inappropriate stays. While these components are still valuable, an effective “next generation”
UM program should include; early automated identification of chronic illness and patients who will require a high intensity of services, management across the entire continuum of care, and as
a source for the collection and analysis of population specific normative data.

It’s no longer sufficient to measure program effectiveness by looking at non-certification rates, denied days, or requested versus certified days. The key to meaningful program evaluation is
the collection of patient specific normative data, updated on each review episode, or any time a patient’s diagnosis or procedures change. The normative data collected should reflect the
exact demographics of your patient population rather than a national average based solely on diagnostic groupings. Population specific normative benchmarks should include real time
adjustment for the age, diagnoses, procedures and co-morbidity for each of your patients.

While the incorporation of population specific normative data in your UM process provides the obvious advantage of a more intelligent length of stay assignment, the primary advantage is the
case mix adjusted benchmark for evaluating the effectiveness of individual patient review and providing the building block needed for population specific analysis of aggregate data. Once the
data is collected on each patient you can now evaluate utilization parameters such as Hospital Days Used per 1000 Covered Lives, against the normative or expected Hospital Days Used
per 1000 Covered Lives given your exact patient population. The same holds true for analysis of utilization by length of stay, by hospital, by service type or by major diagnostic
categories.

While overall utilization statistics may look fine, the collection of patient specific normative data provides a powerful tool to drill down to diagnostic groups and evaluate actual versus normative
utilization. It’s a simple but powerful tool your Utilization Management program should be using.

2012-09-28T20:17:50+00:00 October 28th, 2010|Recent News|