ABOUT TOTAL RESOURCE UTILIZATION (TRU™) BENCHMARKS™

TRU Benchmarks represent a new class of data about healthcare economics. TRU Benchmarks data consist of disease-specific, national and regional benchmarks, across various demographic strata, for 3 observable outcomes-costs, units of use, and services utilized-that embrace the entire continuum of patient care: inpatient, outpatient, emergency room/urgent care, and pharmacy.

These data—the first and only available data of their kind—reflect Total Resource Utilization (TRU™): the total of all healthcare resources consumed in treating a particular medical condition, and the costs of those resources.

1. Building TRU Benchmarks
2. Source Data and Source Databases
3. Episode-Creating Software
4. TRU Disease Models™
     a. Introduction
     b. Functions of a TRU Disease Model
     c. Graphic Presentation

1. Building TRU Benchmarks                                                                                                                      TOP

TRU Benchmarks are generated through a three-phase, proprietary process:

• Raw claims data (Source Data) are extracted from one or more independent third-party databases^* (Source Databases).Those databases contain claims information from a multitude of health plans, and are much larger in scope and breadth than any previously available to the healthcare industry.
• Raw claims data are transformed into disease-specific, episode-based norms,
  though episode-creating software.^†
• Episoded norms are further "grouped" and "cut,"—and enhanced and transformed into actual benchmark—by applying proprietary, disease-specific data models that are based on specialized knowledge of and experience in healthcare, managed care, and pharmaceuticals: TRU Disease Models.^{(TM)(Patent Pending)}

• Utilize technology that integrates data across the continuum of patient care, and links specific treatment costs for each patient to that patient's specific diagnosis.
• Are based on MCO data extracted from the country's largest independent, and most fully integrated, claims-based dataset—MCO data that are matched to the US census by age, gender and geography.
• Incorporate the "episode of care" as the standard unit of measure. This unit of measure is now recognized as the "gold standard," and is also recognized as integral to measuring and managing healthcare costs and utilization.⁺

• Understand the total cost of care for a disease.
• Observe how disease treatment options impact resource utilization.
• Compare their internal resource utilization data to external national and regional benchmarks, and thereby gauge performance.

Healthcare professionals can therefore use these "real world" benchmarks as a resource to help them qualitatively evaluate, and to adjust, institution-wide disease treatment and disease management strategies.

2. Source Data and Source Databases                                                                           TOP

The Source Data consist of raw patient-level diagnosis, treatment, and insurance claims (medical and pharmacy) data obtained from the Source Databases. The Source Database that was utilized for the information appearing on this website:

• Contains de-identified^‡ longitudinal, patient-level medical and pharmacy claims data gathered from more than 66 healthcare plans across the United States, and comprising data on more than 50 million unique participants. These data embrace the continuum of patient care, including:
  • Inpatient services.
  • Outpatient services.
  • Emergency room/urgent care facility services.
  • Pharmacy services.
• Permits, because of the scope and breadth of the Source Data, comparisons
  among patients with similar demography—age, gender, markers of disease
  severity, and presence of other co-existing diseases.
  

3. Episode-Creating Software                                                                                                                    TOP

The Source Data contained in the Source Database are transformed into norms by applying episode-creating software; this is the second step in building TRU Benchmarks. Except where otherwise stated, the Episode Treatment Group™ (ETG™) methodology has been applied to the data presented in this website.

The ETG illness-classification and episode-building software was developed in response to the need in the healthcare industry for a consistent, reliable and widely accepted standard for measuring and evaluating how healthcare resources are utilized and financed. ETGs are designed to establish this standard by organizing medical and pharmacy claims data into discrete, disease-specific episodes of care.

ETGs are utilized by more than 400 managed health plans nationwide (representing over 100 million individuals). ETGs measure resource consumption by (a) tying raw claims data to specific diagnoses, and (b) linking them to those claims. These metrics can then be attributed to a particular treatment option and compared to other treatment options. The ETG software also takes into account the various components and costs of treating a disease, the nature of the disease (for example, chronic or acute), and whether complicating diseases or conditions are present. In sum, ETG software translates raw claims data into discrete, disease-specific, episode-based norms that embrace the "entire process of care that is rendered for a specific condition."⁺

By tracking and organizing all relevant information relating to a particular treatment episode, ETGs permit standardized, consistent and reliable quantification of healthcare services that can serve as:

• A general unit of measure for healthcare analysis.
• An analytical unit to measure and compare the utilization and financial performance of healthcare providers.
• A clinically useful unit to measure healthcare demand.
• A basis to establish disease-management strategies.
  

4. TRU Disease Models™                                                                                                                             TOP

a. Introduction

The third element in generating TRU Benchmarks is a tailored, disease-specific data model: a TRU Disease Model.

Each Disease Model consists of detailed, written specifications of additional metrics and substrata that (1) are applied to the Source Data (whether or not the data are first processed through episode-creating software) and (2) organize, stratify, and segment the Source Data into unique, disease-specific economic benchmarks of healthcare costs, units of use, and services utilized that report (for example):

• Detailed patient demographics (eg, age, gender, geographic region).
• Markers of disease severity, including the presence and number of complications and comorbidities.
• Patterns of pharmacotherapy (eg, the class of prescription drugs used).
• Practice patterns of those physician specialties that actually treat the specific disease being analyzed.
• Episode costs and resource utilization across all healthcare service categories (inpatient care, outpatient care, emergency room/urgent care, pharmacy).

The Disease Models take into account the different levels of severity associated with treatment; this feature produces clinically homogeneous groups that best reflect how each treatment option impacts resource utilization.

The Disease Models are created through a proprietary methodology based on, and incorporating, specialized knowledge of and experience in the healthcare, managed care, and pharmaceutical arenas. Because of this unique and specialized knowledge, the economic benchmarks that are produced reflect how clinicians—in a "real world," managed care environment—actually treat a disease based on an evaluation of patient age, gender, sensitivity, and currently available treatment options.

These "real world" benchmarks can be used by healthcare professionals as a resource to assist them in their ongoing efforts to qualitatively evaluate, and to adjust, institution-wide disease treatment and disease management strategies.

b. Functions of a TRU Disease Model

A TRU Disease Model:

• Defines the method for patient selection from the Source Database.
• Defines the time period of observation for data analysis.
• Defines the disease-specific metrics of costs, units of use, and services utilized.
• Describes the manner in which a third party's episode-grouping or -creating software program is applied (if at all) to Source Data in order to collect and express the Source Data as discrete
  episodes of patient interaction with the healthcare system.
• Provides the programmer/analyst with specifications for extracting, and for further organizing and stratifying, Source Data from the Source Database according to various metrics.

c. Graphic Presentation

The figure below graphically depicts a Disease Model. This flowchart illustrates when different variables are applied to ETG episodes in order to further "group" and "cut" the episode data. The end result of this process: TRU Benchmarks, delivered through an array of patient segments that comprehensively depict a disease-specific patient population.

Typical Disease-Specific Disease Model

* The source Data for this publication was extracted from The PHARMetrics, Inc. Patient-centric Database (formerly known as Integrated Outcomes Database).

^† Episode Treatment Groups™ (ETGs™) software was utilized for the data contained in this website.

⁺ Rosen A, Mayer-Oakes A. Episodes of care: theoretical frameworks versus current operational realities. Jt Comm J Qual Improvement. 1999;25(3):111-128.

^‡ According to the PHARMetrics, Inc. website:

PHARMetrics has addressed patient confidentiality and management of patient-level data concerns with an approach to data management that exceeds all proposed standards, including HIPAA, and ensures complete patient, provider, and health plan anonymity. PHARMetrics is committed to the confidentiality of all patient and plan data it receives.