Risk Adjustment Definitions and Methodology

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1 Illness Burden Illness burden measures the relative health of the population based upon the number and types of health care services used by that group of people. For instance, if the number is in reference to a county, it represents the relative health of the population that resides in that county compared to the population of the state as a whole. If the number is next to a hospital on a procedure-specific report, for example, knee replacements, it represents the relative health and use of services of patients that had a knee replacement at that facility. Several things are taken into consideration when calculating illness burden including how often health care services are used, the types of health care services used, and specific patient diagnoses (chronic disease, cancer, acute illness, etc.). The average illness burden score across the entire population in the database is represented as 1.0. A number that is below 1.0 indicates that the population is relatively healthier and/or utilizes less health services than the state average. For example, a county with an illness burden score of 0.87 means that the population of that county is healthier and/or doesn t use as many services compared to the rest of the population of Colorado represented in the database. Likewise, a county score of 2.3 indicates that the population likely has a greater proportion of health problems and/or the individuals utilize more health care services than the state as a whole. The numbers are meant to be used in a relative manner for comparing one population to another. This information should be taken into consideration when comparing cost and utilization metrics of different regions or facilities. For example, it might make sense that an area with a higher illness burden score has higher costs and utilizes more services than healthier areas, although this is not always the case. Risk Adjustment Several risk adjustment methods are licensed from 3M Health Information Systems and are used to risk adjust data in the Colorado APCD. Each of these is described and defined in more detail later in this document. Inpatient stays are risk adjusted utilizing 3M TM All Patient Refined-Diagnosis Related Groups (APR DRG). Ambulatory (Outpatient) services are risk adjusted utilizing 3M TM Enhanced Ambulatory Patient Groups (EAPG). Population health indicators are adjusted utilizing 3M TM Clinical Risk Groups (CRG). The methods used vary depending upon what is being measured. When risk adjusting use of health care services, then either APR- DRGs or EAPGs are used. When risk adjusting populations for comparisons to another population or group, then CRGs are used. There are a number of factors used for consistent comparisons, including the relative severity of illness(es), risk of mortality, age, etc. Developing Illness Burden Scores and Weights Illness burden is developed using the Clinical Risk Group (CRG) classification system. For each Age/Gender/CRG combination, claims data is used to provide cost and utilization information and a weighting system is developed to identify the relative health care resource usage for a specific type of patient. This weight information is then aggregated to identify the illness burden for any given population. The associated illness burden of a population can help identify expected costs for a population. By understanding a typical or expected cost for a certain patient population, actual patient service usage and costs can provide more meaningful comparisons. Illness Burden Methodology The following steps are used to calculate an illness burden score. (1) A Clinical Risk Group (CRG) tag is assigned to each deidentified person in the APCD database for each calendar year, assigning a health status. (2) A proxy pricing model is applied to the claims data to account for different benefit structures and payment variation. (3) Using the proxy priced claims, costs associated with each deidentified person are aggregated and an average is calculated for each CRG. (4) Ratios of the CRG costs to the average costs are computed for the entire population to generate a weight. (5) Age and gender factors are applied to adjust the weights across the CRGs. (6) At this point, each de-identified individual has an assigned weight based upon their CRG designation, age and gender. For any given population, the illness burden can then be computed by: a. Identifying the population to consider (people within a county, people that received a certain procedure at a specific facility, etc.), b. Averaging their calculated weights together, and c. Aggregating individual weights to high level clinical categories such as Healthy or Complex. Compared to Expected (C2E) Compared to Expected (C2E) numbers allow comparisons of costs and/or use of services with what is typical or expected for a particular population. On the cost side, the expected price is determined by averaging typical costs for patients

2 in the same Clinical Risk Group (CRG), and age and gender categories. Once this is established, each de-identified person is assigned an expected cost. Expected costs for a group are calculated by adding together the expected costs for each deidentified person assigned to that group. Actual costs are determined by adding together the payments received for services associated with those same people. If the actual dollars exceed the expected dollars, the resulting C2E value is a positive percentage. If the C2E value is greater than 25%, it is displayed as a red number. Conversely, if actual expenditures fall below expected results, the number is a negative percentage and will be displayed as a green number if the C2E is below -25%. Similar calculations are applied to report service usage instead of costs. The health of the population and utilization of health care services helps to drive both the illness burden and the C2E values. Knowing the relative health of a population helps to compare usage of services and cost. Why are Illness Burden and Compared to Expected values included in the reports? Illness Burden and Compared to Expected (C2E) values are ways to risk adjust health care claims data to account for differences in the health status for a given population. Risk adjustment provides context to the data so it can be appropriately analyzed and compared. For example, a Primary Care Provider might have very high costs associated with caring for patients compared to a different provider. Without understanding the complexity and health status of the patients that each provider serves, it is difficult to assess whether a difference in cost is warranted. If one provider provides care to a high number of patients with chronic disease (diabetes, asthma, etc.), and the other provider has very few chronic disease patients, the costs to care for those patients could be quite different. Risk adjustment accounts for differences in patient populations and allows for more meaningful comparisons of the data. Risk adjustment is useful for both utilization and cost information. Below is an example of risk adjustment for costs of services, but a similar approach can be used for service utilization. Example: When viewing a report for actual dollars paid for health care services, both the Illness Burden of the population and the Compared to Expected (C2E) costs are displayed. Both of these comparisons should be reviewed, because combined, they can provide some interesting insight into the way health care services are being delivered. It is possible for a population to have a high illness burden score (1.32), indicating less healthy people, but still have lower costs than expected, say -10%. This situation indicates that while the population has been scored as less healthy and/or uses more health services than the state as a whole, costs to serve this population are actually less than costs associated with populations with similar health status across the state. Disease Conditions Disease conditions are determined by running the claims data through 3M s Clinical Risk Group (CRG) process. A year s worth of clinical claims for each de-identified individual is run through the grouping process resulting in a clinical assignment for that person for that year. In the process of this grouping, Episodic Diagnostic Categories (EDCs) are created for an individual. These EDCs identify any conditions or diseases based on the claims data. Classifications are based solely upon claims filed, so it is possible for a person to appear healthy from a claims perspective (no claims for health care services were submitted for that year) when a disease or condition exists. 3M All Patient Refined Diagnosis Related Groups (APR DRG) APR-DRG is a classification system that categorizes inpatient (hospital) records in groups according to their reason for admission, the severity of illness (health status) and their risk of mortality (how likely they are to die). It comprehensively evaluates all patients regardless of age or the conditions found. Inpatient records are grouped into one of 25 Major Diagnostic Categories (MDC), and are then placed into one of 314 mutually exclusive groups which are similar clinically and have similar patterns of resource intensity defined as the amount of resources that are needed to care for a patient during the hospital stay. A threephase/18 step process is then used to determine a distinct subclass for the severity of illness and a distinct subclass for the risk of mortality. Each of the subcategories has 4 possible values: 1-Minor, 2- Moderate, 3- Major, 4-Extreme. See Diagram 1 for illustration. Diagram 1- APR DRG Methodology The three-phase/18 step process simultaneously evaluates co-morbid conditions (concurrently existing but unrelated diseases), age, procedures and principle conditions/diagnosis and their interaction

3 with each other to determine severity of illness and risk of mortality subclasses. See Table 1 for an overview of the phases. Phase Steps Explanation of Step 1 6 All patient attributes are considered against each condition to give a condition level subclass. 2 3 All the conditions are pooled together and the claim is given an overall preliminary severity and risk subclass. Generally multiple high base severity/risk conditions will result in a higher level subclass. 3 9 The record is evaluated for interactions among patient conditions and procedures along with their patient attributes to make a final determination of the severity and risk subclass. Multiple serious conditions involving multiple organ systems will result in a higher subclass. Table 1 3 Phases of APR DRG SOI and ROM subclass determination. Severity of illness is officially defined as the extent of physiologic decomposition or organ system loss of function, and although severity of illness and risk of mortality are highly correlated for many conditions, they often differ because they relate to distinct patient attributes. For example, a patient with acute gallstone attack may be considered a major (level 3) severity of illness but only a minor risk of mortality. The severity of illness is major since there is significant organ system dysfunction associated with acute gallstone attack. However, it is unlikely that the acute event alone will result in death, so the risk of mortality for this patient is minor (level 1). The underlying clinical principles of APR DRGs are that both severity of illness and risk of mortality are highly dependent on the patient s underlying clinical characteristics, and that patients with high severity of illness or risk of mortality are usually characterized by multiple diseases and/or illnesses. The assessment of the severity of illness or risk of mortality, based on the patient s complicated or comorbid conditions, is specific to the patient s base APR DRG. In other words, the determination of the severity of illness and risk of mortality is disease-specific. For example, certain types of infections are considered a more significant problem and require more utilization for a patient with a comorbid condition than in a patient with a fractured arm. In APR DRGs, high severity of illness and risk of mortality are primarily based on the presence of multiple diseases. Patients with multiple co-morbid conditions involving multiple organ systems are typically more complex patients and higher health care service utilization needs. 3M Enhanced Ambulatory Patient Groups (EAPG) Enhanced Ambulatory Patient Groups (EAPG) are patient categories designed to explain the amounts and types of resources used in ambulatory (non-hospital admission) visits. EAPGs simplify ambulatory visits for analysis and reporting. This is achieved by identifying key diagnoses and procedures, both diagnostic and therapeutic, performed during an ambulatory visit. Once identified, these diagnoses and procedures are used to classify the ambulatory visits into the EAPG categories to provide clinical and financial comparisons. Patients in an EAPG typically have similar clinical characteristics and similar health care service use and cost. Some variation in resource use can occur among patients within each EAPG, but the level of variation is known and predictable. For example, while the exact resource use of a particular patient cannot be predicted based upon an EAPG, the pattern of resource use of a group of patients in an EAPG can be predicted. See Diagram 2 for an overview of the EAPG methodology. Diagram 2 - Overview of EAPG method. Once the EAPGs are established, each one is assigned one of four levels of complexity. The complexity of an EAPG is defined by the following criteria: clinical similarity within an EAPG, the type (e.g. incision vs excision) of procedures in a particular EAPG, the amount of resources needed for the procedures in an EAPG, and the likelihood that other ancillary services (e.g. diagnostic vs. therapeutic procedures involving different types of surgical and other types of surgical pathology) will be performed for the procedure in that EAPG. See table 2 for an explanation of the four levels.

4 Level Level I Level II Level III Level IV Description Short treatment time in the operating room. Few laboratory tests or radiology procedures ordered. Few expensive disposable devices used, if any. Laboratory tests and radiology procedures typically ordered as part of procedure. Disposable devices may consume significant resources. Increased length of time in the operating room. Laboratory tests and radiology procedures ordered as part of a procedure. Disposable devices consume significant resources. Longer stay in the operating room than levels I and II. Procedure of major complexity. Treatment and resources used are extensive. Thus, Level IV EAPGs are frequently performed in an inpatient setting, not in an outpatient setting. Table 2 - Levels of EAPG Complexity EAPGs were developed to encompass the full range of ambulatory settings including same day surgery units, hospital emergency rooms, and outpatient clinics. EAPGs were developed to represent ambulatory patients across entire patient population, regardless of age, gender or health condition. 3M Clinical Risk Groups (CRG) Clinical Risk Groups are clinical categories of patients assigned to a single, mutually exclusive, risk category and severity of illness subclass. CRGs are determined by evaluating all claims over a calendar year and determining severity by looking for chronic conditions found over time. CRGs are categorized by patient, meaning that all conditions and treatments across claims are considered to assign the patient - not the conditions or diseases - to a mutually exclusive group. CRGs are used to determine the illness burden of a population so that, any group of patients (for a given geography, physician group, hospital, etc.) can be more meaningfully compared to another group of patients. CRGs can also be used to predict future health care utilization and cost and to explain past health care utilization and cost over an extended period of time so that a total cost of care can be examined. The CRG system follows a four phase process for assigning CRGs, it s severity of illness subclass and its aggregate grouping assignment. See Table 3 for the CRG methodology phases. Phase Phase 1 Phase 2 Phase 3 Phase 4 Description Pre-processing - identify and categorize diagnoses and procedures Identify chronic illnesses and their severity Assign the CRG Post-processing Aggregating the CRGs Table 3 Overview of the CRG methodology phases. In Phase 1 the system executes rules that validate the data. In Phase 2, each condition is assigned to 1 of 37 Major Diagnostic Categories (MDC), the conditions are then categorized into one of 557 Episode Diagnostic Categories (EDC). Each EDC is grouped into one of six types based on the degree of chronic illness associated with the EDC (see Table 4). The procedures are then grouped into 1 of 639 Episode Procedure Categories (EPC). Type Description # EDCs Example 1 Dominant 2 Moderate 3 Minor 4 Manifestation 5 Significant Acute 61 Diabetes 64 Asthma 41 Hyperlipidemia 104 Diabetic Neuropathy 156 Pneumonia 6 Acute 131 Upper Respiratory Infection Table 4 - EDC Types Each MDC with a chronic EDC is assigned to one mutually exclusive PCD (Primary Disease). Then the severity of illness is assigned to each EDC. Severity of illness uses the presence of other diagnoses (both chronic and acute EDCs, and some EPC) and considers them against the following factors: recency, persistence and recurrence, demographic factors, and hospitalization. In Phase 3 the PCDs are evaluated along with the contributing EDC s to assign the patient to one of 272 base CRG groups. Within that CRG group, the individual is assigned to one of nine health statuses. From there, health statuses are further classified into one of as many as six severity of illness subclasses based on the advancement of the overall chronic burden profile.

5 See Table 5 to see an overview CRG classifications. Health Status No. Base CRG Severity Levels Total No. of CRGs Example Base CRG Catastrophic Conditions HX Major Organ Trans Dominant Disease in Three or More Organ Systems Significant Disease in Multiple Organ Systems Single Dominant or Moderate Disease Minor Disease in Multiple Organ Systems Metastatic Colon Malignancy Diabetes Mellitus & Congestive Heart Failure & Obstructive Pulmonary Disease 61 2, 4 or Diabetes Mellitus & Congestive Heart Failure or Diabetes Mellitus Single Minor Disease Enlarged Prostate (BPH) Significant Acute Disease Migraine Single Minor Disease 6 None 6 Chest Pains Healthy 2 None 2 Healthy Table 5 Overview of CRG Phase 3. In Phase 4, the CRG groups are tiered into 3 levels of aggregation groups (see Table 6). Severity of illness levels are maintained and adjusted where appropriate, within each tier. The aggregation groups are often used in creating norms/benchmarks that are used in the risk adjustment of quality and efficiency indicators. Tier CRG ACRG1 ACRG2 ACRG3 No. of Groups Patient Segments Table 6 CRG Aggregation levels. Patient Segments are used to communicate the health status of a population. Where the CRG system outlined above produces precise classifications based upon granular disease differentiation, it is difficult to report and communicate the information across the more than 1,000 categories of health status. Patient segments provide a higher level view while retaining common health conditions for reporting purposes. The descriptions of each category can be found below. Non-User - An individual with enrollment in some insurance system in the APCD that has not filed any medical claims during the calendar year. Healthy No health issues, or minor illnesses with low use of services including primarily prevention, well care, and minor acute care services. Stable - Low illness burden with modest use of services including well care and occasional acute care service. At-risk - Modest illness burden with clear potential for deterioration, increasing inconsistent use of well care, specialty and acute care services. Simple - Medium illness burden with consistent use of services to treat a chronic condition. Complex - Medium to high illness burden with, consistent use of services to treat severe or multiple chronic conditions. Critical - High illness burden with consistent use of services for life threatening illness.

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