The Johns Hopkins ACG System - HUG CONFERENCES Notes_V9_final.pdf · Table 11: No Generalist Seen ... The Johns Hopkins ACG System, Version 9.0 Release Notes. Release Notes 7 Column

The Johns Hopkins ACG® System

Release NotesVersion 9.0December 2009

Release Notes i

Release Notes

The Johns Hopkins ACG® System ...................................................................... i

Release Notes .......................................................................................................... i

Version 9.0 Enhancements Overview .............................................................. 1

Customer Input Requirements ........................................................................ 2 Exceptions ................................................................................................... 2 Table 1: Procedure and Provider Information ............................................... 3 Table 2: Complete Medical Services (previously Diagnosis) File Layout . . . 5 Table 3: Patient Input File Layout ................................................................. 8 Table 4: Pharmacy Data File Layout ........................................................... 12

New Warnings ................................................................................................. 13 Table 5: Warnings List ................................................................................ 13

New Processing Options ................................................................................. 14 Figure 1: Stringent Diagnostic Certainty and Calculate Utilization Markers ...................................................................................................................... 14 Stringent Diagnostic Certainty .................................................................... 15 Calculate Utilization Markers ...................................................................... 16 New Summary Statistics .............................................................................. 16 Data Constraints ........................................................................................... 17 Table 6: Data Constraints ............................................................................ 17 License Constraints ...................................................................................... 18 Table 7: License Constraints ....................................................................... 18

New Markers ................................................................................................... 19 General Considerations ................................................................................ 19 Utilization Markers ...................................................................................... 19

Dialysis Service.......................................................................................19Nursing Service.......................................................................................19Major Procedure......................................................................................19Emergency Visit Count...........................................................................19Inpatient Hospitalization Count...............................................................20Outpatient Visit Count.............................................................................20

Coordination Markers .................................................................................. 21 Majority Source of Care .........................................................................21Table 8: Majority Source of Care ..........................................................21

Release Notes The Johns Hopkins ACG System, Version 9.0

ii Release Notes

Unique Provider Count ...........................................................................22Table 9: Unique Provider Count ............................................................22Specialty Count ......................................................................................22Table 10: Specialty Count .....................................................................22No Generalist Seen .................................................................................23Table 11: No Generalist Seen ................................................................23

Pharmacy Adherence Markers ..................................................................... 24 Table 12: Medication Adherence Markers.............................................24

New Condition Markers ............................................................................... 25 Untreated Rx............................................................................................25Prescription Gaps.....................................................................................26Figure 2: Gap in Medication Possession................................................27Figure 3: Gap in Medication Possession Following Oversupply...........27Figure 4: Gap in Medication Possession Following Hospitalization.....28Medication Possession Ratio (MPR).......................................................29Table 13: MPR Example 1.....................................................................29Table 14: MPR Example 2.....................................................................29Continuous, Single-interval Measure of Medication Availability (CSA).................................................................................................................30Table 15: CSA Example 1......................................................................30Table 16: CSA Example 2......................................................................30

Generic Drug Count Variable ...................................................................... 31

Changes to Existing Markers ......................................................................... 32 Modifications to Rx-MGs ............................................................................ 32 Modifications to EDCs ................................................................................. 32

New Models ...................................................................................................... 34 Likelihood of Hospitalization ....................................................................... 34

Probability IP Hospitalization Score.......................................................34Probability IP Hospitalization Six Months Score....................................34Probability ICU Hospitalization Score....................................................34Probability Injury Hospitalization Score.................................................34Probability Extended Hospitalization Score............................................35

High Pharmacy Utilization Model .............................................................. 35 Probability of Unexpected Pharmacy Cost..............................................35High Risk for Unexpected Pharmacy Cost..............................................35

New Analyses ................................................................................................... 36 Hospitalization Risk Distribution ................................................................. 36

The Johns Hopkins ACG System, Version 9.0 Release Notes

Release Notes iii

Figure 5: Hospitalization Risk Distribution ................................................ 36 Hospital Predictions for Select Major Conditions Analysis ......................... 37 Figure 6: Hospital Predictions for Select Major Conditions Analysis ........ 37 Figure 7: Options Tab ................................................................................. 38 Pharmacy Adherence for Select Conditions Analysis .................................. 39 Figure 8: Pharmacy Adherence for Select Conditions Analysis ................. 39 Comprehensive Patient Clinical Profile Report View .................................. 40 Figure 9: Comprehensive Patient Clinical Profile Report ........................... 41

Changes to Existing Analyses ......................................................................... 42 Actuarial Cost Projections ............................................................................ 42 Figure 10: Actual Cost Projects - % High Risk Total Cost Column ........... 42 Cost Predictions by Selected Conditions ..................................................... 43 Figure 11: Cost Predictions by Selected Conditions ................................... 43 Care Management List ................................................................................. 44 Figure 12: Care Management List ............................................................... 44

Updated Reference Data ................................................................................. 45 Table 17: Revised RUB Definitions ............................................................ 45

Changes to Export Files .................................................................................. 46 Patient Results File ....................................................................................... 46 Table 18: Patient Results File – New System Markers ............................... 46 Table 19: Rx_gaps, Untreated_rx, CSA, and MPR ..................................... 47 Medical Services (previously Diagnosis) Export File ................................. 48 Table 20: Medical Services Export File Layout .......................................... 48 Pharmacy Codes Export File ........................................................................ 48 Table 21: Pharmacy Codes Export File Layout .......................................... 48 Pharmacy Spans Export File ....................................................................... 49 Table 22: Pharmacy Spans Export File Layout ........................................... 49 All Models Export File ................................................................................ 51 Table 23: All Models Naming Convention ................................................. 51

New Command Line Syntax ........................................................................... 52 Table 24: Command Line Options .............................................................. 52

Miscellaneous Software Fixes ........................................................................ 55 Improved Message for "Java Heap Stack" Error .......................................... 55 Handling Null Patient IDs ............................................................................ 55 Manual Updates to Mapping Files ............................................................... 55 Additional Output Options ........................................................................... 55


iv Release Notes

Custom Format Label Changes .................................................................... 55 Change in Default Behavior of Low Birth Weight Flag ............................. 56 Non-matched Designation Changes ............................................................. 56 Version Compatibility .................................................................................. 56

Documentation Enhancements ...................................................................... 56

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Release Notes 1

Version 9.0 Enhancements Overview

This document discusses the enhancements incorporated into Version 9.0 of The Johns Hopkins ACG® Software. Version 9.0 of The Johns Hopkins ACG Software includes extensive enhancements that not only improve the predictive accuracy for identifying high cost members, but also improve the identification of members with opportunities for intervention. This release focuses on several new methodologies that require additional input data and user configuration options. The major new components include:

• Assessments of pharmacy adherence for a subset of chronic conditions where persistent medication use is anticipated.

• Creation of a taxonomy around coordination of care focusing on the presence of a provider delivering the majority source of care, the number of individual providers and specialties involved, and the inclusion of a generalist in coordinating care.

• Predictions of the likelihood of several types of acute inpatient events.

• Introduction of several new EDCs and Rx-MGs to improve the homogeneity of the groupings.

In addition to these new methodologies, there are numerous technical enhancements. Details on each change to the software are presented in the following sections. Files created under Version 8.2 of the software may be opened in Version 9.0. An update file prompt is displayed. A copy of the Version 8.2 file will be saved with the file extension “acgd-saved-old-version.” Some summary statistics and new output variables will be left blank as they are new to Version 9.0 and were not calculated at time of file creation. Reprocessing of files will be required to populate the new output fields.


2 Release Notes

Customer Input Requirements

To support the new methodologies available in Version 9.0, there are additional input file requirements. Refer to the Installation and Usage Guide, Chapter 4 for a more detailed description of the data requirements.

Tip: Your existing input files will continue to work in Version 9.0 of the software without any changes necessary. The markers and models that are currently generated by Version 8.2 of the software will still be available. However, there may be some fields newly introduced as part of Version 9.0 that can not be calculated without the new data elements.

Exceptions

1. The Rx_fill date is now REQUIRED. Previously, the Rx fill date was part of the pharmacy input file layout but was not utilized. Because the newly introduced pharmacy adherence measures make use of the rx fill date, an incorrect or missing date format will cause the pharmacy input file to fail.

2. If you use the command line functionality to process your data, there has been a change in naming convention for the diagnosis input file. Due to the more extensive data requirements, this file was renamed the medical services file. This naming convention carries through to the command line switches documented in the section titled “Command Line Options” below. Your existing batch scripts will need to be updated for this change.

The Diagnosis File Layout has been expanded and renamed the Medical Services File Layout (Table 2). For the first time, the ACG System will be using procedure and provider information. The additional fields and their uses are described in Table 1.


Release Notes 3

Table 1: Procedure and Provider Information

Field Definition Required for

Service Begin Date The beginning date of the medical service in CCYY-MM-DD format.

Generating utilization markers used in hospitalization models. If unavailable, an alternate input method is available on the patient file.

Defining condition markers for pharmacy adherence.

Calculating Coordination Markers.

Service End Date The ending date of the medical service in CCYY-MM-DD format

Generating utilization markers used in hospitalization models. If unavailable, an alternate input method is available on the patient file



Provider ID The servicing provider. Generating Majority Source of Care Physician and Unique Provider Count

Provider Specialty Primary Specialty of Servicing Provider

Generating Specialty Count

Provider Specialty NPI NPI taxonomy code for provider specialty

Defining eligible and generalist specialties for the Majority Source of Care Physician, Unique Provider Count, Specialty Count and Generalist Seen

Place of Service The recommended format is the CMS place of service coding. Less granular codes of IP (inpatient), ED (Emergency Department) and OP (Outpatient) are also accepted


Defining condition markers for pharmacy adherence


4 Release Notes

Field Definition Required for

Service Begin Date The beginning date of the medical service in CCYY-MM-DD format.

Generating utilization markers used in hospitalization models. If unavailable, an alternate input method is available on the patient file.



Revenue Code A billing code used for facility-based services. This is used to identify emergency department visits and inpatient confinements through the presence of a room and board revenue center. CMS Revenue codes are the recommended format


Procedure Code The procedure performed by the servicing provider. The recommended format is CPT41.


Defining eligible and generalist specialties for the Majority Source of Care Physician, Unique Provider Count, Specialty Count and Generalist Seen

Defining condition markers for pharmacy adherence

Tip: The inclusion of provider and procedure information is used for provider attribution and categorization of services used to predict hospitalization. The traditional ADG, ACG, EDC and Rx-MG markers are still based exclusively on diagnoses and pharmacy information.

1 CPT codes copyright 2009 American Medical Association. All rights reserved. CPT is a trademark of the AMA.


Release Notes 5

Table 2: Complete Medical Services (previously Diagnosis) File Layout


6 Release Notes

Column Name Column Description Data Type Example

patient_id A unique string to identify this individual patient.

Text 9567213984-01

icd_version_1 The version of the ICD code in icd_cd_1. The ACG grouping logic currently supports ICD Version 9 and Version 10.

Number 9

icd_cd_1 The ICD code. This code cannot be longer than six characters. Optionally, an explicit decimal can be included. If a decimal is included, it must be in the fourth position. If a decimal is not included, then the ICD code cannot be longer than five characters.

Text 070.22

icd_version_2 The version for the related icd_cd_2 column.

Number 9

icd_cd_2 The ICD code. Text 070.22


Number 9



Number 9



Number 9


service_begin_date The beginning date of the medical service in CCYY-MM-DD format.

Date 2009-12-31

Service_end_date The ending date of the medical service in CCYY-MM-DD format

Date 2009-12-31

Provider_ID The servicing provider. Text 32415-01

Provider_Specialty Primary Specialty of Servicing Provider Text FP

Provider Specialty_NPI

NPI taxonomy code for provider specialty Text 207Q00000X


Release Notes 7


service_place The place of service in a format that segments inpatient (IP), emergency department (ED) and outpatient (OP) settings for medical services. A recommended format is the CMS place of service coding.

Text IP or 21 (the CMS code for acute care inpatient hospital)

revenue_code A code for facility-based services. This is used to identify inpatient confinements through the presence of a room and board revenue center. A recommended format is the CMS revenue center coding. This field is optional and may be substituted with specialized markers in the patient file

Text 0110

procedure_code The procedure performed by the servicing provider. The recommended format is CPT4.

Text 99201

Revenue_code_type Reserved for future international use; the default is null to identify CMS Revenue codes

Text

Procedure_code_type Reserved for future international use; the default is null to identify CPT4 codes

Text

The Patient Input File format (Table 3) has been expanded with optional utilization markers. Alternatively, these markers can be calculated from details provided in the Medical Services Input File if available.

Tip: Refer to Installation and Usage Guide, Chapter 4 for Business Rules for the Utilization Marker.

The low birth weight flag has also changed. The software will now calculate low birth weight newborns based upon their diagnosis codes. A value of zero (or blank) was added to indicate that this calculation should be performed.

Tip: Historically analyses of claims data has indicated that using diagnoses codes to classify low birth weight infants will result in prevalence rates lower than anticipated when compared to birth registries. Users are encouraged to augment low birth weight information when available.


8 Release Notes

Table 3: Patient Input File Layout


patient_id A unique string to identify this individual member.

Text 9567213984-01

age The patient's age (in years) as of the end of the observation/reporting period.

Number 25

sex A single character or digit to indicate whether the patient is a Male or Female. The software will use F or 2 to identify a Female, all other values indicate Male.

Text M

line_of_business A code to indicate the category of the patient's insurance type. This is typically used by a healthplan to identify Commercial, Medicaid, Medicare+Choice, or some other similar category.

Text COMM

company A code to indicate the financial company for this patient. This is typically used by a health plan to differentiate financial companies, financial products, or state or regional company systems.

Text Generic Care 01

product A code to indicate the patient's insurance product type. This is typically used by a health plan to differentiate an HMO, PPO, or POS product line.

Text HMO

employer_group_id A code to indicate the employer or group that this patient is covered under. This is typically used by a health plan to identify an employer (e.g. General Motors) or another logical member/patient grouping (e.g. Maryland Medicaid).

Text GM

employer_group_name The readable name associated with employer_group_id.

Text General Motors, Inc.


Release Notes 9


benefit_plan The patient's benefit plan. This is typically used by a health plan to identify a benefit package or group of benefit packages.

Text HMO Preferred

health_system The health system that this patient is assigned to. This is typically used by a health plan to identify a risk-sharing arrangement or the hospital system in which the patient's PCP belongs.

Text SignaMed MidWest

pcp_id A code to identify the patient's Primary Care Practitioner.

Text P24050

pcp_name The readable name associated with pcp_id.

Text Dr. John Doe M.D.

pcp_group_id A code to identify the group or financial company for the patient's primary care practitioner.

Text V9604

pcp_group_name A readable name associated with pcp_group_id.

Text SignaMed MidWest Family Practice

Pregnant A code to control the ACG pregnancy related grouping logic.

• 0 or Blank - Determine pregnancy based upon the patient's diagnoses.

• 1 - Patient was pregnant during the observation period.

• Other Value - Patient was not pregnant during the observation period.

Number 0

Delivered A code to control the ACG delivery related grouping logic.

• 0 or Blank - Determine delivery based upon the patient's diagnosis.

• 1 - Patient delivered a baby during the observation period.

• 9 - Ignore all information about delivery status.

• Other Value - Patient did not deliver a baby during the observation period.

Number 1


10 Release Notes


Low_birthweight A code to control the low birth weight related grouping logic.

• 0 or blank – Determine low birth weight status upon the patient’s diagnosis

• 9 - Ignore all information about low birth weight.

• 1 - Patient was born with a low birth weight.

• Other Value - Patient was not born with a low birth weight.

Number 9

Pharmacy_cost The total pharmacy cost for this patient during the observation period.

Number 10250.00

Total_cost The total cost (pharmacy plus medical) for this patient during the observation period.

Number 125000.00

Inpatient_hospitalization_count Count of acute care inpatient stays for causes that are not related to childbirth and injury.

Number 1


Release Notes 11


emergency_visits Count of emergency room visits that did not lead to a subsequent acute care inpatient hospitalization

Number 2

outpatient_visits Count of ambulatory and hospital outpatient visits

Number 12

dialysis_service Patient with Chronic Renal Failure receives dialysis services

• 1 - Patient received dialysis services during the observation period.

• Other value - Patient did not receive dialysis services during the observation period.

Number 1

nursing_service Patient receives nursing services

• 1 - Patient received nursing services during the observation period.

• Other value - Patient did not receive nursing services during the observation period.

Number 2

major_procedure Patient had a major procedure performed in an inpatient setting during the observation period

• 1 - Patient had a major procedure during the observation period.

• Other value - Patient did not have a major procedure during the observation period.

Number 0


12 Release Notes

Version 9.0 contains markers of pharmacy adherence. To support the pharmacy adherence analysis, the Pharmacy Data File (Table 4) has been expanded to include days supply (number). Note also that the fill date needs to be populated for calculation of pharmacy adherence measures.

Table 4: Pharmacy Data File Layout


patient_id A unique string to identify this individual member.

Text 9567213984-01

Rx_fill_dt The date that the prescription was filled by the retail pharmacy in CCYY-MM-DD format

Date 2005-12-05

Pharmacy_Code The NDC or ATC code. NDC codes cannot be longer than 13 characters. Optionally, two hyphens can be included. If hyphens are not included, then the pharmacy code cannot be longer than 11 characters. ATC Codes cannot be longer than seven characters

Text 52446046828 or 52446-0468-28 or C09AA01

Pharmacy_Code_type Indicate whether NDC codes or ATC codes are being used. Use (N) to indicate NDC codes and (A) to indicate ATC Codes. This field will allow blanks and assume that the default is NDC Codes.

Text N

Days_supply The number of days of medication supplied with the prescription.

Number 30


Release Notes 13

New Warnings

The inclusion of new data elements generated a number of new warnings. These messages indicate a warning only. With the exception of null patient IDs, the system continues to process through warnings. The complete list of warnings is provided in Table 5 below.

Table 5: Warnings List

Warning Number Warning Message

6 The patient was greater than 107 years old.

7 The person was pregnant but not a female.

8 The person was pregnant but not of child bearing age (<5 or >55).

11 There was an indication of delivery but not of pregnancy, and the person was of child bearing years, so the patient is assumed to be pregnant.

12 The patient had $0 total costs, but had diagnoses.

13 The patient had $0 pharmacy costs, but had pharmacy codes.

14* The patient had total costs <$100 but had Inpatient, outpatient, or ER count >1

15* The patient had the Dialysis service flag set <0 or >1

16* The patient had the Nursing service flag set <0 or >1

17* The patient had the Major procedure flag set <0 or >1

18* The patient had Emergency Department Visits >12

19* The patient had Inpatient hospitalizations >5

20* The patient had Outpatient visits >30

21* The record is missing Days Supply.

23* The record had a null patient ID in the medical services file.

24* The record had a null patient ID in the pharmacy file.

* These warnings are new to Version 9.0.


14 Release Notes

New Processing Options

There are two new processing options that are now available when building an ACG data file (Figure 1). These new processing options are Stringent Diagnostic Certainty and Calculate Utilization Markers.

Figure 1: Stringent Diagnostic Certainty and Calculate Utilization Markers


Release Notes 15

Stringent Diagnostic Certainty

The recording of provisional diagnosis codes can improperly attribute chronic conditions to a patient subsequently misidentifying individuals for care management programs and elevating cost predictions. The goal of stringent diagnostic certainty is to provide greater certainty of a given diagnosis for a subset of chronic conditions. When the Stringent Diagnostic Certainty option is selected, the system may limit diagnoses used in calculating system markers. This option will apply the following logic to remove rule-out, provisional, or suspect diagnoses:

• A subset of diagnoses has been identified as potentially recorded provisionally. For this subset of diagnoses, a second instance of a diagnosis is required for the ACG system marker to be assigned. If the first date of service is present, the diagnosis must be recorded on a separate date. If date of service is not present, it is assumed that each instance of diagnosis represents a unique encounter.

• If a procedure is present, provisional diagnoses are excluded from rows with the following DME, lab or radiology procedures: 36415 - 36416 , 70000 - 76999, 78000 - 78999, 80000 - 87999, 88000 - 88099, 88104 - 88299, 88300 - 88399, 92551 - 92569, 93000 - 93350, 99000 - 99001, G0001, E0100 - E9999.

• If a place of service is present, provisional diagnoses are excluded from rows with the following place of service codes: 12 , 31, 32, 33, 34, 41, 42, 65, 81, 99, 00.

Note: If the stringent diagnostic certainty option is not selected, the ACG System will still attempt to remove provisional diagnoses based upon DME, lab and radiology procedures or place of service as above. If additional procedure and place of service information is not provided, the user will need to apply their own method of excluding rule-out or provisional diagnoses from their input files.

The filtering of provisional diagnoses applies to ADGs, EDCs, Frailty, HOSDOM, Pregnancy, Delivery, Low Birth Weight, Chronic Condition, Complications of Diabetes and Condition markers.

The processing selection related to diagnostic certainty will be identified in the best model selection and reported in the ACG Data File Summary Statistics and build options. Reference disease prevalence may vary based upon this selection.


16 Release Notes

Calculate Utilization Markers

The Calculate Utilization Markers option indicates that the application should calculate these utilization markers: inpatient_hospitalization_count, emergency_visits, outpatient_visits, dialysis_service, nursing_service, and major_procedure from the detail in the Medical Services Input File. When this option is unchecked, the application will look for these markers in the Patient Input File. The default is to calculate these markers from the Medical Services Input File. The selection is stored in the .acgd file within the build options.

Tip: Specific definitions for these utilization markers are provided below.

New Summary Statistics

A number of new summary statistics have been included to support the assessment of data for data constraints. New summary statistics include:

• Patients with dialysis services

• Patients with nursing services

• Patients with major procedures

• Patients with emergency room visits

• Patients with inpatient hospitalizations

• Patients with outpatient visits

• Population average CSA

• Population average MPR

• Hospitalization model selected

Tip: Many of the new summary statistics relate to new output variables calculated by the ACG System. The specific definitions for these system markers are described later in this document.


Release Notes 17

Data Constraints

If insufficient data is provided to support a particular analytical method, the calculation of related markers will be suppressed. Data presence is determined by a minimum of one non-null entry in the field. Table 6 below provides the minimum data requirements for each major analytical module.

Table 6: Data Constraints

Analytic Module

Required Data

Diagnosis PharmacyUtilization Data1

Procedure Data2

Provider Data3

Pharmacy Fill Detail4

Cost Predictions

X (or) X

Hospitalization Predictions X X(or) X

Coordination of Care X X

Pharmacy Adherence X X X X

1. Utilization data includes dialysis service, nursing service, major procedure, emergency room visits, inpatient hospitalizations, and outpatient visits

2. Procedure data includes begin service date, end service date, place of service, and procedure code.

3. Provider data includes provider ID, provider specialty, and provider specialty NPI.

4. Pharmacy fill detail includes fill date and days supply.


18 Release Notes

License Constraints

Likewise, there are license constraints that may limit availability of specific analytical methods. Table 7 provides the minimum license requirements for each major analytical module.

Table 7: License Constraints

Analysis Diagnosis Pharmacy Hospitalization

Cost Predictions X (or) X

Hospitalization Predictions X X

Coordination of Care X

Pharmacy Adherence X X


Release Notes 19

New Markers

General Considerations

All markers generated by Version 9.0 will be exposed as output in the system and are automatically added to the patient sample, patient list, and patient results export. All markers are also available for filtering criteria.

Utilization Markers

Several utilization markers support the calculation of hospitalization models. These markers may be calculated by the user and provided as part of the patient file. Alternatively, if detailed dates, place of service, procedures, and revenue codes are provided in the Medical Services Input File, the software will automatically calculate these markers.

Tip: See Figure 1 and option for having the software automatically calculate these values.

Dialysis Service

Dialysis service is a binary flag that indicates that a patient with chronic renal failure (EDC REN01) has received at least one dialysis procedure during the observation period.

Nursing Service

Nursing service is a binary flag that indicates that a patient has used nursing facility, domiciliary, rest home, assisted living, or custodial care services during the observation period.

Major Procedure

Major procedure is a binary flag that indicates that a patient has had a major procedure performed in an inpatient setting. This marker considers approximately 3000 CPT and HCPCS codes as major procedures.

Emergency Visit Count

This count is an integer count of emergency room visits that did not lead to a subsequent acute care inpatient hospitalization during the observation period. This marker considers place of service, procedure code, and revenue code to identify emergency room visits.


20 Release Notes

Inpatient Hospitalization Count

The inpatient hospitalization count is an integer count of inpatient confinements during the observation period. The count of inpatient hospitalizations excludes admissions with a primary diagnosis for pregnancy, delivery, newborns, and injuries. Transfers made within and between providers count as a single hospitalization event. This marker is dependent upon revenue codes and dates of service.

Outpatient Visit Count

The outpatient visit count is an integer count of outpatient encounters with place of service of physician office (11), outpatient hospital (22), and other (24, 25, 26, 50, 53, 60, 62, 65, 71, 72) place of service codes. Visits are counted a maximum of once per date of service and provider.


Release Notes 21

Coordination Markers

Version 9.0 introduces four complementary markers to assess the coordination of care. The markers provide a means to systematically assess coordination, an important but often neglected dimension of care. In combination, the markers can identify population at risk for poor coordination which has implications for cost, quality, and performance assessment.

These markers require the provider identifier, provider taxonomy, procedure codes, and the Service Begin Date. If any of these data elements are unavailable, none of the markers will be populated. The coordination markers use the provider taxonomy to determine if a provider is eligible, meaning that the provider can manage and coordinate the medical needs of the patient. For example, an internist, cardiologist, and orthopedic surgeon are considered eligible whereas a chiropractor, social worker, and dentist are not eligible in this context. Additionally, a subset of taxonomy codes is identified as generalists.

Majority Source of Care

Majority source of care percent determines the percent of outpatient visits provided by the eligible physicians that saw the patient the most over the observation period (Table 8).

Majority source of care provider is the provider ID for the eligible physician that delivered the highest percent of outpatient visits. In the case of a tie, multiple providers will be included, separated with a space.

Table 8: Majority Source of Care

Example 1 Example 2

MD 1: Internal medicine: 8 visits MD 1: Internal medicine: 4 visits

MD 2: Cardiology: 2 Visits MD 2: Gastroenterology: 4 visits

MD 3: Chiropractor (not eligible): 1visit MD 3: Endocrinology: 2 visits

Majority source of care % = 80% Majority source of care % = 40%


22 Release Notes

Unique Provider Count

Unique provider count is a count of the number of unique eligible providers that provided outpatient care over the observation period for any condition (Table 9).

Table 9: Unique Provider Count

Example 1 Example 2

MD 1: Geriatrician: 2 visits MD 1: Geriatrician: 4 visits

MD 2: Internal Medicine: 4 visits MD 2: Endocrinology: 2 visits

MD 3: Chiropractor (not eligible): 6 visits MD 3: Neurologist: 2 visits

Unique Provider Count = 2 Unique Provider Count = 3

Specialty Count

Specialty count is the count of the number of eligible specialty types that provided outpatient care over the observation period for any condition (Table 10).

Table 10: Specialty Count

Example 1 Example 2

MD 1: Geriatrician: 2 visits MD 1: Geriatrician: 4 visits

MD 2: Internal Medicine: 4 visits MD 2: Endocrinology: 2 visits

MD 3: Radiologist (not eligible): 1 visit MD 3: Neurologist: 2 visits

Specialty Count = 2 Specialty Count = 3


Release Notes 23

No Generalist Seen

No generalist seen is a binary flag indicating no generalist has provided outpatient care over the observation period (Table 11).

Table 11: No Generalist Seen

Example 1 Example 2

MD 1: Endocrinology: 2 visits MD 1: Geriatrician – (Generalist): 4 visits

MD 2: Neurologist: 2 visits MD 2: Endocrinology: 2 visits

MD 3: Ophthalmologist: 1 visit MD 3: Neurologist: 2 visits

No Generalist Seen = Y No Generalist Seen = N


24 Release Notes

Pharmacy Adherence Markers

Version 9.0 includes the evaluation of medication adherence for a subset of chronic conditions that require ongoing drug therapy. Using administrative claims for the data source, this analysis is measuring medication possession. The conditions evaluated are presented in Table 12.

Table 12: Medication Adherence Markers

Condition Marker Condition Marker

Bipolar Disorder Immunosuppression/Transplant

Congestive Heart Failure Ischemic Heart Disease

Depression Osteoporosis

Diabetes Parkinson's Disease

Glaucoma Persistent Asthma

Human Immunodeficiency Virus Rheumatoid Arthritis

Disorders of Lipid Metabolism Schizophrenia

Hypertension Seizure Disorders

Hypothyroidism


Release Notes 25

New Condition Markers

To facilitate the pharmacy adherence analysis, the condition markers have been expanded and refined. There are now 21 conditions identified with a naming convention of the specific condition appended with _condition. These conditions include the 17 conditions related to pharmacy adherence listed above plus Age-related Macular Degeneration, COPD, Chronic Renal Failure and Low Back Pain that are not evaluated for pharmacy adherence. The values within these condition markers indicate the evidence used to identify members with the condition. The following values are possible:

• NP – The condition is not present; there is no evidence of the condition from any data source.

• ICD – The condition was identified only from diagnosis information.

• Rx – The condition was identified only from pharmacy information.

• BTH – The condition was identified by both diagnosis and pharmacy criteria but minimum treatment criteria were not met.

• TRT – The condition was identified according to specific treatment criteria which include a minimum of two prescriptions (on different dates of service) from an appropriate chronic medication drug class.

Tip: The criteria used to define each condition are described fully in the Technical Reference Guide, Chapter 6.

Notes:

• Age-Related Macular Degeneration, COPD, Chronic Renal Failure, and Low Back Pain are identified as chronic conditions for which disease management or medication therapy management is commonly offered. However, these conditions are not defined for purposes of medication adherence and will never be assigned TRT.

• The Hyperlipidemia condition was renamed Disorders of Lipid Metabolism for consistency with EDC and Rx-MG.

Untreated Rx

The marker conditions have been chosen specifically because the chronic administration of medication is, in most instances, appropriate. There is no intention to make the gap analysis exhaustive across all diseases because chronic medication provision is not warranted for many diseases. However, by identifying conditions where chronic administration of medications is appropriate, we are also able to identify another potentially serious problem in treatment, persons with the target conditions but no evidence of medication prescribing. This group represents a potential problem of under-treatment.


26 Release Notes

When there are no pharmacy claims for the designated drug classes and a target condition is present, an untreated flag is set to Y for that condition. If there is an isolated pharmacy claim for the designated drug classes, the untreated flag is set to P. For each condition, there is a field with the naming convention of the specific condition appended with _untreated_rx containing a text flag to identify patients that are not currently treated with medication.

Tip: The specific criteria used to define an untreated condition are described fully in the Technical Reference Guide, Chapter 6.

Prescription Gaps

Each targeted condition is associated with one or more target drug classes identified by our clinician advisors as a subset of drugs that should be given continuously. (See Technical Reference Guide, Chapter 6 for a listing of the disease-drug class pairings.) The measurement of gaps is confined to only these pairs. It is possible for patients to take multiple ingredients within the same drug class and/or temporarily substitute one ingredient for another within the drug class. To prevent the appearance of oversupply when multiple ingredients are prescribed, Gap, MPR and CSA calculations are performed by active ingredient.

Gaps are defined when the time period between the fill date plus the days supply and the subsequent refill date exceed a grace period. For each condition, there is a field with the naming convention of the specific condition appended with _rx_gaps containing an integer evaluation of medications gaps in excess of the grace period. If a person is on multiple drug classes for a single condition, these will be summarized in this field. Additionally, there are frequent instances where drugs are prescribed in combination. Examples of these drug combinations include: dyphylline-guaifenesin, guaifenesin-theophylline, and potassium iodide-theophylline in asthma. The combinations sometimes span different classes. Gaps will be captured separately for each of the active ingredients and summarized at the condition level. Additional detail of drug classes and refill dates is available in the Pharmacy Spans Export File described below.

Prescribing events are tallied for serial prescriptions (trigger/renewal) in the same drug class. Classes are intended to represent groupings of different drugs that reflect a distinct aspect of therapy for a particular condition. Classes should not be substitutable and it is only required that an individual take drugs from a single class to be considered “treated”. Individuals taking drugs from multiple classes are expected to refill each drug class persistently once medication from the drug class is initially prescribed. Gaps require a minimum of two prescriptions for evaluation of the timing between them. Gaps will not capture individuals that stop a therapy completely.

Figure 2 provides a visual presentation of a gap.


Release Notes 27

Figure 2: Gap in Medication Possession

Measurement begins with the Rx Trigger Date, the filling of a prescription. In this example, the prescribed drug supply ends at 30 days. A varying period follows where there is no prescription, but a gap will not be counted (grace period). In this example, if the prescription remains unfilled at 45 days, a gap will be tallied if one cannot be identified as a subsequent prescription for a drug in the same class during the measurement period (one year). Essential to the occurrence of a gap are two prescriptions during the measurement period. A refill is needed to close a prescribing event. Any prescription that is open at the end of the measurement period will not be included in the gap analysis.

There will be occasions when a patient renews a prescription before their current supply has been completely exhausted. In such cases, the initial prescribing event would generate no gap, the new prescribing event would be defined as a new trigger, and the remaining days from the initial prescription would be added to the termination date for the new prescription. Figure 3 provides a visual presentation of these events.

Figure 3: Gap in Medication Possession Following Oversupply


28 Release Notes

If an inpatient hospitalization occurs between two prescribing events, the remaining days supply of that drug as of the admit date will be added to the discharge date to define when the prescription supply ends. Figure 4 demonstrates how the gap analysis would be adjusted.

Figure 4: Gap in Medication Possession Following Hospitalization

In Figure 4, the balance of the drug supply that remains is added on to the discharge date in order to establish when the official supply ends and the gap clock starts ticking.

If the prescription is renewed within the active prescription period, no gap is counted and a new trigger date is set to recompute the days supply as the days supply of the current prescription plus any balance left from the old prescription.


Release Notes 29

Medication Possession Ratio (MPR)

Medication possession ratio considers the same drug classes as above and is calculated as the total number of days for which medication is dispensed (excluding final prescription) divided by the total number of days between the first and last prescription. For each condition, there is a field with the naming convention of the specific condition appended with _MPR containing the ratio of days supply to days per prescribing period. If a person is on multiple drug classes for a single condition, the days supply and prescribing period will be evaluated separately and weighted across drug classes. Tables 13 and 14 provide examples of different MPRs.

Table 13: MPR Example 1

Rx_fill_date Days_supplySupply Available

Upon RefillDays Exceeding

Grace Period

1/15/2009 30

2/10/2009 30 4

4/2/2009 30 2

5/19/2009 30 2

MPR=90 days supply / (5/19/2009 – 1/15/2009) = 0.73

Table 14: MPR Example 2



Grace Period

1/15/2009 30

2/10/2009 30 4

3/10/2009 30 6

4/06/2009 30 9

MPR=90 days supply / (4/06/2009 – 1/15/2009) = 1.11

In general, this measure is more sensitive to large gaps than to frequent gaps. MPR can be greater than 1.0 if the member consistently refills prior to exhausting days supply. Additional detail of drug classes and refill dates is available in the Pharmacy Spans Export File.


30 Release Notes

Continuous, Single-interval Measure of Medication Availability (CSA)

The Continuous, Single-interval Measure of Medication Availability is calculated as the days supply divided by days until the next prescription averaged across all prescriptions. For each condition, there is a field with the naming convention of the specific condition appended with _CSA. Tables 15 and 16 provide examples of different CSAs.

Table 15: CSA Example 1



Grace Period

1/15/2009 30

2/10/2009 30 4

4/2/2009 30 2

5/19/2009 30 2

CSA = ((30 / (2/10/2009 – 1/15/2009)) + (30 / (4/2/2009 – 2/10/2009)) + (30 / (5/19/2009 – 4/2/2009)))/3 = 0.79

Table 16: CSA Example 2



Grace Period

1/15/2009 30

2/10/2009 30 4

3/10/2009 30 6

4/06/2009 30 9

CSA = ((30 / (2/10/2009 – 1/15/2009)) + (30 / (3/10/2009 – 2/10/2009)) + (30 / (4/6/2009 – 3/10/2009)))/3 = 1.11

In general, this measure is more sensitive to frequent gaps than to large gaps. CSA can be greater than 1.0 if the member consistently refills prior to the exhausting days supply. Additional detail of drug classes and refill dates is available in the Pharmacy Spans Export File.


Release Notes 31

Generic Drug Count Variable

A generic drug count is calculated as the count of unique generic drug (active ingredient)/route of administration combinations encountered in the patient’s drug claims. This marker is a proxy for identifying poly-pharmacy members and contributes significantly to the prediction of cost. This marker is incorporated into all pharmacy-based predictive models (Rx-PM and DxRx-PM). Members with a generic drug count of 13 or greater will get additional weight in the predictive models.


32 Release Notes

Changes to Existing Markers

Modifications to Rx-MGs

Several new Rx-MGs were added to Version 9.0 that provide enhanced predictive accuracy to the pharmacy-based predictive models (Rx-PM and DxRx-PM).

• ENDx060: Growth Problems

• ENDx070: Weight Control

• INFx050: Severe Acute Major Infections

• GSIx040: Severe Pain

All pharmacy-based predictive models (Rx-PM and DxRx-PM) were expanded to include these additional Rx-MGs.

Rx-MG CARx040 was renamed from Hyperlipidemia to Disorders of Lipid Metabolism for consistency with the condition marker for Disorders of Lipid Metabolism

Modifications to EDCs

Several new EDCs were added that provide the specificity necessary for medication adherence conditions and improve predictive performance.

• PSY12: Bipolar Disorder. These diagnoses were previously included in EDC PSY09 (Depression).

• EYE15: Age-Related Macular Degeneration. These diagnoses were previously included in EDC EYE03 (Retinal Disorders).

• RHU05: Rheumatoid Arthritis. These diagnoses were previously included in EDC RHU01 (Autoimmune and connective tissue diseases).

• NUR22: Migraine Headaches. These diagnoses were previously included in EDC NUR02 (Headaches).

• NEW03 (low birth weight) was previously unpopulated. This is now being populated for newborns with diagnosis indicating birth weight less than 2500 grams. This EDC will be used to determine low birth weight status for the ACG decision tree.

• HEM04 and NEW06 both represent newborn jaundice. These two categories were being applied inconsistently between ICD9 and ICD10. NEW06 is being retired and all codes have been moved to HEM04.


Release Notes 33

• END04 (previously Thyroid disease) has been renamed Hypothyroidism and is limited to conditions requiring thyroid hormone replacement. Thyroid conditions not requiring thyroid hormone replacement have been moved to END05 (Other Endocrine Disorders).

• CAR11 (Disorders of Lipid Metabolism) was refined to focus on lipid disorders associated with cardiovascular risk. This is the focus of the drug classes associated with the Disorders of Lipid Metabolism with the pharmacy adherence analysis. Other lipid disorders were moved to GTC02 (Inherited metabolic disorders).


34 Release Notes

New Models

Likelihood of Hospitalization

Hospitalization prediction is a refinement to the ACG predictive models specifically calibrated for identifying patients with risk of future hospitalization. While there is a strong correlation between predicted cost and inpatient hospitalization, the hospital prediction models focus on unanticipated hospitalizations by excluding admissions related to injury, childbirth and newborns and are complementary to the ACG-PM cost prediction models. The populations identified by the hospitalization predictions are likely to have chronic conditions amenable to disease or case management.

There are five new predictive model outputs related to the likelihood of hospitalization. These are logistic models that generate a probability score indicating the likelihood of a future hospitalization event. These models incorporate the new utilization markers of inpatient hospitalizations, emergency department visits, outpatient visits, dialysis services, nursing services, and major procedures in addition to the traditional predictive modeling variables. These models require the Medical Services Input File and optionally include the Pharmacy Input File when available. The data applied by the system for hospitalization predictions will be noted in the summary statistics. The model variants are listed below.

Probability IP Hospitalization Score

Probability IP hospitalization score is the probability score for an acute care inpatient hospital admission within the 12 months subsequent to the observation period.

Probability IP Hospitalization Six Months Score

The probability IP hospitalization six months score is the probability score for an acute care inpatient hospital admission within the six months subsequent to the observation period.

Probability ICU Hospitalization Score

The probability ICU hospitalization score is the probability score for an ICU/CCU admission within the 12 months subsequent to the observation period.

Probability Injury Hospitalization Score

The probability injury hospitalization score is the probability score for an injury-related admission within the 12 months subsequent to the observation period.


Release Notes 35

Probability Extended Hospitalization Score

The probability extended hospitalization score is the probability score for being admitted to an acute care hospital for 12 or more days (across one or more admissions) within the 12 months subsequent to the observation period.

High Pharmacy Utilization Model

This pair of markers highlights the subset of individuals who are at risk for both moderate or high morbidity and consuming pharmacy resources at a rate significantly greater than anticipated based on their morbidity. This approach identifies a different subset of the population at risk for future high pharmacy expenditures than traditional diagnoses-based methods. Review of individual cases may reveal use of expensive medications, poor coordination, poor ICD9 data capture, inadequate care, poly-pharmacy or patient abuse. Additional markers in the ACG System may be helpful in categorizing high risk members identified by this method.

Probability of Unexpected Pharmacy Cost

The probability of unexpected pharmacy cost is a numerical probability score representing the result of applying weights from a logistic regression model predicting individuals with moderate or high morbidity who have unusually large pharmacy expenditures. The model independent variables are inclusive of age, gender, ACG categories, select high impact conditions defined by EDCs, Rx-MGs, hospital dominant conditions, and frailty. The markers in the model are same as the DxRx-PM model markers without prior cost.

High Risk for Unexpected Pharmacy Cost

High Risk for Unexpected Pharmacy Cost is a binary flag that indicates individuals with a Probability of Unexpected Pharmacy Cost greater than 0.4.


36 Release Notes

New Analyses

Hospitalization Risk Distribution

The ACG Data File Summary screen (Figure 5) includes a tab entitled, Hospitalization Risk Dist, for the probability of inpatient hospitalization within the next 12 months. The format of this additional report parallels the existing Probability Distribution Summary which has been renamed Total Cost Risk Distribution for clarity.

Figure 5: Hospitalization Risk Distribution


Release Notes 37

Hospital Predictions for Select Major Conditions Analysis

There is a new analysis available from the Analyze menu entitled, Hospital Predictions for Select Major Conditions. The format of this report parallels the Cost Predictions for Selected Conditions report, replacing the cost risk probability with the risk of hospitalization. The conditions listed in this report include all EDCs that are part of the predictive model. Figure 6 provides an example of the Hospital Predictions for Select Major Conditions analysis.

Figure 6: Hospital Predictions for Select Major Conditions Analysis

By default, the analysis will include the probability of inpatient hospitalization within 12 months and the average predicted resource use will be based upon total cost risk. The Options tab can be used to select any available hospitalization scores and optionally calculate average predicted resource use on pharmacy cost risk.


38 Release Notes

Figure 7: Options Tab


Release Notes 39

Pharmacy Adherence for Select Conditions Analysis

There is a new analysis available from the Analyze menu entitled, Pharmacy Adherence for Select Conditions (Figure 8). The format of this report parallels the Cost Predictions for Selected Conditions report, replacing the cost risk probability with the number of medication gaps encountered. Additionally, the average CSA and average MPR are provided for members meeting treatment criteria. The average number of gaps for high- risk members includes members meeting treatment criteria that also have a minimum probability of high total cost greater than 0.4. The conditions listed in this report include the 17 conditions being evaluated for medication adherence.

Figure 8: Pharmacy Adherence for Select Conditions Analysis


40 Release Notes

Comprehensive Patient Clinical Profile Report View

To display the new patient markers, a more Comprehensive Patient Clinical Profile Report (Figure 9) is available from the Analyze menu. This view is presented in addition to the Patient Clinical Profile. As with the Patient Clinical Profile, this report is linked to the care management list and can display a single member or all members meeting the designated criteria.


Release Notes 41

Figure 9: Comprehensive Patient Clinical Profile Report


42 Release Notes

Changes to Existing Analyses

Actuarial Cost Projections

The Actuarial Cost Projections analysis has been revised to include the percent with a probability of hospitalization greater than 0.4 for each of the hospitalization models. For clarity, the % high risk column was renamed to % High Risk Total Cost (Figure 10).

Figure 10: Actual Cost Projects - % High Risk Total Cost Column


Release Notes 43

Cost Predictions by Selected Conditions

The Cost Predictions by Selected Conditions was revised to reflect the new condition markers (Figure 11). There are 21 conditions in total; 17 conditions support medication adherence plus Age-Related Macular Degeneration, Low Back Pain, COPD and Chronic Renal Failure.

Figure 11: Cost Predictions by Selected Conditions


44 Release Notes

Care Management List

The Care Management List (Figure 12) was revised to include several new markers: the Probability of Inpatient Hospitalization within 12 months, the number of unique providers seen and the number of gaps in prescription refills across all conditions. The condition markers have been updated to reflect the 21 conditions available; 17 conditions support medication adherence plus Age-Related Macular Degeneration, Low Back Pain, COPD and Chronic Renal Failure.

Figure 12: Care Management List


Release Notes 45

Updated Reference Data

The US Elderly and US Non-elderly risk assessment variables have been updated to CY 2007 data from IMS Health (Table 17). These variables include coefficients for all model variants, EDC and Rx-MG prevalence rates, and reference concurrent weights. As part of this refresh, six ACGs were moved to different RUBs.

Table 17: Revised RUB Definitions

ACG Description Version 8.2 RUB Version 9.0 RUB

1752 Pregnancy: 4-5 ADGs, 1+ Major ADGs, not delivered

3 4

1762 Pregnancy: 6+ ADGs, no Major ADGs, not delivered

3 4

1900 Acute Minor and Likely to Recur, Age 1

3 2

5010 10+ Other ADG Combinations, Age 1 to 17, no Major ADGs

4 3

5342 Infants: 6+ ADGs, 1+ Major ADGs, normal birth weight

5 4

9900 Invalid Age or Date of Birth 1 0

The reference data spreadsheets that are installed in your program group describe the key characteristics of the updated reference population.


46 Release Notes

Changes to Export Files

Patient Results File

The Patient Results File has been expanded to accommodate new system markers (Table 18).

Table 18: Patient Results File – New System Markers

Export Columns Export Columns

High_Risk_Unexpected_ pharmacy_cost Unique_Provider_Count

Probability_Unexpected_pharmacy_cost Specialty_Count

Dialysis service No_Generalist

Nursing Service Generic Drug Count

Major Procedure Inpatient_hospitalization_prob

Outpatient visits Inpatient_hospitalization_6_months_prob

ER visits ICU_hospitalization_prob

Inpatient stays Injury_hospitalization_prob

Majority_Source_of_Care_percent Extended_hospitalization_prob

Majority_Source_of_Care_Provider


Release Notes 47

In addition, for each of the following conditions (Table 19), Rx_gaps, Untreated_rx, CSA, and MPR are available.

Table 19: Rx_gaps, Untreated_rx, CSA, and MPR


Bipolar Disorder Immunosuppression/Transplant

Congestive Heart Failure Ischemic Heart Disease

Depression Osteoporosis

Diabetes Parkinson's Disease

Glaucoma Persistent Asthma

Human Immunodeficiency Virus Rheumatoid Arthritis

Disorders of Lipid Metabolism Schizophrenia

Hypertension Seizure Disorders

Hypothyroidism


48 Release Notes

Medical Services (previously Diagnosis) Export File

The Medical Services Export option was previously named Diagnoses export. This file has been renamed and expanded to include the data contained in the Medical Services File. The new layout for the Medical Services export option is presented in Table 20.

Table 20: Medical Services Export File Layout


patient_id service_begin_date

icd_version_1 service_end_date

icd_cd_1 provider_id

icd_version_2 provider_specialty

icd_cd_2 provider_specialty_npi

icd_version_3 service_place

icd_cd_3 revenue_code

icd_version_4 procedure_code

icd_cd_4 revenue_code_type

icd_version_5 Procedure_code_type

icd_cd_5

Pharmacy Codes Export File

The Pharmacy Codes Export File has been expanded to include the new pharmacy input fields. The new layout for the Pharmacy Codes File is presented in Table 21.

Table 21: Pharmacy Codes Export File Layout


patient_id

rx_fill_date

rx_cd

rx_code_type

rx_days_supply

Release Notes 49

Pharmacy Spans Export File

The new Pharmacy Spans Export File is a file type that provides the refill detail related to pharmacy adherence. The new layout for the Pharmacy Spans Export File is presented in Table 22.

Table 22: Pharmacy Spans Export File Layout

Column Definition

Patient ID A unique string to identify an individual member and primary key to the ACG data file.

Condition Name The string describing the condition marker being evaluated with this pharmacy span. The patient ID must have a TRT flag in the condition marker.

Rx Drug Class The string describing the drug class associated with this pharmacy span.

Rx Drug Ingredient The string describing the drug ingredient associated with this pharmacy span.

Rx Fill Date The fill date on the pharmacy data file.

Rx Refill Date The subsequent fill date for the same condition-drug class-ingredient combination.

Rx Days Supply The days supply provided on the pharmacy data file.

Rx IP Days The number of inpatient days added to the supply.

Days Carried Over The supply on hand at the end of the previous prescription accounting for refills with existing supply and inpatient days during the refill period.

Rx Supply Begin Date

The date at which any previous supply would be exhausted and the current prescription would begin being consumed (fill date + days carried over).

Rx Supply End Date

The date at which the current prescription supply would be exhausted taking into account days carried over and inpatient days (supply begin + days supply + IP Days – 1).

Rx Supply Available Upon Refill

The supply on hand at the refill date accounting for days carried over and inpatient days during the refill period. The Rx Supply Available Upon Refill for the current prescription will be the same as the Days Carried Over on a subsequent prescription (supply end - refill dt + 1).

Rx Grace Period The grace period associated with the Condition-Drug class combination in the determination of pharmacy gaps.


50 Release Notes

Column Definition

Rx Days Exceeding Grace Period

The number of days without medication possession after accounting for days carried over and inpatient days (refill dt - supply end dt - 1 - grace period).

Rx Eligible for Adherence

A flag indicating that the prescription period was used in the calculation of pharmacy gaps, MPR and CSA. The value Y is included, P is included in CSAand MPR but excluded from gap counts, N is excluded from all pharmacy adherence measures.


Release Notes 51

All Models Export File

The All Models option produces all possible model variants given the data sources provided and diagnostic certainty selected. This export file has been updated to include new model variants. The naming convention for models has also been expanded to allow for additional variations related to predicting hospitalization and diagnostic certainty. The naming convention for predictive modeling outputs is now:

Data source – Use of prior cost – diagnostic certainty – dependent variable – score type. Possible values for each component of the model name are presented in Table 23 below

Table 23: All Models Naming Convention

Name Component Possible Values

Data Source DxPM – the model uses diagnosis-based markers as predictors

RxPM – the model uses pharmacy-based markers as predictors

DxRxPM – the model uses both diagnosis and pharmacy-based markers as predictors

Use of Prior Cost Ttcost – prior total cost is an independent variable in the model

Rxcost – prior pharmacy cost is an independent variable in the model

Nocost – prior cost is not considered by the model

Diagnostic Certainty L – diagnosis markers allow lenient criteria for assignment

S- diagnosis markers require stringent criteria for assignment

Dependent Variable Tt – total cost

Rx – pharmacy cost

Inp – hospitalization within 12 months

Inp6 – hospitalization within 6 months

Ext – extended hospitalization

Icu – hospitalization requiring ICU/CCU

Inj – hospitalization for injury


52 Release Notes

Name Component Possible Values

Score Type Pri – predicted resource index from reference population

Prir – predicted resource index rescaled to study population

Prob – probability of being in the top 5% of of costs next year

Hosp – probability of being hospitalized next year

New Command Line Syntax

The command line interface was updated to reflect the new user options and changes to input and output files. The command line options are provided below. Command line usage is fully described in the Installation and Usage Guide, Appendix C

Table 24: Command Line Options

Option Description

-new-acg-file <file> Creates a new ACG Data File called <file>.

-patient <file Uses <file> as patient source data file.

-patient-format <file> Uses <file> as the format definition for the patient data.

-patient-skip Skips first row from patient file.

-medical <file> Uses <file> as medical source data file.

-medical-skip Skips first row from medical file.

-pharmacy <file> Uses <file> as pharmacy source data file.

-pharmacy-skip Skips first row from pharmacy file.

-rav <rav-code> Uses <rav-code> stated RAV for calculations.

• US-ELD = US Elderly

• US-NONELD = US Non-Elderly

• (The default if no rav is specified is US-NONELD.)

-all-models Generates all valid predictive models.

-ignore-prior-costs Ignores prior cost data.


Release Notes 53

Option Description

-stringent-dx-certainty Uses stringent diagnostic certainty. Default is lenient (legacy method).

-use-provided-util Uses provided utilization markers. Default calculates from medical services data.

-export <type> Exports data from an ACG Data File.

<type> determine what data to export as follows:

• PATIENT - exports patient details

• ADG – exports ADG assignments

• EDC - exports EDC assignments

• MEDC - exports MEDC assignments

• RXMG - exports Rx-MG assignments

• MAJ-RXMG - exports Major Rx-MG assignments

• MEDICAL - exports medical services

• PHARMACY - exports patient pharmacy codes

• NM-DIAGS - exports non-matched diagnosis codes

• NM-PHARMACY - exports non-matched pharmacy codes

• WARNINGS - exports warnings

• LOCAL-WEIGHTS - exports local weights

• MARKERS - exports model markers

• MODELS - exports all model outputs

• PHARMACY-SPANS – exports pharmacy spans

-delim TAB|COMMA Uses a tab or comma delimiter for export. If not specified, TAB is used.

-col-file <file> Exports only the columns listed in <file>. <file> should contain columns on separate lines. Only valid for PATIENT export.

-acg-file <file> Uses the acg data file <file> to export from.

-export-file <file> Exports data into <file>.

-headers NONE|NAME|DESC NONE exports no headers


54 Release Notes

Option Description

NAME exports column names as headers DESC exports descriptions

-install-license <file> Installs the license in <file>.

-install-mapping-file <file> Installs the mapping file <file>.

-help Prints this message.


Release Notes 55

Miscellaneous Software Fixes

Improved Message for "Java Heap Stack" Error

When the ACG System encounters an out-of-memory condition, the “Java heap stack” error was previously received. Most frequently this happens when an analysis spreadsheet includes a very large number of combinations to calculate (e.g., patient ID were included as a grouping field). The new error message now identifies an out of memory condition.

Handling Null Patient IDs

Prior to Version 9.0, the application did not import a data source if there were null patient IDs and did not generate an error. In Version 9.0, if either the Pharmacy file or Diagnosis file contains null patient IDs, a warning code is created, and the file continues to load with the remainder of the data. The warning list will contain a row with only the warning number. All other columns will be missing.

Manual Updates to Mapping Files

When loading a mapping file manually using the file chooser, previously no status was given, and it appeared that the system was hanging. The mapping loaded correctly, but there was no indication that the system was working. This issue has been corrected, and there is now a window with a status bar indicating that the mapping file is installing.

Additional Output Options

The Patient Clinical Profile can now be stored in rich text format in addition to Adobe Acrobat®.

Custom Format Label Changes

For the most part, when a custom file format is used, the column description is applied so that custom format label changes are used by the system. The exceptions were the filter criteria stored in the Report Options tab, the filter criteria applied at data file build time stored the build options, and the PCP ID and Product labels in the member clinical profile. The column description is now used instead of the column name in these views.


56 Release Notes

Change in Default Behavior of Low Birth Weight Flag

The EDC NEW03 defines diagnoses indicating low birth weight. Low birth weight is used in the ACG decision tree to split ACGs 5310, 5320, 5330 and 5340 for infants based on low birth weight status. The low birth weight flag was changed in the input data file to operate like the pregnant and delivered flag. A value of zero has been added to this flag to facilitate this branching from diagnosis codes. Zero is also the new default behavior. In order to regroup the ACGs regardless of low birth weight status, populate Low_birthweight on the Medical Services Input File with a value of nine.

Non-matched Designation Changes

Due to the expansion of markers, a non-matched ICD or Rx will now represent a code that is not part of the mapping file for any category or indicator used by the model. For example, a non-matched Dx code is one that is not mapped to an EDC, ADG, or a chronic condition category, and is not indicated as delivery, complex diabetes, pregnancy, low birth weight, or uncertain (Dx certainty logic). Since valid E Codes are intentionally excluded from the morbidity markers, valid E Codes have been included in the mapping file. Previously, non-matched diagnosis codes were identified based on the ADG mapping. Users will note overall lower non-matched diagnosis rates. The remaining diagnoses should represent invalid codes.

Version Compatibility

Version 9.0 can open .acgd files created under a Version 8.2; however, the data will not incorporate new EDCs, Rx-MGs or model coefficients until the data files have been rebuilt. Likewise, there are many new markers that require additional data elements. These new markers will remain blank until the data file is reprocessed with the required data elements.

Version 8.2 filters are not maintained in Version 9.0. There were changes to the names of multiple fields that would create potential errors for historic filters. If you have a library of filters that you would like to preserve, please contact your technical support representative.

Documentation Enhancements

The documentation has been reorganized to enhance usability. The documentation has been updated for the new markers and has been redistributed into the following three documents:

• Installation and Usage Guide• Applications Guide• Technical Reference Guide


Release Notes 57

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