EL-5-001-3

Data Quality Measure

Last updated

Key Information

Measure Name	Index of dissimilarity - CHIP by age group for M-CHIP and S-CHIP (CHIP-CODE = 2, 3)
File Type	ELG
Measure ID	EL-5-001-3
Measure Type	Frequency
Content area	ELG

Validation

Validation Type	Index of Dissimilarity

Measure Priority

Measure Priority	Medium
Focus Area	N/A
Category	Beneficiary eligibility

Claim Information

Claim Type	N/A
Adjustment Type	N/A
Crossover Type	N/A

Thresholds

Minimum	0
Maximum	0.05
TA Minimun	0
TA Maximum	0.1
Longitudinal Threshold	N/A
For TA (for including in compliance training)	TA- Inferential
For TA (Longitudinal)	No

Data Elements

DD Data Element	MSIS-IDENTIFICATION-NUM • CHIP-CODE
DD Data Element Number	ELG019 • ELG054

Annotation	The age groups for the measure are defined. Each age group should be run as its own frequency. Where the denominator is the records with CHIP code = 2, run a frequency for the defined age groups. For CHIP code = 2, the frequencies across the age groups should sum to 100. (continued on the row below) Where the denominator is the records with CHIP code = 3, run a frequency for the defined age groups. For CHIP code = 3, the frequencies across the age groups should sum to 100. For each chip code, run the frequency of age groups for the previous month. Calculate the change in value from the previous month to the current month for each frequency percent. Sum the changes across all frequencies.
Specification	STEP 1: Enrolled on the last day of DQ report month Define the eligible population from segment ENROLLMENT-TIME-SPAN-ELG00021 by keeping active records that satisfy the following criteria: 1. ENROLLMENT-EFF-DATE <= last day of the DQ report month 2. ENROLLMENT-END-DATE >= last day of the DQ report month OR missing 3. MSIS-IDENTIFICATION-NUM is not missing STEP 2: Primary demographics on the last day of DQ report month Using the MSIS IDs that meet the criteria from STEP 1, join to segment PRIMARY-DEMOGRAPHICS-ELG00002 by keeping records that satisfy the following criteria: 1a. PRIMARY-DEMOGRAPHIC-ELEMENT-EFF-DATE <= last day of the DQ report month 2a. PRIMARY-DEMOGRAPHIC-ELEMENT-END-DATE >= last day of the DQ report month OR missing OR 1b. PRIMARY-DEMOGRAPHIC-ELEMENT-EFF-DATE is missing 2b. PRIMARY-DEMOGRAPHIC-ELEMENT-END-DATE is missing STEP 3: Calculate Age Using the PRIMARY-DEMOGRAPHICS-ELG00002 segment. 1a. If DATE-OF-DEATH is non-missing and occurs before the last day of the DQ report month, Age is equal to the years between DATE-OF-DEATH and DATE-OF-BIRTH. 1b. Otherwise, Age is equal to the years between the last day of the DQ report month and DATE-OF-BIRTH. STEP 4: Create age categories Create age group using the following categories: Age <1 1 <= Age <= 5 6 <= Age <= 14 15 <= Age <= 18 19 <= Age <= 20 21 <= Age <= 44 45 <= Age <= 64 65 <= Age <= 74 75 <= Age <= 84 Age >= 85 STEP 5: Variable demographics on the last day of report month Using the MSIS IDs that meet the criteria from STEP 2, join to segment VARIABLE-DEMOGRAPHIC-ELG00003 by keeping records that satisfy the following criteria: 1a. VARIABLE-DEMOGRAPHIC-ELEMENT-EFF-DATE <= last day of the DQ report month 2a. VARIABLE-DEMOGRAPHIC-ELEMENT-END-DATE >= last day of the DQ report month OR missing OR 1b. VARIABLE-DEMOGRAPHIC-ELEMENT-EFF-DATE is missing 2b. VARIABLE-DEMOGRAPHIC-ELEMENT-END-DATE is missing STEP 6: Merge CHIP-CODE Using the dataset from STEP 4, merge on CHIP-CODE from the dataset in STEP 5 STEP 7: Restrict to a specific CHIP-CODE value From STEP 6, select those where CHIP-CODE = “2” or “3” STEP 8: Calculate frequency From STEP 7, count the total number of MSIS IDS in each age group, separately for each selected CHIP-CODE (“2” or “3”) STEP 9: Calculate percentage Divide the count of MSIS IDs in each age group and CHIP-CODE combination (e.g., CHIP-CODE = 2, Ages 1 - 5) from STEP 8 by the total number of MSIS IDs from STEP 7 STEP 10: Repeat for prior month Repeat STEPS 1 through 9 for the prior month. STEP 11: Calculate change for each age category Calculate one-half of the absolute difference of the percentage for each age group and CHIP-CODE combination between the current and prior month STEP 12: SUM to calculate index of dissimilarity statistic Sum the values from STEP 11 across all age group CHIP-CODE categories

Annotation

The age groups for the measure are defined. Each age group should be run as its own frequency.

Where the denominator is the records with CHIP code = 2, run a frequency for the defined age groups. For CHIP code = 2, the frequencies across the age groups should sum to 100.

(continued on the row below)

Where the denominator is the records with CHIP code = 3, run a frequency for the defined age groups. For CHIP code = 3, the frequencies across the age groups should sum to 100.

For each chip code, run the frequency of age groups for the previous month.

Calculate the change in value from the previous month to the current month for each frequency percent.

Sum the changes across all frequencies.

Specification

STEP 1: Enrolled on the last day of DQ report month

Define the eligible population from segment ENROLLMENT-TIME-SPAN-ELG00021 by keeping active records that satisfy the following criteria:

1. ENROLLMENT-EFF-DATE <= last day of the DQ report month

2. ENROLLMENT-END-DATE >= last day of the DQ report month OR missing

3. MSIS-IDENTIFICATION-NUM is not missing

STEP 2: Primary demographics on the last day of DQ report month

Using the MSIS IDs that meet the criteria from STEP 1, join to segment PRIMARY-DEMOGRAPHICS-ELG00002 by keeping records that satisfy the following criteria:

1a. PRIMARY-DEMOGRAPHIC-ELEMENT-EFF-DATE <= last day of the DQ report month

2a. PRIMARY-DEMOGRAPHIC-ELEMENT-END-DATE >= last day of the DQ report month OR missing

OR

1b. PRIMARY-DEMOGRAPHIC-ELEMENT-EFF-DATE is missing

2b. PRIMARY-DEMOGRAPHIC-ELEMENT-END-DATE is missing

STEP 3: Calculate Age

Using the PRIMARY-DEMOGRAPHICS-ELG00002 segment.

1a. If DATE-OF-DEATH is non-missing and occurs before the last day of the DQ report month, Age is equal to the years between DATE-OF-DEATH and DATE-OF-BIRTH.

1b. Otherwise, Age is equal to the years between the last day of the DQ report month and DATE-OF-BIRTH.

STEP 4: Create age categories

Create age group using the following categories:

Age <1

1 <= Age <= 5

6 <= Age <= 14

15 <= Age <= 18

19 <= Age <= 20

21 <= Age <= 44

45 <= Age <= 64

65 <= Age <= 74

75 <= Age <= 84

Age >= 85

STEP 5: Variable demographics on the last day of report month

Using the MSIS IDs that meet the criteria from STEP 2, join to segment VARIABLE-DEMOGRAPHIC-ELG00003 by keeping records that satisfy the following criteria:

1a. VARIABLE-DEMOGRAPHIC-ELEMENT-EFF-DATE <= last day of the DQ report month

2a. VARIABLE-DEMOGRAPHIC-ELEMENT-END-DATE >= last day of the DQ report month OR missing

OR

1b. VARIABLE-DEMOGRAPHIC-ELEMENT-EFF-DATE is missing

2b. VARIABLE-DEMOGRAPHIC-ELEMENT-END-DATE is missing

STEP 6: Merge CHIP-CODE

Using the dataset from STEP 4, merge on CHIP-CODE from the dataset in STEP 5

STEP 7: Restrict to a specific CHIP-CODE value

From STEP 6, select those where CHIP-CODE = “2” or “3”

STEP 8: Calculate frequency

From STEP 7, count the total number of MSIS IDS in each age group, separately for each selected CHIP-CODE (“2” or “3”)

STEP 9: Calculate percentage

Divide the count of MSIS IDs in each age group and CHIP-CODE combination (e.g., CHIP-CODE = 2, Ages 1 - 5) from STEP 8 by the total number of MSIS IDs from STEP 7

STEP 10: Repeat for prior month

Repeat STEPS 1 through 9 for the prior month.

STEP 11: Calculate change for each age category

Calculate one-half of the absolute difference of the percentage for each age group and CHIP-CODE combination between the current and prior month

STEP 12: SUM to calculate index of dissimilarity statistic

Sum the values from STEP 11 across all age group CHIP-CODE categories