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TMSIS Dataguide Medicaid.gov
Version 3.27.0

EL-1-009-8

Data Quality Measure
Last updated

Key Information

Measure Name Index of dissimilarity - ethnicity
File Type ELG
Measure ID EL-1-009-8
Measure Type Frequency
Content area ELG

Validation

Validation Type Index of Dissimilarity

Measure Priority

Measure Priority Medium
Focus Area Race/ethnicity
Category Beneficiary demographics

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 0.05
Longitudinal Threshold N/A
For TA
(for including in compliance training) 		TA- Inferential
For TA
(Longitudinal) 		No

Data Elements

DD Data Element ETHNICITY-CODE
DD Data Element Number ELG204

Annotation Calculate the index of dissimilarity measure - ethnicity
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: Ethnicity information on the last day of DQ report month

Using the MSIS IDs that meet the criteria from STEP 1, join to segment ETHNICITY-INFORMATION-ELG00015 by keeping active records that satisfy the following criteria:

1a. ETHNICITY-DECLARATION-EFF-DATE <= last day of the DQ report month

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

OR

1b. ETHNICITY-DECLARATION-EFF-DATE is missing

2b. ETHNICITY-DECLARATION-END-DATE is missing



STEP 3: Non-missing ethnicity

Of the MSIS IDs that meet the criteria from STEP 2, further refine the population by keeping records with:

1. ETHNICITY-CODE non-missing



STEP 4: Percent ethnicity for the current month

1. For each distinct value of ethnicity code, set the number of unique MSIS IDs as Numerator_Count_By_Value.

2. Set the total number of unique MSIS IDs across all valid values of ethnicity code as Denominator_Count. Note that Denominator_Count should also equal to the count of MSIS IDs from STEP 3.

3. For each distinct value of ethnicity code, calculate Percent_Current_Month as the ratio of Numerator_Count_By_Value over Denominator_Count.



STEP 5: Percent ethnicity for the previous month

Repeat STEP 1 through STEP 4 for the previous month. For each distinct value of ethnicity code, set the percent of ethnicity code for the previous month as Percent_Prior_Month_1.



STEP 6: Calculate change between months

For each frequency percent, calculate Frequency_Change as the absolute value of (Percent_Current_Month – Percent_Prior_Month_1) / 2. Note that Frequency_Change is a vector of frequencies.



STEP 7: Calculate index of dissimilarity

Calculate the index of dissimilarity by summing Frequency_Change across all frequencies and dividing by 100