MINI-SENTINEL COMMON DATA MODEL DATA QUALITY REVIEW AND CHARACTERIZATION PROCESS AND PROGRAMS

(1)

MINI-SENTINEL COMMON DATA MODEL

DATA QUALITY REVIEW AND CHARACTERIZATION PROCESS AND

PROGRAMS

Program Package version: 3.2

Prepared by the Mini-Sentinel Operations Center

May 2014

Mini-Sentinel is a pilot project sponsored by the

U.S. Food and Drug Administration (FDA)

to inform and

facilitate development of a fully operational active surveillance system, the Sentinel System, for

monitoring the safety of FDA-regulated medical products. Mini-Sentinel is one piece of the

Sentinel

Initiative

, a multi-faceted effort by the FDA to develop a national electronic system that will complement

existing methods of safety surveillance. Mini-Sentinel Collaborators include Data and Academic Partners

that provide access to health care data and ongoing scientific, technical, methodological, and

organizational expertise. The Mini-Sentinel Coordinating Center is funded by the FDA through the

Department of Health and Human Services (HHS) Contract number HHSF223200910006I.

(2)

I. OVERVIEW ... - 1 -

II. DATA QUALITY REVIEW PROCESS ... - 1 -

A. DISTRIBUTED PROGRAMMING AND DATA QUALITY CHECKS ... - 1 -

B. DATA PARTNER QUALITY REVIEW AND CHARACTERIZATION REPORT ... - 2 -

III. PROGRAM PACKAGE ... - 2 -

A. CORE TABLES QUALITY REVIEW ... - 2 -

B. LABORATORY TABLE QUALITY REVIEW... - 4 -

C. VITAL SIGNS TABLE QUALITY REVIEW ... - 4 -

IV. PROGRAM EXECUTION ... - 5 -

V. PROGRAM PACKAGE OUTPUT ... - 5 -

A. CORE QUALITY REVIEW OUTPUT EXAMPLE ... - 5 -

B. LAB QUALITY REVIEW OUTPUT EXAMPLE ... - 6 -

C. VITAL SIGNS QUALITY REVIEW OUTPUT EXAMPLE ... - 7 -

VI. APPENDIX A: LIST OF ALL QA ERR CODES ... - 8 -

(3)

Modification History

Version

Date

Modification

By

3.2 5/30/2014

• Integrated Common Components

Mini-Sentinel Operations Center

• Added MSCDM v4.0 compliance

checks, minor bug fixes

3.1.3 03/03/2014 • Implemented minor bug fixes

Mini-Sentinel Operations Center

3.1.2 09/25/2013 • Implemented minor bug fix

Mini-Sentinel Operations Center

3.1.1 09/16/2013 • Implemented minor bug fix

Mini-Sentinel Operations Center

3.1 09/05/2013 • Added/modified lab and vitals

Mini-Sentinel Operations Center

checks, fixed bugs

3.0.1 03/01/2013 • Updated for UNIX compatibility

Mini-Sentinel Operations Center

3.0 11/12/2012 • Added PatID and EncounterID

Mini-Sentinel Operations Center

matching, enhanced valid date

checks, fixed bugs

• Added clinical data (labs and vitals)

programs

2.0 10/14/2010 • Added duplicate record checks,

Mini-Sentinel Operations Center

modified dataset names, fixed bugs

(4)

I. OVERVIEW

This document describes the process and version 3.2 program package used by the Mini-Sentinel

Operations center (MSOC) for data quality review and characterization of the Mini-Sentinel Distributed

Database (MSDD). To create the MSDD, each Data Partner transforms local source data into the

Mini-Sentinel Common Data Model (MSCDM) format. The MSOC uses a set of data quality review and

characterization programs (i.e., a “program package”) to ensure that the MSDD meets reasonable

standards for data transformation consistency and quality.

II. DATA QUALITY REVIEW PROCESS

A data quality review is conducted by MSOC when a Mini-Sentinel Data Partner updates their MSCDM

database to include additional data. Following a database update, or “refresh,” a distributed program

package developed by the MSOC is executed locally by the Data Partner, and aggregate output tables

are returned to MSOC for review. MSOC analysts perform two independent reviews of the output and

generate a consensus report of findings. MSOC and the Data Partner work closely together to resolve

outstanding issues and approve the data for use in Mini-Sentinel data requests. Updated data are not

used in requests until the refresh has been approved by MSOC.

A. DISTRIBUTED PROGRAMMING AND DATA QUALITY CHECKS

To evaluate data characteristics and quality, MSOC developed distributed code to query the content of

MSCDM formatted tables. The distributed code generates aggregate output tables that help determine

whether the data conform to MSCDM specifications, maintain integrity across variables and across

tables, and trend as expected over time. Output tables are designed to evaluate one or more data checks,

i.e., pre-defined data quality measures or characterizations. Each data check is designated a “level 1,”

“level 2,” “level 3,” or “level 4” data quality check depending on the complexity and assigned an “Err

Code” for tracking and reporting purposes. An “Err Code” can represent a data characteristic or a data

issue (see

Section IIB

for more information on Err Codes).

Level 1 data checks review the completeness and content of each variable in each table to ensure that

the required variables contain data and conform to the formats specified by the MSCDM specifications.

For each MSCDM variable, level 1 data checks verify that data types, variable lengths, and SAS formats

are correct and reported values are acceptable. For example, ensuring that the variable SEX in the

Demographic table has a value of “F,” “M,” “A,” or “U” is a level 1 data check.

Level 2 data checks assess the logical relationship and integrity of data values within a variable or

between two or more variables within and between tables. For example, the MSCDM requires that the

variable ADMITTING_SOURCE in the Encounter table is populated only for inpatient and institutional

encounters (i.e., ENCTYPE= “IP” or “IS”). A level 2 data check would ensure that ADMITTING_SOURCE is

populated only when ENCTYPE= “IP” or “IS”.

Level 3 data checks examine data distributions and trends over time, both within a Data Partner’s

database (by examining output by year and year/month) and across a Data Partner’s databases (by

(5)

comparing updated MSCDM tables to previous versions of the tables). For example, a level 3 data check

would ensure that there are no large, unexpected increases or decreases in diagnosis records over time.

Level 4 data checks examine the occurrence and prevalence of nonsensical diagnoses and examine

variations in care practices across data partners. Level 4 checks are designed to provide more targeted

data analyses and profiling of Data Partner data, and are not necessarily designed to detect and correct

errors. An example level 4 data check would examine the proportion of ovarian cancer diagnoses among

men.

B. DATA PARTNER QUALITY REVIEW AND CHARACTERIZATION REPORT

Following review of the output tables and evaluation of the data checks, MSOC shares with the Data

Partner a summary QA review report containing a list of questions, possible issues, and data

characteristics. If there are data issues, the Data Partner will investigate and provide a written response

in the report either explaining the results or proposing corrective action. All decisions and discussions are

documented in the report in order to develop a knowledge repository about the Data Partner’s data.

Each data characteristic or issue in the report is identified by an Err Code. Err Codes are constructed of

(in this order): the MSCDM table name abbreviation, the data check level (1, 2, 3, or 4), the variable

number (as it appears in MSCDM specifications), and the data check number. For example, the Err Code

“DEM1.3.2” denotes the second level 1 check performed on the variable SEX in the Demographic table.

This check ensures that the variable SEX in the Demographic table is 1 character in length. Using Err

Codes for tracking allows for easy assessment of data trends over time and across Data Partners.

III. PROGRAM PACKAGE

The data quality review and characterization program package contains three sub-packages that query

MSCDM tables. The “Core” quality review sub-package queries the Enrollment, Demographic,

Dispensing, Encounter, Diagnosis, Procedure, Death, and Cause of Death tables. The Laboratory quality

review sub-package queries the Laboratory Result table, and the Vital Signs quality review sub-package

queries the Vital Signs table. All programs are based on MSCDM version 4.0.

A. CORE TABLES QUALITY REVIEW

The Core quality review sub-package is executed first by all Data Partners via the Master SAS Program. A

total of 20 SAS QA programs are included in the sub-package:

• Master SAS Program (00.0_mscdm_data_qa_review_master_file.sas). Selectively executes

programs included in the sub-package in accordance to an MSOC-provided control flow input file

(control_flow.sas7bdat). Requires editing by the Data Partner to identify location of the MSCDM

tables in staging, as well as the location of the Common Components program.

• QA Programs:

o

Enrollment table QA program (01.1_mscdm_data_qa_review-enrollment.sas). Queries the

number of members and records in the Enrollment table, and outputs information on

medical and drug coverage indicators, enrollment start, end, and length.

(6)

o

Demographic table QA program (02.1_mscdm_data_qa_review-demographic.sas). Queries

the number of members and records in the Demographic table, and outputs information on

age, sex, and race.

o

Dispensing table QA program (03.1_mscdm_data_qa_review-dispensing.sas). Queries the

number of members and records in the Dispensing table, and outputs information on

dispensing date, dispensings over time, dispensings per member over time, days supply and

dispensed amount.

o

Encounter table QA program (04.1_mscdm_data_qa_review-encounter.sas). Queries the

number of members, records, encounters, and providers in the Encounter table, and

outputs information on admission and discharge date, encounters over time, encounter

type, length of stay, facility location, admitting source, discharge status and disposition, DRG

and DRG type, and number of encounters per member.

o

Diagnosis table QA program (04.2_mscdm_data_qa_review-diagnosis.sas). Queries the

number of members, records, encounters, and providers in the Diagnosis table, and outputs

information on encounter type, admission date, diagnosis code and type, principal diagnosis

indicators, number of diagnoses per encounter, and number of diagnoses over time.

o

Procedure table QA program (04.3_mscdm_data_qa_review-procedure.sas). Queries the

number of members, records, encounters, and providers in the Procedure table, and

outputs information on encounter type, admission date, procedure code and type, number

of procedures per encounter, and number of procedures over time.

o

Death table QA program (05.1_mscdm_data_qa_review-death.sas). Queries the number of

members and records in the Death table, and outputs information on the source of and

confidence in death information, number of deaths over time, and if the death date has

been imputed.

o

Cause of death table QA program (05.2_mscdm_data_qa_review-causeofdeath.sas).

Queries the number of members and records in the Cause of Death table, and outputs

information on cause of death codes and cause type, and source of and confidence in cause

of death information.

o

Level 1 and 2 checks QA program (99.1_mscdm_data_qa_review-l1_l2.sas). Queries all Core

MSCDM tables to perform level 1 and level 2 checks not performed elsewhere and sets all

level 1 and level 2 flags into one dataset. This program also produces metadata. This

module will always execute if a QA module for any Core tables are executed.

o

Level 4 checks QA program (08.1_mscdm_data_qa_review-level4). Queries all Core MSCDM

tables to perform level 4 checks. Must be run independently of the Master SAS Program.

o

Min-Max Dates program (99.2_mscdm_data_qa_review_minmax_dates.sas). Queries all

Core MSCDM tables and outputs minimum and maximum dates in each, and calculates DP

Min (calculated as the maximum of the Min Dates) and DP Max (calculated as the minimum

of the Max dates).

• Control Flow Program (00.0_mscdm_control_flow.sas). Contains a program that allows selective

and sequential execution of QA modules.

• Standard Macros Program (00.1_mscdm_standard_macros.sas). Contains macros used across all

Core QA programs.

• Standard Formats Program (00.1_mscdm _formats.sas). Contains formats used across all Core QA

programs.

• Log Checker Program (00.3_mscdm_sas_log_checker_directory_cc.sas). Checks program log and

summarizes notes, warnings, and errors in an output PDF file.

(7)

• Signature Request Program (00.4_mscdm_qasignaturerequest.sas). Creates signature files

containing metadata for each MSCDM table.

The Core quality review sub-package also contains three input files:

• Error code crosswalk (flags_xwalk.sas7bdat). Assigns appropriate Err Codes to all checks

performed in the QA programs. See

Appendix A

for a list of Core quality review Err Codes.

• Level 4 codes (level4lookup.sas7bdat). Includes the code lists for conditions of interest included

in Level 4 data checks.

• Control flow (control_flow.sas7bdat). Controls selective and sequential execution of QA

modules.

B. LABORATORY TABLE QUALITY REVIEW

The Laboratory quality review sub-package is executed second and only by Data Partners who have lab

data available. A total of 3 SAS programs are included in the sub-package:

• Lab QA Program (06.1_mscdm_data_qa_review-labs.sas). Queries the number of members and

records in the Laboratory Result table and outputs information on lab tests included, result

units, and available dates (i.e., date of lab vs. order date vs. result date). Many of the checks

included in the program check compliance with MSCDM specifications (e.g., appropriate length,

type, and format) and assess across-variable integrity (e.g., if individual tests have valid

information populated for specimen source and test subtype; if quantitative tests only contain

numeric results).

• Lab Standard Macros (06.1_mscdm_laboratory_macros.sas). Contains macros used in the Lab

QA program.

• Log Checker Program (00.3_mscdm_sas_log_checker_directory_cc.sas). Checks Lab QA program

log and appends notes, warnings, and errors to the output .pdf file generated by the Core QA

program.

The Laboratory quality review sub-package also contains two input files:

- LOINC lookup (loinc_lkp.sas7bdat). Contains a lookup table for specimen source and LOINC

codes for each laboratory test and sub category.

- Procedure lookup (px_lkp.sas7bdat). Includes procedure code list associated with laboratory

tests.

C. VITAL SIGNS TABLE QUALITY REVIEW

The Vital Signs quality review sub-package is executed third and only by Data Partners who have vital

signs data available. A total of 2 SAS programs are included in the sub-package:

• Vital Signs QA Program (07.1_mscdm_data_qa_review-vitals.sas). Queries the number of

members and records in the Vital Signs table and outputs the frequency of height, weight,

diastolic blood pressure, systolic blood pressure, and tobacco use measurements by age group,

sex, and year.

(8)

• Log Checker Program (00.3_mscdm_sas_log_checker_directory_cc.sas). Checks Vital Signs QA

program log and appends notes, warnings, and errors to the output .pdf file generated by the

Core QA and (if applicable) Lab QA program.

IV. PROGRAM EXECUTION

When implementing programs within the MSDD, the MSOC uses a uniform folder structure across Data

Partners to facilitate communications between MSOC and Data Partners and to streamline file

management. Data Partners create a folder named after the quality review package and several

subfolders to organize program inputs and outputs. One of the folders contains output to be sent to

MSOC and another contains intermediate files that remain with the Data Partner, but could be used to

facilitate follow-up queries if necessary.

Table 1 defines the variables that must be initialized by the user to execute the quality review and

characterization program package (i.e., defined by the Data Partner before execution of the programs).

Please note that these values cannot be left blank. Each Data Partner is required to enter user inputs at

the beginning of the applicable data quality program. These inputs are unique to each Data Partner.

Table 1. Master Program Variable Definitions

Label

Field Name

Description

Common Components Path

MSCC

Path to directory containing the Common

Components file (ms_common_components.sas)

Staging MSCDM Path

STAGING

Path to directory containing the MSCDM datasets

pending QA review

V. PROGRAM PACKAGE OUTPUT

Execution of all sections of the data quality review and characterization program package generates up

to 279 output files: 154 Core output tables, 73 Lab output tables, and 21 Vital Signs output tables. In

addition, 15 logs, 13 signature files, 1 lab output summary PDF file, and 1 master output summary PDF

file are generated. See

Appendix B

for a complete list of output files. An example output table for each

sub-package is provided below to demonstrate how output tables are used during data quality review.

A. CORE QUALITY REVIEW OUTPUT EXAMPLE

The output dataset dia_l3_pdx_et.sas examines the frequency of records in the Diagnosis table by

principal diagnosis flag (PDX) and encounter type (ENCTYPE), and helps evaluate compliance with

MSCDM specifications.

Table 2: Example Dia_l3_pdx_et Output

PDX EncType

Count

Percent

AV

100,000

53.3 ED

25,000

13.3

(9)

PDX EncType

Count

Percent

P

IP

1,500

0.8 P

IS

6,000

3.2 S

IP

3,000

1.6 S

IS

12,000

6.4 Per MSCDM specifications, only inpatient and institutional stay encounters (ENCTYPE= ‘IP’ and ‘IS’)

should have PDX values populated. Ambulatory and emergency department visits (ENCTYPE= ‘AV’, ‘OA’,

and ‘ED’) should have blank PDX values. The table above represents a Diagnosis table with compliant

PDX*ENCTYPE values.

In addition to evaluating MSCDM compliance, this table also helps MSOC characterize the data. For

example, the output indicates that only 4.0% of diagnoses are flagged as principal (PDX= ‘P’), 8.0% are

flagged as secondary (PDX= ‘S’), and no diagnoses are flagged as unable to classify (PDX= ‘X’). These

percentages can inform investigator decisions to construct cohorts based on PDX values.

B. LAB QUALITY REVIEW OUTPUT EXAMPLE

The output dataset lab_l2_test_rslttyp_specimen.sas examines the frequency of records in the

Laboratory Result table by test name (MS_TEST_NAME), test subcategory (MS_TEST_SUB_CATEGORY),

specimen source (SPECIMEN_SOURCE), and result type for lab tests with quantitative results.

Table 3: Example lab_l2_test_rslttyp_specimen Output

MS Test

Name

MS Test

Subcategory

Specimen

Source

Result

Type

Number of

Tests

GLUCOSE

FST

SR_PLS

N

400 GLUCOSE

RAN

BLOOD

N

600 HGBA1C

BLOOD

N

500 HGBA1C

BLOOD

M

25 PLATELETS

PLASMA

N

300 PG_QN

BHCG

SERUM

N

200 PG_QN

BHCG

URINE

N

300 PG_QN

HCG

SERUM

N

450 A result type value of ‘N’ indicates a numeric test result and ‘M’ indicates a missing numeric test result.

Since allowable MS_TEST_SUB_CATEGORY and SPECIMEN_SOURCE values are conditional on the test

(e.g., MS_TEST_SUB_CATEGORY should be blank for HGBA1C tests but equal to either ‘FST’ or ‘RAN’ for

GLUCOSE tests), this output table allows MSOC to evaluate compliance with MSCDM specifications. In

addition, result type indicates which quantitative tests have missing result values.

In the example output above, all test name, test subcategory, and specimen source values comply with

the MSCDM. However, there are 25 HGBA1C lab records that have missing results that should be

investigated.

(10)

C. VITAL SIGNS QUALITY REVIEW OUTPUT EXAMPLE

The output dataset vit_l3_num_wt_age_sex_y.sas examines the frequency of weight measurements

taken by age group, sex and year. Given the amount of data included in this table, the example output

below is partially populated and includes information only for 15-18 year old females in 2006 and 2007:

Table 4: Example vit_l3_num_wt_age_sex_y Output

Number of Weight

Year

Age Category

Sex

Count

Percent

Measurements

1 2006

15-18

F

50

0.01

2 2006

15-18

F

42

0.01

3 2006

15-18

F

148

0.01

4 2006

15-18

F

210

0.02

5 2006

15-18

F

2,000

0.20

6 2006

15-18

F

2,200

0.22

1 2007

15-18

F

68

0.01

2 2007

15-18

F

84

0.01

3 2007

15-18

F

3,000

0.30

4 2007

15-18

F

4,200

0.40

5 2007

15-18

F

3,000

0.30

6 2007

15-18

F

3,400

0.30 This table is useful to understand how the number of weight measurements varies by age group, sex,

and year. Unlike the other two example output tables, this output is used for characterization purposes

only (i.e., it is not evaluating compliance with the MSCDM or looking for errors).

In the table above, there are 2,200 15-18 year old female members with six weight measurements in

2006, compared to 50 female members with only one weight measurement in the same year. In 2007,

there are 3,400 15-18 year old female members with six weight measurements, compared to 68 female

members with only one weight measurement in the same year.

(11)

VI. APPENDIX A: LIST OF ALL QA ERR CODES

Full Err Code Description of Error

ALL2.1.1 PatID variable has inconsistent lengths across tables ENR_DEM2.1.10 At least one PatID in the ENR table is not in the DEM table ENR_DIS2.1.11 At least one PatID in the ENR table is not in the DIS table ENR_ENC2.1.12 At least one PatID in the ENR table is not in the ENC table ENR_DIA2.1.13 At least one PatID in the ENR table is not in the DIA table ENR_PRO2.1.14 At least one PatID in the ENR table is not in the PRO table ENR1.0.0 Table does not exist

ENR1.1.1 PatID variable is not character type ENR1.1.2 PatID variable has missing values

ENR1.1.3 PatID variable has non-missing values that are not left-justified ENR1.1.4 PatID variable contains special characters

ENR1.2.1 Enr_Start variable is not SAS date value of numeric data type ENR1.2.2 Enr_Start variable is not of length 4

ENR1.2.3 Enr_Start variable has missing values

ENR1.3.1 Enr_End variable is not SAS date value of numeric data type ENR1.3.2 Enr_End variable is not of length 4

ENR1.3.3 Enr_End variable has missing values

ENR1.3.6 Enr_End variable has values after the maximum dispensing

dates and utilization

ENR1.4.1 MedCov variable is not character type

ENR1.4.2 MedCov variable is not exactly 1 character in length ENR1.4.3 MedCov variable has missing values

ENR1.4.4 MedCov variable has values other than "Y", "N", or "U" ENR1.5.1 DrugCov variable is not character type

ENR1.5.2 DrugCov variable is not exactly 1 character in length ENR1.5.3 DrugCov variable has missing values

ENR1.5.4 DrugCov variable has values other than "Y", "N", or "U" ENR1.6.1 Chart variable is not character type

ENR1.6.2 Chart variable is not exactly 1 character in length ENR1.6.3 Chart variable has missing values

ENR1.6.4 Chart variable has values other than "Y" or "N"

ENR2.0.0 Record(s) have duplicate key value combinations (with respect to table definition)

ENR2.2.1 Enr_Start is after Enr_End

ENR2.2.3 Enr_Start occurs more than once in the file in combination with PatID, MedCov, and DrugCov

(12)

ENR2.3.4 Enr_End occurs more than once in the file in combination with PatID, MedCov, and DrugCov

ENR2.6.1 At least one PatID has records with inconsistent MedCov and DrugCov indicators with the same year/month/day of enrollment

ENR3.0.1 Significant change in number of records between ETLs ENR3.1.1 Problem with number of unique PatIDs

ENR3.2.1 Problem with distribution of Enr_Start variable ENR3.3.4 Problem with distribution of Enr_End variable

ENR3.4.1 Problem with distribution of enrollment months per patient for patients with MedCov = "Y"

ENR3.4.2 Problem with distribution of MedCov indicators

ENR3.4.3 Problem with distribution of MedCov indicators per year within the ETL ENR3.4.4 Problem with distribution of MedCov indicators per year-month within the

ETL

ENR3.4.5 Problem with distribution of MedCov indicators per year across ETLs ENR3.4.6 Problem with distribution of MedCov indicators per year-month across ETLs ENR3.5.1 Problem with distribution of enrollment months per patient for patients with

DrugCov = "Y"

ENR3.5.2 Problem with distribution of DrugCov indicators

ENR3.5.3 Problem with distribution of DrugCov indicators per year within the ETL ENR3.5.4 Problem with distribution of DrugCov indicators per year-month within the

ETL

ENR3.5.5 Problem with distribution of DrugCov indicators per year across ETLs ENR3.5.6 Problem with distribution of DrugCov indicators per year-month across ETLs ENR3.6.1 Problem with distribution of enrollment months per patient for patients with

MedCov = "Y" and DrugCov = "Y"

ENR3.6.2 Problem with distribution of MedCov*DrugCov indicators

ENR3.6.3 Problem with distribution of MedCov*DrugCov indicators per year within the ETL

ENR3.6.4 Problem with distribution of MedCov*DrugCov indicators per year-month within the ETL

ENR3.6.5 Problem with distribution of MedCov*DrugCov indicators per year across ETLs

ENR3.6.6 Problem with distribution of MedCov*DrugCov indicators per year-month across ETLs

ENR3.6.7 Problem with distribution of total number of patients with MedCov = "Y" and DrugCov = "Y" and at least 1 overlapping enrollment span

ENR3.6.8 Problem with distribution of total number of overlapping enrollment spans for all patients with MedCov = "Y" and DrugCov = "Y"

(13)

DEM1.0.0 Table does not exist

DEM1.1.1 PatID variable is not character type DEM1.1.2 PatID variable has missing values

DEM1.1.3 PatID variable has non-missing values that are not left-justified DEM1.1.4 PatID variable contains special characters

DEM1.2.1 Birth_Date variable is not SAS date value of numeric data type DEM1.2.2 Birth_Date variable is not of length 4

DEM1.2.3 Birth_Date variable has missing values

DEM1.2.4 Birth_Date variable has values before 1/1/1885 DEM1.3.1 Sex variable is not character type

DEM1.3.2 Sex variable is not exactly 1 character in length DEM1.3.3 Sex variable has missing values

DEM1.3.4 Sex has values other than "F", "M", "A", or "U" DEM1.4.1 Hispanic variable is not character type

DEM1.4.2 Hispanic variable is not exactly 1 character in length DEM1.4.3 Hispanic variable has missing values

DEM1.4.4 Hispanic variable has values other than "Y", "N", or "U" DEM1.5.1 Race variable is not character type

DEM1.5.2 Race variable is not exactly 1 character in length DEM1.5.3 Race variable has missing values

DEM1.5.4 Race variable has values other than "0", "1", "2", "3", "4", or "5" DEM1.6.1 ZIP variable is not character type

DEM1.6.2 ZIP variable is not exactly 5 characters in length DEM1.6.3 ZIP variable has missing values

DEM1.7.1 ZIP_Date variable is not SAS date value of numeric data type DEM1.7.2 ZIP_Date variable is not length of 4

DEM1.7.3 ZIP_Date variable has missing values

DEM1.7.4 ZIP_Date variable has values before MinDate DEM1.7.5 ZIP_Date variable has values after MaxDate

DEM2.0.0 Record(s) have duplicate key value combinations (with respect to table definition)

DEM3.0.1 Significant change in number of records between ETLs DEM3.1.1 Problem with number of unique PatIDs

DEM3.2.2 Problem with distribution of age

DEM3.2.3 Problem with distribution of age groups (0-1 yrs, 2-4 yrs, 5-9 yrs, 10-14 yrs, 15-18 yrs, 19-21 yrs, 22-44 yrs, 45-64 yrs, 65-74 yrs, 75+ yrs)

DEM3.3.1 Problem with distribution of Sex variable DEM3.4.1 Problem with distribution of Race variable DEM3.5.1 Problem with distribution of Hispanic variable

(14)

DIS1.0.0 Table does not exist

DIS1.1.1 PatID variable is not character type DIS1.1.2 PatID variable has missing values

DIS1.1.3 PatID variable has non-missing values that are not left-justified DIS1.1.4 PatID variable contains special characters

DIS1.2.1 RxDate variable is not a SAS date value of numeric data type DIS1.2.2 RxDate variable is not of length 4

DIS1.2.3 RxDate variable has missing values DIS1.3.1 NDC variable is not character data type

DIS1.3.2 NDC variable is not exactly 11 characters in length DIS1.3.3 NDC variable has missing values

DIS1.3.4 NDC variable contains special characters or non-digits DIS1.4.1 RxSup variable is not numeric type

DIS1.4.2 RxSup variable is not of length 4

DIS1.4.3 RxSup variable has negative, missing, or zero values

DIS1.4.4 RxSup variable has a format length (no format length should be specified) DIS1.5.1 RxAmt variable is not numeric type

DIS1.5.2 RxAmt variable is not of length 4

DIS1.5.3 RxAmt variable has negative, missing or zero values

DIS1.5.4 RxAmt variable has a format length (no format length should be specified) DIS2.0.0 Record(s) have duplicate key value combinations (with respect to table

definition)

DIS3.0.1 Significant change in number of records between ETLs DIS3.1.1 Problem with number of unique PatIDs

DIS3.2.1 Problem with distribution of RxDate (i.e. total number of dispensings per year) within the ETL

DIS3.2.2 Problem with distribution of RxDate (i.e. total number of dispensings per year-month) within the ETL

DIS3.2.3 Significant change in number of records per RxDate (year) across ETLs DIS3.2.4 Significant change in number of records per RxDate (year-month) across ETLs DIS3.2.5 Problem with distribution of RxDate (overall) within the ETL

DIS3.2.6 Problem with distribution of RxDate (overall) across ETLs DIS3.4.1 Problem with distribution of RxSup

DIS3.5.1 Problem with distribution of RxAmt

DIS3.5.2 Problem with average number of prescriptions per PatID by year ENR_ENC2.1.3 At least one PatID in the ENC table is not in the ENR table ENC_DIA_PRO2.2.1 EncounterID variable has inconsistent lengths across tables

(15)

ENC_DIA_PRO2.2.6 ENC table has EncounterID values which are not found in the DIA and PRO tables

ENC_DIA_PRO2.5.1 Provider variable has inconsistent lengths across tables ENC_DIA2.2.4 ENC table has EncounterID values not found in the DIA table ENC_PRO2.2.5 ENC table has EncounterID values not found in the PRO table ENC1.0.0 Table does not exist

ENC1.1.1 PatID variable is not character type ENC1.1.2 PatID variable has missing values

ENC1.1.3 PatID variable has non-missing values that are not left-justified ENC1.1.4 PatID variable contains special characters

ENC1.2.1 EncounterID variable is not character type ENC1.2.2 EncounterID variable has missing values

ENC1.2.3 EncounterID variable has non-missing values that are not left-justified ENC1.2.4 EncounterID variable contains special characters

ENC1.3.1 ADate variable is not SAS date value of numeric data type ENC1.3.2 ADate variable is not of length 4

ENC1.3.3 ADate variable has missing values

ENC1.4.1 DDate variable is not SAS date value of numeric data type ENC1.4.2 DDate variable is not of length 4

ENC1.5.1 Provider variable is not character type ENC1.5.2 Provider

of the table (part of the definition of the table) variable has missing values and should be populated for all records ENC1.5.3 Provider variable has non-missing values that are not left-justified

ENC1.5.4 Provider variable contains special characters ENC1.6.1 Facility_Location variable is not character type

ENC1.6.2 Facility_Location variable is not exactly 3 characters in length ENC1.6.3 Facility_Location variable contains non-digits

ENC1.6.4 Facility_Location has missing values

ENC1.6.5 Facility_Location variable has non-missing values that are not left-justified ENC1.7.1 EncType variable is not character type

ENC1.7.2 EncType variable is not exactly 2 characters in length ENC1.7.3 EncType variable has missing values

ENC1.7.4 EncType variable has values other than "IP", "IS", "ED", "AV", or "OA" ENC1.8.1 Facility_Code variable is not character type

ENC1.8.2 Facility_Code variable contains special characters

ENC1.8.3 Facility_Code variable has non-missing values that are not left-justified ENC1.8.4 Facility_Code has missing values

(16)

ENC1.9.2 Discharge_Disposition variable is not exactly 1 character in length

ENC1.9.3 Discharge_Disposition variable has values other than "A", "E", "U", or missing ENC1.10.1 Discharge_Status variable is not character data type

ENC1.10.2 Discharge_Status variable is not exactly 2 characters in length

ENC1.10.3 Discharge_Status variable has values other than "AF", "AL", "AM", "AW", "EX", "HH", "HS", "HO", "IP", "NH", "OT", "RS", "RH", "SH", "SN", “UN”, or missing

ENC1.11.1 DRG variable is not character type

ENC1.11.2 DRG variable is not exactly 3 characters in length ENC1.11.3 DRG variable contains non-digits

ENC1.12.1 DRG_Type variable is not character type

ENC1.12.2 DRG_Type variable is not exactly 1 character in length

ENC1.12.3 DRG_Type variable contains values other than "1", "2", or missing ENC1.13.1 Admitting_Source variable is not character type

ENC1.13.2 Admitting_Source variable is not exactly 2 characters in length

ENC1.13.3 Admitting_Source variable contains values other than "AV", "ED", "AF", "AL", "HH", "HS", "HO", "IP", "NH", "OT", "RS", "RH", "SN", "UN", or missing ENC2.0.0 Record(s) have duplicate key value combinations (with respect to table

definition)

ENC2.2.1 EncounterID values occur more than once

ENC2.2.7 EncounterID variable does not contain (in this order) PatID, ADate, Provider, EncType

ENC2.3.1 ADate is after DDate (for IP and IS only)

ENC2.3.2 ADate and DDate variables have values before DP_MinDate ENC2.4.1 DDate variable is missing for EncType value "IP"

ENC2.4.2 DDate variable is populated for records with EncType values other than "IP" or "IS"

ENC2.9.1 Discharge_Disposition variable is missing for EncType values "IP" or "IS" ENC2.9.2 Discharge_Disposition variable is populated for records with EncType values

other than "IP" or "IS"

ENC2.10.1 Discharge_Status variable is missing for EncType values "IP" or "IS"

ENC2.10.2 Discharge_Status variable is populated for records with EncType values other than "IP" or "IS"

ENC2.11.1 DRG variable is missing for EncType values "IP" or "IS"

ENC2.11.2 DRG variable is populated for records with EncType values other than "IP", "IS", or "ED"

ENC2.12.1 DRG_Type variable is missing for EncType values "IP" or "IS"

ENC2.12.2 DRG_Type variable is populated for records with EncType values other than "IP", "IS", or "ED"

(17)

ENC2.13.2 Admitting_Source variable is

other than "IP" or "IS" populated for records with EncType values ENC3.0.1 Significant change in number of records between ETLs

ENC3.1.1 Problem with number of unique PatIDs ENC3.2.1 Problem with number of unique EncounterIDs

ENC3.3.1 Problem with distribution of ADate (i.e. total number of records per year) within the ETL

ENC3.3.2 Problem with distribution of ADate (i.e. total number of records per

month) within the ETL

year-ENC3.3.3 Significant change in number of records per ADate (year) across ETLs ENC3.3.4 Significant change in number of records per ADate (year-month) across ETLs ENC3.3.5 Problem with distribution of ADate (overall) within the ETL

ENC3.3.6 Problem with distribution of ADate (overall) across ETLs

ENC3.4.1 Problem with distribution of DDate (i.e. total number of records per year) within the ETL

ENC3.4.5 Problem with distribution of DDate (i.e. total number of records per

month) within the ETL

year-ENC3.4.6 Significant change in number of records per DDate (year) across ETLs ENC3.4.7 Significant change in number of records per DDate (year-month) across ETLs ENC3.4.8 Problem with distribution of DDate (overall) within the ETL

ENC3.4.9 Problem with distribution of DDate (overall) across ETLs

ENC3.4.10 Problem with distribution of DDate variable by EncType per year ENC3.4.11 Problem with distribution of DDate variable by EncType per year-month ENC3.4.12 Problem with distribution of length of stay (DDate-ADate + 1) by EncType ENC3.4.13 Problem with distribution of length of stay (DDate-ADate + 1) by EncType per

year

ENC3.5.1 Problem with number of unique Provider values ENC3.7.4 Problem with distribution of number

EncType of encounters per member by year and ENC3.7.5 Problem with distribution of number of encounters per member by

year-month and EncType

ENC3.7.6 Problem with distribution of number of records by EncType per year within the ETL

ENC3.7.7 Problem with distribution of number of records by EncType per year-month within the ETL

ENC3.7.8 Significant change in number of records by EncType per year across ETLs ENC3.7.9 Significant change in number

ETLs of records by EncType per year-month across ENC3.9.1 Problem with distribution of Discharge_Disposition variable (overall)

(18)

ENC3.9.2 Problem with distribution of Discharge_Disposition variable (by EncType) ENC3.10.1 Problem with distribution of Discharge_Status variable (overall)

ENC3.10.2 Problem with distribution of Discharge_Status variable (by EncType) ENC3.11.1 Problem with distribution of DRG variable

ENC3.12.1 Problem with distribution of DRG_Type variable (overall)

ENC3.12.2 Problem with distribution of DRG_Type variable (by year to confirm switch from old to new system)

ENC3.12.3 Problem with distribution of DRG_Type variable (by EncType) ENC3.13.1 Problem with distribution of Admitting_Source variable (overall) ENC3.13.2 Problem with distribution of Admitting_Source variable (by EncType) ENR_DIA2.1.4 At least one PatID in the DIA table is not in the ENR table

ENC_DIA2.2.2 DIA table has EncounterID values not found in the ENC table DIA1.0.0 Table does not exist

DIA1.1.1 PatID variable is not character type DIA1.1.2 PatID variable has missing values

DIA1.1.3 PatID variable has non-missing values that are not left-justified DIA1.1.4 PatID variable contains special characters

DIA1.2.1 EncounterID variable is not character type DIA1.2.2 EncounterID variable has missing values

DIA1.2.3 EncounterID variable has non-missing values that are not left-justified DIA1.2.4 EncounterID variable contains special characters

DIA1.3.1 ADate variable is not SAS date value of numeric data type DIA1.3.2 ADate variable is not of length 4

DIA1.3.3 ADate variable has missing values DIA1.4.1 Provider variable is not character type

DIA1.4.2 Provider variable has missing values and should be populated for all records of the table (part of the definition of the table)

DIA1.4.3 Provider variable has non-missing values that are not left-justified DIA1.4.4 Provider variable contains special characters

DIA1.5.1 EncType variable is not character type

DIA1.5.2 EncType variable is not exactly 2 characters in length

DIA1.5.3 EncType variable has missing values and should be populated for all records of the table (part of the definition of the table)

DIA1.5.4 EncType variable has values other than "IP", "IS", "ED", "AV", or "OA" DIA1.6.1 DX variable Is not character type

DIA1.6.2 DX variable is not exactly 18 characters in length

DIA1.6.3 DX variable has missing values and should be populated for all records of the table (part of the definition of the table)

(19)

DIA1.6.5 Problem with the length of DX values DIA1.7.1 Dx_Codetype variable is not character type

DIA1.7.2 Dx_Codetype variable is not exactly 2 characters in length

DIA1.7.3 Dx_Codetype variable contains values other than "09", "10", "11", "SM", or "OT"

DIA1.8.1 OrigDX variable is not character type DIA1.9.1 PDX variable is not character type

DIA1.9.2 PDX variable is not exactly 1 character in length

DIA1.9.3 PDX variable contains values other than "P", "S", "X", or missing DIA2.0.0 Record(s) have duplicate key value combinations (with respect to table

definition)

DIA2.2.6 EncounterID variable does not contain (in this order) PatID, ADate, Provider, EncType

DIA2.9.2 PDX variable is populated for EncType values other than "IP" or "IS" DIA2.9.1 PDX variable has missing values for EncType values "IP" or "IS" DIA3.0.1 Significant change in number of records between ETLs DIA3.1.1 Problem with number of unique PatIDs

DIA3.2.1 Problem with number of unique EncounterIDs

DIA3.3.1 Problem with distribution of ADate (i.e. total number of records per year) within the ETL

DIA3.3.2 Problem with distribution of ADate (i.e. total number of records per year-month) within the ETL

DIA3.3.3 Significant change in number of records per ADate (year) across ETLs DIA3.3.4 Significant change in number of records per ADate (year-month) across ETLs DIA3.3.5 Problem with distribution of ADate (overall) within the ETL

DIA3.3.6 Problem with distribution of ADate (overall) across ETLs DIA3.4.1 Problem with number of unique Provider values

DIA3.5.1 Problem with distribution of number of records by EncType per year within the ETL

DIA3.5.2 Problem with distribution of number of records by EncType per year-month within the ETL

DIA3.5.3 Significant change in number of records by EncType per year across ETLs DIA3.5.4 Significant change in number

ETLs of records by EncType per year-month across DIA3.5.5 Problem with distribution of number of unique diagnoses per encounter visit

(overall)

DIA3.6.1 Problem with distribution of DX variable

DIA3.6.2 DX variable is not consistent with Dx_Codetype variable DIA3.7.1 Problem with distribution of Dx_Codetype (by year) DIA3.7.2 Problem with distribution of Dx_Codetype (by EncType)

(20)

DIA3.9.1 Problem with distribution of PDX variable. DIA3.9.2 Problem with distribution of PDX*EncType

ENR_PRO2.1.5 At least one PatID in the PRO table is not in the ENR table ENC_PRO2.2.3 PRO table has EncounterID values not found in the ENC table PRO1.0.0 Table does not exist

PRO1.1.1 PatID variable is not character type PRO1.1.2 PatID variable has missing values

PRO1.1.3 PatID variable has non-missing values that are not left-justified PRO1.1.4 PatID variable contains special characters

PRO1.2.1 EncounterID variable is not character type PRO1.2.2 EncounterID variable has missing values

PRO1.2.3 EncounterID variable has non-missing values that are not left-justified PRO1.2.4 EncounterID variable contains special characters

PRO1.3.1 ADate variable is not SAS date value of numeric data type PRO1.3.2 ADate variable is not of length 4

PRO1.3.3 ADate variable has missing values PRO1.4.1 Provider variable is not character type

PRO1.4.2 Provider variable has missing values and should be

of the table (part of the definition of the table) populated for all records PRO1.4.3 Provider variable has non-missing values that are not left-justified

PRO1.4.4 Provider variable contains special characters PRO1.5.1 EncType variable is not character type

PRO1.5.2 EncType variable is not exactly 2 characters in length PRO1.5.3 EncType variable has missing values

PRO1.5.4 EncType variable has values other than "IP", "IS", "ED", "AV", or "OA" PRO1.6.1 PX variable Is not character type

PRO1.6.2 PX variable is not exactly 11 characters in length PRO1.6.3 PX variable has missing values

PRO1.6.4 PX variable contains special characters other than a decimal point PRO1.6.5 Problem with the length of PX values

PRO1.7.1 PX_Codetype variable Is not character type

PRO1.7.2 PX_Codetype variable is not exactly 2 characters in length PRO1.7.3 PX_Codetype variable has missing values

PRO1.7.4 PX_Codetype variable contains values other than "09", "10", "11", "C2", "C3", "C4", "H3", "HC", "LC", "LO", "ND", "OT", or "RE"

PRO1.8.1 OrigPX variable is not character type

PRO2.0.0 Record(s) have duplicate key value combinations (with respect to table definition)

PRO2.2.1 EncounterID variable does not contain (in this order) PatID, ADate, Provider, EncType

(21)

PRO3.0.1 Significant change in number of records between ETLs PRO3.1.1 Problem with number of unique PatIDs

PRO3.2.1 Problem with number of unique EncounterIDs

PRO3.3.1 Problem with distribution of ADate (i.e. total number of records per year) within the ETL

PRO3.3.2 Problem with distribution of ADate (i.e. total number of records per year-month) within the ETL

PRO3.3.3 Significant change in number of records per ADate (year) across ETLs PRO3.3.4 Significant change in number of records per ADate (year-month) across ETLs PRO3.3.5 Problem with distribution of ADate (overall) within the ETL

PRO3.3.6 Problem with distribution of ADate (overall) across ETLs PRO3.4.1 Problem with number of unique Provider values

PRO3.5.1 Problem with distribution of number of records by EncType per year within the ETL

PRO3.5.2 Problem with distribution of number of records by EncType per year-month within the ETL

PRO3.5.3 Significant change in number of records by EncType per year across ETLs PRO3.5.4 Significant change in number of records by EncType per year-month across

ETLs

PRO3.5.5 Problem with distribution of number of unique procedures per encounter visit (overall)

PRO3.6.1 Problem with distribution of PX variable

PRO3.6.2 PX variable is not consistent with PX_Codetype variable PRO3.7.1 Problem with distribution of PX_Codetype (year) PRO3.7.2 Problem with distribution of PX_Codetype (by EncType) ENR_DTH2.1.6 At least one PatID in the DTH table is not in the ENR table

DTH_COD2.1.1 At least one PatID in the DTH table is not in the COD table (if both tables exist)

DTH1.1.1 PatID variable is not character type DTH1.1.2 PatID variable has missing values

DTH1.1.3 PatID variable has non-missing values that are not left-justified DTH1.1.4 PatID variable contains special characters

DTH1.2.1 DeathDt variable is not SAS date value of numeric data type DTH1.2.2 DeathDt variable is not of length 4

DTH1.2.3 DeathDt variable has missing values

DTH1.2.4 DeathDt variable has values before 1/1/1885 DTH1.3.1 DtImpute variable is not character type

DTH1.3.2 DtImpute variable is not exactly 1 character in length DTH1.3.3 DtImpute variable has missing values

(22)

DTH1.4.1 Source variable is not character type

DTH1.4.2 Source variable is not exactly 1 character in length DTH1.4.3 Source variable has missing values

DTH1.4.4 Source variable has values other than "L", "N", "S", or "T" DTH1.5.1 Confidence variable is not character type

DTH1.5.2 Confidence variable is not exactly 1 character in length DTH1.5.3 Confidence variable has missing values

DTH1.5.4 Confidence variable has values other than "E", "F", or "P"

DTH2.0.0 Record(s) have duplicate key value combinations (with respect to table definition)

DTH3.0.1 Significant change in number of records between ETLs DTH3.1.1 Problem with number of unique PatIDs

DTH3.2.1 Problem with distribution of DeathDt variable by year DTH3.2.2 Problem with distribution of DeathDt variable by year-month DTH3.3.1 Problem with distribution of DtImpute

DTH3.4.1 Problem with distribution of Source DTH3.5.1 Problem with distribution of Confidence

ENR_COD2.1.7 At least one PatID in the COD table is not in the ENR table DTH_COD2.1.2 At least one PatID in

exist) the COD table is not in the DTH table (if both tables COD1.1.1 PatID variable is not character type

COD1.1.2 PatID variable has missing values

COD1.1.3 PatID variable has non-missing values that are not left-justified COD1.1.4 PatID variable contains special characters

COD1.2.1 COD variable is not character type COD1.2.2 COD variable has missing values

COD1.2.3 COD variable is not exactly 8 characters in length

COD1.2.6 COD variable has non-missing values that are not left-justified COD1.2.7 Problem with the length of COD values

COD1.3.1 CodeType variable is not character type

COD1.3.2 CodeType variable is not exactly 2 characters in length COD1.3.3 CodeType variable has missing values

COD1.3.4 CodeType variable has values other than "09" or "10"

COD1.3.5 CodeType variable has non-missing values that are not left-justified COD1.4.1 CauseType variable is not character type

COD1.4.2 CauseType variable is not exactly 1 character in length COD1.4.3 CauseType variable has missing values

COD1.4.4 CauseType variable has values other than "C", "I", "O", or "U" COD1.5.1 Source variable is not character type

(23)

COD1.5.3 Source variable has missing values

COD1.5.4 Source variable has values other than "L", "N", "S", or "T" COD1.6.1 Confidence variable is not character type

COD1.6.2 Confidence variable is not exactly 1 character in length COD1.6.3 Confidence variable has missing values

COD1.6.4 Confidence variable has values other than "E", "F", or "P"

COD2.0.0 Record(s) have duplicate key value combinations (with respect to table definition)

COD3.0.1 Significant change in number of records between ETLs COD3.1.1 Problem with number of unique PatIDs

COD3.2.1 Problem with distribution of COD variable

COD3.2.2 COD variable is not consistent with CodeType variable COD3.4.1 Problem with distribution of CauseType

COD3.5.1 Problem with distribution of Source COD3.6.1 Problem with distribution of Confidence

DIA4.6.1 Problem with number of ovarian cancer encounters (per year-month) within ETL

DIA4.6.2 Problem with number of ovarian cancer encounters (overall) within ETL DIA4.6.3 Problem with number of ovarian cancer encounters by sex (per year-month)

within ETL

DIA4.6.4 Problem with number of ovarian cancer encounters by sex (overall) within ETL

DIA4.6.5 Significant change in number of ovarian cancer encounters (per year-month) across ETLs

DIA4.6.6 Significant change in number of ovarian cancer encounters (overall) across ETLs

DIA4.6.7 Significant change in number of ovarian cancer encounters by sex (per year-month) across ETLs

DIA4.6.8 Significant change in number of ovarian cancer encounters by sex (overall) across ETLs

DIA4.6.9 Problem with number of prostate cancer encounters (per year-month) within ETL

DIA4.6.10 Problem with number of prostate cancer encounters (overall) within ETL DIA4.6.11 Problem with number of prostate cancer encounters by sex (per year-month)

within ETL

DIA4.6.12 Problem with number of prostate cancer encounters by sex (overall) within ETL

DIA4.6.13 Significant change in number of prostate cancer encounters (per year-month) across ETLs

DIA4.6.14 Significant change in number of prostate cancer encounters (overall) across ETLs

(24)

DIA4.6.15 Significant change in number

month) across ETLs of prostate cancer encounters by sex (per year-DIA4.6.16 Significant change in number

across ETLs of prostate cancer encounters by sex (overall) DIA4.6.17 Problem with number of pregnancy encounters (per year-month) within ETL DIA4.6.18 Problem with number of pregnancy encounters (overall) within ETL

DIA4.6.19 Problem with number of pregnancy encounters by sex (per

within ETL year-month)

DIA4.6.20 Problem with number of pregnancy encounters by sex (overall) within ETL DIA4.6.21 Significant change in number

across ETLs of pregnancy encounters (per year-month) DIA4.6.22 Significant change in number of pregnancy encounters (overall) across ETLs DIA4.6.23 Significant change in number

month) across ETLs of pregnancy encounters by sex (per year-DIA4.6.24 Significant change in number

ETLs of pregnancy encounters by sex (overall) across ENC4.13.1 Problem with ED to IP encounter rates (per year-month) within ETL

ENC4.13.2 Problem with ED to IP encounter rates (overall) within ETL

ENC4.13.3 Significant change in ED to IP encounter rates (per year-month) across ETLs ENC4.13.4 Significant change in ED to IP encounter rates (overall) across ETLs

PRO4.6.1 Problem with number of hysterectomy

ETL encounters (per year-month) within

PRO4.6.2 Problem with number of hysterectomy encounters (overall) within ETL PRO4.6.3 Problem with number of hysterectomy encounters by sex (per year-month)

within ETL

PRO4.6.4 Problem with number of hysterectomy encounters by sex (overall) within ETL PRO4.6.5 Significant change in number

across ETLs of hysterectomy encounters (per year-month) PRO4.6.6 Significant change in number

ETLs of hysterectomy encounters (overall) across PRO4.6.7 Significant change in number

month) across ETLs of hysterectomy encounters by sex (per year-PRO4.6.8 Significant change in number

across ETLs of hysterectomy encounters by sex (overall) LAB1.0.0 Table does not exist

LAB1.1.1 PatID variable is not character type

LAB1.2.1 MS_Test_Name variable is not character type

LAB1.2.2 MS_Test_Name variable is not exactly 10 characters in length LAB1.2.3 MS_Test_Name variable has missing values

(25)

LAB1.2.4 MS_Test_Name variable has values other than "ALP", "ALT", "ANC", "BILI_TOT", "CK", "CK_MB", "CK_MBI", "CREATININE", "D_DIMER_QL", "D_DIMER_QN", "GLUCOSE", "HGB", "HGBA1C", "INF_A", "INF_AB", "INF_B", "INF_NS", "INR", "LIPASE", "PG_QL", "PG_QN", "PLATELETS", "TROP_I", "TROP_T_QL", or "TROP_T_QN"

LAB1.2.5 MS_Test_Name does not have value "ALP" on at least one record LAB1.2.6 MS_Test_Name does not have value "ALT" on at least one record LAB1.2.7 MS_Test_Name does not have value "ANC" on at least one record LAB1.2.8 MS_Test_Name does not have value "BILI_TOT" on at least one record LAB1.2.9 MS_Test_Name does not have value "CK" on at least one record LAB1.2.10 MS_Test_Name does not have value "CK_MB" on at least one record LAB1.2.11 MS_Test_Name does not have value "CK_MBI" on at least one record LAB1.2.12 MS_Test_Name does not have value "CREATININE" on at least one record LAB1.2.13 MS_Test_Name does not have value "D_DIMER_QL" on at least one record LAB1.2.14 MS_Test_Name does not have value "D_DIMER_QN" on at least one record LAB1.2.15 MS_Test_Name does not have value "GLUCOSE" on at least one record LAB1.2.16 MS_Test_Name does not have value "HGB" on at least one record LAB1.2.17 MS_Test_Name does not have value "HGBA1C" on at least one record LAB1.2.18 MS_Test_Name does not have value "INF_A" on at least one record LAB1.2.19 MS_Test_Name does not have value "INF_AB" on at least one record LAB1.2.20 MS_Test_Name does not have value "INF_B" on at least one record LAB1.2.21 MS_Test_Name does not have value "INF_NS" on at least one record LAB1.2.22 MS_Test_Name does not have value "INR" on at least one record LAB1.2.23 MS_Test_Name does not have value "LIPASE" on at least one record LAB1.2.24 MS_Test_Name does not have value "PG_QL" on at least one record LAB1.2.25 MS_Test_Name does not have value "PG_QN" on at least one record LAB1.2.26 MS_Test_Name does not have value "PLATELETS" on at least one record LAB1.2.27 MS_Test_Name does not have value "TROP_I" on at least one record LAB1.2.28 MS_Test_Name does not have value "TROP_T_QL" on at least one record LAB1.2.29 MS_Test_Name does not have value "TROP_T_QN" on at least one record LAB1.3.1 MS_Test_Sub_Category variable is not character type

LAB1.3.2 MS_Test_Sub_Category variable is not exactly 6 characters in length LAB1.3.3 MS_Test_Sub_Category variable has values other than "BHCG", "DDU",

"EIA", "FEU", "FST", "HCG", "IF", "NS", "PCR", "RAN", "VTC", or missing LAB1.3.4 MS_Test_Sub_Category variable has non-missing values that are not

left-justified

(26)

LAB1.4.2 Specimen_Source variable is not exactly 6 characters in length

LAB1.4.3 Specimen_Source variable has values other than "BAL", "BALBX", "BLOOD", "CSF", "NPH", "NPWASH", "NS", "NSWAB", "NWASH", "OTHER", "PLASMA", "PPP", "SERUM", "SPUTUM", "SR_PLS", "THRT", "UNK" or "URINE"

LAB1.4.4 Specimen_Source variable has non-missing values that are not left-justified LAB1.4.5 Specimen_Source variable has missing values

LAB1.5.1 LOINC variable is not character type

LAB1.5.2 LOINC variable is not exactly 10 characters in length

LAB1.5.3 LOINC variable has non-missing values that are not left-justified LAB1.5.4 LOINC variable has missing values

LAB1.5.5 First character of LOINC variable is a zero

LAB1.5.6 Second-to-last character of LOINC variable is not a hyphen LAB1.5.7 Last character of LOINC variable is not a number 0-9 LAB1.7.1 Stat variable is not character type

LAB1.7.2 Stat variable is not exactly 1 character in length LAB1.7.3 Stat variable has missing values

LAB1.7.4 Stat variable has values other than "E", "R", "S", or "U" LAB1.8.1 Pt_Loc variable is not character type

LAB1.8.2 Pt_Loc variable is not exactly 1 character in length LAB1.8.3 Pt_Loc variable has missing values

LAB1.8.4 Pt_Loc variable has values other than "E", "H", "I", "O", or "U" LAB1.9.1 Result_Loc variable is not character type

LAB1.9.2 Result_Loc variable is not exactly 1 character in length LAB1.9.3 Result_Loc variable has missing values

LAB1.9.4 Result_Loc variable has values other than "L" or "P" LAB1.10.1 LOCAL_CD variable is not character type

LAB1.11.1 BATTERY_CD variable is not character type LAB1.12.1 PX variable Is not character type

LAB1.13.1 PX_Codetype variable Is not character type

LAB1.13.2 PX_Codetype variable is not exactly 2 characters in length LAB1.13.3 PX_Codetype

"C4", "H3", "Hvariable contains values other than "09", "10", "11", "C2", "C3", C", "LO", "ND", "OT", "RE", or missing LAB1.14.1 Order_dt variable is not SAS date value of numeric data type

LAB1.14.2 Order_dt variable is not of length 4 LAB1.14.3 Order_dt variable has missing values

LAB1.15.1 Lab_dt variable is not SAS date value of numeric data type LAB1.15.2 Lab_dt variable is not of length 4

(27)

LAB1.16.1 Lab_tm variable is not SAS time value of numeric data type LAB1.16.2 Lab_tm variable is not of length 4

LAB1.16.3 Lab_tm variable has missing values

LAB1.17.1 Result_dt variable is not SAS date value of numeric data type LAB1.17.2 Result_dt variable is not of length 4

LAB1.17.3 Result_dt variable has missing values

LAB1.18.1 Result_tm variable is not SAS time value of numeric data type LAB1.18.2 Result_tm variable is not of length 4

LAB1.18.3 Result_tm variable has missing values LAB1.19.1 Orig_Result variable Is not character type

LAB1.19.2 Orig_Result variable is not exactly 8 characters in length LAB1.19.3 Orig_Result variable has missing values

LAB1.19.4 Orig_Result variable contains special characters ">", "<", ">=", or "<=" LAB1.19.5 Orig_Result variable contains values which imply an unresulted lab record LAB1.20.1 MS_Result_C variable Is not character type

LAB1.20.2 MS_Result_C variable is not exactly 12 characters in length

LAB1.20.3 MS_Result_C variable has non-missing values that are not left-justified LAB1.21.1 MS_Result_N variable is not numeric type

LAB1.21.2 MS_Result_N variable is not of length 8 LAB1.21.3 MS_Result_N variable contains negative values LAB1.22.1 Modifier variable is not character type

LAB1.22.2 Modifier variable is not exactly 2 characters in length LAB1.22.3 Modifier variable has missing values

LAB1.22.4 Modifier variable has values other than "EQ", "GE", "GT", "LE", "LT", or "TX" LAB1.23.1 Orig_Result_unit variable is not character type

LAB1.23.2 Orig_Result_unit variable is not exactly 11 characters in length LAB1.23.3 Orig_Result_unit variable has missing values for records where

MS_Test_Name is not equal to "D_DIMER_QL", "INF_A", "INF_AB", "INF_B", "INF_NS", "INR", "PG_QL", or "TROP_T_QL"

LAB1.24.1 Std_Result_unit variable is not character type

LAB1.24.2 Std_Result_unit variable is not exactly 11 characters in length LAB1.24.3 Std_Result_unit variable has missing values for records where

MS_Test_Name is not equal to "D_DIMER_QL", "INF_A", "INF_AB", "INF_B", "INF_NS", "INR", "PG_QL", or "TROP_T_QL"

LAB1.24.4 Std_Result_unit variable has non-missing values that are not left-justified LAB1.24.5 Std_Result_unit variable has values in lowercase text

(28)

LAB1.25.2 MS_Result_unit variable is not exactly 11 characters in length LAB1.25.3 MS_Result_unit variable has missing values

LAB1.25.4 MS_Result_unit variable has non-missing values that are not left-justified LAB1.26.1 Norm_Range_low variable is not character type

LAB1.26.2 Norm_Range_low variable is not exactly 8 characters in length

LAB1.26.3 Norm_Range_low variable contains special characters such as "-", ">", "<", ">=", or "<="

LAB1.27.1 Modifier_low variable is not character type

LAB1.27.2 Modifier_low variable is not exactly 2 characters in length

LAB1.27.3 Modifier_low variable has values other than "EQ", "GE", "GT", or missing LAB1.28.1 Norm_Range_high variable is not character type

LAB1.28.2 Norm_Range_high variable is not exactly 8 characters in length

LAB1.28.3 Norm_Range_high variable contains special characters such as "-", ">", "<", ">=", or "<="

LAB1.29.1 Modifier_high variable is not character type

LAB1.29.2 Modifier_high variable is not exactly 2 characters in length

LAB1.29.3 Modifier_high variable has values other than "EQ", "LE", "LT", or missing LAB1.30.1 Abn_ind variable is not character type

LAB1.30.2 Abn_ind variable is not exactly 2 characters in length LAB1.30.3 Abn_ind variable has missing values

LAB1.30.4 Abn_ind variable has values other than "AB", "AH", "AL", "CH", "CL", "CR", "IN", "NL", or "UN"

LAB1.32.1 Order_dept variable is not character type LAB1.33.1 Facility_Code variable is not character type

ENR_LAB2.1.8 At least one PatID in the LAB table is not in the ENR table ENR_LAB2.1.15 At least one PatID in the ENR table is not in the LAB table

ENR_LAB2.1.17 For at least one PatID with enrollment coverage, all of the labs were collected outside of the eligible enrollment period

LAB2.3.1 MS_Test_Name has values "ALP" and MS_Test_Sub_Category is not missing LAB2.3.2 MS_Test_Name has values "ALT" and MS_Test_Sub_Category is not missing LAB2.3.3 MS_Test_Name has values "ANC" and MS_Test_Sub_Category is not missing LAB2.3.4 MS_Test_Name has values "BILI_TOT" and MS_Test_Sub_Category is not

missing

LAB2.3.5 MS_Test_Name has values "CK" and MS_Test_Sub_Category is not missing LAB2.3.6 MS_Test_Name has values "CK_MB" and MS_Test_Sub_Category is not

MINI-SENTINEL COMMON DATA MODEL DATA QUALITY REVIEW AND CHARACTERIZATION PROCESS AND PROGRAMS