cdc infertility prevention project quality assurance guide

CDC INFERTILITY PREVENTION PROJECT Quality Assurance Guide

1

CDC reviews submitted IPP data to:

check values for validity, consistency, and format of individual records

identify records with an out-of-date-range specimen collection date

compare summary frequencies over time for all core variables to detect significant changes in the distribution

Each region is responsible for providing CDC with an up-to-date data codebook. The codebook should accompany a

memo detailing any issues resulting in anomalous data and should also include a data summary table. The anomalous

data issues might potentially result from reporting problems for an individual state or laboratory or any updates/changes

to the codebook. The summary table should provide the total number of records by month corresponding to each

quarterly and year-end data submission. The regional data codebook and QA memorandum are stored on the IPP server

at CDC.

Validation and continual improvement in the contents and quality of the Facility Reference File is important to correctly

capture geographic information as well as the facility type (formerly a data element in the Prevalence Dataset).

3.1 Validating Number of Records Received

CDC requests that each region send a quarterly and end-of-year summary table with the number of records submitted −

by state or project area and month of specimen collection date. CDC compares the region‟s summary table count to the

number of records uploaded to the CDC data store to ensure that all records were correctly received.

3.2 Validating Date of Specimen Collection

For each region, CDC generates a table showing the total number of records excluded from the national dataset due to a missing specimen collection date. This analysis also identifies the number of records for which the specimen collection date is invalid, i.e., outside appropriate reporting dates. The regions are notified of these anomalies and given an opportunity to review/address them before the end-of-year close out date.

3.3 Variable Format and Length Requirements

CDC will validate regional submission to ensure that they meet the variable format and length requirements outlined in the National Data Codebook for all core variables in the prevalence monitoring and facility reference files. Variable format and length requirements are included in Table 3. Records that do not meet these specifications are identified via report output with a description of the validity check in a summary list. The regions are notified of these invalid records and given an opportunity to review/address them before the end-of-year close out date.

3.4 Value Requirements

Records that do not meet the value specifications shown in Table 3 or that have missing values are identified via report output with a description of the validity check in a summary list. The regions are notified of these invalid or missing data and given an opportunity to review/address them before the end-of-year close out date.

3.5 Cross-field Requirements

Records that do not meet the cross-field specifications shown in Table 3 are identified via report output with a description of the validity check in a summary list. The regions are notified of these invalid records and given an opportunity to review/address them before the end-of-year close out date.


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TABLE 3. Key IPP Variables and corresponding value, format (length), and cross-field specifications

Item Variable Valid values Value definition

Format

(Length)

Value

checks

Cross-field

checks

1

Region 01 Region 1 char (2) Valid

value and

length

Compare

value for

Region

against

source of

regional data

file

02 Region 2

03 Region 3

04 Region 4

05 Region 5

06 Region 6

07 Region 7

08 Region 8

09 Region 9

10 Region 10

2

quarter 0

End of Year char (1) Valid

value and

length

Quarter

must

correspon

d to valid

quarter.

1 Quarter 1

2 Quarter 2

3 Quarter 3

4 Quarter 4

3

year Format: YYYY

Range: 1988 –

present

char (4) Valid

value and

length

Year

must

correspon

d to valid

Year

4

state_code 2-digit code

identifying state of

patient residence

Refer to:

http://www.itl.nist.go

v/fipspubs/

See Section 3 for

more detailed

information

char (2) Valid

value and

length

5

facility_state_code 2-digit code

identifying state of

facility location

Refer to:


v/fipspubs/

See Section 3 for

more detailed

information

char (2) Valid

value and

length

Check that

facility_state

_code

„belongs to‟

the specified

region

6

county_code 3-digit code

identifying county

Refer to:


v/fipspubs/

char (3) Valid

value and

length

Future plan −

Check that

county is

valid for state

7

birth_dt MMDDYYYY format

Missing date elements

are represented with a

period (“.”)

num(8) Valid

value and

length

„YYYY‟

should be

http://www.itl.nist.gov/fipspubs/







3


Format

(Length)

Value

checks

Cross-field

checks

between

(current

year-99)

and

current

year

8

age Range: 00 - 99

Unknown values are left

blank

char (2) Valid

value and

length

9

calculated_age Range: 00 - 99

Invalid or unknown

values are left blank

char (2) Valid

value and

length

Note: CDC

creates this

variable

10

sex 1 Male char (1) Valid

value and

length

Note: A blank

field is

captured as

Missing data.

2 Female

9 Unknown

11

race_a 1 Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

race_i 1 Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

race_b 1 Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

race_p 1

Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

race_w 1 Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

race_o 1 Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

race_u 1 Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

race_r 1 Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

race_al 1 Yes char (1) Valid

value and

length

Need at least

one race or

ethnicity value

ethnicity 1 Yes, Hispanic or

Latino

char (1) Valid

value and

length

Need at least

one race or

ethnicity value 2 No, Not Hispanic or

Latino

9 Unknown

12 specimen_source 01 Cervix/Endocervix char (2) Valid

value and

For

specimen_so05 Oropharnyx


4


Format

(Length)

Value

checks

Cross-field

checks

07 Other length urce 01 and

12, sex

should be

female.

For

specimen_so

urce 10, sex

should be

male.

09 Rectum

10 Urethra

11 Urine

12 Vagina

99 Unknown

13

specimen_dt MMDDYYYY

format

Missing date elements

are represented with a

period (“.”)

num (8) Valid

value and

length

14

facility_type 01 HIV Counseling and

Testing Site

char (2) Valid

value and

length

Check sex for

value 14, 15

Check age

for values 19,

20, 21

If value =27

(integrated

clinic), then

visit_type

should have

a value

Check

volume of

records by

facility_type

for each state

Each state

should have

at least one

facility_type

02 STD

03 Drug Treatment

04 Family Planning

07 Other Health Dept. Clinic

08 Private Physician/HMO

09 Hospital (Inpatient)

10 Emergency Room (ER)

14 Labor and Delivery

15 Prenatal

16 National Job Training

Program

17 School-based clinic

18 Mental Health Provider

19 Adult Correctional Facility

20 Juvenile Correctional

Facility

21 Adolescent/Teen Clinic

22 Alternative/Outreach

Settings

23 Homeless Shelter

24 Community Health Center

25 HIV Clinic

26 University/College Health

Center


5


Format

(Length)

Value

checks

Cross-field

checks

27 Integrated Clinic

28 School Screening

29 Hospital (Outpatient)

66 Indian Health Service

77 Military

88 Other

15

visit_type 1 Family Planning char (1) Valid

value and

length

Check sex

for value 3

2 STD

3 Prenatal

4 Other

9 Not Available

16

facility_link_id char (24) Valid

value and

length

17

lab_id Format varies by

region.

char (20) Valid

value and

length

Check

volume of

records by

facility_state_

code (to

ensure that

there is a

lab_id for

every state)

18

ct_test_type 17.1 TMA/GP/Aptima Combo

2CT/GC

char (4) Valid

value and

length

Check the

volume of

records by

ct_test_rslt

because

each

ct_test_rslt

should have

a

ct_test_type.

18.1 SDA/BD/BDProbeTec

CT/GC

19.1 PCR/Roche/Amplicor

CT/GC

19.2 PCR/Roche/COBAS

CT/GC

20 Nucleic Acid

Hybrid./GP/PACE

2CT/GC

21 Signal

Amplification/Digene/Hybr

id Capture 2 CT/GC DNA

09.1 TMA/GP/Aptima CT

06.1 PCR/Roche/Amplicor CT


6


Format

(Length)

Value

checks

Cross-field

checks


Amplicor CT

08.1 SDA/BD/BDProbeTec CT

05.1 Nucleic Acid

Hybrid./GP/PACE 2CT

04 EIA

03 DFA

02 Culture

88 Other

99 Unknown

19

ct_test_rslt 1 - Positive

2 - Negative

3 - Indeterminate/E

quivocal

9 - Unknown

char (1) Valid

value and

length

Check cross-

tab of

gc_test_rslt

and

ct_test_rslt

by

facility_state_

code to verify

that each test

record has

either a ct or

gc test result

(or both).

20

gc_test_type 17.1 TMA/GP/Aptima Combo

2CT/GC

char (4) Valid

value and

length

Check the

volume of

records by

gc_test_rslt

because

each

gc_test_rslt

should have

a

gc_test_type.

18.1 SDA/BD/BDProbeTec

CT/GC

19.1 PCR/Roche/Amplicor

CT/GC


CT/GC

20 Nucleic Acid

Hybrid./GP/PACE

2CT/GC


7


Format

(Length)

Value

checks

Cross-field

checks

21 Signal

Amplification/Digene/Hybr

id Capture 2 CT/GC DNA

16.1 TMA/GP/Aptima GC

11.1 Nucleic Acid

Hybrid./GP/PACE 2GC

12.1 PCR/Roche/Amplicor GC


Amplicor NG

15.1 SDA/BD/BDProbeTec GC

10 Culture

88 Other

99 Known

21

gc_test_rslt 1 Positive char (1) Valid

value and

length

Check cross-

tab of

gc_test_rslt

and

ct_test_rslt

by

facility_state_

code to verify

that each test

record has

either a ct or

gc test result

(or both).

2 Negative

3 Indeterminate

/ Equivocal

9 Unknown

22

facility_id char (22) Valid

value and

length

23

facility_name char(100) Valid

value and

length

24

facility_city_code char(6) Valid

value and

length

Future plan -

Check cross-

tab of

facility_city_c

ode and

facility_city_n

ame to verify

that each city

code has a

correspondin

g city name.

25 facility_city_name char(100) Valid

value and


8


Format

(Length)

Value

checks

Cross-field

checks

length

26

facility_county_code char(3) Valid

value and

length

Future plan-

Check cross-

tab of

facility_count

y_code and

facility_count

y_name to

verify that

each city

code has a

correspondin

g county

name.

27

facility_county_name char(100) Valid

value and

length

28

facility_state_postal char(2) Valid

value and

length

29

facility_zip_code char(5) Valid

value and

length

3.6 Aberration Detection

CDC compares the total number of regional records received by state with the number of records received during the

previous reporting time periods (quarters, years) to identify any significant changes in volume. CDC then compares the

current frequency distributions of variables shown in TABLE 4 with the same distributions from previous reporting

periods. For each variable noted, a volume that varies more than 15% up or down will be flagged for further evaluation.

TABLE 4. Record counts checked for changes in volume over time by region (and state)

Variable Record count trends for:

facility_state_code state

age age (in individual years)

sex gender

race_check race_a Asian

race_b Black

race_i American Indian

race_o Other

race_p Pacific Islander

race_u Unknown

race_w White

ethnicity

specimen_source 10 different sources

facility_type 27 different types

ct_test_type NAATS, non-NAATS

ct_test_rslt

gc_test_type

gc_test_rslt


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3.7 Chlamydia positivity distribution

Chlamydia positivity distribution by state is analyzed by age group and facility type. Table 1 from this output (not

shown here) identifies inconsistencies in chlamydia positivity and the total number of tests by quarter for the

following age ranges:

10−14

15−19

20−24

25−29

30−34

For example, regional data are expected to indicate a higher percent positivity for the age group 15−19 than for the

age group 30-34. Historically, QA reviews have not quantified the expected differences in positivity between age

groups. However, future efforts may include reviewing data trends to identify the expected differences in positivity

levels.

Table 2 from this output (not shown here) identifies the inconsistencies in chlamydia positivity and the total number

of tests by facility type for each quarter. Research is required for any noted:

missing data

large increases and decreases in the percent positivity

changes greater than 15% in the number of tests compared to previously reported counts

For example, regions should research and document any new facility types (as well as any missing data,

increases/decreases in percent positivity, or changes in the number of tests). Also, the percent positivity reported

by the family planning clinics is expected to be lower than for the STD clinics. To capture non-seasonal

differences, quarterly positivity rates should be compared with the quarterly rates from the previous year rather

than with quarters within the same year.

3.8 Laboratory Validation

This validation compares laboratory IDs by region for each state in order to verify that each lab associated with a

chlamydia or gonorrhea test result.CDC also attempts to identify any laboratories no longer included in the regional

datasets.

3.9 Laboratory test method validation

This validation is conducted for each state (by region) using a frequency table for laboratory ID and chlamydia test type.

The table is used to validate the chlamydia test types reported by state (or project area) and to determine if there are

changes in reported ct_test_type. If a laboratory changes test methods, the region must verify that change. This

validation is repeated for gonorrhea test type.

3.10 Merging Prevalence Monitoring data with the Facility Reference File

Merging the prevalence monitoring data with the Facility Reference File generates a facility listing that identifies the data

with which a facility is associated as well as the total number of tests reported by each facility. CDC reviews this listing

for missing facility information.


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Appendix 2

Quality Assurance

Sample SAS Outputs

Output 1. Reference Section 3.1 – Validating Number of Records Received

Table of STATE by month year

STATE Month year

Frequency JAN10 FEB10 MAR10 APR10 MAY10 JUN10 Total

599 664 1274 1351 1234 947 6069

BA 8722 8670 11233 9520 9360 9627 57132

GN 21061 22219 25577 24722 22629 24559 140767

HA 13192 14449 17075 14600 13698 14708 87722

MP 6220 7534 8123 7589 7031 7688 44185

OC 9025 8718 10521 9198 8871 10008 56341

PC 6457 6320 7985 6984 6253 6295 40294

WN 9180 9358 11064 9808 8631 7350 55391

Total 74456 77932 92852 83772 77707 81182 487901

Output 2 . Reference Section 3.2 – Validating Date of Specimen of Collection

3.2 Validating Date of Specimen Collection - '2010 Quarter 2'

Region # - Total records with missing or invalid specimen date by region by state

State

Total

records

BA 0

GN 0

HA 188

MP 0

OC 0

PC 9

WN 0


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Output 3. Reference Sections 3.3, 3.4 and 3.5 – Variable Format, Length, Value & Cross-field Requirements

Check_type Variable Check message

*Invalid

value

*Invalid

Variable

Format

*Invalid

Variable

Length

Number

of

records

3.5 - Cross-field check region invalid region number in region variable . . 1

3.5 - Cross-field check quarter records not in the quarter . . 245

3.4 - Value check facility_state_code missing value . . 606

3.5 - Cross-field check birth_dt records less than specimen date year minus 99 years . . 589

3.5 - Cross-field check birth_dt records greater than specimen year . . 9

3.4 - Value check race_check missing value missing . . 4

3.4 - Value check race_a invalid value . . . 497

3.4 - Value check race_i invalid value . . . 499

3.4 - Value check race_b invalid value . . . 142

3.4 - Value check race_p invalid value . . . 501

3.4 - Value check race_w invalid value . . . 382

3.4 - Value check race_o invalid value . . . 490

3.4 - Value check race_u invalid value . . . 499

3.4 - Value check ethnicity missing value . . 15

3.4 - Value check specimen_source missing value . . 154

3.5 - Cross-field check specimen_source invalid sex for specimen_source(cervix/vagina) . . 255

3.5 - Cross-field check specimen_source invalid sex for specimen_source (urethra) . . 385

3.4 - Value check facility_type missing value . . 606

3.5 - Cross-field check facility_type invalid age for juvenile corrections . . 388

3.5 - Cross-field check facility_type integrated clinics with missing or N/A visit_type . . 431

3.4 - Value check visit_type missing value . . 158

3.5 - Cross-field check visit_type invalid sex for visit type(prenatal) . . 11

3.3 - Format and Length check ct_test_type invalid variable length . 3 .

3.4 - Value check ct_test_type invalid value 08. . . 27

3.4 - Value check ct_test_type invalid value 17. . . 487

3.3 - Format and Length check gc_test_type invalid variable length . 3 .

3.4 - Value check gc_test_type invalid value 17. . . 487

3.5 - Cross-field check gc_test_type gc_test_type without gc_test_rslt . . 12

3.4 - Value check gc_test_rslt missing value . . 12

3.3 - Format and Length check facility_city_code invalid variable length . 4 .


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Output 4. Reference Section 3.6 -- Aberration Detection

3.6 – Sex by Quarter (Percent change is bold, when less than equal -15% or greater than equal 15%)

Region

Sex

2009

Q1 Q2 Q3 Q4

2009

Total

2010

Q1 Q2 Q3 Q4

2010

Total

% change

2009-2010

% change

10q1-10q1

% change

10q2-10q2

00 F 2611 2505 2440 2115 9671 2341 1871 0 0 4212 -56.44 -10.3 -25.3

Output 5. Reference Section 3.7 -- CT positivity distribution (Table 1)

Region 00 - CHLAMYDIA - Females in Family Planning - Positivity by state by Age Group (Percent change is bold, when

less than equal -15% or greater than equal 15%)

ST Age Group

2009 Pvty

2009 #

Tested

Qtr 1 2010 Pvty

Qtr 1 2010

# Tested

Qtr 2 2010 Pvty

Qtr 2 2010

# Tested

Qtr 3 2010 Pvty

Qtr 3 2010

# Tested

Qtr 4 2010 Pvty

Qtr 4 2010

# Tested

2010 Pvty

2010 Total

# Tested

% change 2009-2010 Pvty

% change 2009-2010

# Tested

BA . 6.78% 59 . . . . . . . . . 0 NA -100.0

< 10 . 2 . 48 . 22 5.00% 20 8.33% 24 2.63% 114 NA 5600.0

10 - 14 4.20% 690 2.60% 192 3.40% 147 5.11% 137 5.22% 134 3.93% 610 -6.4 -11.6

15 - 19 6.84% 13059 7.27% 3162 7.90% 2938 8.45% 2676 7.52% 2834 7.76% 11610 13.5 -11.1

20 - 24 6.42% 17940 6.69% 4203 6.52% 4205 7.16% 4272 5.92% 3933 6.59% 16613 2.6 -7.4

25 - 29 5.31% 7009 5.69% 1563 4.43% 1467 4.85% 1443 5.04% 1389 5.02% 5862 -5.5 -16.4

30 - 39 3.54% 4093 3.23% 866 3.07% 748 2.78% 792 2.99% 737 3.02% 3143 -14.7 -23.2

40 - 90 3.16% 2217 1.62% 557 1.17% 426 2.20% 454 1.87% 428 1.72% 1865 -45.7 -15.9

Reference Section 3.7 -- CT positivity distribution (Table 2)

Region 00 - CHLAMYDIA - Positivity by state by facility_type (Percent change is bold, when less than equal -15% or

greater than equal 15%)

ST Fac

type

2009

Pvty

2009

# Tested

Qtr 1

2010 Pvty

Qtr 1

2010 #

Tested

Qtr 2

2010 Pvty

Qtr 2

2010 #

Tested

Qtr 3

2010 Pvty

Qtr 3

2010 #

Tested

Qtr 4

2010 Pvty

Qtr 4

2010 #

Tested

2010

Pvty

2010

Total #

Tested

%

change 2009-2010 Pvty

%

change 2009-2010

# Tested

BA FP 5.63% 36128 6.19% 8317 6.34% 7727 6.73% 7592 5.59% 7364 6.22% 31000 10.4 -14.2

STD 7.55% 3774 6.05% 810 3.62% 857 5.61% 945 7.86% 802 5.74% 3414 -24.0 -9.5

Jail 6.87% 4045 5.15% 1106 5.20% 1038 6.18% 1117 4.75% 948 5.35% 4209 -22.2 4.1

Other 5.88% 1122 5.87% 358 8.76% 331 6.43% 140 9.59% 365 7.87% 1194 33.8 6.4


13


14

Output 6. Reference Section 3.8 -- Laboratory Validation Table

Laboratory validation by quarter (Percent change is bold, when less than equal -15% or greater than equal 15%)

Region LAB 2009

Q1

Q2 Q3 Q4 2009

Total

2010

Q1

Q2 Q3 Q4 2010

Total

% change

09q1-10q1

% change

09q2-10q2

% change

2009-2010

00 BA-91 2611 2505 2440 2115 9671 2341 1871 0 0 4212 -10.3 -25.3 -56.4

HA-55 3815 3974 3994 3783 15566 3953 3562 0 0 7515 3.6 -10.4 -51.7

Output 7. Reference Section 3.9 -- Laboratory Test Method Validation Table

Lab Test Method Validation – CT Test Type by Lab by Quarter (Percent change is bold, when less than equal -15% or


Region Lab CT

Test_type

2009

Q1

Q2 Q3 Q4 2009

Total

2010

Q1

Q2 2010

Total

% chg

09q1-

10q1

% chg

09q2-

10q2

% chg

2009-

2010

00 BA-11 SDA/BD/BDProbeTec

CT/GC

2611 2505 2440 2115 9671 2341 1871 4212 -10.3 -25.3 -56.4

GN-31 SDA/BD/BDProbeTec

CT/GC

3815 3974 3994 3783 15566 3953 3562 7515 3.6 -10.4 -51.7

Lab Test Method Validation – GC Test Type by Lab by Quarter (Percent change is bold, when less than equal -15% or


Region Lab GC

Test_type

2009

Q1

Q2 Q3 Q4 2009

Total

2010

Q1

Q2 2010

Total

% chg

09q1-

10q1

% chg

09q2-

10q2

% chg

2009-

2010

00 BA-11 SDA/BD/BDProbeTec

CT/GC

2611 2505 2440 2115 9671 2341 1871 4212 -10.3 -25.3 -56.4

GN-31 SDA/BD/BDProbeTec

CT/GC

3815 3974 3994 3783 15566 3953 3562 7515 3.6 -10.4 -51.7


15

Output 8. Reference Section 3.10 -- Prevalence Monitoring data merge with Facility Reference File

Facility Fac Facility Line Clinic Nbr of link_id st_cd _ID Facility Name Facility_type data file tests

091 09 1 Dustinville Family Planning X X 390

cdc infertility prevention project quality assurance guide

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