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Birth Defects Among New Jersey Residents

origin_of_data: NJDOH Family Health Service Early ID Monitoring
publication_date: 201710
indicator_title: Birth Defects Among New Jersey Residents
link_to_dataset: http://www.state.nj.us/health/ceohs/public-health-tracking/health-outcomes/
abstract: The data cover children born between 2000 and the most recent year of publicly-available data who have been registered by the date the extract was created. NJ law requires that a child must be registered between birth and through five years of age, but does specify a time period following diagnosis within which the child must be registered. Therefore, though a birth defect may be present at birth, a child may not be registered until several years later. This creates a dynamic data base where records maybe updated or added, thereby creating small variations in reported counts for a given year over time. All registrations are for live births and the child must be a resident of NJ at the time of registration. Out-of-state births are included when a child was a resident of NJ at the time of birth but may have been born in a neighboring hospital, e.g., Children’s Hospital of Philadelphia, or the child was a resident of another state at the time of birth and subsequently moved to NJ. The parent data base covers the entire state of NJ. The data in this extract is reported at the state level and include prevalence rates per 10,000 live births and counts for: anencephaly, spina bifeda (without anencephaly), hypoplastic left heart syndrome, tetralogy of fallot, transposition of the great arteries, cleft lip (with or without cleft palate), cleft palate (without cleft lip), hypospadias, gastroschisis, upper and lower limb deficiencies, and Trisomy 21.
purpose: These data were compiled for the EPHT Project to show the prevalence of twelve specific birth defects in NJ.
supplemental_data_info: The parent data base represents the final version of the SAS-based Registry system prior to the implementation of the web-based Birth Defects and Autism Reporting System (BDARS). The parent data base was used to populate the BDARS with legacy data. The parent data base was updated on a daily basis. This included new registrations and updates, e.g., new diagnosis, change in address, etc., to existing records. Therefore, any data requests for new data should include data from previous years. In July 2009, the parent data base was moved from a stand alone computer, where a limited amount of information from a registration was stored in a SAS data set, to the web-based BDARS, which stores all information from a registration in a Postgre SQL database. Therefore, limited data may be available for children registered prior to July 1, 2009. Any individual cell where the value is less than five will not be reported. This is done to preserve the privacy of the individual, as some birth defects are so rare that a child may be identified by simply identifying the birth defect and the county of residence. Data for birth 2009 includes legacy registrations and new registrations from the web-based BDARS.
beginning_date_in_dataset: 20000101
end_date_of_dataset: Most recent year of publicly available data
publication_date_of_dataset: Time Period End Date
dataset_status: Complete
update_frequency: Annually
westbound_coordinate: -75.559791000000004
eastbound_coordinate: -73.893980999999997
northbound_coordinate: 41.357427000000001
southbound_coordinate: 38.928767999999998
theme_keyword: Anencephalus;7400, Spina bifida;74190, Hypoplas left heart synd;7467, Tetralogy of fallot;7452, Compl transpos great ves;74510, Cleft palate NOS;74900, Cleft lip NOS;74910, Cleft palate and lip NOS;74920, Reduc deform up limb NOS;75520, Reduction deform leg NOS;75530, Down's syndrome;7580, Congn anoml abd wall NOS;75670, Hypospadias;75261,
theme_keyword: Health outcomes; health effects; birth defects; adverse reproductive outcomes; neural tube defects; NTD; Cardiac anomalies; heart defects; congenital heart defect; congenital heart disease; CHD; Oral clefts; Orofacial cleft; genital disorder; reproductive disorder; Gastroschisis; Gastroschisis (disorder);
themekey_type: NONE
theme_keyword: Special Child Health Registry, Special Child Health Services Registry, Birth Defects Registry, Birth Defects, Anencephaly, Spina bifida, hypoplastic left heart syndrome, tetralogy of Fallot, transposition of the great arteries, cleft lip with or without cleft palate, cleft palate without cleft lip, hypospadias, gastroschisis, upper limb deficiencies, lower limb deficiencies, trisomy 21, Down Syndrome
placekey_type: FIPS 5-2 (State)
place_keyword: New Jersey, NJ, 34
placekey_type: FIPS 6-4 (County)
place_keyword: Atlantic, 34001; Bergen, 34003; Burlington, 34005;Camden, 34007;
place_keyword: Cape May, 34009; Cumberland, 34011;
place_keyword: Essex, 34013; Gloucester, 34015;
place_keyword: Hudson, 34017; Hunterdon, 34019;
place_keyword: Mercer, 34021; Middlesex, 34023;
place_keyword: Monmouth, 34025; Morris, 34027;
place_keyword: Ocean, 34029; Passaic, 34031;
place_keyword: Salem, 34033; Somerset, 34035;
place_keyword: Sussex, 34037; Union, 34039;
place_keyword: Warren, 34041
access_constraints_to_data: NONE
use_constraints_of_data: These are aggregate summary measures of select birth defects in children. Data should not be used in epidemiologic investigations of health outcome and environmental linkages. Data cannot be used for commercial purposes but can be used to form a basis for additional health studies or specific remediation actions.
contact_person: FHS Early ID and Monitoring
contact_organization: NJDOH Division of Family Health Services Early Identification and Monitoring Program
address_type: Mailing and Physical
address: NJDOH Division of Family Health Services Early Identification and Monitoring Program PO Box 364
city: Trenton
state: NJ
ZIP_code: 08625-0364
country: United States of America
telephone_number: 609-292-5676
security_system: NONE
security_classification: Unclassified
security_handling_procedure: NONE
native_dataset_environment: Data stored as relational tables in a Postgre SQL database. Required data tables were downloaded into ACCESS databases and manipulated using SAS.
GIS_notes: NONE
data_completeness: The data extract is based upon children who were registered through mid-June 2017. As the most recent birth year is 2015, about one-half of these children would have been registered in the stand alone SAS-based Registry and had their records moved to the new Web-based Birth Defects and Autism Reporting System (BDARS), which was implemented on July 1, 2009. Children registered after July 1, 2009 were registered using the web-based BDARS. For the legacy data (registration prior to July 1, 2009) all diagnosis descriptions from the hard copy registration forms were converted to ICD9-CM codes by staff nurses, which were stored in the Registry data. For children registered through the web-based BDARS, the original text diagnosis descriptions were captured and staff Nurses converted these descriptions to the appropriate ICD9-CM code. Only those records meeting the diagnostic criteria of the 12 selected birth defects were extracted into a working data set for further processing. The records were checked for duplicates, resulting in a final analytical data set which contains multiple records for some children because some children have multiple birth defects. When the parent data from the stand alone SAS-based Registry was moved to the web-based BDARS, a SAS program was used to check the accuracy and validity of the data. Inconsistencies were found by checking each value in a field with acceptable values, e.g., acceptable values for sex are 1, 2, or 9, and comparing related fields, e.g., data of birth of child with date of birth of mother. The four digit code used by NJ to identify county and municipality were checked for valid values and consistency between county value and zip code. Possible duplicate records were identified by comparing each extracted record with every other extracted record. A name, both first and last, were considered potential duplicates if they matched on a character-by-character basis, had a similar soundex value, had a spedis (function in SAS that assigns a cost to change one spelling to another) value within a certain range, or a five character string of the shorter name was included within the longer name (Jones within Smith-Jones), or the last and first names had been switched (Scott James vs James Scott). A date of birth was considered similar if it was exactly the same, or the month and day was the same and birth year was +/- 2 years, or the year was the same and the month and day had been switched (1/10/2005 vs 10/1/2005), or miss keying of values due to similarity in appearance (1 vs 7) on the hard copy registration, or proximity on the numeric key pad (6 vs 9). A record was identified as a possible match if there were similarities in all three fields, first name, last name, and date of birth. The list of all matches and possible matches were manually reviewed. The web-based BDARS contains data checks and validations to ensure only valid information is entered and an automated process to identify duplicates, which are manually reviewed and merged by NJDOH staff. The denominator dataset for all live births was specific to the birth year specified above.
data_processing_step_description: Created an extract of all children registered whose date of birth was within the date range specified above and an extract of all diagnoses meeting the criteria of the 12 selected birth defects from ACCESS data files that were created in mid-June 2017 from the web-based Birth Defects and Autism Reporting System (BDARS) that was implemented on July 1, 2009.
data_processing_step_date: 201707
data_processing_step_description: Created a working data set from the above extracted records where only the records from children who were diagnosed with one of the 12 selected birth defects were retained.
data_processing_step_date: 201707
data_processing_step_description: Cleaned the above extracted dataset by checking for duplicate registrations, i.e., where a child may have been registered by more than one facility. Possible duplicates were identified by comparing each record in the extracted data with every other record in the extracted data using a set of criteria that identified similarities in first name, last name, and date of birth, see Completeness Report below for specific criteria. Each possible duplicate record was manually reviewed.
data_processing_step_date: 201707
data_processing_step_description: Added address and mother's information from the ACCESS data files to the above child records.
data_processing_step_date: 201707
data_processing_step_description: Created a dataset of unique registered children from the originally extracted dataset. During this process all duplicate records were merged into a single record. The merged record retained all the information from the separate duplicate records. The merged duplicate records were then processed to ensure that all diagnoses for a child were identified and if the merged record contained duplicate diagnoses, e.g., Down Syndrome, icd9-cm of 75800, then the duplicate diagnosis was counted only once.
data_processing_step_date: 201707
data_processing_step_description: Created analytical numerator and denominator datasets that were used to produce all summary tables. Numerator Data: The records in the unique registered children dataset were then merged by unique registration number with a data set containing matched Registry and Birth file records. This matched (deterministic with manual review) dataset is created on a regular basis, however, there is normally a 3 to 4 year delay in matching records because children may be registered up to age 6 years. These merged records contain demographic information, e.g., mother's race and ethnicity, which was not present in the Registry data that was originally entered into the stand alone SAS-based Registry system. Since these merged records may contain multiple values for a single demographic, when selecting values for the final analytical dataset, the order of preference was birth file first, then initial registration (based upon registration date), and finally duplicate registration. The final analytical dataset was assigned variable names and values based upon the data dictionary. Denominator Data: A flat file supplied by the NJ Center for Health Statistics for the specific birth year, which had been previously converted to SAS files as part of the regular matching of Registry and birth files described above, was used for the denominator data. An analytical data set was created by selecting only those fields needed for analysis then assigning variable names and values based upon the data dictionary.
data_processing_step_date: 201707
data_processing_step_description: Created summary table files in both CSV and XML file formats using numerator and denominator dataset described above.
data_processing_step_date: 201707
contact_person: NJEPHT Metadata Coordinator
contact_organization: NJ Department of Health
address_type: Physical
address: 135 East State Street 4th Floor, Rear Office # 465
city: Trenton
state: NJ
ZIP_code: 08625
country: United States of America
telephone_number: 609-826-4972
e-mail: nj.epht@doh.nj.gov
data_file_spec_info: Data available in CSV and XML formats. Files size is less than 3MB.
data_use_liability: In preparation of data, every effort has been made to offer the most current, and correct data possible. Nevertheless, inadvertent errors in data may occur. The NJEPHTN and National EPHTN disclaim any responsibility for data errors and accuracy of the information that may be contained within this database. The state and national EPHTN also reserve the right to make changes at any time without notice.
data_request_info: All data release requires approval of NJ Department of Health Institutional Review Board (IRB). Please contact data steward with additional questions.
contact_person: NJEPHT Metadata Coordinator
contact_organization: NJ Department of Health
address_type: Physical
address: 135 East State Street 4th Floor, Rear Office # 465
city: Trenton
state: NJ
ZIP_code: 08625
country: United States of America
telephone_number: 609-826-4972
e-mail: nj.epht@doh.nj.gov
metadata_standard_name: EPHTN Tracking Network Profile Version 1.2
metadata_access_constraints: NONE
metadata_use_constraints: NONE