1. Using ICD Codes and Birth Records to Prevent Mismatches of Multiple Births in Linked Hospital Readmission Data Alison Fraser 1, MSPH, Zhiwei Liu 2, MS, Emily Smith 1, MA, Geraldine Mineau 1, PhD and Wu Xu 2, PhD 1 University of Utah, Salt Lake City, Utah; 2 Utah Department of Health, Salt Lake City, Utah Multiple births present a challenge for accurately identifying newborn readmissions when using probabilistic linkage methods and the given name is missing. We discovered that using ICD newborn codes and linking to birth certificates to identify multiple births in hospital discharge data improves the linking accuracy for newborn readmissions by 37.6% Abstract Introduction Data Using probabilistic linkage methods for identifying hospital inpatient record readmissions can lead to incorrect matches for newborns and infants from multiple births as many hospitals do not record the baby’s name, but all other significant linking variables match including parent’s social security number (SSN). As part of a larger study linking hospital discharge records, this study examined the impact of identifying multiple births on newborn and infant (<1 year) linking rates. UofUUDOH SSN Y Encrypted SSN Y Medical Record Number Y Genealogical database to link and query Y Multiple Births Flagged Y research resource at the University of Utah (UofU) includes over 12 million records or documents representing over 8 million individuals. central component of the UPDB is a vast set of family histories or genealogies, in which family members are linked to demographic and medical information. individuals in this database are linked to a number of state-wide data sets, especially birth certificates. These birth certificates and genealogies provide a source for identifying multiple births. Utah Population Database ( UPDB ) Utah Department of Health Inpatient Discharge Summaries (UDOH) contains statewide, population-based healthcare information associated with 56 hospitals in Utah from 1996-2006. developed a comparative study on 290,537 discharge records from 12/1/2004 to 12/31/2005, specifically 59,488 infants <1 year old restricts transfer of SSN and Medical Record Number – must be encrypted has incomplete linking information - 42% of patients > 1 year old have full names cf. 22% of Infants Linkage Methods Linkage was conducted separately by the Utah Department of Health (UDOH) using LinkSolv 7.0 (MatchWare Technologies) and then at the University of Utah (UofU) using QualityStage 7.5, a part of IBM’s Websphere Information Integration Solution. Both products assign a numeric weight which is used to determine threshold values of accepted and rejected links. The UDOH used social security number (SSN), hospital medical record number, name, birth date, gender, zip code, and hospital as linking variables with nine independent blocking and matching strategies. The UofU linked the inpatient records stratified by gender using names, dates, zip codes and encrypted SSN in 22 different combinations for blocking and matching. In addition, UofU linked 49,464 (83.1%) inpatient records to the UPDB. The UofU identified 1,640 infant twins on inpatient records via ICD-9-CM diagnosis codes V3100-V372. After linking the inpatient records to the UPDB, the multiplicity flag on their birth certificates was used to identify infants admitted to the hospital after delivery. There were an additional 114 infants identified via linking to birth certificates for a total of 1,754 inpatient events involving infant twins. UDOH did not flag multiple births in their linkage. Findings from Linkage Comparison The results of the independent linkage projects were compared for 59,975 infant hospital discharge records. The medical record number was used as an independent source of verification. the UDOH linkage method identified 1,826 (3.2%) infants with 3,856 multiple admissions the UofU method identified only 646 (1.1%) infants with 1,386 multiple admissions the readmissions from UDOH which did not match on medical record number and were not matched by UofU were manually scanned and determined to be mismatches there were 670 infants with 1,450 (37.6%) mismatched admissions, of which 609 (90.1%) were from multiple births the majority of mismatches (1,193) were newborn delivery records linked to their siblings’ newborn delivery records the major source of the mismatches was absent first names with 629 (93.8%) mismatches where one or both of the records did not have a given name, but had matched on other pertinent linking variables; the remaining mismatches with names were primarily “Baby A” and “Baby B” UofU did not match 753 infants to 1,563 admissions due to missing key linking variables, especially medical record number A combination of links via medical record number and links by UofU was considered the “Gold Standard” with 1,567 infants identified with 3,522 multiple admissions. Conclusion Linkage methods for hospital discharge record must address multiple births. The majority of incorrectly linked infants are twins and can be flagged through the delivery diagnosis code on inpatient records. Furthermore, linking to an external database that contains genealogical records and birth certificates means that multiple births can be identified, even if they don’t link to their delivery record or if they are born out of state. Access to medical record number is key to linking infants when names are missing from the records. Acknowledgement: This project is sponsored by NIH grant R01 RR021746, P.I. Mineau, Sharing statewide health data for genetic research; CDC grant P01 CD000284, P.I. Samore, Utah Research Center for Excellence in Public Health Informatics and the Office of Health Care Statistics, Utah Department of Health. Partial support for datasets within the UPDB is provided by the Huntsman Cancer Institute. UPDB web site: http://www.hci.utah.edu/groups/ppr/ InfantsTransfers or Readmissions Mismatched Infants Infants with missed admissions UDOH1,826 (3.2%) 2,030670200 UofU 646 (1.1%) 7400753 Gold Standard 1,3851,53000 Table 1. Differences in Availability of Linking Variables and Strategies Figure 1. Percentage of Inpatient Records with Full Names by Age and Sex Table 2. Distribution of Infants with multiple Admissions Gold Standard Linking Strategy for Infant Multiple Birth Re-Admissions Utilize diagnosis codes and linked birth certificates to flag multiple births Identify different gender twins Use diagnosis codes to differentiate twins, eg. one twin is low birth weight, other twin is normal weight Use diagnosis codes to flag delivery records to avoid mis- matching Use medical record number from same facility to identify readmissions where name is missing Link multiple birth only if a) first name is available and matches b) other twin is different gender c) medical record number matches