Related Experiment Video
Updated: Jun 2, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Validation of diagnosis codes for low birth weight and small for gestational age in the Medicaid Analytic eXtract
Xi Wang1, Yehua Wang1, Yanmin Zhu2
1Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL, United States.
The accuracy of low birth weight (LBW) and small for gestational age (SGA) in administrative health care records is crucial for perinatal studies but there are few published validity studies. Using 1999-2010 Medicaid Analytic eXtract (MAX) data linked to birth certificates (BCs), we identified mother-infant dyads (≥30 days enrollment after delivery, with valid gestational age [GA] and birth weight [BW] data). We identified LBW and SGA according to International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Infants with BW < 10% of the US reference were flagged as SGA. For LBW group diagnoses, we imputed BW using median, mean BW from BCs, and ICD code boundaries of infants in the same LBW group. We calculated the sensitivity, specificity, and positive and negative predictive values to assess performance. We identified 1 536 272 live births. All LBW groups had low Ses and high SPs and NPVs, whereas PPVs varied. Among infants with SGA diagnoses based on GA/BW from the BC, SE of the SGA codes was 13.36%, SP was 99.01%, and PPV was 67.37%. Combining imputation with LBW codes increased SE up to 22.09% (lower boundary) but decreased PPV to 41.53% (lower boundary). The ICD-9-CM codes from administrative health care records had low SE but high SP. Imputation based on GA and BW did not add much value to SGA identification.
The accuracy of low birth weight (LBW) and small for gestational age (SGA) in administrative health care records is crucial for perinatal studies but there are few published validity studies. Using 1999-2010 Medicaid Analytic eXtract (MAX) data linked to birth certificates (BCs), we identified mother-infant dyads (≥30 days enrollment after delivery, with valid gestational age [GA] and birth weight [BW] data). We identified LBW and SGA according to International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Infants with BW < 10% of the US reference were flagged as SGA. For LBW group diagnoses, we imputed BW using median, mean BW from BCs, and ICD code boundaries of infants in the same LBW group. We calculated the sensitivity, specificity, and positive and negative predictive values to assess performance. We identified 1 536 272 live births. All LBW groups had low Ses and high SPs and NPVs, whereas PPVs varied. Among infants with SGA diagnoses based on GA/BW from the BC, SE of the SGA codes was 13.36%, SP was 99.01%, and PPV was 67.37%. Combining imputation with LBW codes increased SE up to 22.09% (lower boundary) but decreased PPV to 41.53% (lower boundary). The ICD-9-CM codes from administrative health care records had low SE but high SP. Imputation based on GA and BW did not add much value to SGA identification.
Related Concept Videos
Data Validation
Nursing assessment guides are generally based on holistic models rather than medical...
Methods of Documentation V: CBE
In CBE, healthcare professionals establish predefined standards of practice that define what constitutes...
Formulating and Validating Nursing Diagnosis II
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
Documentation of Nursing Diagnosis
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
z Scores and Area Under the Curve
Regression Toward the Mean

