Dataset Information

Identifying neonatal intensive care (NICU) admissions using administrative claims data.

ABSTRACT:

Background

To define a method for identifying neonatal intensive care unit (NICU) admissions using administrative claims data.

Methods

This was a retrospective cohort study using claims from Optum's de-identified Clinformatics® Data Mart Database (CDM) from 2016 -2020. We developed a definition to identify NICU admissions using a list of codes from the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), Current Procedural Terminology (CPT), and revenue codes frequently associated with NICU admissions. We compared agreement between codes using Kappa statistics and calculated positive predictive values (PPV) and 95% confidence intervals (CI).

Results

On average, revenue codes (3.3%) alone identified more NICU hospitalizations compared to CPT codes alone (1.5%), whereas the use of CPT and revenue (8.9%) and CPT or revenue codes (13.7%) captured the most NICU hospitalizations, which aligns with rates of preterm birth. Gestational age alone (4.2%) and birthweight codes alone (2.0%) identified the least number of potential NICU hospitalizations. Setting CPT codes as the standard and revenue codes as the "test,", revenue codes resulted in identifying 86% of NICU admissions (sensitivity) and 97% of non-NICU admissions (specificity).

Conclusions

Using administrative data, we developed a robust definition for identifying neonatal admissions. The identified definition of NICU codes is easily adaptable, repeatable, and flexible for use in other datasets.

SUBMITTER: Vance AJ

PROVIDER: S-EPMC10916318 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identifying neonatal intensive care (NICU) admissions using administrative claims data.

Vance A J AJ Bell S S Tilea A A Beck D D Tabb K M KM Zivin K K

Journal of neonatal-perinatal medicine 20230101 4

<h4>Background</h4>To define a method for identifying neonatal intensive care unit (NICU) admissions using administrative claims data.<h4>Methods</h4>This was a retrospective cohort study using claims from Optum's de-identified Clinformatics® Data Mart Database (CDM) from 2016 -2020. We developed a definition to identify NICU admissions using a list of codes from the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), Current Procedural Terminology (CPT), ...[more]

PMID: 38073398

Similar Datasets

Project description:BackgroundThe goal of regionalized perinatal care, specifically levels of maternal care, is to improve maternal outcomes through risk-appropriate obstetric care. Studies of levels of maternal care are limited by current approaches to identify a hospital's level of care, often relying on hospital self-reported data, which is expensive and challenging to collect and validate. The study objective was to develop an empiric approach to determine a hospital's level of maternal care using administrative data reflective of the patient care provided and apply this approach to describe the levels of maternal care available over time.MethodsRetrospective cohort study of mother-infant dyads who delivered in California, Missouri, and Pennsylvania hospitals from 2000 to 2009. Linked mother-infant administrative records with an infant born at 24-44 weeks' gestation and a birth weight of 400-8000 g were included. Using the American College of Obstetricians and Gynecologists and the Society for Maternal Fetal Medicine descriptions of levels of maternal care, four levels were classified based on the appropriate location of care for patients with specific medical or pregnancy conditions. Individual hospitals were assigned a level of maternal care annually based on the volume of patients who delivered reflective of the four classified levels as determined by International Classification of Diseases and Current Procedural Terminology.ResultsBased on the included 6,895,000 mother-infant dyads, the obstetric hospital levels of maternal care I, II, III and IV were identified. High-risk patients more frequently delivered in hospitals with higher level maternal care, accounting for 8.9, 10.9, 13.8, and 16.9% of deliveries in level I, II, III and IV hospitals, respectively. The total number of obstetric hospitals decreased over the study period, while the proportion of hospitals with high-level (level III or IV) maternal care increased. High-level hospitals were located in more densely populated areas.ConclusionIdentification of the level of maternal care, independent of hospital self-reported variables, is feasible using administrative data. This empiric approach, which accounts for changes in hospitals over time, is a valuable framework for perinatal researchers and other stakeholders to inexpensively identify measurable benefits of levels of maternal care and characterize where specific patient populations receive care.

Project description:Background: Neonatal intensive care unit (NICU) patient satisfaction is measured as parent satisfaction. Parents are critical to the family-centered care model and can evaluate care. Several EMpowerment of PArents in THe Intensive Care (EMPATHIC) instruments were developed in the Netherlands to measure parent satisfaction with neonatal and pediatric intensive care. EMPATHIC instruments comprise five domains and a total score: information, care and treatment, organization, parental participation, and professional attitude. To our knowledge, the EMPATHIC has not been adapted for USA use. Objectives: (1) To select a relevant EMPATHIC instrument for our study. (2) To expand the content reflecting the role of nurses and the cultural heterogeneity of USA NICU infants. (3) To adapt the selected EMPATHIC instrument to USA English. (4) To establish psychometric properties of the linguistically adapted instrument. (5) To evaluate instrument performance with additional items. Methods: The EMPATHIC-30 was selected based on shortest length, high overlap with neonatal EMPATHIC-N, and availability of a validated Spanish-language version. Six items from the EMPATHIC-N were added, two of which were split into separate items, resulting in the EMPATHIC-38. A neonatal nurse practitioner adapted wording to USA English. Cognitive debriefing was performed with eight NICU parents to evaluate adapted wording. Parent survey data from a study about missed nursing care and NICU parent satisfaction were utilized. Internal consistency of the five domains and overall score was measured by Cronbach's alpha. Spearman's rank correlations were computed for domains and overall score with four validity measures. Differential validity was determined using 13 parent demographic subgroups. Results: Data were from 282 parents. Parent race was predominantly White (61%) or Black (22%). One fifth were Hispanic. The adapted wording was satisfactory. Four of the five EMPATHIC-30 and EMPATHIC-38 domains had Cronbach alphas at or above 0.70, indicating acceptable reliability. Correlations between the domain, total scores, and validity indicators ranged from 0.30 to 0.57, indicating positive, moderate associations. Results were replicated in demographic subgroups. Reliability and validity of the three domains with additional items were better than or equivalent to values for the original. Conclusion: The linguistically adapted EMPATHIC-30-NICU-USA and the expanded EMPATHIC-38-NICU-USA exhibit satisfactory psychometric properties and are suitable for use in USA NICUs.

Project description:BackgroundChronic obstructive pulmonary disease (COPD) is the fourth leading cause of death among US adults and is projected to be the third by 2020. In anticipation of the increasing burden imposed on healthcare systems and payers by patients with COPD, a means of identifying COPD patients who incur higher healthcare utilization and costs is needed.MethodsThis retrospective, cross-sectional analysis of US managed care administrative claims data describes a practical way to identify COPD patients. We analyze 7.79 million members for potential inclusion in the COPD cohort, who were continuously eligible during a 1-year study period. A younger commercial population (7.7 million) is compared with an older Medicare population (0.115 million). We outline a novel approach to stratifying COPD patients using "complexity" of illness, based on occurrence of claims for given comorbid conditions. Additionally, a unique algorithm was developed to identify and stratify COPD exacerbations using claims data.ResultsA total of 42,565 commercial (median age 56 years; 51.4% female) and 8507 Medicare patients (median 75 years; 53.1% female) were identified as having COPD. Important differences were observed in comorbidities between the younger commercial versus the older Medicare population. Stratifying by complexity, 45.0%, 33.6%, and 21.4% of commercial patients and 36.6%, 35.8%, and 27.6% of older patients were low, moderate, and high, respectively. A higher proportion of patients with high complexity disease experienced multiple (≥2) exacerbations (61.7% commercial; 49.0% Medicare) than patients with moderate- (56.9%; 41.6%), or low-complexity disease (33.4%; 20.5%). Utilization of healthcare services also increased with an increase in complexity.ConclusionIn patients with COPD identified from Medicare or commercial claims data, there is a relationship between complexity as determined by pulmonary and non-pulmonary comorbid conditions and the prevalence of exacerbations and utilization of healthcare services. Identification of COPD patients at highest risk of exacerbations using complexity stratification may facilitate improved disease management by targeting those most in need of treatment.

Dataset Information

Identifying neonatal intensive care (NICU) admissions using administrative claims data.

Background

Methods

Results

Conclusions

Publications

Identifying neonatal intensive care (NICU) admissions using administrative claims data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets