Changepoint analysis of gestational age and birth weight: proposing a refinement of Diagnosis Related Groups.

BACKGROUND: Although the complexity and length of treatment is connected to the newborn's maturity and birth weight, most case-mix grouping schemes classify newborns by birth weight alone. The objective of this study was to determine whether the definition of thresholds based on a changepoint analysis of variability of birth weight and gestational age contributes to a more homogenous classification. METHODS: This retrospective observational study was conducted at a Tertiary Care Center with Level III Neonatal Intensive Care and included neonate cases from 2016 through 2018. The institutional database of routinely collected health data was used. The design of this cohort study was explorative. The cases were categorized according to WHO gestational age classes and SwissDRG birth weight classes. A changepoint analysis was conducted. Cut-off values were determined. RESULTS: When grouping the cases according to the calculated changepoints, the variability within the groups with regard to case related costs could be reduced. A refined grouping was achieved especially with cases of >2500 g birth weight. An adjusted Grouping Grid for practical purposes was developed. CONCLUSIONS: A novel method of classification of newborn cases by changepoint analysis was developed, providing the possibility to assign costs or outcome indicators to grouping mechanisms by gestational age and birth weight combined.

The Robson classification for caesarean section-A proposed method based on routinely collected health data.

BACKGROUND: With an increasing rate of caesarean sections as well as rising numbers of multiple pregnancies, valid classifications for benchmarking are needed. The Robson classification provides a method to group cases with caesarean section in order to assess differences in outcome across regions and sites. In this study we set up a novel method of classification by using routinely collected health data. We hypothesize i that routinely collected health data can be used to apply complex medical classifications and ii that the Robson classification is capable of classifying mothers and their corresponding newborn into meaningful groups with regard to outcome. METHODS AND FINDINGS: The study was conducted at the coding department and the department of obstetrics and gynecology Inselspital, University Hospital of Bern, Switzerland. The study population contained inpatient cases from 2014 until 2017. Administrative and health data were extracted from the Data Warehouse. Cases were classified by a Structured Query Language code according to the Robson criteria using data from the administrative system, the electronic health record and from the laboratory system. An automated query to classify the cases according to Robson could be implemented and successfully validated. A linkage of the mother's class to the corresponding newborn could be established. The distribution of clinical indicators was described. It could be shown that the Robson classes are associated to outcome parameters and case related costs. CONCLUSIONS: With this study it could be demonstrated, that a complex query on routinely collected health data would serve for medical classification and monitoring of quality and outcome. Risk-stratification might be conducted using this data set and should be the next step in order to evaluate the Robson criteria and outcome. This study will enhance the discussion to adopt an automated classification on routinely collected health data for quality assurance purposes.

Increased Expiratory Computed Tomography Density Reveals Possible Abnormalities in Radiologically Preserved Lung Parenchyma in Idiopathic Pulmonary Fibrosis.

OBJECTIVES: Idiopathic pulmonary fibrosis (IPF) is a progressive lethal chronic lung disease with unclear pathogenesis. Radiological hallmark is the pattern of usual interstitial pneumonia accentuated in peripheral and basal areas with otherwise preserved lung structure. One hypothesis is that alveolar collapse and consequent induration lead to fibrotic transformation of lung tissue. The aim of the study was to investigate normal-appearing tissue during expiration for signs of collapsibility and differences from other diseases or controls. MATERIALS AND METHODS: We retrospectively assessed a total of 43 patients (15 IPFs, 13 chronic obstructive pulmonary diseases, and 15 controls) with nonenhanced computed tomography (CT) in inspiration and expiration, performed for routine clinical workup. Densitometry of visually unaffected lung tissue was conducted in all lung lobes with a region of interest of 15-mm in diameter on soft tissue kernel reconstruction (slice thickness, 1 mm) during inspiration and expiration. RESULTS: One-factor analysis of variance analysis yielded significant difference in attenuation changes between inspiration and expiration of unaffected lung parenchyma among all subject groups in all lung lobes. For IPF patients, the highest differences in densities were observed in the lower lobes, which is the predominantly affected site of usual interstitial pneumonia. In the chronic obstructive pulmonary disease group, the density remained rather equal in the entire lung. CONCLUSIONS: High CT attenuation changes between inspiration and expiration in IPF patients might suggest altered lung parenchyma in normal-appearing tissue on CT. Density changes during the respiratory cycle might be explained by alveolar collapse of radiologically unaffected lung tissue possibly preceding fibrosis. These results support the concept of alveolar collapse preceding lung fibrosis in IPF.