Avoidable morbidity in infants. A classification based on diagnoses in administrative databases
Related Experiment Video
Updated: Nov 2, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
K M McConnochie1, K J Roghmann, G S Liptak
1Department of Pediatrics, University of Rochester School of Medicine, NY, USA.
Objectives:
A hierarchical classification for avoidable morbidity in infants was developed based on a conceptual model for causes of morbidity. Experts rated the impact of risk factors and health services on diseases coded according to the International Classification of Diseases, 9th Revision, Classification Modification (ICD-9-CM). An etiologic framework was chosen for the classification because knowledge of etiology often suggests strategies for prevention. Causes of morbidity that cluster on the basis of similar risk factors might be avoided using similar strategies.
Methods:
Diseases (346 different diagnoses) were rated by 16 general pediatricians; 12 attributes were considered, including the impact on disease occurrence and on severity of five risk factors, preventive health services, and medical treatment. Raters evaluated the impact of health services, constitutional risk factors, and environmental risk factors without regard for service site (eg, inpatient, emergency department, primary care office). Environmental risk factors categories, including family, social, and physical environments, were rated separately. The impact of health services was rated on prevention, treatment, and complications of care.
Results:
Only ratings indicating that the impact of a risk factor category was substantial were used for the final classification of 275 diagnoses. Consistent with the multifactorial etiology of many diseases, many diagnoses had ratings indicating substantial impact of multiple risk factors. Five mutually exclusive clusters were derived from the 12 ratings based on factor analysis and recognized strategies for prevention. Ordered by level of avoidability, these clusters were termed vaccine-preventable, health-care quality indicators, environmental, environmental/constitutional, and constitutional.
Conclusions:
The usefulness of this classification for policy-oriented epidemiologic and health services research is grounded in the premise that prevention is the cardinal objective of child health policy. Cluster-specific hospitalization rates, ie, rates aggregated for all diagnoses falling in a cluster, might be used for allocating resources to interventions directed at environmental or health service determinants of morbidity. Widespread use of ICD-9-CM codes in hospital discharge and ambulatory databases suggests many potential applications for this classification of morbidity burden in population groups.
Related Concept Videos
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 assessment...
Classification of Illness
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe and...
Nursing Interventions II: Selecting and Classifying the Nursing Interventions
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...
Nursing Diagnosis
The nursing diagnosis focuses on evidence-based...
Formulating and Validating Nursing Diagnosis I
There are thirteen domains for...