Administrative coding data and health care-associated infections.

Area of Science:

• Health care epidemiology
• Infection control
• Health informatics

Background:

• Health care-associated infections (HAIs) surveillance is crucial for patient safety and public health reporting.
• Administrative data, including International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, are increasingly considered for HAI surveillance.
• Electronic surveillance systems are being developed to meet mandatory public reporting demands for HAIs.

Purpose of the Study:

• To evaluate the utility of administrative data, specifically ICD-9-CM codes, for health care-associated infection surveillance.
• To explore the potential of ICD-9-CM codes in facilitating automated surveillance and freeing up infection control personnel.
• To address the controversy surrounding the appropriate use of administrative coding data in HAI detection.

Main Methods:

• Analysis of administrative data, focusing on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes.
• Comparison of administrative data-based surveillance with traditional methods for detecting health care-associated infections.
• Assessment of the attributes of ICD-9-CM codes for automated surveillance capabilities.

Main Results:

• ICD-9-CM codes possess characteristics suitable for detecting health care-associated infections (HAIs) and enabling automated surveillance.
• Administrative coding data have been criticized for lacking essential elements required for comprehensive HAI surveillance.
• The use of administrative coding data as the sole method for HAI surveillance is considered inappropriate.

Conclusions:

• Administrative data, particularly ICD-9-CM codes, can be a valuable tool to augment traditional health care-associated infection surveillance methods.
• While ICD-9-CM data can facilitate automated surveillance, they are not a substitute for comprehensive infection control practices.
• Further research and validation are needed to optimize the integration of administrative data into HAI surveillance systems.