OBJECTIVE: The ICD-10-CM classification system contains more specificity than its predecessor ICD-9-CM. A stated reason for transitioning to ICD-10-CM was to increase the availability of detailed data. This study aims to determine whether the increased specificity contained in ICD-10-CM is utilized in the ambulatory care setting and inform an evidence-based approach to evaluate ICD-11 content for implementation planning in the United States. MATERIALS AND METHODS: Diagnosis codes and text descriptions were extracted from a 25% random sample of the IQVIA Ambulatory EMR-US database for 2014 (ICD-9-CM, n = 14 327 155) and 2019 (ICD-10-CM, n = 13 062 900). Code utilization data was analyzed for the total and unique number of codes. Frequencies and tests of significance determined the percentage of available codes utilized and the unspecified code rates for both code sets in each year. RESULTS: Only 44.6% of available ICD-10-CM codes were used compared to 91.5% of available ICD-9-CM codes. Of the total codes used, 14.5% ICD-9-CM codes were unspecified, while 33.3% ICD-10-CM codes were unspecified. DISCUSSION: Even though greater detail is available, a 108.5% increase in using unspecified codes with ICD-10-CM was found. The utilization data analyzed in this study does not support a rationale for the large increase in the number of codes in ICD-10-CM. New technologies and methods are likely needed to fully utilize detailed classification systems. CONCLUSION: These results help evaluate the content needed in the United States national ICD standard. This analysis of codes in the current ICD standard is important for ICD-11 evaluation, implementation, and use.

OBJECTIVE: This study investigated how well-suited the International Classification of Diseases, 11th Revision, for Mortality and Morbidity Statistics, (ICD-11 MMS) is for 2 morbidity use cases, patient safety and quality, examining the level of detail captured, and evaluating the necessity for the development of a US clinical modification (CM). MATERIALS AND METHODS: Utilizing the 5 NCVHS-specified perspectives plus the consumer perspective, a framework was created of International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) use cases. Analysis yielded candidate source criteria for use in case evaluation. Patient safety and quality were chosen because they are relevant across all perspectives.Granularity differences and content coverage of ICD-11 MMS entities were assessed pre- and post-coordination to determine suitability for the 2 use cases. Pressure ulcers, a common condition across 3 patient safety applications, became the focus for comparing ICD-10-CM codes to ICD-11 MMS codes. For 3 electronic clinical quality measures (eCQMs), the evaluation centered on specified value sets for ischemic stroke, hypertension, and diabetes. RESULTS: For pressure ulcers, the ICD-11 MMS was found to exceed ICD-10-CM capabilities via post-coordinated extension codes. For the 3 eCQM value sets explored, the ICD-11 MMS fully represented the disease concepts when post-coordinated code clusters were used. CONCLUSIONS: The examples from the patient safety and quality use cases evaluated in this study are appropriate for ICD-11 MMS. It captures greater detail than ICD-10-CM, and ICD-11 MMS specificity would benefit both use cases. The authors believe this preliminary study indicates the US should invest resources to explore adopting the WHO ICD-11 MMS and tooling and guidelines to implement post-coordination.

The health informatics field continues to evolve and grow. The adoption of electronic health records has increased dramatically. Integrated medical devices, telemedicine, consumer-directed apps, and precision medicine are mainstream. There are continued developments in genomics data mining and pattern recognition. The reimbursement models are rapidly changing and require detailed accountability via measurement and high-quality, integrated data. The data that are collected in the continuum of care can prove truly helpful in evidence-based decision-making and in the sciences, to verify or disprove existing models or theories. The rapid changes in health IT, along with an increasing growth in the reliance on IT in health care, has resulted in an increasing demand for trained workers. A survey by Hoffman and Ash1 and a later study by Hersh2 indicated that the most important skills for health informaticians include knowledge of the following: the use of information in clinical care, change management, relational databases, interoperability standards, and project management and best practices for IT use in the health care setting. The ability to analyze large amounts of structured and unstructured data has also become a requirement for future informaticians. It is indeed challenging to educate the future wave of informaticians and the health professionals who interact with these technologies.

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome.