There are important reasons for delaying implementation of the new ICD-10 coding system

Assessing the impact of transitioning to 11th revision of the International Classification of Diseases (ICD-11) on comorbidity indices

OBJECTIVES

This study aimed to support the implementation of the 11th Revision of the International Classification of Diseases (ICD-11). We used common comorbidity indices as a case study for proactively assessing the impact of transitioning to ICD-11 for mortality and morbidity statistics (ICD-11-MMS) on real-world data analyses.

MATERIALS AND METHODS

Using the MIMIC IV database and a table of mappings between the clinical modification of previous versions of ICD and ICD-11-MMS, we assembled a population whose diagnosis can be represented in ICD-11-MMS. We assessed the impact of ICD version on cross-sectional analyses by comparing the populations' distribution of Charlson and Elixhauser comorbidity indices (CCI, ECI) across different ICD versions, along with the adjustment in comorbidity weighting.

RESULTS

We found that ICD versioning could lead to (1) alterations in the population distribution and (2) changes in the weight that can be assigned to a comorbidity category in a reweighting initiative. In addition, this study allowed the creation of the corresponding ICD-11-MMS codes list for each component of the CCI and the ECI.

DISCUSSION

In common with the implementations of previous versions of ICD, implementation of ICD-11-MMS potentially hinders comparability of comorbidity burden on health outcomes in research and clinical settings.

CONCLUSION

Further research is essential to enhance ICD-11-MMS usability, while mitigating, after identification, its adverse effects on comparability of analyses.

Problems and Barriers during the Process of Clinical Coding: a Focus Group Study of Coders' Perceptions

Coded data are the basis of information systems in all countries that rely on Diagnosis Related Groups in order to reimburse/finance hospitals, including both administrative and clinical data. To identify the problems and barriers that affect the quality of the coded data is paramount to improve data quality as well as to enhance its usability and outcomes. This study aims to explore problems and possible solutions associated with the clinical coding process. Problems were identified according to the perspective of ten medical coders, as the result of four focus groups sessions. This convenience sample was sourced from four public hospitals in Portugal. Questions relating to problems with the coding process were developed from the literature and authors' expertise. Focus groups sessions were taped, transcribed and analyzed to elicit themes. Variability in the documents used for coding, illegibility of hand writing when coding on paper, increase of errors due to an extra actor in the coding process when transcribed from paper, difficulties in the diagnoses' coding, coding delay and unavailability of resources and tools designed to help coders, were some of the problems identified. Some problems were identified and solutions such as the standardization of the documents used for coding an episode, the adoption of the electronic coding, the development of tools to help coding and audits, and the recognition of the importance of coding by the management were described as relevant factors for the improvement of the quality of data.

The necessity to develop a national classification system for Iranian traditional medicine

BACKGROUND

Classification of disease and interventions in traditional medicine (TM) is necessary for standardised coding of information. Currently, in Iran, there is no standard electronic classification system for disease and interventions in TM.

OBJECTIVE

The current study aimed to develop a national framework for the classification of disease and intervention in Persian medicine based on expert opinion.

METHOD

A descriptive cross-sectional study was carried out in 2018. The existing systems for the classification of disease and interventions in TM were reviewed in detail, and some of the structural and content characteristics were extracted for the development of the classification of Iranian traditional medicine. Based on these features, a self-administered questionnaire was developed. Study participants (25) were experts in the field of Persian medicine and health information management in Tehran medical universities.

RESULTS

Main axes for the classification of disease and interventions were determined. The most important applications of the classification system were related to clinical coding, policymaking, reporting of mortality and morbidity data, cost analysis and determining the quality indicators. Half of the participants (50%) stated that the classification system should be designed by maintaining the main axis of the World Health Organization classification system and changing the subgroups if necessary. A computer-assisted coding system for TM was proposed for the current study.

CONCLUSION

Development of this classification system will provide nationally comparable data that can be widely used by governments, national organisations and academic researchers.

Using Electronic Health Records To Generate Phenotypes For Research

Electronic health records contain patient-level data collected during and for clinical care. Data within the electronic health record include diagnostic billing codes, procedure codes, vital signs, laboratory test results, clinical imaging, and physician notes. With repeated clinic visits, these data are longitudinal, providing important information on disease development, progression, and response to treatment or intervention strategies. The near universal adoption of electronic health records nationally has the potential to provide population-scale real-world clinical data accessible for biomedical research, including genetic association studies. For this research potential to be realized, high-quality research-grade variables must be extracted from these clinical data warehouses. We describe here common and emerging electronic phenotyping approaches applied to electronic health records, as well as current limitations of both the approaches and the biases associated with these clinically collected data that impact their use in research. © 2018 by John Wiley & Sons, Inc.

A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals

OBJECTIVE

To compare the Agency for Healthcare Research and Quality's Quality and Safety Review System (QSRS) and the proposed triadic structure for the 11th version of the International Classification of Disease (ICD-11) in their ability to capture adverse events in U.S. hospitals.

DATA SOURCES/STUDY SETTING

One thousand patient admissions between 2014 and 2016 from three general, acute care hospitals located in Maryland and Washington D.C.

STUDY DESIGN

The admissions chosen for the study were a random sample from all three hospitals.

DATA COLLECTION/EXTRACTION METHODS

All 1000 admissions were abstracted through QSRS by one set of Certified Coding Specialists and a different set of coders assigned the draft ICD-11 codes. Previously assigned ICD-10-CM codes for 230 of the admissions were also used.

PRINCIPAL FINDINGS

We found less than 20 percent agreement between QSRS and ICD-11 in identifying the same adverse event. The likelihood of a mismatch between QSRS and ICD-11 was almost twice that of a match. The findings were similar to the agreement found between QSRS and ICD-10-CM in identifying the same adverse event. When coders were provided with a list of potential adverse events, the sensitivity and negative predictive value of ICD-11 improved.

CONCLUSIONS

While ICD-11 may offer an efficient way of identifying adverse events, our analysis found that in its draft form, it has a limited ability to capture the same types of events as QSRS. Coders may require additional training on identifying adverse events in the chart if ICD-11 is going to prove its maximum benefit.

Shifts in Alcohol-Related Diagnoses After the Introduction of International Classification of Diseases, Tenth Revision, Clinical Modification Coding in U.S. Hospitals: Implications for Epidemiologic Research

BACKGROUND

In October 2015, the United States transitioned healthcare diagnosis codes from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), to the Tenth Revision (ICD-10-CM). Trend analyses of alcohol-related stays could show discontinuities solely from the change in classification systems. This study examined the impact of the ICD-10-CM coding system on estimates of hospital stays involving alcohol-related diagnoses.

METHODS

This analysis used 2014 to 2017 administrative data from the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project State Inpatient Databases for 17 states. Quarterly ICD-9-CM data from second quarter 2014 through third quarter 2015 were concatenated with ICD-10-CM data from fourth quarter 2015 through first quarter 2017. Quarterly counts of alcohol-related stays were examined overall and then by 6 diagnostic subgroups: withdrawal, abuse, dependence, alcohol-induced mental disorders (AIMD), nonpsychiatric alcohol-induced disease, and intoxication or toxic effects. Within each group, we calculated the difference in the average number of stays between ICD-9-CM and ICD-10-CM coding periods.

RESULTS

On average, the number of stays involving any alcohol-related diagnosis in the 6 quarters before and after the ICD-10-CM transition was stable. However, substantial shifts in stays occurred for alcohol abuse, AIMD, and intoxication or toxic effects. For example, the average quarterly number of stays involving AIMD was 170.7% higher in the ICD-10-CM period than in the ICD-9-CM period. This increase was driven in large part by 1 ICD-10-CM code, Alcohol use, unspecified with unspecified alcohol-induced disorder.

CONCLUSIONS

Researchers conducting trend analyses of inpatient stays involving alcohol-related diagnoses should consider how ongoing modifications in the ICD-10-CM code system and coding guidelines might affect their work. An advisable approach for trend analyses across the ICD-10-CM transition is to aggregate diagnosis codes into broader, clinically meaningful groups-including a single global group that encompasses all alcohol-related stays-and then to select diagnostic groupings that minimize discontinuities between the 2 coding systems while providing useful information on this important indicator of population health.

A Census of Disease Ontologies

For centuries, humans have sought to classify diseases based on phenotypic presentation and available treatments. Today, a wide landscape of strategies, resources, and tools exist to classify patients and diseases. Ontologies can provide a robust foundation of logic for precise stratification and classification along diverse axes such as etiology, development, treatment, and genetics. Disease and phenotype ontologies are used in four primary ways: ( a) search, retrieval, and annotation of knowledge; ( b) data integration and analysis; ( c) clinical decision support; and ( d) knowledge discovery. Computational inference can connect existing knowledge and generate new insights and hypotheses about drug targets, prognosis prediction, or diagnosis. In this review, we examine the rise of disease and phenotype ontologies and the diverse ways they are represented and applied in biomedicine.

The complexity and challenges of the International Classification of Diseases, Ninth Revision, Clinical Modification to International Classification of Diseases, 10th Revision, Clinical Modification transition in EDs

Beginning October 2015, the Center for Medicare and Medicaid Services will require medical providers to use the vastly expanded International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) system. Despite wide availability of information and mapping tools for the next generation of the ICD classification system, some of the challenges associated with transition from ICD-9-CM to ICD-10-CM are not well understood. To quantify the challenges faced by emergency physicians, we analyzed a subset of a 2010 Illinois Medicaid database of emergency department ICD-9-CM codes, seeking to determine the accuracy of existing mapping tools in order to better prepare emergency physicians for the change to the expanded ICD-10-CM system. We found that 27% of 1830 codes represented convoluted multidirectional mappings. We then analyzed the convoluted transitions and found that 8% of total visit encounters (23% of the convoluted transitions) were clinically incorrect. The ambiguity and inaccuracy of these mappings may impact the workflow associated with the translation process and affect the potential mapping between ICD codes and Current Procedural Codes, which determine physician reimbursement.

ICD-10-CM Crosswalks in the primary care setting: assessing reliability of the GEMs and reimbursement mappings

OBJECTIVE

The general equivalence mappings (GEMs) and reimbursement mappings (RMs) facilitate translation between ICD-9-CM and ICD-10-CM. This study compared prospectively dual-encoded diagnoses assigned by professional coders with the GEMs/RMs in a clinical setting.

MATERIALS AND METHODS

Professional coders manually encoded diagnoses from 100 primary care notes into both ICD-9-CM and ICD-10-CM. The investigators evaluated whether manual mappings were reproducible using the GEMs/RMs. Reproducible mappings with one ICD-9-CM and one ICD-10-CM code ("one-to-one") were classified as exact or approximate using GEMs flags. Mismatches were characterized manually.

RESULTS

Manual encodings were reproducible from the forward GEMs, backward GEMs, and RMs in 85.2%, 90.4%, and 88.1% of diagnoses, respectively. For one-to-one, reproducible mappings, 61% (forward) and 63% (backward) were approximate mappings compared to 85% and 95% in the GEMs as a whole. Mismatches between manual and GEMs encodings were due to differences in coder interpretation (11%-13%), subtle hierarchical differences (52%-55%), or unknown reasons (32%-35%).

DISCUSSION

This study highlights inconsistencies between manual encoding and using the GEMs/RMs. The number of approximate mappings in our population compared to all one-to-one GEMs entries supports the notion that statistics describing the GEMs as a whole might not represent the most important mappings for each organization. The mismatch characteristics highlight the subtle differences between manual encoding and using the GEMs/RMs.

CONCLUSION

These results support the need for organizations to assess the GEMs and RMs in their own environment to avoid changes in reimbursement and longitudinal statistics.

Challenges and remediation for Patient Safety Indicators in the transition to ICD-10-CM

Reporting of hospital adverse events relies on Patient Safety Indicators (PSIs) using International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes. The US transition to ICD-10-CM in 2015 could result in erroneous comparisons of PSIs. Using the General Equivalent Mappings (GEMs), we compared the accuracy of ICD-9-CM coded PSIs against recommended ICD-10-CM codes from the Centers for Medicaid/Medicare Services (CMS). We further predict their impact in a cohort of 38,644 patients (1,446,581 visits and 399 hospitals). We compared the predicted results to the published PSI related ICD-10-CM diagnosis codes. We provide the first report of substantial hospital safety reporting errors with five direct comparisons from the 23 types of PSIs (transfusion and anesthesia related PSIs). One PSI was excluded from the comparison between code sets due to reorganization, while 15 additional PSIs were inaccurate to a lesser degree due to the complexity of the coding translation. The ICD-10-CM translations proposed by CMS pose impending risks for (1) comparing safety incidents, (2) inflating the number of PSIs, and (3) increasing the variability of calculations attributable to the abundance of coding system translations. Ethical organizations addressing 'data-, process-, and system-focused' improvements could be penalized using the new ICD-10-CM Agency for Healthcare Research and Quality PSIs because of apparent increases in PSIs bearing the same PSI identifier and label, yet calculated differently. Here we investigate which PSIs would reliably transition between ICD-9-CM and ICD-10-CM, and those at risk of under-reporting and over-reporting adverse events while the frequency of these adverse events remain unchanged.

The transition to ICD-10-CM: challenges for pediatric practice

BACKGROUND AND OBJECTIVES

Diagnostic codes are used widely within health care for billing, quality assessment, and to measure clinical outcomes. The US health care system will transition to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), in October 2015. Little is known about how this transition will affect pediatric practices. The objective of this study was to examine how the transition to ICD-10-CM may result in ambiguity of clinical information and financial disruption for pediatricians.

METHODS

Using a statewide data set from Illinois Medicaid specified for pediatricians, 2708 International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis codes were identified. Diagnosis codes were categorized into 1 of 5 categories: identity, class-to-subclass, subclass-to-class, convoluted, and no translation. The convoluted and high-cost diagnostic codes (n = 636) were analyzed for accuracy and categorized into "information loss," "overlapping categories," "inconsistent," and "consistent." Finally, reimbursement by Medicaid was calculated for each category.

RESULTS

Twenty-six percent of pediatric diagnosis codes are convoluted, which represents 21% of Illinois Medicaid pediatric patient encounters and 16% of reimbursement. The diagnosis codes represented by information loss (3.6%), overlapping categories (3.2%), and inconsistent (1.2%) represent 8% of Medicaid pediatric reimbursement.

CONCLUSIONS

The potential for financial disruption and administrative errors from 8% of reimbursement diagnosis codes necessitates special attention to these codes in preparing for the transition to ICD-10-CM for pediatric practices.

The ICD-10 system: a gift that keeps on taking

The Protecting Access to Medicare Act of 2014 was signed into law on April Fool's Day. Indeed, 2014 saw unprecedented enthusiasm for the possibility of a permanent solution to the sustainable growth rate formula. Congress failed to come together on methods to pay for that fix. Instead, Congress provided another temporary patch on April 1. As part of that law, International Classification of Diseases-10 (ICD-10) adoption was pushed back by at least 1 year until, at the earliest, October 1, 2015. While many physicians support the delay in ICD-10 implementation, there are those that disagree.

The long road to semantic interoperability in support of public health: experiences from two states

Proliferation of health information technologies creates opportunities to improve clinical and public health, including high quality, safer care and lower costs. To maximize such potential benefits, health information technologies must readily and reliably exchange information with other systems. However, evidence from public health surveillance programs in two states suggests that operational clinical information systems often fail to use available standards, a barrier to semantic interoperability. Furthermore, analysis of existing policies incentivizing semantic interoperability suggests they have limited impact and are fragmented. In this essay, we discuss three approaches for increasing semantic interoperability to support national goals for using health information technologies. A clear, comprehensive strategy requiring collaborative efforts by clinical and public health stakeholders is suggested as a guide for the long road towards better population health data and outcomes.