A descriptive research study was performed to investigate the completeness of the ICD-10-CM coding system in capturing public health diseases when compared to ICD-9-CM. In order to do this, the infectious and reportable public health conditions\u2014such as avian flu, smallpox, anthrax, and such\u2014were examined first by reviewing each state department of health\u2019s website to determine which diseases are required to be reported. Once this list was developed, it was supplemented with the CDC national reportable disease listing. The final list of public health reportable infectious diseases included all the reportable infectious diseases by state as well as those required by CDC. This list was supplemented with two other areas that are very pertinent to public health\u2014the top 10 causes of mortality:<\/p>\n
\u25cfAccidents<\/p>\n
\u25cfAlzheimer\u2019s disease<\/p>\n
\u25cfCerebrovascular disease<\/p>\n
\u25cfDiabetes mellitus<\/p>\n
\u25cfInfluenza<\/p>\n
\u25cfLower respiratory disease<\/p>\n
\u25cfNephritis<\/p>\n
\u25cfSepticemia<\/p>\n
\u25cfHeart disease<\/p>\n
\u25cfThe top five malignant neoplasms<\/p>\n
And the classification of death and injury resulting from terrorism list, including 10 major categories as follows:<\/p>\n
\u25cfTerrorism involving explosion of marine weapons<\/p>\n
\u25cfDestruction of aircraft<\/p>\n
\u25cfOther explosions and fragments<\/p>\n
\u25cfFires<\/p>\n
\u25cfFirearms<\/p>\n
\u25cfNuclear weapons<\/p>\n
\u25cfBiological weapons<\/p>\n
\u25cfChemical weapons<\/p>\n
\u25cfTerrorism other specified<\/p>\n
\u25cfSequelae of terrorism<\/p>\n
A total of 248 public health disease categories were developed. When coding the diseases, several more codes and descriptions were listed so that the number of codes far exceeded the 248 disease categories. A website was then developed so that all of the public health diseases and descriptions could be easily accessed by the researchers and the focus group members. For example, when organizing the reportable disease list on the website, every disease was categorized alphabetically. When the specific reportable disease was accessed, a spreadsheet with each of the ICD-9-CM and ICD-10-CM codes could be easily viewed. This was extremely useful for reviewing the codes, rankings, explanations for using a specific ranking, and so forth. Although the list of 248 disease categories is not exhaustive of all public health diseases, it was believed to provide an adequate number to make comparisons between the two coding systems. The 248 public health diseases were then coded using both ICD-9-CM and ICD-10-CM so that comparisons between the two coding systems could be made. The research coder for this study has a master\u2019s of science degree in information science and is a registered health information administrator (RHIA) and has taught coding for more than 20 years. She was also trained and educated on the ICD-10-CM coding system through AHIMA\u2019s online ICD-10-CM coding seminars. The research assistant, who performed data entry and assisted in some of the ICD-10-CM coding, has a master\u2019s of science degree in health information systems and was also trained and educated on the ICD-10-CM coding system. All final codes were approved by a research coder. Quality checks for final codes were performed by a secondary investigator, who has a doctorate in public health and is an RHIA and certified coding specialist (CCS); and also by the principal investigator, who has a doctorate in epidemiology and is an RHIA.<\/p>\n
Comparison tables that describe the specificity of the coding for ICD-9-CM and ICD-10-CM for each of the public health diseases were developed. A ranked score was assigned to each public health disease for both the ICD-10-CM and ICD-9-CM coding systems. The ranking was determined by comparing the number of codes, level of specificity, and ability of the code description to fully capture the diagnostic term. The ranked or ordinal scale consisted of the following:<\/p>\n
5 = Diagnosis is fully captured by the code(s) (all codes, specificity, description is found)<\/p>\n
4 = Diagnosis is almost fully captured by the code(s) (minor detail is missing)<\/p>\n
3 = Diagnosis is partially captured by the code(s) (moderate detail is missing)<\/p>\n
2 = Diagnosis is less than partially captured by the code(s) (major detail is missing)<\/p>\n
1 = Diagnosis is not captured by the code(s) (codes, specificity, description is not found)<\/p>\n
The ranking scale was developed by the research team and reviewed and approved by the focus group members. All assigned rankings were also reviewed and approved by the research team and by all focus group members. Researchers do acknowledge that there was some subjectivity involved in the assignment of the rankings.<\/p>\n
Once all rankings were assigned, a focus group that included seven experts in ICD-9-CM, ICD-10-CM, and public health convened. Two of the focus group members have medical degrees, two are working on their doctorates in public health and have extensive education and training in coding, and three have coding credentials and have worked in the coding field for more than 10 years. The purpose of the focus group was to review and examine the information accumulated from the study and provide feedback and recommendations regarding where changes need to be made in the ICD-10-CM system. Therefore, the focus group examined the rankings and made changes. The researchers reviewed and discussed all comments from the focus group, clarifying any questions, and then made the appropriate changes to the rankings and code descriptions. In the analysis of all the public health diseases, such as reportable diseases (p < 0.001), top 10 causes of death (p < 0.001), and those related to terrorism (p < 0.001), it was found that the overall rankings for disease capture for ICD-10-CM were significantly higher than the rankings for ICD-9-CM. In this example the p value is a statistic that demonstrates statistical significance. It is computed by running statistical tests to determine if the differences between ICD-9-CM and ICD-10-CM rankings were real or due to chance. If the p value is less than 0.05, the differences seen are not due to chance and it demonstrates that what was found in this study is real. (Watzlaf et al. 2007).<\/p>\n
Watzlaf V.J.M., J.H. Garvin, S. Moeini, and P. Anania-Firouzan. 2007. The effectiveness of ICD-10-CM in capturing public health diseases. Perspectives in Health Information Management.<\/i> 4(6).World Health Organization. 2015. http:\/\/www.who.int\/en\/.<\/p>\nReal-World Case Discussion Questions<\/h1>\n
1.A descriptive research study was performed to investigate the completeness of the ICD-10-CM coding system in capturing public health diseases when compared to ICD-9-CM. In order to do this, the infectious and reportable public health conditions\u2014such as avian flu, smallpox, anthrax, and such\u2014were examined first. Explain why it would be important to examine infectious and reportable public health conditions when examining ICD-10 and ICD-9 classification systems?<\/p>\n
2.Confirm whether or not the research team for this study had appropriate experience to conduct and participate in the study? Why or why not?<\/p>\n
3.A ranked score was assigned to each public health disease for both the ICD-10-CM and ICD-9-CM coding systems. Identify what this ranked scoring system looked like and do you believe that is was an objective scoring system? If not, explain why.<\/p>\n
4.Explain the final results and conclusions that can be made from this study?<\/p><\/p>\n \n
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