Relevant bibliographies by topics / ICD-10-CM

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'ICD-10-CM'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 April 2022

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Journal articles on the topic "ICD-10-CM"

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Waguespack, Richard W., and Rhonda Buckholtz. "ICD-9-CM to ICD-10-CM Transition." Otolaryngology–Head and Neck Surgery 145, no. 2_suppl (August 2011): P10—P11. http://dx.doi.org/10.1177/0194599811415818a8.

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Parman, Cindy. "ICD-10-CM Updates!" Oncology Issues 31, no. 6 (November 2016): 12–16. http://dx.doi.org/10.1080/10463356.2016.11884133.

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Cartwright, Donna J. "ICD-9-CM to ICD-10-CM Codes: What? Why? How?" Advances in Wound Care 2, no. 10 (December 2013): 588–92. http://dx.doi.org/10.1089/wound.2013.0478.

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Parman, Cindy. "Still More ICD-10-CM Updates!" Oncology Issues 33, no. 6 (November 2, 2018): 8–12. http://dx.doi.org/10.1080/10463356.2018.1536109.

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Hodorowicz, Mary Ann. "New ICD-10-CM Coding System." AADE in Practice 4, no. 2 (February 19, 2016): 12–15. http://dx.doi.org/10.1177/2325160316629899.

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Wu, Patrick, Aliya Gifford, Xiangrui Meng, Xue Li, Harry Campbell, Tim Varley, Juan Zhao, et al. "Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation." JMIR Medical Informatics 7, no. 4 (November 29, 2019): e14325. http://dx.doi.org/10.2196/14325.

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Background The phecode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) using the electronic health record (EHR). Objective The goal of this paper was to develop and perform an initial evaluation of maps from the International Classification of Diseases, 10th Revision (ICD-10) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes to phecodes. Methods We mapped ICD-10 and ICD-10-CM codes to phecodes using a number of methods and resources, such as concept relationships and explicit mappings from the Centers for Medicare & Medicaid Services, the Unified Medical Language System, Observational Health Data Sciences and Informatics, Systematized Nomenclature of Medicine-Clinical Terms, and the National Library of Medicine. We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM phecode map by investigating phenotype reproducibility and conducting a PheWAS. Results We mapped >75% of ICD-10 and ICD-10-CM codes to phecodes. Of the unique codes observed in the UKBB (ICD-10) and VUMC (ICD-10-CM) cohorts, >90% were mapped to phecodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease for phenotypes sourced from the ICD-10-CM phecode map. Using the ICD-9-CM and ICD-10-CM maps, we conducted a PheWAS with a Lipoprotein(a) genetic variant, rs10455872, which replicated two known genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P<.001; odds ratio (OR) 1.60 [95% CI 1.43-1.80] vs ICD-10-CM: P<.001; OR 1.60 [95% CI 1.43-1.80]) and chronic ischemic heart disease (ICD-9-CM: P<.001; OR 1.56 [95% CI 1.35-1.79] vs ICD-10-CM: P<.001; OR 1.47 [95% CI 1.22-1.77]). Conclusions This study introduces the beta versions of ICD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for PheWAS in the EHR.
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Cartagena, F. Phil, Molly Schaeffer, Dorothy Rifai, Victoria Doroshenko, and Howard S. Goldberg. "Leveraging the NLM map from SNOMED CT to ICD-10-CM to facilitate adoption of ICD-10-CM." Journal of the American Medical Informatics Association 22, no. 3 (March 13, 2015): 659–70. http://dx.doi.org/10.1093/jamia/ocu042.

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Abstract Objective Develop and test web services to retrieve and identify the most precise ICD-10-CM code(s) for a given clinical encounter. Facilitate creation of user interfaces that 1) provide an initial shortlist of candidate codes, ideally visible on a single screen; and 2) enable code refinement. Materials and Methods To satisfy our high-level use cases, the analysis and design process involved reviewing available maps and crosswalks, designing the rule adjudication framework, determining necessary metadata, retrieving related codes, and iteratively improving the code refinement algorithm. Results The Partners ICD-10-CM Search and Mapping Services (PI-10 Services) are SOAP web services written using Microsoft's.NET 4.0 Framework, Windows Communications Framework, and SQL Server 2012. The services cover 96% of the Partners problem list subset of SNOMED CT codes that map to ICD-10-CM codes and can return up to 76% of the 69 823 billable ICD-10-CM codes prior to creation of custom mapping rules. Discussion We consider ways to increase 1) the coverage ratio of the Partners problem list subset of SNOMED CT codes and 2) the upper bound of returnable ICD-10-CM codes by creating custom mapping rules. Future work will investigate the utility of the transitive closure of SNOMED CT codes and other methods to assist in custom rule creation and, ultimately, to provide more complete coverage of ICD-10-CM codes. Conclusions ICD-10-CM will be easier for clinicians to manage if applications display short lists of candidate codes from which clinicians can subsequently select a code for further refinement. The PI-10 Services support ICD-10 migration by implementing this paradigm and enabling users to consistently and accurately find the best ICD-10-CM code(s) without translation from ICD-9-CM.
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Seare, J., J. Yang, S. Yu, and V. Zarotsky. "Building a bridge: ICD-9-CM to ICD-10-CM mapping challenges and solutions." Value in Health 17, no. 3 (May 2014): A187. http://dx.doi.org/10.1016/j.jval.2014.03.1094.

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DiSantostefano, Jan. "Getting to Know the ICD-10-CM." Journal for Nurse Practitioners 6, no. 2 (February 2010): 149–50. http://dx.doi.org/10.1016/j.nurpra.2009.11.001.

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Bhakoo, A., and B. P. Olivieri. "ICD-10-CM for the interventional radiologist." Journal of Vascular and Interventional Radiology 26, no. 2 (February 2015): S210. http://dx.doi.org/10.1016/j.jvir.2014.12.560.

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Dissertations / Theses on the topic "ICD-10-CM"

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Butz, Jennifer Anne. "The Transition to ICD-10-CM/PCS: A Comparison of Physician and Coder Perceptions." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1428911324.

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Monestime, Judith. "ICD-10-CM Implementation Strategies: An Application of the Technology Acceptance Model." ScholarWorks, 2015. https://scholarworks.waldenu.edu/dissertations/1909.

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The United States is one of the last countries to transition to the 10th edition of the International Classification of Diseases (ICD-10) coding system. The move from the 35-year-old system, ICD-9, to ICD-10, represents a milestone in the transformation of the 21st century healthcare industry. All covered healthcare entities were mandated to use the ICD-10 system on October 1, 2015, to justify medical necessity, an essential component in determining whether a service is payable or not. Despite the promising outcomes of this shift, more than 70% of healthcare organizations identified concerns related to education efforts, including lack of best practices for the ICD-10 transition. Lack of preparation for the implementation of ICD-10 undermines the clinical, technological, operational, and financial processes of healthcare organizations. This study was an exploration of implementation strategies used to overcome barriers to transition to ICD-10. A single case study was conducted, grounded by the conceptual framework of the technology acceptance model, to learn about ways to mitigate the barriers of this new coding system. Data were gathered from the review of documents, observations, and semistructured interviews with 9 participants of a public healthcare organization in Florida. Data were coded to identify themes. Key themes that emerged from the study included (a) in-depth ICD-10 training, (b) the prevalence of ICD-10 cheat sheets, (c) lack of system readiness, and (d) perception of usefulness of job performance. The results of the study may contribute to social change by identifying successful implementation strategies to mitigate operational disruptions that will allow providers to capture more detailed health information about the severity of patients' conditions.
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Januel, Jean-Marie. "Les données de routine des séjours d’hospitalisation pour évaluer la sécurité des patients : études de la qualité des données et perspectives de validation d’indicateurs de la sécurité des patients." Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10355/document.

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Évaluer la sécurité des patients hospitalisés constitue un enjeu majeur de la gestion des risques pour les services de santé. Le développement d’indicateurs destinés à mesurer les événements indésirables liés aux soins (EIS) est une étape cruciale dont le défi principal repose sur la performance des données utilisées. Le développement d’indicateurs de la sécurité des patients – les Patient Safety Indicators (PSIs) – par l’Agency for Healthcare Research and Quality (AHRQ) aux Etats Unis, utilisant des codes de la 9ème révision (cliniquement modifiée) de la Classification Internationale des Maladies (CIM) présente des perspectives intéressantes. Nos travaux ont abordé cinq questions fondamentales liées au développement de ces indicateurs : la définition du cadre nosologique, la faisabilité de calcul des algorithmes et leur validité, la qualité des données pour coder les diagnostics médicaux à partir de la CIM et leur performance pour comparer plusieurs pays, et la possibilité d’établir une valeur de référence pour comparer ces indicateurs. Certaines questions demeurent cependant et nous proposons des pistes de recherche pour améliorer les PSIs : une meilleure définition des algorithmes et l’utilisation d’autres sources de données pour les valider (i.e., données de registre), ainsi que l’utilisation de modèles d’ajustement utilisant l’index de Charlson, le nombre moyen de diagnostics codés et une variable de la valeur prédictive positive, afin de contrôler les variations du case-mix et les différences de qualité du codage entre hôpitaux et pays
Assessing safety among hospitalized patients is a major issue for health services. The development of indicators to measure adverse events related to health care (HAE) is a crucial step, for which the main challenge lies on the performance of the data used for this approach. Based on the limitations of the measurement in terms of reproducibility and on the high cost of studies conducted using medical records audit, the development of Patient Safety Indicators (PSI) by the Agency for Healthcare Research and Quality (AHRQ) in the United States, using codes from the clinically modified 9th revision of the International Classification of Diseases (ICD) shows interesting prospects. Our work addressed five key issues related to the development of these indicators: nosological definition; feasibility and validity of codes based algorithms; quality of medical diagnoses coding using ICD codes, comparability across countries; and possibility of establishing a benchmark to compare these indicators. Some questions remain, and we suggest several research pathways regarding possible improvements of PSI based on a better definition of PSI algorithms and the use of other data sources to validate PSI (i.e., registry data). Thus, the use of adjustment models including the Charlson index, the average number of diagnoses coded and a variable of the positive predictive value should be considered to control the case-mix variations and differences of quality of coding for comparisons between hospitals or countries
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Teixeira, Juliana Filipa da Rocha. "Impacto da transição ICD-9-CM para a ICD-10-CM/PCS nos internamentos evitáveis em Portugal - um estudo observacional retrospetivo." Dissertação, 2019. https://hdl.handle.net/10216/124737.

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Teixeira, Juliana Filipa da Rocha. "Impacto da transição ICD-9-CM para a ICD-10-CM/PCS nos internamentos evitáveis em Portugal - um estudo observacional retrospetivo." Master's thesis, 2019. https://hdl.handle.net/10216/124737.

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Hsu, Wei-Ting, and 許瑋婷. "Automatically assigning ICD-10-CM codes for inpatients with comorbidity and complication." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/d2wr5a.

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Tien, Ming-Hui, and 田敏慧. "Implementation of ICD-10-CM/PCS at Medical Centers and Regional Hospitals in Taiwan." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/26095667146243228000.

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碩士
國立陽明大學
醫務管理研究所
104
Study Aim: The main purpose of this study was to analyze the correlation between hospitals’ and respondents’ characteristics and the attitudes toward ICD-10 implementation, as well as to identify the most difficult jobs and assistances needed at major hospitals in Taiwan. Materials and Methods: The samples of this study included all of the medical centers and district hospitals in Taiwan. A self-administered structured questionnaire was developed to collect data with response rate of 98%. Descriptive analysis and multiple regression were conducted for the purpose of the study. Main results: 1.The general attitude of ICD-10 implementation had non-significant difference, except for hospital ownership. 2.For the executives support view, it showed although the hospital executives were very concerned about the ICD-10 implementation, but coders were still insufficient current. 3.For professional coders view, it showed the coder although generally had received sufficient education and training current, but in practice a lot of coding consistency of diagnostic or procedure codes had still not a consensus. 4.For the ICD-10 implementation apply to practical work view, the respondent’s attitude was positive. 5.For medical professional’s compliance view , although the coders and physician's communication had no problem, but the physician cannot provide adequate medical messages for coding more complete and accurate. 6.For the government authority view, the government associated units previously had a lot of planning in the implementation process, the government planning and the practice process was still not comprehensive. 7.The respondents considered the coding consulting was the most needed by outside assistance, there were many coding problems encounter currently. Conclusions: This study found that hospital ownership was significantly associated with the attitudes toward ICD-10 implementation. It also found that for ICD-10 implementation, the executive’s support was the most important factor, strengthening physicians’ understanding of ICD-10 needed to be improved the most, and consultation about coding was the help most sought.
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Chen, Kuan-Yu, and 陳冠宇. "A Method for Automatic ICD-10-CM Coding from Clinical Free Text by using UMLS." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/3rryv8.

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Novo, Ricardo Filipe Lopes. "An analysis of all hospitalization causes in mainland Portugal : evolution and the clinical coding." Master's thesis, 2021. http://hdl.handle.net/10400.14/35245.

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Analysing the evolution of all cause-specific hospitalizations at a national level provides important information that comprehends an overall representation of the country healthcare supporting researchers, healthcare managers and decision-makers to efficiently plan and allocate resources (Hoeymans et al., 2012; Rossetto et al., 2019; Swe et al., 2020). In order to delineate policies to address needs and priorities in specific population groups, it is important to assess trends and patterns throughout time by specific characteristics, such as gender and age (Krumholz et al., 2015). Additionally, in Portugal on January 1st 2017 was implemented a new classification system of diseases, International Classification of Diseases, Tenth Revision, Clinical Modification and Procedure Coding System (ICD-10-CM/PCS), which implied a wide adaptation at several levels and which may have affected the hospitalization causes trends (Alonso et al., 2019, 2020). This thesis aims to provide a characterization of how hospitalizations causes have been evolving from 2000 until 2016 by highlighting the main trends and patterns as well as the main differences that have occurred during this period, throughout a retrospective descriptive study. Afterwards, an assessment of the ICD-10-CM/PCS implementation implications on hospitalizations causes trends will be performed with an interrupted time series approach. The results of this study point out evidence of declining trends among allcause hospitalizations in mainland Portugal with some differences according to age and gender among each specific cause. After the characterization of how hospitalizations evolved, we observed that ICD-10-CM/PCS caused variations in some cause-specific hospitalizations, yet, when considering all-cause hospitalizations, no variation due to the transition was found. Therefore, future studies on epidemiological profiles and trends should consider the variations vi ii caused by the codification transition. However, we must be cautious with results as 2017 hospital data completeness still needs to be assured and it would be preferable to include a symmetric distribution before and after the transition, by thus including 2018 as well.
Analisar a evolução de todas as causas específicas de hospitalização a nível nacional fornece informações relevantes onde é compreendida uma representação geral da saúde do país, apoiando pesquisadores, gestores da área da saúde e tomadores de decisão para planear e alocar recursos de forma mais eficiente (Hoeymans et al., 2012; Rossetto et al., 2019; Swe et al., 2020). É importante analisar as tendências e padrões das causas de hospitalização ao longo do tempo e por características específicas, como o sexo e a idade, com o intuito de delinear políticas que atendam às necessidades e prioridades em grupos da população específicos (Krumholz et al., 2015). A 1 de janeiro de 2017 foi implementado, em Portugal, o novo sistema de classificação de doenças, International Classification of Diseases, Tenth Revision, Clinical Modification and Procedure Coding System (ICD-10-CM/PCS), que levou a uma adaptação a vários níveis e que poderá ter afetado a evolução das causas de hospitalização (Alonso et al., 2019, 2020). O objetivo deste estudo é caracterizar a evolução de todas causas de hospitalização de 2000 a 2016, destacando as principais tendências e padrões associados, bem como as principais diferenças ocorridas nesse mesmo período, através de um estudo descritivo retrospetivo. Posteriormente, serão analisadas as implicações da implementação da ICD-10-CM/PCS nas tendências das causas de hospitalização com uma abordagem de séries temporais interrompidas. Os resultados deste estudo demonstraram evidência de tendências decrescentes em todas as hospitalizações ocorridas em Portugal Continental, no entanto, com algumas diferenças consoante a idade, o sexo e a causa específica em questão. Após a caracterização da evolução das hospitalizações observou-se que a implementação da ICD-10-CM/PCS levou a algumas variações em determinadas causas específicas de hospitalização, porém, quando v consideradas todas as hospitalizações nenhuma variação foi associada à transição da codificação. Assim, no futuro estudos sobre perfis e tendências epidemiológicas devem ter em consideração oscilações provocadas pela transição da codificação. No entanto, devemos ser cautelosos com os resultados, pois a completitude dos dados hospitalares do ano de 2017 ainda precisa ser garantida e seria, também, preferível incluir uma distribuição simétrica antes e depois da transição, incluindo assim o ano de 2018.
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Chang, Chiu-ta, and 張久大. "探討健保推動ICD-10-CM/PCS TW-DRGs對住院支付之影響-以中部某醫學中心實際編碼為例." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/64w44j.

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碩士
中國醫藥大學
醫務管理學系碩士在職專班
104
Objective: Since January 1, 2016, the health care reporting code in Taiwan has been fully converted from ICD-9-CM(2001) to ICD-10-CM/PCS(2014). Total coding numbers of ICD-10-CM/PCS is about 8 times to ICD-9-CM coding numbers. The system structure between these two coding system is very different. It may also causes TW-DRGs changes. To estimate the impact on aggregate payments based on the TW-DRGs assigned using ICD-9-CM coded data with the ICD-9-CM version of the TW-DRGs are compared to ICD-10-CM/PCS coded date with the ICD-10-CM/PCS version of the TW-DRGs is very important. Methods: This paper uses the coding data since 2015 January to June. Payment based on the TW-DRGs assigned using ICD-9-CM coded data with the ICD-9-CM version of the TW-DRGs are compared to payment based on the TW-DRGs assigned using ICD-10-CM/PCS coded data with the ICD-10-CM/PCS version of the TW-DRGs. Use relative weight to estimate the payment between ICD-9-CM and ICD-10-CM/PCS TW-DRGs version. This paper will use total aggregate relative weight in each MDC(Major Diagnostic Categories) group, to compare between these two TW-DRGs, and use the Coefficient of Variance in each TW-DRGs medical cost, to identify ICD-10-CM/PCS version TW-DRGs should recheck its rules or not. Result: 7,778(28.27%) cases had changed in ICD-10-CM/PCS TW-DRGs assignment. Total relative weight decrease 76.67, 44.90% shifted to higher-weight TW-DRGs, 55.10% shifted to lower-weight TW-DRGs. Aggregate weight change was -0.23%. Conclusion: The results of this study show that aggregate payments will decrease on ICD-10-CM/PCS TW-DRGs, and suggest to revise ICD-10-CM/PCS TW-DRGs rules, not just mapping from ICD-9 version. Hospitals need to take serious on this, and prepare on this change as early as they can.
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Books on the topic "ICD-10-CM"

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A, Venable Carol, ed. ICD-10-CM preview. Chicago, IL: AHIMA, 2003.

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Hazelwood, Anita C. ICD-10-CM and ICD-10-PCS preview. 2nd ed. Chicago, Ill: AHIMA, 2009.

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A, Venable Carol, and American Health Information Management Association., eds. ICD-10-CM and ICD-10-PCS preview. 2nd ed. Chicago, Ill: AHIMA, 2009.

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Hazelwood, Anita C. ICD-10-CM and ICD-10-PCS preview. 2nd ed. Chicago, Ill: AHIMA, 2009.

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Hazelwood, Anita C. ICD-10-CM and ICD-10-PCS preview. Chicago, Ill: AHIMA, 2004.

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Buck, Carol J. 2010 ICD-10-CM draft. Maryland Heights, Mo: Saunders Elsevier, 2010.

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J, Buck Carol, ed. 2014 ICD-10-CM draft. 2nd ed. St. Louis, Missouri: Elsevier/Saunders, 2014.

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2013 ICD-10-CM draft. 2nd ed. St. Louis, Mo: Elsevier, 2013.

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Buck, Carol J. 2010 ICD-10-CM draft. Maryland Heights, Mo: Saunders Elsevier, 2010.

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E, Bowman Sue, American Health Information Management Association, and American Medical Association, eds. Pocket guide of ICD-10-CM and ICD-10-PCS. Chicago, Ill: AHIMA, 2010.

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Book chapters on the topic "ICD-10-CM"

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"Diseases of the Ear and Mastoid Process (H60-H95)." In Pediatric ICD-10-CM, 175–77. American Academy of Pediatrics, 2016. http://dx.doi.org/10.1542/9781610020435-ch08.

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"External causes of morbidity (V00-Y99)." In Pediatric ICD-10-CM, 359–89. American Academy of Pediatrics, 2015. http://dx.doi.org/10.1542/9781581109016-ch20.

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"Symptoms, Signs, and Abnormal Clinical and Laboratory Findings, Not Elsewhere Classified (R00-R99)." In Pediatric ICD-10-CM, 259–69. American Academy of Pediatrics, 2016. http://dx.doi.org/10.1542/9781610020435-ch18.

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"Certain conditions originating in the perinatal period (P00-P99)." In Pediatric ICD-10-CM, 231–39. American Academy of Pediatrics, 2015. http://dx.doi.org/10.1542/9781581109016-ch16.

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"Diseases of the Circulatory System (I00-I99)." In Pediatric ICD-10-CM, 179–84. American Academy of Pediatrics, 2016. http://dx.doi.org/10.1542/9781610020435-ch09.

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"Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism (D50-D89)." In Pediatric ICD-10-CM, 133–38. American Academy of Pediatrics, 2015. http://dx.doi.org/10.1542/9781581109016-ch03.

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"Congenital Malformations, Deformations and Chromosomal Abnormalities (Q00-Q99)." In Pediatric ICD-10-CM, 249–57. American Academy of Pediatrics, 2016. http://dx.doi.org/10.1542/9781610020435-ch17.

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"Diseases of the Respiratory System (J00-J99)." In Pediatric ICD-10-CM, 185–93. American Academy of Pediatrics, 2016. http://dx.doi.org/10.1542/9781610020435-ch10.

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"Certain Conditions Originating in the Perinatal Period (P00-P99)." In Pediatric ICD-10-CM, 239–47. American Academy of Pediatrics, 2016. http://dx.doi.org/10.1542/9781610020435-ch16.

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"Diseases of the ear and mastoid process (H60-H95)." In Pediatric ICD-10-CM, 171–73. American Academy of Pediatrics, 2015. http://dx.doi.org/10.1542/9781581109016-ch08.

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Conference papers on the topic "ICD-10-CM"

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Gilbert, T., H. Holmer, and K. Carlson. "0099 Validity of ICD-10-CM diagnosis codes for traumatic brain injury in VA administrative data." In Injury and Violence Prevention for a Changing World: From Local to Global: SAVIR 2021 Conference Abstracts. BMJ Publishing Group Ltd, 2021. http://dx.doi.org/10.1136/injuryprev-2021-savir.75.

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Hedegaard, Holly, and Renee Johnson. "27 Development and testing of surveillance case definitions and reporting frameworks to standardise the use of ICD-10-CM coded data for injury surveillance, epidemiology and research." In SAVIR 2017. BMJ Publishing Group Ltd, 2017. http://dx.doi.org/10.1136/injuryprev-2017-042560.27.

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Machado, José, Nicolás Lori, Ana Cecilia Coimbra, Filipe Miranda, and António Abelha. "Medical Diagnosis Classification Using WEKA." In Human Interaction and Emerging Technologies (IHIET-AI 2022) Artificial Intelligence and Future Applications. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe100880.

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The use of data mining techniques is not new—commonly it is used in various other industries, such as financial services, marketing and manufacturing. The main goal of data mining is to find patterns in a large dataset that yield insight and expertise. Thus, in terms of healthcare, data mining methods have a wide range of uses, including diagnosing cancers, pattern recognition and prognosticating patient health outcomes. Each patient's diagnosis at the University of Porto Hospital (Centro Hospitalar Universitário Universitário do Porto) has an ICD-10-CM code. This data can be used to build a predictive model to classify diagnosis using secondary diagnosis. Three datasets were then created to be tested using data mining techniques. As a result, the algorithm that had the best performance was the Random Tree (99.8% corrected classified instances) using the third dataset with the five main diagnoses of each patient as parameters.
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Reports on the topic "ICD-10-CM"

1

Hedegaard, Holly, Matthew Garnett, Renee Johnson, and Karen Thomas. A Revised ICD–10–CM Surveillance Case Definition for Injury-related Emergency Department Visits. National Center for Health Statistics (U.S.), September 2021. http://dx.doi.org/10.15620/cdc:108998.

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2

Hedegaard, Holly, Matthew Garnett, Renee Johnson, and Karen Thomas. A Revised ICD–10–CM Surveillance Case Definition for Injury-related Emergency Department Visits. National Center for Health Statistics (U.S.), September 2021. http://dx.doi.org/10.15620/cdc:109050.

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