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ICD-10-CM Implementation Strategies: An Application of the Technology Acceptance Model

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.

Identiferoai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-3012
Date01 January 2015
CreatorsMonestime, Judith
PublisherScholarWorks
Source SetsWalden University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceWalden Dissertations and Doctoral Studies

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