Implementing a cost-effective method of improving coding accuracy

Priyatilake, H.; Kumar, Lalit; Appleton, S G

doi:10.1308/rcsbull.2019.238

Cited by 5 publications

(7 citation statements)

References 12 publications

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“…Considering the poor use of code among clinicians [ 5 ] and that important information for clinical decision-making is only recorded in free text [ 26 ], it is still a way to reflect, and to monitor improvements. It is vital to improving clinical coding accuracy, which is paramount for audit, benchmarking and surveillance [ 27 ], and more tools are needed to help in this purpose.…”

Section: Discussionmentioning

confidence: 99%

Consultation analysis: use of free text versus coded text

Martin¹

2021

Health Technol.

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General practice in the United Kingdom has been using electronic health records for over two decades, but coding clinical information remains poor. Lack of interest and training are considerable barriers preventing code use levels improvement. Tailored training could be the way forward, to break barriers in the uptake of coding; to do so it is paramount to understand coding use of the particular clinicians, to recognise their needs. It should be possible to easily assess text quantity and quality in medical consultations. A tool to measure these parameters, which could be used to tailor training needs and assess change, is demonstrated. The tool is presented and a preliminary study using a randomised sample of five recent consultations from thirteen different clinicians is used as an example. The tool, based on using a word processor and a spread-sheet, allowed quantitative analysis among clinicians while word clouds permitted a qualitative comparison between coded and free text. The average amount of free text per consultation was 68.2 words, (ranging from 25.4 and 130.2 among clinicians); an average of 6% of the text was coded (ranging from 0 to 13%). Patterns among clinicians could be identified. Using Word cloud, a different text use was demonstrated depending on its purpose. Some free text could be turned into code but nomenclature probably prevented some of the codings, like the expression of time. This proof of concept demonstrated that it is possible to calculate what percentage of consultations are coded and what codes are used. This allowed understanding clinicians' preferences; training needs and gaps in nomenclature.

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Section: Discussionmentioning

confidence: 99%

Consultation analysis: use of free text versus coded text

Martin¹

2021

Health Technol.

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“…Researchers believed that an increased budget for hiring staff, training, education, and continuing education could be effective (Doktorchik et al, 2020). Moreover, other studies similarly indicated the importance of clinical coders' communication with physicians (Abdulla et al, 2020;Doktorchik et al, 2020) and their feedbacks to improve clinical coding accuracy (Priyatilake et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…A Canadian study similarly highlighted clinical coders’ experience, their limited opportunities for training and continuing education, and increased workload as the reasons for decreased clinical coding accuracy (Doktorchik et al, 2020). Priyatilake et al (2019) indicated that staff shortage and the increased workload made clinical coders rely on a discharge summary to code a medical record and this problem increased their errors. Researchers believed that an increased budget for hiring staff, training, education, and continuing education could be effective (Doktorchik et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, the accuracy of coding diagnoses and procedures is of particular importance (Cheng et al, 2009). Despite this importance, different studies indicated that many countries, developing or developed ones, faced high coding errors (Abdulla et al, 2020; Priyatilake et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Understanding the clinical coding problems, and analysing their underlying causes, are of special importance to improve the clinical coding quality (Alonso et al, 2020; Doktorchik et al, 2020; Zafirah et al, 2018). In this regard, different studies highlighted the most important factors leading to incorrect clinical coding in different countries such as incomplete documentation of medical records, failure to implement standard documentation and clinical coding, shortage of clinical coders, and inappropriate guidelines (Adeleke et al, 2015; Alonso et al, 2020; Doktorchik et al, 2020; Priyatilake et al, 2019; Tang et al, 2017). Investigating the experiences of clinical coders and health information managers can help identify clinical coding problems.…”

Section: Introductionmentioning

confidence: 99%

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Identification of root causes of clinical coding problems in Iranian hospitals

Jebraeily

Farzi

Fozoonkhah

et al. 2021

HIM J

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Background Improving the quality of coded data requires the identification and evaluation of the root causes of clinical coding problems to inform appropriate solutions. Objective The objective of this study was to identify the root causes of clinical coding problems. Method Twenty-one clinical coders from three cities in Iran were interviewed. The five formal categories in Ishikawa's cause-and-effect diagram were applied as pre-determined themes for the data analysis. Results The study indicated 16 root causes of clinical coding problems in the five main themes: (i) policies, protocols, and processes (lack of clinical documentation guidelines; lack of audit of clinical coding and feedback to clinical coders; the long interval between documentation and clinical coding; and not using coded data for reimbursement; (ii) individual factors (shortage of clinical coders; low-skilled clinical coders; clinical coders' insufficient communication with physicians; and the lack of continuing education; (iii) equipment and materials (incomplete medical records; lack of access to electronic medical records and electronic coding support tools; (iv) working environment (lack of an appropriate, dynamic, and motivational workspace; and (v) management factors (mangers' inattention to the importance of coding and clinical documentation; and to providing the required staff support. Conclusion The study identified 16 root causes of clinical coding problems that stand in the way of clinical coding quality improvement. Implications The quality of clinical coding could be improved by hospital managers and health policymakers taking these problems into account to develop strategies and implement solutions that target the root causes of clinical coding problems.

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