Identification of root causes of clinical coding problems in Iranian hospitals

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.

A Comparison of Solo and Pair Programming in Terms of Flow Experience, Coding Quality, and Coding Achievement

Cooperative learning manifests itself as pair programming in coding education. There is a limited number of studies experimentally demonstrating that pair programming is effective in the educational context. Therefore, in this study, solo and pair programming were compared in terms of flow experience, coding quality, and coding achievement. The method used in this study is a pretest-posttest quasi-experimental design. The study group consists of 42 volunteer senior university students (28 males, 14 females). While solo programming was performed in the control group, pair programming was performed in the experimental group. It was concluded that the flow experience of the experimental group was higher than that of the control group in four weeks of the six-week implementation, whereas the coding quality of the experimental group was higher in three weeks. No difference was found in the other weeks in terms of both flow experience and coding quality. Although the coding achievement of both the control and experimental groups increased in the study, the experimental group did not exhibit better performance in terms of coding achievement. In conclusion, since it was revealed in this study that pair programming is effective, it is recommended to use pair programming more frequently in educational settings.

A qualitative evaluation of clinically coded data quality from health information manager perspectives

Background: It is essential that clinical documentation and clinical coding be of high quality for the production of healthcare data. Objective: This study assessed qualitatively the strengths and barriers regarding clinical coding quality from the perspective of health information managers. Method: Ten health information managers and clinical coding quality coordinators who oversee clinical coders (CCs) were identified and recruited from nine provinces across Canada. Semi-structured interviews were conducted, which included questions on data quality, costs of clinical coding, education for health information management, suggestions for quality improvement and barriers to quality improvement. Interviews were recorded, transcribed and analysed using directed content analysis and informed by institutional ethnography. Results: Common barriers to clinical coding quality included incomplete and unorganised chart documentation, and lack of communication with physicians for clarification. Further, clinical coding quality suffered as a result of limited resources (e.g. staffing and budget) being available to health information management departments. Managers unanimously reported that clinical coding quality improvements can be made by (i) offering interactive training programmes to CCs and (ii) streamlining sources of information from charts. Conclusion: Although clinical coding quality is generally regarded as high across Canada, clinical coding managers perceived quality to be limited by incomplete and inconsistent chart documentation, and increasing expectations for data collection without equal resources allocated to clinical coding professionals. Implications: This study presents novel evidence for clinical coding quality improvement across Canada.

Strengths and Barriers to Coding Hospital Chart Information from Health Information Manager Perspectives: A Qualitative Study

IntroductionIt is essential that clinical documentation and data coding be of high quality for the production of healthcare data for research or administrative purposes. However, there is a limited understanding of the facilitators and barriers of coded data quality and strategies to improve it. Objectives and ApproachOur objective was to qualitatively assess what influences coded data quality from the perspective of health information managers who are responsible for the work of coding specialists. Nine health information managers and/or coding quality coordinators who oversee coding specialists were identified and recruited from nine provinces across Canada to participate in this study. Semi-structured interviews were conducted which asked questions on participant demographics, responsibilities, data quality, costs and budget of coding, continuing education for Health Information Management (HIM), suggestions for quality improvement, and barriers to quality improvement. Interviews were recorded and transcribed, and analyzed using Directed Content Analysis methodology. ResultsInterviewees were primarily responsible for managing staff, quality assurance, audits, reporting, budget, data collection, and transcription. Managers reported that the experienced coders under their employ strengthened coding quality. Common barriers to coding quality included incomplete and unorganized chart documentation, which led to undercoding, and lack of communication and access to physicians for clarification when needed. Further, coding quality suffered as a result of limited resources (e.g. staffing and budget) being available to HIM departments for an ever-expanding workload, that was commonly due to increasingly complex charts and additional project data. Managers unanimously reported that coding quality improvements can be made by 1) making interactive training programs available to coding specialists, and 2) streamlining sources of information from charts (i.e., transitioning to standardized electronic charting). Conclusion/ImplicationsAlthough coding quality is generally regarded as high across Canada, quality can be hampered by incomplete and inconsistent chart documentation, lack of resources (e.g. financial support, staff, education), and inconsistent coding standards across hospitals and provinces. This study presents novel evidence for coding quality improvement across Canada.

Effects of Training on Quality of Clinical Coding at Mbagathi County Referral Hospital, Nairobi City County, Kenya

Introduction: Professionals from various cadres in the health sector raise concerns regarding the poor quality of clinical coding leading to lack of evidence-based practice. Assessing the quality of the clinical coding in one of Nairobi City County’s major hospital would be a step towards establishing the exact gaps in quality of the coding process and outcome. Training the professionals would also foster better clinical coding practice in one of the major facilities nationally. Method: The study aimed at establishing the quality of clinical coding within Mbagathi County Referral Hospital, and thereafter determined the effect of training on the established clinical coding quality. An interventional trial study design was used, with a quality of clinical coding checklist used classify codes assignment or lack of which. The sample included 320 patient files selected randomly from a month-long list of patients. Results: The study found out that the overall baseline code quality was slightly above average given that majority (55%) of the code assignment were good as established by a composite score of the various coding quality attributes assessed. Given the need for training based on the low quality, a training intervention was then conducted based on the needs identified. An indexing database was also installed for the coders to use in encoding the codes assigned. Code quality improved to 77% after the training. Code completion was excellent at the facility, as established from the 97% of the files that were completely coded at baseline and later improved to 99%. Notably, also, is that the hospital improved its coding of procedures and death certification by 32 and 53% respectively. The hospital also started using the indexing tool that was introduced as an intervention. Conclusions: The health facility could act as a good benchmark for code completion. However, code completion without accuracy in the code assignment invalidates the overall quality of coding. Code accuracy improved with the training almost immediately after the interventions. More practice would for sure lead to better clinical coding accuracy.