Clinical coding and the quality and integrity of health data

It is a pleasure to provide the guest editorial for this Special Issue of the Health Information Management Journal (HIMJ). The Journal has had a long and interesting history that can be traced back to the 1970s with humble beginnings, being manually produced with a stencil and duplicating machine by volunteers (Watson, 2019). The fact that we are now publishing a special issue through SAGE Publishing speaks volumes about how far the Journal has come and the title of this Special Issue, Clinical Coding and the Quality and Integrity of Health Data, speaks volumes about how important clinical coding has become to the management of health information in Australia and around the world. In Australia, as the Health Information Management Association of Australia celebrates its 70th anniversary, clinical coders are facing challenges on many fronts. Clinical coded data influences diverse aspects of our health systems, from quality and safety monitoring and funding models to health service planning and infrastructure development. In addition, we have technological developments that will change the clinical coders’ roles substantially over the next 5–10 years. The articles published in this Special Issue reflect these challenges and illustrate the far-reaching consequences of data that lack integrity and are of poor quality. Campbell and Giadresco (2020), through a literature review, investigated the effect of computer assisted coding on the accuracy and quality of clinical coding and its impact on clinical coding professionals. The articles, dissertations and case studies they reviewed demonstrated value in improving clinical coding accuracy and quality through computer assisted coding. Campbell and Giadresco concluded that clinical coders should view computer assisted coding as an opportunity to develop new skills, particularly in monitoring and auditing coding outputs, and that sound change management strategies are needed to ensure a successful transition of the clinical coding workforce to new roles. Improved clinical coding accuracy will benefit our health system enormously but it would be naı̈ve to think that computer assisted coding is the complete answer. Clinical coders will be needed in different roles to help realise the benefits of computer assisted coding. To that end, Hay et al. (2020) discussed the role of documentation improvement specialists and how they can ensure adequate documentation that can be translated into clinical codes. This is a potential role for clinical coders who understand both the clinical documentation and the needs of the end users of the coded data. Hay et al. (2020) also outlined the work of the Australian Commission on Safety and Quality in Health Care, which has promoted improved documentation through its National Safety and Quality Health Service Standards and the use of coded data for monitoring patient safety through its hospital-based outcome indicators. The development of the hospital-based outcome indicators has further elevated the need for high-quality clinical coding. However, barriers exist to achieving quality clinical coding outcomes. Canadian authors, Doktorchik et al. (2020), discussed these barriers in their article ‘A Qualitative Evaluation of Clinically Coded Data Quality From Health Information Manager Perspectives’. Their interviews with health information managers and clinical coding managers revealed that expectations were increasing for high-quality data collection but without additional resources to support this endeavour. They also found that incomplete and disorganised clinical documentation and lack of good communication with clinicians impacted on the quality of clinical coding. These same issues exist in Australia, and I am sure in many other countries around the world. The integrity of clinical coding depends fundamentally on the quality of the patient record. The Portuguese study by Alonso et al. (2020), ‘Health records as the basis of clinical coding: Is the quality adequate? A qualitative study of medical coders’ perceptions’, highlights that clinical records are not just for patient treatment but that the data derived from them are stored in administrative databases and used for many downstream purposes. To that end, the authors conducted focus groups to elicit from clinical coders the problems they face in the health records that influence the quality of the coded data. They identified several issues including missing or incomplete discharge and/or surgical notes, the use of abbreviations, variability in documentation between specialties and lack of specificity in diagnosis descriptions. They also identified that in spite of electronic health records solving illegibility problems, they have created problems of their own, notably the copy and paste facility that results in errors being repeated throughout the record and very large volumes of notes to be