HIM-Interchange

Introduction

Understanding the complexities of injury relies heavily on the narrative data captured at the triage point of contact in emergency departments (ED’s). ED-based injury surveillance systems, such as the Queensland Injury Surveillance Unit (QISU), process and analyse the injury narrative data that is captured in ED systems such as the Emergency Department Information System and FirstNet in participating Queensland public hospitals.

With the current systems in place, capturing specific details involved when a patient presents to the ED is limited. Injury narrative data is useful for injury surveillance purposes, such as identifying features of the injury event that are not captured in the coded fields. This provides a rich source of data for further analysis (Vallmuur 2015). Capturing a complete injury narrative can prove difficult in the ED environment due to clinical workload, diagnostic priorities, lack of viable witnesses, and the system constraint of maximum word limits in text fields (Johnston et al. 2016).

Currently, ED systems in Queensland utilise a subset of codes from the International Statistical Classification of Diseases and Related Health Problems, Australian Modification (ICD-10-AM) and the Systematized Nomenclature of Medicine (SNOMED) Clinical Terms (CT) for the clinical diagnoses. ICD-10-AM is limited in capturing the external causes of the narratives, and although SNOMED-CT has a significantly larger diagnostic range, there are still limits to the capabilities of SNOMED-CT.

With considerations to the limitations and difficulties of capturing injury narrative data, a project was initiated by the QISU called Settling the Injury Narrative Score in 2021. The project was introduced having two main objectives in mind, with the results feeding into an overall larger project that is currently being led by Purdue University.

Objectives

The first objective was to develop an injury narrative scoring system that rated the completeness of the injury narratives to inform the implementation of a machine leaning-based classifier system in the QISU workflow in partnership with Purdue University (Catchpoole et al. 2022).

The first objective was achieved, and a scoring system was developed that rated the completeness of the injury narrative. The scores were based on the injury narrative key elements in the National Data Standards – Injury Surveillance (NDS-IS) (National Injury Surveillance Unit 1998). The NDS-IS are utilised by QISU to validate and code the presentations in participating emergency departments throughout Queensland.

The second objective was to trial the latest revision of the International Classification of Diseases, International Classification of Diseases, 11th Revision (ICD-11), on ED-based injury narrative data to determine the efficacy of the latest revision of the classification. As this was a student tailored project, the scope of this stage of the project was limited due to the time constraints imposed on the student placement. As such, only a subset of ICD-11 codes was trialled in this stage, and the injury narrative scoring system at this stage was a rudimentary system meant for proof of concept.

The second objective was achieved, and the ICD-11 codes were successfully applied to the injury narratives in the same manner as the ICD-10-AM codes. The injury narratives were blind coded, meaning that the ICD-11 codes were assigned without knowledge of the current ICD-10-AM codes to avoid biased coding. Results generated from this objective can be used to inform future ICD-11 revisions and also potentially lead to being used as education material.

Methodology

There are seven elements that are listed in the NDS-IS and the scoring system was based off each of those elements. Each NDS-IS injury element was given a score of one when identified in the injury narrative and the total score was calculated based on the number of elements identified.

ICD-11 was successfully trialled on the injury narrative data that were collected from the 2018 QISU database. ICD-11 codes were successfully assigned to all elements identified in the injury narrative. The ICD-10-to-ICD-11 mapping spreadsheet provided on the ICD-11 web page was utilised to confirm the correct assignment of codes.

Study data were collected and managed using REDCap (Research Electronic Data Capture), electronic data capture tools hosted at Metro North Hospital and Health Service (Harris et al. 2019, Harris et al. 2009). REDCap is a secure, web-based software platform designed to support data capture for research studies, providing:

• An intuitive interface for validated data capture
• Audit trails for tracking data manipulation and export procedures
• Automated export procedures for seamless data downloads to common statistical packages
• Procedures for data integration and interoperability with external sources.

A REDCap form was developed to facilitate the manual review process and the form was designed in alignment with the structure of QISU data. The fields in the REDCap form were based on the QISU dataset, prefilling the fields QISU ID, Age, Gender, Diagnosis Code, Triage Score, Mode of Separation, and Injury Description. The information for these fields were imported directly from the cleaned QISU dataset for convenience. The remaining fields, ICD-11 Diagnosis Code, Injury Narrative Criteria, What went wrong, Mechanism, Objects/Substance, Place of Occurrence, Activity, Protective Equipment, and Prominent Features were manually entered in order to rate the completeness of the injury narrative.

After manually entering the fields, extra fields for External Cause Code, Object or Substance Code, Place of Occurrence Code, and Activity Code were added as they were required for ICD-11 coding. These fields were linked to the corresponding key element to allow for the manual review and ICD-11 coding phases to be completed concurrently.

Results

Of the 724 records reviewed and coded, 54 scored 0 points, 73 scored 1 point, 208 scored 2 points, 340 scored 3 points, 47 scored 7 points, and only 2 scored 5 points (see Figure 1). Approximately 47% of the total records reviewed scored 3 points and of that, 100% of those records included the Mechanism. Of the records that scored 3 points, 334 documented What went wrong and 291 records documented Object/Substance.

The top three scoring elements documented were noted as: Mechanism (641), What went wrong (516), and Object/Substance (416), as seen in Figure 2. These results highlight the emphasis placed on certain elements from both a clinical and a data quality standpoint; there is a significant difference with the top three scoring elements. This further outlines the importance of a more dynamic scoring system, potentially adding in weighted values for the different elements (e.g., Mechanism would be weighted more than Presence or Absence of Safety Equipment).

The injury narrative scores per triage category show a significant number of the records in triage category 4, with 366 records (see Figure 3). These values help us identify the trends in which triage category provides the most or the least information. As the severity of the presentation increases, the information provided or is available decreases. The outlier to this trend is the triage category 5, which could be possibly due to patients presenting to the emergency department for monitoring of injuries.

Based on the results, the objective to develop a scoring system to rate the completeness of the injury narrative text was successful.

The injury codes used were categorised based on the ICD-11 Chapter 22: Injury, poisoning or certain other consequences of external causes. The adverse reactions category was based on Chapter 4: Diseases of the Immune system, post-accident examination category was based on Chapter 24: Factors Influencing Health Status or Contact with Health Services, and the sexual assault category was based on Chapter 23: External Causes of Morbidity or Mortality (World Health Organization 2021).

As seen in Figure 4, Head Injuries were the most commonly documented injury type with 145 records, with the second and third most common being Wrist/Hand Injuries and Ankle/Foot Injuries, respectively. The injury narratives were coded in ICD-11 using the source information in order to provide accurate assignment of codes. An ICD-10 to ICD-11 mapping spreadsheet was available on the WHO website which was utilised for double checking the ICD-11 codes assigned.

Reflections

Highlights and Innovations

This project provided many opportunities for personal development as well as exposure to a professional setting. There were three key highlights identified upon completion of the placement:

• Contribution to fundamental development of ongoing research project
• Trialling ICD-11
• Use of REDCap.

From the perspective of a student, knowing that the results and findings of the project can and will be utilised for further studies proved to be a significant highlight. It was motivating for the student to meet with the stakeholders as it allowed a different perspective on the project. The meetings also provided more context as to the knowledge the findings of the project can provide for future researchers and the project team.

Exposure to research-based activities also provided a different perspective for the student on different roles a Health Information Manager (HIM) may undertake. This was a highlight as it expanded the student’s understanding of their potential, therefore opening their mind to new possibilities.

ICD-11 was adopted by the World Health Assembly in 2019 and came into effect (available for use) January 2022 (Chaib 2019). By gaining exposure to ICD-11, the student gained experience utilising the web-based ICD-11 coding tool. This also provided the student with an idea of where the future of clinical coding is heading and possibilities for future projects revolving around ICD-11.

Other key highlights and innovations include using REDCap, a web application for building and managing online surveys and databases and utilising injury surveillance data and understanding the processes that are involved in capturing that information. This had advantages over a spreadsheet analysis, including, greater security and quality of the data through user access control, authentication, record management and compliance with various legislation that govern the privacy and security requirements of clinical data.

The rising use of REDCap within Queensland Health is not limited to research projects, with many legacy spreadsheets and databases used for internal data management being replaced by the system. With electronic medical records becoming increasingly integrated with clinical systems, there will be many future opportunities to increase accessibility to data for research, while upholding and even increasing data quality, privacy, and security standards with systems such as REDCap.

Lessons Learnt

Reflecting on the student experience there were a number of key points that stood out, some only apparent toward the end of the placement. Overall, they were all vital to the development of a student and transition to a practicing Health Information Manager.

Understandably, the everyday environment of the office may differ depending on the organisation, but a consistent theme identified is that balancing time between correspondence with both internal and external stakeholders and the daily tasks can be difficult. This may come down to one’s own organisational skills however, it would be difficult to navigate the schedules of many different individuals to find a segment of time that worked for all parties. The main lesson learnt from this is that it is important to be open and transparent about your needs as this will allow all stakeholders to respond appropriately and effectively to any requests that you may have. It also means that all parties are aware and on the same page regarding the discussion topic.

The second lesson learnt for the student was realised during the reviewing of the data. The entire phase of reviewing the data was extensive and required a degree of interpretation and high level of accuracy. While this phase was enjoyable, the question, “Is there any way for this to be completed more efficiently?” was at the forefront of the student’s mind. This is an incredibly important mindset to have as a Health Information Manager because the world of health is evolving and slowly transitioning to a digital platform. Thinking about how processes can be optimised and completed in a systematic way that reduces extra work is important as it can lead to increased efficiencies and better patient care in the form of more readily available information.

What Worked Well

Throughout the project, the supervisors agreed to a fortnightly meeting to provide regular updates and discussions. This was a useful strategy as it allowed for continuous support and direction for the project. It also provided a regular time for any questions or concerns about the project to be addressed early to avoid more serious issues later in the project.

A pseudo buddy system was utilised during the project, and this was helpful as it meant that questions could be asked as they arose or quickly confirm information that was easily addressed rather than spending meeting time doing so. Having been physically placed with the QISU team meant that any questions relating to capture of injury data or injury coding could be addressed as they arose. It also created a stronger feeling of being part of the team and helped to develop new connections.

Navigating a student placement can be tricky enough and having to navigate placement whilst living through a pandemic was even trickier! Having remote access worked well as it meant that lockdowns that occurred throughout the placement would not affect or delay project activities. It also meant that in the event of unforeseen circumstances impacting on the ability to undertake the work in the office, placement days could be completed from home. Storing the files on Microsoft Teams meant that all project team members always had access to the project files and did not require an individual to store and maintain the records. This allowed for efficient transfer of information amongst the team members.

From a supervisor perspective, the COVID-19 pandemic introduced challenges in almost every workplace. The use of Microsoft Teams and other cloud-based Microsoft Office applications made communication and documentation easier to negate the effects of restrictions placed on students visiting hospitals and healthcare facilities.

Although each of the tasks were quite large in their own rights, completing the manual review and ICD-11 coding phases concurrently meant that the data would not be double handled. This allowed for more efficient processing of the records resulting in three quarters of the sample size successfully reviewed and coded.

What Could Be Improved

A key part of good project management is to reflect on areas for improvement and to apply those learnings to future projects (Jugdev 2015). While overall the project and the project management processes worked well, several areas for improvement have been identified. The REDCap form could have been refined to prevent and reduce human error issues such as typing errors when assigning ICD-11 codes. An improvement that could be made to the REDCap form would be to add in drop-down selections for the ICD-11 codes; not to directly code from the REDCap form, but to act as a preventative measure of typing errors that affect the results. During the development of the scoring system, we concluded that the scoring system was rudimentary with no weighting given to each triage injury narrative. While this would give us a good initial indication of completeness, it may not reflect the clinical priority given to each category in ED data collection. Overall, the project processes were well thought out with minimal improvements required.

While the project was a great success, there were some areas of improvement identified from a student supervisor perspective. There was a gap in contact between the project plan and the student commencing their placement. A catch up and preparation meeting a week before the placement start date may benefit both the student and supervisor to ensure project deliverables, timelines and expectations are aligned. This has been applied to the next cohort of students at the Jamieson Trauma Institute with the implementation of preparation meetings scheduled a week before the commencement of the placement to plan the first few weeks of activities and ensure agreement of the project deliverables.

It is also important to note that while the student placement was done in a non-traditional Health Information Manager role, the student did have a Health Information Manager as the supervisor and access to the experience of recent graduates from the Queensland University of Technology Bachelor of Health Information Management degree. Due to the varying nature of non-traditional health information management student placements, a tailored approach is required, and the student may not benefit from a standard placement plan. There may be a benefit to establishing an early career mentor program which could give final year students access to recent graduates (e.g., less than 5 years) to discuss their experiences, what to expect from placement, maximising opportunities, and where to go from the completion of their placement. Involvement of the Health Information Management Association of Australia in facilitating this could be beneficial by establishing an early career pool of members that could be available to give advice and guidance to final year student and recent graduates entering the workforce.

Conclusion

This student placement project at Jamieson Trauma Institute provided a number of opportunities to demonstrate the diversity of the health information management skillset through the application of those skills in the injury surveillance field of research, data collection and disease classification. It provided an opportunity to test the capacity of ICD-11 for injury surveillance and to gain an early understanding of the classification in this field of surveillance. Student and supervisor skills and knowledge were enhanced by the experience and areas for improvement for future student placement projects were identified in the field of research and non-traditional health information management roles. The collaboration proved to be an invaluable experience, in particular for the student, but also for the placement supervisors. Successful projects such as these can be beneficial for all involved and continue to advance the health information profession.