Paramedicine informatics – leveraging advancing technology to drive positive change

Abstract

As all areas of healthcare continue to experience rapid digitisation, the field of health informatics is becoming increasingly important. Large health systems are employing more informatics professionals to ensure that the health information systems deployed are safe, efficient, equitable and, most importantly, adopted by users. The value of informatics to paramedicine is only increasing as we continue to see rapid expansion of digital health technologies. New wearable technologies, improved cellular infrastructure, and leaps in generative artificial intelligence and natural language processing capabilities have made informatics even more relevant to paramedicine. However, we need paramedicine professionals with the necessary informatics competencies in place to take advantage of the opportunities provided by informatics. Health informatics can improve our systems and quality of care by using maturity models, artificial intelligence evaluation frameworks, implementation science, and health data interoperability. Given the unique context of paramedicine in healthcare, we recommend that a specialised informatics subdivision of paramedicine informatics be recognised as a pathway to further professional growth and distinguish paramedicine as a unique healthcare profession with specific knowledge frameworks and needs.

Background

Health Informatics is the science of how to use data, information, and knowledge to improve human health and the delivery of healthcare services. ¹ The field of informatics has existed in various forms since the 1950s and has seen radical changes since the exponential growth of computers. ² As healthcare rapidly digitises, the informatics field continues to grow and expand, leading to several divisions and specialisations.

Some informatics specialisations include biomedical, clinical, pharmacy, and nursing, among others. These fields have emerged out of necessity due to the explosion of digital health information and the recognition that each area has specialised knowledge frameworks. ³ For example, nursing informatics has informally existed since the 1960s, with the field of nursing informatics being a fully recognised specialty in 1992.^3,4 Basic informatics competencies are included in the pre-licensure curriculum for bachelor-prepared nurses. These specialists fill roles in hospitals, long-term care facilities, and private industries and perform a wide range of job functions, including project management, health information system management, policy writing, system design and more. They liaise with healthcare information technology (IT) to ensure that the correct system is selected to meet workflow, standards, and clinical needs, particularly for nursing. ³ With more digitisation of healthcare and new technologies like natural language processing (NLP) and generative artificial intelligence (AI), more of these roles are needed.

Large health systems have recognised the need for more informatics professionals. A recent example was the deployment of ambient AI scribes for physicians in the Kaiser Permanente system in the United States. The organisation deployed a ‘tech stack’ of 1000 informaticists for a programme that involved 10,000 physician users. ⁵ These informatics professionals managed the rollout, liaised between users and vendors, and developed measurement standards and AI evaluation frameworks. These institutions have realised that to benefit from these technologies fully, they must invest in those who understand how to implement, evaluate and maintain them – in other words, highly trained humans who can support technology.

The importance of informatics to paramedicine in the United Kingdom was outlined by Davis (2013) as a way to advance the profession in terms of clinical practice, academics and system benchmarking. ⁶ Since then, technology and digital health have only advanced; new wearable health technologies, improved cellular network infrastructure, and leaps in generative AI and NLP capabilities have made informatics even more relevant to paramedicine. However, despite the advances and the promise of current and future technology, modern paramedics all too often employ data collection processes that have remained largely unchanged since the 1970s – go on a call, provide some treatment, and then retrospectively chart the treatment often based on harried notes written on various surface.

In this commentary, we discuss what informatics can do in the current technology landscape to help improve paramedicine, and we make the case for the importance of informatics in advancing paramedicine through research, quality measurement, and overall system knowledge.

What informatics can do

Maturity models

Maturity models are tools that an organisation can use for self-evaluation, comparison and planning. Maturity models reflect best practices and can be applied to help organisations identify gaps, prioritise investments, provide system benchmarking standards and develop growth strategies and institutional road maps. ⁷ These models can support continuous improvement and manage high-complexity projects such as digital health initiatives, including electronic patient care report adoption, remote monitoring and AI integration. ⁸ According to Carvalho et al. (2016), ‘maturity models are based on the premise that people, organisations, functional areas, processes, etc., evolve through a process of development and growth toward a more advanced maturity accomplished in several stages’ (p. 1). ⁹ Models consist of several maturity levels across multiple dimensions to allow a robust evaluation of the organisation and technologies. ⁹ These models can be implemented at the organisational or national level. For example, the Healthcare Information and Management Systems Society (HIMSS) Electronic Medical Record Adoption Model is designed to evaluate and plan electronic medical record (EMR) adoption within a hospital organisation. ¹⁰ Whereas the National E-Health Transition Authority of Australia created the Interoperability Maturity Model that measures the interoperability capacities of the different healthcare services at a national level. ¹¹ Maturity models are essential in guiding the adoption and assessment of healthcare technologies. Informatics professionals participate in and guide the development of maturity models.

The multidimensional nature of maturity models would accommodate the various stakeholders in paramedicine. The nature of these models would allow the inclusion of the various other service delivery methods employed by paramedicine outside of emergency response, such as community paramedicine or inter-facility transfers. A standardised maturity model would allow jurisdictions to benchmark and compare their practices.

AI evaluation frameworks

Progress in AI has been accelerating at an ever-increasing pace. With advancements in generative AI and NLP, these technologies are opening up new solutions in healthcare. ¹² As clinical decision support systems, ambient AI scribes, and AI-aided documentation become more prevalent, using a robust evaluation framework is critical for successful implementation. Since implementing and integrating AI systems is often complex and cost-intensive, a robust framework that evaluates AI systems early and often during deployment and use can be critical for a successful implementation. ¹³ Often, technical evaluations fail to consider the clinical workflow and ethical application of AI in healthcare, and a theory-based approach to framework development is recommended.^13,14 For example, Mass General Brigham used a clinical trial-informed framework to evaluate implementing AI scribes. It included four phases: Safety, Efficacy, Effectiveness and Monitoring. ⁵ With clear goals and developing best practices for each phase, this framework allowed the success and growth of their AI scribe programme safely and equitably.

In paramedicine practice, AI's ethics and workflow integration will be complex. Dealing with cross-organisation training data, ambient and bystander noise, and informed consent for recordings will be challenging. Paramedicine informaticists would possess the knowledge to assist in identifying and providing guidance on ethical concerns that would be unique to using technology in paramedicine practice. Ensuring we build proactive ethical frameworks rather than reacting to a gap, not to mention the need to be able to access AI in the community, where areas of intermittent, weak, or non-existent internet connectivity are commonplace. It will be critical for those looking to implement AI programmes, like ambient scribes and NLP, to understand the specific workflow needs and challenges that paramedics face. Developing AI evaluation frameworks specifically for paramedicine could address some of these challenges early in the implementation process.

Implementation science

Implementation science is a field that developed from the evidence-based practice movement. ¹⁵ The implementation of evidence-based interventions was sub-optimal, and many of these interventions never made it to broad use, with some estimates of implementation failures as high as two-thirds of all attempts. ¹⁶ Implementation science was intended to produce knowledge that closed the gaps between what is proven effective and the perceptions and uses in the field. ¹⁵ Several implementation science models, including the technology acceptance model, ¹⁷ the unified theory of acceptance and use of technology, ¹⁸ the sociotechnical model, ¹⁹ the consolidated framework for implementation research, and the fit between individual, task, technology model ²⁰ are frequently deployed in implementing digital health technologies. Given the variety of models that can be employed, it is critical to understand what type of analysis they support and what types of questions they can answer. Implementation science explores the interaction between people, processes, and technology and can help distinguish between interoperable data systems and interoperable workflows. ²⁰

While the implementation science models can and have been used in paramedicine, they have been used to evaluate the introduction of new programmes, like palliative care at home. ²¹ Some have been applied to technologies for paramedicine in the development stage, ²² however, these models fail to account for the interaction between the paramedic system and other systems. Paramedicine has a unique place in healthcare, meaning it will consistently interact with other systems, such as the hospital emergency department or long-term care providers. It is also heterogeneous, meaning that paramedicine no longer fits nicely into the single emergency call followed by transport to hospital paradigm. Paramedicine models are complex; therefore, the implementation models that support paramedicine must be robust.

Data interoperability

Health data interoperability is a critical part of the future of healthcare.^23,24 Interoperability is the ability of systems to access, integrate and cooperatively use data in a coordinated manner. ²⁵ This can be within an organisation, a region, nationally or internationally. HIMSS defines four levels of interoperability: Foundational (Level 1), Structural (Level 2), Semantic (Level 3), and Organisational (Level 4). ²⁵ The requirements range from establishing interconnectivity to allow systems to communicate securely (Level 1) to governance, policy, social, legal and organisation considerations to share data within and between organisations and establishing shared consent, trust and integrated workflows (Level 4). ²⁵ Terminology standards and health information exchange standards, like HL7 Fast Healthcare Interoperability Resources, already exist to improve the interoperability of health records. ²⁶ As healthcare continues to expand the role of EMRs, the information in those records must be available to practitioners when required for care. Informatics professionals work with stakeholders to ensure that new systems and technologies are interoperable at an organisational level.

Paramedicine interacts with multiple branches of healthcare as a part of its regular operations. For example, paramedics regularly transfer patients to the emergency departments of hospitals or from the hospital to a long-term care facility. Seamlessly transferring electronic patient data between these organisations could help reduce patient adverse events. ²⁷ An example of interoperability in action is the Operational Medical Networks Informatics Integrator system deployed in Singapore. This system fully integrates pre-hospital and in-hospital records and allows the live telemetry of vital signs from the field to the emergency department and EMR. ²⁸ During care, paramedics need to gather and synthesise patient information quickly, including a patient's medical record. Through the interoperability of the advanced monitoring equipment or the patient's wearable health devices and the paramedic's electronic patient care report, patient and incident information can be gathered and quickly included for the paramedic to use in treatment and disposition decisions, and documentation.

Why we need paramedicine informatics

Paramedicine is a unique branch of healthcare, and as such, it has specialised knowledge frameworks and collects unique data elements. Paramedicine often faces difficulty effectively integrating new technologies and struggles to integrate with the health systems they serve, ²⁹ including linking health records. ³⁰ There is a recognised need to improve and leverage advancing technologies in paramedicine. ³¹ For these reasons, we advocate for the recognition and development of an informatics subspecialty of paramedicine informatics and list some potential benefits to paramedicine.

Develop paramedicine-specific models

Content is important in developing maturity models and studying implementation science, but context is equally important. ²⁰ We need informaticists who understand the context of paramedicine practice to develop the necessary maturity models and theory-based frameworks. For example, the maturity models for an EMR implementation in a hospital consider the various hospital specialties: diagnostics, labs, consulting physicians, etc. ¹⁰ A model for paramedicine must consider integration with mobile equipment, intermittent connectivity, multiple paramedic crews providing treatment to the same patient, parallel agencies (such as fire departments), and potentially multiple integrations and interoperability with different digital health information systems such as hospital and long-term care EMRs and primary care electronic health records. While there may be some overlap in technology or in information needs with other disciplines, the context of paramedicine is sufficiently unique, and it would be difficult or impossible to adapt current models to fit our purposes. Paramedicine can, however, leverage the multitude of frameworks and best practices for developing models available in the informatics world. ³²

Identify opportunities for technology improvement in paramedicine

Despite the increasing rate of digitisation of healthcare, there is a slower adoption and implementation rate of digital health technologies in paramedicine. ²⁹ The lack of a paramedicine-specific informatics subspecialty results in a paucity of health informatics competencies and informatics roles for paramedics, contributing to slow technology uptake.^33,34 It has been shown that paramedics who possess health informatics competencies and an understanding of technology and its applications to paramedicine directly contribute to organisational innovation. ³⁵ Currently, paramedic participation in the development and selection of technology is restricted to those in specialty positions, such as management or physician directors, who often have no specific training in health informatics. ³⁴ This limits the participation of front-line staff and the awareness of current technologies and their viability in paramedicine. If paramedicine is going to leverage advancing technologies to improve services, we need paramedics who understand the technology and how it can be applied in a paramedicine context in roles that can create change.^31,35 This will include paramedics with the skills to integrate technology into research, education and clinical care, data analytics, data integration, and hardware and software development and troubleshooting. ³³ We need both paramedicine leaders with advanced health informatics competencies and paramedic ‘super users’ with basic informatics competencies for decision-making and successful technology implementations.

Evaluate and monitor the performance of technologies

Paramedicine services are pressured to adopt new technologies to improve system outputs. However, paramedicine has yet to develop specific frameworks to evaluate and monitor these technologies or even outcome measures that can describe what ‘success’ looks like. With the exponential increase in generative AI tools in healthcare, generative AI will inevitably be used in paramedicine. Along with AI use, there is the need for a context-specific framework to ensure the tool is effective, safe for patients and trusted by paramedics. ³⁶ For example, when implementing AI-powered demand forecasting, it is critical to have a framework that evaluates the explainability and transparency of how the model makes decisions. ⁵ An evaluation framework may help identify if traditionally marginalised communities have been appropriately included in the predictive modelling. Having paramedicine informaticists who understand how to measure validity, safety, efficiency and satisfaction and who can liaise with vendors to ensure effective partnerships, roadmap maturity, and workflow integration can improve the adoption and effective use of these technologies. ⁵ These roles will require people with the necessary competencies and understanding of informatics, not simply a senior manager who has inherited ‘technology’ as one of many corner-of-the-desk initiatives.

Improve the continuity of patient care

Health data interoperability will be key in improving the continuity of patient care and in ‘downrange’ decision making – where important clinical decisions may depend on data collected on-scene (e.g., first presenting rhythm in a cardiac arrest, etc.). This will be a complex task in paramedicine, requiring an organisational level of interoperability. ²⁵ Paramedicine will require professionals with informatics competencies to drive the changes needed to achieve this level of interoperability and have a seat at the table when interoperability programmes are being discussed at a policy and governance level. ²⁵ For example, programmes like the International Patient Summary, which originated in Europe and is being implemented around the globe, could be a way for paramedics to access critical patient information in a timely manner and vice versa.^37–39 However, paramedicine has yet to be included as a use case in most implementations of the International Patient Summary. Having paramedicine informaticists available as expert resources and meaningfully contributing to these discussions will help improve interoperability by highlighting the importance and contribution of paramedicine in the patient's journey.

Challenges and barriers

Paramedicine, not unlike other branches of healthcare, is currently facing many challenges. Services across the globe are encountering staff shortages, system utilisation strain and offload delays.^40,41 These overwhelming and immediate challenges can make it difficult to dedicate time, effort, and resources to develop a new concept for paramedicine education, research and practice, not to mention that any system change can be met with resistance. However, paramedicine informatics opportunities could contribute to solving these challenges. Improving and accelerating alternate delivery and referral programmes through data integration, easing documentation burden and improving workflows, and researching applications of new and existing technologies to improve system efficiencies are all contributions from informatics that could alleviate system pressures.^42,43

How do we get there

To advance the idea of paramedicine informatics, we must first identify the competencies that these professionals would require. Existing competency frameworks^44,45 could be leveraged and adapted to paramedicine similar to other professions, such as nursing, to be included in entry-to-practice education and continuing education for existing professionals. ⁴⁶ These professionals would then need roles within the organisation at both the front-line and leadership levels, where currently, a lack of defined roles exists. ³⁴ These roles can range from temporary technology implementation to long-term planning and guidance on digital transformations.

With limited resources and increasing pressure to adopt digital technologies, paramedicine services can benefit from the knowledge provided by professionals with this unique skill set. By creating forward-looking vendor contracts, ⁵ ensuring successful implementations, ²⁰ frequent and robust evaluations of existing technologies, and the capabilities to liaise with stakeholders in every healthcare domain, paramedicine informaticists can maximise the benefits of digital health technologies for services, front-line paramedics and our patients. Further research in paramedicine informatics would be valuable in identifying further solutions to challenges such as resistance to change and concerns about technology interfering with patient care. ⁴²

Conclusion

Informatics has a significant role to play in the future of healthcare. Rapid digitisation, the push for widespread health data interoperability, and the use of generative AI to improve clinical care and documentation will be critical for all healthcare organisations in the future. Paramedicine cannot afford to be left behind in this evolution; with the rate of acceleration in technology, this risk grows daily.

As paramedicine continues its journey towards further professionalisation, the development and recognition of paramedicine informatics can provide a pathway to further professional growth and distinguish paramedicine as a unique healthcare profession with specific knowledge frameworks and needs. It will be critical to provide the next generation of paramedics with the informatics competencies they require to succeed. Paramedicine informatics can help our systems get context-specific models and frameworks in place to ensure that our patients and providers can fully benefit from the future of healthcare technology and position paramedicine as drivers of positive change, not merely passengers in someone else's vehicle.