Innovation and its relation to optimal healthcare provision

Innovation development in healthcare has paved paths toward improved system efficiency, quality of patient care, collaboration and communication mechanisms, and cost-effective healthcare services, increasing the overall efficiency of the healthcare system significantly [13].

Recent trends—a perspective of EMR

According to the Office of the National Coordinator for Health Information Technology, as of 2021, over 90% of hospitals and 50% of clinical physicians have adopted and implemented some form of EMR system in their healthcare practice [14]. This trend has been driven by various factors such as government incentives, not-for-profit organizations, and the potential for improved care delivery and cost savings. In addition, the rise in consumerism in healthcare in terms of enhanced use of technology by individuals to manage their health allows them to track their health metrics and communicate with their healthcare providers [15]. This shows that EMR has a dominant positive role in healthcare transformation by increasing the affordability and accessibility of healthcare services while also leading toward improved efficiency and quality of patient care effectively.

Effective usage practices and requirements

The COVID-19 pandemic led to the production of a massive volume of health data, igniting interest in the use of big data analytic tools and artificial intelligence (AI) to improve organizational issues in the healthcare system, predictive and prescriptive analytics, pandemic management, diagnosis, drug discovery, and treatment [16,17,18]. The ever-increasing use of AI and machine learning in healthcare has contributed effectively toward a rigorous and informed analysis of large amounts of data and identifying patterns or trends that may be useful for improving care delivery or identifying potential issues. For instance, AI algorithms can effectively increase the efficacy of prediction related to the likelihood of a patient developing a particular condition based on their medical history and other factors [19]. In addition, the use of other health information technologies, such as telemedicine, increased from 0.3% of all clinical encounters before the pandemic to 23.6% of all encounters in 2020 [20]. Given the timesaving and convenience of telemedicine coupled with the experience of physicians and patients in using telemedicine during the pandemic, the widespread use of such technologies is likely to continue in the post-pandemic era [21].

The leveraging of these technological advances relies significantly on interoperability and collaboration in healthcare departments by enabling different systems to exchange and use patient data. Hence, in addition to developing a centralized EMR with a standardized user interface, these recent trends in the use of health information technologies also require robust integration with EMRs.

Healthcare dynamics—a regulatory perspective

Governments significantly influence healthcare through policy development, funding allocation, and shaping delivery models, which can both facilitate and hinder healthcare innovation [22]. For instance, the US Affordable Care Act of 2010 enhanced healthcare services access, improved care quality, reduced costs, and improved patient outcomes [23]. Notably, the US government played a crucial role in promoting EMR implementation, making it mandatory for hospitals to transition to digital format. It further invested $27 million as part of the Health Information Technology for Economic and Clinical Health (HITECH) Act [24], leading to a near-universal EMR implementation in US hospitals and demonstrating the government’s immense influence on healthcare innovation.

Challenges to health innovation

Despite the numerous benefits, their growing need in the post-pandemic era, and the governmental push for widespread adoption, EMR’s effectiveness can be hindered by lack of unification, particularly in the US healthcare system [25]. For example, with the growing number of patients with multimorbidity, there has been a growing call to restructure the US primary care system to multidisciplinary care [26, 27]. Multidisciplinary care can include (i) collaboration through shared consultations, (ii) co-located teams of highly coordinated healthcare professionals but without shared consultations, (iii) collaboration via referral and counter-referral, which usually has a clinical leader who collates medical information from other specialists and guides the overall care of the patients, and (iv) non-hierarchical continuous horizontal collaboration which lacks a distinctive clinical leader [26]. While EMRs can significantly improve healthcare procedures, diagnoses, and symptom management in all four types of multidisciplinary care models, the use of proprietary formats and strict privacy protocols by different EMR systems can impede information sharing between healthcare organizations [28], especially when some of the team members are outside of the primary point of care [27, 29].

In addition, many patients may travel across state lines to avail medical facilities unavailable locally. For instance, about 8% of patients travel across state lines in the US to avail opioid treatment programs [30] or access abortion facilities [31]. The lack of non-centralized EMR means that the health data cannot be readily shared between healthcare practitioners beyond what is recalled or volunteered by the patient traveling across state lines to avail healthcare, which may exacerbate the quality of care and patient satisfaction.

Hence, it is essential to standardize data formats and develop interoperability national standards to maximize EMR benefits, enhance data quality, and boost healthcare accessibility and quality.