An Introduction to Healthcare Informatics

Building Data-Driven Tools

Peter Mccaffrey

• Publisher: Academic Press
• Year: 2020
• ISBN:
  9780128149164
• Topic: Medicine
• Subtopic: Biotechnology in Medicine

An Introduction to Healthcare Informatics: Building Data-Driven Tools bridges the gap between the current healthcare IT landscape and cutting edge technologies in data science, cloud infrastructure, application development and even artificial intelligence. Information technology encompasses several rapidly evolving areas, however healthcare as a field suffers from a relatively archaic technology landscape and a lack of curriculum to effectively train its millions of practitioners in the skills they need to utilize data and related tools.

The book discusses topics such as data access, data analysis, big data current landscape and application architecture. Additionally, it encompasses a discussion on the future developments in the field. This book provides physicians, nurses and health scientists with the concepts and skills necessary to work with analysts and IT professionals and even perform analysis and application architecture themselves.

• Presents case-based learning relevant to healthcare, bringing each concept accompanied by an example which becomes critical when explaining the function of SQL, databases, basic models etc.
• Provides a roadmap for implementing modern technologies and design patters in a healthcare setting, helping the reader to understand both the archaic enterprise systems that often exist in hospitals as well as emerging tools and how they can be used together
• Explains healthcare-specific stakeholders and the management of analytical projects within healthcare, allowing healthcare practitioners to successfully navigate the political and bureaucratic challenges to implementation
• Brings diagrams for each example and technology describing how they operate individually as well as how they fit into a larger reference architecture built upon throughout the book

Section 1

Storing and accessing data

Chapter 1: The healthcare IT landscape

Abstract

Healthcare is a unique setting for many reasons: regulatory and legal, cultural, professional, and, most of all, technical. The confluence of these multiple factors creates a complex and nuanced technical landscape that stands apart from any other field. Despite this, the healthcare informatician must be intimately familiar with both the components of this landscape and the forces, which have caused them to look as they do. This chapter will cover a brief history of the electronic medical record system and electronic order entry. From there, it will focus on the standards of interoperation, which will serve as the subject of subsequent Chapters, and it will describe the regulatory pressures, which have influenced their development (e.g., the HITECH Act and its relationship to reimbursement). We will also discuss the typical flow of data between IT components in a healthcare system. Finally, we will address the organizational concerns, including security, that have arisen around these interoperating components.

After reading this chapter, you should be able to describe the key IT components of a modern hospital and explain the driving regulatory and organizational pressures that motivate and constrain them. You should also be able to explain how data move within a healthcare institution and the critical interoperability and security challenges, which arise in that flow.

Keywords

Healthcare IT; Information technology; Healthcare informatics; Healthcare data; Interoperability

1.1: How we got here and the growth of healthcare IT

As a member of the modern healthcare workforce, technology seems like an inextricable part of the clinical experience. For many, interacting with the myriad components of healthcare technology can represent an onerous aspect of clinical work and the blame for such burdensome interactions is commonly placed on IT departments and hospital management as being woefully out of touch with providers on the front lines. While this certainly bears some truth, there is much more to the story of how healthcare IT has evolved. In this section, we will discuss the developmental history of modern healthcare IT with the goal of understanding of the dynamics that have shaped its current incarnation.

Without reaching back too far in the history of healthcare, it can be said that much of the deep history of medical practice (mainly that preceding the late 19th century) was without a central organizing force.¹ Professional and intellectual societies certainly offered a central space for aggregating and sharing knowledge of diagnostic and treatment practices, and yet healthcare remained largely a cottage industry of individual practitioners. Clinical luminaries such as Dr. William Osler certainly improved upon this state of personalized, artisanal medicine by leading in the development of more consistent and robust training processes in the form of the clinical residency, the routine use of laboratory testing, and the establishment of routine clinical rounds but, still, the professional implementation of healthcare was situated mainly in the small clinic and placed within the hands of the expert individual.²

The advent of modern health insurance, however, represented a deeply transformative force in healthcare. Although there had been insurance products focused on disability and coverage for accidents, it was not until the 1920s that hospitals began offering payment plans through which patients could cover medical expenses themselves. These hospital-based policies quickly became aggregated into the first Blue Cross organizations in the 1930s. The second World War accelerated the growth of structured medical expense coverage as the wage freeze drove employers to create and offer employer-sponsored health benefits as a means of attracting employees.³ This was mirrored in a Federal effort to provide such coverage benefits to those without employer-sponsored or private plans, leading to the development of Medicare in the mid-1960s.⁴ Further maturation of insurance instruments brought about more complex processes for defining and submitting claims, such as the creation of diagnosis-related groups in the 1980s, which required more data to be provided to insurers.⁵

Healthcare systems responded to thinning profit margins and increasingly complex requirements for successful reimbursement by consolidating into large, multiinstitution integrated delivery networks. These became a popular trend in the 1990s and required hospitals to share and reconcile information not just intra- but intermurally.⁶ Importantly, the 90s and 2000s brought about an increasing concern on the part of payers (largely the Centers for Medicare and Medicaid Services) that physician fee-for-service practice was susceptible to exploitation through overutilization of tests and procedures. The response was a shift toward outcomes-based payment instruments, which again heightened the demand both for more detail in claims submissions and for analytical reporting of key performance and outcomes measures such as readmission rates.⁷

The relevance of these historical punctuations and their impact on the implementation of healthcare cannot be understated. With the rapid growth and development of health insurance and the accordant rise in healthcare costs, the industry itself became financially operated by the insurance industry and, as a direct consequence, the mechanics of healthcare became increasingly parceled into claimable and billable services. Healthcare facilities, in an attempt to render billable services at scale, became powerful instruments of insurance revenue provided that they could efficiently track and execute services rendered and their resulting claims.

This historical context lends strong justification to the axiom that data are the currency of healthcare because without the ability to track and organize data in order to prove that services were justified and implemented, the entire hospital organism ceases to function. It is unsurprising, then, that some electronic systems naturally arose from this demand but perhaps equally unsurprising that, for many institutions, such systems did not. Early examples of electronic health information systems began to appear in the 1960s with Massachusetts General Hospital's creation of MUMPS, a database and early programming language for storing patient record data on mainframe systems and the subject of an entire chapter of this book, and the Regenstrief Institute's development the first electronic medical record system shortly thereafter. Although such systems provided clear benefit in the ability to store, retrieve, and organize record data, these earlier attempts were often confined to government hospitals and more tech-forward medical institutions, while mainstream physician practices and hospitals were turned off by the high cost and staffing demands required to maintain and operate these systems.

The digital transformation proceeded slowly over the concluding decades of the 20th century, but it was 2009, and the passing of the American Reinvestment & Recovery Act (ARRA) that brought unprecedentedly rapid digitization to healthcare organizations. Among the many modernization efforts included in this legislation was the Health Information Technology for Economic and Clinical Health (HITECH) Act, which introduced the concept of meaningful use, a regulated definition of the implementation and systematic engagement with electronic medical information systems.⁸ Importantly, meaningful use was incentivized through payments disbursed by the Centers for Medicare & Medicaid Services—the largest healthcare payer in the United States. This combined effectively with the aforementioned evolution in health insurance to catalyze the mass transformation of healthcare from paper to digital infrastructure. This transformation has been brisk as healthcare institutions have faced financial pressure to demonstrate meaningful use through pervasive and consistent interaction with electronic information systems and to preserve revenue amid increasing demand for claim auditability, contextual information, and performance monitoring. Likewise, this has created a welcome boom for the providers of electronic health information systems, many of whom had tools based upon more antiquated technology, which were presented with a sudden need to scale through federally driven market demand.

This rapid scaling has not been without its share of serious complications, foremost of which is the security of healthcare information as it flows through complex and often adolescent technical ecosystems. Healthcare institutions are caught between an immense pressure to continue to drive revenue through successfully reimbursed claims, which requires increasing the fluidity of data collection and access, and the grave threats of financial penalty and loss of accreditation that accompany any misadventure in doing so.

1.2: The role of informatics

The trajectory of healthcare information technology and the pressures that have shaped its history and current form hopefully prove useful in understanding why healthcare information systems face the challenges of interoperation for which they are so often criticized. This historical context hopefully also sheds light on why the management of these systems is traditionally focused on risk aversion and change mitigation before technical and developmental creativity and offers some measure of explanation as to why analytics can be so often frustrated by uncooperative technology. The story of the growth and development of healthcare IT is, in essence, one of unsynchronized timing where what is ideal from a technology standpoint, what is achievable from a pragmatic standpoint, and what is imminently necessary from a regulatory compliance standpoint are almost never aligned. This is, however, the setting in which the healthcare informaticist and data engineer work and for whom understanding the many forces that shape the healthcare IT landscape is so critical.

Although this book informs the reader about the many shapes and functions of healthcare data, it also serves as a statement about the expected role of informatics and the locations in which technical creativity must be deployed. Healthcare is a challenging environment but at the time of this writing, new, formerly hypothetical advances in the form of big data, rich reporting, machine learning, and artificial intelligence are nonetheless quickly becoming vehicles for real value in adjacent fields. Granted, their origins are comparatively unencumbered by the technical debt present in so many healthcare systems, but the need to make healthcare fertile ground for their growth and impact is perhaps more real now than ever before. Thus, the goal of informatics is to understand the often suboptimal anatomy of healthcare IT and the principles of effective problem solving and analytical engineering such that those suboptimal obstacles may not simply be identified or accommodated but that they may be solved. This is a rigorous and ambitious task, but it is wholly worth the requisite effort.

The following three sections will serve as a review of the ...