INTRODUCTION

The healthcare industry is constantly experiencing change. How the industry responds will be determined by numerous influences. The influences include data and platforms, digital therapeutics, healthcare reform, consumer-centric products, care communities, and a shift from healthcare to health and wellness (DeloitteHealth, 2019; Siwicki, 2019). As with other industries, healthcare organizations must be business savvy, risk averse, and persist in the use of meaningful evidence-based data to achieve quality, safety, and sustainable value-based outcomes. This chapter will focus on the drivers affecting the current and future healthcare landscape and how technology will continue to generate databases that are essential for sustainability, policy development, and meeting regulatory requirements and consumer demands.

The chapters that follow will include information necessary to accelerate knowledge, improve decision-making, and enable healthcare professionals, students, and educators to use data to achieve quality, safety, and value-based outcomes. Specifically, Chapter 2 focuses on a new age of imperatives that will impact quality, safety, and value-based outcomes within the context of new rules, leadership skills, and a competitive healthcare market. Chapter 3 concentrates on different quality improvement tools, methods, and selecting the right tool for interprofessional projects. Tools that are pivotal to planning data collection and analysis will be explored. Chapter 4 provides information on the value of data to inform administrative and clinical decisions to achieve peak performance, anchor strategic initiatives, and improve operational thinking. Chapter 5 is an overview to understand how data science accelerates discovery, improves decisions, and creates a data-driven economy for healthcare success. Chapter 6 discusses the advantage of collecting, managing, and analyzing big data and how the 5Vs (volume, velocity, veracity, variety, and value) are central to mapping and designing interprofessional strategies to promote organization-wide improvement. Chapter 7 provides information on how data influences and guides the development, implementation, and interpretation of policy and regulations by interprofessional teams. Chapter 8 is a discussion of the importance of innovation, data diffusion, and dissemination necessary for interprofessional teams who participate in data improvement processes. Chapter 9 presents information needed by interprofessional teams when developing a business case for change and practice innovation. Chapter 10 is an introduction on how consumer demands and data are driving change by consumers and leveraging interprofessional team power. Chapter 11 provides an introduction to data mining tools and techniques beneficial to interprofessional teams. Chapter 12 discusses how interprofessional teams use evidence to guide quality and safety initiatives. Chapter 13 focuses on how interprofessional teams extract and use data effectively. Chapter 14 provides a futuristic perspective of data and charting a course for care in the 21st and beyond.

Each of the chapters is central to understanding how data frames quality, safety, innovation, and sustainability in interprofessional practice as consumers become more engaged in their care. Adding value to each chapter are case exemplars for application authored by experts from practice, management, and education.

CURRENT AND FUTURE HEALTHCARE INFLUENCES AND DRIVERS

On a daily basis, leaders in healthcare organizations are confronted with the rising costs of care, shortfalls of quality and efficiency of care, and how interprofessional teams can collaboratively use evidence-based data to achieve improved results, satisfy patients, and create data rich infrastructures. Healthcare of the future will be driven by innumerable data connectivity and consumer engagement. Archetypes that create strategic initiatives and improved business models will be commonplace in order to develop a “culture of health, reduce disparities, and improve well-being of the U.S. population in the 21st century” (DeloitteHealth, 2019; National Academy of Medicine, 2019, para. 2).

Data and platforms are the cornerstone of a health ecosystem that generates decision-making insights fundamental to invest in new and improved healthcare technology (DeloitteHealth, 2019). With the increasing cost burden generated by chronic health conditions and an aging demographic, the use of data is a beneficial investment in the digital health technology market. This investment will offer individuals across the care continuum expanded opportunities to manage well-being. Favorable reimbursement policy development and efficacy research are possible as digital technology expands.

Digital therapeutics has increasingly become a debated and discussed topic in order to establish a comprehensive network of options for disorders and diseases. According to the Digital Therapeutics Alliance, “digital therapeutics deliver evidence-based therapeutic interventions to patients that are driven by high-quality software programs to prevent, manage, or treat a broad spectrum of physical, mental, and behavioral conditions” (Digital Therapeutics Alliance, 2019, p.1). Digital therapeutics produces a broader product from others available in the digital health landscape (Comstock, 2018). The benefits in this field are infinite for all stakeholders as it evolves.

Nationally, healthcare reform continues to remain an agenda item as prices escalate, mandates for quality and safety outcomes increase, and prevention services expand (Centers for Medicare and Medicaid Services [CMS], 2011a, 2011b). While the Patient Protection and Affordable Care Act of 2010 remains law, parts have been restructured with actions that create positive and negative outcomes (Office of Legislative Council, 2010). Regardless of the changes, meaningful use, collection, and analysis of data remain central to healthcare organizations survival. Understanding the value of data, selecting various digital platforms and devices, and analysis of information will continue to be markers for success as future reforms occur and interprofessional teams collectively engage in improvement activities.

The growth of consumer engagement in healthcare continues to expand and consumer-centric products are continuously being introduced into the market. In 2016, 46% of U.S. consumers were active users of digital health devices (Adams et al., 2016). The demand will continue as healthcare consumers become more knowledgeable about the benefits of preventive health and digital products that are unique to their behavior, lifestyle, genetics, and the environment. While healthcare products are marketed daily, developers must consider that each consumer is structurally, emotionally, and chemically different (Babalola, 2017). Consider for example the healthcare consumer who has the option to trial and purchase a phone application to measure pulse rates during walking. Based upon market demand, the product margin is predictable based on volume. Unlike the phone application, cardiac bypass surgery does not offer a trial period before the procedure is performed (Babalola, 2017; Mwachofi & Al-Assaf, 2011). This presents developers of new products with many challenges. Future research and development departments will require large quantities of data collection and analysis as new consumer-centric health products are marketed in order to personalize services.

The U.S. population continues to age at a rapid rate. As Americans age, the number of continuing care communities (CCCs) continue to grow contributing to a demographic who are active, use digital technologies to manage health status for a productive and meaningful life, and seek care communities for continuum of care options (Szlauderbach, 2020). As the popularity of CCCs increase, multiple markets will be tasked to develop new technologies that promote preventive health dedicated to health and well-being. Metrics will guide data collection and analysis that focus on outcomes important to individuals, families, and care providers (Rowe et al., 2016).

The shift from health to health and wellness will continue to be a significant influence in contemporary society as life expectancy anddemands for new technologies and wellness-focused commodities increase (Alder et al., 2016). Influencing the shift is data coupled with personalized health coaching in order to create a pathway that optimizes individual healthy outcomes. As data from genetic testing are collected and analyzed, research opportunities that focus on prevention and care for illnesses will transpire (Mann, 2019).

HEALTHCARE TECHNOLOGY ADVANCEMENTS DURING THE PAST DECADE

In the past decade, the healthcare industry has experienced an information revolution similar to the industrial revolution. The information revolution is credited with a variety of technology advancements in an era where the electronic medical record was adopted. As healthcare organizations leverage technology to improve outcomes, the technology advances of the past decade provide roadmaps for developing a future landscape for transforming quality, while ensuring safe and affordable care. As outcome-driven markets increase, digital health markets will continue to soar. In 2018, the digital health market represented a funding investment increase by 230% with predictions to continuing rising (Zweig et al., 2018).

Change in healthcare is constant and how data are obtained and disseminated impacts daily operations. Quantum leaps in efficiency and effectiveness have and will continue to occur with the diffusion of technology and availability of electronic networks that provide instant access across all points of care (Geibert, 2017). Technology has evolved with a shift from power to value as evidenced by greater throughput and efficiency in emergency departments and clinics with the use of protocol automation.

The previous example is only one of the many advances where value, both human and financial, is attributed to technology advances during the past decade. The following technological advances are further examples that will transform healthcare and the importance of data, as individuals remain the centrality of care delivery beyond the 21st century.

Telemedicine has gained much popularity since its introduction, offering opportunities to treat chronic diseases without traditional visits to providers and expanded accessibility to care in remote areas. One of the most documented uses of telepresence is in mental health. Patients receive prevention, treatment, and reduced stigma associated with office visits using this technology (Newman, 2017).

Patient-centric devices that are wearable have continuously entered the market. Patients are able to transmit cardiac, weight, pulse, and oxygen level information without visiting a provider’s office. Future advancements will offer opportunities where biochips will aid in the treatment and management of chronic disorders such as diabetes, cardiac disease, and dosing requirements required from many chronic conditions (Shah, 2015).

Traditional software of the past decade is incapable of providing seamless data to consumers and providers. Cloud-based technologies offer new advances for rapid capture and transmission of electronic medical records (Shah, 2015). This advancement does however raise red flags related to patient privacy and data security. Healthcare organizations are therefore confronted with the question, “is the data value greater than financial gains”? (Newman, 2017). The answer remains a significant challenge nationally and globally in healthcare organizations and information technology circles.

Maximizing technology and use of data management systems during the past decade has offered multiple opportunities in healthcare. The value of big and small data remains a valuable source of information when analyzed and integrated into strategic and financial planning. Big data that are generated from multiple sources offer a snapshot of what is occurring without answering why. The data are used to describe, interpret, and predict (Henley, 2014). Small data on the other hand provides material to answer a specific question or address a problem. Small data can support big data by generating new knowledge and has potential for change in care, operational efficiency, and satisfaction (McCartney, 2015). Future healthcare demands will require shifts from big and small data to meaningful specialty-specific analytics. The prominence of specialty-specific analytics will intensify as healthcare organizations access, share, and analyze evidence that will include population health management and efficient treatment pathways (Das, 2018).

These are only a few of the many advances in the past decade that will benefit the healthcare industry. Future developments remain promising and offer opportunities for entrepreneurs to capture segments of healthcare technology markets.

MEETING HEALTHCARE POLICY, REGULATIONS, AND CONSUMER DEMANDS

Meeting policy, regulations, and consumer demands require continuous actions by any healthcare organization due to the volumes of data generated daily. The best-case scenario of how data influences each of these demands is characteristic of the activities related to each demand.

Policy in healthcare establishes a general plan of action to guide desired outcomes and make decisions. For example, policies guide how data are collected, analyzed, and used to improve healthcare quality, safety, and efficiency. Policy changes occur often due to provisions within healthcare reforms, federal and state requirements, the Centers of Medicare and Medicaid provisions, the Joint Commission Standards, and other accrediting requirements. Therefore, communication of health policies to employees and use of technologies that regularly update them based on evidence are foundational to success, consistent practice, and avoidance of deficiencies and penalties (Leahy, 2019).

The exponential number of federal regulations that affect the healthcare industry requires significant resources in order to meet the demands. According to the American Hospital Association (AHA) (2017), there are 629 regulatory requirements mandated by four agencies that promulgate the requirements. The agencies include the Centers for Medicare and Medicaid, the Office of Civil Rights, the Office of Inspector General, and the Office of the National Coordinator for Health Information Technology. While regulatory frameworks are necessary for ensuring basic standards compliance, it is estimated that $39 billion per year is dedicated to comply with the administrative aspects of compliance. While the requirements are steeped in a foundation aimed at ensuring patients receive quality and safe care, the results evidence less time spent in patient care and spiraling healthcare costs (AHA, 2017; Singh, 2018).

How the healthcare industry continues to respond to the regulatory challenges is unclear. However, there is current evidence that the challenges have resulted in fines for data breaches, increased information technology infrastructure costs, lowering of reimbursements, and fraudulent claims to identify a few (Singh, 2018). One thing remains constant, regulatory demands will continue. Capturing meaningful data and thorough analysis remains a key ingredient for the vitality of healthcare organizations and dealing with human lives.

Healthcare organizations depend on patients in order to generate revenues. Understanding patient needs and demands is requisite to remain competitive and maintain loyalty. Using data from a variety of sources such as satisfaction scores, type and frequency of services used, and health data create a data-centric culture where patient-centrality becomes central to strategic decisions and actions (Betts & Korenda, 2018). More patients are reviewing quality ratings and prices when making decisions regarding care and providers. Engaging patients to become active consumers of health and well-being can result in improved outcomes, improve the patient experience, lower healthcare costs, and ultimately meet patient demands.

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