week 1 healthcare IT

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10THE IMPACT OF TECHNOLOGY ON US HEALTHCARE

Healthcare is the only civil system where new technology makes prices go up instead of down.

—Jaan Tallinn

Learning Objectives

• Analyze the relationship between healthcare costs and the constant development of new medical technologies.

• Gain familiarity with a variety of emerging medical technologies. • Evaluate the impact of e-therapy, telemedicine, e-health, and telehealth

on the US healthcare system. • Recognize the pros and cons of electronic health records and electronic

medical records. • Understand how information technology and value-based care are

interdependent. • Apply key principles of cybersecurity to the workings of a healthcare

organization.

Medical and Information Technology

This chapter will focus on the impact of technology on the US healthcare system (see exhibit 10.1). Deciding where to start a discussion of this topic is difficult, because we will be studying emerging technologies and their impact on healthcare in perpetuity! Technological advances and innovations occur at a rapid pace, almost beyond our system’s ability to manage the change. Evolving technologies can help expand the capabilities of our healthcare system, improve quality, and increase access, although—as stated in Tallinn’s quote at the start of the chapter—they can also be a major driver of costs.

Technology in healthcare largely falls into one of three categories: (1) medical technology, (2) information technology, and (3) data analytics and knowledge management. The additional area of pharmaceutical technology will be addressed in chapter 11.

C o p y r i g h t 2 0 2 1 . A U P H A / H A P B o o k .

A l l r i g h t s r e s e r v e d . M a y n o t b e r e p r o d u c e d i n a n y f o r m w i t h o u t p e r m i s s i o n f r o m t h e p u b l i s h e r , e x c e p t f a i r u s e s p e r m i t t e d u n d e r U . S . o r a p p l i c a b l e c o p y r i g h t l a w .

EBSCO Publishing : eBook Collection (EBSCOhost) - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS AN: 2452145 ; Stephen L. Wagner.; The United States Healthcare System: Overview, Driving Forces, and Outlook for the Future Account: s4264928.main.eds

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Cost Equitable

access

Quality

• Nature of our complex system • Historical issues that have influenced the

development of the system •

• Comparison with other developed countries

• Components of our healthcare system • People and providers • • Financing a massive system • • Medical and information technology • The pharmaceutical industry • Complementary and alternative

medicine • Politics/economics • The future of the system

The Aim of the Healthcare System Issues That Require Our Attention

For patients

Provider experience

Beliefs and attitudes about health and healthcare

Patient care—the purpose of the system

Quality—easier said than done

EXHIBIT 10.1 Area of Focus

for This Chapter

Medical technology involves the application of science and technical knowledge for the improvement of medical care and the health of society (Cohen et al. 2004). The phrase is often used to refer specifically to tech- nologies involved in direct patient care. Examples may include the following:

• Telemedicine • Implantable devices • Robotically assisted surgical devices • Genomics • Precision medicine • Diagnostics • Radiology and imagining • Laboratory services • Tissue engineering/replacement and artificial organs

Medical technology has brought about tremendous improvement in our abil- ity to diagnose and treat various conditions, yet it has also contributed to sky- rocketing costs and an increased dependency on technology and the healthcare system for our well-being (Kamra, Singh, and De 2016; Kumar 2011).

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The terms information technology (IT) and health information technol- ogy (HIT), for the purposes of this discussion, are interchangeable, though specific definitions may vary. The North Dakota Information Technology Department (2019) defines information technology broadly as “the use of hardware, software, services and supporting infrastructure to manage and deliver information using voice, data, and video.” The definition further states that IT encompasses all of the following:

• All computers with a human interface • All computer peripherals that will not operate unless connected to a

computer or network • All voice, video, and data networks and the equipment, staff, and

purchased services needed to operate them • All technology services provided by vendors or contractors • All functions associated with developing, purchasing, licensing, or

maintaining software

The definition of IT in healthcare can be further refined to refer to the elec- tronic systems that healthcare professionals—and, increasingly, patients—use to store, share, and analyze health information.

Key concerns of HIT include the following (Office of the National Coordinator for Health Information Technology [ONC] 2018a):

• Electronic health records (EHRs), which help providers record, store, access, and share patient information digitally

• Personal health records (PHRs), which can be used to track information about the care a patient receives and various other health issues outside the formal care environment (e.g., eating behavior, exercise, blood pressure readings)

• Electronic prescribing (e-prescribing), which allows for direct, paperless communication with a pharmacy (minimizing risk of lost prescriptions or problems with legibility)

• Privacy and security (i.e., cybersecurity) initiatives to protect personal health information (PHI)—for example, by encryption that allows only authorized people to read it.

The category of data analytics and knowledge management includes technologies that support effective decision making in healthcare. Examples include the following:

• Analytical systems that draw vast amounts of data from diverse sources, sometimes known as “big data” (NEJM Catalyst 2018; Dinov et al. 2016)

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• Evidence-based practice-support systems (Kathol, deGruy, and Rollman 2014)

• Medical decision-support systems incorporating artificial intelligence (Eckerson 2007; Schiff 2012)

• Other decision-making technologies (Alliance of Advanced BioMedical Engineering 2019; Feldman, Martin, and Skotnes 2012; Taylor 2017; Siegel 2013; Medical Futurist 2016; Zimmer 2011).

Medical Technologies in Constant Development

Our use of technology in healthcare is vast, and new developments contin- ually emerge, bringing both opportunities and challenges (Ashrafian et al. 2017; Westgate 2017). Exhibit 10.2 provides just a small sampling of the important technologies we see in healthcare today. Many technologies are brand new or still in development, whereas others are well established. Echocardiogram (EKG) machines, for instance, have been around for

Imaging Ultrasound devices Positron emission tomography (PET scan) Teleradiology Nuclear imaging Magnetic resonance imaging (MRI) Intraoperative MRI

Diagnostic Testing Monoclonal antibodies to detect pathogens and evidence of infection (e.g., HIV) Genetic testing for gene mutations that cause disease (e.g., amyotrophic lateral

sclerosis) Advanced laboratory services to detect early-stage disease (e.g., Alzheimer’s

disease, Parkinson’s disease) Noninvasive testing of cognitive decline

Surgical Treatments and Technologies Artificial joints (e.g., hips, knees, shoulders) Implantable cardiac devices for monitoring heart function Implantable cardiac devices for treatment (e.g., defibrillators, pacemakers,

stents) Minimally invasive surgical techniques such as those using a laparoscope (e.g.,

appendectomy, cholecystectomy, hysterectomy) Reconstructive surgery using donor- or patient-derived tissues (e.g., coronary

bypass, skin graft, corneal transplant)

EXHIBIT 10.2 Healthcare Technology

Examples

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more than 100 years; the Dutch physiologist Wilhelm Einthoven devel- oped the machine in the late 1800s, eventually earning a Nobel Prize (Rubin 2017).

Numerous technologies have been refined and improved over the course of many years, to the point that procedures that once were largely unknown—hip replacements and back surgeries, for instance—are now commonplace (Anderson, Neary, and Pickstone 2007; Wolford, Palso, and Bercovitz 2015). Our future technologies continually evolve from the tech- nologies that exist in the present, becoming much more advanced with the passage of time. Today, cameras small enough be swallowed have transformed traditional procedures such as colonoscopies.

Many of the wearable or implantable technologies in use today (e.g., smart watches) developed from the miniaturization of devices that were pre- viously too large or too heavy for that kind of use (Kirby 2016; Medtech Plus 2019). Wearable monitoring technologies are a major area of development for healthcare, given their ability to collect continuous data and provide snap- shots of a patient’s health status at any given time. Modern material science, biomedical research, and bioengineering have made these devices a reality, and their uses, applications, and possibilities continue to be explored (Mara- khimov and Joo 2017). Chapter 14 will examine the future implications of these and other technological advances in greater detail.

Telemedicine, E-health, and Telehealth

Telemedicine, e-health (sometimes written as eHealth), and telehealth represent exciting new areas of service delivery, with the potential to be among the biggest disruptors ever seen in healthcare. The terms are closely related—in that they all involve the delivery of health-related information and services electronically via the internet—yet they have subtle distinc- tions. Telemedicine refers to the electronic delivery of treatment to patients, as an alternative to face-to-face care. E-health and telehealth, on the other hand, are more general terms that can refer to a variety of health-related services, including patient education. An important component of e-health is mHealth, which pertains specifically to the use of mobile technologies (Otto et al. 2018).

Telemedicine and e-health activities may be either synchronous or asynchronous in nature. Synchronous activities are those that occur in real time—for instance, face-to-face videoconferencing. Asynchronous activities do not occur in real time but rather involve the storage and forwarding of information; use of an online educational module would be one such exam- ple (Ruiz, Mintzer, and Leipzig 2006; Verhoeven et al. 2010).

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Overcoming Limitations of Geography As noted in previous chapters, healthcare delivery, access, costs, and quality can vary widely from one location to another, and such discrepancies have long been a concern for people living in remote or underserved areas. If a patient lives 200 miles away from the nearest specialist, accessing needed services can be difficult. And when the travel is too demanding, the patient might choose to simply not keep regular appointments, which then becomes a compliance issue.

For many years, healthcare has been regarded as a “local matter,” and in some respects it still is: If you are having a heart attack, you will need immediate service at the local emergency room. In many other situations, however, telemedicine and e-health offer solutions that can minimize the need for travel and provide access to important services regardless of geogra- phy; in many cases, they can reduce costs as well.

As patients gain access to providers beyond their local areas, options for acute, chronic, and preventive services multiply, and competition increases. With the speed and ubiquitous nature of the internet, patients today can see a doctor across the continent or even in another country if they prefer (Miyazaki et al. 2012; American Hospital Association 2017; Biparti- san Policy Center 2018; Knickman and Kovner 2015; Varghese and Phillips 2009). Some barriers still exist, such as regulation and licensing issues, but continued technological advances and regulatory changes are expected to further expand the availability of services in the years ahead (Weiss and Pol- lack 2017; Dinesen et al. 2016; Dinesen and Toft 2009). Forward-thinking scholars have written extensively about this reality for many years (Heinzel- mann, Lugn, and Kvedar 2005; Huston and Huston 2000; LaMay 1997).

Implications for Mental and Behavioral Health The expansion of services through digital modalities is having a major impact in the areas of mental and behavioral health. For many years, shortages of qualified professionals, maldistribution of services, and issues of patient compliance have hindered the effective treatment of people with mental and behavioral health needs (Lake and Turner 2017). As many as 25 percent of patients who visit a primary care office have diagnosable mental illnesses, yet the conditions have often gone untreated because of the limited availability of personnel and resources. With telemedicine, however, mental and behav- ioral health services can be provided remotely with little delay, embedded in primary care processes, and made more readily available to people in rural and underserved areas (Townley and Yalowich 2015; Mace, Boccanelli, and Dormond 2018).

Mace, Boccanelli, and Dormond (2018) conducted a study of 329 behavioral health provider organizations representing all 50 states, plus

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additional informants, and they found that 48 percent of respondents used telehealth for behavioral health services. Direct videoconferencing was the most commonly used modality, most frequently used by psychiatrists and mental health counselors. The study also identified several barriers to imple- mentation, most notably reimbursement issues, cost of implementation, lack of organizational and political leadership, workforce shortages, the need for staff education and training, and reluctance on the part of clients. A number of legal and ethical issues still need to be resolved concerning telemedicine for mental and behavioral health, and a consensus on best practices for these areas remains to be developed (Kavalaris et al. 2015; Novotney 2011; Donkin et al. 2011; Lutterman et al. 2017).

Overcoming Barriers to Change Resistance to change—from both patients and providers—can be a serious barrier to telemedicine initiatives and other innovations (Linkous 2012). People often have a tendency to resist change, whether out of fear, uncer- tainty, or the idea that “if it ain’t broke, don’t fix it” (Gorman 2015; Kumar and Khiljee 2016). Gilley, Godek, and Gilley (2009) describe such resistance within organizations as “organizational immunity to change.”

Additional barriers and complications come into play when tech- nologies cross multiple governmental jurisdictions. For instance, if video- conferencing is used across state lines, the psychiatrist might need to obtain a license in the state in which the services are received. Questions of liability and ethics may also arise. If somebody from India, for example, is delivering healthcare via the internet to a patient in the United States, who is liable when a problem occurs? The law is still developing in this area (American Medical Association [AMA] 2015; Parimbelli et al. 2018; Stanberry 2006).

Morris, Wooding, and Grant (2011) found that, on average, newly developed health interventions needed 17 years before they were fully accepted by healthcare providers. Everett Rogers (2003), who wrote extensively on the diffusion of innovation and the barriers to that diffu- sion, identified five groups based on the speed with which they adopt new technology:

• Innovators (representing about 2.5 percent of the population) • Early adopters (13.5 percent of the population) • Early majority (34 percent of the population) • Late majority (34 percent of the population) • Laggards (16 percent of the population)

This distribution roughly translates to a bell-shaped curve.

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The AMA (2014) has developed a framework for telemedicine to help guide its development and implementation. Key elements include the following:

• Developing a solid evidence base • Promoting the patient–physician relationship and care coordination • Ensuring that physicians are able practice in the patient’s state • Identifying technical solutions and requirements • Enabling appropriate reporting, payment, and coverage • Providing education and tools for physicians

Information Management

The field of information management encompasses a large array of techno- logical, managerial, and analytical processes. Organizations often produce a vast quantity of data yet have difficulty using it, because it is not in the form of usable information. It is sometimes said that “we are drowning in a sea of data, but starving for information.” Information management seeks to address that concern.

Healthcare organizations collect information from a wide variety of sources, including the following:

• Medical records from all sources available • Demographic information about the patient • Treatment plans • Identification of the patient within the last provider organization • Details of the admitting/receiving clerk • Insurance/health plan information • Relevant appointments • Diagnoses • Allergies • Medication lists • Physician orders • Anticipated goals (care plan), including rehabilitation plans • Home health/hospice information • Follow-up notes and plans • Nursing details • Self-care status • Disabilities and impairments

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• Nutrition details • Therapist details • Social service details • Laboratory systems information • Imaging systems, or picture archiving and communication (PAC)

systems • Human resource systems • Accounting systems • Financial management systems

Data collected from these sources are then organized, collated, and analyzed to produce usable information that can be applied in the healthcare setting or for administrative purposes. Organizations often use systems called data warehouses to manage this abundance of information. Data warehouses are not the same as databases. Whereas a database is “any collection of data orga- nized for storage, accessibility, and retrieval,” a data warehouse is a specific type of database that “integrates copies of transaction data from disparate source systems and provisions them for analytical use” (Cardon 2018).

Health informatics uses these stored data and goes beyond the empha- sis on transactions to provide insights for healthcare improvement. Specific applications may address such areas as treatments for cancer, nursing care, images and diagnostics, consumer health, public health, or clinical research.

Electronic Health Records and Electronic Medical Records

The terms electronic health record (EHR) and electronic medical record (EMR) are often used interchangeably, but they are not the same. Technically, an EMR is simply an electronic version of the kind of paper chart traditionally used by a healthcare organization. It has the extra capabilities that digital technology provides—such as the ability to track data over time and screen records easily for the purposes of improving care—but it is still a single- facility system. The EHR, on the other hand, goes beyond the clinical record of a single facility and includes information from all the providers treating the patient—potentially including hospitals, nursing homes, and laboratories, as well as all physicians and clinical specialists.

The EHR provides a longitudinal record with a broad view of the patient’s treatment and health status over time. When physicians lack com- plete information about a patient’s hospitalizations or other provider visits, they are more likely to duplicate procedures, perform unnecessary tests, or recommend treatment that is suboptimal or inappropriate. Relying on

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patients to provide this information is not always effective: Patients are often poor historians about the course of their treatment, particularly when that treatment is complex and multifaceted. A true EHR system ensures that the necessary information is available to support better coordination of care, better measurement of quality, and reduced risk of medical error.

As organizations merge, are acquired, or band together through affili- ation agreements, the interoperability of EHR systems—that is, the ability of the systems to talk to one another—is extremely important. Many electronic systems were built on proprietary technologies, making interoperability and the creation of longitudinal records difficult. In many cases, the only solution has been to replace the old legacy systems with more modern longitudinal EHRs (Chapple 2018).

Personal Health Records and Patient Portals A personal health record (PHR) is “an electronic application through which patients can maintain and manage their health information (and that of others for whom they are authorized) in a private, secure, and confidential environment” (ONC 2016). The PHR contains similar information to the EHR and EMR, but it is intended to be used and managed by the patient or responsible party. It helps keep patients informed and engaged in the man- agement of their care and health status.

PHRs are individually managed, and so their effectiveness may vary depending on how well they have been maintained. The public has become increasingly computer savvy, yet the skills, access, and attention to detail necessary to maintain a PHR are not universal. When a PHR has an incom- plete accounting of services received by the patient, its benefit as a system for provider use is diminished. In some ways, the PHR has the same potential flaws as the EMR.

Discussion continues about how PHRs best fit into the healthcare environment, and more research is needed to fully understand how they might be used to benefit patients and providers (Irizarry, DeVito Dabbs, and Curran 2015; Kaelber et al. 2008; Kaelber and Pan 2008). A report by the Markle Foundation (2006) provides a wealth of information on this topic.

A patient portal is a secure website through which patients can con- veniently access their personal health information at any time, using a user name and password. Patient portals differ from PHRs in that they are typi- cally provided by providers of healthcare services. Patients can use patient portals to access such health information as the following (ONC 2019b):

• Recent doctor visits • Discharge summaries • Medications

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• Immunizations • Allergies • Lab results

Some patient portals also allow patients to do the following:

• Securely message their doctor • Request prescription refills • Schedule nonurgent appointments • Check benefits and coverage • Update contact information • Make payments • Download and complete forms • View educational materials

Patients generally have limited ability to add or change information in the portal records (Mayo Clinic 2017; Xtelligent Healthcare Media 2017).

Incentives for EHR Adoption Even though early electronic records for healthcare existed more than 40 years ago, we still must do more to integrate these innovations into regular patient care (Shortliffe 2005). A number of US laws and policies have sought to encourage the adoption of EHRs. The American Recovery and Reinvest- ment Act of 2009 provided $27 billion in incentive payments to hospitals and physicians who adopted electronic record systems in line with certain criteria (Schilling 2018; Worzala 2009). One of the most important of these criteria involved demonstrating “meaningful use”—that is, use of the information system in a meaningful way to provide care and improve engagement. Key elements of meaningful use include the following:

• Patient access to the system • Patient–provider messaging, educational resources, and information

gathering (e.g., uploading data from home monitoring devices) • Self-management tools and electronic reporting on the patient care

experience

Meaningful use criteria were implemented in three stages between 2011 and 2016, as shown in exhibit 10.3. Stage 1 began with a focus on capturing and sharing data, stage 2 focused on advanced clinical processes, and stage 3 focused on improving outcomes. Stage 3 required the mean- ingful interaction of patients with providers using electronic means, and it

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encouraged a focus on improving population health. In 2017, the meaning- ful use criteria were incorporated into the new Merit-Based Incentive Pay- ment System (ONC 2019a).

Confidentiality Concerns in EHR Every healthcare professional should be well versed in the healthcare privacy protections under the Health Insurance Portability and Accountability Act (HIPAA) of 1996 (US Department of Health and Human Services [HHS] 2019b, 2017a, 2017b). HIPAA allows for the legal use of personal health information strictly for the purposes of healthcare delivery operations and reimbursement. Another party has no reason to access or review a person’s medical records unless it is involved in the delivery of care or related opera- tions (e.g., billing activity that requires specific information). Access should be on a need-to-know basis. The party does not have an unequivocal right

Stage 1: Meaningful use criteria focus on data capture and sharing

Stage 2: Meaningful use criteria focus on advanced clinical processes

Stage 3: Meaningful use criteria focus on improved outcomes

Electronic capture of health information in a standardized format

More rigorous health information exchange (HIE)

Improvement in quality, safety, and efficiency, leading to better health outcomes

Use of that information to track key clinical conditions

Increased requirements for e-prescribing and incorporating lab results

Decision support for national high-priority conditions

Communication of that information for care coordination processes

Electronic transmission of patient care summaries across multiple settings

Patient access to self- management tools

Initiation of the reporting of clinical quality measures and public health information

More patient-controlled data

Access to comprehensive patient data through patient-centered HIE

Use of information to engage patients and their families in care

Improved population health

Time line: 2011–2012 Time line: 2014 Time line: 2016

EXHIBIT 10.3 Stages of

Meaningful Use

Source: Adapted from ONC (2013).

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to peruse the record and “read all about it.” One should go to the record and get the information specifically needed—“no more, no less,” as they say.

I recall, in the early years of HIPAA, leading student discussions about the need for the law. I would ask, “How many of you would want to have a sensitive medical procedure done or a sensitive medical condition treated at the healthcare organization where you work?” Most indicated that they would not, feeling that their privacy would undoubtedly be compromised.

Healthcare organizations must spend a great deal of energy and resources making sure their records are safeguarded, or else they could face severe penalties. The number of complaints related to HIPAA has increased as new technologies have enabled easier access to electronic records. HIPAA complaints are investigated by the US Department of Health and Human Services Office of Civil Rights (OCR). Near the end of 2019, the office reported: “Since the compliance date of the Privacy Rule in April 2003, OCR has received over 223,135 HIPAA complaints and has initiated over 987 compliance reviews. We have resolved ninety-nine percent of these cases (219,964)” (HHS 2019a).

Health Information Exchange Longitudinal views provided by patient records are often incomplete because of a lack of integration of clinical content from the various providers the patient has seen. To address this issue, many healthcare systems are working to better integrate with affiliated practices and providing them with access to critical patient information.

Health information exchange (HIE) refers to the organization and sharing of electronic health-related information in a manner that protects the confidentiality, privacy, and security of the information. Organizations can participate in large HIE organizations or regional health information organiza- tions (RHIOs) to gain better access to patient data as well as population health information. HIEs enable the sharing of health information among providers and, as appropriate, with individuals on a local, regional, and national basis (see exhibit 10.4). They support better integration of patient information while employing nationally recognized standards for interoperability and security (ONC 2017). The interplay of EHRs and HIEs is an important aspect of the infrastructure to create the Nationwide Health Information Network (NHIN), now called the eHealth Exchange (ONC 2018b; Sequoia Project 2019).

The Wisconsin Statewide Health Information Network (WISHIN) provides an example of how an HIE can be organized to work for the benefit of health organizations and their patients. The exchange connects more than 1,000 providers and enables the widespread, timely, and secure sharing of health information to support patients and caregivers throughout the state (WISHIN 2013).

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Information Technology and Value-Based Care

As the US healthcare system seeks to transition toward value-based care, a modern IT system is essential. The delivery of value-based care depends heav- ily on the availability of contemporaneous data on the care provided, the out- comes associated with that care, the patient base of the practice, and the costs of the practice’s operations. It simply is not possible with manual systems, where data capture is difficult, costly, time consuming, and often inaccurate (Ebbevi et al. 2016; NEJM Catalyst 2017; Tinetti, Naik, and Dodson 2016; Veenstra et al. 2017).

Collection of Metrics for Population Health For most of our nation’s history, healthcare has focused on care for indi- vidual patients. Today, however, taking good care of individual patients is no longer sufficient; we must also focus on the health of the entire population being served. Population health management is a key element of what has been called the “second curve” of medicine (Health Research and Educa- tion Trust 2013), and it requires well-developed IT systems to support the collection of various data and metrics. If we cannot measure the popula- tion health outcomes we seek, we cannot measure the improvements our

Primary care

Hospital

Specialist

Patient record

Pharmacy

Laboratory and

radiology

EXHIBIT 10.4 Health

Information Exchange

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innovations create. To paraphrase Peter Drucker, if you can’t measure it, you can’t manage it (Prusak 2010).

Cloud Computing Another IT topic that has become highly relevant to health practice manag- ers is cloud computing, which enables users to access data, resources, and computing power through a network of remote servers, rather than having to maintain the hardware and software themselves. Cloud computing incorpo- rates the concept of “software as a service” (SaaS), which allows for software to be accessed via the internet rather than installed locally. Essentially, cloud computing allows virtually every aspect of health IT service to be done “on the cloud.”

Cloud computing can offer many potential advantages to a health practice, including the following (Carnevale et al. 2017; Taneja and Maney 2018):

• Cost. The cost of cloud computing can be significantly less than the cost of maintaining the software, hardware, and services within the practice. Cloud services often have the latest hardware and software available, which many small and medium-sized practices would be unable to afford.

• Security. The physical security and cybersecurity of IT systems are growing areas of concern for most practices. Moving the practice’s IT functions to the cloud reduces the likelihood of a physical loss of IT assets and may reduce the probability of cyber threats.

• 24/7 services. Most cloud computing services operate on a 24/7 basis. • Backup. Reputable cloud service companies offer sophisticated backup

services to prevent catastrophic IT failures. • Scalability. Cloud services tend to be much more scalable than

traditional IT systems—in other words, the systems can more easily be enlarged to accommodate more work.

• Expertise. Most small and medium-sized practices do not have the same level of IT expertise that is available from a cloud computing service.

• Flexibility. Although most cloud services require a service contract of a specified length, the commitment is likely less than the commitment the organization would make when buying the necessary equipment and software and hiring the appropriate expertise.

Of course, cloud computing may also present some disadvantages:

• Reliance on the internet. Cloud services depend on a working internet connection, and problems with that connection can cause IT systems

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to fail. Organizations must consider the reliability of their internet service provider as well as their routers when making the decision to use such services.

• Lost data. Providers are not perfect. Data may be lost if a company goes out of business or performs at a lower level of quality than expected.

• Compatibility. If an organization does not switch all of its IT services to the cloud-based service, the functions may encounter compatibility issues. Such issues will need to be addressed before moving forward to the cloud.

• Stakeholder temperament. Some people simply are not comfortable with the idea of their data and important business functions being handled remotely by a cloud service. Discussions with stakeholders throughout the practice should occur before moving forward.

Cybersecurity

The increasing connectedness and digitization of the healthcare world have contributed to new a type of risk, as security breaches and other computer- based crimes have become commonplace. Cyber criminals have discovered that healthcare facilities are rich sources of personal information that can be used for identity theft and even blackmail. Unfortunately, many health- care organizations are easy targets. According to a Bloomberg report, cyber attacks cost healthcare facilities more than $6 billion per year (Pettypiece 2015).

The HIPAA Journal (2018) states that the top 10 security breaches in 2017 exposed nearly 3 million patient records, through either hacking or other IT events (e.g., accidental or unintended release of records). In 2018, Atrium Health, headquartered in Charlotte, North Carolina, had a beach that potentially exposed 2.65 million patient records (Arndt 2018). The breach was carried out through an outside billing agent—highlight- ing the fact that patient information may be exposed not only by the organization itself but also by entities working on behalf of the healthcare organization.

Healthcare’s cybersecurity problem is massive; however, no one really knows the true extent of the problem because organizations are often unaware of the events or are reluctant to report them when they occur (Lau- ritsen and Cork 2017). Cyber risk has become so widespread that organiza- tions can now buy insurance to pay damages in the event of a breach (PWC Netherlands 2019).

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Common Cyber Risks Common cyber risks include the following (Center for Internet Security 2019; Landi 2018):

• Phishing attacks typically involve emails that are disguised so that they appear to be from a trusted party. The messages usually ask the recipient to click on a link and enter personal information (e.g., name, passwords), thus enabling the sender to access accounts or systems.

• Trojans and malware are special programs designed by hackers. The programs enable the hacker to access information in systems on the affected computer and on the networks to which the computer is connected.

• Ransomware and advertising scams are also programs designed by hackers. If downloaded by a user, the programs cause the computer to be infected by various viruses. In the case of ransomware, data in the system become unavailable to the user unless a ransom is paid to the hacker, at which point a code is provided to unlock the data. Ransomware has become a real and growing threat.

• Password theft is simply the stealing of a password from a person who has access to the system.

• Third-party access can be a threat if vendors and other parties that deal with the organization and have access to its IT systems steal data directly or allow computers to become infected with malicious software.

What Is the Healthcare Organization’s Responsibility? Data breaches often occur despite the best efforts of the organization to prevent them. Nevertheless, one of the most important things an organiza- tion can do is to make sure that clear policies and procedures are in place for the use of all electronic communication devices. Policies should address such issues as the following (Center for Internet Security 2019; Harrison and Pagliery 2015; Landi 2018; Pettypiece 2015; Wagner 2017):

• Proper access of information • Password security • Appropriate management and surveillance of security policies • Appropriate electronic safeguards in the form of firewalls, web and

email encryption, and malware protection

The organization must also make sure that all staff members receive sufficient training on these policies and procedures.

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Technology and Cost

Thanks to its commitment to the advancement of science, its entrepreneurial spirit, and its overall economic environment, the United States has become a powerhouse in the development of new medical technologies (Ferguson 2017; Medical Futurist 2016)—with both positive and negative effects (Ber- wick 2008). Technological advances have greatly expanded the capabilities of healthcare, bringing numerous benefits to patients; yet, at the same time, these advances have led to significantly higher costs (Cohen et al. 2004; Cal- lahan and Baily 2008). At the risk of making light of the topic, one might say that “death is cheap.” Prior to the development of our current technologies, providers were much more limited in what they could do to cure illnesses, alleviate suffering and disability, and extend life—and costs were lower as a result. Today, we have become much more dependent on the use of expen- sive, technologically advanced treatments (Kumar 2011). Furthermore, patients who have their medical conditions mitigated through technology often require expensive care for the rest of their lives. Many people would argue that technology is the single most significant factor in the dramatic increase of overall healthcare costs in the United States.

In most industries—electronics, for instance—technology leads to improvement in productivity, which reduces pressure on wages and ultimately reduces the cost of the product or service (Nordhaus 2006). Healthcare is different, however, in that technology often does not lead to improvement in productivity; rather, it typically leads to the accretion of more services to the overall continuum and armamentarium of healthcare. At the same time, healthcare must compete with other industries to attract the best and brightest talent, which puts an upward pressure on wages. The effect of having increased wages without a proportional increase in productivity is known as Baumol’s Cost Disease, after the economist William Baumol (Baumol 2012; Bailey, Anttiroiko, and Valkama 2016; Maiello 2017). When providers take care of unique patient care needs in a one-on-one setting, their ability to increase pro- ductivity is limited. And when providers do attempt to improve productivity— for instance, by increasing the number of patients seen in a given period—the efforts have often led to dissatisfaction on the part of both patients and pro- viders (Bodenheimer and Sinsky 2014). Some scholars do point out, however, that this relationship is far from conclusive and that increased productivity and satisfaction can exist together (Boffeli et al. 2012; Wood et al. 2009).

Organizations must commit significant resources to absorbing and managing the abundance of new technologies, processes, and knowledge that continue to emerge. PubMed (2019), a service of the US National Library of Medicine, currently has more than 30 million citations, and Jinha (2010) estimates that more than 50 million scholarly articles have been published

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since medical publishing began in 1665. What person can read them all? Of course, no one. Managing the influx of information, medical technologies, and drugs and devices will be a major challenge in the years ahead (Taneja and Maney 2018).

Innovation and Leadership

The effective management and application of technology in healthcare requires strong leadership, with an openness to new ideas and ways of thinking. Leaders must avoid being “held hostage” by their own insights and successes, and thus locked in their ways. As the saying goes, “the true definition of insanity is doing the same thing over and over again and expecting different results.” Leaders also must not allow allegiance to their own group to create a “tribal” environment that hampers cooperation across organizational lines (Costich, Scutchfield, and Ingram 2015). Many of the challenges associated with technology will require the cooperation of mul- tiple organizations and professional groups (Porter-O’Grady and Malloch 2017). A study by Paulus, Davis, and Steele (2008) of the Geisinger Health System found that “Clinician leadership at all levels, when paired with busi- ness partners and engaged clinical champions, supports progress in clinical transformation.”

Often in healthcare, we seem to invent things faster than we can effec- tively use them. Looking ahead, we will need a new system architecture and a new paradigm of leadership, because the old paradigms are becoming obso- lete. Tim Porter-O’Grady and colleagues have written extensively on the topic of “quantum leadership,” which seems particularly well suited for our current environment (Porter-O’Grady and Malloch 2017, 2011). Quantum leader- ship is a process of “leading from the future,” whereby a high-performing organization projects a mind-set that helps pull it toward a desired future state. On the surface, quantum leadership might seem like a “far-out” con- cept, but it really just involves placing creativity and innovation on a higher level. In contrast to traditional linear thinking, quantum leadership focuses its vision on the next generation of services and the next modes of operation.

A fundamental concept of quantum physics is the idea that everything is connected—an idea that is highly applicable to modern healthcare. Other fundamental concepts include having a moral purpose and acting to make a difference in the lives of people in the organization, as well as the community in general; relationship building; and making informed decisions by acquir- ing knowledge, listening, and empowering (Porter-O’Grady 1999). Thomas Kilmann (1989, 2009) espouses similar ideas about the quantum organiza- tion and its potential for resolving conflict and organizing for creativity and

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innovation. Judging from a review of the literature, quantum leadership appears to have been more readily accepted in nursing than in other disci- plines (American Nurse Today 2013; Porter-O’Grady and Malloch 2011; Porter-O’Grady 1999; Watson et al. 2018).

Innovation can be risky, and adoption of innovations often moves slowly in a cautious, risk-averse field such as healthcare (Berwick 2003). Clay- ton Christensen (1997), in his book The Innovator’s Dilemma, discusses two factors that often interfere with large organizations’ ability to innovate and cause them to lose ground to competitors. First, because innovation often does not produce immediate value in the early stages, it may be less meaning- ful to large organizations that are primarily focused on current operational results. Second, large organizations tend to have high expectations for sales, whereas smaller organizations are often less concerned with immediate returns and more willing to innovate. Thus, smaller organizations are often better able to focus on niche markets and improve their products and services exponentially over time, eventually pushing into larger areas of the industry and ultimately displacing the technologies of the larger organizations. Chris- tensen and Raynor (2003) stress the importance of having leaders committed to change and disruptive growth.

A key aspect of leadership is the development of followers. In today’s digital age, the development of effective knowledge workers requires special emphasis on the following:

• Conceptual thinking versus functional analysis • Multiple intelligences, including emotional intelligence • Outcome-based practice, as opposed to process-focused activities • Team performance, as opposed to individual performance • Integration and a focus on the whole organization and its mission

These ideas, which are core elements of quantum leadership, suggest a sub- stantial leap toward the creation of environments capable of dealing with rapid change, uncertainty, ethical demands, and interconnectedness.

The Technological Imperative

More than 50 years ago, the noted healthcare economist Victor Fuchs (1968) introduced the idea of the technological imperative. He wrote: “Medical tra- dition emphasizes giving the best care that is technically possible; the only legitimate and explicitly recognized constraint is the state of the art.” Because of this imperative, physicians are “usually under considerable pressure to use the latest procedures and the most elaborate treatment.”

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The United States is foremost among the countries of the world in terms of medical innovation. Technology has been a wonderful asset for our healthcare system, and our society seems to have a constant desire for advanced medical technology at any cost. We should pause, however, to ask: To what extent does our push for innovation help us accomplish the goals of the healthcare system, and to what extent might it be counterproductive? How might we develop smarter ways to use this technology to achieve its fullest potential? The degree to which technology dominates our healthcare system can at times become a burden (Collier 2018; Rutten and Bonsel 1992); it may raise ethical concerns as well. Ultimately, healthcare is more than a technology. Technology cannot replace care and comparison, nor should it lessen our personal responsibility to care for patients (Barger-Lux and Heaney 1986; Hofmann 2002).

Advancement of health IT and continued integration of our IT sys- tems will be essential in the years ahead (see exhibit 10.5). As we move along this path, we must ensure that our efforts are grounded in the fundamentals of who our IT systems should serve, for what purpose, and in what manner, to better serve our patients and our communities (see exhibit 10.6).

Stand-alone system

Partially integrated

system

Fully integrated

system

EXHIBIT 10.5 Continuum of IT System Integration

For whom? Patients Providers Support staff

For what purpose? Patient care Documentation Research Imaging Other ancillaries Communication Decision support

What characteristics? Usable Specific Secure Smooth flowing Implementable Scalable

EXHIBIT 10.6 What IT Systems Should Do

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Discussion Questions

1. What are the main categories of technology use in healthcare? 2. Are there limits to the value of technological advances? 3. In what ways does medical technology drive healthcare cost? 4. Do we overuse medical technology in the United States?

References

Alliance of Advanced BioMedical Engineering. 2019. “Monitoring.” Accessed Octo- ber 13. https://aabme.asme.org/categories/monitoring.

American Hospital Association (AHA). 2017. “Emerging Strategies to Ensure Access to Health Care Services.” Published November 16. www.aha.org/system/ files/2018-06/task-force-emergency-medical-center.pdf.

American Medical Association (AMA). 2015. “What Physicians Need to Know About Telemedical Liability.” Published February 11. www.ama- assn.org/practice-management/sustainability/what-physicians-need- know-about-telemedical-liability.

———. 2014. “Physicians Take On Telemedicine to Bolster Care Delivery.” Pub- lished July 3. www.ama-assn.org/practice-management/digital/physicians- take-telemedicine-bolster-care-delivery.

American Nurse Today. 2013. “Quantum Leadership: Upside Down.” Published March 11. www.americannursetoday.com/quantum-leadership-upside- down/.

Anderson, J., F. Neary, and J. Pickstone. 2007. Surgeons, Manufacturers, and Patients: A Transatlantic History of Total Hip Replacement. New York: Pal- grave Macmillan.

Arndt, R. 2018. “Atrium Health Data Breach Exposes up to 2.65 Million Patients’ Data.” Modern Healthcare. Published November 28. www.modernhealthcare. com/article/20181128/NEWS/181129940.

Ashrafian, H., O. Clancy, V. Grover, and A. Darzi. 2017. “The Evolution of Robotic Surgery: Surgical and Anaesthetic Aspects.” British Journal of Anaesthesia 119 (Suppl. 1): i72–84. https://doi.org/10.1093/bja/aex383.

Bailey, S. J., A.-V. Anttiroiko, and P. Valkama. 2016. “Application of Baumol’s Cost Disease to Public Sector Services: Conceptual, Theoretical and Empirical Fal- sities.” Public Management Review 18 (1): 91–109. https://doi.org/10.108 0/14719037.2014.958092.

Barger-Lux, M. J., and R. P. Heaney. 1986. “For Better and Worse: The Technologi- cal Imperative in Health Care.” Social Science & Medicine 22 (12): 1313–20. https://doi.org/10.1016/0277-9536(86)90094-8.

Baumol, W. J. 2012. The Cost Disease: Why Computers Get Cheaper and Health Care Doesn’t. New Haven, CT: Yale University Press.

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

C h a p t e r 1 0 : T h e I m p a c t o f Te c h n o l o g y o n U S H e a l t h c a r e 347

Berwick, D. M. 2008. “Taming the Technology Beast.” JAMA 299 (24): 2898–99. https://doi.org/10.1001/jama.299.24.2898.

———. 2003. “Disseminating Innovations in Health Care.” JAMA 290 (15): 1969– 75. https://doi.org/10.1001/jama.289.15.1969.

Bipartisan Policy Center. 2018. Reinventing Rural Health Care: A Case Study of Seven Upper Midwest States. Published January. https://bipartisanpolicy.org/ wp-content/uploads/2018/01/BPC-Health-Reinventing-Rural-Health- Care-1.pdf.

Bodenheimer, T., and C. Sinsky. 2014. “From Triple to Quadruple Aim: Care of the Patient Requires Care of the Provider.” Annals of Family Medicine 12 (6): 573–76. https://doi.org/10.1370/afm.1713.

Boffeli, T. J., K. L. Thongvanh, S. J. H. Evans, and C. R. Ahrens. 2012. “Patient Experience and Physician Productivity: Debunking the Mythical Divide at HealthPartners Clinics.” Permanente Journal 16 (4): 19–25. https://doi. org/10.7812/tpp/12-049.

Callahan, D., and M. Baily. 2008. “Health Care Costs and Medical Technology.” In From Birth to Death and Bench to Clinic: The Hastings Center Bioethics Briefing Book for Journalists, Policymakers, and Campaigns, edited by Mary Crowley, 79–82. Garrison, NY: Hastings Center. www.thehastingscenter.org/ wp-content/uploads/Health-Care-Costs-BB17.pdf.

Cardon, D. 2018. Database vs. Data Warehouse: A Comparative Review. Health Catalyst. Accessed October 13, 2019. www.healthcatalyst.com/wp-content/ uploads/2014/05/Database-vs-Data-Warehouse-A-Comparative-Review. pdf.

Carnevale, L., A. Celesti, M. Fazio, P. Bramanti, and M. Villari. 2017. “How to Enable Clinical Workflows to Integrate Big Healthcare Data.” In Proceedings of the 2017 IEEE Symposium on Computers and Communications. Accessed October 13, 2019. https://doi.org/10.1109/ISCC.2017.8024634.

Center for Internet Security. 2019. “Cyber Attacks: In the Healthcare Sector.” Acce- ssed October 13. www.cisecurity.org/blog/cyber-attacks-in-the-healthcare- sector/.

Chapple, M. 2018. “What Is Your Hospital’s Strategy for Sunsetting Legacy Sys- tems?” HealthTech. Published August 2. https://healthtechmagazine.net/ article/2018/08/what-your-hospitals-strategy-sunsetting-legacy-systems.

Christensen, C. M. 1997. The Innovator’s Dilemma: The Revolutionary Book That Will Change the Way You Do Business. Boston: Harvard Business School Press.

Christensen, C. M., and M. E. Raynor. 2003. The Innovator’s Solution: Creating and Sustaining Successful Growth. Boston: Harvard Business School Press.

Cohen, A. B, R. S. Hanft, W. E. Encinosa, S. M. Spernak, S. A. Stewart, and C. C White. 2004. Technology in American Health Care. Ann Arbor, MI: Univer- sity of Michigan Press.

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

T h e U n i t e d S t a t e s H e a l t h c a r e S y s t e m348

Collier, R. 2018. “Medical Technology Often a Burden If Designed Without Physi- cian Input.” Canadian Medical Association Journal/Journal de l’Association Medicale Canadienne 190 (36): E1091–92. https://doi.org/10.1503/ cmaj.109-5656.

Costich, J. F., F. D. Scutchfield, and R. C. Ingram. 2015. “Population Health, Public Health, and Accountable Care: Emerging Roles and Relationships.” Ameri- can Journal of Public Health 105 (5): 846–50. https://doi.org/10.2105/ AJPH.2014.302484.

Dinesen, B., B. Nonnecke, D. Lindeman, E. Toft, K. Kidholm, K. Jethwani, H. M. Young, H. Spindler, C. U. Oestergaard, J. A. Southard, M. Gutierrez, N. Anderson, N. M. Albert, J. J. Han, and T. Nesbitt. 2016. “Personalized Telehealth in the Future: A Global Research Agenda.” Journal of Medical Internet Research 18 (3): e53. https://doi.org/10.2196/jmir.5257.

Dinesen, B., and E. Toft. 2009. “Telehomecare Challenge Collaboration Among Healthcare Professionals.” Wireless Personal Communications 51 (4): 711–24. https://doi.org/10.1007/s11277-009-9767-3.

Dinov, I. D., B. Heavner, M. Tang, G. Glusman, K. Chard, M. Darcy, R. Madduri, J. Pa, C. Spino, C. Kesselman, I. Foster, E. W. Deutsch, N. D. Price, J. D. Van Horn, J. Ames, K. Clark, L. Hood, B. M. Hampstead, W. Dauer, and A. W. Toga. 2016. “Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.” PLOS ONE 11 (8): e0157077. https://doi. org/10.1371/journal.pone.0157077.

Donkin, L., H. Christensen, S. L. Naismith, B. Neal, I. B. Hickie, and N. Glozier. 2011. “A Systematic Review of the Impact of Adherence on the Effectiveness of e-Therapies.” Journal of Medical Internet Research 13 (3): e52. https:// doi.org/10.2196/jmir.1772.

Ebbevi, D., H. H. Forsberg, A. Essén, and S. Ernestam. 2016. “Value-Based Health Care for Chronic Care.” Quality Management in Health Care 25 (4): 203– 12. https://doi.org/10.1097/QMH.0000000000000115.

Eckerson, W. 2007. “Extending the Value of Your Data Warehousing Invest- ment.” Data Warehouse Institute. Published May 10. http://tdwi.org/ articles/2007/05/10/predictive-analytics.aspx?sc_lang=en.

Feldman, B., E. M. Martin, and T. Skotnes. 2012. “Big Data in Healthcare: Hype and Hope.” Published October. www.scribd.com/document/107279699/ Big-Data-in-Healthcare-Hype-and-Hope.

Ferguson, M. 2017. “Health Economics Outcomes: Research and Evidence Strate- gies.” In Managing Medical Devices Within a Regulatory Framework, edited by B. A. Fiedler, 277–95. Waltham, MA: Elsevier. https://doi.org/10.1016/ B978-0-12-804179-6.00016-2.

Fuchs, V. R. 1968. “The Growing Demand for Medical Care.” New Eng- land Journal of Medicine 279 (4): 190–95. https://doi.org/10.1056/ NEJM196807252790405.

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

C h a p t e r 1 0 : T h e I m p a c t o f Te c h n o l o g y o n U S H e a l t h c a r e 349

Gilley, A., M. Godek, and J. W. Gilley. 2009. “Change, Resistance, and the Organiza- tional Immune System.” SAM Advanced Management Journal 74 (4): 4–10.

Gorman, D. 2015. “On the Barriers to Significant Innovation in and Reform of Healthcare.” Internal Medicine Journal 45 (6): 597–99. https://doi. org/10.1111/imj.12775.

Harrison, V., and J. Pagliery. 2015. “Nearly 1 Million New Malware Threats Released Every Day.” CNN. Published April 14. https://money.cnn. com/2015/04/14/technology/security/cyber-attack-hacks-security/index.html.

Health Research and Education Trust. 2013. Metrics for the Second Curve of Health Care. Published April. www.hpoe.org/Reports-HPOE/Metrics_Second_ Curve_4_13.pdf.

Heinzelmann, P. J., N. E. Lugn, and J. C. Kvedar. 2005. “Telemedicine in the Future.” Journal of Telemedicine and Telecare 11 (8): 384–90. https://doi. org/10.1177/1357633X0501100802.

HIPAA Journal. 2018. “Largest Healthcare Data Breaches of 2017.” Published January 4. www.hipaajournal.com/largest-healthcare-data-breaches-2017/.

Hofmann, B. 2002. “Is There a Technological Imperative in Health Care?” Inter- national Journal of Technology Assessment in Health Care 18 (3): 675–89. https://doi.org/10.1017/S0266462302000491.

Huston, T. L., and J. L. Huston. 2000. “Is Telemedicine a Practical Reality?” Communications of the ACM 43 (6): 91–95. https://doi.org/10.1145/ 336460.336481.

Irizarry, T., A. DeVito Dabbs, and C. R. Curran. 2015. “Patient Portals and Patient Engagement: A State of the Science Review.” Journal of Medical Internet Research 17 (6): e148. https://doi.org/10.2196/jmir.4255.

Jinha, A. E. 2010. “50 Million: An Estimate of the Number of Scholarly Arti- cles in Existence.” Learned Publishing 23 (3): 258–63. https://doi. org/10.1087/20100308.

Kaelber, D. C., A. K. Jha, D. Johnston, B. Middleton, and D. W. Bates. 2008. “A Research Agenda for Personal Health Records (PHRs).” Journal of the American Medical Informatics Association 15 (6): 729–36. https://doi. org/10.1197/jamia.M2547.

Kaelber, D., and E. C. Pan. 2008. “The Value of Personal Health Record (PHR) Systems.” In AMIA Annual Symposium Proceedings, 2008, 343–47. www. ncbi.nlm.nih.gov/pubmed/18999276.

Kamra, V., H. Singh, and K. K. De. 2016. “Factors Affecting Patient Satisfaction: An Exploratory Study for Quality Management in the Health-Care Sector.” Total Quality Management & Business Excellence 27 (9–10): 1013–27. https://doi. org/10.1080/14783363.2015.1057488.

Kathol, R. G., F. deGruy, and B. L. Rollman. 2014. “Value-Based Financially Sustain- able Behavioral Health Components in Patient-Centered Medical Homes.” Annals of Family Medicine 12 (2): 172–75. https://doi.org/10.1370/ afm.1619.

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

T h e U n i t e d S t a t e s H e a l t h c a r e S y s t e m350

Kavalaris, S., F.-E. Kioupakis, K. Kaltsas, and E. Serrelis. 2015. “ScienceDirect Development of a Multi-Vector Information Security Rating Scale for Smart Devices as a Means for Raising Public InfoSec Awareness.” Procedia Com- puter Science 65: 500–509. https://doi.org/10.1016/j.procs.2015.09.122.

Kilmann, R. H. 2009. “A Completely Integrated Program for Creating and Main- taining Organizational Success.” Killman Diagnostics. Accessed October 14, 2019. https://kilmanndiagnostics.com/a-completely-integrated-program- for-creating-and-maintaining-organizational-success/.

———. 1989. “A Completely Integrated Program for Creating and Maintaining Organizational Success.” Organizational Dynamics 18 (1): 4–19. https:// doi.org/10.1016/0090-2616(89)90028-4.

Kirby, C. 2016. “How Miniaturized Electronic Devices Can Be Used as Medi- cal Therapeutics.” Stanford Engineering. Published April 12. https:// engineering.stanford.edu/magazine/article/how-miniaturized-electronic- devices-can-be-used-medical-therapeutics.

Knickman, J. R., and A. R. Kovner. 2015. “The Future of Health Care Delivery and Health Policy.” In Jonas and Kovner’s Health Care Delivery in the United States, 11th ed., edited by J. R. Knickman and A. R. Kovner, 333–42. New York: Springer.

Kumar, R. D. C., and N. Khiljee. 2016. “Leadership in Healthcare.” Anaesthesia and Intensive Care Medicine 17 (1): 63–65. https://doi.org/10.1016/j. mpaic.2015.10.012.

Kumar, R. K. 2011. “Technology and Healthcare Costs.” Annals of Pediatric Cardi- ology 4 (1): 84–86. https://doi.org/10.4103/0974-2069.79634.

Lake, J., and M. S. Turner. 2017. “Urgent Need for Improved Mental Health Care and a More Collaborative Model of Care.” Permanente Journal 21: 17-024. https://doi.org/10.7812/TPP/17-024.

LaMay, C. L. 1997. “Telemedicine and Competitive Change in Health Care.” SPINE 22 (1): 88–97.

Landi, H. 2018. “What Can the Industry Learn from Recent High-Profile Health- care Cyber Attacks?” Healthcare Innovation. Published July 26. www. hcinnovationgroup.com/cybersecurity/article/13030570/what-can-the- industry-learn-from-recent-highprofile-healthcare-cyber-attacks.

Lauritsen, J. L., and D. L. Cork. 2017. “Expanding Our Understanding of Crime.” Criminology & Public Policy 16 (4): 1075–98. https://doi. org/10.1111/1745-9133.12332.

Linkous, J. 2012. The Role of Telehealth in an Evolving Health Care Environment. Washington, DC: National Academies Press.

Lutterman, T., R. Shaw, W. Fisher, and R. Manderscheid. 2017. Trend in Psy- chiatric Inpatient Capacity, United States and Each State, 1970 to 2014. National Association of State Mental Health Program Directors. Assess- ment No. 2. Published August. www.nasmhpd.org/sites/default/files/ TACPaper.2.Psychiatric-Inpatient-Capacity_508C.pdf.

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

C h a p t e r 1 0 : T h e I m p a c t o f Te c h n o l o g y o n U S H e a l t h c a r e 351

Mace, S., A. Boccanelli, and M. Dormond. 2018. The Use of Telehealth Within Behavioral Health Settings: Utilization, Opportunities, and Challenges. University of Michigan, School of Public Health, Behavioral Health Work- force Research Center. Published March. www.behavioralhealthworkforce. org/wp-content/uploads/2018/05/Telehealth-Full-Paper_5.17.18- clean.pdf.

Maiello, M. 2017. “Diagnosing William Baumol’s Cost Disease.” Chicago Booth Review. Published May 18. http://review.chicagobooth.edu/ economics/2017/article/diagnosing-william-baumol-s-cost-disease.

Marakhimov, A., and J. Joo. 2017. “Consumer Adaptation and Infusion of Wear- able Devices for Healthcare.” Computers in Human Behavior 76: 135–48. https://doi.org/10.1016/j.chb.2017.07.016.

Markle Foundation. 2006. Connecting Americans to Their Health Care: A Common Framework for Networked Personal Health Information. Published December 7. http://library.ahima.org/PdfView?oid=74759.

Mayo Clinic. 2017. “Personal Health Records and Patient Portals.” Published July 6. www.mayoclinic.org/healthy-lifestyle/consumer-health/in-depth/ personal-health-record/art-20047273.

Medical Futurist. 2016. “Top 20 Medical Technology Advances: Medicine in the Future—Part I.” Published July 14. https://medicalfuturist.com/20- potential-technological-advances-in-the-future-of-medicine-part-i.

Medtech Plus. 2019. “Digitization and Miniaturization.” Accessed October 14. www.medtech.plus/en/trend-topics/digitization-and-miniaturization.

Miyazaki, M., E. Igras, L. Liu, and T. Ohyanagi. 2012. “Global Health Through EHealth/Telehealth.” In eHealth and Remote Monitoring, edited by A. H. El Hassani. https://doi.org/10.5772/47922.

Morris, Z. S., S. Wooding, and J. Grant. 2011. “The Answer Is 17 Years, What Is the Question: Understanding Time Lags in Translational Research.” Journal of the Royal Society of Medicine 104 (12): 510–20. https://doi.org/10.1258/ jrsm.2011.110180.

NEJM Catalyst. 2018. “Healthcare Big Data and the Promise of Value-Based Care.” Published January 1. https://catalyst.nejm.org/big-data-healthcare/.

———. 2017. “What Is Value-Based Healthcare?” Published January 1. https:// catalyst.nejm.org/what-is-value-based-healthcare/.

Nordhaus, W. D. 2006. Baumol’s Diseases: A Macroeconomic Perspective. National Bureau of Economic Research. Working Paper 12218. Published May. www. nber.org/papers/w12218.

North Dakota Information Technology Department. 2019. “Definition of Infor- mation Technology.” Accessed October 14. www.nd.gov/itd/about-us/ definition-information-technology.

Novotney, A. 2011. “A New Emphasis on Telehealth.” Journal of the American Psychological Association 42 (6): 40. www.apa.org/monitor/2011/06/ telehealth.aspx.

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

T h e U n i t e d S t a t e s H e a l t h c a r e S y s t e m352

Office of the National Coordinator for Health Information Technology (ONC). 2019a. “Meaningful Use.” Reviewed October 22. www.healthit.gov/topic/ meaningful-use-and-macra/meaningful-use.

———. 2019b. “What Is a Patient Portal?” Accessed December 18. www.healthit. gov/faq/what-patient-portal.

———. 2018a. Health IT: Advancing America’s Health Care. Accessed October 14, 2019. www.healthit.gov/sites/default/files/pdf/health-information- technology-fact-sheet.pdf.

———. 2018b. What Is the NHIN? Accessed October 14, 2019. www.healthit.gov/ sites/default/files/what-Is-the-nhin--2.pdf.

———. 2017. “Health Information Exchange.” Reviewed October 12. www.heal- thit.gov/topic/health-it-basics/health-information-exchange.

———. 2016. “What Is a Personal Health Record?” Reviewed May 2. www.healthit. gov/faq/what-personal-health-record-0.

———. 2013. “What Is Meaningful Use?” Reviewed June 1. www.healthit.gov/faq/ what-meaningful-use.

Otto, L., L. Harst, H. Schlieter, B. Wollschlaeger, P. Richter, and P. Tim- pel. 2018. “Towards a Unified Understanding of eHealth and Related Terms— Proposal of a Consolidated Terminological Basis.” In Proceed- ings of the 11th International Joint Conference on Biomedical Engineer- ing Systems and Technologies, vol. 5, 533–39. https://doi.org/10.5220/ 0006651005330539.

Parimbelli, E., B. Bottalico, E. Losiouk, M. Tomasi, A. Santosuosso, G. Lanzola, S. Quaglini, and R. Bellazzi. 2018. “Trusting Telemedicine: A Discussion on Risks, Safety, Legal Implications and Liability of Involved Stakehold- ers.” International Journal of Medical Informatics 112: 90–98. https://doi. org/10.1016/j.ijmedinf.2018.01.012.

Paulus, R. A., K. Davis, and G. D. Steele. 2008. “Continuous Innovation in Health Care: Implications of the Geisinger Experience.” Health Affairs 27 (5): 1235–45. https://doi.org/10.1377/hlthaff.27.5.1235.

Pettypiece, S. 2015. “Rising Cyber Attacks Costing Health System $6 Billion Annually.” Bloomberg. Published May 7. www.bloomberg.com/news/arti- cles/2015-05-07/rising-cyber-attacks-costing-health-system-6-billion-annually.

Porter-O’Grady, T. 1999. “Quantum Leadership: New Roles for a New Age.” Journal of Nursing Administration 29 (10): 37–42. https://doi. org/10.1097/00005110-199910000-00008.

Porter-O’Grady, T., and K. Malloch. 2017. Quantum Leadership: Creating Sustain- able Value in Health Care, 5th ed. New York: Jones & Bartlett.

———. 2011. Quantum Leadership: Advancing Innovation, Transforming Health Care, 3rd ed. New York: Jones & Bartlett.

Prusak, L. 2010. “What Can’t Be Measured.” Harvard Business Review. Published October 7. https://hbr.org/2010/10/what-cant-be-measured.

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

C h a p t e r 1 0 : T h e I m p a c t o f Te c h n o l o g y o n U S H e a l t h c a r e 353

PubMed. 2019. “PubMed FAQs.” Updated July 25. www.ncbi.nlm.nih.gov/books/ NBK3827/#pubmedhelp.FAQs.

PWC Netherlands. 2019. “Cybercrime in Insurance.” Accessed October 14. www. pwc.nl/en/industries/insurers/cybercrime-in-insurance.html.

Rogers, E. M. 2003. Diffusion of Innovations, 5th ed. New York: Free Press. Rubin, A. 2017. “History of the EKG Machine.” Jamaica Hospital Medical Center.

Published August 24. https://jamaicahospital.org/newsletter/?p=4528. Ruiz, J. G., M J. Mintzer, and R. M. Leipzig. 2006. “The Impact of E-Learning

in Medical Education.” Academic Medicine 81 (3): 207–12. https://doi. org/10.1097/00001888-200603000-00002.

Rutten, F. F., and G. J. Bonsel. 1992. “High Cost Technology in Health Care: A Benefit or a Burden?” Social Science & Medicine 35 (4): 567–77. https://doi. org/10.1016/0277-9536(92)90350-Y.

Schiff, M. 2012. “BI Experts: Why Predictive Analytics Will Continue to Grow.” Data Warehouse Institute. Published March 6. http://tdwi.org/Articles/ 2012/03/06/Predictive-Analytics-Growth.aspx?Page=1.

Schilling, B. 2018. “The Federal Government Has Put Billions into Promoting Elec tronic Health Record Use: How Is It Going?” Commonwealth Fund. Accessed October 14, 2019. www.commonwealthfund.org/ publications/newsletter-ar ticle/federal-government-has-put-billions- promoting-electronic-health.

Sequoia Project. 2019. “About the Sequoia Project.” Accessed December 20. https://sequoiaproject.org/about-us/.

Shortliffe, E. H. 2005. “Strategic Action in Health Information Technology: Why the Obvious Has Taken So Long.” Health Affairs 24 (5): 1222–33. https:// doi.org/10.1377/hlthaff.24.5.1222.

Siegel, E. 2013. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Hoboken, NJ: John Wiley & Sons.

Stanberry, B. 2006. “Legal and Ethical Aspects of Telemedicine.” Journal of Telemedicine and Telecare 12 (4): 166–75. https://doi.org/10.1258/ 135763306777488825.

Taneja, H., and K. Maney. 2018. “The End of Scale.” MIT Sloan Management Review 59 (3): 67–72. https://sloanreview.mit.edu/article/the-end-of-scale/.

Taylor, K. 2017. “12 Medical Technology Innovations Likely to Transform Health Care in 2017.” Deloitte Center for Health Solutions. Published January 17. http://blogs.deloitte.com/centerforhealthsolutions/12-medical- technology-innovations-likely-transform-health-care-2017/.

Tinetti, M. E., A. D. Naik, and J. A. Dodson. 2016. “Moving from Disease- Centered to Patient Goals–Directed Care for Patients with Multiple Chronic Conditions.” JAMA Cardiology 1 (1): 9–10. https://doi.org/10.1001/jamacardio.2015.0248.

Townley, C., and R. Yalowich. 2015. Improving Behavioral Health Access & Integra- tion Using Telehealth & Teleconsultation: A Health Care System for the 21st

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

T h e U n i t e d S t a t e s H e a l t h c a r e S y s t e m354

Century. National Academy for State Health Policy. Published November. https://nashp.org/wp-content/uploads/2015/11/Telemedicine1.pdf.

US Department of Health and Human Services (HHS). 2019a. “Enforcement High- lights.” Reviewed December 10. www.hhs.gov/hipaa/for-professionals/ compliance-enforcement/data/enforcement-highlights/index.html.

———. 2019b. “Health Information Privacy.” Accessed October 14. www.hhs.gov/ hipaa/index.html.

———. 2017a. “HIPAA Case Examples.” Reviewed June 7. www.hhs.gov/hipaa/ for-professionals/compliance-enforcement/examples/index.html.

———. 2017b. “HIPAA for Professionals.” Reviewed June 16. www.hhs.gov/ hipaa/for-professionals/index.html.

Varghese, S. B., and C. A. Phillips. 2009. “Caring in Telehealth.” Telemedicine and e-Health 15 (10): 1005–9. https://doi.org/10.1089/tmj.2009.0070.

Veenstra, G. L., K. Ahaus, G. A. Welker, E. Heineman, M. J. van der Laan, and F. L. H. Muntinghe. 2017. “Rethinking Clinical Governance: Healthcare Professionals’ Views: A Delphi Study.” BMJ Open 7 (1): e012591. https:// doi.org/10.1136/bmjopen-2016-012591.

Verhoeven, F., K. Tanja-Dijkstra, N. Nijland, G. Eysenbach, and L. van Gemert- Pijnen. 2010. “Asynchronous and Synchronous Teleconsultation for Diabetes Care: A Systematic Literature Review.” Journal of Diabetes Science and Tech- nology 4 (3): 666–84. https://doi.org/10.1177/193229681000400323.

Wagner, S. L. 2017. Fundamentals of Medical Practice Management. Chicago: Health Administration Press.

Watson, J., T. Porter-O’Grady, S. Horton-Deutsch, and K. Malloch. 2018. “Quantum Caring Leadership: Integrating Quantum Leadership with Car- ing Science.” Nursing Science Quarterly 31 (3): 253–58. https://doi. org/10.1177/0894318418774893.

Weiss, B., and A. A. Pollack. 2017. “Barriers to Global Health Development: An International Quantitative Survey.” PLOS ONE 12 (10): e0184846. https:// doi.org/10.1371/journal.pone.0184846.

Westgate, A. 2017. “Top Five Most Disruptive Technologies on the Health- care Horizon.” Managed Healthcare Executive. Published September 11. www.managedhealthcareexecutive.com/business-strategy/top-five-most- disruptive-technologies-healthcare-horizon.

Wisconsin Statewide Health Information Network (WISHIN). 2013. “Who Is WISHIN?” Accessed October 14, 2019. www.wishin.org/AboutWISHIN.aspx.

Wolford, M. L., K. Palso, and A. Bercovitz. 2015. “Hospitalization for Total Hip Replacement Among Inpatients Aged 45 and Over: United States, 2000–2010.” NCHS Data Brief 186: 1–8. www.ncbi.nlm.nih.gov/ pubmed/26375255.

Wood, G. C., R. Spahr, J. Gerdes, Z. S. Daar, R. Hutchison, and W. F. Stewart. 2009. “Patient Satisfaction and Physician Productivity: Complementary or Mutually

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

C h a p t e r 1 0 : T h e I m p a c t o f Te c h n o l o g y o n U S H e a l t h c a r e 355

Exclusive?” American Journal of Medical Quality 24 (6): 498–504. https:// doi.org/10.1177/1062860609338869.

Worzala, C. 2009. “Policy Update: Federal Incentives for the Adoption of Electronic Health Records.” Journal of Oncology Practice 5 (5): 262–63. https://doi. org/10.1200/JOP.091034.

Xtelligent Healthcare Media. 2017. “How Do Patient Portals and Personal Health Records Differ?” Published February 17. https://patientengagementhit. com/features/how-do-patient-portals-and-personal-health-records-differ.

Zimmer, B. 2011. “Is It Time to Welcome Our New Computer Overlords?” Atlantic. Published February 17. www.theatlantic.com/technology/ archive/2011/02/is-it-time-to-welcome-our-new-computer-overlords/ 71388/.

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use

EBSCOhost - printed on 5/17/2022 2:26 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use