The Digital Reconstruction of Healthcare

Transitioning from Brick and Mortar to Virtual Care

Paul Cerrato, John Halamka

• Publisher: HIMSS Publishing
• Year: 2021
• ISBN:
  9781000397246
• Edition: 1
• Topic: Medicine
• Subtopic: Public Health, Administration & Care

The complex challenges facing healthcare require innovative solutions that can make patient care more effective, easily available, and affordable. One such solution is the digital reconstruction of medicine that transitions much of patient care from hospitals, clinics, and offices to a variety of virtual settings. This reconstruction involves telemedicine, hospital-at-home services, mobile apps, remote sensing devices, clinical data analytics, and other cutting-edge technologies. The Digital Reconstruction of Healthcare: Transitioning from Brick and Mortar to Virtual Care takes a deep dive into these tools and how they can transform medicine to meet the unique needs of patients across the globe.

This book enables readers to peer into the very near future and prepare them for the opportunities afforded by the digital shift in healthcare. It is also a wake-up call to readers who are less than enthusiastic about these digital tools and helps them to realize the cost of ignoring these tools. It is written for a wide range of medical professionals including:

• Physicians, nurses, and entrepreneurs who want to understand how to use or develop digital products and services

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• IT managers who need to fold these tools into existing computer networks at hospitals, clinics, and medical offices

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• Healthcare executives who decide how to invest in these platforms and products

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• Insurers who need to stay current on the latest trends and the evidence to support their cost effectiveness

Filled with insights from international experts, this book also features Dr. John Halamka's lessons learned from years of international consulting with government officials on digital health. It also taps into senior research analyst Paul Cerrato's expertise in AI, data analytics, and machine learning. Combining these lessons learned with an in-depth analysis of clinical informatics research, this book aims to separate hyped AI "solutions" from evidence-based digital tools. Together, these two pillars support the contention that these technologies can, in fact, help solve many of the seemingly intractable problems facing healthcare providers and patients.

Chapter 1 Is Digital Reconstruction Necessary?

DOI: 10.1201/9781003094234-1

In the United States, healthcare spending increased from $74.6 billion in 1970 to $3.5 trillion in 2017. Most health economists agree that this steep climb in expenditures is unsustainable.¹ As we write this chapter, projections for 2020 are not very encouraging: PwC’s Health Research Institute anticipates a 5% net growth increase in medical costs for 2020.² One would expect exceptional quality of care at this price, but the US healthcare system ranks last among 11 high-income countries, with higher morbidity and mortality rates for preventable disorders.³ The causes of this disparity between costs and quality of care would require an in-depth analysis that is beyond the scope of this book. Our primary goal here is to explore the role of information technology (IT) and the possible impact that digital solutions may have on this health crisis.

In this context, it is instructive to review one of the potential solutions discussed in the PwC report: “Employers and payers will nudge people toward lower-cost sites of care. Payers are designing plans to encourage members to choose free-standing facilities and in-home care, rather than more expensive sites. How those benefits are designed and how employees perceive the costs will shape the effectiveness of site of care strategies. Payers and employers are aiming to grow the role of telemedicine as employees grow more comfortable with it, especially if out-of-pocket costs are lower and quality and experience don’t suffer.“² The PwC report was penned before the COVID-19 pandemic disrupted the global healthcare ecosystem. That disruption has put telemedicine and other forms of remote care in an entirely different light.

To answer the question, Is digital reconstruction necessary?, we address the following questions:

• Are digital health initiatives effective?
• Is episodic healthcare meeting patients’ needs?
• How are healthcare needs being met in countries with a less-than-optimal healthcare infrastructure?
• Do we need a digitally enhanced clinical decision support system (CDSS) to address the of errors?
• Will the COVID-19 pandemic require more online solutions?

Reviewing the Evidence on Effectiveness

The evidence to support the cost effectiveness of digital systems such as telemedicine, hospital at-home programs, remote patient monitoring, and mobile health apps is mixed. A 2013 analysis found the average cost of an in-person acute care visit for patients with private insurance was $136 to $176, whereas a similar telemedicine consultation was $40 to $50.⁴ More recently, an analysis found that follow-up patient care after elective surgery may be more cost effective when telemedicine services are used. When 1,200 post-neurosurgical patients in India received either remote care or in-person care over 52 months, remote patient monitoring was deemed more effective and less expensive. The improvement was attributed in part to patients not having to travel to a medical facility for care.⁵ Among patients with type 2 diabetes, mobile health interventions were likewise found cost effective in a 2020 systematic review of 23 studies. Rinaldi et al. cautioned, however: “Cost of mHealth interventions varied substantially based on type and combination of technology used …”⁶

One of the largest analyses of digital health companies, on the other hand, concluded that their services have yet to provide a “substantial impact on disease burden or cost in the US healthcare system” among patients with high-burden, expensive medical conditions.⁷ Safavi et al. studied digital health vendors such as Jawbone, which provides biosensors to patients; Health Catalyst, a healthcare analytics firm that provides services to hospitals; Weltok, which offers population health management; Sharecare, which focuses on consumer health engagement; Accolade, a telemedicine service; and Doximity, a social networking service for physicians.

The observation that 104 analyzed studies did not demonstrate a meaningful impact on clinical outcomes or cost can be attributed to a “sin of omission.” Only 27.9% of the studies looked at high-burden conditions, and none measured costs. Thus, it is impossible to conclude that the 20 top digital health companies studied have no effect on cost effectiveness, only that we do not yet know what impact they have because investigators have not been looking at the right metrics. In other words, a lack of evidence is not equivalent to negative evidence. The interventions provided by these and many other vendors and health-care providers have the potential to improve clinical outcomes and costs because they improve care coordination, improve patient engagement, offer actionable for advanced data and much more.

A systematic review of 39 studies from 19 countries that examined mobile health interventions rather than digital health companies concluded that mHealth was cost effective, economically beneficial, or cost saving.⁸ The analysis looked at a wide array of digital solutions, as illustrated in Figure 1.1. Among the 34 studies that evaluated these mHealth programs in upper- and upper-middle-income countries, 70.6% reported positive costing outcomes. In the 5 lower-middle and lower-income countries, all reported positive costing outcomes. The vast majority of the 39 analyses used behavior change communication approaches and found high rates of positive outcomes. These included programs that attempted to improve attendance and medication adherence. SMS was the most frequently used intervention, which was used to send appointment reminders, provide patient support, conduct surveys, and collect data. Among the studies that looked at SMS, 4 focused on diabetes management or prevention, and allo were deemed cost effective.

Several investigators have reviewed the evidence specifically supporting tele-medicine services. The challenge in interpreting this evidence is the same as the challenge of interpreting studies in clinical medicine, namely, one size does not fit all. In controlled trials that examine the effectiveness of a treatment protocol for treating cardiovascular disease, for instance, a trial may conclude that a drug or lifestyle intervention is ineffective across the entire patient population, but that does not rule out its value in certain subgroups. Similarly, when reviewing telemedicine services, it is tempting to lump all services together or to treat different patient cohorts as one homogenous group. But it is far more likely that the benefits or harm caused by telemedicine varies depending on the type of disorder being treated, the severity of the disease, the communication tools being employed, the type of teleservice—asynchronous or synchronous—the state law governing the patient/clinician interaction, and whether service was offered directly to patients or to other clinicians as a tele-consultation. For example, tele-consultation has been shown to improve asthma control and quality of life when it was compared to routine care. But single case tele-care management failed to improve asthma control.⁹ Similarly, telehealth care in which nurses contacted patients by phone was no more effective than in-person care. On the other hand, combining telecare with other approaches was found useful. For example, linking self-monitoring of asthma symptoms with the help of a Web-based questionnaire with feedback from clinicians, in conjunction with a weekly lung function assessment that prompted a clinical visit when needed, did improve asthma control. Likewise, giving patients an application that monitored their symptoms and combining it with 2-way text messaging and a medication diary generated positive outcomes. For a more in-depth review of the evidence on telemedicine, see Chapter 5.

Type	Definition of application	Examples of activities
Behavior Change Communication (BCC) or Social BCC	Provide health information and behavior change messages directly to clients or the general public and help link people with services. Message content may increase individuals’ knowledge or influence their attitudes and behaviors.	Appointment reminders Support for medication adherence Promote healthy behavior (e.g. smoking cessation) Community mobilization Awareness-raising, education Apps to support self-management
Information systems / Data collection	Increase the speed, reliability, quality, and accuracy of data collected through electronic methods and send to various levels of health system (district, state, national) for quicker analysis compared to paper-based systems.	Collection and reporting of patient health and service provision Electronic health records (EHR) Registries, vital events tracking, surveillance and household surveys
Logistics / Supply management	Help track and manage commodities, prevent stock-outs, and facilitate equipment maintenance. Transmit information from lower- level to higher level health facility.	Ensure medicines and basic supplies are in stock
Service delivery	Support health worker performance related to diagnosis, treatment, disease management and referrals, as well as preventive services. Provide decision support to patients.	Electronic decision support, point of care tools, checklists, diagnostic tools, treatment algorithms Improve communication: provider-provider, provider-patient (notify test results, follow-up visits)
Financial transactions and incentives	Improve access to health services, expedite payments to providers and health services, and reduce cash-based operating costs.	Load/transfer/withdraw money, savings accounts, and insurance Performance-based incentives, vouchers for services (e.g., family planning and antenatal services)
Workforce development and support	Facilitate training and education, provider work planning and scheduling, supportive supervision, and human resource management.	Train and retain health care workers, provide education
Note. Adapted from the Global Health Learning Center mHealth Basics, USAID (2014) and mHealth Compendium (2015) doi:10.1371 /journal.pone.0170581.t001

Figure 1.1 Mobile Health Interventions. The digital health options available to clinicians and patients include basic tools, such as appointment reminders and more advanced systems that provide clinical decision support. (Source: Iribarren SJ, Cato K, Falzon L, Stone PW. What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions. PLOS ONE. 2017;12:e0170581. doi:10.1371/journal.pone.0170581⁸)

There is also evidence to suggest that hospital at-home programs are clinically and cost effective. Bruce Leff, MD, at Johns Hopkins Hospital, has done much of the groundbreaking research in this area. He and his colleagues evaluated such a program in 455 elderly patients in 3 Medicare-managed systems and a VA medical center and found positive results. “On an intention-to-treat basis, patients treated in hospital-at-home had a shorter length of stay (3.2 vs. 4.9 days) (P = 0.004), and there was some evidence that they also had fewer complications. The mean cost was lower for hospital-at-home care than for acute hospital care ($5,081 vs. $7,480) (P < 0.001).“¹⁰ Mayo Clinic and several other large healthcare systems are currently investigating similar models, which we will discuss at gr...

Table of contents

• Cover Page
• Half Title Page
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• Preface
• Acknowledgments
• About the Authors
• Chapter 1: Is Digital Reconstruction Necessary?
• Chapter 2: The Merits and Limitations of Telemedicine, Hospital at Home, and Remote Patient Monitoring
• Chapter 3: The Digital Assault on COVID-19
• Chapter 4: Entering the Age of Big Data and AI-Assisted Medicine
• Chapter 5: Exploring the Artificial Intelligence/Machine Learning Toolbox
• Chapter 6: The Transformative Impact of Conversational Technologies
• Chapter 7: Securing the Future of Digital Health
• Chapter 8: The Digital Reconstruction of Global Health
• Index