CHAPTER 24
Innovations in Healthcare Impacting Healthcare Information Technology
Kathleen A. McCormick
In this chapter, you will learn how to
• Define three key healthcare innovations impacting healthcare IT
• Describe some genetic/genomics examples throughout the continuum of care in health
• Identify the major sources where new evidence can be found in pharmacogenomics
• Identify the IT challenges and uses of clinical decision support for monitoring genetics/genomics and pharmacogenomics
• Describe the volume of mobile devices and the impact on healthcare IT
• Define where telemedicine is being used in healthcare IT
While there were many innovations in healthcare IT described in Chapter 23, this chapter builds upon those innovations by describing three major sources:
• Genetics/genomics/pharmacogenomics
• Mobile devices
• Telemedicine
This chapter addresses basic concepts and current directions for each of these sources of innovation and describes the impact of each on healthcare IT.
Innovations in Genetics/Genomics/Pharmacogenomics
It is now many years since the Human Genome Project was launched in June 1989.1 This chapter defines the implications of genomic science for engineers, computer scientists, and those in healthcare professions. The growth in genomic science has increased steadily in those years, and the volume of tools to analyze the data, diagnose patients, recommend treatments, and integrate into the electronic health record (EHR) and mobile devices has accelerated. The United States and other countries have entered into the era of Precision Medicine that includes $240 million total funding through 2017, targeted to new initiatives and more healthcare IT innovations, $300 million for the Moonshot project for cancer, and $45 million for Brain Research. The U.S. emphasis for Precision Medicine is on cancer therapeutics and resistances.2 The million patients who consent to being studied in the Precision Medicine cohort, now called the All of Us Project, will have data collected that includes their tissue samples, EHRs, and information about their diet, exercise, lifestyles, and other health information that may be relevant to diagnosis and treatment of disease.
Three of the most important definitions for the reader to understand in the context of this chapter are
• Genetics The study of individual genes and their impact on relatively rare single gene disorders (e.g., Down syndrome)
• Genomics The study of all of the genes in the human genomes together, including their interactions with each other, the environment, and other psychosocial and cultural factors (e.g., cancer)
• Pharmacogenomics The study of the influences of genetic variation on medication and adverse events (e.g., how metabolism of commonly used medications, such as warfarin, differs depending on a person’s individual genetic makeup)
The reason these three definitions are so important is that throughout the continuum of healthcare from birth to death, the data that should be collected for an individual for purposes of improving healthcare outcomes, quality, and safety can be influenced by research in genetics, genomics, and pharmacogenomics. This research can identify the impact of variations in genes, genomes, and medication metabolism, respectively. Greater precision in data collection can also have substantial economic benefits. Healthcare outcomes previously were dependent upon clinical practice guidelines and quality measures, as described in Chapter 22. Now healthcare providers recognize that some healthcare outcomes are directly dependent on a person’s individual genetic makeup, with variations in genes determining susceptibility to or increased risk of certain diseases.
These variations are known for prenatal conditions, for newborns, childhood, and adult disorders. Genetic screening tools can more precisely characterize health disorders and can improve medication choices, including drugs that may target underlying diseases caused by genomics. The genetics/genomics profiles may also help clinicians to manage common symptoms such as fatigue, pain, sleep disorders, abnormal clotting, the healing process, and skin breakdown.
Genetics/Genomics Throughout the Healthcare Continuum
Since 2013, teams of clinicians from the National Institutes of Health (NIH), National Human Genome Research Institute (NHGRI) have recognized the influences of genetics and genomics across the healthcare continuum.3 In the preconception period (before a child is conceived), testing can be done to determine if the parents are carriers for genetic variants associated with such diseases as cystic fibrosis and sickle cell disease. Carriers of these diseases may require genetic counseling in the preconception period. In the preconception period, genetic testing of single cells from multiple in vitro fertilization (IVF) embryos is helpful to ensure a healthy genome when the parents are known to be at risk of a genetic disorder. Prenatal care occurs when the mother is pregnant. During this time in the pregnancy, samples of the baby’s genetics can be tested from the mother’s plasma through amniocentesis (to detect, for example, Zika virus, which can lead to genetic deformities). This test also can focus on single gene disorders, chromosomal abnormalities, congenital malformations, and other hereditary genomic conditions. Also in the prenatal period, liquid biopsy can now isolate fetal stem cells in nearly 100 percent of circulating blood in a pregnant woman and allow for full genotyping of the fetus as early as eight weeks in the pregnancy. Newborn screening is done with a blood sample from a child’s heel at birth. Most parents are familiar with the screening test from dried blood that can determine if further genetic tests should be done for conditions such as immunodeficiency from HIV or congenital heart disease.
Disease susceptibility can be determined from genetic tests. For example, if a person has inherited the BRCA2 and BRCA3 genes, they may be more susceptible to acquiring breast and ovarian cancer. Disease screening/diagnosis can be done with fecal (stool) material. DNA testing is done to determine if a person has colon cancer. The family history assists in the accuracy of the genetic testing matched to treatment. The family history helps to narrow the list of candidate genes for testing based on how the condition or disease has presented within the family members in the past.
Prognosis and therapeutic decisions can test for therapies that are matching tumor type with treatment choices. An example is found in matching the mutations found in non-small cell lung cancer with a treatment choice of tyrosine kinase inhibitors. Tumors have genetic profiles that can then be matched to the correct treatment. Also, some patients who carry specific genetic enzymes are not able to metabolize certain medications or have an increased risk of adverse effects from certain medications.
Monitoring disease burden, symptoms, and recurrence occurs when a patient has a genetic enzyme that determines whether they can convert codeine into an active metabolite morphine, which would help control pain.
New Major Sources of Evidence with a Focus on Pharmacogenomics
In February 26, 2015, the Institute of Medicine (now called the National Academy of Medicine) stated, “in many instances, there is sufficient evidence to justify the use of genetic testing to inform choice or dosage of medications.”4
The influences of pharmacogenomics on medication and observations of adverse events can be organized into five specific categories:
• Medication efficacy
• Pharmacodynamics (the study of the mechanism of action, concentration, and effect of drugs)
• Pharmacokinetics (the study of drug absorption, distribution, metabolism, and excretion)
• Target
• Toxicity resulting in inducers or inhibitors
It is estimated that the effects of genetics and genomics are adversely affecting 20–50 percent of patients receiving medications.5
The individual’s genetic inheritance affects their body’s response to drugs. Never before has it been deemed essential that the patient’s ethnicity be included in the EHR. Engineers, computer scientists, and clinicians need to identify current genetic and genomic information resources, such as the Pharmacogenomics Knowledgebase (PharmGKB) web site and the Clinical Pharmacogenomics Implementation Consortium (CPIC) guidelines, which should be included in EHRs. They also need to work on policies regarding access to genomic information stored within the EHR. Lastly, they need to understand the unique issues of privacy and security related to the use and potential misuse of genomic information. Therefore, the new monitoring in healthcare is to match the individual’s genome profile to deliver the best drug for the person at the best dosage that is the most effective and least likely to cause side effects. That is the new concept of personalized treatment in Precision Medicine and the documentation that drugs were administered and side effects and adverse drug reactions were monitored and outcomes evaluated.6
Another project funded by the National Institutes of Health is a knowledge base that collects, curates, and disseminates knowledge about the impact of human genetics variation on drugs response. The PharmGKB is a pharmacogenomics knowledge resource that encompasses clinical information including dosing guidelines and drug labels, potentially clinically actionable gene-drug associations, and genotype-phenotype relationships.7 The data are extracted and curated from pharmacogenomics literature, and like other guidelines, include knowledge extraction, annotation, aggregation, and integration. Where available, some of the drugs in the PharmGKB have clinical interpretations and clinical implementation plans. Specific workgroup consortia are studying the pharmacogenomics of four specific drugs: warfarin, tamoxifen, SSRI class (including drugs like citalopram, escitalopram, paroxetine, sertraline), and clopidogrel.
The guidelines resulting from the extraction of evidence are produced in a database called the Clinical Pharmacogenomics Implementation Consortium (CPIC).8 Workgroups are also implementing the CPIC guidelines into EHRs using clinical decision support (CDS). It is necessary to bring clinical decision support to the point of care information about pharmacogenomics. It is also necessary to bring clinical decision support about pharmacogenomics to patients during the entire continuum of care.
As an example of a warning that might be placed in a patient’s EHR, consider a leukemia patient whose genotype result predicts that the patient will be at risk for myelosuppression (bone marrow suppression) when taking a particular drug. The patient’s EHR should include a warning such as “The patient is at risk for myelosuppression with normal doses of 6-mercaptopurine. If disease treatment normally starts at the ‘full dose,’ consider starting at 30–70 percent of target dose (e.g., 1–1.5 mg/kg/d), and titrate based on tolerance. Allow 2–4 weeks to reach steady state after each dose adjustment.”
Effective March 15, 2017, there are 36 CPIC guidelines with sufficient evidence to implement in clinical practice.8 There are 83 more drugs in the pipeline for CPIC, and the FDA has identified pharmacogenomics biomarkers on drug labels in 155 drugs. The PharmGKB is evaluating 560 drug interactions for sufficient evidence to produce CPIC guidelines.
The IT Volume Challenge of Monitoring Genetics/Genomics/Pharmacogenomics in Healthcare
A genetic analysis of a single patient can produce about 1 terabyte of data in a single encounter.9 Genetics/genomics may be analyzed before or at the time of diagnosis and multiple times during treatment, as well as being integrated with lab blood data, doctors’ and nurses’ clinical observations, tissue biopsy and other data, and imaging data (such as X-ray, MRI, CAT scans). The volume of new data is so large that healthcare information technologists will need to develop roadmaps for incorporation into their current practice and EHRs. If one studied the genetics of an individual over the continuum of care from birth to death, the amount of data, the multiple repositories in which the data are stored, the multiple formats the data are described in, and the multiple standards applied to the data would be daunting. The mining of these data over time and through different environmental locations in which the person has resided is becoming a formidable task and a new science in big data mining, storage, and retrieval.
The NIH is developing roadmaps to determine if the genetic and genomic findings are clinically relevant. The project, called ClinGen (Clinical Genome Resource), is intended to be a resource that defines the clinical relevance of genomic variants. The goal is to aid in the diagnosis and treatments for use in the Precision Medicine Initiative. ClinGen also aims to improve patient care by accelerating the understanding of genomic variation in healthcare through data sharing, knowledge curation, and technology development. Three questions are raised in considering whether a clinical variation has been found in ClinGen: Is the gene associated with the disease? Is the gene variation causative of the disease? Is this information something that can be used in describing a treatment? Working groups are establishing data models and standards for integrating these finding into EHRs.10
One project is being conducted to develop workflow and algorithm pathways for the inclusion of genetic, genomic, and pharmacogenomics information into user-friendly CDS formats linked to the EHR. This work is taking place at St. Jude’s Children’s Research Hospital. The work specifically supports a model workflow with the CDS algorithm to incorporate pharmacogenomics tests into their EHR.11 Additionally, other national initiatives have been funded by the NIH to facilitate strategies to integrate genomics into practice, including Implementing Genomics in Practice (IGNITE) and the Electronic Medical Records and Genomics (eMERGE) Network.12
At the National Academy of Medicine (NAM), another relevant implementation project is Displaying and Integrating Genetic Information Through the EHR, or DIGITizE. This work is a part of the NAM Roundtable on Genomics and Precision Health. Several vendors working on this project include Cerner, Epic, and Allscripts. Roundtable members are launching pilot studies focused on pharmacogenomics with some vendors. The DIGITizE working groups are also developing an implementation guide, the Logical Observation Identifiers Names and Codes (LOINC) database, and an Allele Registry with ClinGen.13
Researchers and clinicians have identified the need for a toolbox or toolkit to help in the dissemination of information and implementation of the genetic scientific information on diagnosis and treatment into clinical practice. A toolkit that has been developed was made available as of March 15, 2016, through Genome.gov.14 The toolkit provides links to resources that helps the developers identify which tests to include, how to interpret results, and how to manage genetic conditions. It specifically provides links to find specific genes, conditions, or medications and link them to ClinGen. The Guidelines for Pharmacogenomics are included in these resources. Some of the disease-specific information includes resources addressing cancer and rare disorders. Links to family history tools and for baby’s first genetic tests are included. Several sources for basic and advanced education are also provided for healthcare providers and consumers.
Another team that is advancing the development of an ecosystem for sharing genomic and clinical data is the Global Alliance for Genomics and Health. It has several projects. The Beacon project is developing an open technical specification for sharing data from large-scale population sequencing projects, the clinical data, and the curated data on variations. The BRCA Challenge aims to exchange data on breast, ovarian, and other cancers that are variants in the breast cancer genes (BRAC1 and BRAC2). Another component of the global effort is the Matchmaker Exchange, a collaborative effort with the Rare Diseases Research Consortium. The advantage of an exchange is that even if the suspicious gene variant occurs in only a few people, querying the database can potentially identify cases with similar gene disruptions in common and establish the diagnosis of a rare disease. The data set can be queried for the presence or absence of a specific allele without requiring compatible data sets or compromising patient identity.15
Necessary Components in Electronic Health Records
Relevant to healthcare information technology is the need to ensure that the family history section in the EHR elicits a minimum of three generations and that the physical assessment section is updated regularly and includes genetic and environmental information and risk factors.16 This assessment will uncover who the biological parents are, if they had conditions that are known to be linked to genetics, and risks associated with surgery (e.g., complications from anesthesia) and other procedures (e.g., blood clotting or unusual bleeding disorders). The Surgeon General has a free genetic screening tool on the HHS web site.17 The family history is also a window into conditions for which an asymptomatic patient/consumer may have a genetic predisposition. For complex diseases such as cardiac disease, hypertension, or diabetes, the consumer needs to be guided about routine screening, testing, and targeted actions they can take to prevent the condition, or gain early treatment when diagnosed, and seek continuing education about new diagnostic and treatment options. Since 2010, the Centers for Medicare and Medicaid Services (CMS) requires the provider to incorporate the family history into the physical exam for the patient encounter to be reimbursed.
There are standardized symbols and nomenclature to be used in the family history. The Pedigree Association Task Force first developed them in 1995. Since 2008, recommended symbols and nomenclature have been defined.18 When standardized tools, nomenclature, and symbols are used, integration across professional practices is possible, and interpretation is consistent between sites.
Necessary Components of the Healthcare Delivery Team
Incorporating genomics, and especially pharmacogenomics, into the delivery of healthcare necessitates adding new members to the traditional team of doctors, nurses, and pharmacists, including a geneticist, and perhaps one or more computer scientists, engineers, programmers, and security experts. This team might also include a genetic counselor if one is available in the facility. If a healthcare facility cannot support such a team, it might need consultation mechanisms with larger practices and academic settings. Genetic, genomic, pharmacogenomics, and bioinformatics competencies have been developed for training in all of these special areas.
Challenges in the IT Transfer of Genomics and Pharmacogenomics into Clinical Practice
There are challenges that remain in the integration of the genomics information into EHR implementation. The most notable are data sharing and information storage and retrieval policies related to data into the EHR from genomic resources. There are further challenges to move data from EHRs into the new mobile technologies (including wearable biosensors), telemedicine, and digital medical devices. Some small companies are beginning to develop tools that translate the CPIC guidelines into alert sheets for healthcare practitioners. Others also link the CPIC guidelines to drug databases that identify drug-drug interaction and drug overdose information. Still others are integrating the CPIC guidelines into clinical decision support tools to integrate into the EHR.
Innovations in Mobile Devices in Healthcare
Mobile devices are slated for a $57 billion growth internationally by 2020.19 The markets include mobile devices, sensors, and smart homes. Monthly global data traffic is expected to be 49 exabytes by 2021 according to a Cisco White Paper.20
Wireless Communication Technologies and Standards
The foundation of mHealth is the capability of mobile devices to connect with networks in multiple ways. Rapid growth has occurred with three hardware elements enabling mobile health (mHealth). The hardware advances are larger physical device size, wireless network access, and longer battery life. Large, redundant storage capacity has become available through cloud computing services. In addition, the development of the smartphone has allowed powerful handheld computing with the ability to access the Internet.
The technology is supported by Wi-Fi, Bluetooth, and radio frequency identification (RFID). The regulation of wireless technology in the United States evolves under the direction of the Federal Communications Commission (FCC). Fourth-generation (4G) wireless supports all Internet Protocol (IP) communication and uses additional technology to transfer data at high bit rates. The International Telecommunications Union Radiocommunication Sector (ITU-R) sets the standards for International Mobile Telecommunications Advanced (IMT-Advanced) technology.21, 22
The ITM-Advanced standard for 4G services is a data rate of 100 megabits per second (Mbps) for communications while traveling in a car or train and 1 gigabit per second (Gbps) for communications while standing still.23
Wi-Fi is intended for local networks called wireless local area networks (WLANs). Bluetooth is intended for a wireless personal network (WPAN). Wi-Fi and Bluetooth are complementary.24
Wireless Application Environment (WAE) specifies an application framework, and Wireless Application Protocol (WAP) is an open standard allowing telephone communication access from mobile devices.25
Mobile devices can exchange data through Wi-Fi or connect to the Internet (in the United States) through 2.4 GHz ultra high frequency (UHF) waves and 5 GHz super high frequency (SHF) waves. Advanced hardware makes this connection through a wireless network access point, or hotspot. These standards are from the Institute of Electrical and Electronics Engineering (IEEE) standard 802.11.25
Protection for these wireless connections is through various encryption technologies such as Wi-Fi Protected Access (WPA) and Wi-Fi Protected Access 2 (WPA2) security protocols.25 To assure devices can communicate with one another, Extensible Authentication Protocol (EAP) is used. Wi-Fi security concerns are covered by the National Institute of Standards and Technology (NIST) Special Publication 800-153, “Guidelines for Securing Wireless Local Area Networks (WLANs).”26 Security of Bluetooth wireless technologies is also covered by a NIST Special Publication (800-121, Revision 1).27
RFID is a technology that uses radio frequency electromagnetic fields to transfer data. It is usually used to track inventory. The International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) set standards for RFID. Security concerns are addressed using cryptography standards addressed in NIST Special Publication 800-98, “Guidelines for Securing Radio Frequency Identification (RFID) Systems.”28
Mobile Devices Connected to the Internet
When mobile devices are connected to the Internet, the network model and communications protocols use the Transmission Control Protocol (TCP) and the Internet Protocol (IP), or TCP/IP. The Internet Engineering Task Force (IETF) maintains the standards for mobile devices connected to the Internet. Other commonly known protocols for the Internet user interface include the Simple Mail Transfer Protocol (SMTP), File Transfer Protocol (FTP), and Hypertext Transfer Protocol (HTTP). HTTP Secure (HTTPS) is a protocol for secure communication over computer networks and is used on the Internet.
When mobile devices are connected to the Internet to connect to the EHR, the application programming interfaces (APIs) require different HIT standards. The current standards are in need of change since the current standards are not inclusive of information flow into and out of the EHR. This level of standard will eventually lead to consumer mobile devices connected to EHRs for data retrieval.
Mobile Device Security Protocols
To provide encryption security protocols, Pretty Good Privacy (PCP) and GNU Privacy Guard (GPG) are used. Cryptography network protocols are Secure Sockets Layer (SSL) and Transport Layer Security (TLS). New protocols will be on the horizon to protect the mobile devices from cybersecurity threats that protect sender to receiver.29 An alternative to TLS to monitor is the Direct Project.30
How Mobile Networks Are Being Used in Healthcare
As the mHIMSS Roadmap describes, “patients and providers are leveraging mobile devices to seek care, participate in, and deliver care. Mobile devices represent the opportunity to interact and provide this care beyond the office walls.”31 In a 2015 update to the mHIMSS Roadmap, the task force added the following topics: new care models (including consumer engagement), policy, privacy and security, return-on-investment and payment, standards and interoperability, and technology (infrastructure, standards, and interoperability).32
mHealth is identified by the National Institutes of Health as one of the key innovations to be studied in the All of Us Research Program (https://www.nih.gov/allofus-research-program). The program will support projects that use mHealth technologies to correlate activity, physiological measures, and environmental exposures with health outcomes.33
Across NIH, other studies are being conducted on mHealth. Mobile devices are being studied to facilitate anytime, anywhere access to healthcare data that extends beyond traditional clinical settings. NIH is conducting studies to develop new consumer engagement techniques and strategies for more effective and timely engagement between clinicians, patients, and consumers. Finally, mobile devices are considered a necessary ingredient going forward to determine the genetic/genomic variance in populations that are compliant with treatment, add alternative treatments such as diet and exercise to their treatments, and prevent the occurrence of persons with genetic predispositions from actually developing diseases. Mobile health is being touted as the path forward for consolidated and value-based care.
The Most Popular Mobile Health Apps
An IMS Institute for Healthcare Informatics report notes that significant variation exists in the functionality of mHealth apps available to consumers, with most having narrow functionality intended to inform, instruct, record, display, guide, remind/alert, or communicate. The report also points out that “depending on the intent of an app, multi-functionality is not always required to meet the purpose of an app and therefore should not be considered the single factor in assessing or rating mHealth apps.”34
The most popular mobile device mHealth apps by category in 2015 were fitness apps (36%), lifestyle and stress management apps (17%), and diet and nutrition apps (12%).34 There were over 130 fitness apps for public use. The most popular were MapMyFitness, Fitbit, and Runtastic. For disease and treatment management, the most widely used mHealth mobile apps by category in 2015 were for disease-specific information (9%), women’s health and pregnancy (7%), and medication reminders and drug information (6%). In 2015, the top disease specific mHealth mobile device apps were mental health apps (29%), diabetes apps (15%), heart and circulatory apps (10%), musculoskeletal apps (7%), and nervous system apps (6%).34
The public utilized the apps to inform, instruct, record, display, guide, remind/alert, and communicate. The rapid advances in the devices have led to the rapid adoption and consumer-driven health wearables (watches, shoes with biofeedback, and stress relievers).
Between 2013 and 2015, there was a significant increase in the number of mHealth apps with the capability to connect to social media (up 8% from 26% to 34%). An app called QuitNow that provides real-time stats on consumption of cigarettes. Another example is C25K Couch to 5K that provides a training companion, and posts workouts and progress through Facebook.34
Mobile apps are available that integrate with social media for specific populations such as those with communication difficulties. The apps help people with autism, Down syndrome, amyotrophic lateral sclerosis (aka Lou Gehrig’s disease), apraxia (difficulty speaking), stroke, or other conditions communicate through augmentation and alternative communication, and link to social media for support and educational community groups.
A major problem in mobile application is the sustainability rate, which was measured in 30-day usage of the app. The majority of persons with mental health issues sustain their usage only 40 percent, whereas the highest sustainability rate has been with fitness (76%), diabetes (67%), smoking cessation (63%), and caloric counting (62%). Overall app sustainability in 2015 is 59 percent.34
Healthcare Professionals’ Use of Mobile Devices
The use of smartphones and tablets has become ubiquitous in most healthcare environments. The concept of bring your own device (BYOD) is now prominent in many healthcare settings. Healthcare professionals are bringing their Androids, iPhones, iPads, and tablets into their work environments. They are connecting to the vendor systems and integrating into the EHR. The IT departments have to secure those devices and their communications with the enterprise.
Major Barriers to Advancing Mobile Devices
The major barriers to widespread adoption of devices are the following: lack of evidence that the content changes patient outcomes; limited integration with EHR, personal health record (PHR), and patient portals; access gaps in coverage and communication; data privacy and security; and lack of reimbursement. As mentioned previously, these are being addressed by the HIMSS task force on mHealth.32
Steps to Institutionalizing Genomic and Mobile Technologies
The most significant driver for both genomics and mobile technologies is the consumer. This section identifies the gaps that are common to both the genomics and mobile device areas.
The establishment of regulatory guidelines is ongoing but not complete. Security and privacy guidelines are not inclusive of genomic and mobile technologies. There is a gap in curating and evaluating the content on applications, and there is a lack of the following:
• Inclusive reimbursement models
• Strategic healthcare system buy-in to clinicians prescribing apps
• Integration of genomics and mobile devices into the clinical workflow, EHRs, PHRs, models for CDS to support the test result and interpretations, continuum of care, and optimized connectivity
• Predictors of success in consumers who should be screened for genetic tests, and those who should be prescribed mobile apps
The stakeholders moving forward are developers, regulators, institutions, payers, health systems, providers, and patients/consumers. Partnerships need to be facilitated to remove the barriers for these innovations. While there are databases of diseases and treatment and databases of pharmacogenomics, there currently are no genetic/genomics databases for symptom management (e.g., pain and fatigue).
Innovative Institutions Pushing Advances in Genomics and Mobile Devices
There are two national academic research programs (Stanford and MIT) and four companies that highlight the integration of genomics and mobile device use specifically focused on the aging population. A description of these innovative programs is as follows:
• Human Longevity, Inc. (HLI) is linking human genomics, informatics, next-generation DNA sequencing technologies, and stem cell advances to solve diseases of aging.
• The Google-owned company Calico is focused on comparative genomics to harness advanced technologies and understand the biology that controls lifespan.
• Palo Alto Investors is investing in prizes related to senescence (aging) research. They are asking questions such as why women live longer than men.
• The ABEO Smart Shoe from the Stanford Center for Longevity is sold through The Walking Company.
• The MIT AgeLab is a multidisciplinary research program that works with business, government, and NGOs to improve the quality of life of older persons.
Nine Technologies for Future Innovation Using Devices
According to the American Association of Retired Persons (AARP), the following nine technologies are still needed for innovation:35
• Hearing and vision, preventive aging care, cognitive and brain health, and life support tools
• Health sensors for vital sign monitoring, and diagnostic devices
• Care navigation of care records, care planning tools, and care coordination solutions
• Emergency detection and response—the integration of home security systems with sensors to detect falls, location tracking (in patients with Alzheimer’s disease), and activity of daily living monitors (eating, walking, toileting)
• Physical fitness devices with enabling solutions for those persons with mobility impairments. This is also known as aging with vitality.
• Diet and nutrition tracking tools for cognitively impaired, immobile, and handicapped persons, with solutions for cooking
• Social engagement for mobility assistance, online communities, and peer-to-peer support
• Behavioral and emotional companionship solutions with support groups, self-help solutions, stress/emotional management, and grieving after loss
• Medication reminders, tracking tools, and compliance services
Social Media Being Used in Healthcare
The types of social media used in healthcare are a separate description that will not be fully addressed in this book. When healthcare providers and government agencies and officials want to get a message out to the press, they use Twitter. When they create groups for patients with similar conditions and want to educate, monitor, and evaluate groups of patients and consumers, they use Facebook. Oftentimes, a healthcare professional is a member of the Facebook group. Professionals and enterprises used LinkedIn to create communities of correspondence. All of these modes are available on smartphones, so the correspondence can be within healthcare and external to healthcare. Video platforms include YouTube for educational transmissions. Shared services utilize Skype and FaceTime to communicate with health professionals and patients/consumers.
Innovations in Telehealth
The American Telemedicine Association (ATA) defines telemedicine as “the use of medical information exchanged from one site to another via electronic communications to improve patients’ health status.”36 ATA treats the terms “telemedicine” and “telehealth” as synonyms and uses them interchangeably to refer in general to the use of remote healthcare technology to deliver clinical services.37 It clarifies the distinction sometimes made between the terms as follows: “Closely associated with telemedicine is the term ‘telehealth,’ which is often used to encompass a broader definition of remote healthcare that does not always involve clinical services.”36
Telehealth is used in healthcare for live video conferencing, for consultation and remote patient monitoring and e-visits via a secure web portal. With mobile devices in patients’ homes, telehealth can now be an extension of mobile health for home care monitoring in patients with chronic health conditions.
One of the advances in healthcare that makes healthcare practitioners more accessible to consumers and patients is the presence of nurse practitioners in retail clinics and pharmacies. Often equipped with telehealth, the nurse practitioner and pharmacist can triage the patient and call upon specialists and experts in academic healthcare and acute healthcare environments while the patient is in the retail clinic. When consultants are in demand for psychiatric and dermatologic needs of patients, for example, telehealth has provided a means for patients in remote and urban areas to have the advantage of a specialist consultant.
Major Services of Telehealth
Examples of major services of telehealth are defined by the ATA as follows:38
• Primary care and specialist referral services may involve a primary care or allied health professional providing a consultation with a patient or a specialist assisting the primary care physician in rendering a diagnosis. This may involve the use of live interactive video or the use of store and forward transmission of diagnostic images, vital signs, and/or video clips along with patient data for later review.
• Remote patient monitoring, including home telehealth, uses devices to remotely collect and send data to a home health agency or a remote diagnostic testing facility (RDTF) for interpretation. Such applications might include a specific vital sign, such as blood glucose or heart ECG or a variety of indicators for homebound patients. Such services can be used to supplement the use of visiting nurses.
• Consumer medical and health information includes the use of the Internet and wireless devices for consumers to obtain specialized health information and online discussion groups to provide peer-to-peer support.
• Medical education provides continuing medical education credits for health professionals and special medical education seminars for targeted groups in remote locations.
Delivery Mechanisms Used for Telehealth
ATA defines four delivery mechanisms that support telehealth:39
• Networked programs link tertiary care hospitals and clinics with outlying clinics and community health centers in rural or suburban areas. The links may use dedicated high-speed lines or the Internet for telecommunication links between sites. ATA estimates the number of existing telemedicine networks in the United States at roughly 200 providing connectivity to over 3,000 sites.
• Point-to-point connections using private high-speed networks are used by hospitals and clinics that deliver services directly or outsource specialty services to independent medical service providers. Such outsourced services include radiology, stroke assessment, mental health, and intensive care services.
• Monitoring center links are used for cardiac, pulmonary, or fetal monitoring, home care and related services that provide care to patients in the home. Often normal landline or wireless connections are used to communicate directly between the patient and the center although some systems use the Internet.
• Web-based e-health patient service sites provide direct consumer outreach and services over the Internet. Under telemedicine, these include those sites that provide direct patient care.
Chapter Review
This chapter has described healthcare innovations in three areas: genetics/genomics/pharmacogenomics, mobile devices, and telehealth. While there are other innovations and issues, barriers to implementation, and regulations affecting these and other areas, this chapter highlighted the healthcare IT needs in these three areas. The healthcare technology innovations in these areas have been embraced by consumers so rapidly that the healthcare industry and regulators are under pressure to address the hurdles of interstate licensure and reimbursement associated with these innovations. Further advances will be made in these three areas in the next five to ten years, and you can stay up to date by accessing the sources cited in this chapter. The next five to ten years will also demonstrate rapid advances in these three innovations, so primary sources have been provided for students.
Questions
To test your comprehension of the chapter, answer the following questions and then check your answers against the list of correct answers that follows the questions.
1. The importance of genomics in healthcare is to:
A. Understand the genetics in healthcare
B. Facilitate risk identification and diagnosis and establish prognosis and symptom management
C. Plan for the future of healthcare
D. Understand the actions of each gene
2. Why does genetic and genomic information require big data storage and analytics?
A. Quality cost data has to be included in documenting genetics/genomic information.
B. State and national healthcare data are needed.
C. It is costly to pay for the genetics/genomics data.
D. The diagnosis and analysis data involved in genomics requires the integration of several large databases, oftentimes requiring cloud computing.
3. What part of the continuum of care is affected by genetics and genomics?
A. None of the continuum of care components is affected.
B. The continuum of care from preconception to death.
C. The continuum of care from a diagnosis to death.
D. The continuum of care from diagnosis to treatment.
4. Where can the guidelines be found for pharmacogenomics evidence?
A. There is no evidence in pharmacogenomics.
B. There is evidence in the FDA guidelines for genomics.
C. There is evidence in the AHRQ guidelines for disease treatment.
D. The CPIC guidelines contain the pharmacogenomics evidence.
5. What best describes wireless communications?
A. Networks that provide faster performance
B. Networks that support only the Internet
C. Mobile computing devices that connect with networks in multiple ways
D. New technology transfers high bit rates
6. What best represents the future of mHealth inside healthcare facilities?
A. Path toward consolidated and value-based care
B. Access to TCP Internet usage
C. Complete HL7 coverage
D. Unified Internet communications
7. What are the most common mHealth platforms?
A. Smartphones, electronic tablets, and remote technologies
B. Cellular networks, wireless networks, and mobile devices
C. Electronic tablets, mobile devices, and cellular networks
D. Remote technologies, smartphones, and wireless devices
8. What is the correct definition of telehealth?
A. Telehealth is the use of medical information exchanged from one site to another via electronic communications to improve patients’ health status.
B. Telehealth is the emerging field in medical informatics, referring to the organization and delivery of health services and information using the Web and related technologies.
C. Telehealth is the field of informatics using a handheld device.
D. Telehealth cannot be defined since it is an evolving method.
Answers
1. B. The importance of genomics in healthcare is to facilitate risk identification and diagnosis and to establish prognosis and symptom management.
2. D. The diagnosis and analysis involved in genomics requires the integration of several large databases. An actionable treatment course cannot be selected until the genes and pathways involved in the abnormality have been researched in multiple public and private databases. Both the clinical actions and the biologic actions need to determine the relevance to the treatment. These involve heuristic tools, curated and annotated databases, genomic tumor databases, and other knowledge bases that include outcome databases, genomic registries, integrative analysis tools, and machine learning systems. And in many cases, there are several possible treatment alternatives to a particular abnormality.
3. B. The entire continuum of care from preconception to death is affected by genetics and genomics.
4. D. The Clinical Pharmacogenomics Implementation Consortium (CPIC) guidelines contain the pharmacogenomics evidence.
5. C. Mobile computer devices that connect with networks in multiple ways best describes wireless communications. Technologies used to wirelessly communicate with mobile devices include mobile telecommunication such as Wi-Fi.
6. A. The future of mHealth inside healthcare facilities is best represented as a path toward consolidated and value-based care. Some of these innovations include paging and first-responder communication systems.
7. B. Cellular networks, wireless networks, and mobile devices are the most common mHealth platforms.
8. A. Telehealth is the use of medical information exchanged from one site to another via electronic communications to improve patients’ health status.
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