Telemedicine uses electronic information and telecommunications technologies to support remote clinical healthcare, education, and administration. It has grown in popularity due to rising healthcare costs and physician shortages. Common telemedicine practices include teleradiology, teleneurology, and telepsychiatry which allow specialists to consult remotely. While telemedicine provides benefits like improved access to care, it also faces barriers such as reimbursement issues, high costs, and legal/regulatory challenges. Public health informatics applies information science to public health practice, research and learning. It involves surveillance systems that collect and analyze health data to monitor diseases and protect population health.

1. Chapter 17: Telemedicine
Robert Hoyt MD
Thomas Martin PhD
Learning Objectives
After reviewing the presentation, viewers should be able to:
State the difference between telehealth and telemedicine
List the various types of telemedicine consultations, such as
teleradiology and teleneurology
List the potential benefits of telemedicine to patients and
clinicians
Identify the different means of transferring information with
telemedicine, such as store and forward
Discuss the most significant ongoing telemedicine projects

2. Definitions
Telehealth: The use of electronic information and
telecommunications technologies to support long-distance
clinical health care, patient and professional health-related
education, public health and health administration
Telemedicine: “the use of medical information exchanged from
one site to another via electronic communications to improve
patients' health status” or simply the remote delivery of
healthcare
Popularity of Telemedicine
Rising cost of healthcare worldwide
new strategies (telemedicine) to prevent readmissions
Shortage of specialists in rural areas
Rise in chronic diseases and aging of population
Improved collaboration among physicians and disparate
healthcare organizations
Raises patient satisfaction when it results in better access to
specialty care

3. Electronic Telemedicine Modes
Radio Doctor—predicted in 1924
TV
Telephone
Internet
Telemedicine Communication ModesCommunication
ModeProsConsPatient-Portal
Secure messagingAsynchronous. Able to attach photos.
Response can be formatted with
template. Could use VoIP. Audit trail is availableNot as
personal as live visit. Usually not connected to EHR or other
enterprise information but may be in
the futureTelephoneWidely available, simple and inexpensive.
Real-timeNot asynchronous. Unstructured.
No audit trail. Only real-timeAudio-VideoMaximal input to
clinician. Can include review of x-rays, etc. Perhaps more

4. personal than just messagingCurrently, most expensive in terms
of networks and hardware, but that is
changing
Telemedicine Transmission Modes
Store-and-forward
Images or videos are saved and sent later
Asynchronous communication
Real time
A specialist views video images transmitted from a remote site
and discusses the case with another physician
Requires more sophisticated equipment: two way interactive
telemonitors permit the specialist to see and talk to the patient
Remote monitoring
Monitor patients at home or in a nursing home; usually part of
disease management
Telemedicine Categories

5. (Author’s classification)
Televisits:
Teleconsultations:
Teleradiology, teledermatology, teleneurology, telepharmacy
Telemonitoring
Telerounding: hospital inpatients
Telerobots
eICUs
Telehomecare: monitoring physiological parameters, activity,
diet, etc. at home
Teleconsultation is a worldwide phenomenon because
specialists tend to practice in large metropolitan areas, and not
in rural areas
Most programs consist of a central medical hub and several
rural spokes
Programs attempt to improve access to services in rural and
underserved areas, to include prisons. This reduces travel time
and lowers the cost for specialists and patients alike
The most commonly delivered services are mental health,
dermatology, cardiology, radiology and orthopedics
Teleconsultations

6. Teleradiology: with new digital imaging, EHRs and other
technologies, this teleconsultation makes sense
Radiologists can be home at night, read an image, dictate a
report via voice recognition and host it all in the cloud for
others to view and link to the local EHR
vRad is a service that reads images, usually during the night,
when there may be a shortage of radiologists in some areas
In 2013 The American College of Radiologists published
Teleradiology Practice Guidelines. The Task Force outlined
benefits as well as challenges to the practice
Teleconsultations
Teleneurology: there is a shortage of neurologists in rural areas
and a shortage covering ERs due to liability issues
This is very significant given the fact that many stroke patients
may benefit from receiving “clot busters” in the first 3 hours of
a stroke
Teleradiology permits a remote neurologist to read the CAT
scan of the brain and see the neurological exam being conducted
on the patient
There are now several commercial teleneurology groups that

7. contract to cover emergency rooms remotely
Concussions are another medical problem that potentially could
benefit from teleneurology
Teleconsultations
Telemental Health (Telepsychiatry): There is a national
shortage of mental health workers in the US
There is evidence that a remote session with a therapist has the
same outcome as a face to face visit
This approach is particularly valuable for ERs, prisons and
post-deployed active duty military personnel
Some use Skype to accomplish a visit, while others use more
elaborate audio-visual technology
This is an international effort
Teleconsultations
Teledermatology: Very logical specialty because there are very

8. few emergencies in this specialty and an image of a skin lesion
is frequently diagnostic
Store and forward most common mode
Digital cameras/camera phones have only made the process that
much easier
There are several international initiatives that support
teledermatology, mentioned in the textbook
Artificial intelligence can interpret the images
Teleconsultations
Retinal images can now be obtained, even without dilating the
pupil.
A primary care doc can image a diabetic while in the office and
forward it to an ophthalmologist for a reading (store and
forward)
There is go evidence that this increases screening in patients
with diabetes
Teleophthalmology

9. Telerounding
Robot rounds: expensive robots can be placed at the bedside to
collect and store information and then communicate to the
responsible physician, preventing a second set of rounds
Virtual ICU or eICU: Due to a nationwide shortage of ICU
experts (intensivists) eICUs have appeared that have a central
hub at a larger medical center covering small remote ICUs
It includes not just an ICU nurse and physician covering remote
patients but care is based on the best possible evidence
Particularly valuable at night or weekends when coverage may
be light
Families can converse with remote staff
eICUs have great potential to improve morbidity/mortality and
length of stay but articles have tended to show conflicting
results
Telemonitoring
Telehomecare: the concept is that monitoring patients at home
may prevent unnecessary ER visits and hospital admissions
Multiple sensor now exist to measure a myriad of physiological
markers (see next slide)
This approach is embraced by the medical home model and
accountable care organizations
Unfortunately, thus far most telehomecare studies have not
shown a significant impact on medical quality, cost, etc.
Telemonitoring

10. Available Sensors and Devices
Measure:
Weight
Blood Pressure
Glucose: blood sugar
Oximeter: oxygen level
Spirometry : breathing capacity
Temperature
Medication tracker
PT/INR: how thin the blood is on blood thinners
Motion detectors/chair and bed sensors: can detect falls
Fitness
Health Buddy Telemonitoring Example

11. Telemedicine Initiatives
Informatics for Diabetes Education and Telemedicine
(IDEATel)
Georgia Partnership for Telehealth (GPT)
Middle East Society of Telemedicine (MESOTEL)
University of Texas Medical Branch at Galveston
Teleburn at the Ottawa Telemedicine Network
California Central Valley Teleretinal Program
Northwest Telehealth
More examples in the textbook
Barriers to Telemedicine
Limited reimbursement
Limited research showing reasonable benefit and return on
investment
High initial cost
Limited availability of high speed telecommunications
Bandwidth issues

12. Need for high resolution images or video for some specialties
Licensure laws
Lack of standards
Lack of evaluation by a certifying organization
Fear of malpractice as a result of telemedicine
Ethical and legal challenges
Sustainability due to inadequate long term business
Lack of sophistication on the part of the patient
Barriers to Telemedicine
21
Telehealth is a broad term that means remote delivery of
medical care, administration and education
Telemedicine is the remote delivery of medical care using
technology

13. Almost all specialties are testing telemedicine
In spite of no reimbursement eICUs are expanding
Telehomecare is popular but too new to know its actual impact
Multiple barriers to telemedicine exist
Conclusions
Chapter 19: Public Health Informatics
Brian Dixon PhD
Saurabh Rahurkar DrPH

14. Learning Objectives
After reviewing the presentation, viewers should be able to:
Define public health informatics (PHI)
Explain the importance of informatics to the practice of public
health and the role of informatics within a public health agency
Define and distinguish the various forms of public health
surveillance systems used in practice
List several common data sources used in the field of public
health for surveillance
Public health: “the science and art of preventing disease,
prolonging life, and promoting health through the organized
efforts and informed choices of society, organizations, public
and private communities, and individuals.”
Public health informatics: “systematic application of
information and computer science and technology to public
health practice, research and learning”
Whereas physicians and care delivery organizations focus on the
health of individuals, public health focuses on the health of
populations and communities.
Definitions

15. Definitions
Public health surveillance: ongoing systematic collection,
analysis, and interpretation of health-related data essential to
planning, implementation and evaluation of public health
practice, closely integrated with the timely dissemination of
these data for prevention and control
Syndromic surveillance: surveillance using health-related data
that precede diagnosis and signal a sufficient probability of a
case or an outbreak to warrant further public health response
Introduction
The overarching goal of public health has been to monitor a
variety of medical diseases and conditions rapidly and
accurately so as to intervene as early as possible to detect,
prevent, and mitigate the spread of epidemics, the effects of
natural disasters, and bioterrorism
To address these challenges, public health organizations
conduct a range of activities across three, broad core functions
– assessment, policy development and assurance.

16. Assessment – Public health agencies spend most of their time
and resources on investigations of potential threats to the
public’s health. Activities include testing and monitoring of
water quality, laboratory examination of diseases carried by
mosquitoes, tracking food-borne illnesses, testing for
environmental hazards (e.g. soil lead levels), monitoring for
potential bioterrorism threats, and tracing the contacts for
individuals exposed to diseases as well as hazardous chemicals.
Public Health 3 Core Functions
Policy Development – Public health agencies also create
policies and regulations to protect the health of populations. For
example, children may be required to have certain
immunizations before they can attend school to prevent disease
outbreaks that would harm children and disrupt family life.
Agencies use the evidence they gather from their investigations
as well as the scientific literature to advocate for policies that

17. state and federal legislative bodies ultimately adopt for the
health of populations and communities.
Public Health 3 Core Functions
Assurance – Once laws and regulations are passed to protect
health, public health agencies are tasked with assuring
compliance with them. Local health departments may perform
housing inspections to assure that landlords comply with rules
concerning pest control. Restaurant inspectors typically work
for local health authorities, and they assure that those who
prepare food wash their hands, wear gloves, and take other
precautions to prevent the spread of disease.
Public Health 3 Core Functions
Public Health Surveillance
Public health surveillance (PHS): the systematic collection,
analysis, interpretation and dissemination of health-related data,

18. is the bedrock of public health practice.
This is because the surveillance systems capture and manage the
volumes of data and information necessary to support the three
core functions of public health.
The notion of PHS can be traced as far back as the Renaissance.
Public Health Surveillance Goals
Estimate significance of the problem
Determine distribution of illness
Outline natural history of a disease
Detect epidemics
Identify epidemiological and laboratory research needs
Evaluate programs and control measures
Detect changes in infectious diseases
Monitor changes in health practices and behaviors
Assess the quality and safety of health care, drugs, devices,
diagnostics and procedures
Support public health planning

19. Indicator-based surveillance refers to the monitoring of a
specific disease/health condition, or a class of diseases/health
conditions that are of interest to public health.
Event-based surveillance monitors data from specific events
where a large number of people gather in one place
PHS Types
Case
Syndromic
Sentinel
Behavioral
Integrated disease
Clinical outcomes
Types of Surveillance Systems

20. Case Surveillance Systems
Collect data on individual cases of a health event or disease
with previously determined case definitions in respect to
criteria for person, time, place, clinical & laboratory diagnosis
Analyze case counts and rates, trends over time and geographic
clustering patterns
Historically, case surveillance has been the focus of most public
health surveillance
The NEDSS Base System is an example of a case management
system
Syndromic Surveillance Systems
Collect data on clusters of symptoms and clinical features of an
undiagnosed disease or health event in near real time allowing
for early detection and rapid response mobilization
Data can be obtained through specific surveillance systems as
well as existing epidemiologic data such as insurance claims,
school and work absenteeism reports, over the counter (OTC)
medication sales, consumer driven health inquiries on the
Internet, mortality reports and animal illnesses or deaths for
syndromic surveillance
Geographic and temporal aberration and geographic clustering
analyses are performed with real-time syndromic surveillance
data
Syndromic surveillance systems can also be used to track
longitudinal data and monitor disease trends

21. Eight syndromes are monitored:
Botulism-like illnesses
Febrile (fever) illnesses (influenza-like illnesses)
Gastrointestinal (stomach) symptoms
Hemorrhagic (bleeding) illnesses
Neurological syndromes
Rash associated illnesses
Respiratory syndromes
Shock or coma
Syndromic Surveillance
Syndromic data is based on symptoms and not hard evidence
such as cultures. Experts try to predict epidemics and
bioterrorism based on this early data
Syndromic surveillance is part of Meaningful Use with the goal
of submitting reports to public health
ESSENCE is a syndromic surveillance system that is not real
time

22. RODS is similar and being used by a limited number of hospital
systems and approaches real time reporting
Distribute is an “influenza-like” syndrome surveillance system
Syndromic Surveillance
This is a CDC web-based program to improve disease detection,
monitoring and situational awareness for healthcare
organizations by reporting emergency room, pharmacy and
laboratory data. Participants include DOD, Veterans Affairs
and civilian hospitals
BioSense 2.0 allowed state and local health departments to
access data that would support syndromic surveillance systems
under meaningful use. A search engine can conduct a query by
syndrome, location and date
The goal is to provide a web based clearinghouse where data
can be stored, searched and analyzed from and by multiple
parties
Biosense

23. Sentinel Surveillance Systems
Collect and analyze data from designated agencies selected for
their geographic location, medical specialty, and ability to
accurately diagnose and report high quality data. They include
health facilities or laboratories in selected locations that report
all cases of a certain health event or disease to analyze trends in
the entire population
Pros: Useful to monitor and identify suspected health events or
diseases
Cons: Less reliable in assessing the magnitude of health events
on a national level as well as rare events since data collection is
limited to specific geographic locations
Behavioral Surveillance Systems
Collect data on health-risk behaviors, preventative health
behaviors, and health care access in relation to chronic disease
and injury
Analyze the prevalence of behaviors as well as the trends in the
prevalence of behaviors over time
Information is most commonly collected by personal interview
or examination
Inferential and descriptive analysis methods such as age
adjusted rates, linear regression, and weighted analyses are used
Most acute when conducted regularly, every 3 to 5 years

24. Integrated Disease Surveillance
and Response (IDSR)
Incorporates epidemiologic and laboratory data in systems
designed to monitor communicable diseases at all levels of the
public health jurisdiction, particularly in Africa
Useful for: detecting, registering and confirming individual
cases of disease; reporting, analysis, use, and feedback of data;
and preparing for and responding to epidemics
Clinical Outcomes Surveillance
Monitors clinical outcomes to study disease progression or
regression in a population
Analyzes the rates of and factors associated with clinical
outcomes using descriptive and inferential methods such as
incidence rates from probability samples

25. Laboratory Based Surveillance
Collects data from public health laboratories, which routinely
conduct tests for viruses, bacteria, and other pathogens
Used to detect and monitor infectious and food-borne diseases
based on standard methods for identifying and reporting the
genetic makeup of specific disease-causing agents
Commonly used in case surveillance and sentinel surveillance
Strategic vision for how informatics and information technology
should support the practice of public health
Everyone in a public health agency needs to know something
about informatics and information systems
Information systems should deliver value to the public health
agency by supporting the work done by its professional staff.
Public Health Informatics Core Elements

26. The CDC would like a robust interoperable web based system to
integrate all aspects of public health
This will require data standards, security measures and high
level funding to succeed
The PHIN Strategic Plan for 2011-2016 can be found on the
CDC web site
Public Health Information Network
The capability to electronically transmit immunization data to
immunization registries or immunization information systems
The capability to electronically transmit reportable lab results
The capability to electronically transmit syndromic surveillance
data from an EHR
The capability to report cancer cases to a state registry from a
certified EHR
The capability to report specific cases to a non-cancer state
registry from a certified EHR
Meaningful Use and Public Health

27. Health Information Exchange and Public Health Use Cases
Mandated reporting of lab diagnoses
Non-mandated reporting of lab data
Mandated reporting of physician-based diagnoses
Non-mandated reporting of clinical data:
Public health investigation
Clinical care in public health clinics
Population-level quality monitoring
Mass-casualty events
Disaster medical response
Public health alerting - patient level
Public health alerting - population level
Geographic Information Systems (GIS)
Epidemiologists often characterize data by place, time and
person
In 1855, Dr. John Snow created a simple map to show where
patients with cholera lived in London in relation to the drinking
water source in the Soho District of London

28. Modern GIS uses digitized maps from satellites or aerial
photography
A GIS is a system of hardware, software and data used for the
mapping and analysis of geographic data
GIS provides access to large volumes of data; the ability to
select, query, merge and spatially analyze data; and visually
display data through maps
Using GPS and mobile technology, field workers can enter
epidemiologic data to populate a GIS
Geographic Information Systems (GISs)
GIS Map

29. HealthMap
global avian influenza outbreaks
Partners in Information Access for the Public Health Workforce
Resource
County and Local Health Data
State Health Data
Individual State Data
National Health Data
Global Health Data
Statistical Reports
Demographic Data
Geographic Information Systems (GIS)
Training and Education
Health Information Technology and Standards
Tools for Data Collection and Planning
Public Health Data Tools and Statistics

30. The National Health Interview Survey (NHIS)
The National Health and Nutrition Examination Survey
(NHANES)
The National Survey of Family Growth (NSFG)
National Health Care Surveys
Project Tycho
Public Health Data Tools and Statistics
The Association of Schools of Public Health (ASPH) estimates
that the field of public health will require 250,000 more workers
by 2020 to avert a national public health crisis
University of Washington’s Center for Public Health
Informatics developed a list of informatics competencies for
public health workers to meet the needs of the evolving public
health field as well as for the Public Health Informatician
A Public Health Informatician is “a public health professional

31. who works in practice, research, or academia and whose
primary work function is to use informatics to improve
population health
PHI Workforce
All of the goals of the US Public Health system also pertain to
the international community
The World Health Organization represents world public health
with the following goals:
Foster health security
Promote health development
Strengthen health systems
Global Public Health Informatics
WHO Programs

32. Global Alert and Response (GAR): the integrated infectious
disease surveillance program within WHO
International Health Regulations
Early Warning Surveillance: surveillance mechanism to
effectively identify disease outbreaks and other health issues
immediately following acute emergencies
Global Public Health Intelligence Network: to electronically
monitor infectious disease outbreaks
Global Outbreak Alert and Response Network: provide a rapid
identification and response to outbreaks and alert the
international community
Systems need to integrate diseases that affect animals with
human data
Enhance the global response to outbreaks
Improve communication between health entities e.g. the Ebola
virus crisis
Better diagnostic tools for earlier detection
PHI Challenges

33. Public Health Informatics is an important part of Health
Informatics
Public Health reporting is part of Meaningful Use
Public Health surveillance is the backbone of public health to
detect and track epidemics, natural disasters and bioterrorism
Geographical Information Systems can provide maps with
important health data overlays
New public health programs will continue to evolve that will
require informaticists to analyze, disseminate and store data
Conclusions
Chapter 20: eResearch
John Sharp

34. Learning Objectives
After reviewing the presentation, viewers should be able to:
Describe the scope of eResearch and Clinical Research
Informatics within the clinical research workflow
Describe the use of EHR data in various phases of research
including research originating from EHR data
Conceptualize how informatics tools can be utilized in
recruiting subjects for clinical research
Detail how informatics supports the ongoing management of
clinical trials
Review the new trends in big data, real-time analytics and data
mining
Definition
eResearch: use of information technology to support research
In the past few years we have witnessed the shift from paper-
based research to almost completely electronic
Major contributing factors: adoption of electronic medical
records and electronic research platforms

35. There is no doubt that health informatics and specifically
eResearch will have a major impact on evidence based medicine
in the future
The new field to study eResearch is Clinical Research
Informatics
Preparatory to Research
Electronic retrieval of information:
PubMed
National Library of Medicine
Google Scholar
Google Books
ClinicalTrials.gov (WHO for international)
Research collaboration networks have seen significant growth in
recent years. Research networks are typically web-based
applications which include features such as a personal profile,
opportunities to connect with others with similar interests and
the ability to post status updates

36. Preparatory to Research
Research Collaborative Networks Tools
Vivo: An open source tool developed at Cornell University
Harvard Profiles Catalyst: An open source community of over
130 member institutions with built-in network analysis and data
visualization tool
SciVal Experts: Commercial solution to find research funding
and measure benchmarks
EHR Recruiting: ability to evaluate adequate pools of patients
to be recruited into the study. This requires a clinical data
repository from EHR data with a query tool to search de-
identified clinical information. By modifying inclusion and
exclusion criteria, a researcher can find the appropriate cohort
for recruitment based on a reasonable recruitment rate
Electronic grant process: researchers can search for grant
opportunities and grant submission is now common for
government and civilian agencies
Preparatory to Research

37. Study Initiation
Volunteer recruitment on the Internet
ResearchMatch: matches patients seeking clinical trials and
researchers seeking volunteers
TrialX: permits volunteer to search clinical trials from
ClinicalTrials.gov
Social network: example, ArmyOfWomen
EHR can be used to find cohorts of eligible patients and create
patient contact lists (alerts) for recruitment. Clinical trial alerts
can be embedded within EHR based on diagnoses, lab tests or
other patient characteristics. Alert would typically remind
provider that patient may be eligible for a clinical trial and who
to contact
ResearchMatch Program

38. Study Management
and Data Management
Clinical trial management systems (CTMS)
Manage the planning, preparation, performance, and reporting
of clinical trials
Budget management, study calendar of patient visits, and
creating electronic case report forms (eCRFs)
Examples of CTMSs
Research Electronic Data Capture (REDCap) by Vanderbilt
OpenClinica
REDCap Program

39. EHRs and Clinical Trials
Integration is rarely available within commercial EHRs
Data from EHRs can be exported and then imported into study
data management systems
Design a variety of study types: epidemiologic research
Identification of risk factors
Comparative effectiveness research
Challenges with EHR Data
Data that is not routinely collected in EHRs can be collected
with “smart forms”
Collection of research data using medical devices (e.g. EKG).
Many organizations are integrating device data with EHRs
Patient Reported Outcomes (PROs): is the term used to denote
health data that is provided by the patient through a system of
reporting. This data might be collected with a tablet and
inputted into the EHR

40. Data Management Systems
for FDA Regulated Studies
Regulation 21 CFR Part 11
Selecting a system compatible with regulatory requirements
Significant validation tests must be developed and executed
Commercial programs may assist: PhaseForward and Oracle
Clinical
Open source programs such as OpenClinica can help
Interfaces and Query Tools
Clinical data repositories to support research are commonplace
and based on EHR data:
i2b2: Informatics for Integrating Biology and the Bedside
TrialViz (UK)
STRIDE (Stanford University)
Challenges: gain regular access to source clinical systems and
preservation of semantics across systems during aggregation
process
Natural language processing of unstructured EHR data is
critical

41. Health Information Organizations are also a rich resource for
research
Big data means big research tools such as Hadoop. The Apache
Hadoop software library “is a framework that allows for the
distributed processing of large data sets across clusters of
computers using a simple programming model”
Research can come from voluminous image data
Research can also arise from genomic information integrated
with EHR data
Interfaces and Query Tools
Data Analysis
With tools like The R Project for Statistical Computing, an open
source statistical package, there is the potential for integration
of the statistical package with the data repository
REDCap provides access to their API (Application
Programming Interface) to connect directly to statistical
programs. SAS also provides for integration of patient data
from a variety of sources with tools for data cleaning,
standardization and exploration
Data visualization is a new and evolving field to assist research
Real time analytics is the provision of analyzed data relatively

42. instantly to support decision making. IBM’s Watson is the best
example we have today
eResearch has become an almost paperless process
There is a need for Clinical Research Informaticists
EHR data is the largest source of research data today
There are obstacles in using all EHR data for research because
much of it is unstructured
Informatics tools can be used for patient recruiting and
management of research
Big data is the results of EHRs, imaging and genomics so that
researchers must have tools to analyze these huge data sets
Conclusions
Chapter 18: Bioinformatics
Robert E. Hoyt MD
William R. Hersh

43. Indra Neil Sarkar MD
Learning Objectives
After viewing the presentation, viewers should be able to:
Define bioinformatics, translational bioinformatics and other
bioinformatics-related terms
State the importance of bioinformatics in future medical
treatments and prevention
Describe the Human Genome Project and its important
implications
List major private and governmental bioinformatics initiatives
List several bioinformatics projects that involve EHRs
Describe the application of bioinformatics in genetic profiling
of individuals and large populations

44. Definitions
Bioinformatics = Computational Biology or the field of science
in which biology, computer science and information technology
merge to form a single discipline
Bioinformatics makes use of fundamental aspects of computer
science (such as databases and artificial intelligence) to develop
algorithms for facilitating the development and testing of
biological hypotheses
Finding genes of various organisms
Predicting structure or function of newly developed proteins
Developing protein models and examining evolutionary
relationships
Transformational Bioinformatics: Simply put, is the
specialization of bioinformatics for human health
Genomics is the field that analyzes genetic material from a
species
Proteomics is the study at the level of proteins (e.g., through
gene expression)
Pharmacogenomics is the study of genetic material in
relationship with drug targets
Metabolomics is the study of genes, proteins or metabolites

45. Definitions
Biologists
collect molecular data:
DNA & Protein sequences,
gene expression, etc.
Computer scientists
(+Mathematicians, Statisticians, etc.)
Develop tools, softwares, algorithms
to store and analyze the data.
Bioinformaticians
Study biological questions by analyzing molecular data
The field of science in which biology, computer science and
information technology merge into a single discipline

46. 5
Translational Bioinformatics
Metagenomics is the analysis of genetic material derived from
complete microbial communities harvested from natural
environments
A phenotype is the observable characteristic, structure, function
and behavior of a living organism. Size and hair color could be
examples. Phenotype is strongly guided by the genotype. The
Phenome refers to total phenotypic traits
Genotype is based on the raw genetic information that is
associated with a phenotype or regulation of biological
function. The genome is the total of genotypic traits
Definitions

47. The human body has about 100 trillion cells and each one
contains a complete set of genetic information (chromosomes)
in the nucleus; exceptions are eggs, sperm and red blood cells
Humans have a pair of 23 chromosomes in each cell that
includes an X and Y chromosome for males and two Xs for
females
Offspring inherit one pair from each parent
Chromosomes are listed approximately by size with
chromosome 1 being the largest and chromosome 23 the
smallest
Genomic Primer
Chromosomes consist of double twisted helices of
deoxyribonucleic acid (DNA)
DNA is composed of four sugar-based building blocks
(“nucleotides”: adenine [A], thymine [T], cytosine [C], and
guanine [G]) that are generally found in pairs (“Watson-Crick”
pairing: A-T, C-G)
An organism’s DNA encodes its full complement of proteins

48. essential for cellular function
Genes are regions on chromosomes that encode instructions,
which may result in proteins that then enable biological
functions
Genomic Primer
The process of decoding genes involves transcribing the DNA
into ribonucleic acid (RNA) and then translation into amino
acids that form the building blocks for proteins
Collectively, the complete set of genes is referred to as a
“genome” (combination of “gene” and “chromosome”)
It is estimated that humans have between 20,000 and 30,000
genes and genomes are about 99.9% the same between
individuals
Variations in genomes between individuals are known as single
nucleotide polymorphisms (SNPs) (pronounced “snips”)
Genomic Primer

49. Genome-wide associations studies (GWASs) are being
conducted where two groups of participants are studied; those
with a disease of interest, compared with those without the
disease. The variations or SNPs discovered are said to be
associated with the disease, but true cause and effect is often
unclear
Similarly, phenome-wide association studies (PheWAS) are
being carried out comparing genes to disease associations, most
recently using the electronic health record for phenotypical
information
Genomic Primer
Genes
Importance of Bioinformatics
Diagnosing hereditary diseases

50. Discovering future drugs targets
Developing personalized drugs based on genetic profiles
(personalized medicine)
Developing gene therapies to treat diseases with a strong
genomic component (e.g. cancer)
Discover:
New indications for an old drug (drug repurposing)
New targets for existing drugs (e.g., treatment of tongue cancer
using RET inhibitors)
Drugs to work better in certain patient groups (gender, age,
race, ethnicity, etc.) with possible genetic variants
What drugs to avoid due to higher incidence of side effects that
are genetically modulated
Improve clinical decision support for electronic health records
Importance of Pharmacogenomics
The Human Genome Project

51. International collaborative project started in 1990 and finished
in 2003
3 million SNPs discovered
Ethical, legal and social issues also discussed
Huge relational databases are necessary to store and retrieve
this massive information
New technologies such as DNA arrays (gene chips) speed up
analysis
Significant drop in cost along the way
Other Projects
National Human Genome Research Institute (NHGRI)
Encyclopedia of DNA Elements (ENCODE) Project
Human Microbiome Project (HMP)
Humans have more bacteria on and in their body than cells =
microbiome
Project will determine whether individuals share a core human
microbiome and try to understand whether changes in the human
microbiome can be correlated with changes in human health
Studies are already suggesting the intestinal bacteria function
like a new organ system

52. Other Projects
Human Variome Project
The PhenX Project
1000 Genomes Project
Pediatric Cancer Genome Project
National Center for Biotechnology Information (NCBI)
Hosts thousands of databases associated with biomedicine,
Including MEDLINE and GenBank databases
The NCBI provides access to sequences from over 285,000
organisms
Others noted in the textbook
Personal Genomics
The goal is to have “tailor made” medications and treatments
that target the individual and not a group having little in
common with the patient
Also to offer bio-surveillance for future outbreaks of infectious
diseases
All of Us Project will collect biological data to further precision
or personalized medicine

53. Cost of Human Genome Determination Decreasing
Personal Genetics Testing
Available commercially without a doctor’s order:
Often less than $100
DNA Direct
AncestryDNA
23andMe
Myriad™ specializes in cancer-genetic links but they found they
could not patent BRAC gene testing

54. Ethical Questions Related to Genetic Testing
Testing is not regulated, lacks external standards for accuracy,
has not demonstrated economic viability or clinical benefits and
has the potential to mislead customers, according to Varmus
Patients must be sure of accuracy before undergoing e.g. a
prophylactic mastectomy
Patients will need genetic counseling as most physicians have
not had this training
Genetic Information Nondiscrimination Act of 2008 protects
patients against discrimination by employers and healthcare
insurers based on genetic information
Genomic Information Integrated with Electronic Health Records
Genetic profiles will likely be part of many electronic health
records in the future
Cost will become less of a factor but adding the genetic
information will raise multiple other questions and data storage
must be increased due to large data files
The Electronic Medical Records and Genomics (eMERGE)
Network is a consortium of nine healthcare organizations with
significant investments in both EHR and genomic analytics
across the United States that have already started the process

55. In order for EHRs to incorporate genomic data:
They must store data in structured format
Data must be standards based
Phenotypic information must also be stored as structured data
Data must be available for use by rules engines
EHRs must be able to display information needed by the
clinician based on phenotypic and genotypic data
SNOMED CT will be modified to incorporate genomic data
Data standards and clinical decision support will need to be
enhanced
Genomic Information Integrated with Electronic Health Records
Digital family histories are now a reality with pervasive EHRs
and meaningful use
It will likely be at least a decade before we can intelligently
integrate genomic information into EHRs, so in the mean time
we can expect some use of the family history to alert clinicians
of genetic risk of e.g. cancer
The US government is interested in better family history

56. integration and hence their creation of the web site My Family
Health Portrait
Digital Family Histories
Translational bioinformatics will blend traditional
bioinformatics with health informatics
We are experiencing huge advances in bioinformatics but we are
still a ways off in terms of incorporating this information into
the average medical practice
It is logical that eventually genomic information will be part of
every EHR; in the meantime we will use family histories
Direct to consumer genomic testing is very interesting but not
always evidence based
Conclusions