Relating to your current or future career in healthcare, how will Telemedicine be paramount in caring for your patients?
my career is respiratory therapy
Chapter 18: Bioinformatics
Robert E. Hoyt MD
William R. Hersh
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
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
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
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
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 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
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
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
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
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
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
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
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 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
Chapter 20: eResearch
John Sharp
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
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
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
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
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
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
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
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 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 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
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
Electronic Telemedicine Modes
Radio Doctor—predicted in 1924
TV
Telephone
Internet
Telemedicine Communication Modes
Communication Mode Pros Cons
Patient-Portal
Secure messaging Asynchronous. Able to attach photos. Response can be formatted with
template. Could use VoIP. Audit trail is available Not as personal as live visit. Usually not connected to EHR or other enterprise information but may be in
the future
Telephone Widely available, simple and inexpensive. Real-time Not asynchronous. Unstructured.
No audit trail. Only real-time
Audio-Video Maximal input to clinician. Can include review of x-rays, etc. Perhaps more personal than just messaging Currently, 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
(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
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 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 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
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
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
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
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
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
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
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.
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 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, 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
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
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
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
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
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
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
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
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
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
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
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
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 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
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
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