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Informatics

Editor: Dac Teoli Updated: 9/4/2023 6:15:29 PM

Definition/Introduction

Health informatics is the interprofessional field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem-solving, decision making, motivated by efforts to improve human health. In other words, it is the science of information where the information is defined as data with meaning.

For the healthcare practitioner, the subspecialty of clinical informatics is most relevant. Clinical Informatics is an interprofessional practice that blends medical practice with information technologies and behavioral management principles. Rather than a rigid academic or technical pursuit, clinical informatics is a practical discipline that improves patient outcomes, advances medical research, and increases the value of healthcare delivery. The key to these goals is the understanding that the successful evolution of health care is determined not by technical capability, but by how effectively the technology is designed and integrated into existing cultures, regulatory frameworks, and institutional workflows.

Though clinical informatics has been practiced since the 1950s, it was not until the internet era that the discipline began achieving widespread consideration and application outside academics. In the United States, clinical informatics was driven further into the spotlight as new federal laws (see below) strongly incentivized the adoption of new healthcare information technology systems, citing these systems as solutions to the nation’s soaring health care costs and chronic disease rates.[1][2][3]

Issues of Concern

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Issues of Concern

Applications

As a practical discipline, clinical informatics has far-reaching applications within the healthcare framework—individual physicians, multi-center hospital systems, medical insurance firms, government agencies, medical device developers and more are all potential beneficiaries.  Examples include:  

Electronic Health Record (EHR): Perhaps the most publicly high-profile application of clinical informatics is the universal adoption of the EHR. The Affordable Care Act of 2009 (see below) mandated that all healthcare institutions transition from paper to exclusively digital medical record system. Since it must record every patient encounter, medication ordered, and laboratory test performed, the EHR impacts every aspect of a healthcare institution’s operations. Subsequent EHR adoption achieved varied results. Successful institutions integrated the new EHR systems with existing institutional culture and workflows with minimal disruption to or even improved delivery of healthcare services. Other institutions with less effective or absent clinical informatics support saw worsened employee morale, decreased operational effectiveness, and compromised patient safety. 

Predictive Medicine: One of the most promising potential applications of clinical informatics is the development of predictive medicine. Predictive medicine is the science of accurately risk-stratifying an individual for developing the disease within a specified time-frame. While predictive capabilities traditionally revolved around genetics (e.g. karyotype testing for Down Syndrome, BRCA gene testing for breast cancer), clinical informatics has helped to usher in a new era of predictive medicine based on so-called Big Data, huge quantities of data obtained from a variety of disparate sources in real-time. Predictive tools based on big data has the potential to help clinicians better predict who will get sick when and how best to intervene before the patient becomes sick. Though healthcare has yet to develop its own predictive tools, Target Corporation, a major retailer, has already developed a big-data informatics system that predicts when a customer is pregnant; the company subsequently tailors its marketing efforts towards those customers accordingly.

Epidemic Tracking: Not limited to healthcare data, clinical informaticists can assist in capturing and transforming any data source into usable information. In 2014, public health specialists published a report demonstrating how they could track and predict HIV outbreaks based on real-time data captured from the social media platform, Twitter. Prior research demonstrated how Twitter could also be used to predict outbreaks of influenza. With the measles and Ebola crises of 2015, other groups are now attempting to apply clinical informatics principles to capture non-traditional streams of data and create systems of predicting and preventing the next epidemics.  

Legislation

Executive Order 13335 (2004), also known as the Incentives for the Use of Health Information Technology and Establishing the Position of the National Health Information Technology Coordinator, created the Office of the National Coordinator of Health Information Technology (ONC). While this did not directly affect clinical informatics or healthcare at large, it was the United States Federal Government’s first step in creating a nationwide health information exchange, a foundational system for collecting and exchanging data across hospitals, regions, and states. To date, a national healthcare information exchange nor standards for creating one has not yet been established.  

American Recovery and Reinvestment Act (AARA or Recovery Act) of 2009 was signed into law by President Obama. Aiming to stimulate the ailing economy that had been plagued by the Great Recession between 2007 and 2009, the total sum of the stimulus package was $787 billion.[4] The ARRA authorized hundreds of billions of dollars that were to be used for new health and healthcare spending. These monetary funds were to be used as discretionary appropriations and mandatory spending that should promote the adoption of electronic health records.[5] The American Recovery & Reinvestment Act of 2009 (ARRA, or Recovery Act), established the Health Information Technology for Economic Clinical Health Act (HITECH Act), which requires CMS to provide incentive payments under Medicare and Medicaid to “Meaningful Users” of Electronic Health Records. The HITECH Act catalyzed industry adoption of clinical informatics with the goal of “Improving Health Care Quality, Safety, and Efficiency.” Through a system of payments and penalties, the HITECH Act strongly incentivized not only adopting the EHR but also achieving “Meaningful Use,” a set of requirements that demonstrate effective integration and use of the EHR within the healthcare institution. The HITECH Act further strengthened patient information privacy standards for the new era of digitized and highly transferable information.   

Under the AARA, among other institutions, the National Institutes of Health (NIH) received a $10.4 billion allocation in order to support scientific research priorities, update buildings and facilities, conduct extramural construction, repairs, and alterations, and conduct comparative effectiveness research. The two largest categories of spending involved allocating grants to researchers and investigators who had submitted applications to the NIH and investigators who previously submitted research proposals. The funds allocated to investigators who had previously submitted research proposals were meant to cover projects that were highly creditable but missed the pay-line. Additionally, The National Heart, Lung, and Blood Institute also received an allocation of $763 million.[4]

Governing and Professional Institutions 

International Medical Informatics Association (IMIA): Founded in 1987, IMIA is the foremost international coordinating body for the promotion and development of medically-related informatics interests including biomedical informatics and clinical informatics. It serves as the hub that coordinates the efforts and goals of regional subsidiary institutions worldwide.

American Medical Informatics Association (AMIA): AMIA is the United States affiliate institution of its IMIA parent organization. Though officially the United States representative organization, AMIA is composed of thousands of members from over 40 countries worldwide. AMIA’s goal, like IMIA’s, is to promote and develop the role of informatics in improving patient care, healthcare operations, and biomedical research. 

American Board of Medical Specialties (ABMS): The ABMS is the certifying body regulating and overseeing all physicians and physician specialists, including physician clinical informaticists. In 2011, ABMS officially recognized clinical informatics as a subspecialty of medicine and began offering board certification to qualifying physicians in 2013 through the American Board of Preventative Medicine.

Other Informatics Subspecialties:

  • Translational Bioinformatics
  • Imaging Informatics
  • Public Health Informatics

Ontology:

  • A framework for representing knowledge (e.g., SNOMED CT).

Taxonomy:

Is the practice and science of classification. It adds structure to the information to make it easy to search and filter.

The core concern of an informatician is transforming data into information into knowledge.

  • Data (Pleural datum): observations (characters, symbols, signs) that may or may not be meaningful.
  • Information: data that has meaning or facts from which conclusion can be drawn. Data has a structure or relationship.
  • Knowledge: information believed to be justifiably true. Processed information for a purpose.
  • Wisdom: Knowledge over time

Informatics Fields

A number of highly subspecialized areas of informatics have developed.  Some examples include the following:

  • Internet Informatics: The study of technologies behind internet-based information systems and skills needed to map problems to deployable internet-based solutions.
  • Data Mining & Information Analysis: Integrates the collection, analysis, and visualization of complex data and its critical role in research, business, and government.
  • Life Science Informatics: Examines artificial information systems, which help scientists make great progress in identifying core components of organisms and ecosystems.
  • Social Computing: Studies social interaction and developing systems that act as introducers, recommenders, coordinators, and record-keepers.
  • Human-Computer Interaction: Informatics that studies how design and development work impacts users.
  • Information Architecture: Information architecture studies the development of successful Web sites, software, intranets, and online communities. Architects structure the information and its presentation in a logical and intuitive way so that information can be successfully used.
  • Information Assurance and Cybersecurity: The practice of creating and managing safe and secure systems. It is crucial for organizations public and private, large and small. Organizational informatics:
  • Organizational informatics is fundamentally interested in the application of information, information systems and information and communications technology within organizations of various forms including the private sector, public sector, and voluntary sector organizations. [6][7][8][9]

Clinical Significance

Informatics involves the practice of information processing and the engineering of information systems. The field considers the interaction between humans and information. Informatics has a social impact on information technologies.

Medical informatics can be an important tool to control and address public health concerns using an interprofessional team of physicians, nurses, pharmacists, and public health workers. Some examples include patients missing immunizations or tracking the proper use of controlled substances. The future of medical informatics is promising and many healthcare professionals should have a background in informatics. (Level V)[10]

References


[1]

Padula WV, Blackshaw L, Brindle CT, Volchenboum SL. An Approach to Acquiring, Normalizing, and Managing EHR Data From a Clinical Data Repository for Studying Pressure Ulcer Outcomes. Journal of wound, ostomy, and continence nursing : official publication of The Wound, Ostomy and Continence Nurses Society. 2016 Jan-Feb:43(1):39-45. doi: 10.1097/WON.0000000000000185. Epub     [PubMed PMID: 26727681]


[2]

Gertych A, Pietka E. Foreword to the special issue on Information Technologies in Biomedicine. Computers in biology and medicine. 2016 Feb 1:69():234-5. doi: 10.1016/j.compbiomed.2015.12.005. Epub 2015 Dec 15     [PubMed PMID: 26726075]


[3]

Romagnoli KM, Boyce RD, Empey PE, Adams S, Hochheiser H. Bringing clinical pharmacogenomics information to pharmacists: A qualitative study of information needs and resource requirements. International journal of medical informatics. 2016 Feb:86():54-61. doi: 10.1016/j.ijmedinf.2015.11.015. Epub 2015 Nov 30     [PubMed PMID: 26725696]

Level 2 (mid-level) evidence

[4]

Lauer MS. National Heart, Lung, and Blood Institute and the American Recovery and Reinvestment Act of 2009: 1 year later. Journal of the American College of Cardiology. 2010 Jul 13:56(3):234-6. doi: 10.1016/j.jacc.2010.03.042. Epub     [PubMed PMID: 20620744]


[5]

Goldstein MM. The health privacy provisions in the American Recovery and Reinvestment Act of 2009: implications for public health policy and practice. Public health reports (Washington, D.C. : 1974). 2010 Mar-Apr:125(2):343-9     [PubMed PMID: 20297763]


[6]

Smith S, Kogan JR, Berman NB, Dell MS, Brock DM, Robins LS. The Development and Preliminary Validation of a Rubric to Assess Medical Students' Written Summary Statements in Virtual Patient Cases. Academic medicine : journal of the Association of American Medical Colleges. 2016 Jan:91(1):94-100. doi: 10.1097/ACM.0000000000000800. Epub     [PubMed PMID: 26726864]

Level 3 (low-level) evidence

[7]

Jha AK, Burke MF, DesRoches C, Joshi MS, Kralovec PD, Campbell EG, Buntin MB. Progress toward meaningful use: hospitals' adoption of electronic health records. The American journal of managed care. 2011 Dec:17(12 Spec No.):SP117-24     [PubMed PMID: 22216770]


[8]

Mennemeyer ST, Menachemi N, Rahurkar S, Ford EW. Impact of the HITECH Act on physicians' adoption of electronic health records. Journal of the American Medical Informatics Association : JAMIA. 2016 Mar:23(2):375-9. doi: 10.1093/jamia/ocv103. Epub 2015 Jul 30     [PubMed PMID: 26228764]


[9]

Young SD, Rivers C, Lewis B. Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes. Preventive medicine. 2014 Jun:63():112-5. doi: 10.1016/j.ypmed.2014.01.024. Epub 2014 Feb 8     [PubMed PMID: 24513169]


[10]

Nagar R, Yuan Q, Freifeld CC, Santillana M, Nojima A, Chunara R, Brownstein JS. A case study of the New York City 2012-2013 influenza season with daily geocoded Twitter data from temporal and spatiotemporal perspectives. Journal of medical Internet research. 2014 Oct 20:16(10):e236. doi: 10.2196/jmir.3416. Epub 2014 Oct 20     [PubMed PMID: 25331122]

Level 2 (mid-level) evidence