One thing to consider when planning for health information exchange is the needs of the patient and how they will benefit from the technology. Since HIE aims to connect providers and public health agencies in orders to share and aggregate patient data so information is easily accessible at multiple points of care, it is easy to see how it can improve patient outcomes. However, when looking at direct use cases by the patient we can look to personal health records, or PHRs, to see how patient needs can be met with health information exchange. PHRs are an “Internet-based set of tools that allow people to access and coordinate their life-long health information and make appropriate parts of it available to those who need it” (Braunstein, 2014, p. 169). These tools include technologies that allow patients to do tasks such as access test results, track immunizations, and send information to new providers. HIE helps these tools function by exchanging information from the providers to the patient. Access to this information on the patient level gives patients more control over their own health care and it helps them coordinate care when the patient has multiple providers that are in different locations.

Connecting patients with points of care through HIE and PHR is important because it allows them to have easier access to the providers, lab and imaging results, and appointment scheduling. According to one study that looked at consumers’ attitudes toward personal use of HIE, the interest in personal use of HIE was higher among those “who believed their healthcare providers communication with each other was suboptimal” and “who believed that using personal HIE would improve their communication with their physicians” (O’Donnell, 2011). Increasing patient access to their own health information and improving their access to their providers will allow patients to make more informed decisions about their own healthcare.

One of the largest concerns with utilization of PHR and HIE is security and protection of patient data. One way to address this concern is to create an opt-in approach to health technologies where the patient first must consent to having their data uploaded to the HIE from the physician’s EHR. While this does help address patient concerns of who can see their data, there are still concerns of what data is shared and used. According to one article, “the more such information is made available to authorized users of the system, the more patients feel concerned about privacy” (Tripathi, 2009). This is important because the less a provider decides to share, the more comfortable a patient might be to opt-in, but it also means that there is less detailed information in the HIE for use. Finding a balance between the type of information that is being shared, how much information is shared, and who can access the information is necessary to maximize the number of patients that utilize the HIE while also having the highest quality of information.

One type of technology that is already in use is the patient portal. A patient portal is a web-based application that “facilitates communication between patients and their health providers” (Braunstein, 2014, p. 179). These portals allow patients to send and receive secure messages from their providers, make appointments, and view test results. One quality of patient portals that limits their uses for HIE is that normally patients cannot input their own clinical data into the portal. For this reason, the implementation of technology that would allow patients to also upload their own clinical data, such as heart rate or blood pressure, would improve on the patient’s impact on HIE data. This could be done through the integration of wearable health devices that track patient vitals to the patient’s portal so they can upload recent health data for use by their physician.

Privacy and data protection is not just a patient concern, but also a valid legal and ethical concern. When developing HIE and patient access applications, developers need to consider The Health Insurance Portability and Accountability Act. HIPAA is an important piece of legislation because it lays out the framework for protections in patient health information. In order for HIE to ethically and legally provide services, they must make sure that patient information takes top priority since the Privacy Rule of HIPAA places limits on who can view and access health information.

As the demand for exchange of information grows with a heavily computerized health care system, the future of HIE depends on the resources that are given to it. In an idealized future, HIE infrastructures will grow nationally to the point where information that originated from one hospital can easily be shared electronically with another point of care anywhere in the country without the need for health professionals to fax information. Patients would be able to access their own health records from multiple clinics and hospitals with ease so they can make informed decisions about the coordination of the care. HIE could also be used to improve public health coordination, especially in situations like a pandemic where patient data about symptoms and disease diagnosis would allow researchers to have accurate and up to date information to formulate public health guidelines. Unfortunately, HIE is still facing an uphill battle. One study notes that “For the first time since our survey began in 2006, we observed a decrease in the number of operational HIE efforts and a much larger decline in the number of efforts in the planning stage” (Adler-Milstein, 2016). This is due to a lack of national funding and inability to secure participants. In order to continue to promote health information exchange efforts, federal and state funding needs to be secured.

One of the biggest governmental motivators for HIE is the Office of the National Coordinator. In fact, for the ONC a “near-term goal is to ensure the widespread adoption and use of directed, electronic information sharing that allows providers and patients to securely send and receive information for coordinated, seamless care and to meet meaningful-use requirements” (Williams, 2012). The ONC has been creating and implementing policies that promote the growth and use of technologies that facilitate the electronic exchange of information. This has included improving interoperability by promoting standards that make information exchange easier, such as the Direct protocol which provides “a simple, secure, standardized way to send encrypted health information to trusted recipients over the Internet, enabling providers to meet meaningful-use exchange requirements” (Williams, 2012).

In this final concept map, HIE is mapped based on the input sources, the output services, the structure of the HIE, and the core consideration of patient privacy. The top half of the concept map is concerned with the flow of information, with the HIE being the intermediary that is used to facilitate the movement of data. The bottom half of the map includes a breakdown of the HIE architecture and key considerations that are needed when building the HIE, which includes not only how the information is stored and transmitted, but also how it will maintain its integrity with data protection. This map does not include background information, such as how the ONC has influenced the growths of HIE and the importance of interoperability with EHR systems. This is because while these factors help the HIE get started, they do not have as much influence on the structure of HIE in terms of what data it takes in, who the data is for, and how the data is organized and transmitted.

References

Adler-Milstein, J., Lin, S. C., & Jha, A. K. (2016). The Number Of Health Information Exchange Efforts Is Declining, Leaving The Viability Of Broad Clinical Data Exchange Uncertain. Health Affairs, 35(7), 1278-1285. doi:10.1377/hlthaff.2015.1439

Braunstein, M. L. (2014). Contemporary health informatics. Chicago, IL: AHIMA Press.

O’Donnell, H. C., Patel, V., Kern, L. M., Barrón, Y., Teixeira, P., Dhopeshwarkar, R., & Kaushal, R. (2011). Healthcare Consumers’ Attitudes Towards Physician and Personal Use of Health Information Exchange. Journal of General Internal Medicine, 26(9), 1019-1026. doi:10.1007/s11606-011-1733-6

Tripathi, M., Delano, D., Lund, B., & Rudolph, L. (2009). Engaging Patients For Health Information Exchange. Health Affairs, 28(2), 435-443. doi:10.1377/hlthaff.28.2.435

Williams, C., Mostashari, F., Mertz, K., Hogin, E., & Atwal, P. (2012). From The Office Of The National Coordinator: The Strategy For Advancing The Exchange Of Health Information. Health Affairs, 31(3), 527-536. doi:10.1377/hlthaff.2011.1314

One group’s workflow that would be important to consider while designing and implementing a health information exchange would be physicians. Since many of the users of HIE systems that are being developed are clinicians, their workflow and processes would be very important when designing and implementing health information exchanges. With the introduction of new technology, architects need to understand how the technology changes workflow for the users. One example of this is a study that was conducted to understand how HIE implementation changed workflow for multiple practice sites and emergency departments. In this study, they examined both the nurse workflows and the provider workflows. According to the article, “Nurses’ exchange use was highly focused on recent hospital visits and they rarely browsed medical history” while “Nurse practitioners and physicians accessed the exchange for a wider range of reasons than nurses” (Unertl, Johnson, & Lorenzi, 2011). They found that because nurses preferred summaries over raw data, “nurse access to the exchange was often frustrated by summary data unavailability” (Unertl et al., 2011). This is different from physicians, where they “accessed a broader scope of information and browsed more of a patient’s medical history” (Unertl et al., 2011). Knowing the uses of the HIE, the engineers behind the systems would be able to adjust the user experience and offer features that would help users complete their tasks efficiently. In this example, offering summary services to nurses would improve the HIE.

When considering implementing solutions, looking at previous uses is important because it allows for recognition of the failures of these systems and where improvement needs to be made. In another study that evaluated the use of HIE in emergency departments, where researchers found that “the most frequent health information exchange use was for diagnostics, discharge summaries, histories, and physicals” but this usage varied as not all providers used it frequently (Thorn, Carter, & Bailey, 2014). In the article, it is noted that the “core barrier to higher usage is difficulty accessing health information exchange” (Thorn et al., 2014). The providers “ wanted consistent data so that they knew what information was available, reports would be easy to find, and needed information was available” (Thorn et al., 2014).  In this case, designers of the HIE would have to evaluate the user’s responses to find ways to increase usability and improve workflow. For new implementations of HIE, architects need to be sure that they consider the use cases and workflows of the providers so that during implementation the users find the tools helpful. Additionally, during implementation there should be consistent improvement in the HIE to adjust the system to complement the workflow of the providers. This is in line with some of the AHRQ Health IT tools for workflow. When considering the AHRQ Health IT tools for workflow, one of the tools is to assess and adjust workflows. This can be done during the implementation phase and it allows for improvement to the system to ensure that usage rises by making sure the intervention is more beneficial than a burden.

Human factors is “the discipline that tries to optimize the relationship between technology and the human” (Meyer, 2010). To be more precise, human factors “ applies knowledge about human strengths and limitations to the design of interactive systems of people, equipment, and their environment to ensure their effectiveness, safety, and ease of use” (Henricksen et al).  In order to optimize this relationship, usability of the technology is extremely important. This can be done through a user-centered design process, which is “a set of methods to address user needs throughout the product life cycle” (Meyer, 2010). Using human factors and user-centered design will improve the usability and usefulness of technology.

In one area that physicians and nurses get frustrated with health technology is burnout and “click fatigue.” The issues of “click fatigue” comes in when providers spend more time interacting with technology and screens than they do patients. As providers spend less time completing tasks on screens and use less clicks to get the information they need, the more time they have to tackle patient centered tasks. This is important because “70% of doctors using EHRs attribute the bulk of their administrative burden to the software” (Collier, 2018). When the software is optimized for the workflows of the practice, time is saved. This is a human factors issue because the designers of the software must consider the workflows of the users to increase usability and efficiency. Another important factor to note is that researchers have found that “the quality of documentation by medical residents decreased as the number of dialog boxes they had to open to record information increased” (Collier, 2018). Optimizing the software to fit with the workflow of the users without making it overly complicated is important to ensure efficiency and quality.

In terms of health information exchange, this is important because designers of the systems must be able to identify multiple use cases and then tailor the experience to those users. For example, the use of the health information exchange in the emergency department would differ from the use of a pharmacist trying to reconcile a patient’s medication. While the HIE system would be the same, the interface for each user would have to be different depending on their needs. This is where human factors comes in, where architects need to consider the human element, or how the user’s workflow functions, during the design and implementation process.

References

Beth, M. (2016, June 16). Introduction to Human Factors and Usability in Health IT Design. Retrieved October 28, 2020, from http://www.himss.org/News/NewsDetail.aspx?ItemNumber=6088

Collier, R. (2018). Rethinking EHR interfaces to reduce click fatigue and physician burnout. Canadian Medical Association Journal, 190(33). doi:10.1503/cmaj.109-5644

Henricksen et al. Chapter 5. Understanding Adverse Events: A Human Factors Framework

Thorn, S. A., Carter, M. A., & Bailey, J. E. (2014). Emergency Physicians’ Perspectives on Their Use of Health Information Exchange. Annals of Emergency Medicine, 63(3), 329-337. doi:10.1016/j.annemergmed.2013.09.024

Unertl, K. M., Johnson, K. B., & Lorenzi, N. M. (2011). Health information exchange technology on the front lines of healthcare: Workflow factors and patterns of use. Journal of the American Medical Informatics Association, 19(3), 392-400. doi:10.1136/amiajnl-2011-000432

Health information exchange, or HIE, is an important component of health informatics because it helps with the transmission of health data between multiple points of care. HIE efforts work to bring “ information about the patient—regardless of where care or services have been delivered— to the clinician and the care team to enable well-informed, coordinated, patient-centered care” (Health Policy Brief). These systems are intended to allow clinicians to access a patient’s health history regardless of where the patient has previously received care. Additionally, these systems can be beneficial to public health organizations, with them playing “a critical role in many other strategies designed to improve the health of populations, including clinical research, assessing the effectiveness of various treatments, monitoring the safety of medical products, and detecting and responding to health threats” (Health Policy Brief). HIE can provide patient level information that may be beneficial on the population level and can allow public health professionals tools to mitigate disease through surveillance and contact tracing.

Public health is a broad discipline that is tasked with protecting the health of entire populations. This is done through implementing educational programs, recommending policies, administering services and conducting research to prevent the spread and occurrence of health problems. In order to do this, “Public health relies on data reported by healthcare partners to conduct nearly every aspect of its core functions” (Shapiro, Mostashari, Hripcsak, Soulakis, & Kuperman, 2011). Historically, reporting processes have been done manually. However, “information technology offers the opportunity to replace manual reporting processes with automated ones, and innovators are increasingly developing such approaches” (Shapiro et al., 2011). One benefit that public health agencies can receive through the use of health information exchange include the transmission of laboratory reports to public health surveillance programs. For example, health departments could use the information that has been given to them to trigger investigations and contact tracing. The HIE could be a “a gateway to relevant epidemiologic information” and assist with not only surveillance programs but also give users information that they may be interested in (Shapiro et al., 2001).

One example of a public health HIE is the Northwest Public Health Information Exchange, or the NW-PHIE. This health information exchange covers points of care across Washington and Idaho and is used by public health programs to monitor and respond to health emergencies. According to a study that examined the NW-PHIE, it was noted that the organization “has implemented HITSP Biosurveillance standards, developed a specification for sharing summary syndromic surveillance data and demonstrated how the NHIN Gateway and services can be used to support public health surveillance” (Dobbs, Trebatoski, & Revere, 2010). This was done through sending patient-level, transactional data to the public health agencies and creating a process for taking that data to create “a patient encounter record which then gets analyzed to identify incidents of importance to public health” (Dobbs et al., 2010). The data that is sent is meant to be easily imported for the creation of epidemiology curves for public health tracking.

Telehealth allows for health professionals and patients who are separated by a distance to use information and technologies to provide care. This can include the practice of medicine between health providers and patients when they are not in the same location and exchanging information between multiple health professionals (Adeogun, Tiwari, & Alcock, 2011). In one model for telehealth, health information exchange is used in multiple steps of the care process. First, alters can be set up to inform or remind patients to carry out tests or take their medications. Then, patients can send their test results to their health providers when tests have been conducted outside of the provider’s office. Additionally, health professionals can set up alerts for the patient to inform the patient of the arrival of the results or when the results are outside of a set parameter. This can lead to the next stage, where “patients and health professionals have a live dialogue either on the phone or through video conferencing to discuss results and progress of patients” (Adeogun et al., 2011). In order to facilitate the visit, providers would be able to have access to the patient’s health information and check the patient’s compliance to their health regimens. Telehealth allows for better connections to care and helps patients achieve care outside of the traditional setting. In order to make sure this is possible, providers should be able to utilize HIE to make sure both them and patients have access to all of the patients’ information.

One way to illustrate health information exchange is to consider the example of COVID-19 surveillance and reporting. Public health agencies could utilize HIE to gather up to date information from emergency rooms, primary care providers, and testing sites to track population level data and to conduct contact tracing. This is important because patients might be using multiple points of care and tracking this information will allow for better individual care and population level tracking. In one example, a patient may be screened for COVID-19 symptoms through telehealth, obtain testing at a drive through site of Health System A, and have a follow up with a provider in Health System B. For this reason, there has to be a system that allows for patient data to follow the patient so providers at these multiple sites can coordinate care and so public health officials can use this information for contact tracing and disease monitoring. One proposed method of further integrating HIE with COVID-19 surveillance is to “link medical records of COVID-19 patients to their cellular devices and obtain the histories of their movements before diagnosis and of other persons whose cellular devices indicate they came in proximity of these persons” (Lenert & McSwain, 2020). While this method could pose important questions about patient privacy, if implemented properly it could be an important tool that uses the integration of technology and contact tracing methods to improve public health outcomes during the pandemic.

(Lenert & Mcswain, 2020)

Meaningful Use was a policy that was created to promote the meaningful use of certified Electronic Health Record systems. This also included ensuring that EHRs could connect and provide for the electronic transfer of information. During the first stage of Meaningful Use, it was “optional for providers transferring a patient to the care of another provider to furnish that provider with a summary of care record 50 percent of the time, and noted that such information need not be transmitted electronically” (Health Policy Brief). This changed during stage 2, where hospitals and professionals were required to submit a summary of care electronically for “more than 10 percent of transitions of care and referrals” (Health Policy Brief). Additionally, during this stage patients would be able to download and transmit their own information. This is important because the Meaningful Use objectives support the interoperability of EHR technologies, which is essential for HIE. Health information exchange organizations that utilize EHR systems for data input benefited significantly from Meaningful Use because it made sure that these systems were able to output their information to other systems.

Just as HIE has benefited from Meaningful Use objectives, HIE is supported in the Federal Health IT Strategic Plan. One example of this is Objective 1C, which aims to advance the communications infrastructure that supports health delivery. This is also a primary use of HIE, meaning that health information exchanges seek to improve the infrastructure that health data is transmitted on and to ensure the health data can be accessible from many points of care. The next example is Object 2A, which involves enabling individuals, providers, and public health entities to securely transmit and access electronic health information. Again, this objective is directly in line with the goals of many HIE systems because a common goal is that patient data can be accessible from not only providers, but also the patients and public health agencies. Similarly Objective 2B, which is to identify and advance the technical standards to support secure and interoperable health information, helps advance HIE because health information exchanges need consistent standards for health information so different health records can be accessed and incorporated into the HIE.

References

Adeogun, O., Tiwari, A., & Alcock, J. (2011). Models of information exchange for UK telehealth systems. International Journal of Medical Informatics, 80(5), 359-370. doi:10.1016/j.ijmedinf.2011.01.013

Dobbs, D., Trebatoski, M., & Revere, D. (2010). The Northwest Public Health Information Exchange’s Accomplishments in Connecting a Health Information Exchange with Public Health. Online Journal of Public Health Informatics, 2(2). doi:10.5210/ojphi.v2i2.3210

Federal Health IT Strategic Plan

“Health Policy Brief: Interoperability,” Health Affairs, August 11, 2014

Lenert, L., & Mcswain, B. Y. (2020). Balancing health privacy, health information exchange, and research in the context of the COVID-19 pandemic. Journal of the American Medical Informatics Association, 27(6), 963-966. doi:10.1093/jamia/ocaa039

Shapiro, J. S., Mostashari, F., Hripcsak, G., Soulakis, N., & Kuperman, G. (2011). Using Health Information Exchange to Improve Public Health. American Journal of Public Health, 101(4), 616-623. doi:10.2105/ajph.2008.158980

In order to understand the relationship between evidence based practice and informatics, it is important to evaluate what evidence practice is. One definition of evidence based practice is “the conscientious, explicit and judicious use of current best evidence in making decisions” (Ammenwerth, 2015). This definition was created to describe evidence based medicine, where both external evidence and individual expertise help guide a provider to make the best clinical decisions. It is a method that is used to improve the patient care that is administered by the provider. Health informatics also seeks to improve health care, however it does so through the use of technical interventions instead. Evidence based decision making can be applied to health informatics as well, where evidence on efficiency or effectiveness can be used when making decisions regarding implementation of certain health IT systems. This is important because health IT “indirectly affects the patient by influencing clinical processes and clinical decision making in a vivid health care environment” (Ammenwerth, 2015).

Evidence based health informatics begins with the current based evidence. This evidence is scientific evidence that has been derived “from well-designed systematic evaluation studies or systematic reviews” (Ammenwerth, 2015). These studies have to evaluate health IT starting with the development phase through needs assessments, test runs, and simulation studies. Additionally, early use and routine use reviews are needed for evidence based informatics. This means that performance measurements, usability studies, usage pattern analysis, and cost analysis are important to evidence based health informatics as well. The result of evidence based informatics is that many guidelines are developed with existing evidence in mind.

As evidence based guidelines in health informatics is examined, HIE can be used as an example. As we enter the age of standardized use of electronic health records and care becomes more and more specialized, electronically sharing data from multiple points of care is advantageous to many providers. HIE is “the key component of health informatics through which information from various electronic record systems is shared and is potentially transformative for the healthcare system” (Braunstein, 2014, p. 55). Development of HIE began due to the challenges faced when exchanging data between different systems as a result of changing and interoperable interfaces. While care coordination has been considered an essential concept for managing chronic diseases, in practice it is challenging when “every provider has their own EMR, and that EMR can come from any one of the hundreds of companies certified for Meaningful Use” (Braunstein, 2014, p. 57). While these electronic record systems were certified for use by the Office of the National Coordinator, they did not work well together, which is what created these challenges. As the government began to recognize the importance of HIE systems, a greater movement towards interoperability guidelines were placed. Through EHR practice, governing agencies have been able to refine guidelines that benefit interoperability and support the development of HIE. One example of this occurring is this March, where the Center for Medicare & Medicaid Services released new rules that established “policies that break down barriers in the nation’s health system to enable better patient access to their health information, improve interoperability and unleash innovation, while reducing burden on payers and providers” (CMS.gov).

Some existing guidelines for HIE are set by eHealth Initiative, the Health Information Management Systems Society, and the Office of the National Coordinator for Health Information Technology. These guidelines focus on the classification and goals of the HIE, such as the architecture of the systems and function of the systems. The architecture of HIEs include Centralized, Federated, and Hybrid, and these classifications denote where the data is stored and how it is accessed. In the centralized model, the data is stored in a central repository. This differs from the federated HIE, where all of the clinical data is stored at the source. Hybrid HIEs use both storage methods for the data, typically having a patient index that directs to where the data is stored. Functionality is classified through how the data is exchanged and the three classifications are directed exchange, query based exchange, and consumer mediated exchange.

While these classifications adequately cover the data storage and exchange methods that are used for HIEs, improvement still needs to be made since they do not fully cover the scope of HIE. One way to find areas of improvement is by examining existing HIE systems, such as the Indiana Health Information Exchange, and evaluate their systems and outcomes to help refine existing guidelines for future HIE. The Indiana Health Information Exchange is an excellent example for this because it is “the country’s largest HIE” and considered “the premier example of centralized HIE” (Braunstein, 2014, p. 64). This system uses a centralized model to offer a variety of services across the state, such as a portal for lab results and clinical reports, a community health record, a population health management system, a diagnostic-imaging sharing service, and analytics tools for managing care. The IHIE has many value adding services, and these services are one of the ways that this HIE stands out. The guidelines for HIE should be adjusted to include service specific information. For example, if one were to create an HIE that had the services of result delivery and surveillance of population health for COVID-19, guidelines for services that deliver test results to patients and services that aggregate population health data would assist in the development of the HIE.

Practice based evidence is different from EBP because it is scientific evidence that is developed in a real world setting and it is an important research method. In one study where the PBE method was used to explore traumatic brain injury inpatient rehabilitation practices, the researchers were able to look at “information on the types, intensity, and duration of key activities used in interdisciplinary rehabilitation using a separate taxonomy for each discipline” (Horn et al., 2015). This is important because they were able to gain more detailed information on the processes used in addition to the outcomes. In health informatics, this is an important method of research because understanding the processes of the systems that are being developed is just as important as the outcomes that are produced. Understanding the processes will help with efficiency and effectiveness with the development of future projects. Practice based evidence can also be applied to researching existing projects because we can study the “practice” or the systems themselves.

Data mining is the extraction of information from data and it “implies in-depth searching to find additional information that may have previously gone unnoticed during a more routine analyses of the data” (Penny & Smith, 2012). This process is an increasingly popular method for research as computer systems have become more capable of processing large amounts of data. In the focus area of health information exchange, HIEs can be used as tools to aid in the data mining process. For example, the data from a statewide HIE such as Indiana Health Information Exchange was aggregated, we could use data mining to research questions like what populations in the state are hit hardest with COVID-19, and if wealthier counties have fared better than poorer counties during the pandemic. Since the aggregated data from this hypothetical HIE should include anonymized location data and COVID-19 test results, it would be a good data source for data mining.

One issue with data mining and HIE is ensuring that patient data is protected and remains private. However, there are measures that can be taken in order to ensure patient information is protected. One measure is to use secure multiparty computation, which encrypts data, as a result “ensuring that no party learns anything about another’s data values” (Clifton, Kantarcioglu, & Vaidya, 2002). Another measure is to obscure data, which is done by making private data available, but with enough noise added that exact values (or approximations sufficient to allow misuse) cannot be determined” (Clifton et al., 2002). A common way of doing this is aggregation, where there is not enough information to get an individual’s data with only the information from the community level. Each method has its benefits and downfalls. Secure multiparty computation allows for more specific data sets and high levels of privacy but is very costly and difficult to achieve, while obscuring data is much easier to do but you are left with less specific population level data. However, when used in the case of public health research and population level data is the goal, then patient privacy from data mining HIE is achievable.

Clinical decision support systems are important because they can help increase quality of care while decreasing the errors. This is done by delivering “information tools to the point of care” (Hills, Lober, & Painter, 2008). In HIE, this is achieved by ensuring “records follow the patient and clinicians have access to critical health care information when treatment decisions are being made” (Hills et al., 2008). Health information exchange makes it easier for patient data to be accessed by providers at multiple points of care, which helps them make decisions based on the patient’s medical history. For example, when prescribing a medication, access to a patient’s full medication would help the provider avoid errors.

References

Ammenwerth, E. (2015). Evidence-based Health Informatics: How Do We Know What We Know? Methods of Information in Medicine, 54(04), 298-307. doi:10.3414/me14-01-0119

Braunstein, M. L. (2014). Contemporary health informatics. Chicago, IL: AHIMA Press.

Clifton, C., Kantarcioglu, M., & Vaidya, J. (2002, November). Defining privacy for data mining. In National science foundation workshop on next generation data mining (Vol. 1, No. 26, p. 1).

Fact sheet Interoperability and Patient Access Fact Sheet. (2020, March 9). Retrieved October 01, 2020, from https://www.cms.gov/newsroom/fact-sheets/interoperability-and-patient-access-fact-sheet

Hills, R., Lober, W., & Painter, I. (2008). Biosurveillance, Case Reporting, and Decision Support: Public Health Interactions with a Health Information Exchange. In Biosurveillance and Biosecurity (Vol. 5354, pp. 10–21). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-89746-0_2

Horn, S. D., Corrigan, J. D., Bogner, J., Hammond, F. M., Seel, R. T., Smout, R. J., … & Whiteneck, G. G. (2015). Traumatic Brain Injury–Practice Based Evidence study: design and patients, centers, treatments, and outcomes. Archives of physical medicine and rehabilitation, 96(8), S178-S196.

Penny, K. I., & Smith, G. D. (2012). The use of data-mining to identify indicators of health-related quality of life in patients with irritable bowel syndrome. Journal of clinical nursing, 21(19-20), 2761–2771. https://doi.org/10.1111/j.1365-2702.2011.03897.x

In order to identify challenges in health informatics, first there has to be a definition of informatics itself. Informatics is a broad discipline that utilizes information science and computer science to study the effective uses of data and information. To simply this, informatics can take raw data and turn it into usable information. Health informatics is the application of informatics in the health sector. It includes the effective use of data and technology for problem solving and decision making in order to improve health outcomes. Health informatics encompasses clinical informatics and public health informatics, which focuses on informatics at the individual and population level. There are many factors that contribute to informatics, such as the structure of information systems, the behavior of these systems, and how these systems interact with themselves and each other. Ultimately, health informatics could be defined as the study of the uses of data, information, and knowledge and how these uses can improve health on the individual and population levels.

Now that health informatics has been defined, challenges that are being faced in the area can be more easily identified. One challenge that is being faced by the health informatics discipline is the lack of a health infrastructure that can easily exchange data between different points of care. An example of this is the lack of interoperability between different health organization in terms of exchanging patient health record. While many health systems have adopted electronic health record systems such as Cerner and Epic, not all of these systems allows for easy exchange of information outside of their established ecosystems. Interoperability is important because it makes it easier for patients who receive care from providers that may be affiliated with different health systems since their health records such as previous appointment notes, referrals, and medication lists would be accessible by all of the patients providers. This would improve care by reducing medical errors such as drug interactions and it would improve the cost of care by reducing redundant testing and appointments.

An additional benefit of interoperability and health information exchange would be allowing public health agencies on both the state and federal level to have access to aggregated data that could improve population health tracking and epidemiological research on chronic diseases such as diabetes. Unfortunately, the United States lacks a unified health system and a unified health information exchange so transmitting data between different organizations can be more challenging than expected. In the end, this challenge of interoperability is extremely important for maintaining a comprehensive health record for both patients and providers while also supporting important population health tracking databases that can be used by epidemiologists and other public health professionals to improve public health initiatives.

This is an informatics challenge because it requires information science and technology to create methods and tools to effectively create health information systems. On the individual level, health information exchange systems would use the efficient exchange of patient data to identify potential health errors such as allergy and drug interactions before they happen. On the public health level, the effective exchange of this information can be used to monitor specific health concerns such as infectious diseases or chronic issues among specific population groups.  In the essay “Technology and Informatics” by Connors, Warren, and Popkess-Vawter, it is noted that informatics is “the science that encompasses information science and computer science to study the process, management, and retrieval of information.” Understanding this definition allows for explaining how the issue of information exchange and interoperability between electronic health record systems is an informatics issues. This is because the information that is being managed and retrieved is the patient’s health data and the information systems that are being devised are aiding in the storage, analysis, and dissemination of this data. In that same essay, the authors note that “the electronic health record is the central component of the health IT infrastructure.” As a result, connecting these EHR systems to allow for the flow of patient information is an informatics challenge that falls into both the clinical informatics and public health informatics spheres.

A video that explains the importance of data systems for public health professionals is linked below. In this video from the Public Health Informatics Institute, the definition of informatics is supported because it describes how informatics specialist design systems around data to support the exchange and use of information. Additionally, it explains how health information systems can benefit health professionals by creating a strong foundation of information that they can use to make informed decisions.

Hello!

My name is Evan Morton and I am a graduate student at DePaul University studying Health Informatics. I have a background in public health and I am interested in how informatics can be applied in public health practice. During this fall term, I will be exploring what informatics is, how informatics is being used, and what is in store for the future of informatics.

Thank you for reading and joining me in the journey into technology and information science in healthcare!