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I found this video to be really helpful and thorough in better understanding the transformation from meaningless data to wisdom that can be applied. Going into this semester, one of the things I most wanted to get out of this course was to better understand how the data that I am so used to inputting into the EHR can be further applied on a larger scale to change patient outcomes. I will continue to think back on the DIKW pyramid and hope that in my future career as an FNP, I can find ways to utilize the data gathered in my own practice to gain wisdom. Through this, I hope to improve my own patient outcomes through application of informatics.

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DIKW Pyramid Illustration with Sample Data

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A previous course I have taken at Simmons discussed ICD-10 codes and one assignment we had was to look up ICD-10 codes for particular disease states to get practice finding codes and applying them. This week, my eyes were opened to just how important these codes are and will be to my future career as a nurse practitioner. I was shocked to learn that ICD-10 has over 69,000 codes and how specific these codes are to any condition I may encounter. It does seem overwhelming to be able to determine which specific code is the right code to select but I am sure this is a skill that will only come with practice.

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Personally, I do not have a lot of experience with implementation in my current RN role. When I first became a nurse, EPIC was already implemented and everyone at my current facility was already comfortable with the software and how to utilize the EHR. One aspect of implementation that I have seem in practice is the use of "champions" who become professionals in a sense for a new process or procedure and serve as a point of contact for staff members to ask questions to or to help troubleshoot any issues. This practice was used when my unit was implementing a new model of out ZOLL machine. Two nurses on the floor attended three training sessions to master the new tool and were able to help train others on the floor to make sure everyone felt comfortable with the change.

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Software Development Lifecycle in 9 minutes!

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Going into this course, I have very limited experience with the field of informatics. My experience centers mainly around utilizing EPIC at my current RN job and utilizing the EHR to chart patient data. One of the main goals that I hope to get out of this course is to learn about how the data that I am so used to inputting into the EHR can be utilized on a larger scale to improve patient outcomes. I also hope to be able to learn ways that, as a nurse practitioner, I can apply informatics in my own future practice and make meaning out of the data that I am so used to obtaining.

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Health Transparency- 21st Century Cures Act

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Health Transparency- 21st Century Cures Act

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Beginning on April 5, 2021, the 21st Century Cures Act was enacted that required eight types of clinical notes to not be blocked from patients and made available "without delay." When this act was passed, I know that at my job, it was met with a lot of skepticism. Fellow nurses were concerned that patient's would be able to read their objective notes and interpret them incorrectly. I was able to witness several instances in which a patient would have access to their lab and test results before the provider could get to their room to explain what they meant, ultimately causing panic and alarm. Although I think it is a great idea for patients to be able to have access to their records, it is important to always explain results as soon as possible in the same manner as before to avoid unnecessary panic.

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November 2023 - "Disincentive Penalties for Information-Blocking Providers" proposed by the Department of Health and Human Services (HHS). This proposed rule was posted to the Federal Register and is taking comments until 11:59 p.m. ET on January 2, 2024.

The rule will affect physicians who participate in the Medicare program.

More information can be found on the HHS website

As of April 2021, "blocking" patients from their own health records is against the law and may result in fines for hospitals and clinicians. Learn how the Cures Act and information-blocking rule affect patients at WhereIsMyMedicalRecord.org.

The Cures Act final rule and information-blocking guidelines apply to:

health care providers

health information networks and exchanges

Information technology developers of certified health IT (e.g., electronic health record vendors)

For more details about each of these groups, review this document from the Office of the National Coordinator for Health Information Technology (ONC). If you or your job is listed in this document, the Cures rule applies to you.

In June 2023, the Department of Health and Human Services Office of the Inspector General (OIG) posted its final rule implementing information-blocking penalties. The final rule established statutory penalties created by the 21st Century Cures Act.

These penalties apply to electronic health record vendors (EHRs), health information exchanges, and health information networks (HINs).

If OIG determines that individuals or entities have blocked information, they may be subject to a penalty of up to one million dollars per violation.

Only certain entities are subject to an OIG information-blocking penalty:

health information developers of certified health IT

entities offering certified health IT

health information exchanges, and

health information networks.

Learn more at OIG Information-Blocking Fast Facts.

All notes must be shared with patients. On October 6, 2022, the definition of electronic health information (EHI) in the 21st Century Cures Act expanded. It now encompasses not only the United States Core Data for Interoperability (USCDI) Version 1, but also all electronic protected health information (ePHI).

PHI encompasses any identifiable health information about a patient that is used, maintained, stored, or transmitted by a health care provider who bills an insurance company for services provided to any patient-also known as a covered entity. To be clear, patient access isn't affected by whether the patient has insurance or not.

With this change to the interoperability and information blocking rule, EHI now extends to the designated record set (as defined by the Health Insurance Portability and Accountability Act), which includes both medical and payment records. This means the rule now applies to any information that could be used to make decisions about individuals, including patients. For entities subject to information-blocking rules, all ePHI within a designated record set will be treated as EHI and subject to the rules.
EHI could include:

Medical records and billing records about individuals maintained by or for a covered health care provider

Enrollment, payment, claims adjudication, and case or medical management record systems

Other records that are used, in whole or in part, by or for the covered entity to make decisions about individuals

More information about EHI and ePHI can be found at HealthIT.gov.

Yes. There are complex situations in which information can be blocked-and these are called exceptions. Unless one of the exceptions applies, clinical notes must not be blocked.

For complete details, refer to the information-blocking FAQ on HealthIT.gov.
Summary of the Exceptions
The rule refers throughout to "actors." They include:

Health care providers (including physicians, physician assistants, nurse practitioners, nurses, social workers, chaplains, therapists, and many other roles directly involved in patient care)

Health information networks or health information exchanges

Health IT developers of certified health IT (e.g., electronic health record vendors)

We list below exceptions outlined by the final rule. These fall into two categories ( source).
Category 1. Exceptions that involve not fulfilling requests to access, exchange, or use electronic health information (EHI):

Preventing Harm Exception: If a patient makes the request for information, the provider must have a reasonable expectation that providing the information will result in physical harm to the life of the patient, clinician, or another person. If the legal representative of the patient requests the information, the clinician has to have a reasonable expectation that the release of information will result in harm to the patient, the clinician or another person.

Privacy Exception: It will not be information blocking if an actor does not fulfill a request to access, exchange, or uses EHI in order to protect an individual's privacy, provided certain conditions are met.

Security Exception: It will not be information blocking for an actor to interfere with the access, exchange, or use of EHI in order to protect the security of EHI, provided certain conditions are met.

Infeasibility Exception: It will not be information blocking if an actor does not fulfill a request to access, exchange, or use EHI due to the infeasibility of the request, provided certain conditions are met.

Health IT Performance Exception: It will not be information blocking for an actor to take reasonable and necessary measures to make health IT temporarily unavailable or to degrade the health IT's performance for the benefit of the overall performance of the health IT, provided certain conditions are met.

Category 2. Exceptions that involve procedures for fulfilling requests to access, exchange, or use of EHI:

Content and Manner Exception: It will not be information blocking for an actor to limit the content or fulfillment methods for accessing, exchanging, or using EHI, provided certain conditions are met.

Fees Exception: It will not be information blocking for an actor to charge fees, including fees that result in a reasonable profit margin, for accessing, exchanging, or using EHI, provided certain conditions are met

Licensing Exception: It will not be information blocking for an actor to license interoperability elements for EHI to be accessed, exchanged, or used, provided certain conditions are met.

Details regarding conditions that must be met to fulfill these exceptions can be found on the ONC website.

There are a few types of clinical notes to which the rules do not apply. Examples include:

Psychotherapy side notes or process recordings that are not intended to be a part of the individual's medical/mental health record. These notes must be recorded (in any medium) by a mental health professional documenting or analyzing the contents of the conversation (transference/countertransference for instance) during a private, group, joint, or family counseling session. Note that all behavioral health care providers are required to share their notes regarding:

medication prescription and monitoring

counseling session start and stop times

the modalities and frequencies of treatment furnished

results of clinical tests

any summary of the following items: diagnosis, functional status, the treatment plan, symptoms, prognosis, and progress to date

Information compiled in reasonable anticipation of, or use in a civil, criminal, or administrative action or proceeding and not intended to be a part of the health record.

Under the Cures rule, in certain specified situations, you can block (or "hide") information from patient access on online portals. These are known as exceptions. For instance, you can block information in the following scenarios:

If you believe a patient will harm another person or themselves as a result of reading the information

If you need to protect the security of another person's electronic health information (e.g., a mother's health information in a child's record; health information related to domestic violence concerns)

Unless one of the exceptions applies, clinical notes must not be blocked. Details about exceptions are outlined at HealthIT.gov.

So far, studies suggest that some clinicians are changing the way they write notes in response to open notes implementations, while some are not. However, many clinicians experienced in sharing notes have reported positive changes in the way they write their notes, commenting that that the notes have become more valuable overall, especially to patients.

Few report "dumbing down" their language. Instead, they find themselves using fewer abbreviations in their notes and trying to avoid language that could appear judgmental to patients. Some report modulating their approach so that their notes become "teaching notes."

In general, patients do not expect clinicians to write notes in layperson language, and in one large study, more than 90% report understanding their notes well. Studies suggest that most patients are not bothered by terms they don't understand; they are happy to research them. They feel reading notes helps them prepare more focused questions for clinicians. Overall, studies show repeatedly that patients are enthusiastic about having a window into more information about their health.

The 21st Century Cures Act was signed into law by President Barack Obama in 2016 with overwhelmingly bipartisan support. Information sharing is central to the Cures Act. The Cures Act Final Rule -also known as the "information blocking rule," which defines what and how information must be shared with patients-was released by the Office of the National Coordinator for Health Information Technology (ONC) in 2022.

Some refer to this as the "information sharing rule." It mandates that patients have rapid, free, and full access upon request to test results, medication lists, referral information, and clinical notes, all in electronic formats.

Some refer to the Cures Act final rule as the "Open Notes Rule." This is inaccurate. While ONC strongly supports the concept of open notes and the efforts of the OpenNotes movement based at Beth Israel Deaconess Medical Center, it's important to note that the Cures Act final rule and open notes are not synonymous. The final rule extends well beyond clinical notes.
See the ONC's relevant FAQ about clinical notes.

Disclaimer

This web page hosted by OpenNotes is for informational purposes only and does not confer official technical or legal advice.

State laws around data release may not supersede the 21st Century Cures Act. The Cures Act final rule specifically states that information need not be released to patients if such release is prohibited by other laws. For example, the California Health and Safety Code limits the online release of the specified results related to HIV antibodies, hepatitis antigens, "abusing the use of drugs," and malignant pathology.

When necessary, and when possible, health care providers should consult with their organization's Health Information Management, compliance, legal, finance, and public affairs experts/teams to find out how the rule applies to them.

Statements from OpenNotes

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As of April 5, 2021, the federal rule on Interoperability, Information Blocking, and ONC Health IT Certification-which implemented the 21st Century Cures Act-went into effect. The "Cures Rule" requires healthcare providers give patients access to all of the health information in their electronic medical records "without delay" and without charge.

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Quality and Safety Education for Nurses (QSEN)

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Quality and Safety Education for Nurses (QSEN)

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Quality and Safety Education for Nurses (QSEN) is an initiative involving six competencies:
1. Patient-Centered Care
2. Teamwork and Collaboration
3. Evidence-Based Practice
4. Quality Improvement
5. Safety
6. Informatics
These six competencies are then broken into three groups: knowledge, skills and attitudes. The informatics competency in particular focuses on the ability of nurses to utilize both information and technology to "communicate, manage knowledge, mitigate error, and support decision making." QSEN supports the idea that nurses should be educated and empowered to utilize technology to not only gather information but also to "support clinical decision-making, error prevention, and care coordination."

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When completing the asynchronous work for this week, one muddy point for me was the TIGER initiative. When watching the video, I was a little unsure of what exactly the initiative was aiming to accomplish and how it relates to informatics. With more research, I was able to gain a better understanding of the initiative.

TIGER refers to Technology Informatics Guiding Education Reform. The goal of the TIGER initiative is very similar to that of the informatics competency for QSEN which aims to define action steps that can assist nurses to utilize technology and informatics to ultimately improve the quality of patient care. Similar to the six competencies of QSEN, the TIGER Initiative developed nine goals:

1. Standards and Interoperability

2. Healthcare Information Technology National Agenda/Policy

3. Informatics Competencies

4. Education and Faculty Development

5. Staff Development/Continuing Education

6. Usability/Clinical Application Design

7. Virtual Demonstration Center

8. Leadership Development

9. Consumer Empowerment/Personal Health Record

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An Initiative for Technology and Health Informatics Education

The Technology Informatics Guiding Education Reform (TIGER) initiative from HIMSS provides the global health workforce with innovative informatics/eHealth tools and resources to transform health for all.

The global TIGER network collaborates to integrate informatics/eHealth into healthcare education, certification, practice and research through an inclusive, interdisciplinary, intergenerational approach.

Education Reform

We create an environment that maximizes the possibilities of technology toward knowledge development and dissemination, driving rapid implementation of best practices as well as competency and curriculum development.

Interprofessional Community Development and Growth

We actively engage and collaborate with the global healthcare workforce, students and adult learners to encourage standardized, person-centered and technology-enabled processes to facilitate teamwork and relationships across the continuum of care worldwide.

Global Workforce Development

We foster a respectful learning community of diverse stakeholders that embrace shared values to drive innovation and technology around the world.

Global Recommendations

While informatics recommendations on competencies and education support the design of curricula and courses, they are unable to inform educators on how to customize content for local needs and requirements. That's why the TIGER International Competency Synthesis Project (ICSP) and the EU*US eHealth Work Project came together to describe and validate the TIGER initiative's framework of global informatics core competencies for health professionals.

Together, these projects compiled a recommendation framework of health informatics competencies (v2.0) to measure, inform, educate and advance development of a skilled workforce throughout the EU and U.S. and around the world. Although the EU*US eHealth Work Project has ended, we are compiling global case studies to continue bringing our findings to life, with a focus on all states within the EU.
Hear TIGER International Task Force Former Co-Chairs Ursula Hübner, PhD, professor, University of Applied Sciences Osnabrück, Germany, and Beth L. Elias, PhD, MS, FHIMSS, adjunct faculty, Panuska College of Professional Studies, University of Scranton, present these important project findings at the HIMSS19 Global Health Conference.
TIGER International Task Force

The TIGER International Task Force, seated under the HIMSS Professional Development Committee, provides our global community of 34 countries with knowledge, leadership and guidance in its efforts to reform technology and informatics education. It provides domain expertise through activities, projects and collaborations within the interprofessional community to support faculty, students, adult learners and providers.

TIGER Resources

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The Technology Informatics Guiding Education Reform (TIGER) initiative offers tools and resources for learners to advance their technology and health informatics skills and for educators to develop valuable curricula.

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This article focuses on the importance of interoperability and standardized data. When patient information is stored across a variety of incompatible data systems, there is a limitation placed on healthcare providers to gain a full picture of their patients. If there was a single, homogenous health information system that could be accessed by any given provider that a patient elects to see, then both time and money can be saved in avoiding duplicate labs/tests. It can also assist in instances where patients may be "poor historians" if a provider is able to have access to all of their records on a single platform. I think that interoperability through a universal health record would greatly improve patient outcomes while reducing costs all around.

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Introduction

The digitalization of medicine promises great advances for global health. Electronic medical records, mobile health apps, medical imaging, low-cost gene sequencing as well as new sensors and wearable devices provide an ever-increasing flow of digital health data. Combined with artificial intelligence, cloud computing and big data analytics, this wealth of data holds huge potential for healthcare and can improve the lives of millions of patients worldwide - with better diagnostics, personalized treatments, and early disease prevention.1,2,3,4,5,6

But medical data are only useful if they can be turned into meaningful information. This requires high-quality datasets, seamless communication across IT systems and standard data formats that can be processed by humans and machines. Judged by these criteria, however, large parts of today's medical data are virtually useless: Hidden in isolated data silos and incompatible systems, the data are difficult to exchange, process and interpret. In fact, the current medical landscape seems less characterized by "big data" but rather by a large number of disconnected small data. These are suboptimal conditions for the data-driven technologies anticipated to drive medical innovation. Uncovering the full potential of digital medicine requires an interconnected data infrastructure with fast, reliable and secure interfaces, international standards for data exchange as well as medical terminologies that define unambiguous vocabularies for the communication of medical information. In short: Digital health depends on interoperability.

The aim of this article is to show why interoperability is so important for achieving the full potential of digitalization in healthcare and medicine. Although the importance of interoperable health IT systems is increasingly acknowledged,7,8,9 awareness of this topic is still relatively low among healthcare professionals - especially compared with topics such as artificial intelligence, big data or mobile technologies, which are generally seen as the main drivers of digital health innovation.6,10,11,12,13 Accordingly, progress in health interoperability is slow.14 Here, we argue that interoperability is indispensable for advances in digital health and that it is, in fact, a prerequisite for most of the innovations envisioned for future medicine.

Our article starts with an overview of interoperability and its different levels: technical, syntactic, semantic, and organizational. It then shows how interoperability can improve medicine, focusing on four areas that especially benefit from (and sometimes crucially depend on) interoperable health IT systems: (1) artificial intelligence and big data; (2) medical communication; (3) research; and (4) international cooperation (Fig. 1). We chose these four areas because they illustrate particularly well how interoperability can facilitate digital transformation and improve medicine and healthcare (however, the areas are not mutually exclusive, and advancing, for example, medical communication can also improve international cooperation). Note that our views are shaped by our German/European perspective. However, we discuss points general enough to be relevant for international readers. Also note that, though giving some examples of specific health IT standards and medical terminologies that can improve interoperability, this article does not aim to provide detailed technical discussions of specific standards or terminologies (this information can be found elsewhere15,16).

Overview showing how interoperability can improve medicine in the areas of artificial intelligence (AI) and big data, medical communication, research, and international cooperation

Interoperability

Interoperability can be broadly defined as "the ability of two or more systems or components to exchange information and to use the information that has been exchanged".17 Most definitions further distinguish between different components, layers or levels of interoperability.15,16 Although these components can slightly differ across definitions, they generally follow a distinction between lower-level technical components and higher-level organizational components. In line with this conceptualization, this section gives a brief overview of technical, syntactic, semantic and organizational aspects of interoperability.

Technical interoperability

Technical interoperability ensures basic data exchange capabilities between systems (for example, moving data from a USB stick to a computer). This requires communication channels and protocols for data transmission. With today's digital networks and communication protocols, achieving technical interoperability is usually relatively straightforward. However, moving data from A to B is not enough. To process the data and extract meaningful information, syntactic and semantic interoperability is needed.

Syntactic interoperability

Syntactic interoperability specifies the format and structure of the data (for example, in an XML document). The structured exchange of health data is supported by international standards development organizations (SDOs) such as Health Level Seven International (HL7) or Integrating the Healthcare Enterprise (IHE), which specify health IT standards and their use across systems. An emerging standard for the communication of health data is, for example, HL7's Fast Healthcare Interoperability Resources (FHIR), which defines around 140 common healthcare concepts, so-called resources, which can be accessed and exchanged using modern web technologies.18 FHIR is increasingly adopted by the health industry, as it lends itself to the development of mobile health apps that run on different IT systems.19 Another initiative aiming to improve the structured exchange of health data is openEHR. OpenEHR allows medical professionals and health IT experts to define clinical content using so-called archetypes, specifications of clinical concepts based on an underlying reference model.20 OpenEHR includes a portable language for querying, the Archetype Querying Language (AQL), as well as tools for defining and publishing the archetypes.

Semantic interoperability

While standards such as FHIR and openEHR already define basic semantics of health data, semantic interoperability is really the domain of medical terminologies, nomenclatures, and ontologies. They ensure that the meaning of medical concepts can be shared across systems, thus providing a digital "lingua franca", a common language for medical terms that is, ideally, understandable to humans and machines worldwide. With more than 340,000 medical concepts (including, for example, clinical findings, procedures, substances, organisms, or body structures), the terminology SNOMED CT seems particularly well-suited as a general-purpose language for advancing semantic interoperability in medicine and healthcare.21 It can be complemented by more domain-specific terminologies such as, for example, Logical Observation Identifiers Names and Codes (LOINC) for laboratory observations,22 the Identification of Medicinal Products (IDMP) for medicines,23 the nomenclature of the HUGO Gene Nomenclature Committee (HGNC) for genes24 or the Human Phenotype Ontology (HPO) for phenotypic abnormalities.25 Combined with the standards discussed above, the use of these terminologies can ensure that health data have a clear structure and unambiguous semantics.

Organizational interoperability

At the highest layer, interoperability also involves organizations, legislations and policies. Exchanging data across health IT systems is not an end in itself but should, ultimately, help healthcare professionals to work more efficiently and improve patients' health. This requires common business processes and workflows that enable a seamless provision of healthcare across institutions. As different stakeholders in healthcare have different interests (and these interests do not always aim to maximize interoperability), this also requires policies that provide incentives for interoperable data exchange and, if necessary, enforce interoperability via legal regulations.

How interoperability can improve medicine

Interoperability for artificial intelligence and big data

Digital technologies such as artificial intelligence (AI) and the large-scale analytics subsumed under the term "big data" are increasingly changing medicine and healthcare.6,10,12 These technologies rely on growing volumes of digital medical data. Therefore, to use AI algorithms and big data analytics to their full capacity and feed them with maximum input, processing information from different systems and across institutional boundaries is crucial. A comprehensive analysis of a patient's health data could, for example, require information from general practitioners, hospitals, laboratories, mobile health apps, and wearable sensors. Similarly, multiple data sources are often necessary when data are scarce, for example, in the areas of rare diseases, precision medicine, or pharmacogenomics: tailoring treatments and drugs to increasingly smaller subpopulations of patients requires a large pool of comparable data, making it necessary to exchange information across systems, institutions, and countries.

Unfortunately, today's digital health infrastructure makes large-scale data processing across IT systems still unnecessarily difficult. Current health IT systems operate with a wide variety of data formats, custom specifications and ambiguous semantics. This situation is exacerbated by the trend to store increasing amounts of unstructured data in non-relational databases and so-called data lakes.26 Although these unstructured data are, arguably, better than no data - and modern algorithms can partly extract useful information even from unstructured data - they are difficult to process. As a consequence, time-consuming data cleaning and pre-processing procedures are usually necessary before analysis.

Moreover, running algorithms on unstructured, non-standardized data can introduce errors that distort analysis results. An AI algorithm programmed to identify, for example, diabetes patients from unstructured text could erroneously select patients with a family history of diabetes, not actual diabetes (not to mention the different types and subgroups of diabetes that could easily be confused). Such errors are difficult to detect in large datasets because the sheer volume of the data makes it difficult to anticipate, detect and correct all possible errors. This can introduce systematic biases, which compromise the validity of analysis results and which will eventually undermine trust in digital health technologies. This problem becomes even more relevant when considering the rise of artificial neural networks and deep learning algorithms. Although these algorithms can increasingly compete with (and even outperform) human experts,27,28,29 the mechanisms that drive their decisions usually remain hidden within the network. As these methods are essentially "black boxes" for human users, it is important that their calculations are based on a solid foundation. This requires data with a clear structure and unambiguous semantics. Otherwise, modern AI algorithms could do more harm than good - not because their calculations are wrong but because they rely on questionable input.

To avoid these pitfalls and provide AI algorithms and big data technologies with usable input, interoperability of health data is essential. The largest barrier for applying AI and big data to medicine is, arguably, not a lack of algorithms but a lack of suitable data for developing AI and big data applications. Using the international standards and terminologies mentioned previously can therefore help to provide algorithms with structured and meaningful data and foster the use of AI and big data in medicine.

Interoperability for medical communication

Digital medicine does not always require sophisticated analytics or complex AI algorithms. In many cases, simply making the right information available to the right person at the right time can significantly improve patient care. Often, important parts of medical information are lost as patients move through the healthcare system. For example, if a patient is rehospitalized, relevant information from previous visits to other hospitals may not be available (in Germany, medical information can sometimes not even be shared across different departments of the same hospital due to data protection regulations). This leads to inefficiencies in care and sometimes poses serious risks for patients (for example, if a lack of communication results in adverse drug interactions). Giving healthcare providers the necessary information about their patients can help to avoid such inefficiencies and improve the quality of care.

Promoting the use of interoperable electronic health records (EHRs) is particularly important in this context. Too often, EHRs are disconnected, proprietary solutions buried in systems that do not talk to each other. The use of international standards and terminologies can make EHRs interoperable, enabling the reliable communication of medical information. Existing specifications for patient summary data such as the International Patient Summary (IPS) developed by HL7 and the European Committee for Standardization (CEN)30 can further help clinicians to access relevant, accurate, and up-to-date medical information about their patients.

Importantly, by making relevant health information easily accessible, interoperable health IT systems should also make lives easier for physicians and other healthcare professionals. The rise of digital health technologies often raises concerns that physicians have to spend more time with documentation and data entry and less time with their patients. But interoperable EHRs can reduce the documentation burden (for example, by avoiding repeated entry of data) and simplify cumbersome information retrieval processes. This can enable physicians to focus on their patients and provide optimal care.

On the other end of the spectrum, interoperable EHRs can also help patients to manage their own health more actively. Currently, much of the information that drives providers' decisions about treatments is not easily accessible to the patients themselves, making them inactive bystanders in the treatment process. If patients are given better access to their health data (combining, for example, information about prescriptions, treatments and data from personal health apps), they can take more control of their health. This in itself can have positive health effects, as patients turn from helpless recipients of healthcare to active managers of their health and well-being.

Interoperability for research

Apart from improving health at the point of care, interoperability can also advance medical research. This is particularly true for the field of real-world evidence: Using interoperable formats for real-world data (that is, data routinely collected in medical care or, increasingly, via mobile apps in patients' everyday lives) opens up various opportunities for researchers. First, if real-world data are interoperable, they can be used for large-scale observational studies at regional, national or global levels. Such studies can address epidemiological questions and public health concerns, providing, for example, up-to-date insights into prevalence and incidence of disease, typical treatment pathways of patients or gaps in care. Second, real-world data are a treasure trove for the AI and machine learning methods discussed above. Being able to find patterns and correlations in high-dimensional datasets, these methods can help researchers to identify interesting new research hypotheses, which can subsequently be investigated more closely in controlled clinical trials (these controlled trials will remain important to rule out spurious correlations and identify causal relationships).

More generally, if health data are structured according to international standards, data are much easier to analyze, and efforts needed for data cleaning and pre-processing are reduced. This can speed up the research process and also makes the development of analysis scripts more flexible: If researchers and data scientists know that data will conform to certain formats and semantics, analyses no longer need to be programmed with direct access to the data. Instead, analyses can be developed remotely and later be transferred to the data site to compute results. This can unlock data sources that would otherwise not be easily accessible (due to, for example, strict data protection regulations). It can also improve research quality because analyses can be programmed by experts worldwide, not only by those who have direct access to the data (and who happen to know their idiosyncratic structure). Similarly, interoperable data can ensure that one analysis can be done across many different data sources, covering data from different institutions or countries. This enables research in areas where data are sparse and therefore need to be pooled across different institutions (see next section).

In sum, interoperability can generate new medical insights, making it possible to analyze existing data sources more efficiently. This can advance translational medicine and help to move research discoveries swiftly from the laboratory to the point of care. At a larger scale, it can drive evidence-based practices in medicine and accelerate their implementation into public health policies.

Interoperability for international cooperation

Interoperable interfaces and standard terminologies make health data exchangeable and comparable across systems, institutions and countries. This has obvious benefits for cross-institutional and international cooperation. As mentioned previously, exchanging health data across different IT systems is especially important when data are scarce or when very large datasets are needed, such as in research on rare diseases, precision medicine or drug development. In the case of rare diseases, for example, the number of patients is often so small that even large health institutions may have access to only a handful of cases of a given disease (sometimes only a single patient). To get a better understanding of these diseases and improve diagnosis and treatment, data exchange across institutions is therefore crucial. National and international networks like the Undiagnosed Diseases Network (UDN)31 in the US or the European Reference Networks (ERNs)32 already aim to improve collaboration between clinicians treating rare diseases. The adoption of standard data formats and terminologies such as the Orphanet rare disease nomenclature33 or the previously mentioned HPO for phenotypic abnormalities25 can help to coordinate international efforts to optimize research and care in this area.

Exchanging health data internationally is also essential for tackling global health issues more effectively. Arguably the most serious public health risk - or, for that matter, the most serious risk for humanity in general - is a global pandemic.34 Last year's centenary of the 1918 influenza epidemic should remind us of the potentially devastating consequences of such pandemics, with levels of human suffering and death only comparable to the deadliest wars (the 1918 influenza epidemic, or "Spanish flu", has been estimated to have killed at least 50 million people worldwide).35 In today's highly connected world, a dangerous epidemic could spread within hours from almost anywhere in the world to Berlin, Beijing or Buenos Aires, killing tens of millions of people within a few months.36 But the same global connectedness by which epidemics can spread rapidly around the globe can also help us to control them. If health data are interoperable so that information can be easily exchanged across borders and organizations, effective surveillance systems can be established that allow for an accurate tracking of global disease movements. Outbreaks can then be detected early and further spread prevented.

Importantly, interoperable health IT systems not only facilitate the exchange of data but also the exchange of algorithms, applications and technologies. If organizations standardize their data, cutting-edge health applications developed for these standardized data could be made available to patients and physicians worldwide. The wide use of smartphones and mobile apps can further contribute to the dissemination of digital health technology. This can aid the "democratization" of medicine, making health technologies globally accessible and improving healthcare in underprivileged regions of the world.37,38

2019 has seen the first exchange of common data models between European countries (an electronic prescription and a digital patient summary).39,40 This demonstrates that cross-border exchange of interoperable health data is attainable, even though it is still a long way to a global infrastructure for interoperable data exchange. But gradually expanding the reach of these and other, more extended data models will eventually advance the international exchange of health data to provide seamless, cross-border care to patients.

Conclusion and outlook

Digital medicine depends on interoperable and standardized data. In this article, we discussed how interoperable health data can help to realize the full potential of AI and big data, improve the communication of medical information, make medical research more efficient and foster international cooperation. As interoperability requires the collaborative efforts of healthcare professionals, researchers, IT experts, data engineers, and politicians, it is important to make interoperability a prominent topic in medicine and healthcare. Eventually, efforts to improve interoperability will pay huge dividends: With international standards and medical terminologies, interoperability can pave the way for an interconnected digital health infrastructure that overcomes barriers between individuals, organizations and countries. This will make it possible to turn digital medical data into meaningful information and improve the health and well-being of patients worldwide.

Acknowledgements

We acknowledge support from the German Research Foundation (DFG) and the Open Access Publication Fund of Charité - Universitätsmedizin Berlin.

Author information

Affiliations

1. Berlin Institute of Health (BIH), Berlin, Germany

Moritz Lehne, Julian Sass, Andrea Essenwanger, Josef Schepers & Sylvia Thun

2. Charité - Universitätsmedizin Berlin, Berlin, Germany

Sylvia Thun

3. Hochschule Niederrhein - University of Applied Sciences, Krefeld, Germany

Sylvia Thun

Contributions

M.L. developed the concept for the article and wrote the initial draft. J.S., A.E., J.S., and S.T. contributed important ideas and participated in reviewing and editing of the text.

Corresponding author

Correspondence to Moritz Lehne.

Ethics declarations

Competing interests

S.T. is vice chair of HL7 Deutschland e.V. The remaining authors declare no competing interests.

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Lehne, M., Sass, J., Essenwanger, A. et al. Why digital medicine depends on interoperability. npj Digit. Med. 2, 79 (2019). https://doi.org/10.1038/s41746-019-0158-1
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# data[].attributes.attachment_link.title
Why digital medicine depends on interoperability - npj Digital Medicine

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Digital data are anticipated to transform medicine. However, most of today's medical data lack interoperability: hidden in isolated databases, incompatible systems and proprietary software, the data are difficult to exchange, analyze, and interpret. This slows down medical progress, as technologies that rely on these data - artificial intelligence, big data or mobile applications - cannot be used to their full potential.

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I found this video to be a really great and concise explanation of big data and how big data differs from regular data collection as well as how the five V's apply to big data.

1. Volume: How much data is being collected
2. Variety: Different types of data being collected
3. Velocity: The speed at which data is being collected
4. Veracity: Accuracy and trustworthiness of the data
5. Value: Outcomes and benefits of data.

Big data is a concept I had never before considered and the necessity of higher level storage systems to store such a large amount of data such as patient data in a hospital. The thought of having to analyze so much data is overwhelming to me but I am looking forward to learning more about how it can be utilized for the improvement of patient outcomes.

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Big Data In 5 Minutes | What Is Big Data?| Big Data Analytics | Big Data Tutorial | Simplilearn

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Meaningful use refers to using certified EHR technology to "improve quality, safety, efficiency, and reduce health
disparities." While learning about the different objectives of meaningful use, I was able to connect the objectives to what I have experienced so far with EPIC as a nurse. I was interested to learn that all of these features that I am so used to having in an EHR were actually part of a mandate that hospitals needed to utilize in order to obtain incentives. An example that I am really familiar with is the clinical alerts that populate and flag in a patient's chart to alert the patient care team of best practices and potential medication interactions. I know personally, these alerts always make me slow down at work to ensure I am not making any mistakes and providing safe patient care. I am also thankful that electronic orders and e-prescribing are part of the mandate to ensure I never have to try and interpret a doctor's handwriting.

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Going into this week, I had been utilizing the terms EMR and EHR interchangeably without considering that they may refer to two entirely different concepts. I found this short video to be really helpful in further explaining the difference between the two terms.

Electronic Medical Record (EMR): Institution- specific record that does not interact with other institutions.

Electronic Health Record (EHR): Lifetime patient record. Data from all specialties. Includes components such as CPOE, EMAR and clinical documentation.

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Massachusetts Health Information Exchange (Mass HIway)

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Massachusetts Health Information Exchange (Mass HIway)

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This week, I really enjoyed learning about the use of Health Information Exchanges. Working on a medical-surgical floor, we are constantly admitting new patients to the floor and having to fill out their admission documentation. Part of the admission involves reconciling the patient's home medications and confirming allergies. I think that if this information was not readily available across healthcare facilities, it would ultimately result in a lot of extra time needed to go over this information. Especially with the aging population and those patients with progressing dementia, having information all in one place that can be accessed across providers and facilities ensures appropriate continuity of care while promoting safe and effective patient outcomes.

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Welcome to the Mass HIway

The Mass HIway, the Massachusetts Health Information Exchange (HIE), is a secure Health Information Services Provider (HISP). The HIway is available to all healthcare systems in the Commonwealth, and can be used to cost-effectively improve care coordination, care quality, patient satisfaction, and public health reporting via Direct Messaging. To learn more, click here.

HIway Account Management

The Mass HIway supports providers in connecting and using the Mass HIway. This support is provided by our HIway Account Management team. To learn more, click here.

Statewide ENS Framework

To enable utilization of Event Notification Services (ENS) across Massachusetts, EOHHS and the Mass HIway have developed the Statewide ENS Framework to create an interoperable ENS network that serves all care providers in the Commonwealth. To learn more about the framework, click here.

HIway Connection Requirement

Certain provider Organizations are subject to the HIway Connection Requirement. Currently, Acute Care Hospitals, Community Health Centers, and Medium/Large Medical Ambulatory Practices are subject to this requirement. Acute Care Hospitals must also participate in the Statewide ENS Framework.

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Massachusetts Health Information HIway - HOME | MASSHIWAY Target

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The Mass HIway, the Massachusetts Health Information Exchange (HIE), is a secure Health Information Services Provider (HISP). The HIway is available to all healthcare systems in the Commonwealth, and can be used to cost-effectively improve care coordination, care quality, patient satisfaction, and public health reporting via Direct Messaging.

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Improving health outcomes with big data | Ronda Hughes | TEDxUofSC

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The Importance of Health Information Exchange

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The Importance of Health Information Exchange

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Office of the National Coordinator for Health IT

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Health Information Exchange: Making a Difference

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I found this short video to be a really concise and helpful summary of the HITECH act and the concept of meaningful use. I was really interested to learn about meaningful use this week and think that in the absence of a universal EHR, this act can assist in making patient care more universal and easily accessible across healthcare facilities. Now that I have learned about meaningful use, I have been able to realize how it has been applied in my current setting as a nurse such as with computerized provider order entry and best practice advisories. I have been able to see first hand how the terms of meaningful use can be applied in a hospital setting to promote improved patient outcomes and patient safety.

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The HITECH Act: Electronic Health Records and Meaningful Use

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21st Century Cures Act and Immediate Access to Medical Records

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21st Century Cures Act and Immediate Access to Medical Records

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I found this Tik Tok video to be a good summary of the problems that are presented with the immediate access of patient health data from a physician's perspective. From a nurse's perspective, I have seen a lot of negative aspects of patient's having immediate access to their medical records. I have seen patient's who have gotten results from tests/scans before the doctor has had an opportunity to come and explain them to the patient. This gap in time can lead to unnecessary anxiety and misunderstanding for the patient given that they do not understand the results that they have access to but know that it may sound bad. As a nurse, I have had to provide emotional support to these patients and communicate to the providers to come and explain the results as soon as they can. However, after watching the video from this week, I do think there are benefits in giving patients more power over their health records and in the absence of a universal health record that they can still have continuity of care.

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16.8K Likes, 1.8K Comments. TikTok video from Magnolia Printz M.D. (@balancedanesthesia): "21st Century Cures Act #learnontiktok #tiktokpartner". Imagine getting a radiology report before your doctor has a chance to review it showing that there is a tumor somewhere on your body￼ | Or imagine a teenager's medical records being released to their parents automatically ￼ | Did you know starting April 2021 federal law mandates that patients have immediate access to their medical records free of charge?￼ | ....

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Prior to the content this week, I had never heard of Clinical Decision Support and having only worked with electronic health records from a nurse's perspective, I had never considered the benefit on the provider's side. One example that I have seen in practice is the use of order sets from clinical decision support. For example, on the floor I work on, we get a lot of patients with pneumonia. Within our EPIC system, we have a pneumonia pathway that includes an order set specific for patients with a diagnosis of pneumonia. Within the order set there are tasks such as to utilize incentive spirometer and acapella, obtain a sputum sample and urine sample as well as to have the patient ambulate at least three times daily. The use of these order sets saves providers time in placing orders while also ensuring all patients with the same diagnosis follow the same evidence-based treatment plan.

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This video summarizes Maryland's health information exchange system known as CRISP. CRISP functions similarly to the Mass HIway in allowing sharing of health information across entities. This concept made me consider potential negative aspects of having singular health information exchanges across states. I wonder if it would ever be possible to have a health information exchange system for all of the United States to allow for even greater sharing of patient information and to allow for continuity of care in the instance of patient's moving across state lines.

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Understanding the State's Health Information Exchange (HIE)

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I found this website to be really helpful in finding examples of datasets. This website was incredibly easy to navigate and had many informative datasets. I like how on this particular website, there were detailed explanations of data meaning as well as information on how to contact the dataset creator. Datasets such as this one can be helpful in providing increased access to such data that can help improve patient care, patient safety and overall health outcomes.

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An official website of the United States government

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I found this TikTok to offer a comical but accurate representation of some of the limitations posed by telehealth and telemedicine visits. In the asynchronous material this week, we spent a lot of time discussing the benefits of telemedicine and how, especially during the unprecedented times of the COVID-19 pandemic, it has allowed for a more continuous access to care. However, one of the limitations, as depicted by the above TikTok is that providers are unable to complete an in-person assessment. This requires providers to be skilled in directing patients on how to adjust their cameras to show specific areas of concern. In addition, camera quality can serve to pose as an additional limitation when providers are unable to gain a high-quality view of the patient through the computer screen. Telehealth and telemedicine still have a long way to go if there is hope for them to be able to entirely replace in-person provider visits for some patients.

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1.4K Likes, 56 Comments. TikTok video from Christy (@grey.collective): "When technology fails. #telemedicine #medicine #funny #doctorsoftiktok #pov #duet". POV: Telemedicine nowadays be like... | Hi there! Good to see you! Yeah we are doing video visits nowadays. There's a lot we can do through that! | What can I help you with?

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Advantages and Disadvantages of Telehealth

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Advantages and Disadvantages of Telehealth

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This video offers a really concise yet thorough summary of the various advantages and limitations of telehealth. Telehealth is able to expand access to care, such as in rural areas and in communities that lack providers. Telehealth is also more convenient for some patients given the fact that it reduces the need to leave work and cuts down on transportation time where patients can have their doctors visits from the comfort of their own home or office. Telehealth can also reduce stress that can accompany in-person visits and even alleviate phenomena such as white coat syndrome that results from nerves when patients are in the presence of medical professionals. However, with the vast amount of benefits, there are also potential limitations as well. This video brought up on limitation that I had never considered before which was that telehealth can contribute to over-utilization of care given that patients are able to get immediate access whenever they need it, even if a condition can resolve on its own.

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This TED Talk was a really interesting explanation of how the unprecedented COVID-19 pandemic impacted the rapid growth of telehealth and telemedicine. I will always remember the first telehealth appointment I had. I had been exposed to COVID-19 by a friend and had to get a COVID test. At the time, COVID tests were less available, so I had to schedule a virtual appointment with a provider to have them order a test for me. I remember not knowing what to expect from this visit and being nervous to have to explain my situation to a provider that I was unfamiliar with. However, the process went smoothly and I remember leaving thinking about how easy it was to meet with the provider through the computer and be able to get a drive through test within the next hour. Since then, I have had several virtual appointments and have gotten really comfortable in getting medical care through telehealth visits.

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The COVID-19 Telehealth Accelerator | Jack Miner | TEDxTraverseCity

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Prior to the asynchronous work this week, I had never heard of the term "gamification." However, I was really intrigued to learn about how gamification can be utilized in the healthcare setting to allow for an increased collection of data and better understanding of various health conditions. I also enjoyed learning about tools such as Jerry the Bear that can be utilized in the pediatric population to help kids better understand their diagnoses and to better learn how to manage their conditions.

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When researching other similar apps to those discussed this week, I came across an app called Empower by the company "Ayogo." The Empower app helps patients develop new behavioral habits specific to their condition. Patients using this app are required to check in daily and are assigned small tasks that over time are expected to result in better habits and improved health outcomes.

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ayogo | experts in patient perceived self-efficacy

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Ayogo's GoalMama gives Nurse Family Partnership nurses realtime insight into the self-efficacy of their program members, enabling NFP's mission to empower first-time moms to transform their lives and create better futures for themselves and their babies.

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Mango Health was another app that I came across that functions to issue reminder alerts to patients to take their medications throughout the day. In addition to the set reminders, patients using the app have the ability to earn points and redeem the points for gift cards to a variety of stores and businesses. It is thought that through adding a reward component to the app, patients will be more likely to adhere to their medication regimens and have enhanced health outcomes.

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Boston Hospital Aims to Fight Alarm Fatigue

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Boston Hospital Aims to Fight Alarm Fatigue

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This news story centers around Boston Medical Center's 2014 efforts to reduce alarm fatigue in their staff. Working on a medical-surgical unit, I have had first hand experience with alarm fatigue be it the call lights, bed alarms, IV pumps and telemetry monitors. It is so hard to differentiate false alarms from those that need immediate action. I was interested to learn that in 2014, The Joint Commission even made reducing alarm fatigue a national safety goal. I think there is still work to be done but even something as simple as taking the time to adjust manufacturer settings on machines to only alert to critical events can be a useful first step to promoting patient safety by reducing alarm fatigue.

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Boston hospital alarm fatigue technique held up as national model

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Implementation of Expanding Patient Access to Health Records

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Implementation of Expanding Patient Access to Health Records

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This video is a recording of a virtual meeting regarding challenges to implementation of patient access to health records. Although the video itself is rather long and drawn out, there are a variety of interesting points made regarding all of the different factors and considerations that go into creating a way for patient's to have this increased access. For instance, it is important to consider what information they have access to and how quickly they have access to that information. As we discussed in previous weeks, the immediate access that patients have to portals such as MyChart can create unnecessary stress and anxiety when patients have access to test results and notes before providers can review and explain them to the patient. This presentation really made me consider how much work goes into ensuring that health records are compliant with new laws and regulations requiring that patient's have immediate access to their health records.

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Patient access to health records: What are the challenges to implementation?

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This video gave explanation into new apps that all aim to expand access to medical care through patient's cell phones. Uber Health was developed to help patients get rides when necessary to get to appointments if they are unable to find transportation. Medici functions to quickly connect patients to a variety of providers through video chat or even text to help accelerate care and promote quick outcomes. Ada functions as an improved Google/WedMD where patients can input their symptoms and Ada asks appropriate follow up questions to determine what may be causing symptoms and guide patients in an appropriate direction. Lastly, Ginger IO serves to quickly connect patients to licensed therapists or mental health coaches even on nights, weekends and holidays.

All of these apps aim to function on the existing technology that patients have and are comfortable with on their cell phones to improve access to care. I was surprised to learn that most of these apps are free of cost and that with Ginger IO for example, can be covered through company insurance benefits. These apps are all a step in the right direction for improving access to care through telehealth and telemedicine.

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3 Apps that Will Change the Way You Think About Healthcare

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MyChart and Patient Access to Medical Records

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MyChart and Patient Access to Medical Records

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In my current RN role, my facility has implemented MyChart through Epic to give patients immediate access to their medical records. Among such records are lab values, provider and nurse notes and other documentation of care. When patients are discharged from our floor, their discharge paperwork automatically prints out with an access code and detailed instructions on how to access MyChart if Epic recognizes that the patient was not already registered. Although I think that this is an excellent concept and resource for patients to be able to gain control and access over their care and medical records, I have also seen first hand the downfalls of this software in which patients can be prone to unnecessary anxiety and stress when test and lab results are posted to their portal before a provider has had a chance to come review and explain the meaning to them. I think that more tweaking is definitely necessary to allow patients access to their records while also giving providers and nurses some breathing room when test and lab results are posted.

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MyChart lets you see your medications, test results, upcoming appointments, medical bills, price estimates, and more all in one place, even if you've been seen at multiple healthcare organizations.

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Gamification to Help Teach Kids about Emergency Preparedness

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Gamification to Help Teach Kids about Emergency Preparedness

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The American Red Cross has developed the Monster Guard App as a free way to help kids ages 7-11 prepare for real-life emergencies such as home fires, tornadoes and floods. In the app, kids can accomplish a variety of tasks including:

- Play through 14 fun training sessions
- Role-play as 5 different characters in simulated training environments
- Beat high scores and earn badges
- Learn about preventing home fires and wildfires
- Prepare for emergencies like tornadoes, earthquakes,
hurricanes, and floods
- Gather supplies for a family emergency supplies kit
- Learn how to cope with stressful situations
- Watch fun animations packed with important information

I found this to be a really unique but important concept. Especially now with the COVID-19 pandemic and with kids home more than they are at school or in the real world, it is important to continue to promote safety in the case of an emergency. Monster Guard serves to empower these kids to have control over the unexpected and to know what to expect if the unexpected were to happen.

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Red Cross Suggests FREE Monster Guard App for Housebound Families

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HIPAA stands for the Health Insurance Portability and Accountability Act (1996) and aims to limit access to protected health information (PHI) from misuse. This video surprised me when it listed off all 18 categories of protected health information ranging from names and email addresses to phone numbers and health records. Having worked as both a nursing assistant and a nurse, I have become very familiar with the requirements of HIPAA in the hospital setting. I know that on my unit in particular, we have special bins (we call them "HIPAA Hoppers") where we can safely dispose of documents with patient identifying information on it. Also, with recent restrictions placed on patient visitors, we have had to become more cautious of who we given information to regarding patient care. On admission, we alway make sure to ask patients who we can give updates and information to if someone were to call for an update. We also give patient's the opportunity to have "confidential encounters" where no information at all can be shared with anyone. I was really surprised and shocked to learned that HIPAA violations can result in fines of up to $250,000. As a patient, this gives me piece of mind in knowing my information is protected, but as a nurse and future provider, makes me nervous of ever coming into violation of HIPAA rules and regulations.

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What is HIPAA? [HIPAA + Violation Penalties Explained]

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127.4K Likes, 971 Comments. TikTok video from Steveioe (@steveioe): "HIPAA 😌 #MuFKR". original sound.

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When watching the asynchronous lectures this week, in a discussion about HIPAA, FERPA (The Family Educational Rights and Privacy Act (1974)) was also mentioned as a similar concept, but one that can be applied to schools. The HIPAA Security Rule requires appropriate administrative, physical and technical safeguards to ensure the confidentiality, integrity, and security of electronic PHI while FERPA is in place to protect the privacy of student education records and designates rights for students and their parents. I distinctly remember in high school, when I was applying to colleges and requesting letters of recommendation from my teachers, I had to sign a FERPA waiver to waive my right to read what my teachers had written about me. I was really interested to learn about how the concepts of HIPAA and protection of information can apply to other fields outside of healthcare.

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HIPAA and FERPA are both federal laws designed to protect the privacy and security of individuals. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) applies to the healthcare industry where the Family Educational Rights and Privacy Act of 1974 (FERPA) applies to the education industry.

provides privacy and security for protected health information (PHI). Created by the U.S. Department of Health and Human Services ( ), the HIPAA Privacy Rule protects sensitive patient information by setting forth patient rights and standards for health plans, health care clearinghouses and health care providers who collect and store patient identifiable information in electronic form. The HIPAA Security Rule requires appropriate administrative, physical and technical safeguards to ensure the confidentiality, integrity, and security of electronic PHI.

is in place to protect the privacy of student education records and designates rights for students and their parents. According to the Department of Education, education records include such information as academic report cards, transcripts, class schedules, disciplinary records, contact information, and family information. The law applies to all schools that receive funds under an applicable program of the U.S. Department of Educatons. FERPA gives parents certain rights with respect to their children's education records. These rights transfer to the student when he or she reaches the age of 18 or attends a school beyond the high school level.

The HIPAA Privacy Rule does not typically apply to primary and secondary schools. In grades K-12, student health records are considered to be educational records. This consideration is either because student health information in education records is protected under FERPA or because the school is not a HIPAA-covered entity. In fact, FERPA applies to most public and private postsecondary institutions and to student records at campus health clinics of these institutions. In that case, they are either referred to as education records or treatment records under FERPA and therefore are excluded from the HIPAA Privacy Rule, even when the school is a HIPAA-covered entity.

In the case where a health plan at a higher education institution is treating nonstudents, they are still not considered to be bound by HIPAA unless they transmit health care information in electronic form in connection with the submission of claims for payment.

Regardless of whether HIPAA or FERPA applies, state laws concerning privacy need to be considered as well. State laws are more specific and rarely conflict with HIPAA or FERPA. And, if more than one law is applicable, the more stringent one typically applies.

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What is the Difference Between HIPAA and FERPA?

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HIPAA and FERPA are both federal laws designed to protect the privacy and security of individuals. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) applies to the healthcare industry where the Family Educational Rights and Privacy Act of 1974 (FERPA) applies to the education industry. HIPAA provides privacy ...

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When going over the asynchronous material from this week, considering the concept of data analysis was really overwhelming to me. This was something I spent a lot of time in during my undergraduate degree when I was studying biology, so I also found it interesting to see how data analysis can be applied to the field of informatics and nursing in particular. I am very used to being able to plot data on charts and try and visualize data and trends but I still find it overwhelming to apply such large data sets, as is the case with those in healthcare and apply it to patient care. I found this video to be really interesting to hear about the role of a healthcare data analyst and how this particular analyst utilizes data to draw larger conclusions to guide interventions in healthcare.

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From my undergraduate biology studies, I remember how difficult it was to take all the gathered data from labs and experiments and determining what the best way to visually organize and present it was to uncover trends. I found this video to be a really concise, yet helpful, explanation of some tips and tricks for how to better visualize data. I think it is important to note that without proper ordering and structure, data is just a bunch of meaningless numbers. Knowing how to assign meaning to these numbers is what allows for the those in the field of informatics to draw conclusions and initiate interventions based on the gathered data.

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Data Visualization: 9 Actionable Tips You Can Use Now

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Prior to going over the material from this week, data storytelling was something entirely foreign to me. After watching the TED Talk that was posted in the asynchronous work, I wanted to do some more research on the use of data storytelling in informatics. I found this article posted through Harvard that was a really well-written explanation of the field. I think that being able to see data and then organize it into a way that can be visualized and assigned a narrative is what makes data so powerful. This field is incredibly important to being able to utilize data to initiate change through putting it into comprehensive forms such as in images, charts and narrative.  I know that personally, if I am given a lot of charts and graphs to look at that are just numbers and plotted points, it is sometimes difficult to understand what they are trying to convey. I think it is so important to give meaning to the data through data storytelling to better get points across and convince others to take actions.

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When you hear the term "data analysis," what do you think of? Your mind may jump to scouring spreadsheets, implementing algorithms, and making mathematical calculations-all "hard skills" of data analysis. Yet, hard skills are useless without their soft skill counterparts. It's not enough to just analyze data; you need to know how to communicate the story it tells in a clear, compelling manner-a skill called data storytelling.

According to the Bureau of Labor Statistics, the demand for research analysts is expected to grow 25 percent between 2020 and 2030, much faster than the average across all industries. Many companies have begun including data storytelling as a required skill in analyst job descriptions, while others have opted to hire for data storyteller positions to supplement their existing analytics teams' abilities. Possessing the skills to both analyze data and communicate its insights can help you stand out as a well-rounded candidate.

Here's a primer on the key components of data storytelling, why storytelling is an impactful communication tool, and how to craft a compelling narrative of your own.

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What Is Data Storytelling?

Data storytelling is the ability to effectively communicate insights from a dataset using narratives and visualizations. It can be used to put data insights into context for and inspire action from your audience.

There are three key components to data storytelling:

1. Data: Thorough analysis of accurate, complete data serves as the foundation of your data story. Analyzing data using descriptive, diagnostic, predictive, and prescriptive analysis can enable you to understand its full picture.

2. Narrative: A verbal or written narrative, also called a storyline, is used to communicate insights gleaned from data, the context surrounding it, and actions you recommend and aim to inspire in your audience.

3. Visualizations: Visual representations of your data and narrative can be useful for communicating its story clearly and memorably. These can be charts, graphs, diagrams, pictures, or videos.

Data storytelling can be used internally (for instance, to communicate the need for product improvements based on user data) or externally (for instance, to create a compelling case for buying your product to potential customers).

The Advantages of Data-Driven Decision-Making

The Psychological Power of Storytelling

Humans have told stories since the Cro-Magnon era to communicate with others for survival and record accounts of daily life. While storytelling methods have come a long way since the days of cave paintings, its psychological power holds true tens of thousands of years later.

The brain's preference for stories over pure data stems from the fact that it takes in so much information every day and needs to determine what's important to process and remember and what can be discarded.

When someone hears a story, multiple parts of the brain are engaged, including:

Wernicke's area, which controls language comprehension

The amygdala, which processes emotional response

Mirror neurons, which play a role in empathizing with others

When multiple areas of the brain are engaged, the hippocampus-which stores short-term memories-is more likely to convert the experience of hearing a story into a long-term memory.

Rather than presenting your team with a spreadsheet of data and rattling off numbers, consider how you can engage multiple parts of their brains. Using data storytelling, you can evoke an emotional response on a neural level that can help your points be remembered and acted upon.

How to Craft a Compelling Data Narrative

Data storytelling uses the same narrative elements as any story you've read or heard before: characters, setting, conflict, and resolution.

To help illustrate this, imagine you're a data analyst and just discovered your company's recent decline in sales has been driven by customers of all genders between the ages of 14 and 23. You find that the drop was caused by a viral social media post highlighting your company's negative impact on the environment, and craft a narrative using the four key story elements:

1. Characters: The players and stakeholders include customers between the ages of 14 and 23, environmentally conscious consumers, and your internal team. This doesn't need to be part of your presentation, but you should define the key players for yourself beforehand.

2. Setting: Set the scene by explaining there's been a recent drop in sales driven by customers of all genders ages 14 to 23. Use a data visualization to show the decline across audience types and highlight the largest drop in young users.

3. Conflict: Describe the root issue: A viral social media post highlighted your company's negative impact on the environment and caused tens of thousands of young customers to stop using your product. Incorporate research (such as this article in the Harvard Business Review) about how consumers are more environmentally conscious than ever and how sustainably-marketed products can potentially drive more revenue than their unsustainable counterparts. Remind the team of your company's current unsustainable manufacturing practices to clarify why customers stopped purchasing your product. Use visualizations here, too.

4. Resolution: Propose your solution. Based on this data, you present a long-term goal to pivot to sustainable manufacturing practices. You also center marketing and public relations efforts on making this pivot visible across all audience segments. Use visualizations that show the investment required for sustainable manufacturing practices can pay off in the form of earning customers from the growing environmentally conscious market segment.

If there isn't a conflict in your data story-for instance, if the data showed your current marketing campaign was driving traffic and exceeding your goal-you can skip that element and go straight to recommending that the current course of action be maintained.

Whatever story the data tells, you can communicate it effectively by formatting your narrative with these elements and walking your audience through each piece with the help of visualizations.

Communicating the Need for Action

Data storytelling can help turn data insights into action. Without effective communication, insights can go unnoticed or unremembered by your audience; both hard and soft skills are crucial for leveraging data to its fullest potential.

Harvard Business School Professor Jan Hammond speaks to this in the online course Business Analytics, one of three courses that make up the Credential of Readiness (CORe) program.

"Always remember that applying analytical techniques to managerial problems requires both art and science," Hammond says. "Over my career, I've learned that it's the soft skills that are the hardest to master, but they're critically important."
Do you want to become a data-driven professional? Explore our eight-week Business Analytics course and our three-course Credential of Readiness (CORe) program to deepen your analytical skills and apply them to real-world business problems.

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Data Storytelling: How to Tell a Story with Data

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Data storytelling is the ability to communicate insights from data using narratives and visualizations. Here's how to effectively tell a story with data.

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When creating my infographic for the fourth assignment of the semester, I actually watched this video and found it really helpful with 7 tips on how to design infographics so that they are the most effective. After creating my infographic, I realized how much work goes into trying to convey points and statistics most effectively to the audience. Personally, I found the Canva app to be very useful in simplifying the process of creating an infographic and made it very easy to incorporate charts and images to better visualize the data. I will definitely be sure to utilize Canva in the future if I ever have to create an infographic in my future practice.

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7 Ways to Use Infographics in Healthcare + Templates

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This video presented and interesting perspective on the potential downfalls when it comes to visualizing data. I found it interesting that both pharmaceutical and veterinary studies were more likely to show positive data and leave out data that does not support their point or product. It is important to be transparent to the audience when generating data visualizations. Although leaving out negative data can make the visualization more appealing, it is important to ensure the audience is being accurately informed with all the data available.

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I found this video to provide a concise and simplified understanding of the basic concepts of ethics. Autonomy refers to the right of all persons to have a fundamental right to self-determination. Essentially, key decisions about a person's life should, if possible, be made by that person. Equality and Justice refers to the idea that all persons are equal and have the right to be treated equally. Beneficence refers to the idea that all persons have a duty to advance the good of others. Physicians should strive to do what is best for the patient, even if patents cannot afford their services. Non-malfeasance refers to the idea that all persons have a duty to prevent harm to others. This refers to the commons idea of "do no harm." Two concepts that I was unfamiliar with prior to going over the work for this week were the principles of impossibility and integrity. Impossibility refers to the concept that providers provider care under circumstances that it is possible to meet the goals of care. Lastly, integrity refers to the duty to fulfill their obligations to the best of his or her abilities, even when no one is looking.

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Prior to this week, I had only been familiar with the basic concepts of ethics. I had never heard of the concept of ethics specifically designed for the field of informatics and found it to be an interesting, yet necessary concept. With the field of informatics growing so rapidly, it is important to consider how data can be utilized and shared in the most ethical way possible to avoid any conflicts. After learning about concepts such as the principles of information-privacy, disposition, openness and security, I was able to better understand how data can be protected in the field of informatics. The Principle of Access really made me consider patient's access to their medical records and how hospitals are required to give patient's immediate access to their charts "without delay." This concept aligns with informatic ethics in that the subject of an electronic record should have access to that record and should be able to correct that record if needed. I will always think back to these concepts as I enter into my future practice as an FNP and will have to consider how the data I collect for patients will be utilized and applied.