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Ethics: Yes, Even When Nobody is Watching

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Ethics: Yes, Even When Nobody is Watching

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Since we talked about ethics this week I thought this video is perfect for it. It explains what ethics means and how it can affect us and people close to us when "no one is watching". As a speaker gave an example of her kids seeing her behaviors and learning from her. Also, she spoke of where our personal ethics come from. I can see how it can relate to medical professionals since sometimes our job is dependent on ethics and sometimes "no one is watching".

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Ethics: Yes, Even When Nobody is Watching | Dawne Ware | TEDxFairfieldUniversity

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This week we learned about legal and ethical issues in nursing. In healthcare, we have ethical parameters to follow and we must keep patients protected by keeping their health information private. It is critical to understand the standards of care, adhere to evidence-based recommendations, and prioritize the patient. This website talks about 6 ethical issues in healthcare that arose in recent times.

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"First, do no harm." The seemingly simple maxim of healthcare proves far more complex when considered in the context of rapidly advancing medical technology, constant budget constraints, and new health threats. At a time when emerging technologies such as big data and artificial intelligence (AI) are challenging the fundamental notion of what a healthcare provider is, the battle to stop a worldwide pandemic reveals just how difficult ethical issues in healthcare can become when resources are strained.

How do you test the efficacy of a new medical technology without harming patients? Who gets care when the number of patients exceeds a hospital's capacity? What organizations should have access to data that can predict a patient's future health issues? Deliberating such complex practical and moral issues is a constant challenge in healthcare administration, and medical professionals can benefit greatly from training in ethical issues and public policy.

Here are just six of the major ethical issues facing the healthcare industry in 2020. Each issued-based section includes related questions that highlight specific challenges that leaders face when making day-to-day medical decisions and far-reaching policies that affect patient health.

Taking Advantage of Big Data Without Dehumanizing Patients

Medical professionals routinely make difficult decisions, including life-or-death calls, for patients and their families. They rely on extensive scientific training and increasingly sophisticated technology to do so, but their experience, instincts, and knowledge of individual patients also guide them. The increasing role of big data and predictive analytics in medical decision-making raises questions about the ethics of big data in healthcare - specifically whether data-driven decisions risk dehumanizing patients.

The term "big data" refers to the proliferation of digital information in the modern age. Advances in data storage and processing technology have dramatically changed the speed and volume of data analysis capabilities and given rise to predictive analytics. Such analysis promises more accurate diagnostic and therapeutic assessments, but assessments based purely on technology and data, no matter how accurate, lack an essential human touch. Imagine, for example, a decision to end treatment of a loved one's terminal illness based solely on a predictive score produced by an algorithm.

As healthcare data collection technology advances, the industry faces questions about how to handle automatically collected data. Many modern medical devices are capable of reporting an incredible variety of health information, with or without a patient's knowledge. For example, digital pills, also known as smart pills, are pharmaceuticals that contain an ingestible sensor that transmits data after the pill is consumed.

The first digital pill to be approved in the United States was a form of the antipsychotic medication aripiprazole (sold under the trade name Abilify) in 2017. A digital sensor in the pills is activated by the patient's stomach acid and generates an electrical signal that's picked up by a patch on the rib cage and then transmitted to a smartphone app. The technology offers a promising benefit for treating patients who struggle with medication adherence, but critics cite concerns about who should have access to such data and how it can be protected.

The advent of predictive and prescriptive algorithms that can analyze large amounts of data also increases the potential privacy risks associated with stored medical specimens. Medical researchers have long collected and stored blood and tissue samples for future research, but the value of biological samples has increased as advances have been made in genetics, genomics, and biotechnology.

Reusing stored biological samples and data collected from research participants in past studies, as well as samples collected from patients for clinical or diagnostic purposes, raises new issues about the responsibility of healthcare providers to obtain informed consent. A patient may give permission to a healthcare provider or clinical researcher to use a tissue sample for one test, for example, but have no control over its use in future projects.

Ethical Considerations

What is the best way to acquire a patient's informed consent to the use of predictive analytics and other advanced analyses techniques that are based on the patient's private data?

What are the ethical limitations on the use of data that is collected automatically by digital pills and other medical devices and technologies that report sensitive data, sometimes without the patient's knowledge?

Do current policies and regulations related to biospecimens offer adequate privacy protection to patients?

Safeguarding Patient Privacy When Using Population Health Data

The digitization of patient information provides enormous benefits. Electronic health records (EHRs) create a centralized, shareable record of a patient's entire medical history; allow for the automation of healthcare provider workflows; and enable advanced medical assessment tools. Because they hold large amounts of very personal data, they also carry the risk of privacy violation. Protecting patient data is a core responsibility of healthcare providers, and the federal law restricting release of medical information strictly regulates the handling of sensitive patient health information, but the field of population health complicates issues of patient privacy.

Population health is the analysis of health outcomes of large groups of people. The use and effectiveness of population health is increasing in the era of big data, which can be used to find links between diseases and specific environments or socioeconomic groups. Population health can discover widespread health problems or locate segments of the population that have a particularly high occurrence of a disease, for example.

Sharing patient data for secondary purposes, such as population health programs, requires either consent from the patient or anonymization of the data. However, even anonymized data can be misused. Through the practice of de-anonymization, or data re-identification, anonymous data can be compared with publicly available information and matched to an individual. The same information that public health officials use to diagnose, treat, and promote public policies could potentially be used by insurance companies, lenders, marketers, landlords, and employers.

Whether population health information is matched to an individual or applied in aggregate to a population, if it's used for purposes other than promoting health, it has the potential to negatively impact those who supplied the data. An analysis that reveals a high rate of a disease in a given population could be used to focus education and treatment efforts; it could also be used to adjust insurance coverage.

Ethical Considerations

What protections could be put in place to safeguard the de-anonymization of patient data?

How can patients be protected from the negative effects of inherent bias in the algorithms used to analyze public health data?

What level of control should individual patients have over the use of their private health information that becomes part of public health databases?

Ensuring Equal Access to Customized Medicine

Customized medicine refers to the creation of bioidentical limbs and organs to replace injured or missing ones. Biological 3D printers can create limbs and organs customized for a patient's body, and scientists use DNA mapping to "grow" organs that are genetically identical to a patient's own cells, according to Electronic Health Reporter.

The related field of precision medicine, or personalized medicine, also uses genomic data. Precision medicine doesn't describe drugs or medical devices designed specifically for unique patients, but rather the tailoring of treatments to the individual characteristics of patients that have been classified using big data analytics and population health.

Enabled by advances in the understanding of how unique molecular and genetic profiles make an individual susceptible to a particular disease, personalized medicine has applications in risk assessment, prevention, detection, diagnosis, treatment, and management of diseases.

Customized medicine and other advanced treatments raise issues of income inequality and equal access to healthcare. Advances such as DNA mapping and bioidentical organs hold the potential to lengthen lives dramatically, but treatments that are prohibitively expensive for many or most patients violate the tenets of health equity.

Ethical Considerations

How can healthcare providers ensure equitable access to expensive technologies that not only treat illnesses but also promise to promote longevity and enhance patients' quality of life?

What are the ethics of cost/benefit analyses when human lives are at stake?

What policies could help avoid "genetic discrimination" when medical test results reveal conditions or genetic susceptibilities to specific diseases that weren't the subject of the original tests?

Reconciling Patient Care Decisions with Financial Management

One of the constant ethical challenges facing healthcare administrators is how to make capital allocations that strike a balance between patients' medical needs and fiscal responsibility. Health administrators responsible for healthcare finance management decisions may be put in a position to question, for example, whether a drug needs to be prescribed or an imaging test needs to be done. Even efforts to reduce waste and inappropriate use of resources, critical aspects of responsible fiscal stewardship, can unintentionally impinge on patients' best interests.

The sometimes conflicting responsibilities of supporting optimal patient outcomes and fiscal responsibility can lead to a state of "moral injury." Describing the injury of a person's moral conscience and values resulting from the experience of committing a moral transgression, moral injury results in feelings of shame and guilt. The risk of moral injury can be particularly high in a profit-driven healthcare environment where multiple factors other than patient care influence treatment decisions.

Ethical Considerations

What is the right balance between meeting the medical needs of patients and maintaining fiscal responsibility when making decisions about capital allocation?

How can healthcare administrators address waste and inappropriate use of resources without impinging on the medical decisions made by healthcare providers in the best interests of their patients?

What steps can be taken to address the moral injury that many healthcare providers feel when they're forced by economic considerations to make decisions that go against their moral beliefs and their own expectations?

How can a sense of ethics be instilled in the day-to-day decision-making of healthcare workers in medical departments and in administrative roles?

Implementing Artificial Intelligence and Robotics Ethically

The growing use of AI and robotics also raises issues of healthcare technology ethics. AI refers to the ability of computers to mimic human intelligence and learning. Potential medical applications include analysis of radiologic images. AI used for health-related predictive analysis relies on large, diverse datasets, including EHRs.

However, the ability of AI-powered tools to analyze virtually any dataset, from income data to criminal records, raises concerns about its potential for abuse. The Genetic Information Nondiscrimination Act of 2008 prohibits employers and health insurers from considering genetic information when making decisions such as hiring and firing or health insurance eligibility. However, the law doesn't apply to nongenetic predictive data.

Robotics are already heavily used in healthcare; robot-assisted surgeries are now commonplace, and robotic prosthetics are advancing rapidly. However, some see a future where robots care for the sick and elderly and robotic enhancements provide patients with superhuman capabilities - applications with more problematic implications.

Robotic health workers offer a potential answer to labor shortages, but their use could dehumanize those they're meant to serve and those they replace. The evolution of robotics in healthcare beyond compensatory measures and into human enhancements raises issues of access and fairness for patients and challenges the definition of a healthcare provider.

Ethical Considerations

What procedures are in place to ensure that AI, robotics, and other advanced technologies are adopted only after they're proven to be effective in meeting the healthcare needs of patients?

How much say should patients have in the use of advanced technologies as part of their medical treatment?

Will predictions about a patient's future health generated by AI systems be made available to insurance companies and other third parties?

What effect will AI-based medical care have on the relationship between patients and their doctors and other healthcare providers?

Devising Ethical Responses to Pandemics and Other Widespread Medical Emergencies

The outbreak of the COVID-19 virus provides a grim illustration of ethical issues in pandemic planning and response. When the World Health Organization (WHO) declared COVID-19 a pandemic in March 2020, tens of thousands of cases had been confirmed across more than 100 countries. The daily loss of life caused by the virus created an immediate healthcare crisis, prompting a rush to develop a vaccine and the enactment of social distancing measures in countries around the world.

A rapid response during pandemics is crucial, but rushing healthcare efforts can add risk to processes such as drug trials. Deciding how much risk is justified under the circumstances is an ongoing debate. Lacking a vaccine, public health officials have fought the outbreak with social distancing measures that slow the spread of the disease, helping to mitigate outbreak spikes that overwhelm medical facilities and ultimately result in more lives lost.

When determining how strict such measures should be, lawmakers and public health officials must balance the good of communities against individual liberties, a literal life-and-death decision with substantial financial, political, and social ramifications.

When pandemics and other widespread medical emergencies do overwhelm the capacity of medical facilities, even starker ethical questions arise. Healthcare professionals, who are themselves at risk of infection, may be forced to decide which patients should receive treatment or access to lifesaving equipment and treatment when need exceeds capacity.

Ethical Considerations

How should healthcare providers decide who gets treated when the demand for their services outstrips their capacity to supply them to all patients who are in need?

How can healthcare professionals protect against age bias and other forms of discrimination when making these decisions?

In the race to develop vaccines and treatments for deadly diseases, such as COVID-19, how does the healthcare industry ensure that the potential risks to patients and caregivers of these new treatments are properly balanced with the potential rewards they promise?

What role do healthcare providers play in devising and enforcing policies, such as social distancing measures, that restrict the freedoms of their patients?

Combining the Science of Health with the World of Business

Addressing the difficult ethical issues influencing the science and business of healthcare requires leaders with exceptional knowledge and skills. Whether forming technology ethics committees, fostering greater collaboration between healthcare administrators and clinicians, or influencing regulations that protect the use of personal information and predictive data, such leaders support ethical healthcare while balancing medical and financial responsibilities.

With courses in innovation, strategy, and ethical issues and public policy, AdventHealth University Online's Master of Healthcare Administration in Strategy and Innovation and Master of Business Administration (MHA/MBA) Dual Degree program develops strategic thinkers and leaders capable of making significant impacts and initiating positive change. Find out more about how this unique program offered through a partnership between AdventHealth University Online and Stetson University is creating leaders to shape the future of the healthcare industry.
Recommended Readings AdventHealth University and Stetson University Announce Partnership and MHA/MBA Dual-Degree Healthcare Administration: Salary, Careers, and Education MHA vs. MBA: What Are the Differences? Sources: American Medical Association, The Top 10 Ethical Issues Medical Students Should Be Taught BMC Medical Ethics, "Addressing Harm in Moral Case Deliberation: The Views and Experiences of Facilitators"BMC Medical Ethics, "Broad Consent for Biobanks Is Best - Provided It Is Also Deep"BMC Medical Ethics, "Digital Pills: A Scoping Review of the Empirical Literature and Analysis of the Ethical Aspects"BMC Medical Ethics, "Do Patients and Research Subjects Have a Right to Receive Their Genomic Raw Data? An Ethical and Legal Analysis"Deloitte Insights, "Using Predictive Analytics in Health Care"Electronic Health Reporter, "First Do No Harm: The Ethics of Healthcare in 2020"GINAhelp.org, Genetic Information Nondiscrimination Act Healthcare Financial Management Association, "Beyond Compliance: Healthcare CFOs Face Many Situations in Which Ethics Can Guide Decision-making"HealthITAnalytics, "What Are Precision Medicine and Personalized Medicine?"HealthTech, Medical Xpress, "Artificial Intelligence in Medicine Raises Legal and Ethical Concerns"National Center for Biotechnology Information, "Considerations for Ethics Review of Big Data Health Research: A Scoping Review"RoboticsBiz, "8 Ethical Issues in the Use of Robotics in Healthcare"STAT, "Research in the Time of Coronavirus: Keep It Ethical"The Conversation, "The Coronavirus Pandemic Is Forcing Us to Ask Some Very Hard Questions. But Are We Ready for the Answers?"The Hasting Center, "Why Health Care Organizations Need Technology Ethics Committees"The Medical Futurist, "The Most Pressing Issues in Bioethics"The New York Times The Washington Post The Washington Post U.S. News & World Report, "Why Will It Take So Long for a COVID-19 Vaccine?", "U.S. Hospitals May Have to Ration Care During the Pandemic. Here's One Approach.", "Too Many Tests, Too Little Time: Doctors Say They Face 'Moral Injury' Because of a Business Model That Interferes with Patient Care", "First Digital Pill Approved to Worries About Biomedical 'Big Brother'" "How Predictive Analytics in Healthcare Is Improving Patient Care"

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At a time when emerging technologies such as big data and artificial intelligence (AI) are challenging the fundamental notion of what a healthcare provider is, the battle to stop a worldwide pandemic reveals just how difficult ethical issues in healthcare can become when resources are strained.

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Engaging Students with Visual Stories: Using Infographics in Nursing Education

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Engaging Students with Visual Stories: Using Infographics in Nursing Education

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Infographics can help capture attention and make complex knowledge understandable, making it a useful teaching/learning strategy. Although infographics can be effective to engage students, they are infrequently used because of educator inexperience with this technology. This article gives a general overview of using infographics in nursing education and includes resources for developing and spreading infographics as well as step-by-step instructions based on evidence.

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Engaging Students with Visual Stories: Using Infographics in Nursing Education

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Infographics represent visual stories which engage and guide audiences to the realization of patterns, relationships, and conclusions. Infographics he...

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This week we learned about visualizing data and infographics. Just like storytelling, infographics can be very useful. Also, there are multiple types of infographics that can be used that are described in this video. Using infographics can be a quick way of quickly understanding data. It is also a more interesting way to observe information.

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9 Ways Businesses Are Channeling the Power of Data

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9 Ways Businesses Are Channeling the Power of Data

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One of the things I learned this week was how data can be used to convince people using numbers. Collecting meaningful data and sharing it with the right software can be very persuasive. This not only applies to healthcare but even businesses that sell cars.

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From the outside looking in, technology careers can almost seem like mystical jobs, where every employee is working on an innovative project that will profoundly shape our future. While this can sometimes be the case, it's important to remember that many technology careers also have practical applications for life and work today.

The field of data analytics is changing business best practices in industries from manufacturing to marketing. "Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more informed business decisions," says Pushpraj Kumar, business analyst at iFour Technolab.

You know this tech career is important, but you're still not clear on exactly how data analytics shapes the decisions organizations make on a daily basis. We spoke with experts to bring you nine data analytics examples in a variety of industries. Prepare to be surprised as you see how far-reaching a career in data analytics can be!

What is data analytics?

Before we talk about how data analytics is being used, you need to understand what it is. Data analytics may seem complicated, but the idea behind it is actually quite simple: It's the process of sorting through raw data to find meaningful patterns. Data analytics is a powerful decision-making tool that allows business leaders to have all the information they need to move their organization in the right direction.

"There are oceans of useless raw data around us, and it is data analytics that closes the gap by making this data useful," says Kirill Rebrov, cofounder of Demografy. Data analysts use a variety of tools and technologies to gather all sorts of data, like statistics about how much time users spend on a website, demographic information about customers or traffic patterns in a city.

Kumar shares that there are four main types of data analysis:

Descriptive analytics reveal what happened in the past

Diagnostic analytics answer why something happened

Predictive analytics tell what will probably happen in the future

Prescriptive analytics show what actions should be taken to make progress or avoid problems in the future

Once that data has been gathered and organized, it's up to data analysts to interpret it according to the four types of data analytics. "Data can tell many different stories. The analysis lens you use will determine the outcome," says Ryan Prestel, cofounder and CEO of JadeTrack.

9 Exciting examples of data analytics driving change

Businesses in every type of industry can harness the power of data analytics. "There are entire industries most people never think about for a career that leverage analytics skills," says Jen Hood, analytics coach at The Career Force. These are just some of the ways business across various industries are putting data to work.

1. Increasing the quality of medical care

Healthcare facilities across the nation are making use of data analytics to provide higher-quality care and improve patient outcomes. One organization "analyzed data to predict negative health events that seniors could experience from home care," Kumar says. Thanks to their data analysis, they were able to significantly reduce the number of patient hospitalizations and ER visits.

That's just one example. With the implementation of electronic health records systems and an increasingly digitized healthcare system overall, there are worlds of opportunity for data-based innovations and advancements within the medical field.

2. Fighting climate change in local communities

Many local governments are dedicated to fighting the effects of climate change by creating a more sustainable community. It's a goal they couldn't achieve without help from data analytics. "By providing transparency to city-wide sustainability analytics, such as water use, energy use, waste and recycling and emissions, the entire community can do its part to improve energy efficiency and accelerate climate action efforts," Prestel says.

3. Revealing trends for research institutions

Organizations that conduct research using polls or surveys rely on strong data analytics to find patterns in their results. "Data analytics is vital in analyzing surveys, polls, public opinion, etc. For example, it helps segment audiences by different demographic groups and analyze attitudes and trends in each of them, producing more specific, accurate and actionable snapshots of public opinion," Rebrov says.

4. Stopping hackers in their tracks

Cyber security is increasingly important in our digital world. Data analytics-sometimes called security analytics in this field-helps these professionals protect businesses and individuals from hackers. "Data sets are gathered and analyzed in order to create improved detection of threats and create a proactive way of dealing with those threats," says Will Ellis, founder of Privacy Australia and IT security consultant.

5. Serving customers with useful products

Companies that create and sell products drill into their data to learn more about what their customers are looking for. Data analytics gives product developers insights into things like customers' budgets and the features they want to see before making a purchase. The work of data analysts influences everything from the design of next year's trendiest baby stroller to the features of a new luxury sedan.

6. Driving marketing campaigns for businesses

Marketing and data analytics often go hand in hand. Marketing teams refer to data analytics on a regular basis so they can gauge the success of their campaigns and make changes if necessary. "Data analytics is used by marketing teams to run targeted marketing campaigns by segmenting audiences since segmented campaigns produce higher return on investment," Rebrov says.

7. Promoting smart energy usage for utility companies

Many people don't think much about their household's energy usage, but utility companies are taking advantage of data analytics to change that. "For example, energy companies are offering customers up to one-minute real-time energy data," Prestel says. "With the ability to track performance, customers easily understand and manage their energy demand to save time and money."

8. Improving the insurance industry

Insurance companies have always relied heavily on data to make business decisions that serve customers well. Now technology advancements in data analytics are taking the industry even further.

"Data is already being used to help insurers set fairer and more accurate policy premiums, identify fraudulent claims and improve their marketing efforts," Kumar says. He adds that some companies take this further by offering programs like good-driver discounts that allow them to monitor their driving habits and use the data to reduce pricing.

9. Creating manufacturer warranties that make sense

Cars, computers and everything in between come with free or paid warranties. Many people don't realize that manufacturing companies need to carefully analyze the data about their products to offer these warranties. "Most larger manufacturers have warranty departments which rely on analysts to predict what expenses are going to be," Hood says.

Dig into the data

These data analytics examples have shown you how much of an impact this tech career can have on all types of organizations. You're intrigued by the possibilities of working in data analytics, but you still need to learn more about daily work in this career.

Dig into even more data about this job title with our article, " What Does a Data Analyst Do? Exploring the Day-to-Day of This Tech Career."

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Data Analytics Examples: 9 Ways Businesses Are Channeling the Power of Data

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From the outside looking in, technology careers can almost seem like mystical jobs, where every employee is working on an innovative project that will profoundly shape our future. While this can sometimes be the case, it's important to remember that many technology careers also have practical applications for life and work today.

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How your brain responds to stories and why they're crucial for leaders

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How your brain responds to stories and why they're crucial for leaders

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This TED talk talks about how storytelling can affect people. Stories are a great way to connect to other people and for example, when stakeholders feel connected to you it might be easier to persuade them. Stories make our whole brain "light up" and experience things that we are told about. When we are at the movie theater we might experience elevated heart rates to the things we see on the screen. It is also a critical skill for a leader and the act of storytelling helps people to trust you more.

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Karen Eber: How your brain responds to stories -- and why they're crucial for leaders | TED

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One of the things he talks about in this TED talk is that usually, data in healthcare isn't easy to access because of privacy reasons. As said in the video, this can prevent researchers from accessing the data they need for cancer and others. Even though data needs to be encrypted and not shared, sometimes it might be a bad thing.

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Privacy Issues & Technology in Healthcare Organizations

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Privacy Issues & Technology in Healthcare Organizations

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This article does a great job of addressing privacy concerns within healthcare. For example, health privacy has become increasingly important due to the rapid rate of technology integration in healthcare. New technologies like mobile apps allow you to view test results or past medical history. Now we are able to track substantially larger amounts of information about a patient than ever before and put it in an easy-to-access place such as a cloud-based service.

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March 17, 2022 - The use of artificial intelligence (AI) in the delivery of health care continues to grow rapidly. Access to patient medical data is often central to the use of AI in the delivery of health care. As the exchange of medical information between patients, physicians, and the care team through AI products increases, protecting an individual's information and privacy becomes even more important.

The expanded use of AI in health care has generated significant focus on the risks and safeguards to the privacy and security of the underlying data, leading to increased scrutiny and enforcement. Entities using or selling AI-based health care products need to take into account federal and state laws and regulations applicable to the data they are collecting and using that govern the protection and use of patient information and other common practical issues that face AI-based health care products.

Below, we outline several important data privacy and security issues that should be considered when creating AI-based products or deciding to use such products in health care delivery.
Data use through de-identification
The collection and use of patient health information in AI products may inevitably implicate the Health Insurance Portability and Accountability Act (HIPAA) and various state privacy and security laws and regulations. It is important for AI health care companies as well as institutions using AI health care products to understand whether HIPAA or other state laws apply to the data. One avenue to potentially avoid these regulations may be de-identifying the data before it is uploaded into an AI database.

What it means to be de-identified will vary depending on what laws and regulations apply to the data being used. For example, if the patient information is covered by HIPAA, de-identification of the protected health information (PHI) requires the removal of certain identifiers or an expert's determination that data can be considered de-identified. Even if the data is initially de-identified in compliance with the applicable standard, AI products present some unique challenges to the de-identification process.

As an AI product develops and expands, often new data elements are added to the AI system or the amount of data in a particular element is increased creating a potential for privacy issues. In some cases, the additional data is collected to address potential algorithmic bias in the AI system, as a marketable AI product should be seen as trustworthy, effective, and fair.

AI-based products create additional privacy challenges especially when de-identified data is used to try and address potential bias issues. As more data is added to the AI systems, the potential to create identifiable data also increases, especially as the increased sophistication of AI systems has made it easier to create data linkages where such links did not previously exist. As the amount and number of data elements increases, it is important to continually assess the risk that the AI systems are generating identifiable patient data where it was once de-identified.
Vendor due diligence - data access, data storage, and ransomware
Performing sufficient vendor due diligence is key before entrusting any third party with patient data, including their PHI. How the data is collected (e.g., directly from patient records) and where it is ultimately stored create two significant due diligence points. In both cases, failure to conduct appropriate due diligence can lead to legal and monetary consequences.

In the case of collection, entities allowing system access to collect data face not only legal requirements but also potentially significant liability if the data is not properly protected. AI technology is equally vulnerable to manipulation like any other technology, and networks connecting patient data with patient care should be secured. In this time of increased ransomware attacks and attackers' particular focus on health care, any external access points need to be thoroughly vetted and monitored to limit these potential threats.

In particular, examining how an entity handles access management to the data as well as ensuring the entity institutes high-level data governance and management to protect and manage the processing of the patient data should be standard in any due diligence efforts related to AI products. One other critical piece that is often overlooked is adding a high-level risk assessment and potential risk mitigation efforts to determine if the potential vulnerabilities outweigh the risk for access to such a product.

Health care entities need to critically consider, without assuming, whether direct access is the only way in which the AI product can function or provide value to the health care entity or whether there are cost-effective alternatives, such as a separate database of information that the entity pulls and populates within direct access to the main system.

In the case of storage, AI health care companies should consider these same diligence questions as any obligation of the company will generally need to be passed down to its vendors. Often, these companies may not see such vulnerabilities as high risk and would prefer to spend their limited funds in other places. But if the vendor fails to perform as needed, the reputational risk of that failure could occur and prove that ultimately the cost of such diligence is a better investment if the alternative is having your product become unmarketable because of reputational damage.
Security safeguards to protect health care data
Privacy cannot be had without security. Appropriate security safeguards must be adopted to maintain privacy as well as to build trust in the technology. Security safeguards that AI companies should be considering are:

* Enhanced compliance monitoring: Information systems and data should be audited and monitored routinely to determine if any data compromises are occurring. There are many affordable third-party products available today to help with such monitoring and should be considered as part of any information security program.

* Access controls: It is essential to understand who will have access to the data and algorithms and ensure strict controls appropriate to the level of access are provided.

* Training: Personnel and vendors must be educated on their access limitations, limitations on data use, and security obligations with regards to the data. In particular, this should include any limitations found in patient consents or authorizations.
Conclusion
There is much excitement about the benefits that AI technologies can bring into health care. Protecting data privacy is an important component in ensuring the long-term use and success of these AI products. Without patient and physician trust that these AI-based products are considering and maintaining patient data privacy, such advances may be short-lived.

Opinions expressed are those of the author. They do not reflect the views of Reuters News, which, under the Trust Principles, is committed to integrity, independence, and freedom from bias. Westlaw Today is owned by Thomson Reuters and operates independently of Reuters News.

Linda A. Malek
Linda A. Malek is a partner at Moses & Singer LLP and chair of the firm's Healthcare and Privacy & Cybersecurity practices. Her practice concentrates on regulatory, technology and business matters in the health care industry. She can be reached at LMalek@mosessinger.com.

Pralika Jain
Pralika Jain is an associate Moses & Singer's health care practice. She counsels companies at all stages of the life cycle, from formation to investment to exit, building and protecting IP, and providing strategic advice to founders and investors in connection with complex transactions. As counsel to companies and institutions in the health care and technology industries, she regularly advises on matters related to privacy and data laws across jurisdictions. She can be reached at PJain@mosessinger.com

Jason Johnson
Jason Johnson is a partner at the firm in the Healthcare, Privacy & Cybersecurity and Intellectual Property practice groups. He focuses his practice on the legal aspects of innovations in digital health, the privacy and security of data under U.S. and European laws, and the complex regulatory and compliance issues related to clinical research and business matters. His clients include academic medical centers, health care technology companies, emerging to late-stage biotechnology companies, pharmaceutical and medical device companies and other health care and research related organizations. He can be reached at JJohnson@mosessinger.com.

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Data privacy and artificial intelligence in health care

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March 17, 2022 - The use of artificial intelligence (AI) in the delivery of health care continues to grow rapidly. Access to patient medical data is often central to the use of AI in the delivery of health care.

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Understanding and fighting alert fatigue

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Understanding and fighting alert fatigue

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This website provides a lot of information on alert fatigue and includes things that can help to reduce it. As a nurse on a floor with many TELE monitors, I can say I have witnessed alert fatigue when no one is looking at the monitor because it goes off so often.

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In 2013, a 16-year-old boy at one of the US's top hospitals was given a 3800% overdose of his medication.

The hospital's built-in alert system noticed the overdose order and sent alerts to a doctor and a pharmacist. And yet, a short time later, the overdose was administered and the seizures, full-body numbness, and struggle for the boy's life began.

How could this happen-especially when the safety system caught the problem before the medication arrived at the boy's bedside?

The answer is alert fatigue.

Both the doctor and the pharmacist ignored the system's alert because that same system generates alerts for about 50% of the hundreds of prescriptions they deal with each day. They'd learned that most of those alerts were false alarms, and, as a coping mechanism, they'd started giving them a cursory glance at best.

And so a boy who should have taken a single pill took 38. And while he ultimately survived, the consequences to his health were significant.

Stories like these are common-and too often fatal-in hospitals and the aviation industry. In fact, a 2013 survey found that 19 out of 20 hospitals rank alert fatigue as their number one safety concern.

And while the risks are different, alert fatigue is also common for IT and DevOps teams as they monitor the always-on technology that drives our businesses.

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Understanding and fighting alert fatigue | Atlassian

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In 2013, a 16-year-old boy at one of the US's top hospitals was given a 3800% overdose of his medication. The hospital's built-in alert system noticed the overdose order and sent alerts to a doctor and a pharmacist. And yet, a short time later, the overdose was administered and the seizures, full-body numbness, and struggle for the boy's life began.

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This video explains how alert fatigue occurs. Some alerts we see on a day-to-day basis do not require any clinical intervention and having these unnecessary pop-ups makes it extremely difficult to slow down and read a pop-up you may actually be important. This video brings the dangers to light but shows it needs to be improved on a more technological basis and how it does not fall only on doctors and nurses to fix.

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TED Talk: The Power of Gamification in Education

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TED Talk: The Power of Gamification in Education

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Another TED Talk. This person talks about how games are important for learning especially at a young age. Learning with games was replaced with grades and tables and a specific system that makes kids bored and does not promote any learning.

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The Power of Gamification in Education | Scott Hebert | TEDxUAlberta

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This video lays out the concept of Gamification in a clear, easy-to-understand way. As a gamer myself I love games. Games combined with something useful to learn-even better. It can also be a good learning technique for people, especially kids (aka the teddy bear with diabetes and insulin game).

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This video shows all the benefits for a patient using telehealth. Parents or caregivers of elderly patients are also able to use telehealth to alleviate the stress of coming to the office. Telehealth visits also may help patients who need an in-person appointment to actually get in and be seen. There are not enough doctors around these days so it is nice that telehealth is an option for our ever-growing healthcare industry.

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This week I learned that Telehealth has been booming due to the pandemic. It is important to know what is suitable for a telehealth appointment and what is not. The legal guidelines and technical requirements need to be investigated for successful visits, as well as good communication skills. This website provides resources on information on all of that.

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The Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services defines telehealth as the use of electronic information and telecommunications technologies to support and promote long-distance clinical health care, patient and professional health-related education, public health and health administration. Technologies include videoconferencing, the internet, store-and-forward imaging, streaming media, and terrestrial and wireless communications.
Spotlight on ONC Telehealth Resources and Reports
Telehealth applications include:

Live (synchronous) videoconferencing: a two-way audiovisual link between a patient and a care provider

Store-and-forward (asynchronous) videoconferencing: transmission of a recorded health history to a health practitioner, usually a specialist.

Remote patient monitoring (RPM): the use of connected electronic tools to record personal health and medical data in one location for review by a provider in another location, usually at a different time.

Mobile health (mHealth): health care and public health information provided through mobile devices. The information may include general educational information, targeted texts, and notifications about disease outbreaks.

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The Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services defines telehealth as the use of electronic information and telecommunications technologies to support and promote long-distance clinical health care, patient and professional health-related education, public health and health administration.

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Health Information Exchange: Making a Difference

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Health Information Exchange: Making a Difference

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This video is talking about how HIE made a difference in healthcare. For example, before HIE it took a very long time to track down things that healthcare providers really needed on a real-time basis. And now HIE changed things in a positive ways such as with flooding health records aren't lost but instead they are still stored electronically.

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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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Read "Fostering Research on the Economic and Social Impacts of Information Technology" at NAP.edu

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Read "Fostering Research on the Economic and Social Impacts of Information Technology" at NAP.edu

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This website explains in dept different kinds of research that can be done and how they can be used. It might be of help when reading the dataset and not understanding how it was done. It also talks about concepts described in asynchronous lecture like Metadata.

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Read “Fostering Research on the Economic and Social Impacts of Information Technology” at NAP.edu

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Read chapter Executive Summary: The tremendous growth in use of information technology (IT) has led to an increased interest in understanding its social a…

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TED talk. How ownership of our health records can save lives

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TED talk. How ownership of our health records can save lives

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This TED talk hits home. I am an immigrant myself and can understand his frustration. He talks about how his mom had to be diagnosed with asthma once again when coming to a new country which is very upsetting considering you have to watch your loved one suffering. He also talks about limits of EHRs such as they are nation based.

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How ownership of our health records can save lives | Nima Salami | TEDxDelft

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Electronic Health Records (EHRs): How AI is improving clinician use

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Electronic Health Records (EHRs): How AI is improving clinician use

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ELECTRONIC HEALTH RECORDS (EHRS): HOW AI IS IMPROVING CLINICIAN USE

This article talks about the history of EHR and how clinical use can be improved with AI. For example, documenting takes a lot of the provider's time and things like AI-powered voice assistance can help decrease that time.

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The widespread adoption of Electronic Health Records (EHRs) has resulted in the accumulation of more medical information than ever before, with the average patient generating around 80 megabytes of clinical data per year.

One of the central justifications behind the implementation of EHRs was their perceived ability to more effectively collect and analyze this data, extracting meaningful insights and informing the decision-making process.

Despite the best intentions, and extensive Government investment, the process of EHR adoption has been challenging at best, with many studies citing them as a leading cause of physician burnout and early retirement.

Advancements in AI research, particularly in machine learning and NLP, are showing great promise in addressing some of the critical bottlenecks associated with EHRs, reducing the administrative burden placed on clinicians.

History of Electronic Health Record's

Before exploring the ways AI is being leveraged to more effectively gather insights from patient data and reduce the administrative burden on clinicians, it is important to firstly give a brief overview of EHRs, and the principles behind their adoption.

The first clinical information system was developed by Lockheed in the mid-1960's, with all medical records kept on paper and stored in manual filing systems up to that point. Despite their purported benefits adoption rates were low, with one study finding that only 9% of US hospitals had completed a basic EHR adoption by 2008. All that changed with the advent of the HITECH act in 2009, which provided financial incentives to encourage clinics and hospitals to transition from the old paper charts to electronic records.

The benefits of widespread adoption were clear and intuitive. Rather than having to manually search specially made shelves for hand-written visit notes, clinicians could now access patient information electronically from a centralized system, saving time and allowing for effective data analysis.

Despite the estimated $36 billion in Government payments to subsidize EHR adoption, they haven't been universally well-received.

Many of the most popular EHRs are built around legacy systems, making them cumbersome and difficult to navigate. A recent study from Stanford found that 71% of respondents viewed EHRs as greatly contributing to physician burnout, with 59% agreeing a complete overhaul is required. Common complaints ranged from systems requiring too many clicks, frequent crashes and complexity of use.

As well as negatively impacting patient care, physician burnout is estimated to cost the healthcare industry up to $6.3 billion annually.

Here are just some of the ways AI is being applied to Electronic Health Records to reduce this burden.

AI-Powered Voice Assistants

Perhaps the most damning statistic associated with EHR adoption is the average of 6 hours a day Doctors are spending on data entry, taking valuable time away from patient interaction, and contributing to a burnout rate that is nearly double that of the general population.

Advancements in the field of Natural Language Processing (NLP), have led to a proliferation of AI medical transcription solutions that aim to solve this problem.

One such example is Suki, an AI-powered voice assistant that aims to reduce the administrative burden placed on medical professionals. Described as "Alexa for Doctors", clinicians can use Suki to take voice notes during patient examinations, which are then parsed and uploaded directly to the EHR in real-time. The system can also be queried in a manner similar to Alexa, enabling Doctors to retrieve patient information using simple voice commands, allowing for critical insights at the point of care.

According to Suki, the digital assistant has reduced the average time it takes a physician to make a note by 76% across their user base, going from over 13 minutes to just above 3.

Another company hoping to remove the need for laborious medical data entry is Robin Healthcare, who have developed a device that can be placed in the examining room, allowing Doctors to forget about the documentation process altogether.

Rather than speaking directly to the device to make voice-notes, Robin captures all the audio in a room and leverages NLP to filter out small talk and parse only the relevant medical terminology, allowing the doctor to maintain a natural conversation with the patient.

The successes brought on by the lies of Robin and Suki are not isolated either. Deployment of Nuance's Dragon Medical One speech recognition solution resulted in a 65% reduction in time spent of triage notes at Concord Hospital in Kansas City during a trial.

Such a drastic reduction in time spent of clinical documentation will doubtless alleviate much of the pressure placed on medical professionals through manual data entry, freeing up time to put their expertise to better use.

Clinical Decision Support & Predictive Analytics

A central tenet behind the adoption of electronic health records was their ability to assist clinical decision-making and diagnoses by leveraging big data tools to extract critical insights. While great strides have been made in this area, there is still work to be done to get the most out of the potential treasure trove of patient information, with only 8% of clinicians viewing the primary value of EHRs as clinically related (the majority of respondents in a recent study viewed EHRs as predominantly data storage tools).

Advancements in machine learning have led to renewed interest in Computerized Clinical Decision Support Systems (CDSS) and predictive analytics models, used to augment clinician knowledge in the complex decision-making processes.

A recent example of this came through the application of Google's DeepMind to electronic patient records to identify patients at high-risk of Acute Kidney Injury (AKI), a condition with an in-hospital mortality rate of up to 45%. AKI is notoriously difficult to spot and early detection is crucial, with research showing that up to 30% of cases could be prevented with early intervention.

Working with the US Department of Veteran Affairs (VA), DeepMind applied their artificial intelligence to a comprehensive EHR dataset to set about solving this problem. The AI was able to predict AKI up to 48 hours earlier than current diagnostic methods with 90% accuracy, giving doctors a much-needed window to provide life-saving dialysis treatment.

Similar success was seen in a 2016 study that applied NLP techniques to medical records in order to identify patients at risk of Kawasaki disease, a form of vasculitis where effective treatment hinges on early detection. The NLP-based algorithm was able to identify at-risk patients with a sensitivity of 93.6% compared to traditional, more time-consuming methods.

As well as leveraging EHR data to predict patients at high-risk of disease, intelligent CDSS tools are increasingly being utilized to analyze physician notes in real-time, proving evidence-based treatment recommendations at the point of care.

Poor integration with EHRs and generic rules-based treatment recommendations had led to a perception from many practitioners that CCDS tools were invasive and interfered with the natural flow of patient care. AI-powered tools like Google Health and Micromedex aim to change this perception.

Integrating seamlessly with a hospitals EHR, Micromedex provides customized treatment pathways based on the information contained in a patients record, identifying potential diagnoses, drug therapies and risk factors, informing the Doctors decision-making process.

Describing the benefits the system has brought to TidalHealth Peninsula Regional, Supervisor of in-patient pharmacy Rachel Cordrey stated;
"Using this tool, clinicians can just use natural language to ask what they want to ask and get rapid turnaround on any drug information questions from a trusted database of evidence-based information. By working with an AI platform and then integrating this tool into our EHR, we've seen great benefit for patient care".
AI-assisted tools like Micromedex and Google Health aim not to replace clinicians, but to augment their knowledge, allowing for evidence-based treatment recommendations.

Clinical Trial Matching

The integration of AI and Electronic Health Records is also having a broader impact on the process of drug discovery, rather than simply being used to provide insights at the point of care.

The median cost of a clinical trial in the US is estimated to be around $48 million, with the selection and recruitment of appropriate candidates a critical bottleneck in the process. We previously discussed the development of a new cancer treatment where the recruitment process alone took 5 years, delaying the provision of potentially life-saving treatments.

Clinical trials are complex, and often require the participation of candidates who meet a very specific set of criteria, including age cohort, disease type and length of illness. Traditionally clinical research coordinators will manually comb through electronic health records to identify relevant candidates before approaching them about participating in a trial, a laborious and admin-heavy task.

The application of AI tools to patient records is revolutionizing this process, drastically cutting the time it takes to recruit trial participants.

Companies like IQVIA and Deep6 are employing advanced analytics techniques to sift through the vast amounts of fragmented data contained in an EHR. Use of NLP text-mining can identify relevant patient cohorts automatically, matching the information contained in a patients record to the description of a clinical trial.

A process that traditionally takes months can now be done in minutes, drastically accelerating the rate at which experimental treatments can be tested and approved.

The process of widespread Electronic Health Record adoption has been a long and complex one. 50 years on from the development of the first clinical information systems, work remains to be done to reduce the burden placed on physicians and to remove the perception that EHRs are simply a time-consuming tool for data storage.

Rather than replacing the need for doctor-patient interaction, tools like Suki, Micromedex and Deep6 are at their best when augmenting care-provision, providing critical insights and recommendations at the point of care and removing the need for time-consuming data-entry.

Alldus Director Mike Froggatt offered his insights into how the integration of AI and EHRs is changing the face of the healthcare provision;
"We've seen a real and lasting shift in how we interact with our personal health data. During the pandemic there has been an obvious rise in the need for telehealth and communicating with your healthcare providers remotely, this means that not only do different healthcare providers need to have access to your EHR's, but they need to be able to access that information from separate and decentralized locations. This is where we are seeing the biggest hiring trends when it comes to EHR AI solutions. Knowledge of EHR's as a domain specialty is what the market is crying out for and the first requirement in most of the searches we conduct."
If you're interested in a career focusing on AI in Healthcare check out our latest US Artificial Intelligence jobs or upload your resume today to stay up-to-date with the latest jobs in your area.

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Electronic Health Records (EHRs): How AI is improving clinician use | Alldus

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Despite extensive Government investment over the past decade, the widespread adoption of EHRs has not been universally well-recieved, with them often being cited as a leading cause of clinician burnout. We explore how AI is being leveragef to improve EHR use and toprovide cirtical patient insights.

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How technology can be used to improve access to quality healthcare

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How technology can be used to improve access to quality healthcare

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TED talk. How technology can be used to improve access to quality healthcare

I love finding TED talks about topics we study it's way more engaging. This talk talks about the meaningful use and EHRs and how it improves the quality of health care. Listening to it makes me realize how grateful we should be for the healthcare access we have. He also mentions how EHR can help deal with barriers faced as a healthcare providers. Great TED talk apart from the speaker making fun of Boris Johnson...

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How technology can help access to quality healthcare | Simon Mashudu Marcus | TEDxGoodenoughCollege

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How to improve patient outcomes by exhibiting meaningful use

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How to improve patient outcomes by exhibiting meaningful use

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Meaningful use and developing a custom EHR solution

I like this website because it not only talks about meaningful use but also talks about EHR software development. It is nice to look at it from a different side. It talks about certain needs healthcare providers might need while using EHR and how it can be accomplished.

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The concept of Meaningful Use regulations can be challenging to grasp. Yet, the main thing to understand about them is that while aiming at reduced cost of healthcare and improved patient outcomes, the meaningful use initiative refers to the practical use of EHR systems. So, to get a better idea about meaningful use, let's delve into EHRs.

Out-of-the-box EHRs

Some of the out-of-the-box EHRs used by practices and hospitals on a large scale are Cerner, Allscripts, eClinicalWorks, Epic, VA-CPRS, e-MDs, McKesson, Practice Fusion, Athenahealth, and NextGen. All of them have general functionality associated with EHR systems.

Before purchasing any less known off-the-shelf EHR solution, make sure it meets the guidelines of Certification Committee for Health Information Technology (CCHIT). Along with some operational benefits, certified EHR technology (CEHRT) can streamline workflows, reduce healthcare costs, and enable data access across the hospital network.

Custom EHR development

When developing a custom EHR solution with a certified software vendor, you should clearly understand your needs first. You may even want to create a collaborative environment among the doctors, nurse practitioners, physician assistants, and anesthetists of your facility everyone, who will be the end users of the future EHR system. This way, you'll collect everyone's individual work approaches and needs.

The next step is to communicate these needs to healthcare software developers. No matter how experienced a vendor is, they will genuinely appreciate your input, which they will use to create elaborate project specification. Your chance of getting an effective EHR solution depends on how clearly you express your expectations of the future software.

EHR features for meaningful use

User-friendly interface

The more features the app has, the more difficult it is to leverage complex functionality and ease of use. However, a caregiver must find the EHR interface convenient enough to willingly use it on a daily basis. Otherwise, healthcare professionals will do everything to avoid using the EHR system and that's not just inconsistent with the 'meaningful use', but devastating in general.

Smooth integration

For the users of other in-house systems to be able to contribute their data and access the general records, your EHR should be easy to integrate with other internal software. This is necessary to create a hospital data network and allow all the departments to share data with each other.

If integrated with a billing system, an EHR system can speed up the entire healthcare delivery process and facilitate the work of a medical billing department. To make this happen, a software development company should also add HCPCS, CPT, ICD-10 coding system standards to the EHR, as these standards simplify the process of communication with insurance companies.

To take maximum advantage of your EHR system, you can have it integrated with partner pharmacies and laboratories. This way, doctors will be able to easily share the e-prescriptions with the pharmacies and ask labs to run the tests for them.

Documentation handling

Doctors and nurses often complain about the time it takes them to handle documentation, and they have all the rights to do so. If EHR systems are supposed to hold the key to the future, they must be able to assist in the documentation routine of all medical professionals and give them time for more substantial tasks.

There're two ways to do this. First is to include customizable templates of a variety of documents, reflecting all the details in them and letting caregivers input as little data manually, as possible. Second is to implement a voice recording technology, so that doctors could create audio notes. A 'voice to text' feature would be a brilliant addition.

Electronic Prescriptions

Electronic prescriptions are one of the main objectives of meaningful use. With this feature, a patient's chart can contain all the medication ever prescribed to a patient. Such history can help a doctor make a better choice of medication, thus improving patient outcomes. If extended, this feature can even check whether the recently prescribed medication is compatible with the one a patient is already taking and warn a caregiver in case of any dangerous combinations or possible side-effects.

Patient Portal

A patient portal is also one of the requirements of EHR meaningful use. It is an online-available place where a patient can learn everything about their health and check their personal data at any time they want. The information stored on a Patient Portal usually includes:

Number of visits to the clinic or hospital

Detailed reports of check-ups and examinations

Medication prescriptions

List of medication a patient is allergic or immune to

All laboratory test results.

Conclusion

When developed professionally and with the listed features in mind, an EHR system can truly help to bring meaningful use to hospitals. Make sure to choose your EHR vendor carefully to get an effective solution tailored to your needs and compatible with the meaningful use regulations.

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How to improve patient outcomes by exhibiting meaningful use

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The concept of Meaningful Use regulations can be challenging to grasp. Yet, the main thing to understand about them is that while aiming at reduced cost of healthcare and improved patient outcomes, the meaningful use initiative refers to the practical use of EHR systems. So, to get a better idea about meaningful use, let's delve into EHRs.

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This article talks about the history and future of Data, Information, Knowledge and Wisdom Model. For example how Wisdom was added later on to Data, Information, and Knowledge data. Also I liked how it showed different systems that relate to different steps of this "pyramid".

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Informatics: Evolution of the Nelson Data, Information, Knowledge and Wisdom Model: Part 1

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As a visual learner I learn and retain information best from pictures/videos. I liked this video as it explains step by step what each of those steps are. It also presents it as a pyramid which explain well how each one of those steps depends on the step prior.

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This website explains well the importance of interoperability for nurses and patients. It also talks about the biggest challenges that nurses face with regards to data access and exchange across systems and recommendations to other health care systems on how to support their nurses through advancing interoperability. The care would be much better and faster if the data from prior visits or encounters with patient would be available together with the information about the patient themselves and their own health management. As an occasional patient myself I do get frustrated when I get asked the same questions over and over again and I answer "no" just to avoid giving explanation to those repeated questions.

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Estimated read time: 5 minutes

When a patient arrives at a health care organization, they are greeted by a nurse who asks a series of questions and collects a number of documents as part of the admission process. While providing this information is crucial for receiving quality care, chances are the patient has been through this process already at least once during a previous care encounter.

This is just one example of where interoperability, the capacity of different information systems, devices or applications to access and exchange data within and across organizational boundaries, could play a role in eliminating the redundant, time-consuming and potentially life-threatening aspects of health care.

In this Q&A, Becky Fox, chief nursing informatics officer at Atrium Health, discusses why interoperability is key to decreasing documentation burden, clinician and provider burnout, and improving the overall health care experience.

The importance of interoperability for nurses and patients
Why is interoperability important to nursing staff, and how does it impact their day-to-day work?
Fox: We want to leverage all the data we have about patients to drive the best treatment and outcomes possible. Through mining the data with analytics, we can make the data more meaningful to clinicians, so they can focus on patient care rather than having to pull information together. In the health care industry, we are at a great place right now, where we can gather information from multiple sources, quickly synthesize to get to understanding and make data actionable.

Let me share an example. When a patient comes into a health care organization or an ambulatory setting, the nurse goes through a series of questions during the visit or admission process to gather information about the patient. Wouldn't it be great if the nurse already had detailed information from all the patient's previous health experiences and didn't have to go through the exercise of asking a lot of repetitive questions? Not only data from prior visits or encounters, but also information about the patient themselves and their own health management-from wearables, to health apps, and of course, demographic and social information. It would be great if all of that information could be taken in, digested, and presented to help the clinicians focus their questions and assessments. The end result would be quicker and better care.

That is what interoperability is all about: bringing multiple sources of information together and using health care technology, innovations and analytics to apply it more meaningfully to the care we provide to patients. It's also about being able to use the data to engage patients and consumers in changing behaviors in a positive way along their health care journey. Interoperability, coupled with usability, can help remove noise and mundane tasks from the workflow. It's an opportunity to collectively leverage information that has already been collected and contribute to the bigger picture of decreasing the burden of documentation, clinician burnout and improving the patient/consumer experience.
How does interoperability impact patient care?
There are still gaps that happen in health care. For example, when a patient goes into a care setting and fills out a series of questions, screening tools and has discussions with care providers, and then they go to a different health care setting, and they have to do it all again. Anytime you are repeating processes, things can be overlooked, missed or not understood. It's also annoying to the patient! They can end up with redundant testing, procedures and assessments, and all these examples have a financial cost to the patient, the institution and payors. There is also the cost of time and potential delay in care and decision-making when, for instance, a lab test has to be repeated.

We, as health care leaders, all collectively must address this by working to improve interoperability, the usability of data and how to better share all data across all systems in meaningful ways.

Overcoming roadblocks to health care interoperability
What are the biggest challenges that nurses face with regards to data access and exchange across systems?
While health care systems collect and document similar information about patients, it is not standardized. If all health care systems, regardless of their EHR vendor, collected and documented the same data, sharing information across hospitals and health systems would be significantly easier. There are some industry leaders working together to establish standards of such, and I think in the near future, you are going to see movement in this direction.

We are also at a place in the health IT journey in which technology and analytics are really making great strides, with even bigger strides to come. We realize we must collect data from multiple places, but we need data normalization to occur in the process, so that we are all speaking a common language. The implementation of standards that we can all agree upon is also extremely important.

The other thing that is shifting is our mindset in how we view and share our data.As we move in the direction of managing the health of large populations and look at data from more outside entities, we will need to be more accepting of data which may have errors in it.We can't be purists. We must look at data in terms of themes, directions and aggregation. We know there are going to be lessons learned. And, we can't let perfect get in the way of progress. We have to participate in this transformation and not be afraid of moving forward. As an industry we all need to work together to make sure we are sharing, streamlining and consolidating data. That is what will contribute to changing health care in the U.S. and around the world.
What are your recommendations to other health care systems on how to support their nurses through advancing interoperability?
At Atrium Health, we have a significant focus on our population health strategy. Looking at sources of data across different systems is another step in the journey of pulling information together and providing the best health care for our patients. If a health care system isn't yet on a population health journey and isn't sharing information with other health systems, then this would be a good place to start. We're all in this together, and our patients are going to expect that their health information is being shared, reviewed, analyzed and leveraged to give them the best care possible.

Health systems need to make sure they are participating in all avenues of interoperability and implementing standard tools, work and documentation. Nursing leaders must participate in the conversations of how-to bring interoperability to the beside and to ambulatory clinicians, so they can be their best for their patients.

Interoperability is not just for physicians, it's for all clinicians, and nursing needs to be at the table to make sure that all of the right data sources are being brought to the forefront in meaningful ways.
At Cerner, we're doing our part to innovate and transform health information technology for nurses. Learn more here.

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Why Interoperability Progress is Significant for Nursing

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Estimated read time: 5 minutes When a patient arrives at a health care organization, they are greeted by a nurse who asks a series of questions and collects a number of documents as part of the admission process.

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How interoperability & data sharing can improve patient safety

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How interoperability & data sharing can improve patient safety

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This short video explain well how interoperability and data sharing can improve patient safety. As a patient comes in doctors and nurses have to go through different files and noted to see a full picture and patients have to re-introduce themselves to doctors. Creating a system that shares information between hospitals will allow doctors to know what tests to order improving healthcare quality for patients.

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How interoperability & data sharing can improve patient safety

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I really liked this page since it can be used as a "booklet". It talks about TIGER initiative with some background on it. It also has some case studies and Recommendations. Recommendations are written in a way as to what  Information technology vendors,  Healthcare delivery organizations, Government and policy makers and etc. do for this initiative to be successful.

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Since we are talking about TIGER initiative this week I thought it is a good idea to find something that talks about what is it. I liked this website since it tells the history of how TIGER initiative came about and different phases of it. This website also has a quiz that can be completed.

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TIGER Initiative Foundation: History & Purpose - Video & Lesson Transcript | Study.com

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The TIGER (Technology Informatics Guiding Education Reform) initiative was created to reform the field of health informatics. Look into the history…

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Nursing informatics is a specialty that combines technology and patient care.
The ANA defines it as: "the specialty that integrates nursing science with multiple information and analytical sciences to identify, define, manage, and communicate data, information, knowledge, and wisdom in nursing practice."

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This website not only explains what it is but also explains what Nurses that work in Informatics do and what their responsibilities are. With the COVID pandemic a lot of jobs focused on working online. When I thought about Nurse Informatics I thought they mostly work from home but what I found out was different. They work in hospitals, urgent care clinics, counseling centers, technology companies, ambulatory care centers, healthcare product companies, EHR companies, and many more.

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As the technology and systems required to deliver superior patient care multiply, nursing informatics has evolved to ensure that these systems-and the physicians, nurses, and staff who use them-are set up for success.

Nursing informatics is a specialty that combines technology and patient care. The nurse informaticist acts as the bridge between a healthcare organization's systems and its providers and clinical staff. Because of their unique training both as registered nurses (RNs) and information technology specialists, nurse informaticists understand how all the pieces fit together and provide valuable input into how systems should be designed from a provider standpoint.

The need for nurse informaticists has arisen as today's healthcare professionals navigate interconnected enterprises filled with largely disconnected systems. For example, it's possible today to use just one solution to manage all healthcare operations for governance, risk management, and compliance. However, that system must work with an electronic health records (EHR) platform and a medical diagnosis program, among others. When used effectively and in tandem, these solutions dramatically improve patient care quality and safety. Nursing informatics plays a significant role in selecting, implementing, constructing, and connecting healthcare information systems. Despite its influence and importance, it's a role that often goes unrecognized in health systems. We define nursing informatics and demonstrate the positive impact it has on an organization when properly staffed and supported .

What is the nursing informatics specialty?

Since healthcare organizations began moving to EHRs, nursing informatics specialists have played a key role in the continuing evolution of healthcare. But what is nursing informatics, exactly? In Nursing Informatics: Scope and Standards of Practice 2nd Edition, the ANA defines it as:

... the specialty that integrates nursing science with multiple information and analytical sciences to identify, define, manage, and communicate data, information, knowledge, and wisdom in nursing practice.

The ANA goes onto advise that:

NI supports nurses, consumers, patients, the interprofessional healthcare team, and other stakeholders in their decision-making in all roles and settings to achieve desired outcomes. This support is accomplished through the use of information structures, information processes, and information technology.

The benefits of easing technological adoption and use by physicians and nurses cannot be overstated. Atul Gawande, MD, of Partners Healthcare, wrote a compelling article titled Why Doctors Hate Their Computers . With never-ending demands placed on clinicians today and their workdays stretching ever longer, the results are epidemic levels of burnout, depression, and even suicidal thinking.

In a similar vein, newer studies seek to understand the relationship between documentation burden in our modern healthcare system and burnout in nurses and other providers working in direct patient care. In one , almost half of nurses (49%) reported feeling discomfort while entering chart data into a computerized point-of-care workstation, and 61% said they were concerned about the placement of technology. These findings underscore the importance of and need for clinical informaticists in easing the burden on providers.

The evolving definition of NI

The definition of nursing informatics has evolved over time, and we have yet to settle on a consensus definition. Some believe nursing informatics falls under the umbrella of medical informatics (also referred to as clinical informatics), while others contend that just as nursing is its own specialty with its own responsibilities, nursing informatics needs its own distinct definition as well.

Roles and responsibilities of a nurse informaticist

The day-to-day responsibilities of a nurse informaticist vary depending on organizational needs around information management. The American Nursing Informatics Association (ANIA) is the association of professional nurses and associates who use informatics to improve the health of populations by optimizing information management and communication. Its members have roles in system design and implementation, education, research (analysis and evaluation), standards and policy development, quality improvement, and management and administration. The ANIA does not list the primary responsibilities of a nurse informaticist but published a position statement on the responsibilities of a CNIO .

To help understand the roles we can refer to theAmerican Medical Informatics Association's () list of a nurse informaticist's responsibilities, which are as follows:

Improve workflow through communication and information technologies

Retrieve and review information to improve patient safety

Contribute to the construction of an interoperable national data infrastructure

Advance public health by influencing health care policy

Develop information systems based on current standards of care

Ensure information systems remain updated

Educate staff on changes to EHRs and EMRs

Where do nurse informatics professionals work?

Nurse informaticists work in various settings to aid in managing the use of information systems, whether or not those healthcare sites or companies directly service patients. Examples include hospitals and health systems, urgent care clinics, counseling centers, technology companies (including telemedicine), ambulatory care centers, healthcare product companies, EHR companies, and many more. Typically, these professionals report up to IT or nurse leaders.

Depending on the setting, nurse informaticists can hold one of several job titles. Informatics nurse, clinical informatics nurse, nursing informatics specialist, chief nursing officer, chief information officer, chief nursing informatics officer, clinical analyst, and health informatics officer are the most common titles nurse informaticists hold. Regardless, number of career opportunities can arise from a role in nursing informatics.

Nurse informaticists are, first and foremost, nurses. Most organizations prefer to hire informatics nurses who possess at least a bachelor's degree in nursing (e.g., BSN or MSN), with many requiring a master's degree in health informatics or a similar field of study.

Why is nursing informatics important?

Most organizations have knowledgeable and dedicated providers and staff who are truly committed to providing great care for their patients. Technology and software solutions can help make it easier for providers and staff to deliver high-quality patient care-if they're properly implemented.

The field of nursing informatics produces professionals who help ensure a seamless relationship between the various systems within an organization, which in turn makes it easier for providers to focus on what's most important: their patients.

Nurse informaticists also play a valuable role in the following areas, among others:

Improved quality of care and patient outcomes: One of the many benefits of incorporating technology into healthcare is that it makes it easier for providers to glean more data and information about their patients. But that data is only useful if it's collected, analyzed, and applied, and shared effectively, and that can only happen if providers are able to easily use the organization's EHR system.

Nurse informaticists help ensure EHRs are optimally designed to fit the organization's workflow and are easy for providers to use. The less time providers have to spend navigating clunky or inefficient technology, the more time they can spend focusing on getting and sharing the right information about their patients.

More efficient clinical processes: Nursing informatics is all about efficiency. Technology solutions are designed to simplify provider workloads and streamline clinical processes, and nurse informaticists play a pivotal role in the proper setup and implementation of those solutions.

Organizational change management: Nurse informaticists are leaders in process and change management. A recent ANIA addressed the need for these professionals to prepare for and guide others through change-planned initiatives, volatile environments, and/or unexpected situations-by:

anticipating where situations are moving

facilitating the implementation of change

sustaining momentum by taking charge and advancing progress

Advances in telehealth and other technology: The COVID-19 pandemic has drastically increased the importance of having an effective and efficient telehealth solution for healthcare organizations. Nurse informaticists have played a major role in evaluating telehealth platforms to ensure the technology is compatible with practice guidelines in ambulatory and hospital settings, as well as in helping implement and roll out these systems and train providers on how to effectively use them.

Patient care coordination: Patient care coordination is no easy task. It involves myriad moving parts (patients, providers, specialists, therapists, pharmacists, billing departments, and so on) that, if not effectively managed, can quickly turn into a confusing mess that threatens quality of care for the patient and introduces unnecessary risk. Nurse informaticists are trained to take a holistic approach to complex systems. Not only do they have the clinical knowledge necessary to anticipate patient and provider needs, but because they understand how these systems work, they can more readily anticipate potential failure points in the patient care cycle before they occur. In doing so, nurse informaticists can proactively address these obstacles and ensure a seamless and effective patient experience.

As technology's role in healthcare continues to expand, so too will the role of nursing informatics in helping healthcare organizations adopt and effectively implement new technologies. A holistic and data-driven approach to patient care and healthcare operations benefits providers, staff, patients, and organizations-and nursing informatics plays a major part in ensuring this approach is successful.

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As the technology and systems required to deliver superior patient care multiply, nursing informatics has evolved to ensure that these systems-and the physicians, nurses, and staff who use them-are set up for success. Nursing informatics is a specialty that combines technology and patient care.

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Interacting with digital technology is a future in the healthcare environment. This TED talk explains well how data and informatics can be used in healthcare and help patients. He talks about how it can prevent health issues that the patient is susceptible to based on patient genomics and biologics. Building in live prediction charts based on individual level data can help us to improve health outcomes. This models can predict your healthcare and would allow you to address it. Aaron Black also talks about the risks of working with data.  He mentions the importance of accuracy of the information collected for valid outcomes. Aaron Black emphasized how data in healthcare can be a privacy issue.

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Interacting with digital technology is a future in the healthcare environment. This TED talk explains well how data and informatics can be used in healthcare and help patients. He talks about how it can prevent health issues that the patient is susceptible to based on patient genomics and biologics. Building in live prediction charts based on individual level data can help us to improve health outcomes. This models can predict your healthcare and would allow you to address it. Aaron Black also talks about the risks of working with data.  He mentions the importance of accuracy of the information collected for valid outcomes. Aaron Black emphasized how data in healthcare can be a privacy issue.

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Data driven healthcare: It's personal | Aaron Black | TEDxTysons