October 26, 2023

Balancing Innovation and Privacy: Harnessing AI’s Potential while Ensuring Data Security in Healthcare

Between diagnosing diseases, optimizing treatment plans, and drug discovery, AI has the potential to transform healthcare in unprecedented ways. However, this transformation comes with a significant responsibility: the need to strike a delicate balance between innovation and privacy.

The Data Security Challenge

Data Vulnerabilities

The large volumes of data required for AI training and decision-making create potential vulnerabilities if not adequately protected. These vulnerabilities include concerns such as bias and fairness, data quality, poisoning, and drift, to name just a few.

Privacy Concerns

Patients rightfully expect their medical data to be kept confidential. The use of AI raises concerns about who has access to their sensitive information and for what purposes.

Regulatory Compliance

Healthcare organizations are subject to strict regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in Europe. Non-compliance with these regulations can result in hefty fines and legal repercussions.

Striking the Balance

Data Encryption

Encrypting data at rest and in transit is crucial. This ensures that even if unauthorized access occurs, the data remains unreadable.

Access Control

Implement strict access controls to limit data access to authorized personnel only. Regularly audit and monitor data access to detect and prevent unauthorized use.

Ethical AI

Develop AI models that are explainable, transparent, and ethically trained to avoid biases and respect patient rights.

Patient Consent

Ensure that patients are informed about how their data will be used and obtain their informed consent when required by regulations.

Regular Audits and Compliance

Continuously assess and update security measures to comply with evolving data protection laws.

The Future of AI-Driven Healthcare

Interoperability

Ensure that AI systems can seamlessly integrate with existing healthcare infrastructure and share data securely.

Education and Training

Healthcare professionals and AI developers must be educated on data security best practices and ethical AI principles.

Collaboration

Encourage collaboration between healthcare institutions, tech companies, and regulators to establish common standards and guidelines.

Final Thoughts

With the limitless potential of AI across industries, it’s important to uphold the responsible deployment of AI in healthcare, as it demands a commitment to data security and patient privacy. Achieving this balance between innovation and privacy will enable us to harness AI's transformative power while maintaining the trust and ethical standards that are central to healthcare.

 

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About Mocingbird

 

Mocingbird is a SaaS management platform dedicated to improving medicine and clinician well-being. Our comprehensive solution eliminates the chaos of ongoing credentialing and delivers high-impact Continuing Medical Education (CME). With Mocingbird, individual clinicians gain a convenient one-stop solution to validate, track, document, and calculate their CME requirements for professional license maintenance. Healthcare organizations benefit from a powerful management tool that provides a real-time compliance overview for effective risk mitigation. Founded by Interventional Cardiologist, Dr. George Fernaine, and Orthopedic Spine Surgeon and CEO, Dr. Ian Madom. Schedule a meeting with the Mocingbird team.  

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About the Author

With 10+ years of industry experience, George Rhinehart is Mocingbird’s Director of Engineering. His background includes roles as an electronics engineer, software engineer, and software manager at Lockheed Martin and Northrop Grumman, where he worked on air and space defense contracts. He holds a BS in Computer Engineering, an MS in Systems Engineering, and an MBA

October 23, 2023

Navigating the Complexities of Data Security in Healthcare

Data security has become a paramount concern across various industries, but it holds a unique significance in the healthcare sector. With the increasing digitization of patient records and the integration of technology into medical practices, the healthcare industry faces a multitude of challenges when it comes to safeguarding this sensitive data. Navigating the complexities of data security in healthcare is not just a matter of compliance; it's a critical step in ensuring the trust and safety of patients.

 

Significance

Patient Privacy

One of the fundamental ethical principles in healthcare is respecting patient privacy. Patients trust healthcare providers to protect their sensitive information, including medical history, diagnoses, and treatment plans. A breach of this trust can lead to severe consequences for both patients and healthcare providers.

Compliance Requirements

Healthcare organizations are subject to strict regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in Europe. Non-compliance with these regulations can result in hefty fines and legal repercussions.

Financial Impact

Data breaches can have a significant financial impact on healthcare organizations. They not only face fines but also incur costs related to breach investigation, legal fees, and potential settlements.

 

Challenges

Diverse Data Ecosystem

Healthcare data comes in various forms, including electronic health records (EHRs), medical imaging, wearable device data, and more. Managing and securing this diverse data ecosystem is a complex task.

Human Error

Despite advanced technology, human error remains a leading cause of data breaches in healthcare. This includes unintentional actions like misaddressed emails, as well as deliberate insider threats.

Ransomware Attacks

The healthcare industry has been a prime target for ransomware attacks in recent years. These attacks can cripple healthcare systems and compromise patient care.

 

Best Practices

Encryption

Encrypting data at rest and in transit is crucial. This ensures that even if unauthorized access occurs, the data remains unreadable.

Access Control

Implement strict access controls to limit who can access patient data. Only authorized personnel should have access, and their permissions should be regularly reviewed and updated.

Employee Training

Conduct regular training sessions to educate staff about the importance of data security and how to recognize and respond to potential threats.

Incident Response Plan

Develop a robust incident response plan that outlines steps to take in case of a data breach or other security events. Time is critical in mitigating the impact of an event.

Regular Audits and Assessments

Perform regular security audits and assessments to identify vulnerabilities and ensure compliance with regulations.

 

Emerging Trends

Blockchain

The use of blockchain technology is gaining traction in healthcare to enhance data security and integrity.

Artificial Intelligence

AI is being used to detect anomalies in patient data that may indicate a security breach.

Zero Trust Architecture

This approach challenges traditional security models by assuming that threats can come from within the network. It requires constant verification of trust for anyone trying to access resources.

 

Final Thoughts

Data security in healthcare is a multifaceted challenge that demands constant vigilance and innovation. Healthcare organizations must prioritize the protection of patient data not only to comply with regulations but also to maintain patient trust and the quality of healthcare services. The security landscape is ever-changing, so staying informed is essential when attempting to successfully navigate this complex space.

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About Mocingbird

Mocingbird is a SaaS management platform dedicated to improving medicine and clinician well-being. Our comprehensive solution eliminates the chaos of ongoing credentialing and delivers high-impact Continuing Medical Education (CME). With Mocingbird, individual clinicians gain a convenient one-stop solution to validate, track, document, and calculate their CME requirements for professional license maintenance. Healthcare organizations benefit from a powerful management tool that provides a real-time compliance overview for effective risk mitigation. Founded by Interventional Cardiologist, Dr. George Fernaine, and Orthopedic Spine Surgeon and CEO, Dr. Ian Madom. Schedule a meeting with the Mocingbird team.  

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About the Author

With 10+ years of industry experience, George Rhinehart is Mocingbird’s Director of Engineering. His background includes roles as an electronics engineer, software engineer, and software manager at Lockheed Martin and Northrop Grumman, where he worked on air and space defense contracts. He holds a BS in Computer Engineering, an MS in Systems Engineering, and an MBA

August 25, 2022

The Transition From Nursing Student to Professional Nurse

It took me almost 30 years to figure out what I want to be. When I was little I wanted to be a fireman or a dinosaur. Neither one of those worked out. Now that I am grown up, I can say that I am proud to be a nurse. Nursing school was a very demanding and emotional rollercoaster, so much so that the mere thought of going back for my NP anytime soon makes me really want to look into a career as a dinosaur. Trying to juggle personal life responsibilities, financial well-being, self-care, social connections, clinicals, and late-night studying is physically and emotionally draining. But I would do it again in a heartbeat to get to where I am today.

In nursing school, you often hear that you learn 1% of the job in school and the other 99% when you start working. I’m not sure why school costs so much…. There are days when I feel like I know nothing at all, but then there are little moments, whether it’s with a patient or another team member, that show me I am exactly where I am meant to be. The transition from student to professional nurse is a reality shock. Once you put your scrubs on and step onto the unit, you are expected to be a professional. Your patients expect to be able to rely on and trust you. It doesn't matter if it’s day one or year 10, you are expected to have the capacity and knowledge to treat the patient with the utmost respect, dignity, care, and empathy. 

I understood what it meant to be a nurse when I was working at a Boston hospital on a med-surg floor. One of my patients had been there for months and was clearly depressed. She was neglecting her mental and physical health and it was obvious she had given up. She refused showers or bed baths, wouldn’t get up to use the bathroom, never brushed her hair, and barely ate any food. Her hair particularly was a stressor for her. She had been laying in this bed with the back of her head pressed against the pillow for months, so she was losing a lot of it. On top of that, it was the most tangled head of hair I had ever seen in my entire life. She told me she just wanted to shave it off and was very adamant about it, but she was clearly upset that it had come to that.

I spent three hours sitting in her room detangling her hair. When I was done, I french braided it and you should have seen the glowing smile on her face. I hadn’t seen her smile in months, which was one of the best moments in my nursing career so far. It may seem silly and hair detangling is definitely not something I am required to do, but my job as a nurse is to make sure my patients feel seen, heard, cared for, and comfortable. I learned that being a nurse isn’t just taking vital signs, performing head-to-toe assessments, administering medications, etc. It is my duty to nurture each and every one of my patients, helping them find new ways to grow, heal and lead a happier life.

One of my biggest takeaways from this experience is how amazing and rewarding it is to be a part of this respected profession. I have quickly realized that while yes, this is a job, it also becomes a part of your identity. Nursing will never simply be a job for me, it is a passion. It is a constant process of learning and growing in my personal and professional life.

Author: Sam Dorman

May 31, 2022

Long Weekends Aren’t Meant For Unexpected CME Deadlines

Memorial day weekend (#MDW) is an important time to reflect on all of those who have served and have given the ultimate sacrifice for our way of life.  Unfortunately, this weekend is also associated with many clinicians as a time to “catch up” on all those looming deadlines with some state licenses due for renewal.

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April 6, 2022

Artificial Intelligence Will See You Now: AI In Healthcare

What is AI?

Artificial intelligence (AI) refers to computer systems that simulate or exhibit a specific aspect of human intelligence or intelligent behavior, such as learning, reasoning, and problem-solving. 

It is not a single technology, but rather a range of computational models and algorithms, the most important of which being Machine Learning (ML), which refers to a system that identifies patterns of data from input and makes predictions from new, never-before-seen data.  

ML algorithms can automatically learn and improve from experience without being explicitly programmed, and such “learnability” represents a key feature of AI. 

The benefits of AI in healthcare

Healthcare is a field in which AI is rapidly evolving, leading to a digital transformation that is:

  • improving the access, quality, safety, and efficiency of various health services
  • supporting evidence-based decision making 
  • fostering communication and coordination
  • allowing for the optimization of health systems' performance
  • unlocking big data to gain insights into patients
  • delivering value at reduced costs, while still improving outcomes and patient experience

Current AI uses in healthcare

Recently, many ML algorithms have been approved for safe use in healthcare by the US FDA. Stanford developed an AI algorithm that can diagnose up to 14 types of medical conditions simultaneously from imaging, Mayo Clinic started using AI to find molecular biomarkers in MRI imaging instead of testing samples collected during surgery, while MIT developed an AI prediction model that can anticipate the development of breast cancer up to 5 years in advance.

Many big tech companies such as Google, Microsoft, Apple, Amazon, and IBM are providing organizations with AI cloud platforms and services as well as ML algorithms. There have also been various cross-sector collaborations, with Apple partnering with over 100 hospitals and clinics for its health records project, allowing consumers to exchange their health data with healthcare providers, or IBM partnering with various hospitals, enabling them to use Watson to make cancer diagnoses and treatment recommendations, a system that can digest information and make recommendations much more quickly and more intelligently than perhaps any machine before it, processing up to 60 million pages of text per second. 

AI-assisted surgical robots are an example of this, as they can be operated both locally and remotely and are able to analyze data from pre-operative medical records to physically guide a surgeon’s instrument in real-time. 

Robots can also be used in the rehabilitation of patients with stroke, to deliver equipment and medical supplies as well as to assist in the care of elderly patients. 

Many hospitals in the United States have also started using ML algorithms for predictive analytics (eg, predicting adverse events, mortality rates, the number of patients in the emergency department), obtaining data that allows them to take proactive measures for the foreseen events days in advance.

EHRs (Electronic Health Records) are the backbone of this process and currently, many EHR vendors, including Epic, Cerner, Allscripts, and Athena have started to add AI into their systems with the purpose of supporting workflows, and clinical decision-making as well as patient engagement. 

Another potential use that can enable clinicians to make quicker and smarter decisions about their patients uses the smartphone as a catalyst. Various companies are developing sensors that attach to phones to collect all sorts of biological data. 

Ultimately, these applications can fall into 4 different categories:

  • Patient-facing
  • Doctor-facing
  • Research
  • Telehealth

The future of AI in healthcare

As more and more data are captured, and as computers become better and faster at processing them autonomously, the possibilities keep expanding. The application of AI in healthcare is disruptive, so a good question to ask is whether it will change not only how medicine is practiced, but who is practicing it. As some Silicon Valley investors are speculating, one day AI could take the place of doctors, serving as a diagnostician and even a surgeon, maybe doing the same work with better results for less money. 

But physicians, after all, do more than data processing. They educate and walk the patients through the difficult times of disease and perhaps death, attend at their bedsides, and counsel them. They grasp nuance and learn to master uncertainty. No AI could replace that humanity in the eyes of a sick patient. 


Chen M, Decary M. Artificial intelligence in healthcare: An essential guide for health leaders. Healthc Manage Forum. 2020 Jan;33(1):10-18. doi: 10.1177/0840470419873123. Epub 2019 Sep 24. PMID: 31550922.


About the Author

Dr. Patrizia Scali is an Italian ECFMG certified medical doctor. 

Dr. Scali graduated medical school from Università degli Studi di Milano-Bicocca in Milan, Italy and has completed all 3 USMLE Step exams. She has also completed an Accelerated Certificate Program in Business Administration at University of California, Irvine (UCI).

Dr. Scali  has conducted pediatric hematology research in Italy, as well as hepatology lab research at Yale School of Medicine in the US. She has worked as a primary care physician in Italy, her home country, where she also had extensive experience as a telemedicine doctor.

March 15, 2022

The Medical Supply Chain

The global healthcare system we experience today is the consequence of an extremely efficient, yet fragile, supply chain. This efficiency, therefore, comes at the expense of resilience, meaning it is vulnerable to “black swan” events like Covid-19.

Healthcare facilities work with one another in a group purchasing organization. They contract with two or three large distributors, which either purchase from wholesalers or contract directly with manufacturers. 

As the Covid-19 pandemic ravaged the world, we can all remember the shortages the healthcare system suffered. As the caseload kept increasing, the need for PPEs soared, filling the news with images of healthcare workers improvising hospital gowns and face shields. The same thing happened with some critical medical supplies. By April 2020, prices for N95 masks were up 6,136%, while those of isolation gowns had spiked by 2,000%. U.S. health care leaders had to resort to protocols for rationing testing and ventilators as the shortages continued.  

This supply chain failure led to a paradigm shift from a centralized supply chain in the US into thousands of domestic manufacturers stepping up and producing PPEs as well as other critical medical supplies. An example of this included Austin-based Tito’s, which transitioned from producing vodka to hand sanitizer. Cumbersome vendor-approval processes and inflexible funding rules did not help.

In a world where large-scale disruptions such as climate change and natural disasters, shifting global economic or geopolitical conditions as well as cyberattacks are likely to become more common, the Covid-19 pandemic has opened our eyes to the dangers of a supply chain that focuses exclusively on efficiency.


https://hbr.org/2021/02/one-way-to-build-more-resilient-medical-supply-chains-in-the-u-s


About the Author

Dr. Patrizia Scali is an Italian ECFMG certified medical doctor. 

Dr. Scali graduated medical school from Università degli Studi di Milano-Bicocca in Milan, Italy and has completed all 3 USMLE Step exams. She has also completed an Accelerated Certificate Program in Business Administration at University of California, Irvine (UCI).

Dr. Scali  has conducted pediatric hematology research in Italy, as well as hepatology lab research at Yale School of Medicine in the US. She has worked as a primary care physician in Italy, her home country, where she also had extensive experience as a telemedicine doctor. 

February 10, 2022

Filling The Gap Of The US Healthcare Workforce: IMGs and Their Road To Licensure

The US demand for physicians has been higher than the number of US medical school graduates. One way to fulfill this is by seeking IMGs. 

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November 24, 2021

Avoiding Healthcare’s Great Resignation

There's no doubt that the Great Resignation has exponentially impacted the healthcare industry. Here's how you can protect your organization.

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September 21, 2021

Making Changes in Healthcare is Hard – But Why?

The healthcare industry is very complex, which is one of the many reasons that has held back progressive changes. Many problem-solving innovations are pushed to the side because of external factors that are prevalent in healthcare, even if those changes will improve clinician wellness, patient care, education, increase productivity while decreasing compliance risk. 

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June 14, 2021

7 Key Takeaways from Mocingbird+ UBERDOC: The Future of Medicine: Re-imagine Your Digital Practice Webinar

Thank you to all who were able to attend the first-ever Mocingbird + UBERDOC webinar to discuss the future of digital healthcare, the trend of telehealth, the blooming second opinion market, how to expand your patient base, re-conceptualizing your practice, and much more.

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