Science evolves through the efforts of researchers. New advancements build upon the discoveries of predecessors. Our understanding of the structure and development of the universe, galaxies and stars, planets, and comets has only emerged through increasingly in-depth investigations. Often, new technologies and measurement methods have significantly contributed to this understanding. New models that can explain known phenomena and predict new ones become genuine “discoveries” once their predictions are confirmed.

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Looking back, we find many ideas that seem “strange” to us today regarding the properties of nature and the universe. These ideas often persisted for centuries because the explanations at the time were not questioned, primarily due to a lack of verification options, as well as because these phenomena had little significance for daily life. Additionally, there were times when “holy books” seemingly provided adequate instructions for explaining incomprehensible phenomena.

From today’s perspective, many of these old concepts are hardly comprehensible as accepted beliefs of their time. Two relevant examples include:

1. Shells found in mountains far from the sea were thought to have grown there in the ground, like everything that grows from the earth. (Today, creationists believe that the Earth and its fossils were simply created as is.)
2. Until the 19th century, the universe (the solar system plus the sphere of fixed stars) was largely thought to be about 8,500 years old. This age was calculated around 325 AD (Council of Nicaea) based on genealogical data and timelines in the Bible.

Both examples relate to the understanding of time and, consequently, evolution. Their refutation was made possible only through the development of a critical attitude among scientists and a clear objectification of research through theory and evidence.

Development of Two Concepts – Time and Evolution

Paleontological and geological studies have significantly contributed to changing people’s perception of time. The Danish scientist Nils Stensen (Nicolaus Steno) and the Englishman Robert Hooke, around 1670, provided the correct explanation for the shells and shark teeth found in the mountains: mountains do not grow like trees but arise through uplift, such as from ancient sea floors—a concept that lacked supporting facts at the time. The discovery of numerous fossils and the compelling calculations regarding the potential thickness of sediment deposits indicated that the Earth must be much older than previously calculated. The interpretation of geological strata containing fossils later clarified that dinosaurs roamed the Earth hundreds of millions of years ago and largely went extinct around 65 million years ago.

Steno and Hooke (and later others) began to doubt the truth of the Biblical creation narrative, leading to internal conflicts with religious doctrines. Hooke also recognized that fossils indicated extinct species and that the Earth might now be “drier” (climate change…?).

However, both scholars still forced their ideas into the biblical chronology, which necessarily required the postulation of short-term changes in the Earth’s structure in the past, such as significant (grotesque) geological changes due to the Great Flood. This led to catastrophic theories in the 18th and 19th centuries.

Astronomy showed in the 19th century that the sun was likely older than 8,500 years. The most efficient known energy source at the time, coal, was also used to calculate the minimum age of the sun. With a known mass of about 2 x 10³⁰ kg (derived from the Earth’s orbit around the sun and Newton’s laws), it was estimated that if the sun had always shone in the same manner, it could be at least 1 million years old. Today, incorporating insights from nuclear fusion, we know that the sun is approximately 4.5 billion years old.

Finally, Darwin’s publications firmly established the concept of evolution. It became logical to conclude that the Earth has a history and that geological evolution exists—implying also the evolution of the universe.

New Theories and Their Acceptance

The evolution of many ideas, of course, did not always proceed without problems. Some theories were incorrect, others were disbelieved, while some achieved immediate success. Numerous examples can illustrate this variety.

Around 1920, Wegener proposed, based on the morphology of the coastlines of Africa and South America, that the continents move apart and that Africa and South America had been driven apart. He was not believed and was even ridiculed. It wasn’t until around 1960, when studies of the residual magnetic field strength of the ocean floor revealed stripes of alternating magnetic polarity symmetrically distributed around the elevated Mid-Atlantic Ridge, that evidence for the activity of the Earth’s crust (plate tectonics) emerged, leading to the movement of continents.

An example of a prediction that was soon and convincingly confirmed by measurements is the curvature of space predicted by Einstein’s theory of relativity. Light passing close to large masses is deflected in their gravitational field (tracing a curved path from an Euclidean perspective). This led to the prediction in 1915 that it might be measurable during the next solar eclipse. This was achieved in 1918 (though it was hardly recognized afterward), confirming the theory and making Einstein famous.

Science operates under a few fundamental principles. One is that every idea should be traceable and verifiable or, at the very least, refutable. Another foundational thought (dating back to Occam in England, 13th century) is that a simple theory with as few “parameters” as possible is better than a complicated one with many assumptions and “free” parameters.

Furthermore, there is a belief that certain models may be unified through a more general (or “higher”) theory. A good example is again the theory of relativity in the realm of motion and gravitation: it is generally applicable, but at “small” speeds, the equations simplify to Newton’s form.

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Both North America and Europe have adopted FHIR for healthcare data interoperability, but their approaches to implementation and usage differ. However, most stakeholders nowadays prefer FHIR-first solutions like Kodjin for interoperability and regulatory compliance. This article delves into the key differences, challenges, and successes of FHIR implementation in these regions, providing insights for stakeholders involved in healthcare IT.

Understanding FHIR

What is FHIR?

FHIR is developed by Health Level Seven International (HL7), a not-for-profit, ANSI-accredited standards developing organization. The goal of FHIR is to simplify implementation without sacrificing information integrity. It combines the best features of HL7’s version 2, version 3, and CDA (Clinical Document Architecture) standards.

FHIR provides a standard for exchanging healthcare information electronically. This includes detailed patient records, lab results, medications, and more. The key benefit of FHIR is that it makes healthcare data interoperable, meaning different systems can understand and use the data without requiring extensive customization.

Key Components of FHIR

• Resources: Fundamental units of interoperability. Each resource can represent a specific type of data like a patient, medication, or observation. Resources are the building blocks of FHIR, designed to be modular and reusable.
• APIs: RESTful APIs for easy integration and interaction. FHIR uses standard HTTP protocols to allow different systems to communicate with each other efficiently. This makes it easier for developers to create apps that can interact with healthcare data.
• Profiles: Extensions and constraints that allow customization to meet specific regional or organizational needs. Profiles provide a way to define how resources should be used in a particular context, ensuring that they meet specific requirements and standards.
• Security: Built-in mechanisms to ensure data privacy and security. FHIR includes robust security features to protect sensitive healthcare information, including support for OAuth2, OpenID Connect, and other authentication and authorization standards.

North American FHIR Implementation

Overview

North America, particularly the United States and Canada, has been a front-runner in the adoption of FHIR. The region’s approach is driven by both governmental initiatives and private sector innovation. North America’s healthcare landscape is characterized by its diversity and fragmentation, which influences how FHIR is implemented.

Government Initiatives

21st Century Cures Act

The 21st Century Cures Act, passed by the United States Congress in 2016, includes provisions to advance interoperability and prevent information blocking. This legislation encourages the use of FHIR to improve patient access to their health information and to promote data sharing among healthcare providers.

ONC’s Cures Act Final Rule

The Office of the National Coordinator for Health Information Technology (ONC) issued the Cures Act Final Rule, which mandates that certified EHRs adopt FHIR-based APIs to enhance patient access to health information. This rule aims to make it easier for patients to obtain their medical records electronically and to share them with different healthcare providers.

Canada Health Infoway

Canada Health Infoway is a federally funded organization that supports the development and adoption of FHIR to improve the quality and efficiency of healthcare delivery across Canada. The organization works with provincial and territorial governments, as well as healthcare providers, to promote the use of FHIR and other health IT standards.

Private Sector Contributions

Private companies and healthcare providers in North America have significantly contributed to FHIR’s growth by developing applications and platforms that leverage FHIR for better interoperability. Examples include:

• Apple Health Records: Uses FHIR to allow patients to download and view their medical records from multiple providers. Apple Health Records provides a centralized location for patients to access their health information, improving patient engagement and enabling better health management.
• Cerner and Epic: Major EHR vendors that have integrated FHIR into their systems to facilitate data exchange. These companies are leading the way in adopting FHIR, creating more interoperable systems that can share data with other EHRs and health apps.

Challenges in North America

Despite significant advancements, North America faces several challenges in FHIR implementation:

• Fragmented Healthcare System: The diverse and fragmented nature of the healthcare system makes uniform adoption difficult. Different healthcare providers and organizations use various systems and standards, making interoperability challenging.
• Data Privacy Concerns: Ensuring data security and patient privacy across different systems is complex. As healthcare data becomes more accessible, there is a greater need to protect it from unauthorized access and breaches.
• Integration Costs: High costs associated with integrating FHIR into existing legacy systems. Healthcare providers may need to invest in new technology and training to adopt FHIR, which can be a significant financial burden.

European FHIR Implementation

Overview

Europe’s approach to FHIR implementation is more standardized and coordinated compared to North America, driven by collaborative efforts at both national and EU levels. European countries work together to promote interoperability and share best practices, creating a more unified approach to FHIR adoption.

EU Initiatives

eHealth Digital Service Infrastructure (eHDSI)

The eHealth Digital Service Infrastructure (eHDSI) facilitates the exchange of patient data across EU member states using FHIR-based solutions. This initiative aims to improve healthcare delivery for EU citizens by enabling seamless data sharing across borders.

European Interoperability Framework (EIF)

The European Interoperability Framework (EIF) promotes interoperability between public administrations, businesses, and citizens. The EIF provides guidelines and standards for achieving interoperability in various sectors, including healthcare, and supports the adoption of FHIR.

The Innovative Medicines Initiative (IMI)

The Innovative Medicines Initiative (IMI) is a public-private partnership that supports research projects like FAIR4Health, which utilizes FHIR to enhance health data interoperability across Europe. IMI projects aim to improve healthcare through innovation and collaboration.

National Efforts

Several European countries have initiated national programs to adopt FHIR, including:

• Germany: The Digital Healthcare Act (DVG) promotes the use of FHIR for health data interoperability. The DVG encourages the adoption of digital health solutions and aims to improve healthcare delivery through better data exchange.
• France: The French Digital Health Agency (ANS) has adopted FHIR for nationwide health data exchange. ANS works with healthcare providers and organizations to implement FHIR and other health IT standards.
• United Kingdom: NHS Digital leverages FHIR to improve data sharing across its services. The UK’s National Health Service (NHS) is a leader in FHIR adoption, using the standard to enhance interoperability and patient care.

Challenges in Europe

Europe, like North America, faces its own set of challenges in implementing FHIR:

• Diverse Healthcare Systems: The variability in healthcare systems and regulations across countries makes standardized implementation challenging. Each country has its own healthcare system and regulatory framework, which can complicate the adoption of a common standard like FHIR.
• Resource Constraints: Smaller countries may lack the resources needed for comprehensive FHIR adoption. Implementing FHIR requires investments in technology, training, and infrastructure, which can be difficult for countries with limited budgets.
• Data Protection Regulations: Compliance with stringent regulations like GDPR adds complexity to data sharing initiatives. The General Data Protection Regulation (GDPR) imposes strict requirements on how personal data is collected, processed, and stored, impacting FHIR implementation.

Comparing FHIR Implementation: North America vs. Europe

Approach to Standardization

• North America: Driven by a combination of government mandates and private sector innovation, leading to a more diverse but fragmented implementation landscape. The lack of a unified approach can make it difficult to achieve widespread interoperability.
• Europe: Focuses on standardization and collaboration at both the national and EU levels, aiming for a more uniform approach. The emphasis on coordinated efforts helps create a more consistent and interoperable healthcare system.

Government Involvement

• North America: The U.S. government plays a significant role through legislation and regulations, while Canada relies on coordinated federal and provincial efforts. Government initiatives are crucial for promoting interoperability and driving FHIR adoption.
• Europe: EU-wide initiatives and frameworks provide a cohesive strategy, supported by national programs in individual countries. Government involvement at both the EU and national levels ensures a more standardized approach to FHIR implementation.

Private Sector Role

• North America: The private sector is a major driver, with tech giants and EHR vendors leading the charge. Companies like Apple, Cerner, and Epic are at the forefront of FHIR adoption, developing innovative solutions to improve interoperability.
• Europe: While the private sector is involved, the emphasis is more on public sector-led initiatives and collaborations. European countries prioritize government-led efforts to achieve interoperability, with the private sector playing a supportive role.

Interoperability Goals

• North America: Focuses on patient access and data sharing across fragmented healthcare systems. The goal is to make it easier for patients to access their health information and for healthcare providers to share data seamlessly.
• Europe: Aims for seamless data exchange across national borders within the EU, enhancing continuity of care for mobile citizens. The focus is on creating a unified healthcare system where data can be shared easily across countries.

Case Studies

Case Study 1: Apple Health Records (North America)

Apple Health Records provides a prime example of successful FHIR implementation in North America. By integrating FHIR-based APIs, Apple allows patients to access their health records from multiple providers through their iPhone. This initiative has improved patient engagement and facilitated better health management.

Key Features

• Centralized Access: Patients can access their health information from various providers in one place.
• Interoperability: Uses FHIR to enable data exchange between different EHR systems and health apps.
• Patient Empowerment: Empowers patients to take control of their health information and share it with healthcare providers as needed.

Impact

• Improved Patient Engagement: Patients are more engaged in their healthcare, leading to better outcomes.
• Enhanced Data Sharing: Facilitates seamless data sharing between healthcare providers, improving care coordination.
• Innovative Solutions: Encourages the development of new health apps and services that leverage FHIR.

Case Study 2: eHealth Digital Service Infrastructure (Europe)

The eHealth Digital Service Infrastructure (eHDSI) is a key initiative by the European Union to promote cross-border health data exchange. Using FHIR standards, eHDSI enables healthcare providers in different EU countries to share patient data, ensuring continuity of care for travelers and expatriates.

Key Features

• Cross-Border Data Exchange: Facilitates the exchange of health information between EU member states.
• Standardization: Uses FHIR to ensure that data can be understood and used by different healthcare systems.
• Patient Safety: Enhances patient safety by providing healthcare providers with access to comprehensive patient records.

Impact

• Continuity of Care: Ensures that patients receive consistent and high-quality care regardless of where they are in the EU.
• Efficient Healthcare Delivery: Reduces the need for duplicate tests and procedures, improving efficiency and reducing costs.
• Collaborative Innovation: Encourages collaboration between EU countries to develop innovative health solutions.

Table: Comparison of FHIR Implementation

Future Outlook

Emerging Trends

1. AI and Machine Learning: Integrating AI with FHIR can enhance data analytics and patient care. AI algorithms can analyze vast amounts of healthcare data to identify patterns, predict outcomes, and provide personalized treatment recommendations. FHIR’s standardized data format makes it easier to apply AI and machine learning techniques to healthcare data.
2. Telehealth: FHIR’s role in telehealth will expand, providing standardized data exchange for remote care. Telehealth services rely on the ability to access and share patient information in real-time. FHIR enables this by providing a standardized way to exchange data between telehealth platforms and EHR systems, improving the quality and continuity of care for remote patients.
3. Blockchain: Blockchain technology could be integrated with FHIR to enhance data security and integrity. Blockchain provides a secure, decentralized way to store and share data, making it an ideal complement to FHIR’s interoperability capabilities. By using blockchain, healthcare providers can ensure that patient data is tamper-proof and that access is strictly controlled.

Opportunities for Collaboration

Collaboration between North America and Europe can lead to:

• Shared Best Practices: Exchanging knowledge and strategies for successful FHIR implementation. Both regions can learn from each other’s experiences and challenges, leading to more effective and efficient FHIR adoption.
• Joint Research Initiatives: Collaborative research projects to advance FHIR standards and technologies. By working together on research initiatives, North America and Europe can develop new and improved ways to implement and use FHIR, benefiting the global healthcare community.
• Global Standards Alignment: Working towards global harmonization of health data standards. Aligning FHIR standards globally can facilitate international data exchange, improve patient care across borders, and support global health initiatives.

Conclusion

FHIR has the potential to revolutionize healthcare data interoperability, but its implementation varies significantly between North America and Europe. While North America’s approach is driven by a combination of government mandates and private sector innovation, Europe’s strategy focuses on standardization and collaboration at the EU and national levels. Understanding these differences and leveraging the strengths of each region can help advance FHIR implementation globally, ultimately improving patient care and healthcare outcomes.

FAQs

1. What is FHIR, and why is it important?

FHIR (Fast Healthcare Interoperability Resources) is a standard for exchanging healthcare information electronically. It is important because it enables interoperability between different healthcare systems, making it easier to access and share patient data, which improves healthcare delivery and patient outcomes.

2. How does FHIR implementation differ between North America and Europe?

North America’s FHIR implementation is driven by a mix of government mandates and private sector innovation, resulting in a diverse but fragmented landscape. In contrast, Europe’s approach is more standardized and coordinated, with EU-wide initiatives and national programs promoting interoperability.

3. What are the main challenges of FHIR implementation in North America?

The main challenges include the fragmented nature of the healthcare system, data privacy concerns, and high integration costs. These factors complicate uniform adoption and seamless interoperability.

4. How is the private sector contributing to FHIR adoption in North America?

The private sector, including tech giants and EHR vendors, plays a significant role by developing FHIR-based applications and platforms that enhance interoperability. Examples include Apple Health Records and the integration of FHIR by EHR vendors like Cerner and Epic.

5. What future trends can impact FHIR implementation?

Emerging trends like AI and machine learning, telehealth, and blockchain technology are expected to impact FHIR implementation. These technologies can enhance data analytics, remote care, and data security, further advancing interoperability in healthcare.

the references for the article:

1. Health Level Seven International (HL7). Fast Healthcare Interoperability Resources (FHIR) Overview. Available online: https://www.hl7.org/fhir/overview.html
2. U.S. Department of Health and Human Services. 21st Century Cures Act. Available online: https://www.hhs.gov/about/news/2020/05/01/hhs-finalizes-historic-rules-to-provide-patients-more-control-of-their-health-data.html
3. European Commission. eHealth Digital Service Infrastructure (eHDSI). Available online: https://ec.europa.eu/health/ehealth/dsi_en

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Understanding FHIR: A Brief Overview

What is FHIR?

FHIR, developed by Health Level Seven International (HL7), is a standard for exchanging healthcare information electronically. It builds on previous HL7 standards but introduces new paradigms for easier and more efficient data exchange. FHIR leverages modern web technologies, including RESTful APIs, which make it versatile and allow for building enterprise-level data management solutions like Kodjin.

Key Features of FHIR

• Interoperability: Facilitates seamless data exchange across different healthcare systems.
• Modularity: Comprised of resources that can be assembled into working systems.
• Scalability: Suitable for use in small applications and large healthcare networks.
• Extensibility: Allows customization to meet specific needs without compromising interoperability.

The Rise of FHIR: Historical Context

Early Development and Adoption (2011-2014)

FHIR’s journey began in 2011, driven by the need to address limitations in previous HL7 standards. Its initial versions focused on creating a robust framework that could handle diverse healthcare data types. The first draft of FHIR was released in 2012, and by 2014, it had already garnered attention from key industry players due to its potential to revolutionize healthcare interoperability.

In these early years, FHIR’s primary objective was to simplify the exchange of healthcare information through a more flexible and comprehensive framework compared to its predecessors, HL7 v2 and HL7 v3. These previous standards faced criticism for being too complex and difficult to implement. FHIR was designed to overcome these challenges by adopting a modern approach that included the use of web technologies like JSON and XML for data representation and RESTful APIs for data exchange.

Growing Momentum (2015-2017)

Between 2015 and 2017, FHIR adoption accelerated. This period saw the introduction of the FHIR DSTU2 (Draft Standard for Trial Use) version, which provided a more mature and stable framework for developers. The U.S. Office of the National Coordinator for Health Information Technology (ONC) recognized FHIR as a strategic component in achieving nationwide interoperability, further boosting its adoption.

The DSTU2 version marked a significant milestone as it offered a more refined set of resources and guidelines, making it easier for developers to implement FHIR in real-world applications. During this period, several pilot projects and proof-of-concept implementations demonstrated FHIR’s potential, encouraging more healthcare organizations to explore its use.

Major Drivers of FHIR Adoption

Regulatory Support

Regulatory frameworks, particularly in the United States, have been a significant driver of FHIR adoption. The 21st Century Cures Act, enacted in 2016, mandated the use of interoperable systems to enhance patient access to health data. This legislation explicitly endorsed FHIR, propelling its integration into electronic health records (EHRs) and other healthcare systems.

The ONC’s final rule on interoperability and information blocking, released in 2020, further cemented FHIR’s role in the healthcare ecosystem. This rule requires healthcare providers, payers, and health IT developers to adopt standardized APIs based on FHIR to ensure patients have access to their health information without unnecessary barriers.

Technological Advancements

The rise of cloud computing, mobile health applications, and telehealth has also fueled FHIR adoption. These technologies require efficient and scalable data exchange mechanisms, making FHIR an ideal choice. The standard’s RESTful API approach aligns well with modern development practices, facilitating its integration into innovative healthcare solutions.

For instance, mobile health applications that track patient health metrics and provide remote monitoring services rely on FHIR to access and exchange data with EHR systems. Telehealth platforms use FHIR to share patient records, lab results, and treatment plans between remote providers and healthcare facilities, enhancing the quality of care delivered to patients regardless of location.

Industry Collaboration

Collaboration among healthcare stakeholders, including providers, payers, and technology vendors, has been pivotal in promoting FHIR. Initiatives like the Argonaut Project, launched in 2014, brought together leading EHR vendors and healthcare organizations to accelerate FHIR implementation. Such collaborative efforts have led to the development of robust FHIR-based applications and resources.

The Argonaut Project has played a critical role in driving the adoption of FHIR by creating implementation guides and tools that address common interoperability challenges. This collaborative effort has helped standardize FHIR implementations across different organizations, ensuring that data can be shared seamlessly and effectively.

Implementation Challenges

Data Security and Privacy

While FHIR offers significant benefits, ensuring data security and privacy remains a critical challenge. Healthcare data is highly sensitive, and breaches can have severe consequences. Implementing FHIR requires stringent security measures, including encryption, authentication, and access control, to protect patient information.

Organizations must implement robust security protocols to safeguard data exchanged via FHIR APIs. This includes using secure communication channels (e.g., HTTPS), implementing strong authentication mechanisms (e.g., OAuth 2.0), and ensuring that only authorized users have access to sensitive information. Additionally, healthcare providers must comply with regulations such as the Health Insurance Portability and Accountability Act (HIPAA) to ensure data privacy and security.

Standardization and Compliance

Achieving consistent implementation across diverse healthcare systems is another challenge. Variability in how different organizations interpret and implement FHIR can lead to interoperability issues. Efforts are ongoing to establish clear guidelines and best practices to ensure uniformity and compliance with the standard.

HL7 and other industry groups are working to develop comprehensive implementation guides and certification programs to address these challenges. These resources provide detailed instructions on how to implement FHIR in various scenarios, helping organizations achieve consistent and compliant implementations.

Resource and Expertise Constraints

Adopting FHIR necessitates investment in technology and skilled personnel. Smaller healthcare providers and organizations with limited resources may struggle to implement and maintain FHIR-based systems. Addressing these constraints involves providing adequate training and support to facilitate adoption across the healthcare spectrum.

Healthcare organizations must invest in training programs to equip their staff with the necessary skills to implement and manage FHIR-based systems. Additionally, industry partnerships and collaborations can provide smaller providers with the resources and support they need to adopt FHIR successfully.

Case Studies in FHIR Adoption

Mayo Clinic

The Mayo Clinic has been a pioneer in leveraging FHIR to enhance patient care. By integrating FHIR into its EHR system, the clinic has improved data sharing among healthcare providers, leading to better coordinated care and enhanced patient outcomes. Their FHIR implementation supports a range of functions, from appointment scheduling to clinical data exchange.

The Mayo Clinic’s use of FHIR has enabled seamless integration of patient data from various sources, allowing healthcare providers to access comprehensive and up-to-date patient records. This has improved clinical decision-making and reduced the risk of medical errors. The clinic’s success with FHIR demonstrates the potential of the standard to transform healthcare delivery.

SMART on FHIR

The SMART (Substitutable Medical Applications, Reusable Technologies) on FHIR platform is a notable example of FHIR’s potential. It enables developers to create interoperable healthcare applications that can run across different EHR systems. SMART on FHIR has facilitated the development of innovative apps for chronic disease management, clinical decision support, and patient engagement.

The SMART on FHIR platform provides a set of APIs and tools that allow developers to create applications that can access and interact with EHR data in a standardized way. This has led to the creation of a vibrant ecosystem of healthcare apps that can be easily integrated into existing EHR systems, enhancing their functionality and improving patient care.

Global Perspectives on FHIR Adoption

United States

In the United States, FHIR adoption has been driven by regulatory mandates and the push for nationwide interoperability. The ONC’s support for FHIR, coupled with initiatives like the CommonWell Health Alliance and Carequality, has accelerated its integration into healthcare systems. Major EHR vendors, including Epic and Cerner, have incorporated FHIR into their platforms, enhancing data exchange capabilities.

The U.S. has seen significant progress in FHIR adoption due to the alignment of regulatory policies and industry initiatives. The CommonWell Health Alliance, for example, connects healthcare providers across the country using standardized APIs based on FHIR, enabling secure and efficient data exchange. This nationwide network facilitates the seamless transfer of patient information, improving care coordination and patient outcomes.

Europe

In Europe, FHIR adoption varies by country, influenced by differing healthcare systems and regulatory environments. The European Union’s eHealth Network has endorsed FHIR as part of its efforts to promote cross-border health data exchange. Countries like the United Kingdom and Germany have made significant strides in implementing FHIR to improve healthcare delivery and patient access to data.

The UK’s National Health Service (NHS) has adopted FHIR as part of its efforts to create a more integrated and interoperable healthcare system. The NHS has developed several FHIR-based standards and implementation guides to support the exchange of patient data across different healthcare providers. In Germany, the government’s efforts to digitize healthcare have included the adoption of FHIR to enable seamless data exchange and improve patient care.

Asia-Pacific

The Asia-Pacific region is also witnessing growing interest in FHIR. Countries such as Australia and New Zealand have incorporated FHIR into their national health information frameworks to enhance interoperability. In India, the government’s National Digital Health Mission (NDHM) is leveraging FHIR to create a unified health information system.

Australia’s My Health Record system, which provides patients with access to their health information, uses FHIR to facilitate data exchange between healthcare providers and the national health information system. This has improved the quality of care by ensuring that healthcare providers have access to accurate and up-to-date patient information. In New Zealand, the government has implemented FHIR to support the exchange of health information between different healthcare organizations, improving care coordination and patient outcomes.

Future Outlook for FHIR

Enhanced Interoperability

The future of FHIR looks promising, with ongoing efforts to enhance interoperability across healthcare systems. The development of new FHIR versions and resources will further refine its capabilities, enabling more seamless data exchange and integration.

Future versions of FHIR will include additional resources and implementation guides to address specific use cases and scenarios. These enhancements will help healthcare organizations achieve even greater interoperability and ensure that patient data can be exchanged seamlessly across different systems and platforms.

Expansion into New Domains

FHIR’s applicability is expanding beyond traditional healthcare settings. It is being used in public health initiatives, research, and genomics, demonstrating its versatility. The integration of FHIR with emerging technologies like artificial intelligence and machine learning holds the potential to revolutionize healthcare delivery and outcomes.

In public health, FHIR is being used to support initiatives such as disease surveillance and outbreak management. By enabling the exchange of data between public health agencies and healthcare providers, FHIR helps improve the timeliness and accuracy of public health reporting. In research, FHIR is being used to facilitate the exchange of data between research institutions and healthcare providers, supporting the development of new treatments and therapies. In genomics, FHIR is being used to integrate genetic data into clinical workflows, enabling personalized medicine and improving patient outcomes.

Continued Industry Collaboration

Industry collaboration will remain crucial in driving FHIR adoption. Partnerships between healthcare providers, technology vendors, and regulatory bodies will facilitate the development of innovative solutions and best practices. Collaborative efforts will also address implementation challenges and ensure the widespread adoption of FHIR.

Ongoing collaboration between industry stakeholders will help address common challenges and ensure that FHIR implementations are consistent and effective. These partnerships will also drive the development of new tools and resources to support FHIR adoption and ensure that the standard continues to evolve to meet the needs of the healthcare industry.

Table: Key Milestones in FHIR Adoption

Conclusion

The adoption of FHIR over the past decade has significantly transformed healthcare interoperability. Driven by regulatory support, technological advancements, and industry collaboration, FHIR has become a cornerstone of modern healthcare systems. Despite challenges related to data security, standardization, and resource constraints, the future of FHIR looks bright, with ongoing efforts to enhance its capabilities and expand its reach.

FAQs

1. What is the main purpose of FHIR in healthcare?

FHIR aims to facilitate seamless electronic exchange of healthcare information across different systems, improving interoperability and enhancing patient care. It provides a standardized framework that allows different healthcare systems to communicate with each other, ensuring that patient data can be accessed and shared easily and securely.

2. How has regulatory support influenced FHIR adoption?

Regulatory frameworks like the 21st Century Cures Act have mandated the use of interoperable systems, explicitly endorsing FHIR, thereby accelerating its adoption in healthcare. These regulations require healthcare providers and technology vendors to implement FHIR-based APIs, ensuring that patients have access to their health information and that data can be exchanged seamlessly between different systems.

3. What are some common challenges in implementing FHIR?

Common challenges include ensuring data security and privacy, achieving consistent implementation across systems, and addressing resource and expertise constraints. Healthcare organizations must implement robust security measures to protect patient data, ensure that their FHIR implementations are compliant with standards, and invest in training and resources to support their adoption of FHIR.

4. Can FHIR be used in areas other than traditional healthcare settings?

Yes, FHIR is expanding into domains such as public health, research, and genomics, showcasing its versatility in various applications beyond traditional healthcare settings. FHIR is being used to support public health initiatives, facilitate research data exchange, and integrate genetic data into clinical workflows, demonstrating its potential to transform healthcare delivery and outcomes.

5. What is the future outlook for FHIR adoption?

The future of FHIR is promising, with ongoing efforts to enhance interoperability, expand its applicability into new domains, and foster industry collaboration to drive widespread adoption. As FHIR continues to evolve, it will play an increasingly important role in enabling seamless data exchange and improving patient care across the healthcare industry.

References

1. Health Level Seven International (HL7) – FHIR: https://www.hl7.org/fhir/
2. Office of the National Coordinator for Health Information Technology (ONC) – Interoperability: https://www.healthit.gov/topic/interoperability
3. Mayo Clinic – FHIR Case Study: https://www.mayoclinic.org
4. SMART on FHIR: https://smarthealthit.org/
5. 21st Century Cures Act: https://www.congress.gov/bill/114th-congress/house-bill/34
6. Argonaut Project: https://argonautwiki.hl7.org/
7. CommonWell Health Alliance: https://www.commonwellalliance.org/
8. Carequality: https://carequality.org/
9. National Health Service (NHS) – UK: https://www.nhs.uk/
10. National Digital Health Mission (NDHM) – India: https://ndhm.gov.in/
11. My Health Record – Australia: https://www.myhealthrecord.gov.au/

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The realm of machine learning is a multifaceted tapestry woven with intricate patterns of algorithms, neural networks, and statistical models. It encompasses supervised, unsupervised, and reinforcement learning, each offering its own unique set of tools to unravel the mysteries concealed within data. Supervised learning, akin to a watchful mentor, teaches machines to make predictions by learning from labeled training data, while unsupervised learning, like an explorer charting uncharted territories, seeks to discover patterns and structures within unlabeled data. Reinforcement learning, on the other hand, is akin to a virtual apprentice, learning from interactions and experiences to make sequential decisions.

The foundational element in this mosaic is data, often described as the new oil, and rightfully so. Without data, machine learning is like a ship adrift in an ocean of possibilities. The quality, quantity, and variety of data play pivotal roles in the efficacy of machine learning models. The more diverse and voluminous the data, the richer the insights that can be unearthed.

Data preprocessing, the art of cleaning, transforming, and augmenting raw data, is the first threshold in our journey. It’s akin to refining a rough diamond, ensuring that the data is pristine and suitable for analysis. Techniques such as outlier detection, missing data imputation, and feature scaling are the brushes and chisels of data preprocessing, sculpting data into a form that can be readily absorbed by machine learning models.

Once the data is refined, it’s time to choose the right algorithm, the heart of machine learning. Each algorithm has its own unique strengths and weaknesses, akin to specialized tools in a craftsman’s workshop. Decision trees, akin to versatile Swiss army knives, are adept at handling both classification and regression tasks. Support Vector Machines, like precision instruments, excel at finding optimal decision boundaries. Neural networks, inspired by the intricacies of the human brain, shine in tasks requiring complex pattern recognition.

Model training is the crucible where algorithms are honed and refined. It involves exposing the model to the training data, allowing it to learn and adapt. The process is akin to forging a sword, with each pass through the data sharpening the model’s predictive edge. Hyperparameter tuning, the delicate art of fine-tuning model parameters, is akin to adjusting the blade’s angle and temper to achieve the perfect balance between underfitting and overfitting.

Validation and testing are the litmus tests of a machine learning model’s mettle. Cross-validation, the art of assessing a model’s performance across multiple subsets of the data, ensures that the model’s capabilities are robust and not overly tailored to the training data. Testing, or evaluation, is akin to a grand unveiling, where the model’s true predictive prowess is revealed.

Interpreting machine learning models is often akin to deciphering the hieroglyphs of an ancient civilization. Techniques like feature importance analysis, SHAP values, and LIME (Local Interpretable Model-agnostic Explanations) shed light on the inner workings of black-box models, making their decisions more transparent and understandable.

In the era of big data, scalability is the linchpin of success. Distributed computing frameworks like Apache Hadoop and Apache Spark are the engine rooms that power machine learning at scale. These frameworks harness the power of clusters of machines to process vast datasets in parallel, enabling the training of models on data lakes that would otherwise be insurmountable.

Deploying machine learning models into production is the culmination of the journey. It’s akin to launching a satellite into orbit, where the model becomes a beacon guiding real-time decisions. Containerization technologies like Docker and orchestration tools like Kubernetes are the launch pads, ensuring that models are seamlessly integrated into the production environment.

The benefits of harnessing the power of machine learning to unlock data insights are manifold. Businesses can leverage predictive analytics to forecast demand, optimize operations, and enhance customer experiences. Healthcare can utilize machine learning for early disease detection, drug discovery, and personalized treatment plans. Autonomous vehicles can navigate complex environments with the aid of machine learning algorithms, enhancing safety and efficiency.

However, with great power comes great responsibility. Ethical considerations, fairness, and bias mitigation are critical aspects of deploying machine learning in real-world scenarios. Ensuring that machine learning models do not perpetuate discrimination and bias requires vigilance and a commitment to ethical AI principles.

In conclusion, machine learning is the key that unlocks the doors to data insights. It is a journey through the data wilderness, a fusion of art and science, and a catalyst for innovation. As we navigate this landscape, we must tread carefully, ensuring that the insights we unearth are not only powerful but also ethical, equitable, and just. The future lies in our hands, and with the power of machine learning, we can shape it into a brighter and more informed world.

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Chapter 1: Pioneering the Cosmos

The saga of cosmic exploration commenced eons before modern space agencies and sophisticated spacecraft. Distant stargazers such as Galileo Galilei and Johannes Kepler initiated this epic journey by unveiling the mysteries of the cosmos through telescopic observations. These luminaries ignited the imaginations of generations yet unborn, igniting a yearning to fathom the depths of the universe.

It’s imperative to acknowledge Konstantin Tsiolkovsky, a visionary Russian scientist often lauded as the progenitor of astronautics. Tsiolkovsky’s groundbreaking formulations, including the rocket equation and the concept of multi-stage rockets, laid the critical foundation for future space exploration. These visionary ideas precipitated the birth of the Solutions Architecture Service that serves as the nucleus for designing complex cosmic missions today.

Chapter 2: The Space Race Phenomenon

The mid-20th century heralded a pivotal epoch in space exploration, characterized as the Space Race. The United States and the Soviet Union engaged in a spirited competition, determined to showcase their technological prowess and assert ideological dominance. This intense rivalry propelled leaps and bounds in rocket technology and space science.

In 1957, the Soviet Union astounded the world with the launch of Sputnik 1, humanity’s inaugural artificial satellite. This monumental event ushered in the modern space age, leading to the establishment of national space agencies, with NASA at the forefront. The Solutions Architecture Service’s critical role during this epoch is evident, as it facilitated the intricate design of systems essential for catapulting humans beyond Earth’s gravitational embrace.

Chapter 3: Embarking on Human Spaceflight

April 12, 1961, is etched in history as the day Yuri Gagarin, a Soviet cosmonaut, became the inaugural human to venture into the boundless expanse of outer space aboard the Vostok 1 spacecraft. This historic feat flung open the gates of crewed space exploration. Shortly thereafter, American astronaut Alan Shepard joined the ranks as the first American to traverse the cosmos.

As human spaceflight began to gain traction, the Solutions Architecture Service underwent remarkable transformations. It played a pivotal role in crafting life-sustaining systems, spacecraft navigation protocols, and advanced communication networks, thereby safeguarding the astronauts on their celestial odysseys.

Chapter 4: Triumph on the Lunar Surface

The Apollo program, orchestrated by NASA, stands as an iconic pinnacle in the annals of space exploration. On July 20, 1969, the world watched in awe as the lunar module, Eagle, from Apollo 11 touched down gently on the lunar terrain. Neil Armstrong’s immortal words, “That’s one small step for [a] man, one giant leap for mankind,” resonated globally.

The triumphs of the Moon landings were the culmination of meticulous research, development, and precise planning. The Solutions Architecture Service proved to be an indispensable partner, orchestrating the intricate systems essential for lunar voyages, encompassing spacecraft navigation, lunar module descent, and safe ascent back to Earth.

Chapter 5: The Era of Space Shuttles

The 1980s ushered in a novel era of cosmic exploration with the advent of the Space Shuttle program. These reusable spacecraft, exemplified by the likes of the Space Shuttle Columbia and Challenger, revolutionized space travel. Regular missions into low Earth orbit became the norm, democratizing space access and enabling unparalleled scientific research.

During this epoch, the Solutions Architecture Service continued its evolution, adapting to the unique demands of the Space Shuttle program. It played a pivotal role in mission strategizing, seamless deployment of payloads, and ensuring the astronauts’ safety during their journeys to and from the cosmos.

Chapter 6: Uniting Globes in Space

As the chronicles of space exploration advanced, international collaboration took center stage. The International Space Station (ISS) epitomizes the potential of global cooperation. This celestial outpost serves as both a microgravity laboratory and a symbol of unity, transcending national borders in the pursuit of scientific enlightenment.

The Solutions Architecture Service metamorphosed further, facilitating fluid communication and coordination among an array of international partners. It masterminded the harmonious integration of multifarious spacecraft systems and protocols, allowing astronauts hailing from diverse nations to work in synergy and harmony.

Chapter 7: A New Cosmic Frontier

The 21st century heralds fresh challenges and vistas in space exploration. Private enterprises like SpaceX and Blue Origin have entered the cosmic arena, driving innovation and mitigating the costs associated with space access. Rovers like the Mars Curiosity rover have successfully graced the Martian surface, while distant asteroids are no longer beyond our reach.

The Solutions architecture service has adapted nimbly to this dynamic landscape, offering vital support to commercial endeavors and interplanetary expeditions alike. Its pivotal role in ensuring the triumph of missions to enigmatic destinations such as Mars, where both opportunities and obstacles loom large, underscores its enduring relevance.

Conclusion

The history of cosmic exploration is a testament to humanity’s indomitable spirit, boundless innovation, and unflagging pursuit of knowledge. From early visionaries to contemporary trailblazers, our expedition into the cosmos has been marked by ingeniousness, resolute tenacity, and the continually evolving Solutions Architecture Service. As we persist in pushing the boundaries of cosmic exploration, it is this service that will enable us to scale even greater heights, unlocking the profound mysteries of the universe. The cosmos beckons, and humanity, armed with the Solutions Architecture Service, stands poised to heed its call.

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Companies still use antiquated techniques like spreadsheets to manage and track leads. However, this is a terribly ineffective approach that, according to Zoho, can prevent the conversion of almost 70% of leads. a specific lead management platform

Applying strategic strategies is necessary to generate new leads and make sure that the greatest number of leads make it to the ultimate conversion stage.

Any person or business that might be interested in your goods is referred to as a lead. This interest can be shown by exchanging contact information, selecting the “register now” link, going to your website, watching a product video, or taking any other action. Lead management leverages the information offered by a lead to methodically classify them and schedule the action items.

Depending on where each lead is on the marketing funnel, you can either follow up with them directly or retarget them with content. Using your website’s contact form, a C-level representative in the B2B industry might make contact. This is an example of a bottom-funnel lead because your sales team can get in touch with the person and start the process of acquiring the account. A top-of-the-funnel lead, on the other hand, is someone who has been to your website more than three times. To spark additional interest, you can run advertisements that are specifically intended for this audience. Lead management encompasses each and every one of these actions.

As a result, lead management is a vast topic that encompasses almost all sales techniques used to generate and convert leads. Although it is possible to do this manually, it is best to use a digital platform that connects to both your website and your CRM to establish a continuous lifetime of data. The customer can then be led through this lifecycle in a straightforward manner, from first interest to final conversion.

How can you determine if you’re prepared for a next-generation lead management system, though?

You should keep an eye out for the following red flags:

There isn’t just one place to get knowledge. To follow up on leads, your sales and marketing executives must frequently hop between platforms.

Sales has been given unqualified leads. This implies that identifying good and bad leads is taking up too much of your time.

The actions of leads are invisible. Because of this, you are unable to run tailored content campaigns and must rely on customers making contact with you directly.

You frequently miss out on opportunities. It is normal to miss out on a few leads in any lead management system, but this shouldn’t go beyond a certain point.

Poor conversion rates exist. When nurturing actions are lacking, promising leads frequently fail to develop into qualified prospects.

If any of these situations ring a bell, it’s obvious that your company needs a stronger lead management strategy supported by technology. Once installed, it’s crucial to determine who will be responsible for lead management.

Lead management belongs to who?

This is a crucial factor to take into mind because the ROI of the lead management system won’t increase until a particular stakeholder takes ownership and responsibility for it. Interestingly, depending on where the consumer is in the buying process, lead management sits in between sales and marketing. For instance, there are marketing qualified leads (MQL), which are inquiries from customers who want further details on a product. Marketers can now distribute presentations and pitches in an effort to win over customers.

Conversely, sales executives deal directly with sales qualified leads (SQL). These are additionally referred to as “hot/warm leads,” which suggests that they are eager for conversion. Sales can step in at this point and rapidly complete the transaction.

Collaboration between sales and marketing on lead management is always a recommended practice, regardless of the prospects’ intent or level of interest. Marketing is in a position to gather leads, follow up on them, and transfer them to sales when the customer is prepared to buy. To assure upselling and cross-selling, sales is better positioned to qualify the leads and nurture them in collaboration with the marketing team.

This leads us to the actual lead management procedure.

Opens a new window for more information: Top 5 Retail Lead Management Tools for 2020

4 Stages to Lead Management Process Understanding

This entire process can be automated and enhanced if you decide to employ a digital platform by utilizing analytics and artificial intelligence. Generally speaking, a lead must be: 1. Tracked

Since there are numerous ways to generate leads, including through social media, email marketing, paid advertisements, and website visits, we start with automated lead creation. In the B2B industry, leads can even be obtained from phone calls; however, all of these facts must be automatically entered into the tracking system.

Now that lead behavior can be monitored, your product will receive even more intense interest. If a lead consistently visits the product landing page in the same week, for instance, you may start a targeted email campaign and use content to convert the lead.

2. Dispersed

This step in the lead management process is rather straightforward. You can send the information to the appropriate sales team once the leads have been gathered and tracked. For instance, you could have distinct executives for your small-to-midsize business clients, another for a different industry, and regional sales teams.

Keep in mind that your possibility of conversion increases the sooner sales contacts a lead.

3. Adequate

This process was carried out manually for a very long time, relying on the knowledge and experience of sales and marketing executives. Now, AI technology can monitor the traits and parameters defining the lead and can auto-qualify them with the right label.

In fact, a powerful lead management tool will assign a quality score to every lead, based on your ideal customer persona and data collected from lead behavior tracking. Lead qualification significantly cuts down the time spent on follow-ups.

4. Nurtured

In an ideal environment, a qualified lead will certainly result into a successful sale – however, it isn’t always the case.

Your leads may start losing interest, could change their mind about the product demand, or be attracted by a rival. These “warm” leads (promising, yet not displaying instant interest) must be properly cultivated in order to achieve conversion.

5 Best Practices for Lead Management

You can adhere to a number of best practices to ensure efficient lead handling. These assist in achieving two long-term goals: capturing and converting the greatest number of leads possible, and reducing the proportion of “poor leads” in your sales and marketing funnel.

When handling leads, you should adhere to the following five best practices

1. Use targeted content to capture leads

A key component of your lead management approach is targeted content. It develops your brand as a thought leader, a product specialist, and a seller in addition to the B2B market. How-to tips and product reviews, even in a B2C example for lifestyle and cosmetics, can greatly increase client confidence and maintain interest.

2. Consistently employ cleaned lead data

Your sales and marketing system’s data is what determines how successful your campaigns are. The “Garbage-in-Garbage-out” approach applies in this situation since your team will be expending unnecessary effort on fruitless follow-ups and irrelevant campaigns if your sales and CRM funnel is filled with bad leads.

3. Evaluate the results of lead management initiatives

It goes without saying that keeping track of which lead generation efforts are producing the best outcomes is a crucial best practice. To increase profitability, investments in these directions can be strengthened.

4. At the top of the funnel, spread a big net.

Starting the lead management process with hot leads is not advised. It’s likely that your initial lead database may include a range of prospects who are at various phases of the buying process. If you simply look for hot leads, you can lose out on possible “warm” leads that could be encouraged to convert.

You can use strategies like social media presence, pay-per-click display advertising, and properly displayed contact forms to reach a wide audience at the top of the funnel.

5. Work with the sales staff

We cannot emphasize enough how important it is for marketing and sales to work together to develop an effective lead management strategy. While marketers are responsible for producing leads, it is the sales representative’s responsibility to follow up with, assist, and convert the prospect. These two tasks can improve conversion rates and rethink the client experience by cooperating.

5 Top Platforms for Lead Management System Selection

Salesforce, Marketo, and many more digital solutions are available to help automate and enhance the lead creation process. They serve in many respects as platforms for customer relationship management (CRM), mediating communications between your business and potential clients. Therefore, if you’re certain that you need lead management, here are five platforms to take into account:

The company’s sales cloud platform also features an effective lead management capability. Salesforce Opens a new window- Salesforce is a market leader in CRM and associated activities. You can keep track of your active leads using Salesforce lead management Opens a new window, automatically score and route them to the right team, and even integrate your marketing efforts to track their effects on lead creation.

Marketo is another well-known name in the martech industry, and it is supported by Adobe’s capabilities for CEM. Salesforce’s lead management solution from Marketo is a perfect substitute because it integrates your inbound and outbound marketing initiatives and has almost all of Salesforce’s features. A clever analytics feature that connects marketing activities to the ROI produced is also available.

Another alternative to Salesforce is Freshsales. It provides a 360-degree customer dashboard that groups and lists leads that have been won, are open, and have been closed. Similar to Salesforce, it has lead scoring built in so that your sales staff only follow up with the most potential prospects. With an integrated calendar, file manager, and note-taking feature, the platform facilitates communication between sales and marketing.

HubSpot, a provider of marketing solutions, has a CRM automation tool of its own called HubSpot Lead Management.

leads to the opening of a new window that can be used for lead management. To streamline the lead capture and follow-up process, you may automatically send emails, record calls, and exchange notes. HubSpot distinguishes itself from Salesforce in this area thanks to its interesting set of lead generating solutions. You may increase your lead outreach with live bots, social media ads, website forms, and other tools.

The AI-powered lead management package from Zoho, Zoho CRM, is very well-liked by both big corporations and small organizations. It can be integrated with your marketing campaigns to give end-to-end analytics, it is compatible with multi-source lead generation, and it automates distribution and scoring. Gartner Peer Insights recognized Zoho CRM the Best CRM Lead Management Software of 2018.

Introduction to Lead Management: The Future for Marketers

You are now prepared to launch a lead management program as you are armed with these lead management best practices and a deeper comprehension of what it means for your business. Be sure to:

Set a benchmark using your current metrics (customer base, content repository size, martech infrastructure, etc.)

Analyze your customers’ requirements and expectations thoroughly to ensure that your lead generation strategies are effective.

Create a content calendar that is easy to use in attracting and nurturing leads.

Do extensive research and choose a lead management platform that is compatible with your goals and company size.

You now know the basics of lead management, and it’s time to open channels of communication between sales and marketing. The success of your strategic goal ultimately depends on this, which is assisted by modest regular actions made by your sales and marketing professionals.

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It turns out that trees, like human bodies, can carry signs of past trauma or stress. Dendrochronology studies tree rings to find out what events have happened to a tree during its existence. Such events could include, for example, a lightning strike or a forest fire.

Scientific basis of the method

Trees growing in climates with a seasonal climate grow differently in summer and winter: the main growth takes place in summer, while in winter the growth is greatly retarded. The difference in conditions means that wood that grows in winter and summer has different characteristics, including density and color. Visually, this manifests itself in the fact that the tree trunk on the cross-section has a clearly visible structure in the form of a set of concentric rings. Each ring corresponds to one year of the tree’s life (“winter” layer is thinner and visually just separates one “summer” ring from another). It is a well-known way of determining the age of a cut tree by counting the number of annual rings on the saw.

Depending on many factors that acted during the summer period (length of season, temperature regime, amount of precipitation, etc.) the thickness of annual rings is different in different years of a tree’s life, while the thickness of annual rings growing in the same year for trees of the same species growing in the same area is approximately the same. Differences in the thickness of rings in different years are quite significant. If graphs of annual rings thickness variation by years are plotted for trees growing in the same area at the same time, these graphs will be quite close, while they will not coincide for trees growing at different times (due to randomness of climatic factors, exact coincidence of rings thickness sequence over sufficiently long periods is highly unlikely).

Comparison of the sequence of annual rings preserved in a wooden object and samples, the dating of which is known, allows choosing a sample with a matching set of annual rings and thus determine the period in which the wood from which the object was cut down. Such a comparison is actually dendrochronological dating.

Dendrochronological scales

Based on the study of wood samples, the dating of which is known, the so-called dendrochronological scale is constructed – a sequence of thicknesses of annual rings of trees of a particular species in a particular area, from the current moment and as far back in time as possible. For near-contemporary periods, measurements of annual rings of living trees that are old enough are used (there are methods of making such measurements that do not require cutting down the tree).

In order to extend the dating scale by a time interval beyond the limits of one tree’s life, “cross-dating” is used. Its essence is to link together successive generations of trees, the life years of which overlap. Specialists in dendrochronology believe that even on the basis of the roughest method (when rings are divided into two classes – “wide” and “narrow”) 10-year coincidence of alternation of rings allows to identify the scale with probability of error not exceeding 0.1% (as 1/2¹⁰= 0.099%). When taking into account the width of each ring and applying methods of mathematical statistics, the probability of error is significantly reduced. In recent years, X-ray analysis of annual rings is used, which allows taking into account not only the width of the rings, but also other parameters (e.g., the density of wood in the ring). Thus, the dendrochronological scale extends back in time as far as the available material allows to continue the continuous sequence.

After constructing the scale for a certain tree species in a local area, the correlations of this species with other species are analyzed, as well as changes in the ring species in neighboring areas. This allows the absolute scale to be gradually extended to a wider geographic area.

Absolute and relative dating scales can be constructed using the dendrochronological method. If the exact (absolute) life time of one of the generations of trees involved in the dating is known, the resulting scale will be absolute. For example, it may be living trees whose age is known by the number of rings. With the help of the absolute dating scale it is possible to determine the age of wooden objects with almost 100% reliability (in the case of exact coincidence of the order of a sufficient number of rings). In some cases it is possible to construct fragments of the dendrochronological scale based on fragments of wood dated in a different way (for example, timbers from the wall of the structure whose date of construction is known from historical documents). In such cases the resulting scale will no longer be absolute, but relative. The reliability of dating with the help of relative scales, obviously, depends on the reliability of dating of “reference” samples.

The growth of trees can be influenced by local features of the place of growth (relief, watering). Because of this, the thickness of annual rings of a particular tree specimen may not correspond to the scale constructed for this region. But if there is a coincidence, the probability of error is extremely small.

Dendrochronological series are multicentennial series of observations characterizing the radial growth of woody vegetation (trees) and its connection with climatic conditions.

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To become an oologist, you must first of all study to become an ornithologist. The profession will be in demand in museums and zoos.

What do you know about oology?

The science of birds? The first thing that comes to mind is ornithology, but it turns out it’s not the only one. There is a section of zoology that studies animal eggs (mostly birds, of course). In addition, this science also involves collecting eggs and describing them in detail. It is called “oology.”

Since the 1800s, oology has been actively developed, mostly as a hobby. People collected collections of eggs from various birds – ootheca – and described the size, shape, and coloring of each egg. Unlike embryology, oology studies only the shell, not the contents of the eggs. The knowledge gained by oologists helps to provide insight into the population of a species, its evolution, and the environment and the area as a whole. Collecting eggs that does not involve scientific investigation is called “longophilia.”

This science is not as popular now as it was in the nineteenth century, because all specimens of eggs have already been described and studied in detail. The largest collection is at the Western Vertebrate Zoology Foundation in California, with over 800,000 specimens.

However, in some countries it is not allowed to collect the eggs of wild birds, it is considered poaching. For example, in the UK, the illegal harvesting and storage of eggs can lead to imprisonment for up to six months. Similar laws are in effect in some American states.

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To create the new heavy-duty adhesive, the researchers have used polystyrene-b-poly (ethylene-co-butylene)-b-polystyrene (SEBS), a rubber polymer, and endowed it with new properties by changing its chemical structure using a process known as dynamic crosslinking. It allows normally incompatible materials to be joined together. With its help scientists added silica nanoparticles and complex esters of boronic acidAmerican researchers have created the world’s strongest glue from recycled plastic, resulting in a new composite material, which they called SiNP. Boron esters are the key to reusing adhesives because they allow for the repeated formation and breakage of “cross-linked” bonds. The work was published in the journal Science Advances.

“A fundamental discovery was that boronic acid esters on SEBS can rearrange bonds with hydroxyl groups – oxygen and hydrogen – on SiNPs to adapt properties to perform complex tasks. We also found the formation of similar reversible bonds of the boronic acid ester to various surfaces that have hydroxyl groups,” noted Anisur Rahman, MD, lead author of the study.

The glue is also recyclable and retains its properties even at 204 degrees Celsius. Scientists believe that their development will be useful in the aerospace, automotive and construction industries. They are working to improve the technology and expect to commercialize it soon.

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Taken together, this new material holds great promise for applications ranging from creating robots with more power without using additional energy to new helmets and protective materials that can dissipate energy much faster, the authors of the paper claim.

Alfred Crosby, professor of polymer science and engineering at UMass Amherst and senior author of the paper says, “Imagine a super-rubber. When you stretch it to a certain limit, you activate the extra energy stored in the material. When you let go of that rubber band, it travels a whole mile.” Their material will be made from a new metamaterial – a substance designed to have properties not found in naturally occurring materials – that combines an elastic, rubber-like substance with tiny magnets embedded in it. This new “elastomagnetic” material takes advantage of the laws of physics to greatly increase the amount of energy the material can release or absorb.

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