Health Technology, Digital Healthcare
Article | August 16, 2023
Workers in the healthcare industry are among the most burned out demographics following the COVID-19 pandemic. In fact, a report by Medscape on physician burnout and depression in 2022 calculated a five-percentage point increase in burnout overall, from 42% in 2020 to 47% in 2021. Critical care physician burnout was also found to increase from 44% to 51% last year, placing them at the top of Maryville University’s list of physician specialties with the highest cases of burnout. This is closely followed by rheumatology physician burnout, which was 50% in 2021. At the bottom of the list, emergency medicine physician burnout still came in close at a rate of 44%.
Burnout can result in, among other things, exhaustion and a loss of concentration, which can be dangerous in healthcare. With that, advancements in technology have been made to help mitigate stress and reduce the chances of burnout in healthcare.
Maximum Tasks, Minimum Efficiency
Reports show that many technological advancements in the healthcare industry actually aren’t appropriate for managing physician workloads. This is due to the range of tasks physicians need to perform, from creating treatment plans to managing EHRs. Our previous discussion on EHR-Generated Messages highlighted how the misapplication of this algorithm had actually led to these inboxes getting clogged. This has primary care physicians spending more than half their workday interacting with EHRs that only remind physicians to order certain tests, instead of dealing with critical messages from patients or colleagues. This has been counterproductive in terms of efficiency, leading to more burnout symptoms and the tendency to reduce clinical work hours. It is therefore important that technology integrations consistently consider the broader picture of the tasks of physicians.
Tech Developments for Reducing Burnout
Shifts in the industry have thus begun to focus on the quality of efficiency and physician assistance, rather than the quantity of technology available. Here are some notable examples of technology that has become finely integrated within the healthcare industry.
Ambient Technology in Clinical Documentation
Ambient computing streamlines the clinical documentation process by using artificial intelligence to respond to human behavior and needs. This provides front-end speech and computer-assisted documentation, reducing the time needed for physicians to work on admin tasks, and thereby minimizing burnout. Smart hospitals have started leveraging this through sensor-based solutions, and experts from Michigan University believe usage must be made easier and simpler to use for the provider if the healthcare industry is to further leverage ambient computing for CDI. As of 2021, adoption has only started to take off, especially in the revenue cycle.
Computer Modeling in Vaccine Development
The traditional process of designing novel vaccines usually lasts 10 to 15 years and can cost between $200 million and $500 million. However, a feature by News Medical highlights the recent development of COVID-19 vaccines, which uncovered the capabilities of computational modeling systems. This showed an ability to predict which parts of a pathogen may be recognized by the immune system’s B cells and T cells. This allows rapid identification of vaccine targets from a genetic sequence, which reduces the years required for preclinical research. Physicians are thus able to respond faster to vaccine developments, and reduce the overload of health systems during any future pandemics or epidemics in the long term.
Patient Placement Technology
The shortage of physicians is a common setback in the industry, one that staff at the Rice County District Hospital in Lyons, Kansas mitigated using patient placement technology. Patient placement technology coordinated care for patients inside the 25-bed, level 4 hospital, as well as those needing to be transferred to another facility. By integrating local EMS and other transport services with health systems, manual telephone calls were no longer necessary. Hence, physicians were able to quickly and effectively get patients the care they needed while managing time-critical diagnoses. This maximizes the limited resources available without stretching out the workforce. Physicians are able to focus solely on their patients, knowing that the time-consuming logistics are being efficiently handled by technology. The industry needs to continue to look into the practices of reducing burnout among physicians, more so as we continue to recover from the effects of the COVID-19 pandemic. By emphasizing physician wellness and efficient technology, we can continue to assure the health and productivity of healthcare workers into the future.
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Digital Healthcare
Article | November 29, 2023
Unlock EHR interoperability solutions with this article. Discover how healthcare overcomes EHR interoperability challenges to facilitate seamless information sharing for better clinical decisions.
1. Exploring Hurdles in EHR Interoperability
2. Addressing EHR Interoperability Challenges: Mapping Effective Paths
2.1 Upgrading from Outdated Legacy Systems
2.2 Managing Inconsistent Information Across Multiple Sources
2.3 Overcoming Organizational Resistance to Sharing Data
2.4 Balancing Security and Consent
2.5 Harmonizing Data Standards Across Diverse Software Systems
2.6 Optimizing Training Resources for EHR Interoperability
2.7 Strategizing Costs for Specialist-driven Interoperability Management
2.8 Navigating Budget Constraints in EHR Interoperability
2.9 Unifying Patient Identification Standards Across HIEs
2.10 Advancing Allergy Management to Enhance Patient Care
3. Embracing Interoperability for a Connected Healthcare Future
1.Exploring Hurdles in EHR Interoperability
Despite significant efforts and investments in health information systems and technology, coupled with many years of widespread availability, the full benefits of electronic health records (EHRs) still need to be realized. The reality is that most physicians continue to rely on faxing and mailing patient records, just as they did a decade ago. Numerous government-certified EHR products are being used, each utilizing distinct clinical terminologies, technical specifications, and functional capabilities. These differences make it challenging to establish a unified standard interoperability format for data sharing. Interestingly, even EHR systems built on the same platform might not be interoperable, as they are frequently highly customized to an organization’s specific workflow and preferences. Given these circumstances, the article examines ten challenges and their corresponding EHR interoperability solutions to enhance patient care.
2.Addressing EHR Interoperability Challenges: Mapping Effective Paths
The primary goal of healthcare interoperability is to enable seamless sharing of health-related information between healthcare providers and patients, aiding in clinical decision-making. Here are several challenges to accomplishing this aim, along with their corresponding interoperability solutions:
2. 1 Upgrading from Outdated Legacy Systems
One of the significant challenges in achieving EHR interoperability is the need to transition from outdated legacy systems. Many healthcare facilities still rely on older, proprietary EHR systems that need more compatibility and standards to communicate seamlessly with modern, interconnected healthcare networks. These legacy systems often need more data exchange capabilities, leading to inefficiencies, data inconsistencies, and barriers to collaborative patient care. The intricate process of upgrading or replacing these systems while ensuring data integrity and continuity of care poses a considerable obstacle to achieving comprehensive EHR interoperability.
Healthcare institutions need to implement a strategic and phased approach to address this challenge. This involves assessing the existing EHR, identifying interoperability gaps, and selecting modern healthcare interoperability solutions that adhere to industry standards, such as Fast Healthcare Interoperability Resources (HL7 FHIR) and open APIs. A well-defined migration plan should be developed, including data migration, new system integration, and staff training. Collaboration with EHR vendors, IT experts, and clinical stakeholders is crucial to ensuring a smooth transition.
2.2 Managing Inconsistent Information Across Multiple Sources
As patients move through different healthcare settings and encounter various medical professionals, their health information becomes distributed across multiple sources, leading to discrepancies, duplications, and variations in data. This inconsistency can compromise patient safety, treatment accuracy, and healthcare quality. Furthermore, different institutions' varying data formats, coding systems, and documentation practices exacerbate the challenge of creating a unified and accurate patient record.
A potential solution to this challenge involves developing and adopting standardized data exchange protocols. By implementing common data standards and practices, healthcare providers can ensure that patient information is accurately represented and uniformly understood across different systems. In addition, robust data validation processes and reconciliation algorithms can help identify and rectify inconsistencies during data integration. Moreover, creating a centralized patient identity management system that links various patient records to a single, accurate identity can significantly mitigate the issue of duplicated or mismatched information.
2.3 Overcoming Organizational Resistance to Sharing Data
This EHR interoperability challenge pertains to the reluctance of healthcare institutions, clinics, and providers to readily exchange patient information and medical records due to concerns over data privacy, competitive advantage, and operational complexities. This resistance often leads to fragmented patient care, hindered medical research, and compromised clinical decision-making.
Addressing this challenge necessitates the establishment of clear data-sharing protocols, robust privacy safeguards, and incentivized collaboration. By fostering a culture of trust, emphasizing the collective benefits of data exchange, and implementing interoperability standards, the healthcare ecosystem can encourage reluctant organizations to actively share essential patient data, ultimately leading to improved patient outcomes and more efficient healthcare delivery.
2.4 Balancing Security and Consent
This challenge in EHR interoperability revolves around the delicate equilibrium between ensuring patient data security and privacy while enabling the seamless sharing of EHRs across different healthcare systems. Striking the right balance involves addressing concerns about unauthorized access, data breaches, and patient consent preferences. While robust security measures are necessary to safeguard sensitive health information, overly stringent restrictions can hinder the efficient exchange of vital medical data, potentially impeding timely and informed patient care, medical research, and healthcare system efficiency.
Potential EHR interoperability solutions to this challenge include implementing a layered security and consent management approach. This involves combining strong encryption, authentication protocols, and access controls to ensure the integrity and confidentiality of EHRs. Moreover, the adoption of standardized and granular consent mechanisms empowers patients to regulate both access to their data and the purposes for which it can be accessed. An integrated framework that employs advanced technologies like blockchain for secure audit trails and data-sharing logs can enhance transparency and accountability. Furthermore, patient education and awareness campaigns can empower individuals to make informed data-sharing decisions, fostering a collaborative environment where security, consent, and interoperability coexist harmoniously.
2.5 Harmonizing Data Standards Across Diverse Software Systems
This challenge encompasses integrating and exchanging medical data across various software platforms and applications used within the healthcare industry. To tackle this challenge, a comprehensive solution includes the widespread adoption and adherence to standardized data formats, coding conventions, and communication protocols by developers, healthcare organizations, and EHR integration software.
To address this challenge, a comprehensive solution involves the establishment of standardized data formats, coding conventions, and communication protocols widely adopted and adhered to by EHR software developers and healthcare organizations. This could be achieved through industry collaboration, government regulations, and incentives for adopting interoperability standards. Additionally, implementing APIs that translate and map data between different formats can help bridge the gap between diverse software systems.
2.6 Optimizing Training Resources for EHR Interoperability
This hurdle involves preparing healthcare professionals, IT staff, and other stakeholders to effectively navigate and implement interoperable EHR systems. Ensuring that healthcare personnel possess the necessary skills and knowledge to seamlessly integrate, maintain, and utilize interconnected EHR systems amidst rapidly evolving technology and standards poses a significant hurdle. This challenge involves understanding the intricacies of interoperability protocols and grasping the broader context of data security, patient privacy, and efficient data exchange among diverse healthcare entities.
To address this challenge, developing comprehensive and up-to-date training programs that cover both technical aspects (interoperability standards, APIs, and data formats) and practical considerations (security protocols, data governance) is crucial. Collaborations with vendors, industry experts, and academia can ensure the training content remains aligned and updated with current EHR trends. Integrating EHR interoperability education into medical and IT curricula can also lay a foundation for future professionals. Continuous learning opportunities, including EHR analytics courses, certifications, and knowledge-sharing platforms, can further bolster the continual development of skills and knowledge exchange. This process cultivates a skilled workforce capable of fully leveraging EHR interoperability while upholding the integrity and privacy of patient data.
2.7 Strategizing Costs for Specialist-driven Interoperability Management
This challenge pertains to the complex and costly task of ensuring seamless data exchange among diverse EHR systems, mainly when managed by specialists with domain-specific knowledge. These specialists play a crucial role in tailoring EHR interoperability solutions to the unique needs of their medical domains. Still, the financial implications of such endeavors can be substantial, involving customization, integration, and maintenance expenses.
Finding an effective solution requires a multi-faceted approach involving standardized interoperability frameworks, modular system design, strategic resource allocation, and collaborative partnerships among EHR vendors, healthcare institutions, and specialists. By optimizing the balance between customization and standardization and leveraging technological advances like APIs and cloud computing, healthcare ecosystems can mitigate costs while achieving efficient and secure data exchange that benefits patients and healthcare providers.
2.8 Navigating Budget Constraints in EHR Interoperability
This issue relates to healthcare organizations' significant financial limitations when striving to establish seamless EHR data exchange across disparate systems. As healthcare entities aim to enhance patient care coordination and data accessibility, the cost of implementing and maintaining interoperable EHR systems becomes a substantial hurdle. This challenge necessitates a delicate balance between allocating resources for EHR integration, customization, and ongoing maintenance while ensuring that patient data remains secure and accessible to authorized stakeholders.
A possible avenue to deal with the budget constraints in EHR interoperability is the strategic adoption of open-source frameworks. By leveraging open-source solutions, healthcare organizations can reduce licensing fees and development costs associated with proprietary systems, allowing them to allocate resources more efficiently. Additionally, collaborating with industry consortia and governmental initiatives that promote standardized data exchange protocols can foster economies of scale, streamlining the implementation process. Moreover, investing in cloud-based technologies can offer scalable and cost-effective data storage and sharing infrastructure.
2.9 Unifying Patient Identification Standards Across HIEs
The crux of this issue involves the need for consistent patient identification methods across different healthcare systems and data-sharing networks. This inconsistency results in errors, data duplication, and compromised patient safety as information is exchanged between entities. Without a standardized patient identification system, accurate matching of patient records becomes a complex endeavor, hindering the seamless exchange of EHRs and undermining the potential benefits of interoperability.
To address this challenge, a comprehensive solution involves establishing and adopting a universally recognized patient identification standard that spans all participating HIEs. This standard could include using unique patient identifiers or a combination of demographic, biometric, and cryptographic identifiers to ensure accurate and secure patient matching. Additionally, implementing advanced data governance practices, strong privacy protections, and robust data validation algorithms would enhance the accuracy and security of patient identification. Collaboration between healthcare organizations, government agencies, and technology experts is crucial to developing and implementing this standardized approach, fostering a more interconnected and effective healthcare ecosystem while safeguarding patient privacy and data integrity.
2.10 Advancing Allergy Management to Enhance Patient Care
Healthcare providers need help seamlessly sharing allergy-related patient data across different EHR platforms, hindering comprehensive patient care. This lack of interoperability leads to fragmented information, potential medication errors, and compromised treatment decisions, ultimately impacting patient safety and outcomes.
One viable solution for addressing this challenge is to establish standardized data exchange protocols alongside a unified health information exchange framework. Implementing FHIR standards can enable the consistent and secure sharing of allergy information among EHR systems. Additionally, incentivizing healthcare organizations to adopt these interoperability EHR standards and invest in compatible technologies will promote a cohesive ecosystem where allergy data can be accurately and swiftly exchanged. Collaborative efforts among EHR vendors, healthcare providers, and regulatory bodies are essential to ensure the seamless flow of allergy-related information, resulting in enhanced patient care, reduced medical errors, and improved healthcare efficiency.
3.Embracing Interoperability for a Connected Healthcare Future
With the goal of a cohesive healthcare future in mind, the value of embracing interoperability is immeasurable. This article highlights the essential role of interoperability in overcoming the challenges posed by fragmented data and improving patient outcomes. As healthcare systems continue to develop, the smooth exchange of EHRs becomes crucial, fostering collaboration among diverse stakeholders and facilitating well-informed decision-making. By creating an environment in which EHRs can seamlessly communicate, healthcare providers have the potential to offer more comprehensive, patient-centered care, minimize duplication, and expedite both diagnoses and treatments. Although achieving an interoperable healthcare ecosystem may involve complexity, the benefits of efficiency, precision, and overall quality of care underscore its necessity as a transformative journey.
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Health Technology, Digital Healthcare
Article | September 7, 2023
Across the spectrum of healthcare delivery – payor, provider, vendor, consumer, there is a land rush underway to embrace consumer-centric care. With tools like value-based care, chronic disease management, retail services, analytics, and remote patient monitoring, healthcare organizations are pivoting towards capabilities that provide a deeper understanding of patient behaviors and address the whole patient and not just the condition.
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Health Technology
Article | August 12, 2022
Introduction
Over the past couple of years, there has been a substantial rise in the burden of chronic conditions and treatment costs, along with the growing elderly population, which is transforming the healthcare sector at a rapid pace. As per a study, healthcare spending across the globe is anticipated to reach an unprecedented value to total US$ 18.3 trillion by 2030. In response to these trends, volume-based payment models are being replaced by outcome- or value-based models.
Predictive analytics helps health organizations to get in line with these new models and improve patient care and outcomes. From predicting critical conditions such as heart failure and septic shock to preventing readmissions, the recent advancements in big data analytics are boosting the adoption of new predictive analytics solutions that aid clinicians improve outcomes and cut costs.
Predictive analytics in healthcare is most helpful with clinical care, administrative tasks, and managing operations. More importantly, the technology is already making a difference in a wide range of healthcare settings, from small private doctor's offices and large academic hospitals to healthcare insurance companies.
How is Growing Healthcare Data Favoring the Penetration of Predictive Analytics?
The growing inclination toward digitalization in the healthcare industry has led to the creation of huge new data sets. These include radiology images, electronic medical record (EMR) systems, lab results, and health claims data. The amount of data is expected to reach new avenues with increasing genomics and cytogenesis research data in the near future.
New data is being generated and collected by the novel medical devices at the edge, such as monitors and patient wearables. In addition, outside the healthcare setting, patients are generating quasi-health data through the use of health monitoring applications, fitness trackers, and personal wearable devices.
By using data from these sources, health care providers can find new ways to use predictive modeling for health risks, predictive analytics for medical diagnosis, and prescriptive analytics for personalized medicine.
Predictive analytics has become a crucial component of any strategy for health analytics. Today, it's an essential tool for measuring, combining, and making sense of biometric, psychosocial, and behavioral data that wasn't available or was very hard to get a hold of until recently. Here are some of the applications of predictive analytics for healthcare
Identifying Patients at Risk
Clinical Predictions
Disease Progression and Comorbidities
Predicting Length of Stay
Speeding Treatment of Critical Conditions
Reducing Readmissions
The Future Story
With the growing prominence of innovative technologies across the healthcare industry, a number of health IT providers are focusing on developing their own analytics software and engines to assist healthcare spaces deliver optimal patient care.
For instance, in 2020, Eversana, a U.S.-based provider of innovative solutions to the life sciences industry, announced the introduction of its ACTICS predictive analytics solution, which enables clinical spaces to combine multiple data sources into a single comprehensive system.
Also, some U.S. companies are partnering with healthcare institutions to develop proprietary algorithms designed to enhance organizational performance, improve clinical care, and increase operational efficiency. Such developments are projected to increase the popularity of predictive analytics solutions in the healthcare sector in the coming years.
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