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Newsday: Practical AI, Data Governance, and Tech modernization with Vik Patel and Sarah Richardson

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Vik Patel, COO at TIDO joins Sarah on This Week Health Newsday. Vik shares his journey from hospital IT to founding TIDO, discussing the nuanced challenges of integrating AI and the role of strong governance frameworks in avoiding unintended biases. Together, we tackle questions of strategic prioritization, from the intricacies of data migration and legacy archiving to the pressing need for reliable, responsive tech solutions in high-stakes clinical environments. Through the lens of real-world applications, the episode raises important considerations about balancing innovation with practicality in healthcare IT.

Key Points:

  • 04:09 The Importance of AI Governance in Healthcare
  • 07:27 Challenges and Solutions in Healthcare IT
  • 20:00 Practical AI Applications and Integration
  • 30:49 Conclusion and Final Thoughts

News articles:

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Driving Operational Excellence in Health Systems: Strategic Alignment of AI, Data, and Resources

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This Week in Health Tech Podcast with guest James Wellman

In today’s fast-evolving healthcare landscape, operational excellence is no longer a luxury—it’s a necessity. Health systems are challenged to balance the clinical demands of patient care with the operational needs of efficiency, cost-effectiveness, and data management. In the latest  episode of This Week in Health Tech, Vik Patel, COO, Tido Inc. welcomes James Wellman, VP-CIO at Nathan Littauer Hospital and Nursing Home. They discuss topic of achieving  operational excellence using the right combination of data, integration, AI, and resources. 

Healthcare organizations can drive operational efficiency through strategic use of data and AI tools by:

  1. Establishing a strong data governance framework with clear ownership, standardized processes, and engaging subject matter experts across the organization.
  2. Transitioning to a robust, cloud-based data architecture that ensures data portability, interoperability, and security.
  3. Carefully evaluating and adopting AI/RPA solutions, starting with automating repetitive processes and augmenting staffing needs, while remaining cautious about potential biases and limitations of AI models.
  4. Aligning technology strategy with overall organizational goals, using data-driven decision making for investments and service offerings.
  5. Prioritizing education and communication across the organization to get buy-in and ensure effective adoption of new data and technology initiatives.

The Central Role of Data in Modern Healthcare

Healthcare organizations generate enormous amounts of data daily, from patient records to operational performance metrics. But without the ability to effectively manage and interpret this data, much of its potential remains untapped. The podcast episode emphasized how data is the foundation of innovation in healthcare, enabling organizations to make informed decisions, predict patient outcomes, and optimize workflows.

One of the critical points raised is the challenge of fragmented data. Often, healthcare systems struggle with data spread across multiple platforms and departments, making it difficult to get a complete view of their operations or patients. This is where Tido’s integration solutions and AI-driven MIDR (Managed Integration Detection and Response) tools come into play, as they are specifically designed to break down data silos and streamline information flow across systems.

3 Steps to Better Prepare for the Retirement of Your Integration Engineer

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Healthcare Mergers and Acquisition

Our extensive experience managing integrations for various health systems has shown that it is quite common for organizations to depend heavily on one or two key engineers. When these engineers retire, it can pose significant challenges. As an IT director or CIO, it is crucial to prepare for this eventuality to ensure a smooth transition and minimize associated risks. Here are three steps to help you navigate this process effectively:

1. Planning for a Seamless Transition

a. Develop a Transition Plan:

  • Overlap Period: Plan for an overlap period where the retiring engineer works alongside new team members for 10-12 months. This period allows enough time for knowledge transfer and for new team members to encounter various interface issues. It also helps them learn organizational processes and build relationships with IT staff and other departments.
  • Engage an Integration Partner: Partner with a firm like Tido Inc., which provides integration solutions and has experienced integration engineers. Our engineers are familiar with every major EHR and integration engine, and they understand the importance of developing working relationships with IT and service departments like radiology and lab.

b. Assessment and Future State:

  • Comprehensive Assessment: Conduct a thorough assessment of the current integration environment. This allows the new team to learn the setup and interfaces and produces detailed documentation as a byproduct. This assessment should also include discussions with stakeholders to outline a future state and roadmap.
  • Enhance for Future: Tido’s integration assessments not only document the current state but also create a future vision that aligns with strategic initiatives and provides a roadmap for implementation.

2. Knowledge Transfer

a. Documentation and Guides:

  • Enhanced Documentation: During the transition period, ensure the current engineer works with the new team to update all system documentation, integration processes, and project details.
  • Create How-To Guides: Develop step-by-step guides for critical tasks and recurring issues. Tido’s team has templates to assist in creating comprehensive guides and manuals. We also use tools to make documentation easily searchable by any team member.

b. Training and Mentoring:

  • Knowledge Transfer Sessions: Organize training sessions where the retiring engineer spends dedicated time with the new team to transfer knowledge about different interfaces and special nuances.
  • Mentoring: Recognize that the retiring engineer has extensive knowledge of interfaces, organizational processes, and application workflows. Tido Inc. allows the retiring engineer to mentor and work closely with our team, who have been through similar transitions before.

3. Communication Plan

a. Internal Communication:

  • Inform Team Members: Clearly communicate the retirement plan and transition timeline to all relevant team members and stakeholders. This includes the IT team and other department managers and directors. Specially include communication about how to reach support for integration issues if this process will change. Tido’s team can share examples of previous communication plans and help draft these communications if needed.
  • Provide Updates: Keep the team informed about the progress of the transition and any changes to processes or responsibilities, especially support processes.

b. External Communication:

  • Notify Partners and Clients: If the retiring engineer has direct contact with external partners or clients, inform them of the change and introduce the new team.

Benefits of Partnering with Tido Inc.

  • Expertise: Tido’s team has over 15 years of experience providing integration management and support to health systems across North America.
  • Continuity: We ensure smooth, uninterrupted operations during transitions.
  • Scalability: Tido Inc. can scale services according to your needs, providing additional resources if required.
  • Cost-Effective: Our solutions are cost-effective, saving you the expense of hiring and training new personnel. You gain access to an experienced integration team rather than relying on a single individual.

By following these three steps and leveraging the expertise of Tido Inc., you can ensure a seamless transition, effective knowledge transfer, and clear communication, maintaining the integrity and efficiency of your integration systems. Need more information? Please contact us.

TownHall: AI Adoption, Risks, Operational Automation and Predictions

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Today on TownHall, Brett Oliver, Family Physician and Chief Medical Information Officer at Baptist Health talks with Vik Patel, Chief Operating Officer at Tido. As we navigate through the complexities and potentials of AI adoption within health systems, Vik challenges listeners to think critically about the current landscape.

How can AI not only enhance clinical applications but also streamline operational workflows in ways previously unimagined? And with the rapid evolution of AI technologies, what are the risks and considerations health systems must weigh to protect patient data and ensure the unbiased, accurate performance of AI models? This episode doesn’t just scratch the surface; it delves deep into the practicalities and futuristic possibilities of AI in improving patient care, operational efficiency, and the overall healthcare landscape.

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How to leverage your integration engine for seamless EHR Migration and reduce upgrade costs?

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Health System Integration

In the complex landscape of Electronic Health Record (EHR) migration, having a robust integration engine managed by an experienced integration team can be a game-changer for health systems. Integration engines like Cloverleaf, CorePoint, InterSystems, Mirth, Rhapsody, Jaguar, Qvera, and others play a pivotal role in streamlining data flows and connectivity. Here’s why taking advantage of these engines can significantly ease the challenges associated with transitioning to a new EHR and also reduce costs associated with other vendor contract updates.

1. Streamlined Connectivity Timelines:

  • Having an integration engine already connected to downstream systems means a head start in the migration process. For instance, if your current EHR is sending Admission, Discharge, Transfer (ADT) messages and Orders to a Cardiology system, the workflow with the future EHR will likely perform the similar functions. This continuity significantly reduces the time spent on establishing new connections, as the connections between integration engine and the downstream system are already in place.

2. Cost-Efficiency and Resource Optimization:

  • Integrating a new EHR is a resource-intensive process. Utilizing an existing integration engine not only saves time but also contributes to cost-efficiency. The ability to repurpose established connections minimizes the need for additional infrastructure setup, ultimately optimizing resources. Depending on the workflows, timelines, etc. it may not be necessary for the downstream system to create any new interfaces, since the engine could be leveraged to send test messages from the new EHR test environment and also the existing EHR test environment. This could help significantly reduce contract update costs with the downstream system vendors.

3. Consistency in Data Routing:

  • When migrating EHRs, one of the challenges is rewriting existing interfaces. However, with an integration engine, you have the advantage of maintaining consistency in data routing. For example, even though the new EHR might require testing interfaces, your integration team can leverage the existing connections in the engine. This means that ADTs and Orders from the new EHR’s test environment can be seamlessly routed within the engine, eliminating the need for establishing new VPN tunnels or ports.

4. Optimizing Interface Reuse:

  • Many EHR vendors may create new interfaces to accommodate the testing phase of the new system. However, having an integration engine allows for intelligent interface reuse. The engine allows your integration team to review existing interface modifications, mapping etc. and provides a head start for interfacing with the downstream system. Existing interfaces could be cloned and modified as needed based on the messages from the new EHR.

5. Flexibility in Testing Scenarios:

  • The versatility of integration engines enables your team to adapt to various testing scenarios. Whether the new EHR necessitates specific configurations or adjustments, the integration engine provides the flexibility to handle diverse requirements without compromising on connectivity. Combining test automation with the engine can help clinical and IT teams test all possible scenarios without needing to take up valuable time from clinical resources.

Conclusion:

In the intricate landscape of EHR migration, the role of integration engines cannot be overstated. By leveraging the connectivity already established through these engines, health systems can navigate the migration process with greater efficiency, reduced timelines, and minimized disruptions. As technology evolves, integration engines stand as invaluable assets, ensuring seamless transitions and continuity in healthcare data management.

For over 15 years Tido Inc. has been partnering with health systems for EHR migrations and integration management. If you have any questions or need assistance with your health system’s ehr conversion, contact us today. We are here to support you in navigating the challenges of EMR migration and ensuring a smooth transition for your organization.

Navigating Ambulatory EMR Data Conversion: A Step-by-Step Guide

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Physician EMR

Introduction:

Transitioning to a new Ambulatory Electronic Medical Records (EMR) system can be a complex yet essential process for healthcare providers looking to enhance efficiency, streamline workflows, and improve patient care. Ambulatory EMR data conversion requires careful planning and execution to ensure a seamless transition without compromising patient care. In this blog post, we’ll guide you through the crucial steps of this conversion process.

Step 1: Comprehensive Planning and Assessment

Before diving into the conversion process, create a detailed plan that outlines the scope, objectives, and timelines. Engage key stakeholders, including clinicians, IT personnel, and administrators, to gather insights and ensure a comprehensive understanding of the requirements. Identify the specific requirements of your healthcare organization, considering factors such as data volume, system compatibility, and workflow preferences. Identify potential challenges and develop contingency plans.

Step 2: Data Inventory

Take stock of your existing data. Identify the types of information stored in your current EMR system, including patient demographics, medical history, prescriptions, and any customized data fields. This inventory will inform the mapping and migration process in later steps.

Step 3: System / Vendor Selection

Choose a new ambulatory EMR system that aligns with your organization’s needs and goals. Consider factors such as user interface, scalability, interoperability, and vendor support. Ensure that the selected system complies with industry standards and regulations.

Step 4: Data Mapping

Create a detailed mapping of data elements from your existing EMR system to the new one. This involves defining how data will be transferred and ensuring that equivalent data fields exist in the new system. Pay attention to any variations in coding systems, data formats, or terminology.

Step 5: Data Extraction

Use specialized tools to extract data from your current EMR system. Ensure that the extraction process maintains data integrity and security. This step involves exporting patient records, clinical notes, lab results, and any other relevant information in a structured format.

Step 6: Data Transformation

Prepare the extracted data for migration by transforming it into a format compatible with the new EMR system. Address any inconsistencies, duplicate records, or discrepancies in data structure. This transformation ensures a smooth and accurate transition of information.

Step 7: Data Migration

Execute the actual data migration process. Depending on the size of your organization and the complexity of your data, this may be done in phases or as a complete migration. Monitor the process closely to identify and address any issues promptly.

Step 8: Testing

Conduct thorough testing of the new EMR system to ensure that data has been accurately and completely transferred. Test functionality, data retrieval, and interoperability with other systems. Engage end-users in the testing process to gather feedback and address any concerns.

Step 9: Training

Provide comprehensive training to staff members on the new ambulatory EMR system. Ensure that users are familiar with the system’s features, functionalities, and best practices. This step is crucial for a successful transition and optimal utilization of the new system.

Step 10: Go-Live and Post-Implementation Support

Implement the new ambulatory EMR system in a controlled manner. Monitor its performance closely during the initial days and weeks. Offer ongoing support to users, addressing any challenges that may arise. Gather feedback and make necessary adjustments to optimize system usage.

Conclusion:

Ambulatory EMR data conversion is a multifaceted process that requires careful planning, meticulous execution, and ongoing support. By following these steps, healthcare organizations can streamline the transition to a new EMR system, ultimately enhancing patient care and operational efficiency.

For over 15 years Tido Inc. has been partnering with health systems and physician practices for data conversions. If you have any questions or need assistance with your health system’s data conversion, contact us today. We are here to support you in navigating the challenges of EMR migration and ensuring a smooth transition for your organization.

 

Get rid of avoidable re-admissions!

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Hospital Readmissions Monitoring

Did you see this headline last month in Healthcare IT News? RPM brings 30-day mortality rate to almost zero for heart bypass procedure. Remote patient monitoring (RPM) offers to extend the reach of care and allow clinical teams to respond faster to changing patient conditions and reduce re-admissions for chronic conditions and post-operative care. While the article references a single site for the results of this RPM program, there have been numerous other studies and reports citing the promising results of these types of programs. Perhaps not a total elimination, but significant reductions are achievable.

There are a variety of companies out there trying to capitalize on utilizing various forms of RPM to capture early changes in the physiologic status of patients. Apple Watch and afib detection/monitoring is probably the most widely known out there of late. But remote monitoring or in-home monitoring devices have been around for decades, with a variety of connections, from dial-up to wifi to cellular. In addition to companies offering remote monitoring devices, there are a variety of companies offering to do the remote monitoring, hiring clinical teams to monitor patient connections. Often these companies can offer the benefit of scale to manage a smaller group of patients that would otherwise be an overwhelming administrative burden.

So what’s the catch? We know there’s always a catch! Remote monitoring sounds like a simple thing to do, and by and large the technology and FDA approvals already exist to make it happen. But as with anything data-related in healthcare, the data flows are a big pain point.

More connected devices from one ecosystem to another. There’s a lot of those in healthcare. Adding another tech burden for clinical teams to trouble shoot and figure out what happened can quickly render an RPM program ineffective. Even the most savvy clinical team and 100% compliant patients can be undone by connections that aren’t talking.

Whether the decision is to outsource and RPM program or handle it in-house, connections need to be reliable to get the right data to the right person at the right time. Anything less can result in a patient heading to an ER or Urgent Care for something that could’ve, and should’ve, been handled in the comfort of their own home. Not only is this detrimental to the patient, but it can also have a negative impact on reimbursement.

Reliable feeds and early notification of problems can keep clinical teams operating smoothly, ensuring patients receive timely care and interventions. Not only does this keep your teams working for the health of your patients, but it also gives patients confidence that your systems are working just as effectively as your clinical teams keeping them healthy.

Automated applications and integration monitoring can help quickly identify and resolve issues to minimize any downtime impact. For over 10 years Tido Inc. has been partnering with health systems to help maximize their IT systems and quickly resolve issues as they arise, often before the end user even notices. Contact us today so we can talk about how we can help you keep your systems working for you clinical teams and patients.

Rise of the [Diagnostic] AI Machines!

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Radiologist reviewing diagnostic imaging

Are we ready to welcome our AI overlords into healthcare yet? Will we welcome a fully autonomous Dr. Crusher? We’re not likely ready to completely abandon our human healers, but there have been a variety of algorithms and machine learning applications that have been creeping their way into our clinical specialties for many years now. The first AI algorithm was approved by the FDA in 1995, in the beginning of 2023 there are 520. The specialty with the largest number? Radiology! Check out this article from HealthExec, it provides some more detail on the approval and advantages of AI in imaging.

Radiology, and similar specialties that utilize imaging, have long embraced computer systems to improve quality, productivity, and sharing. The complexity behind the scenes of these systems can be quite surprising. Once an image is captured it may still go through multiple systems just to be viewed, PAC Systems, VNA, Dicom viewers, the route is anything but direct. If we want to add another step in the process to have the image analyzed, we are faced with yet another connection.

In a previous blog post we pointed out the challenges that staff face when one of these systems aren’t communicating, these certainly impact our physicians as well. As we add more diagnostic solutions to aid our physicians in treating patients, we want to ensure that their time is actually spent doing what they are trained for. The average radiologist makes roughly $300,000 per year, if we assume that radiologist works 40 hours per week, that’s about $144 per hour.

What happens when the machines stop talking? Likely the radiologist calls the help desk… 5 minutes on hold ($12), they will take 3 minutes to explain the problem to the help desk person ($7.20), who will then transfer them to a specialist where they take another 5 minutes talking over the problem ($12). Helpdesk will then forward the issue to multiple analysts and integration team. At-least 2 different analysts getting pulled into diagnosing the issue. Typically, integration and system analysts make 90k-130k per year or on average $50 per hour. These 2 analysts will work on this issue for about 30min ($100) to diagnose the issue. $131.20 may not seem like a significant amount, but now that radiologist may not be reviewing images, may not be discussing treatments with patients, they may not be doing what they’ve been trained to do. If the radiologist is only 50% as productive without this solution, every hour of outage costs $132…  That’s just for one Radiologist. And typically system issues affect all users. So once you multiply the outage costs for all radiologists and other team members it really adds up fast. There can also be significant downstream impacts to other services waiting on imaging as well that become harder to calculate.

Moving beyond the frustration of the healthcare teams, there can be a detrimental impact to patient satisfaction as well. As results are delayed and the team gets backed up, every hour of delay adds to the patient’s anxiety and fear. Anxiety and fear are not feelings we want our patients to experience, we want them to have confidence in our teams and systems.

Automated applications and integration monitoring can help quickly resolve these problems. With early notifications to the right team in a timely manner, problems can be quickly resolved to minimize downtime impacts. For over 10 years Tido Inc. has been partnering with health systems to help maximize their IT systems and quickly resolve issues as they arise, often before the end user even notices. Contact us today and so we can talk about how we can help you keep your systems working for your clinical teams.

HIMSS 2023 – What did we take away?

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Tido Inc. at HIMSS Conference

From cars to healthcare, Vik and John chat about a variety of topics in the latest This Week in Health Tech podcast, but we focused on Vik’s experience from HIMSS. Check out the episode, we chatted a bit about AI generated automated responses to patient messages to physicians.

After our conversation an interesting study was released in JAMA about ChatGPT outperforming physicians on empathy responding to messages. There’s a lot to unpack there! There is some controversy surrounding the applicability of the study and how it was conducted, but it does raise interesting questions and possibilities for the future. It brings us back to the question about where to use technology in healthcare? How do we do this without unintended consequences or further alienating patients from healthcare? If patient’s know they are interacting with a computer, how does this impact engagement and adherence? What is the applicability in the healthcare environment?

Part of the promise of AI is to do what people do, only do it faster. Synthesize information into a coherent string of words delivered in a certain style. When we consider a response to a patient inquiry, LLMs have the ability to aggregate styles and deliver an empathetic response, they also have the luxury of time, being able to do it quickly. It can take about 15-30 seconds for these AI models to generate a response, it takes a clinician longer to craft a meaningful response.

If we allow AI to write a response, then we still need the human to read it over and make sure it is relevant, applicable, and appropriate. This assurance takes time from the clinician to read over the response, understand the patient question, the context, the patient background, and for some questions to dig a bit deeper and find out why the patient is asking a question.

Before we seek out another solution with many unknowns, we should start to look at what we have now and consider whether or now we are optimizing the current systems. Will a new AI solution really save time, or will it increase the burden with more back and forth? There are so many interconnected solutions out there, are we actually utilizing them, or are we working around them?

Making incremental, seemingly insignificant, improvements can have dramatic improvements to clinical efficiency. Reliable interconnected systems, making sure the information is flowing back and forth, and ensuring that any AI solutions that we will come to rely on actually have access to all the information, is just as essential now as it will be in the future. Disconnected systems can render AI just as inefficient as they render our clinical teams now.

Want to make sure your systems are talking to each other? Tido’s automated applications and integration monitoring can avoid many of the problems and inefficiencies that clinical teams, and AI, will experience when networks aren’t communicating and the information isn’t flowing smoothly. For over 10 years we’ve been partnering with health systems to ensure their getting the most from their current investments. Contact us today and see how we can work with you to optimize your technology investments.

Are your charges still floating in the clouds?

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Health System lost charges

How long did it take for those charges to drop? Was it halfway through the cycle? When did you find out they didn’t? Billing is seldom a simple process, with a variety of different systems required to communicate in order to get reports from the procedure to the billing department. Missing reports can prevent the charges from dropping, wreaking havoc on your revenue cycle.

Reconciliation can catch this, but how often is this done? Once a month? Once a week? 7 days and up to 4 weeks is way too long to find a problem. When you consider how long payment cycles can drag on, delaying them further can be problematic.

I’ve written often on the problems network breaks can cause on clinical teams. Broken networks can cause frustration for every department, not just the clinical teams. Billing is connected to almost every system in the hospital or practice, it’s even more vulnerable to these problems, relying on all these systems working to get an accurate picture of the supplies and time. If the report from Radiology didn’t cross over from the PACS to the VNA to the EHR, will it ever show as completed? If it shows as completed, is the report actually there and available to the billing department?

There are dozens of systems with dozens of different tech stacks, from reporting to supplies to pharmacy, getting a hand on each one to make sure they’re talking can be difficult. With most identification of issues coming from the end user, you often won’t know there’s a problem until its too late. Automated applications and integration monitoring can avoid many of these delays. Notifying the right teams early so problems can be addressed quickly, often before the end users even notice, can keep these teams working and the revenue cycling.

Tido Inc. can help you avoid these costly delays. How confident are we in this? Quite, confident. We have over 10 years of experience partnering with health systems and hospitals on their technology needs, from application monitoring to a variety of digital packages to support their operations.

Need more convincing? Contact us! We’re happy to talk about our processes and some of the results we’ve achieved. In fact, we’re willing to give you 3 months free to try it out, but there’s a catch… Only if you mention the song hinted at in this blog! Check out the next This Week in Health Tech podcast with Vik Patel and I’ll reveal the song!

We know convincing our colleagues in the finance office of the value of this service can be challenging just on the say-so of the vendor, so we’ll help you show the results with a free trial before you have to go and ask for a bigger slice of that pie.