“It\u2019s great to get data, it can be painful to enter data. EHRs benefit all stakeholders tremendously because the information you need is in that one computer in front of you, and a lot of it is structured. The biggest challenge is getting that information in there.”<\/p>\n<\/blockquote>\n\n\n\n
Q1. How is your long term role Emergency Physician at Brigham and Women’s Hospital helping you with your job as Chief Medical Officer and Director of Clinical Innovation at InterSystems? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: It is tremendously helpful. I get to be in the role of the clinician, and I experience so many of the trends, the stresses, the problems and gaps that our customers experience \u2013 not only clinical, but also administrative and operational issues. Having this continuous exposure to the ups and downs of the healthcare day illuminates areas where our EHR could help to improve workflow and quality. On every single shift, I see something new that could have an IT solution. <\/p>\n\n\n\n Healthcare worldwide is going through a very stressful time: burnout is increasing among clinicians, patients are having a harder time getting access to care, communication is spotty. At InterSystems we can do something about that! And the AI capabilities that InterSystems IntelliCare<\/a> brings give us even more capability to address the things that I see in my work as an emergency doc.<\/p>\n\n\n\n Q2. Let’s talk about electronic health records (EHR) and healthcare information systems. What are the main current challenges in using them for a variety of stakeholders, such as clinicians, administrators, and patients? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: Simple \u2013 it\u2019s great to get data, it can be painful to enter data. EHRs benefit all stakeholders tremendously because the information you need is in that one computer in front of you, and a lot of it is structured. The biggest challenge is getting that information in there. Especially because of regulation and payment requirements in the US and other countries, you have to enter data in different fields, different screens, different formats, often in an unnatural way that doesn\u2019t match the flow of thought that evolves in a typical clinical encounter. There\u2019s way too much clerical busy work that could be automated \u2013 and that work leads to stress, take-home work that eats into family time, and burnout.<\/p>\n\n\n\n There are challenges in accessing data, too, and it\u2019s about organization. If you want to know something medically important like \u201cwhat is this patient\u2019s cardiac risk status?\u201d, you have to go to this page for labs, that page for medications, another page for imaging and procedure results, somewhere else for unstructured insights from previous notes. As a physician, my life is a series of healthcare scenarios and \u201cwhat do I do next\u201d questions \u2013 treat pneumonia, address cardiac risk, find an available bed, balance resources, track an epidemic; for each of these, I want to have all the information I need in front of me, in one view, nicely organized. <\/p>\n\n\n\n Q3. In a recent published paper it is reported that “Many clinicians and analysts find EHRs inflexible”. What is your take on this? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: That\u2019s another way of stating some of the challenges I mentioned. <\/p>\n\n\n\n Many EHRs are designed from the database up, not from the workflow down. When I work in the ED, I find that the EHR is very good at handling my one or two most frequent tasks \u2013 reading test results and notes, and making note entry somewhat less painful. But it\u2019s hard to bring up information in a different way for a different purpose \u2013 show me everything about that patient\u2019s cardiac risk, show me everything I need to make the best treatment plan for the next patient\u2019s stroke, tell me what rehab centers are available for the patient after that. A flexible EHR would be like a good hotel concierge \u2013 understand whatever I need to know next, and give me all the right information, in one place and in a usable form. <\/p>\n\n\n\n Q4. What about Data Quality? How do manage possible bias and ensure fairness? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: In general, capturing data and displaying it back works pretty well. Data quality is a real problem when trying to do advanced things with the data \u2013 doing analytics to understand illness trends, sharing data that came from EHRs with slightly different data models, applying guidelines and rules to improve patient care. <\/p>\n\n\n\n There\u2019s lots of partly-missing data, data items that aren\u2019t filled in, just as a consequence of the fast-paced, often rushed nature of medical care and data entry. Or, sometimes a data element on a form is not interpreted uniformly by the many people who are filling that form. If you build an analytic model, or a clinical decision support rule, that relies on that data, it could give you misleading results and affect your decisions. I remember a time earlier in my career when the lab code for a tuberculosis test was changed, but the rules that rely on it did not change, so incorrect alerts for TB started going out; that could have had serious consequences.<\/p>\n\n\n\n Inaccuracies can lead to bias and inequity — for example, when medical centers serving a high-income group capture more data than centers serving a low-income group, or when we rely on past inequitable practice as the basis for training our future decision rules. That has happened on a number of occasions across our industry. It\u2019s very important to think about these possibilities up front when designing analytics and decision support.<\/p>\n\n\n\n Q5. One key aspect is also Data Privacy. What are the common best practices you are aware of? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: Of course, this is a huge issue, and as you know, the solutions are partly about better systems and partly about better human practices. Fundamentally, the goal is that only the right persons see a patient\u2019s information, see only what they need to know, and don\u2019t spread it into other uncontrolled channels.<\/p>\n\n\n\n For the first part, role-based access control is a starting point. Smart access control, giving you easy access to patients with whom you have a defined relationship, is better; it\u2019s a good mix of ease of use and tight privacy control. <\/p>\n\n\n\n For the need-to-know part, there are ways to restrict access to certain elements and sections of the record. For example, administrative personnel commonly cannot see certain clinical data; or some data elements may be legally protected from being used for employment or coverage decisions. On the other hand, it\u2019s problematic to block a clinician\u2019s access to some of a patient\u2019s data, because any data may be important for medical decision making. So, for clinical use, often the best practice is to control at the patient level, not so much the data level.<\/p>\n\n\n\n Q6. Correlative analyses of EHR data with other external data sources can provide significant insights. What are the main challenges here? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: It boils down to making sure the data being used is correct and appropriate for the purpose. First, you need high-quality patient matching, to make sure that the EHR and the external source are in fact talking about the same person or the same group. Second, attention to data quality and interoperability is especially important here, since the EHR and the external database were populated for different reasons and may have different understanding of the same data elements. <\/p>\n\n\n\n This sort of combination also calls for extra attention to data privacy in all of the participating systems, so that the combined data doesn\u2019t reveal an individual\u2019s identity or expose private EHR data in unacceptable ways. <\/p>\n\n\n\n You\u2019re right about the important insights that can be gained from such a combination of sources, if you do a good job addressing these challenges. At the population level, multi-source data can be extremely valuable for many uses \u2013 such as concentrating opioid-treatment resources in neighborhoods where there is a greater history of overdoses, or developing school lunch support programs in areas where EHR data shows malnutrition-related health problems.<\/p>\n\n\n\n Q7. You have recently launched an AI-powered electronic health record (EHR) and healthcare information system. What is it? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: What it is, is amazing. InterSystems IntelliCare is a true game-changer from the point of view of a clinician, a patient, a health quality leader, and more. It is a deep integration of a top-class AI database and engine with a full-function EHR, as well as a digital voice and image capture system \u2013 all built for each other. This integration provides true depth in every part of the record, letting you get the benefit of AI for a wide range of applications. <\/p>\n\n\n\n From providing custom summaries for many medical scenarios, to reducing the work of both structured and unstructured documentation and ordering, to streamlining communication, to orchestrating complex workflows, to mining information in text notes, we find that the AI-enhanced integrated record can improve quality and reduce burden in many ways. I said above that EHRs need to gather and present data the way that matches my medical thought process; InterSystems IntelliCare is built to address that need.<\/p>\n\n\n\n Of course, we\u2019re continuing to advance InterSystems IntelliCare beyond the version just announced \u2013 the potential range of benefits to the care process is staggering.<\/p>\n\n\n\n Q8. Will the use of AI improve Electronic Health Records? If yes, how? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: In a nutshell, I think well-designed generative AI gives us a chance to get back to the kind of practice we once had \u2013 more focus on the patient, more time to think and talk, less busy work, better communication, less time staring at the computer screen. It also will allow us to unlock the vital information buried in clinical notes, which is so often overlooked today. It will provide a greater, easier-to-absorb awareness of what\u2019s going on, with a single patient or with an entire population. And one of the greatest benefits will be more usable information going to the patients themselves.<\/p>\n\n\n\n Q9. There seems to be a tension between one hand delivering streamlined workflows, reduced administrative burden, enhanced patient interactions, and improved operational efficiency and on the other hand maintaining rigorous human oversight for accuracy and safety. How do you manage this? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: With a healthy dose of skepticism, and a great deal of rigor. We are very concerned about measuring, monitoring, and improving our AI systems, particularly with respect to recall (capturing and providing all of the data that it should, without omissions) and precision (not providing false, incorrect, or \u201challucinated<\/a>\u201d information).\u00a0<\/p>\n\n\n\n InterSystems has a large quality assurance \/ testing team that plays a huge role in all of our software development; they have adapted themselves for the particular needs of testing AI, and have developed test suites that we are running constantly as we continue to develop. Guided by this, we have added many guardrails in our software and in our prompt engineering to enhance accuracy and safety. <\/p>\n\n\n\n And yes, it’s always important to make sure that there is a human in the loop at strategic points. We have a variety of forcing functions that ensure that human review and final approval is obtained where needed, especially before data is entered into the record. In general, I much prefer to use AI to reduce work burden by 80% with human-in-the-loop enforced, rather than to reduce burden by 100% but have no oversight; it\u2019s still a tremendous benefit.<\/p>\n\n\n\n Q10. Let’s focus on one of the promises of using AI in this context: Enhanced Patient Engagement. What does it mean in practice? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: As I\u2019ve mentioned, direct benefits to patients are among the most promising areas for AI. This is a whole interview in itself, but I can summarize some important elements. As a patient in a clinical or hospital care situation, imagine that you have a constant summary of where you are in your care plan, what\u2019s coming up next, your latest results and vital signs, the results of your CT scans \u2013 all organized in a readable and understandable fashion. <\/p>\n\n\n\n We just don\u2019t get enough time to give you that kind of information nowadays, but it\u2019s incredibly important. If you need to ask your practice a medical question, AI can help you compose it and help your medical team respond more quickly; or it could streamline things the next time you need to schedule an appointment. And of course, ambient AI voice dictation means that your doctor will have more time in each visit to interact with you, instead of constantly typing into the record. Besides all that, there are lots of ways that AI can interact with you directly at home, helping you to monitor and optimize your self-care, while always standing ready to send a message to your clinical team if a potential problem is arising.<\/p>\n\n\n\n Qx Anything else you wish to add? <\/strong><\/p>\n\n\n\n Jonathan Teich<\/strong>: This is a remarkable time in healthcare. I really believe that enhancements in data handling, interoperability, and especially generative AI are going to revolutionize our healthcare lives for the better, benefitting clinicians and health workers and scientists and patients — more than any innovation that has taken place in my career. We must always be careful to protect safety, privacy, and equity; but I believe we can. I believe that the next few years could see enormous positive changes in the work of healthcare, the accessibility of healthcare, and the quality of healthcare.<\/p>\n\n\n\n ……………………………………………………..<\/p>\n\n\n\n Dr. Jonathan Teich<\/strong> is Chief Medical Officer and Director of Clinical Innovation for EHRs at InterSystems. <\/p>\n\n\n\n He helps lead vision, design, and thought leadership for solutions to high-priority needs of providers, health systems, and governments worldwide, with particular focus on generative AI, usability and workflow, patient engagement, clinical decision support (CDS), and optimizing how EHRs can help achieve strategic clinical and operational goals. <\/em><\/p>\n\n\n\n Dr. Teich is a practicing emergency physician at Brigham and Women\u2019s Hospital and assistant professor at Harvard. He founded the Clinical Informatics R&D department at Partners Healthcare (now Mass General Brigham), developing two generations of innovative electronic health records, computerized provider order entry, knowledge retrieval, and CDS applications, and has authored over one hundred publications and three books in the field. He serves on numerous government and industry panels concerned with CDS, healthcare quality, and workflow design; he has served on the board of directors of AMIA, HIMSS, and the eHealth Initiative. Dr. Teich also volunteers as clinical architect and designer with OpenMRS, an open-source electronic health information system serving over fifty low- and middle-income countries worldwide.<\/em><\/p>\n\n\n\n Resources<\/strong><\/p>\n\n\n\n Electronic Health Records (EHR)<\/a>-2025 American Medical Association.<\/a><\/p>\n\n\n\n Related Interviews<\/strong><\/p>\n\n\n\n On Data Platforms. Interview with Gokhan Uluderya <\/a><\/p>\n\n\n\n On using AI and Data Analytics in Pharmaceutical Research. Interview with Bryn Roberts <\/a><\/p>\n\n\n\n \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026..<\/p>\n\n\n\n![\"\"](\"https:\/\/www.odbms.org\/blog\/wp-content\/uploads\/2025\/03\/2022-05-JT-ISC-cover-1024x843.jpg\")
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