Health Information Systems Improvements

How do you feel about your work email inbox? Do you love it or hate it? Do you find it easy or hard to manage? 📧 Now, imagine having two email inboxes. One for your regular business communication, and another for your health care communication. One place where you deal with messages from patients, team members, other providers, auditors, and more. 😱 And that's not the end of it. You also have to keep up with important information in your business email too, regarding guideline changes, standard changes, protocols, policies, and updates on patient care. All this, without any dedicated time for either. 😓 These systems are called electronic health records (EHRs), and they are supposed to help providers document and manage their clinical work. But instead of making their lives easier, they often make them harder. EHRs are complex, cumbersome, and frustrating to use. 😞 Research shows that EHRs can cause many problems, such as: 🩺 Lower quality of care and patient safety 💥 More medical errors and adverse events 😔 Less clinician satisfaction and well-being 💸 Higher costs and inefficiencies These problems are not simple or easy to solve. They have many causes, such as: 📋 Too many regulatory and administrative requirements 💻 Poor usability and functionality of EHR systems 🚫 Lack of interoperability and data sharing 🙋♂️ Not enough training and support 🧑🤝🧑 Poor workflow and team integration So, how can we fix these problems and improve the health care system for everyone? Here are some possible solutions: 📝 Simplify and standardize documentation and reporting practices 🖱️ Improve EHR usability and user experience 🔄 Enable data interoperability and exchange 🙋♀️ Provide more training and support 🩺 Involve broader care teams in clinical note documentation 🤖 Use artificial intelligence and automation to help with EHR tasks 🗣️ Advocate for policy changes and incentives to reduce EHR burden As a clinician and a health care leader, I believe that EHRs have the potential to transform health care for the better. But we need to overcome the challenges and barriers that prevent us from realizing this potential. We need to work together to create a system that supports clinicians, patients, and health outcomes. 💯

I spent over a decade trying to create a uniform normalized dataset from the data we were getting from over 600 different hospitals. I failed. Repeatedly. I tried many different algorithms, techniques, and a host of solutions that had the promising label “AI.” About a year ago I stumbled on a solution that I had never thought of. Instead of trying to use my fancy tools to understand the chaos of data on the backend, why not use the fancy tools to make it easier for the frontline providers to deliver excellent care AND create uniform and normalized data? True progress means rethinking incentives, workflows, and user experience. We inadvertently unlocked interoperability as a by-product of user-centric product design.    Read the full article:  https://lnkd.in/gHbuTxxa   #HealthcareInteroperability #HealthIT #PatientExperience 

I was recently Featured in an article in Informatics Magazine discussing "How Health Informatics Contributes to Cost Reduction in Healthcare." My focus was at the core being the value of centralized EHRs and the necessity for not only good data but also well-structured data. More specifically: Reduced redundancy: No more duplicate tests! EHRs provide providers with a comprehensive view, preventing unnecessary procedures. Improved care coordination: Seamless communication between doctors, with a patient's consent, leads to better-coordinated care and fewer medication conflicts. Fewer medical errors: EHRs can flag drug interactions and prompt for missing information, reducing errors and improving patient safety. It all comes down to the system's design, the user-friendliness of the dashboards, and fundamentally, the availability of good, structured data. No matter how powerful the analytics engine is, it's only as valuable as the data utilized. #healthcare #ehr #healthinformatics https://lnkd.in/gF-RvVwb

IHI Lucian Leape Institute releases Artificial Intelligence (AI) recommendations for #Patient #Safety and #Health #System #Leaders Expert panel by Institute for Healthcare Improvement convened in January 2024 to explore Gen AI's promise and risks Focused on three use cases Documentation support Clinical decision support Patient-facing chatbots #Documentation #Support Functions - Develop patient history summaries - Support patient record reconciliation, including medication reconciliation - Create documentation of patient-clinician conversations via ambient listening tools - Draft responses to patient messages, including EHR inbox messages Benefits - Reduce clinical documentation burden, thereby reducing clinician burnout and cognitive load. - Identify and potentially resolve inaccuracies in the EHR - Standardize common tasks like medication reconciliation - Improve accessibility of documentation for patients and caregivers - Strengthen trust and communication between patients and providers by allowing clinicians to focus more on the patient Risks and Challenges - Failure to inform patients about GenAI tools and obtain informed consent - Potential increase in clinician workload due to manual review of flagged inaccuracies - AI-generated efficiencies could be used for cost savings instead of providing clinician relief - Concerns over the accuracy and transparency of AI-supported documentation and the need for human oversight Depersonalization of documentation due to the loss of non-verbal communication #Clinical #Decision #Support (CDSS) Functions - Provide diagnostic support and recommendations - Offer early detection or warning of changes to patient condition - Develop and suggest potential treatment plans Benefits - Serve as an aide for clinicians by analyzing information and suggesting potential diagnoses and treatment plans - Improve diagnostic accuracy, save clinicians time, and potentially reduce costs Risks and Challenges - Clinical overreliance, compliance, and automation bias - Lack of transparency, explainability, and validation of AI systems - Prioritization of proprietary data over patient safety and quality care - Existing training data sets may include biases - Technological limitations and challenges of integrating genAI into existing workflows #Patient #Facing #Chatbots Functions - Function as data collectors to support patient triage - Interact with patients and respond to basic questions and concerns - Support care navigation, such as providing information on care center locations and appointment scheduling Benefits - Expand access to care - Democratize access to credible health care information - Provide more accurate and reliable data Risks and Challenges - Ethical concerns about technology mimicking humans and the need for proper disclosure - Chatbot accuracy requires ongoing auditing, maintenance, and updates. - Loss of human connection and potential erosion of trust between patients and clinicians