Upcoming Events

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Abstract

Many health systems are implementing various forms of clinical command centers that apply an “air traffic control” model to monitor and synthesize data for real-time situational awareness to better drive operations. Increasingly predictive analytics can alert to expensive bottlenecks, delays and risks in patient progression through a hospital visit.

This session will categorize and describe approaches to command center operating models to address problems ranging from capacity management and patient flow to clinical deterioration risk, and to providing centralized virtual care. Although there are various approaches, they all start with an ability to aggregate data into a centralized repository and apply machine learning and predictive analytics to develop insight into operational factors such as barriers to discharge, and patient risk factors such as deterioration and sepsis risk.

The session’s specific focus will be on solving the “last mile” problem of communicating actionable insight to the right person in the right context. The assumption is that a holistic system requires both the analytics-driven nerve center as well as the peripheral nervous system of clinical communications technologies.

This focus group will inform a dialog to gather best practices and lessons learned for building towards a more real-time and proactive approach to operations.

Learning Objectives

1. Discuss progress made with various forms of command center operating models
2. Identify foundational requirements for the cultural, process, and technology capabilities needed for this “central nervous system”
3. Discuss specific thoughts about the clinical communications technologies helpful in shortening the time to action in improving operations and reducing risk to patients

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Healthcare organizations are struggling to prevent or mitigate the severity of a third-party or vendor-related data breach. However, as shown in our new research, current approaches to assessing and managing vendor risks are failing. Problems with current approaches to third-party risk management are creating a real economic impact as these organizations are seeing an increase in HHS and OCR fines and investigations. Register to learn more about key results including: - Third-party risk costs the industry 23.7 billion a year - Hidden costs are 10x above dedicated FTE salaries - Cloud applications & medical devices drive risk & breach costs

Learning Objective #1 - Understand the vast hidden costs of managing third-party risk, and what resources would be required to adequately manage risk.

Learning Objective #2 - Understand the gaps that exist in third-party risk management and know the alarming loopholes that are created by these gaps.

Learning Objective #3 - The biggest risks to patient care comes from disruptions or downtime to clinical applications and medical devices due to cyber attacks caused by breaches or ransomware introduced by third-party vendors. Learn what can be done to mitigate this risk.

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Rural IT Leaders wear many hats. From tier 1 technical support to executive oversight, the role of a rural CIO is broad in scope. Often, we take what we can get, and do the best we can with what we are given. With limited staff, staff skill levels, and available capital, we take each day at a time and put out daily fires. Our basic function is to keep the lights on! On top of this, the rural CIO is expected to carry out the Security Official duties. The stress of wearing many hats is taxing, making the burden real and overwhelming.

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Digital transformation requires alignment across multiple stakeholder groups and building systems of engagement by reimagining the overall health care experience from the point of view of patient and caregiver journeys. However, healthcare is in the early stages of digital transformation. Executing a digital strategy requires alignment with organizational goals, a best-of-breed information technology architecture, a robust governance model, and investment in emerging technologies. In this session, the speakers will discuss how the Cleveland Clinic is executing a digital transformation roadmap and present findings from recent research by Damo Consulting on the state of digital in healthcare.

Learning Objective #1 The current state of digital in healthcare

Learning Objective #2 Best practices in developing an enterprise digital strategy and roadmap

Learning Objective #3 Learnings from Cleveland Clinic's digital transformation journey

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Join the AEHIA and CHIME team for more information on opportunities to participate in the AEHIA community. Ask questions and engage members who have attended AEHIA events in the past to learn more about the value of AEHIA events, and how they can help you in your current organization and for the length of your career.

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It is estimated that there are 10-15 medical devices connected to the network for every bed in a hospital, and each device carries its own security and compliance concerns. It is also estimated that healthcare organizations typically keep medical devices in use for as long as 15 years, if not longer. As a result, these ubiquitous devices are extremely susceptible to technical attacks simply because most active security vulnerabilities cannot be patched. As an industry, we recently saw an example of this with one of Microsoft’s latest vulnerabilities known as, “CVE-2019-0708,” presenting a critical security risk. Given these devices are essential to delivering patient care, they are more than just a security risk to operations…they are a patient safety concern.

Learning Objective #1 - Define the current security and patient safety risks posed by medical devices

Learning Objective #2 - Analyze the operational challenges of managing medical device risks

Learning Objective #3 - Identify best practices to incorporate medical devices into risk assessments and to implement a functional medical device governance structure

 

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Abstract

The industry has largely shifted its focus to improving interoperability nationwide. As interoperability expands at a national level and as regulations continue to shape the future state of data exchange, we as an industry are challenged with determining the best path to ensure health information is easily available whenever, wherever, and by whomever it is needed. In this focus group, we will discuss how interoperability is changing and what questions remain including, the role of HIEs with the emergence of national networks, standards development, regulatory impact and how we as an industry can progress interoperability initiatives to improve a person’s health.

Learning Objectives

1. Explain obstacles to sharing data and how regulations are trying to address them
2. Assess the current state of interoperability and how it is changing
3. Discuss opportunities to improve data exchange

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Requesting members with a Large Integrated Delivery Network (IDN)

Enterprise imaging (EI) has been defined as “a set of strategies, initiatives and workflows implemented across a healthcare enterprise to consistently and optimally capture, index, manage, store, distribute, view, exchange, and analyze all clinical imaging and multimedia content to enhance the electronic health record." Healthcare organizations must plan ahead and move towards an established EI implementation and strategy. The aim of this focus group is to better understand the overall priorities of the CIO and help them demonstrate how powerful an EI adoption can be for any healthcare organization.  Source: What is Enterprise Imaging?; SIIM.org; January 2019 Learning Objectives 1. Vital should be able to understand the importance of Enterprise Imaging and how EI implementation ranks among CIO's overall priorities  2. Vital should be able to list two primary tools/techniques that CIOs need from the supplier to help with the adoption of an Enterprise Imaging strategy  3. Vital should be to identify the CIO’s top challenges and barriers around adopting an enterprise imaging solution to improve customer satisfaction.

Requesting members with a Large Integrated Delivery Network (IDN)

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Requesting members with a Large Integrated Delivery Network (IDN)

Enterprise imaging (EI) has been defined as “a set of strategies, initiatives and workflows implemented across a healthcare enterprise to consistently and optimally capture, index, manage, store, distribute, view, exchange, and analyze all clinical imaging and multimedia content to enhance the electronic health record." Healthcare organizations must plan ahead and move towards an established EI implementation and strategy. The aim of this focus group is to better understand the overall priorities of the CIO and help them demonstrate how powerful an EI adoption can be for any healthcare organization.  Source: What is Enterprise Imaging?; SIIM.org; January 2019 Learning Objectives 1. Vital should be able to understand the importance of Enterprise Imaging and how EI implementation ranks among CIO's overall priorities  2. Vital should be able to list two primary tools/techniques that CIOs need from the supplier to help with the adoption of an Enterprise Imaging strategy  3. Vital should be to identify the CIO’s top challenges and barriers around adopting an enterprise imaging solution to improve customer satisfaction.

Requesting members with a Large Integrated Delivery Network (IDN)

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On May 31st, the U.S. Attorney for the District of Kansas announced a $250,000 settlement with Coffey Health System. The settlement resulted from a suit by two whistle blowers claiming Coffey attested to a risk analysis of its EHR system pursuant to the Electronic Health Records Incentive Program and received $3M in incentive payments even though the risk analysis was not completed. Historically, the industry looks to OCR and its enforcement activity when discussing HIPAA risk analysis. While the penalties OCR may levy are not trivial, OCR’s approach of providing technical assistance and allowing organizations to come into compliance limits the number of organizations penalized. Coffey changes that.

Learning Objective #1 Describe the requirements for risk analysis under the Medicare Promoting Interoperability Program Learning Objective #2 Explain the relationship between the Medicare Promoting Interoperability Program and the HIPAA Security Rule Learning Objective #3  List the top reasons why an organization's risk analysis might not meet these requirements

 

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Bots can empower healthcare organizations to build and deploy an AI-powered, compliant, conversational healthcare experience at scale. The service combines built-in medical intelligence with natural language capabilities, extensibility tools and compliance constructs, allowing healthcare organizations to give people access to trusted and relevant healthcare services and information.

Bots;
* Deliver intelligent, conversational healthcare experiences at scale
* Empower healthcare organizations to build and extend intelligent health assistants
* Leverage secure and compliant platforms

The goal of the session is;
* Share lessons learned deploying Bot technical at a large IDN.
* Have an open discussion to share thoughts on if this technology provides value.
* Discuss when it makes sense and when it might not to use a Bot technology.

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When implementing a new EHR or optimizing your current system, key checkpoints are vital to ensure success. Ensuring that the following have been discussed and agreed upon with key stakeholders is critical for success: - Scope is clearly defined - Timeline is realistic - WHO are your champions - Change impact assessments – Readiness - Training - Activation - Optimization --> Continuous Improvement --> Efficiency Communication is critical at all levels and phases. With consistent, robust, clear communication from the highest levels of your organization, adoption is enhanced, minimizing impacts to patient/family satisfaction, as well as co-worker satisfaction.

Learning Objectives:

Key considerations for both an initial EHR implementation, as well as an optimization of a current EHR system Discussion of the key checkpoints vital to the success of implementation and optimization How to leverage and maximize your teams to ensure success, adoption, & continuous improvements

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Abstract

IoT technologies and connected medical devices are proliferating throughout the the healthcare industry and changing how patients are monitored, diagnosed and treated. But once a device is connected to your network, who is responsible for IoMT security and privacy? Recent data shows that the growth of medical IoT devices — along with unpartitioned networks, insufficient access controls and legacy systems — has created a massive and vulnerable attack surface that can be exploited by cybercriminals. This session will include a discussion on how to quantify and assess the IoMT risk across your network and steps that can be taken to manage threats and vulnerabilities. 

Learning Objectives

1. Understand the level of industry awareness regarding the threat associated with connected medical devices within provider networks & health eco-system.
2. Understand the maturity level of actions that have been taken to mitigate the exposure.
3. Solicit feedback on recommended actions and likelihood to adopt.

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Abstract

Today’s CIO is in a position to serve broadly; they must have strategies in place to address the needs of their community. This goes beyond the partnership with their board and leadership; they must convene and motivate multi-disciplinary internal teams that are focused on improving care and consumer (patient, member, employee) quality of life as well as reducing the cost of care. The University of Maryland Medical System (UMMS) faces unique state requirements associated with Maryland’s all-payer system as well as the requirements of the Medicare Shared Savings Program. UMMS will share their journey and lessons learned for the executive leaders tasked with supporting population health management.

Learning Objectives

1. Identify opportunities where CIOs can serve and lead as their organizations shift from a fee-for-service to a value-based care reimbursement model
2. Classify lessons learned into actionable steps that will support population health management activities for your patients and community
3. Identify the five key dimensions of a value-based care maturity model and how to apply these measures locally
4. Understand how CIO leadership can influence each of the VBC maturity model dimensions and bring about needed change management

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Abstract

Today’s CIO is in a position to serve broadly; they must have strategies in place to address the needs of their community. This goes beyond the partnership with their board and leadership; they must convene and motivate multi-disciplinary internal teams that are focused on improving care and consumer (patient, member, employee) quality of life as well as reducing the cost of care. The University of Maryland Medical System (UMMS) faces unique state requirements associated with Maryland’s all-payer system as well as the requirements of the Medicare Shared Savings Program. UMMS will share their journey and lessons learned for the executive leaders tasked with supporting population health management.

Learning Objectives

1. Identify opportunities where CIOs can serve and lead as their organizations shift from a fee-for-service to a value-based care reimbursement model
2. Classify lessons learned into actionable steps that will support population health management activities for your patients and community
3. Identify the five key dimensions of a value-based care maturity model and how to apply these measures locally
4. Understand how CIO leadership can influence each of the VBC maturity model dimensions and bring about needed change management

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How can we create a responsible data environment where we can contribute healthcare data, where privacy and security of that data is protected, and where the data can be made available for continuous learning systems using artificial intelligence (AI) and machine learning (ML)? In this session, we will discuss ideas ranging from the most restrictive to least restrictive, to enabling a new age of clinical discovery.

Learning Objectives:
• Review current state of data rights in healthcare
• Review recent developments regarding data rights in healthcare
• Discuss ways data rights may evolve with machine learning and artificial intelligence