The Current Environment
At the moment, fully integrated healthcare systems are performing value-based-care programs across the board like ACO, Medicare, Medicaid Risk, CCR, and bundled payment programs. This means that several concurrent data feeds like Clinical, Claims, SDOH, HIEs ADT, and EHR are going through the system. This makes for an extremely complicated environment when organizations utilize disparate, non-integrated solutions that don’t have the necessary scalability for physician performance and improvement.
The Ideal AI Solution
The ideal AI solution improves workflows and provides the data elements physicians need to make better decisions. Previously, bolt-on AI tools have been used but the increased complexity from the provider point of view has made things more complex. This is why AI should be transparent and embedded into the heart of the system workflows.
Persivia’s CareSpace® solution implements EMR connectivity into major provider workflows. This in turn allows organizations to streamline processes for greater administrative and clinical productivity.
AI and Healthcare: Major Impact Areas
It’s not just the AI technology itself that provides a major value. Using it across the board in conjunction with specialized teams can help reduce the cognitive burden when it comes to data, clinical, and administrative information flows.
Impact Area 1: Data
As we noted earlier, there are hundreds of data feeds going in and out of hospital systems with entire organizations existing just to manage it. AI can help by taking different data feeds and extracting the information that is needed for specific purposes like quality measurement information, related registry documentation needed for HCC coding, or information needed to close care gaps.
Depending on the number of programs your organization is involved in, you could have hundreds of data streams coming in. If one goes down, it can lead to missing patient information, resulting in additional problems that paint an incomplete picture of quality care. An AI solution can extract the right information from the right stream to prevent these kinds of situations from happening in the first place.
Impact Area 2: Clinical Improvement
By understanding where a patient is in the care pathway, organizations can use AI to make sure the right clinical information is presented to providers so they can make the best decisions.
Impact Area 3: Administrative Improvement
Administrative efforts are complex without the use of AI because they require teams to log into multiple systems, figure out which information is relevant to the patient, and then try to do something about it the “tasking” part of the process.
With an AI tool, organizations can:
This additional layer of automation helps to reduce the burden of gathering information and allows teams to focus on clinical efforts like contacting patients and resolving medication issues
This additional layer of automation helps to reduce the burden of gathering information and allows teams to focus on clinical efforts like contacting patients and resolving medication issues
Impact Area 4: Cost Improvement
Cost management is something that most organizations struggle with. AI can generate risk models from claims data for in-depth insights into HCC risk scores, population costs, physician costs, ADT costs, facility costs, as well as medication and specialty costs. Access to insights can result in better decision-making and overall cost improvement.
Achieving organizational goals with AI
AI means different things according to different contexts. There are several AI applications, specifically in healthcare that have their own place according to the goal that needs to be achieved:
- Neural Networks
- Machine Learning
- Natural Language Processing (NLP)
- Probabilistic Graphical Modeling
One of the major goals for hospitals should be to integrate data for processes like Natural Language Processing that can help to identify key data elements for providers. Additionally, AI should understand what is going on with quality measures and which quality metrics apply to a given population and provider group. AI can then extract the information that is relevant to those groups for better HCC risk adjustment, coding support, and care setting workflows from acute to post-acute and from ambulatory to home.
Persivia’s AI-driven platform Carespace® has the ability to capture data across all possible sources, normalize it, run it through the SOLITON® AI engine, and generate intelligent insights and assessments to close care gaps.
AI can help to identify the patient profile and then apply what it knows to the care pathway relevant to the patient. Surfacing the information can help groups with risk stratification to ensure the appropriate risk models are being applied to a given patient or care coordinator workflow. An integrated AI-driven population health platform like CareSpace® can help automate risk stratification for population calculations so care coordinators can filter and prioritize which patients are likely to have the highest readmissions risks.
Additionally, Persivia’s CareTrak™ application can help as an EMR companion to facilitate decision-making for providers at the clinical level.
Capturing social determinants of health
Using machine learning tools and processes, organizations can extract and identify the thousands of combinations of data elements that can show up on inbound and outbound data streams. From here, these elements can be fed into the rules engine in a format required by state and national HIEs. The more AI extractions that happen here, the greater the availability for data to be used in a standardized way at the state level. This in turn can help to promote health equity at the population level.
Real-time, customization scorecards for quality Improvement
The scorecard brings AI together at the clinical, data, and administrative levels by extracting relevant data and applying clinical and administrative logic to it. The fact that the AI is embedded into the system workflow means that quality metrics, HEDIS measures, screenings, medication adherence metrics, and value-based contracts are all updated in real-time.
The merging of AI with healthcare benefits the industry in ways never before dreamt of. By getting real-time information and event notifications, physicians can respond faster and make better decisions. As we have seen before, this results in higher overall rates of transition of care visits as well as lower overall readmission rates.
The AI revolution in healthcare is already here. It is time for providers and payers working with Value-Based-Care initiatives to take charge. Interested in learning more about how Persivia can help? Contact us to try out a demo today.
Table of Contents