the next pivot
Data, Analytics, and Machine Learning
Over the past three years, we transitioned from being a private/cash-pay transitional living program with a small team comprised mainly of peer support and therapists to an integrated clinical and medical offering. In less than two years, we went from 90% of our revenue from families paying cash for services to 85% of our revenue from commercial insurance reimbursement. I’m incredibly proud of this transition, as we provide greater access to affordable, quality care. We have a long way to go to realize our vision for healthcare provision (patient-centered, relationship-based, and implementing cutting-edge interventions), but it’s a thousand-mile march…we’re just getting started.
• People deserve to use their insurance AND get quality care.
• Quality and affordability are NOT mutually exclusive.
• That said, you can’t do more with less…without innovation.
So, it’s time to talk about the next pivot: the Advaita Innovation Initiative.
The Future of Healthcare: Humanity & Machines
Let me start by saying that modern healthcare has largely stripped humanity out of the vital work of many healthcare professionals. We must get back to doing what humans do best: building authentic, trusting relationships.
To accomplish this, we must lean into technological innovation, not to replace the patient-provider relationship, but so that the relationship becomes the focal point. The future of healthcare will be about building community and collecting, managing, and developing personalized insights on large amounts of data. Healthcare will be about community, real-world issues (social determinants of health), and data. Full stop.
OK, so where are you going with this?
We’re about to make a big, scary pivot into the rapidly evolving landscape of healthcare technology. Say what you will, but I’ve “received a message from the universe.” I resisted this message (having tried unsuccessfully to learn Python multiple times); however, with the advances in machine learning, it’s time to get in the game. Below is a rough outline of what I see as our path forward.
A month ago, we were talking about migrating from Google to Microsoft and implementing PowerBI for analytics; now we’re talking much, much bigger…
Phase 1: Data Integration and Cloud Migration
Our immediate focus is setting a robust foundation for data management. By establishing secure connections from our EHR to Microsoft Cloud and integrating financial data with PowerBI, we aim for a seamless flow of information. This phase is critical for automating reports and developing dashboards that enable real-time insights for our leadership. We will eliminate data entry and create a single source of truth that integrates all of our clinical, practice management, financial, and marketing data.
Objective: Establish a solid foundation for data aggregation and automated reporting to support informed decision-making.
Actions:
Establish ODBC Connection from EHR to Microsoft Cloud: Ensure that the connection is secure and functional for seamless data transfer.
Connect QuickBooks to PowerBI: Integrate financial data into PowerBI for comprehensive financial reporting and analysis.
Consolidate Operational Data: Identify and integrate additional operational data sources into your reporting framework to provide a holistic view of the organization's performance.
Develop Automated Reports: Create automated reports for key financial and operational metrics to provide real-time insights to leadership.
Set Up PowerBI Dashboards: Develop user-friendly dashboards in PowerBI to visualize key data points and trends for quick and effective decision-making.
Metrics:
Successful integration of EHR and financial data into PowerBI.
Timely and accurate automated reporting on key metrics.
Leadership's ability to access and utilize reports for decision-making.
Phase 2: Initial Cloud Architecture and Planning for Machine Learning
Within the next three to six months, we're looking to ensure our data is well-organized and secure in the cloud and to lay the groundwork for incorporating machine learning into our processes. The guidance of a skilled data architect will be key in this phase, ensuring we have a solid plan for future developments.
Objective: Ensure seamless data integration and migration to Microsoft Azure.
Actions:
Contract with a qualified data architect to oversee the setup and integration process.
Develop a comprehensive data governance framework to manage and protect sensitive healthcare information.
Metrics:
Successful migration with no data loss or breaches.
Streamlined data access and reporting.
Phase 3: Modernization and Automation
From 6 to 12 months into our plan, the focus will shift towards leveraging AI to streamline operations. This includes automating tasks like patient scheduling and billing, freeing our staff to focus on what they do best: providing unparalleled care. Our goal is to create an experience as seamless and intuitive as any leading service in other industries, embodying simplicity and efficiency (think: Uber).
Objective: Implement AI and automation to improve operational efficiency and customer experience.
Actions:
Deploy AI-driven solutions for patient scheduling, help desk, contracting, and credentialing.
Automate repetitive tasks to free up staff for higher-value activities.
Enhance customer experience with a focus on simplicity and ease of use, akin to the Uber model.
Metrics:
Reduced wait times
Increased staff productivity
Improved patient satisfaction scores
Phase 4: Advanced Analytics and IP Development
As we move beyond the initial phases of modernization, our attention will turn to utilizing advanced analytics for enhancing patient outcomes and exploring opportunities for developing proprietary technology. This stage is about pushing the boundaries of what's possible in healthcare, transforming insights into tangible improvements in care and operational efficiency.
Objective: Leverage analytics to improve patient outcomes and develop proprietary intellectual property.
Actions:
Utilize advanced analytics to identify trends and insights that can inform value-based healthcare practices.
Explore opportunities for IP development in back-office functions like insurance contracting and provider onboarding.
Foster a culture of innovation and upward mobility within the organization.
Leverage data to assist clinical decision-making.
Metrics:
Demonstrable improvements in patient outcomes
Successful development of intellectual property
Implementation of proprietary solutions in other companies
Wait, are we qualified to do this?
Absolutely not, but who is? You’ve got to have a healthy dose of narcisim to think that you can lead this charge without a massive funding source and a technical background, but we’ve got to make a pivot. Our team impresses me every day with the focus on patients. This initiative will be largely spearheaded outside of normal operations with a small, nimble internal team and lots of external resources (which we hope to bring internal, as we build the SaaS business).
The majority of the team will focus on building out the integrated, whole-person care model and expanding the demographics we serve. We’re just about to get rolling with PHP, outpatient detox, and I hope psychedelic-assisted therapies are coming soon. The Advaita Innovation Initiative is designed to support our model of care and equip leaders with the information need to spend the majority of their time building and training their teams, developing new services, and creating a patient-centered environment.
How do you eat an elephant? One bite at a time (so I hear, being vegan and all).
(In case you were wondering, AIM launched shortly after I put together a similar manifesto…)
