Jim Szyperski is the CEO of Acuity Behavioral Health, an organization redefining inpatient psychiatric care through data-driven innovation. Acuity has pioneered a brand new category—Behavioral Health Operations Intelligence—developed in collaboration with leading health systems. Its Behavioral Health Acuity Index (BHAI) and Acuity Insights platform leverage AI and real-time EHR integration to assist providers deliver more consistent, efficient, and effective care. The platform enables hospitals to reinforce patient outcomes, optimize staffing, and maintain financial sustainability.
Are you able to break down the recent federal and state-level funding cuts? How are they impacting community clinics and inpatient psychiatric units?
Without query, significant funding is being cut from behavioral healthcare programs which can be already understaffed and underfunded nationally. What we’re seeing is just a shifting of problems to the states with none clear resolution. The impact is falling directly on already overwhelmed emergency services, emergency departments, and native hospitals as people have nowhere else to show for treatment.
The recent HHS staffing reductions are especially concerning, as they affect critical agencies like SAMHSA, CDC, and NIH that support mental health and substance use programs. These cuts mean losing staff with years of experience, jeopardizing recent progress like reducing overdose deaths. While you mix federal cuts with state-level reductions, you are making a perfect storm where essentially the most vulnerable populations lose access to essential care at a time once we’re still facing ongoing mental health, overdose, and suicide crises nationwide.
Why has inpatient psychiatric care remained probably the most “opaque and under-optimized” areas of drugs for therefore long?
Inpatient psychiatric care has lagged behind its medical-surgical peers for many years for multiple reasons. First, we have relied heavily on subjective assessments that fluctuate from location to location. The high degree of variation and lack of quantitative, accepted models has stifled the aggregation of usable data from which best practices can evolve. So, unlike other medical specialties with clear diagnostic criteria and treatment protocols, inpatient psychiatry stays “stuck” without an efficient model with which to quantify patient acuity and progress.
Moreover, inpatient psychiatry is the bottom rung on the reimbursement ladder. Current reimbursement models are based on a per diem only scheme that undervalues psychiatric care and disincentivizes investments to extend staffing or implement recent technology. Because it stands, inpatient psychiatric facilities generally cover only about 65% of the hospital’s cost to deliver services. Consequently, hospitals are always operating inpatient units under extreme financial pressure, and at a time limit once they are overwhelmed with patients, understaffed, and badly underfunded. This environment is just not sustainable. Unfortunately, the absence of a baseline, a model to measure and quantify incremental expenses against, ensures there’s a low probability this can change.
Finally, the persistent stigma around mental health has limited investment and a spotlight in comparison with other medical fields. Though the pandemic elevated mental health right into a wide conversational topic, the easy fact is that these considerable conversations have largely remained just that, conversations, with little to no systemic change within the care and treatment of mental illness. The mixture of those aspects has left inpatient psychiatric care, and the highly dedicated nurses and staff treating these patients, “stuck” with outdated methodologies and limited data to drive improvements. That is precisely the gap we’re addressing at Acuity.
You’ve got introduced a brand new category called Behavioral Health Operations Intelligence (BHOI). What exactly does this mean, and the way is it different from traditional health analytics?
Behavioral Health Operations Intelligence (BHOI) is a wholly recent approach to managing inpatient psychiatric care. The BHOI is an entire rewrite of traditional behavioral health methods which can be retrospective, fragmented, and infrequently derived from medical-surgical census models that weren’t designed for more volatile inpatient psychiatric environments.
In stark contrast to census models, the BHOI provides an AI-powered framework for standardizing, measuring, and optimizing care delivery. It’s a clinical operations system specifically developed for inpatient psychiatry and behavioral healthcare usually. The BHOI provides clinical assessment data in the shape of comprehensive patient and unit acuity scores to nurse managers and administrators to accurately inform and make suggestions for operational decisions about staffing, resource allocation, and treatment planning. The BHOI provides actionable data to enhance the care and safety of patients and staff, increase operational efficiency, and establish a model for higher reimbursements.
Briefly, the BHOI establishes a typical language and measurement system across all the behavioral health ecosystem. This standardization allows behavioral healthcare to benchmark performance, discover best practices, and repeatedly improve in ways in which simply weren’t possible before.
How does the BHOI work—and what role does AI play in it?
The BHOI platform consists of two primary elements:
- The Behavioral Health Acuity Index (BHAI), a validated, comprehensive measurement and scoring of patient acuity on a 1-100 scale., and
- Acuity INSIGHT, our AI models that aggregate and analyze the acuity scores along with a series of relevant data streams captured throughout the Electronic Health Record system of record. Examples of this are specific nurse and staffing data streams, medical orders, comorbidities, medication management, etc.
It is vital to notice that each the BHAI and INSIGHT were created intentionally in full collaboration with a few of our nation’s leading health systems, including Yale Latest Haven Health, to make sure the BHOI is clinically accurate, relevant, and trusted by the professionals who use it each day.
Are you able to walk us through how your platform integrates into EHR systems like Epic? What is the impact on clinical decision-making?
Integration with EHR systems like Epic is a lightweight integration, built quickly and seamlessly into nursing staff’s clinical workflow. Specific quantitative data is accessed by flowsheets directly from the patient record and is combined with two short qualitative nurse inputs at shift change. This data is shipped directly from the EHR to our cloud platform and returned inside a second back to the EHR for display to nurse managers and hospital administrators, providing them an accurate and transparent baseline for evaluating patient status.
EHR integration also enables more informed treatment planning. With accurate acuity measurement, nurses managers can higher match care team interventions to patient needs and track whether those interventions are working as expected, dramatically improving resource allocation. Nurse managers assign staff based on actual patient acuity slightly than arbitrary patient-to-staff ratios, ensuring that essentially the most acute patients receive appropriate attention while avoiding unnecessary staffing for lower-acuity patients. Early adopters like Pine Rest Christian Mental Health Services, Cone Health, and Tanner Health are already seeing these advantages of their each day operations.
How does your AI-powered Acuity Insights platform forecast staffing needs and help prevent burnout?
Our Acuity Insights platform addresses probably the most persistent challenges in behavioral health—matching staffing levels to actual patient needs. The platform analyzes historical patterns, current acuity data, and external aspects to predict staffing requirements with remarkable accuracy. Ultimately, when staff are consistently overworked resulting from miscalculated patient needs, or nurse shortages end in double shifts, burnout is inevitable. Our platform helps nurse managers and administrators project the appropriate allocation of staff for every shift based on predicted acuity levels, not only census counts.
Beyond just numbers, the nurse’s real time inputs during shift changes are a key element within the platform’s calculation of patient acuity scores. As well as, the BHOI analyzes which specific nursing skills and specialties might be needed, allowing for more strategic staff deployment by nurse managers, even alerting managers to potential stress points or units at high risk for workers fatigue based on sustained high acuity.
The result’s more balanced workloads, reduced extra time, appropriate staffing levels, an empowered nursing staff, and a more sustainable work environment for these dedicated healthcare professionals.
What are essentially the most powerful predictive capabilities currently baked into Acuity’s system?
Up to now, essentially the most impactful predictive capability of the BHOI is thru INSIGHT, which, to steal a phrase from our Harry Potter loving team, is internally dubbed “Sorting Hat”. Sorting Hat uses our AI to research our expansive data sets and accurately predict (90%+) the extent of intervention by nursing staff that every patient will need the next day. Moreover, Sorting Hat is capable of match nurse workload by volume of patients, by patient acuity points and by nurse skill sets to suggest to nurse managers more balanced and equitable shift assignments to cut back risk of burnout and staff attrition.
Do you think that AI can fully replace subjective assessments in psychiatry—or will it all the time remain a tool for augmentation?
The BHOI is a clinical operations system for inpatient psychiatry, which by definition implies patients affected by Severe Mental Illness (SMI). Inpatient care is psychiatry’s ICU, and on this often volatile environment, for the security of each patients and staff, I imagine AI is an augmentation tool to tell, even suggest options and scenarios to nurse managers and inpatient leadership. The human connection between nurses and patients stays fundamental to effective inpatient treatment, and for my part, AI cannot replicate the nuanced understanding that comes from that relationship.
What AI does exceptionally well is provide objective, consistent measurement to tell and enhance subjective assessments. It provides a typical language for care teams and identifies patterns that usually are not obvious or apparent in human statement. In identifying the patterns, AI can then proffer future scenarios that can inform clinical decisions on patient need, appropriate nursing staff assignments, more efficient bed utilization, etc. This provides enormous efficiency, and ergo financial profit, to hospital inpatient operations throughout the patient stay lifecycle, from admissions through length of stay to discharge.
What challenges do you anticipate as you expand this platform nationally—regulatory, ethical, or technological?
Our platform was created from the bottom up by clinical experts from a few of our country’s leading behavioral healthcare institutions as a brand new category and patient classification system for behavioral healthcare to fill the clinical gap in patient care. In doing so, full attention was paid to HIPAA and the regulatory challenges with privacy and compliance as foundational principles, not afterthoughts. By design, the BHOI doesn’t retain personal information (PHI) but slightly only deidentified data and follows all security protocols.
We’re in continuous dialogue with our customers and nurse users, and investing heavily in incorporating their feedback and concepts into our product roadmap for the BHOI. From a technical perspective, the platform is adaptable to and interoperable with all major EHRs, and our implementation teams work side-by-side with clinical specialists within the real-world environment of inpatient psychiatry.
Perhaps essentially the most significant challenge with industry category creation is change management, particularly within the layered and sophisticated world of healthcare. Creating the notice of any recent technology and helping healthcare leaders understand their ROI on the brand new investment, and the way the BHOI will positively impact nursing staff or departmental KPIs, takes time and is thoughtfully and transparently approached. We have now found that hospitals are embracing the BHOI as a data-driven approach in a field heavily reliant on subjective assessments. The collaborative development model now we have chosen to follow with our health system partners is the crucial underpinning of the muse of a BHOI platform that clinicians actually need to use slightly than feel subjected to.
What does the long run of inpatient psychiatric care seem like if platforms like Acuity’s change into the norm?
At the beginning, mental healthcare IS healthcare, period. This can be a undeniable fact that everyone who has had a member of the family or friend affected by mental illness fully understands. Our mental health and physical health are inextricably intertwined. Unfortunately, our healthcare system was not developed with that premise in mind, and only lately, largely spurred by the pandemic, has the dialogue around mental health change into an everyday topic of conversation in healthcare.
But conversation and motion are miles apart in behavioral healthcare, and recognition, while crucial, is just not a treatment. Physical healthcare has benefitted from many years of information collection, analyses, and modeling. The amazing progress in cardiology, nephrology, oncology, etc. has been driven by best practices which have evolved through research and refinement over time. That has not occurred in behavioral healthcare which has lived a closeted existence.
The term parity is used quite a bit by behavioral healthcare providers within the context of comparisons with general healthcare. But parity implicitly requires a level financial playing field and that can never be achieved until behavioral healthcare tracks more closely with the remaining of healthcare: data-informed, standardized, and optimized as other medical specialties are. The BHOI is step one in creating a transparent pathway towards parity. It’s the primary validated and quantifiable model to be used in inpatient psychiatry that might help level the playing field, and supply actionable data and insights that hospitals can leverage for efficiency, retention of staff, and, yes, financial justification and appropriate reimbursement.
It is important that psychiatric units move as quickly as possible towards sustainability slightly than continuing on as significant cost centers for hospitals. The present state continues a downward path and is just not sustainable. Higher resource allocation, optimized lengths of stay, and improved patient outcomes are essential contributors, but they require quantitative measurements and results, data-driven models, to construct a healthier financial picture for behavioral healthcare. And time is just not our friend, “so allow us to not talk falsely now, the hour is getting late”.
