The behavioral and mental health software market is expected to expand at a compound annual growth rate (CAGR) of 17.3% from 2024 to 2033, according to recent projections — with electronic health record (EHR) systems playing a big role in this surge. However, many providers have been slow to adopt modern behavioral health solutions, leaving them behind clinicians who have pursued such sound investments and reducing the likelihood that clients receive the highest quality care and support.
A bill before Congress, the Behavioral Health Information Technology Coordination Act, would help finance behavioral health technology adoption by providing grant funding of $20 million per year, over five fiscal years, starting in FY2025. The Substance Abuse and Mental Health Services Administration (SAMHSA) and Office of the National Coordinator for Health Information Technology (ONC) also aim to improve the efficiency and cost of data collection, measurement, and reporting with the Behavioral Health Information Technology (BHIT) Initiative, devoting more than $20 million to the effort over three years.
What do these and other efforts to encourage greater adoption of advanced behavioral health solutions mean for providers in mental health, substance use disorders, and intellectual and developmental disability (IDD) settings? It’s time to consider the current state of your technology solutions and whether it’s time to invest in a new EHR, particularly if your current system doesn’t leverage the benefits of AI in healthcare.
Identify technology competencies that will best serve your behavioral health organization with our guide, The Ultimate Guide to Behavioral Health EHR Selection.
How can you tell if your current EHR platform needs an upgrade? Consider the following six warning signs.
One of the biggest indicators of how well (or poorly) your EHR meets your organization’s needs is its triage capabilities.
An EHR built for behavioral health must make it easy to identify individuals who need care and support the most with real-time risk scores. Users should be able to define risk factors and customize rules for managing patients according to characteristics like past suicide attempts or hospitalizations in the past 30 days. Faster risk screening and routing allows the provider to better triage care.
An EHR designed around behavioral health workflows, as opposed to a general EHR, will also make it easier to then tie these screening activities to related assessments within client records and follow through with treatment and support planning, monitoring, and ongoing progress notes.
The many nuances of diagnosing a client with a mental health condition, substance use disorder, or IDD can not only make the task difficult and time-consuming, but also may inform care plans and/or medication prescriptions that aren’t fully effective in treating the person’s symptoms or improving their quality of life. The time and investments lost in that care add up, potentially leading to client frustration and a need to start over with new approaches.
The top behavioral health solutions offer tools that utilize AI to increase the accuracy of providers’ assessments. Core Clinician Assist: Symptom Tracking, for example, uses natural language processing (NLP) to review large datasets — including the notes of all caregivers the client sees — to help identify difficult-to-see symptoms. It then shares a visual of possible diagnoses to aid in clinical decision-making.
Benefits of AI in healthcare like these can enhance preventive care, saving the cost and time of hospitalizations, emergency room trips, and unnecessary services.
Serving clients in all communities effectively is a critical need given today’s behavioral health access challenges. If your EHR requires a clinician to move between different systems to provide increasingly vital services like telehealth appointments, it introduces complexity and creates a source of needless delay.
Modern EHRs for mental health providers allow the clinician to instantly conduct a telehealth appointment without leaving the platform. This seamlessness is a better use of time, results in less frustration for the provider, and is more likely to lead to an on-time and successful appointment. For clinicians who embrace remote appointments, differences in this experience will become even more meaningful to satisfaction with their work environment.
AI for mental health, substance use disorder, and IDD care can also be a valuable tool for collecting data on barriers to care and identifying better service and treatment options both at the population health level and for individuals. Similar to Core’s symptom tracking solution, Core Clinician Assist: HRSN Tracking uses NLP to scan provider notes and identify social determinants of health (SDOH) and health-related social needs (HRSN) early at the point of care. This allows for proactive interventions that improve treatment plan adherence and the ability to quickly connect individuals with support resources, while also providing insights into larger community health concerns.
There’s little room for error when sharing client records and information between providers, or during care coordination — particularly when clients have co-morbidities that require full visibility and a multidisciplinary approach to ensure proper treatment and support. In the United States, about 21.5 million adults have a co-occurring substance use disorder and mental illness, according to SAMSHA, and it’s crucial for their care teams to work together cohesively to address complex needs and avoid conflicting treatment or advice. The prevalence of co-morbidities across individuals’ mental and physical health likewise requires careful coordination and has spurred models for integrating behavioral health into other medical services— like the Primary Care Behavioral Health (PCBH) model, which includes a behavioral health consultant as part of the primary care team, and the Collaborative Care Model (CoCM), involving psychiatric services and care management for conditions like depression.
As care continues to become more integrated, those providers whose data is protected –– but not siloed –– in behavioral health solutions will be best positioned for success. Anomaly detection, another feature backed by AI for mental health, substance use disorders, and IDD, can also flag to care teams potential problems that could lead to negative outcomes by searching for outliers in progress notes.
The business environment for behavioral healthcare is becoming increasingly complicated. Value-based care arrangements are creating greater need for understanding and more accurately and efficiently documenting and reporting the link between intervention and outcome.
One differentiator for keeping up with this shift in care delivery and payment is behavioral health solutions that include evidence-based prompts which enable automated documentation without disrupting the clinician’s natural workflows. Also integral to these efforts is the ability to recognize differences among subsets of client populations receiving interventions to help identify measurement-based best practices. Dashboards need to be intuitive and reflect custom metrics most important to the organization and user, whether administrator or clinician.
Contract modeling requires a more sophisticated EHR designed for behavioral health to effectively project total costs of care and the organization’s ability to hit targets based on the unique characteristics of its patient populations and clinical performance trends. Finally, revenue cycle management can be enhanced with AI and machine learning that can quickly review a host of rule iterations to better ensure claims are clean and filed correctly, reducing denials and speeding up reimbursement.
Lastly, a commonly overlooked EHR aspect impacting an organization’s competitiveness is user experience.
Spend some time observing EHR use at your organization. Does the home screen look the same for every user, regardless of role? Does the clinician need to pause to find a screening tool? If the clinician steps away for a moment to attend to an urgent care need, do they need a few moments to pick up where they left off?
These are all small “tells” that your behavioral health solutions aren’t aligned well around user workflows.
With behavioral health staffing, recruiting, and retention under significant strain, organizations must think of ways to reduce stressors in the workplace. Seeking EHRs with an intuitive user experience and that make use of AI and advanced analytics to minimize steps in processes can ease the burden on staff.
The right EHR will work efficiently with the clinician’s preferred behavioral health workflows, auto-populating and bringing just-in-time information, rules-based best practices, and insights to the forefront as needed, so they support the natural way a clinician works. Dashboards should allow for easy customizations, so they reflect the metrics most relevant for the clinician’s patient population and priorities.
Core Solutions Cx360 EHR platform is built specifically for behavioral health. To learn more about ways Core Solutions can help you overcome your current clinical and business challenges, view a demo today.