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Nearly one million people have died from drug overdoses since 1999, and 75% of overdose deaths in 2020 were opioid-related. This tragic statistic has increased eightfold since 1999.
Complicating matters? Nearly one-fifth of the country is diagnosed with an anxiety disorder, which can begin in adolescence. Chronic anxiety can lead to worsening mental and physical conditions such as depression, substance abuse, chronic pain, poor quality of life and suicide in an already strained health care system in a country. affects the
Don’t sugar coat. we are in danger. Also, current treatment models for substance use disorders (SUDs) and mental health are not working.
Unlocking the right data at the individual patient and population level is critical to reversing this crisis.
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How can data help me?
Medical data is complex, fragmented and often incomplete. In behavioral health, the reality of data is most dire.
Patient data on mental health and substance abuse is often kept separate from other medical records due to lack of interoperability, regulatory constraints, and underinvestment in healthcare IT. But if providers had easy and secure access to trusted behavioral health data, they could make more effective treatment plans based on a patient’s complete medical history.
This concept sounds simple, but it’s actually more complicated.
Imagine this: A patient with a history of opioid addiction is brought to the ER after a car accident. The attending physician prescribes opioids for pain management without knowing the patient’s records. Patients take it unknowingly and then relapse.
What are the barriers to data integration and insights for healthcare providers?
The healthcare industry continues to suffer from a lack of data on mental health and substance abuse. The reason for this gap stems from many deep-seated and institutionalized realities.
First of all, the healthcare industry, especially SUDs and mental health treatment providers, has lagged in adopting new technologies and processes.
Significantly excluded from the incentives provided by the Health Information Technology for Economic and Clinical Health Act of 2009 (HITECH), behavioral health has been left behind in technology access and funding.
That the problem persists is evidenced by the drumbeat of reform by policy centers and industry groups. A June 2022 report from the Medicaid and CHIP Payment and Access Commission (MACPAC) states that funding through state Medicaid programs to accelerate the adoption of health IT will address gaps in access, outcomes data, and oversight. explicitly mentioned as an important step for
The current pay-per-service model in behavioral medicine financially rewards doctors and hospitals for the quantity and cost of the services they provide rather than the quality of the results. Until there is a significant shift to value-based care models, even the most impactful technologies may struggle to sell.
Compliance, Industry Regulations, Privacy Concerns Consistent Obstacles
The Code of Federal Regulations (CFR) Title 42, Part 2 is intended to protect the confidentiality of the addiction treatment records of persons seeking treatment for addiction or diagnosed with addiction under federal assistance programs. We limit the information you can share. provider.
Part 2 has been at the center of confusion and controversy, especially in the shadow of the opioid crisis. Recent changes have alleviated some of the stress created in Part 2, but questions and challenges around consent management and data segmentation remain.
The good news is that there is a template for moving forward. Pediatrics faced the same common challenges many years ago. Grassroots efforts and healthcare provider input have resulted in the successful implementation and operationalization of pediatric data and limit carve-outs.
Process lag for updating records causes “bad data”
Many facilities still keep paper records, so updating records and entering data electronically takes a significant amount of time. Additionally, most medical data are incomplete and often lack the critical connective tissue that binds the data together for improved analysis and outcomes. To make data useful, these providers must use sophisticated data approaches that can consume, connect, and clean data from multiple sources over time.
Disparate and legacy systems remain a persistent hurdle
Many care-critical applications and technologies remain tied to purpose-built, bespoke infrastructure that is difficult and costly to keep up to date. These systems are also often siled, limiting the care team’s ability to develop comprehensive insights.
Enhancing patient care with data
There are many process and data best practices that facilities and providers can use to build a strong data foundation and better collect, share and analyze data.
Data depth and precision
Advanced data science algorithms that account for missing data can correct systematic errors in SUD and mental health data. Additionally, datasets such as the Social Vulnerability Index can enrich patient-level information. Improvements in the integrity and quality of these data will result in robust analyzes and better patient outcomes.
Data insights and trends
Artificial intelligence (AI) and machine learning (ML) can comb through data sets to find meaningful patterns and insights. By leveraging these strong technological capabilities and innovations, behavioral health providers can more quickly and effectively fill imperfect values and standardize disorganized data.
Even if the data is less accurate, there are more and more insights and value providers to be derived from the data. A good analogy is the production of gasoline. Dynamic tools and technologies can quickly transform raw data into sophisticated products that can be used for predictive and prescriptive analytics.
Simply put, SUDs and behavioral health facilities are often at a much earlier stage of data maturity than traditional healthcare facilities, and curating the data they currently hold in a pragmatic way , you can get the maximum profit.
Future casting with dynamic modeling enables health care providers to identify people at risk of developing mental health conditions, provide preventative care before the disease progresses, and stop the disease before it starts. With increasing awareness of the rising prevalence and cost of behavioral health conditions, calls for prevention efforts are growing.
Across SUDs and behavioral therapy providers, predictive analytics may provide insight into which behavioral patterns indicate impairment or whether patients are at risk of recurrence. The infrastructure for predictive capabilities already exists, including patient engagement solutions, electronic surveys, and analytics. Industrializing, standardizing and making these capabilities available to all providers will strengthen industry alignment for individual patient care and measurement-based care.
What is the future of data-driven SUD and mental health information?
Increased data availability presents enormous opportunities to help advance patient care, especially with respect to mental health and substance abuse. Identifying patients who are predisposed, have early signs, are currently battling addiction, or are undergoing treatment is critical to the future of holistic health care.
SUDs and behavioral therapies, as well as traditional healthcare providers, can leverage data science, predictive algorithms, and other technology-driven approaches to build more capable and effective treatment models from the ground up. And healthcare providers can leverage the power of data assets and proven advanced analytics to enhance continuous operational and clinical improvement. These capabilities are already solving some of the most complex health challenges for patients and residents.
Richard Daley is CEO of Sunwave Health.
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