In the realm of healthcare, our ongoing commitment revolves around enhancing the quality of life, not just for individual patients, but for entire populations facing similar healthcare challenges. This intricate process of evaluating and pinpointing strategies to enhance patient outcomes within specific populations, such as those dealing with diabetes, hypertension, or PTSD, is commonly referred to as population health management. Rather than addressing patient care on a case-by-case basis, we acknowledge that assessing a defined population with shared conditions or needs allows us to identify preventive measures, reduce the likelihood of conditions worsening (e.g., hospital admissions), and optimize the allocation of healthcare resources and interventions.
Let's delve into diabetes as an illustrative example, as it is a condition frequently scrutinized within the context of population health. Within the diabetic patient population, we meticulously monitor critical information such as the date and value of the patient's last hemoglobin A1c, the date of their last podiatry visit, and medication compliance.
From this wealth of data, dedicated care teams, consisting of healthcare providers, nurses, social workers, health coaches, and more, collaborate to orchestrate comprehensive care for diabetic patients.
These teams diligently analyze the data they have access to, in whatever format they exist (could be sub-optimal), and then identify the most effective interventions and resources available for each patient. Through ongoing assessment of a specific patient population, these care teams can readily identify the unique needs within the diabetic patient cohort that can significantly enhance their health outcomes. For instance, one such intervention might involve a nutritionist-led food education program. The overarching goal of these initiatives is to actively engage patients in their own care, monitor their progress, and address any emerging needs.
Nevertheless, the true potential of population health and innovative health information technology lies in creating a more effective and efficient means of delivering data and insights to stakeholders, including care teams, patients, and healthcare organizations, all aimed at achieving the best possible outcomes for patients. Data analytics and interoperability play a pivotal role in furnishing timely, precise, comprehensive and actionable information, and are indispensable tools in advancing population health management.
Interoperability facilitates the seamless exchange of data between healthcare organizations, fosters patient engagement, and enables telehealth and remote monitoring. When discussing the care and coordination of population health management, we must ensure that not only the functionality exists, but that it is also used efficiently, often through automated workflows. It's been our observation that if workflow integrations are neglected, clinicians are less inclined to embrace these functionalities. Hence, our objective, particularly with clients like the VA, is not just to exchange data, but to ensure that the received data can be seamlessly harnessed to support population health workflows and the ongoing tracking and maintenance of population health.
These workflows encompass the establishment of adhoc direct messaging protocols complete with guaranteed service level agreements (SLAs), both within and beyond internal care teams. This fosters improved communication while also safeguarding the accuracy of the shared information.
As of May 2021, the Centers for Medicare and Medicaid Services (CMS) mandated that hospitals transmit electronic notifications to primary care physicians (PCPs) whenever patients are admitted, discharged, or transferred to another facility. We also endorse the continuous monitoring of patient readmissions, along with the implementation of a structured process for sending and receiving admission and discharge notifications. By doing so, healthcare professionals gain a better understanding of a patient's risk score associated with their chronic condition and can ensure the patient's discharge instructions and health maintenance plans are effectively executed.
Lastly, we advocate for the use of reports, dashboards, and advanced data analytics to monitor population health metrics specific to each patient's condition, further aiding in the determination of their risk score. These risk scores play a pivotal role in identifying whether external resources or programs are required to support patients within a particular population, streamlining communication among care team members in the process.
Through the establishment of these cross-organization interoperable workflows and processes and data analytics capabilities, we continuously unearth avenues to enhance population health outcomes for our clients, as exemplified by the case of diabetic patients, all while striving to enhance the overall quality of life for every individual.
InnoVet Health specializes in data interoperability, advanced data analytics (AI/ML), and clinical decision support.
By: Amber Werline (Systems Analyst at InnoVet Health)
InnoVet Health is an IT consultant company specializing in AI and business intelligence, digital services, and health interoperability founded by MIT-alumni & informatics experts. Learn more about us on our website or reach out on LinkedIn.
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