What You Don’t Know About Your Patients Could Cost You
Sheila Talton, CEO of Gray Matter Analytics

Healthcare spending is projected to exceed $6 trillion by 2028, largely driven by rising costs of care for an aging population and the growing number of Americans suffering from chronic physical conditions such as pulmonary disease, diabetes and hypertension.

To improve health outcomes while lowering cost of care, providers and payors increasingly are implementing value-based care (VBC) payment models. VBC contracts are structured to reward proactive and preventive healthcare, measurable positive outcomes (such as lower readmission rates) and reduced spending.

Unfortunately, too many provider organizations lack the insights into their patient populations that are necessary to offer whole-person care. They may fail to recognize the existence of social determinants of health (SDoH) — the financial, social and environmental conditions that significantly affect a person’s well-being. They may be unaware of behavioral and mental health issues such as substance abuse and depression. Or they simply may not know whether or when a patient had a specific test or procedure.

The inability of healthcare organizations to access health-relevant information about their patient populations leads to gaps in care that result in poorer health outcomes and higher costs for the healthcare system, communities and families — the antithesis of VBC. Conversely, by having a full picture of a patient’s medical history, income and housing status, access to quality care, personal habits (such as smoking and drinking alcohol) and other factors that contribute to an individual’s health, providers and payors can better coordinate care to improve outcomes and manage costs. 

But to meet VBC program goals, providers and payors need a realistic understanding of the costs of care delivery. That knowledge must come from 1) utilization data and 2) advanced analysis of patient data to identify high-cost segments. 

Through data-driven insights into population health, committed strategies to preventive care and strategic interventions, providers can help patients better control and even prevent the development of chronic conditions, optimize clinic utilization and reduce avoidable emergency department visits.

Further, greater visibility into patient populations can help payors and providers prevent network leakage, select specialists for consults and referrals and identify opportunities for member or patient support and education to encourage routine care over expensive emergency services.  

Providers and payors can take specific actions to gain greater visibility into patient and member populations and ensure the success of VBC initiatives.

Grasp the Dynamics of Population Health and SDoH

Population health simply refers to the health status and outcomes of a group of individuals. Population health management involves identifying strategies to segment patients for proactive, high-value interventions, utilizing disease management or coordinated care models, generating data from care models to drive health policy and considering financial risk and clinical effectiveness.

It is essential that providers and payors know which levers affect the efficacy of a population health investment. This requires understanding the population through data. Analytics can be leveraged to make accurate predictions regarding responsiveness to interventions. For example, to improve health outcomes and lower costs for patients with diabetes, it is important to track data such as blood sugar levels, medication compliance history and access to healthy food. These indicators will help health professionals determine successful approaches to care. 

The link between population health and SDoH is critical. Factors such as socioeconomic status, education level, housing, transportation, community engagement, exposure to crime, social networks and provider availability undeniably affect health outcomes. People who live in a high-crime area and do not have safe transportation to work are inherently at a higher risk for poor health outcomes than those who live in a low-crime area and have reliable transportation options. 

Collecting and analyzing SDoH data helps providers know more about their patients, which enables them to offer more proactive and personalized treatment as well as referrals to support services. These preventive measures reduce healthcare costs over the long term by treating patients before their conditions worsen and require expensive interventions.

Adopt a Data-Driven Approach to Decision Making 

Medical device, EHR, socioeconomic, epidemiologic, genomic, lifestyle and behavior data are important components for mapping care pathways, yet they are not always available in aggregate. This prevents providers from getting the full picture, leaving them unable to make fully informed decisions regarding patient care. 

Data needs to be mastered, standardized and integrated to establish a holistic view of the patient. Combining patient data from multiple sources and in multiple formats requires heavy lifting from a data science and data engineering perspective, but it is imperative that data is cleaned and as complete as possible. Data management and governance policies ensure data trustworthiness by providing a framework that supports data’s usability. Role-specific provisioning can prevent costly security or HIPAA violations. 

Leverage Advanced Analytics

To fully track cost of care and recognize opportunities to decrease costs while also supporting positive health outcomes, providers and payors must harness the power of advanced analytics. With advanced analytics solutions, healthcare organizations can leverage data — including unstructured data — from disparate sources to generate actionable insights regarding next-best actions for patients, treatment plans and resource utilization.

Clinical, claims, historical and SDoH data can be used to identify which patients are at increased risk of health problems. Clinicians then can intervene to offer referrals and treatment options. 

Combined with artificial intelligence, advanced analytics healthcare solutions empower healthcare organizations to mitigate future healthcare costs and increase health equity.

Conclusion

For healthcare organizations to treat their patient populations effectively, they need to collect, analyze and commoditize patient-related data. Unlocking the value of patient data through analytics enables providers to promote wellness, recognize social determinants that drive the patients’ well-being, empathize and engage more effectively with patients, render more accurate diagnoses, recommend the most efficacious treatments, develop tailored medication regimens and ensure adherence and compliance outside hospital walls. By meeting these standards, the healthcare delivery system will organically streamline costs, while elevating the quality and standard of care and improving the overall patient experience. 


About  Sheila Talton

Sheila Talton is President and CEO of Gray Matter Analytics, which she founded in 2013. Prior to launching Gray Matter, Sheila was the VP/Globalization Officer for Cisco Systems in China and South America, President of EDS’ Business Processing Information Services and a Senior Managing Partner at Ernst & Young/Cap Gemini.  Her experience in governance extends to corporate, civic and not-for-profit sectors; currently serving on the boards of Deere & Company, Wintrust Financial Corporation, Sysco Corporation, OGE Energy Corp., Chicago’s Northwestern Memorial Hospital Foundation, The Chicago Network, the Chicago Shakespeare Theater and The Chicago Urban League.


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