Using advanced analytics to examine the ‘whole person’ for better value-based care delivery


The transition from a fee-for-service model to value-based care (VBC) in the United States has continued to accelerate in the wake of the Covid-19 pandemic. That’s because providers operating on a fee-for-service basis have seen their revenues drop sharply for much of the past year as elective procedures have been canceled and many patients have delayed primary care, even. for chronic illnesses. Quite simply, in the traditional healthcare payment model, no service equals no salary.

In contrast, providers with risk-based contracts received a specific amount, either per member or per patient, whether or not that patient received health services. You don’t need a CFO to recognize that something is better than nothing. Nor does it take the Surgeon General to know that a reimbursement model that rewards providers for providing quality care while controlling costs will produce better outcomes for patients, providers and payers. This is the promise of ACV and risk-based payment models.

For many vendors, however, there is one major hurdle preventing them from adopting VBC and alternative payment models: the lack of timely and actionable data. VBC and risk-based contracts focus on preventive medical care and well-being, while “comprehensive care of the person” adds to the equation of care by including mental and emotional well-being. ‘a patient or a limb.

Caring for the whole person means understanding the link between physical conditions (such as diabetes and congestive heart failure) and the components of behavioral health. This knowledge enables providers, patients and payers to develop comprehensive and effective care plans.

Yet without the proper tools to collect and analyze patient and complaints data – including social determinants of health (SDOH) such as a patient’s socio-economic status, housing security and access food, medicine and transportation – it is extremely difficult for providers to be proactive.

Taking care of the whole person depends on whether a plan member or current patient has access to things such as fresh fruits and vegetables, an Uber ride to a routine medical appointment, the enrolling in a smoking cessation program or social support network to help with the long-term effects of Covid-19. Indeed, at the height of the pandemic, there was an increase in demand for behavioral health and addiction treatment services as millions of Americans struggled with depression triggered or exacerbated by fear, isolation and economic anxiety.

Surprisingly, many providers still rely on Excel spreadsheets to track a wide range of quality and claims data for various models of care. These huge datasets quickly become extremely difficult to access in a timely manner. Even in traditional data warehouses, there is no way to effectively integrate aggregated data; such reports have to be entered and hard-coded, which can take months to complete.

In addition, different health systems have varying levels of sophistication. They may have data, but they don’t really understand what the data is telling them or the best action to take based on the information. Or decision making is hampered because the available data is not up to date and the data sources are siled and difficult to aggregate.

The only way to manage hundreds of metrics for different types of healthcare contracts is to use advanced analytics. You can’t act on a patient population unless you can view the data through different prisms, such as chronic disease, SDOH, and behavioral health. To do this, you need analytics that turn data into useful and actionable information.

Scans allow providers to dramatically improve the quality of care they provide because they have actionable information, such as when a patient was last tested for a specific condition or whether a patient adheres to it. prescribed medications. Through a comprehensive preventive approach, patient care is improved, preventable costly care episodes such as emergency room visits and hospitalizations are minimized, and healthcare costs are reduced.

It’s no surprise, then, that analytics can help providers and payers collaborate more effectively to reduce healthcare costs. For payers, analytics eliminate the long lag in claims data. And while clinical data is often more up-to-date, making the information available to any provider who provides limb or patient care can be a daunting task.

Ideally, providers need both clinical data and claims data. Claims data tells you where patients got healthcare services so a healthcare system knows that a patient has also seen an unaffiliated specialist, which is valuable for clinicians looking to treat the person in their area. entirety.

Which brings us back to the fundamental benefit of BCV: better outcomes and lower health costs through a proactive and holistic approach to limb and patient care. which also provides information on the health of the population. Imagine having all of this patient and claims data in a Health Information Exchange (HIE), with multiple health systems contributing the data. This would allow a view of patients and populations across a large metropolitan community. It all starts with data.

But data is not information. Analytics is what turns data into information about patients and member populations. Applying analytics to integrated data, including SDOH, enables providers and payers to improve quality of care through value-based models and effectively manage financial risk.

For healthcare organizations keen to embrace advanced analytics as a path to BCV, here are some tips to consider:

  • First, managing risk using analytics is not a consulting project. Hiring “experts” to analyze where you might be underperforming from a risk standpoint might sound like a good idea, but once those consultants leave you don’t get any more new data. Providers and payers need to be able to monitor themselves through analytics so that they can generate continuous information on clinical and financial performance.
  • Second, an advanced healthcare analytics platform cannot be treated as an IT project. This is a business initiative designed to solve a complex business challenge. So, you need input and buy-in from stakeholders across the business functions of an organization. You also need a user-friendly interface that makes it easy for clinicians and care managers to access and manipulate data.
  • Finally, take advantage of new technologies like the cloud to put a robust solution in the hands of clinicians and care managers so they can proactively manage their member and patient populations. Advanced Analytics as a Service is a highly scalable and reliable delivery model.

Value-based healthcare requires technologies that measure, predict and improve services based on medical and behavioral data, including SDOH. Such tools allow providers to deliver better results that demonstrate value. By adopting flexible healthcare analytics solutions that measure and analyze different data sources and promote a holistic approach to healthcare delivery, providers are in a better position to drive the success of value-based care.


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