The idea of healthcare's "triple aim" has emerged as a new approach to care in the United States. Healthcare organizations and providers are seeking to improve patient experience and access to care, increase the quality of care and lower the costs of care. To achieve the triple aim, providers are looking to population health data and analyses, much of which is contingent upon collecting patient-centered data.
In a webinar hosted by Becker's Hospital Review and sponsored by DataGen, Gloria Kupferman, vice president of DataGen, and Kelly Price, senior director of DataGen, discussed patient-centered analytics and how to approach population health to achieve the triple aim.
Population health refers to the health status and outcomes of all individuals within a particular group, according to DataGen's definition. Unfortunately, there is no standardized method for data collection that accurately represents the comprehensive image of a population's health.
"Each individual patient can ping pong around all the different care settings depending upon their own proclivities, what they're used to doing, where they're insurers send them and where their doctor sends them," said Ms. Kupferman. "Each individual has their own unique way of coming in contact with the healthcare provision setting….There's not a whole lot of coordination."
What's more, Ms. Kupferman added, is that there are a number of patients who never come in contact with the traditional healthcare environment whose data are not included in common data aggregation systems (i.e., provider and payer data).
"In order to assess the current state of play, the current status of the population, you need to know more about each of those individuals and what makes them the same and what makes them different and where are there opportunities to improve on all of those aspects of the triple aim," said Ms. Kupferman.
There are four main data sources that, when grouped together, can provide a clearer portrait of the overall health of a population, suggested Ms. Kupferman: Administrative data is information collected from providers following patient encounters. Payer data offers information on the full spectrum of care, but it doesn't have information not covered by the insurance plan and only provides a look into that payers' patient population. Individual providers collect their own internal data, which is largely clinical and diagnostic. Finally, community health data is generally based on surveys of populations or extrapolations of populations.
Each of these data sources have their pros and cons, but the combination of them all can provide a more complete understanding of a population's health status.
Once organizations have the data, they need to mine it accordingly to better understand the health status. Ms. Price outlined a number of ways to look at and measure the health of a population using the gathered data.
First, looking at the prevalence of chronic conditions in the population can be used to examine market potential, she said. "If you're contemplating opening a dialysis clinic, you need to know the prevalence of folks with end-stage renal disease in your population, in addition to knowing what other providers are engaged in that area."
Ms. Price also discussed the use of risk scores for fitting metrics together and determining the frequency and costs of events.
"You can use risk scores to put your population into cohorts and care patterns," she said. "Use them to identify what populations need more or less care or what individuals within a population need more or less care."
When it comes to population health, patient-centered data and analytics can be key to achieving the triple aim.
"It's one of the big issues that public health planners, ACOs and providers are all going to have to start thinking about in terms of driving down the spend and improving the efficiency of the system," said Ms. Kupferman.
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