Name Is Krisa – IC in global practice
Help hopsitals and health plans around the world, primarily in north America and Europe to build analytics strategy. Help them algin business problems to data and analytics. and in general help achieve better patient care, reduce costs, improved patient experiences.
Today I wanna share a little of what’s going on the industry and what we’re seeing healthcare organizations do in the analytics world. And then ill talk a little bit about analytics culture and what’s needed to develop that.
Variation in care
Duplicative services
Undestanding patients and populations
No show patients -
Identify trending complications across population
Identify causal reasons for readmissions
Obviously to achieve the characteristics listed above, organizations will need to invest resources in people, processes, organization and technology. Any one of these alone will not get you there. Three focus areas help organizations build a strategic analytic culture:
Business Analytics Skills and Resources
Information Environment and Infrastructure
Internal Analytic Processes
A focus on Business analytics skills and resources involves finding the right balance of resources and making analytics more approachable. Your resource strategy must strike a balance between business acumen and analytical rigor. Make sure you have enough of each so that the analytics meet the needs of the business, and the business can be supported by the analytics strategy. In today’s labor environment, analytical skills are in short supply. As you strike that balance, you will want to augment your technical resources by making analytics approachable to the business users as well. Highly graphical, wizard driven tools allow business users to quickly and easily visualize their data and apply analytics without needing to be PhD statisticians. They can find their own answers faster, and better direct your analytic resources to the problems that require deeper analysis.
Business Analytics and Clinical Analytics
Health analytics is commonly divided into two categories: business
analytics and clinical analytics. Business analytics addresses the financial
and operational aspects of healthcare, such as cost and utilization
analyses, contract negotiations, and provider reimbursement. Clinical
analytics, on the other hand, is focused on the care provided to
patients and populations, and cover a range of analyses, such as
risk stratification, population health, measuring intermediate and
long-term outcomes, analyzing provider performance, and more.
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While business and clinical analytics have different purposes, they
overlap in many ways. For instance, it’s impossible to understand the
cost to a payer without understanding what level of care was provided,
how many providers were involved, and what procedures took place.
This interconnectivity is commonly referred to as the Iron Triangle of
healthcare, in which the components of cost, quality, and accessibility
are constantly in competition with one another. In other words,
it’s not possible to affect one aspect without affecting the other two
aspects because the three are inextricable. This is one of the reasons
why health analytics is critical; superior analytic tools are necessary
to understand the complex interdependencies that drive medical outcomes
and costs. And this analysis requires various big data from many
different sources that must be integrated to complete the full picture
of healthcare (Figure 5.8).
For example, the linking
Be sure to explain what a chronic disease is, why it’s important to states, etc.
Another view of top members – this one set to filter the top 10 spend, but you can choose to filter by any criteria – members with appointments tomorrow, members to call, ER visits in the last (period of time), …
The additional filters currently set up to limit chronic condition – but (again) can be anything. IP in the last (period of time), participating in a given program, …
Complication costs give a deeper dive into an element of one column’s data. The first column in the top graph has been selected in this example and details of complication costs are provided. Again, this can be a deeper dive into an aspect of the member’s data.
