As some of you know, I have been working at Deloitte Consulting LLP to integrate a perspective of the near-future healthcare analytics market and its practical implications across areas as diverse as Research and Operational Analytics, Accountable Care Organizations (ACOs) and Insurance Exchanges.
The perspective came to fruition at HIMSS this year where Deloitte launched HealthCare2015. Of course this demo is not called HealthCare2050 as that suggests a time horizon too far down the road to visualize, nor is it named Healthcare2013 as it doesn’t need to be delivered soon. HealthCare 2015 instead provides a mid-term vision that likely has the ingredients in place but yet to be integrated comprehensively.
Our vision for HealthCare2015 is based on three transformative trends underway in the health care and life sciences sectors:
- The movement towards individual insurance markets – some estimate it to be as big as 50% of US insured population by 2020 with ACA creating a giant leap in that direction
- The convergence of health-care and life science industries – which will likely render continual transfer of data between these two hitherto secluded industries, a requirement for growth
- The leveraging of large volumes of untapped data – that sits in unstructured and siloed environments across multiple stakeholders
Let’s explore these trends.
The movement towards individual markets implies that the tools of the trade supporting the overwhelming group markets will need significant adjustment. The same risk pools and same processes cannot be extended to cover the individual markets.
What is a significant piece of data to support real-time, possibly web-based enrollment tools? With auto insurance, one’s premium is driven by not only the coverage required but also one’s driving patterns. Accordingly, the clinical status of the buyer can be a critical piece of information for health insurance. Even more critical are the trends that one can generate out of the insurance seeker’s longitudinal clinical records to determine his or her future needs. Doing so requires reference benchmarks that the individual’s data can be measured against. Is this starting to sound like Comparative Effectiveness Analytics? You bet.
Now let’s explore another scenario. If I am a large provider who is a part of a well-defined ACO, is it good to determine my failure of compliance matrices when I am ready to file the quarterly reports? I don’t think so. It is not only too late by that time to do anything about that quarter but possibly too late to enforce changes to support next quarter. How to handle the situation? Perhaps to have predictive modeling of potential needs of an inpatient, driven by the patient’s own data against a benchmark established for similar patients based on population health analytics.
In both situations the need for the integration of population analytics (comparative analytics, research analytics) with operational analytics seems clear. Also in both situations is the fact that a carefully constructed proactive platform can have significant impact not only on quality of care but also on cost of care, the two tenets that the ACA is based upon.
What is the flow of information required to support a HealthCare2015 vision? Well, I propose one of the many possibilities:
Imagine under an ACO setting, care coordinators trying to make sense of the critical course of care issues with their patients. The integrated platform leverages the currently available operational info to highlight the patients that are falling outside the reference ranges for pre-defined matrices (operational analytics). When the care coordinators drill deeper, they can get detailed information about a particular patient and compare his or her data against benchmarks established for patients showing similar demographic, genomic, ethnicity, gender traits with similar disease conditions, medications, and comorbidities (research analytics). Based on such comparisons, the care coordinator can pick one of the multiple therapeutic pathways that are pre-established based on leading practices used to treat a particular variant of a disease condition, such as life-style based, drug-based, or drug plus insulin based pathways to manage chronic diabetes (research analytics).
Once the care coordinator picks a specific pathway, he or she can be shown how to execute that pathway and highlight the activities that support the ACO/MU matrices that the care-coordinator is a part of. This allows them to schedule notices for care to proactively manage the compliance requirements (ACO compliance). Finally, in case during the open enrollment period the patient’s current insurance plan does not support the chosen pathway efficiently, the clinical data can flow to an insurance portal in order to recommend an appropriate plan for the patient (insurance exchange).
This is not a sci-fi story; the tools are here. It is simply a matter of integrating them smartly. With HealthCare2015, I hope we have taken the first step in that direction.
This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor.
Deloitte shall not be responsible for any loss sustained by any person who relies on this publication
As used in this document, "Deloitte" means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries. Certain services may not be available to attest clients under the rules and regulations of public accounting.
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