BRENNAN healthsystems LAB
|
Modeling Participation in the NHII Background Regional health information organizations
(RHIOs) form the core building blocks of any approach to creating the
National Health Information Network. RHIOs are computer-supported information
sharing alliances composed of health care institutions that need to share
clinical, financial or administrative data. Institutions considering joining
RHIOs require trustable financial projections. Current approaches to health
information technology investment rely on a net-present value analysis, which
is inadequate to capture the dynamic, uncertain course likely to occur in the
RHIO environment. Thus, our team of medical informaticists, operations
researchers and computer scientists proposes to apply methods from operations
research (real options models and stochastic programming) to aid decision
makers in exploring the cost and consequences of various RHIO structures. To insure that the models provide valuable
and useful advice to their intended audiences, we will partner with the
Indiana Health Information Exchange (IHIE) to characterize the essential
business processes, gain real-world data, and solicit concurrent reactions to
the models and their output. The long-range goal of this research is to
create a suite of decision support tools that can guide RHIO pricing options,
discount rates, and optimal configuration choices. However, we must first
develop the modeling core of the decision support system. Our approach in
this feasibility study will consist of four stages. First, we will obtain
preliminary data from our primary industry partner, IHIE, in order to
understand the business processes, operational concerns, and strategic
priorities of this regional health information exchange. Second, we will use
these data to develop preliminary operations research models that capture key
aspects of the process under study, namely, formation of information-sharing
alliances. Third, we will consult with IHIE and a second partner, the
Wisconsin Health Information Exchange, to refine these models, adding to
their scope and introducing additional detail and complexity as warranted.
Fourth, we will validate our models by examining the decisions they propose
through scenario evaluation and simulation studies. Validation will occur at
intermediate stages of the process, involving consultation with our partners,
comparison with published reports, and computer simulations of evolving
information-sharing alliances. Although the operations research methods we propose
to use are valid and well established, they have not been applied in a health
care information technology decision context. They offer substantial
advantage over existing deterministic approaches to economic valuation of
health information technologies because they employ multi-period, dynamic
stochastic models that explicitly address such important aspects as the
impact on one institution of the activity by another institution. We will use
the results of this feasibility modeling project to create a proposal to
conduct a large-scale test of a suite of models involving awardees of the
AHRQ-Connecting Communities for Better Health grants. We will engage
additional partners through dissemination and consultation with IHIE and
WHIE. |
|
|