Contract design thinking: a service oriented architecture SOA for contract models, maintenance and testing

Contract variances complicate academic medical center accounts receivables
because they are one driver of ambiguity when calculating future free cash
flows FFCF [1]. UC Health provides leadership and strategic direction for
UC’s five academic medical centers and 18 health professional schools.
Contract variations within 1 (one) medical center has a multiplier effect
in the consolidated annual financial reporting. In December 2017 we
created an internal project charter [2] to consolidate contracts financial
accounts receivables activity (including system optimisation) within a
revenue cycle operations department. Importantly, this project charter
integrated managed care contracts built is a second Epic application
(Tapestry). Prior to this, information technology IT staff made systems
changes (in the Resolute application only). This work was driven by direct
communications from the contract negotiation functions at UCSD Health. In
April 2018, we started a collaboration with the University of California
San Francisco Medical Center.  At the highest level, the
collaboration was intended to address a fragmented finance and contracts
management landscape built up over time. These campuses share an
electronic medical records system (Epic) which benefits from standardised
exchanges of contract language and data structure definitions. By itself,
executed contracts and several of the Epic recommended design and
contracts management tools can be inadequate in terms of
language, content, medium, and design. Operational challenges created by
incomplete contracts specifications, long cycle times and poor
'fit' between the data and the build almost always add
to aggravated operational issues. Rather than enablers of business
success, contracts become obstacles [3]. Our collaboration has four main
purposes: First  to resolve or at least alleviate the problems of
dysfunctional contract communication. Second to enable the exchange of
pertinent, solution oriented legal, data and
analytic information among different UC medical center revenue
cycle organisations. Third to intensify and expand efforts to simplifying
contracts, especially in fundamental areas like naming, ordering and
sharing test data. Fourth to raise awareness that simplifying contracts
and pre and post contract data might prompt a new cluster for
applied intra- and interdisciplinary research for reducing cash expenses
from fixed and variable costs in time CE.   References 1 Grzegorz
M 11 2008. A portfolio management approach in accounts receivable
management. Journal South East European Journal of Economics and
Business, Vol. 3, No. 2, pp. 89-96. DOI: 10.2478/v10033-008-0018-4 2 Ahl
S, Felker C and Thurman P 12 2017. UCSD Health internal
document. Hospital, Professional, Managed Care contract
performance operational lead re location to revenue cycle patient
financial services / Hospital, Professional, Managed Care contract
contract maintenance setup and support / Contract maintenance co operative
strategy with other UC medical centers . This is identified in a
consolidated revenue cycle data catalog <d/078 2018 03 018 help
create a sustainable contract management service> 3 Swiss Re Centre
for Global Dialogue 2016. International conference on
contract simplification.
<http://bit.ly/2GvLqOK>. See
especially, Kilgour S and Unsworth R. Swiss Re Managing
the complexity: text mining analytics.
<http://bit.ly/2uIqChP> last accesed 2018 04 03. UC
San Diego Health converts its contracts into Oasis Legal XML [4]. This
conversion yields important analytic and information governance
results.  We adopted a (Epic) system capable naming convention
for the data structure. We developed a brief Adobe Spark on the job
training manual, a data catalog for the individual contracts and lines. We
hope to make this a sharable UC standard available to all UC medical
center campus partners (here on Dash). Certain features
in JMP 13 are very useful for exploring this unstructured text
data. JMP Pro 13 helps cluster terms and phrases and use text in
predictive models. Some of the capabilities required for text analysis are
analogous to those required for tabular data. Text analytics is like
general multivariate analysis. Topic analysis is like factor analysis.
Singular value decomposition (SVD) is like principal component analysis.
The Lanczos SVD handles messy data well and yields more meaningful factors
necessary for naming and ordering specific contract lines in Epic. See
2016. JMP 13 Preview: New text analytics in JMP Pro
<http://bit.ly/2H6UQgV> last accesed 2018 04 03. 4
See OASIS Advancing open standards for the information society
<http://bit.ly/2EhrDww> last accesed 2018 04
03. OASIS is a not for profit consortium that brings people
together to agree on intelligent ways to exchange information over the
Internet and within their organisations.