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.

Produced and disseminated by UCSD Health administrative staff ('employees') under the 2015 10 23 University of California Presidential Open Access Policy <http://bit.ly/2ptLzaU>. Last accessed 2018 03 20. The authors do not own the copyrights for this work, but grant to the Regents of the University of California a nonexclusive, irrevocable, worldwide license to exercise any and all rights under copyright, in any medium, and to authorize others to do the same, for the purpose of making their articles widely and freely available in this open access repository. See policy text 3(B)(1). There is no embargo period that would delay this publication. See procedures 5(C).