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Revenue design thinking: implementing enterprise tableau reporting at UC San Diego Health

Cite this dataset

Felker, Christopher; Ahl, Sue; Kavanaugh, Tiffany (2018). Revenue design thinking: implementing enterprise tableau reporting at UC San Diego Health [Dataset]. Dryad. https://doi.org/10.15146/R3X09B

Abstract

In February 2018, the authors agreed to participate in an Enterprise Tableau implementation.

There were 17 (seventeen) pilot projects identified at UCSD Health. This data pertains to 2 (two) agile data analytics projects

Atlas of sustainable operations indicators

Contracts maintenance co operative strategy with other UC medical centers

The authors committed to becoming certified users of Tableau software ('superusers') capable of assisting in a broader use of data analytics in ongoing business and clinical operations. The organisations represented in the community are all at different stages in their design maturity. Some community members are the only designer on their team, some are the only designer in a department, and some are struggling to move their organisation from design thinking to design doing.

Our colleagues conceive Tableau dashboards that use data not replicated in Epic provided reporting tools. Our hypothesis is that this data will quantify several key performance indicators using a 'distance to frontier' methodology. Consistent calculations of these metrics might improve revenue cycle operations across a performance spectrum.

At one end of the spectrum are UCSD system optimisation opportunities and staff focus. In the middle of this spectrum are the comparative performance of UCSD contracted vendors. UCSD's tiered vendor agreements are designed around a 'race' dynamic where the first to collect revenue captures an economic advantage. At the other end of this spectrum is actual payer payment behavior. Calculations based on contracts, denial, ICD-10 coding schema guide the relationship.

Across this spectrum, revenue cycle operations involve combinatorial complexity [1] - many different variables are at play  - patient, procedure, location, doctor, sequencing, payer, adjudicator, claim editing / acceptance rules. If UC San Diego, in partnership with its sister campuses, are likely to discover better solutions using data and data analysis techniques in projects like this one. This is 'discovery' and 'alpha' level work - the future state will involved sharing standardised data sets with other UC medical centers, and Tableau data analytics within a shared enterprise server environment.

This work is currently sponsored in a continuous improvement organisation. Not unique to UC - but an exciting opportunity nonetheless is the opportunity to bring data insights to a workforce dedicated to overcoming social and gender barriers in data use. The princple of communities helps us guide leaner operations while affording numerous staff development opportunities. Risk literacy and statistical thinking is an empowering element of support models for operations staff.

References

1

Jonathan Symonds 2015. Reverse engineering payer behavior to improve denied claims management.  Ayasdi Incorporated <http://bit.ly/2GM5wkX>. Last accessed 2018 03 20.

2

OASIS 2017. LegalXML eContracts Version 1.0. OASIS <http://bit.ly/2HMHLZm>. Last accessed 2018 03 20.

Methods

Design principles

In conversations, research and collaboration, revenue cycle management agreed to a set of principles that will attach to every data set issued by its service. UCSD Health is a laggard in the impllementation of work place collaboration tools (box, trello and slack) so this work is textual (csv, txt, legalxml). Our team has created a data catalog (gsheet), data structure definitions (txt) and oasis legalxml [2] versions of its payer and vendor agreements.

Hypothetical data set (relied upon because the requested data production cycle is longer than the time allotted for an initial presentation)

Comma delimited (csv) randomised data produced by gsheets and stored as a google fusion table. 

Discovery data set

Pipe delimited (psv) extracts from the Epic 2015 electronic medical records system.

This data was defined by a data description document (txt). It was standardised (sdmx statistical data formats, ablebits data cleaning, gsheets additional iso reporting intervals. Tableau - in this discovery phase of the pilot - links to the data tables on a google drive. The alpha solution is to add the data to a sql table hosted by UCSD decision support. The beta solution is the implementation of a tableau server environment. The tableau work sheets, stories and dashboard was created using UC identity and branding guidelines throughout.

Usage notes

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).

Location

San Diego, CA 92122, USA