![Overview of Presentation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recomendados
Recomendados
Más contenido relacionado
La actualidad más candente
La actualidad más candente (20)
Destacado
Destacado (20)
Similar a Academic Helathcare - Business Intelligence Tool
Similar a Academic Helathcare - Business Intelligence Tool (20)
Último
Último (20)
Academic Helathcare - Business Intelligence Tool
- 1. Reporting & Analytics Mike Zang – Director of Information Services Russ Dinsmore – Assistant Director & Data Base Administrator Bess Wildman – Vice Chair and Chief Operating Officer University of Virginia, Department of Medicine
- 19. FRP and Drill Detail for A2
Notas del editor
- We’re going to try and cover a lot of ground this afternoon. I’d like to talk to all of you today about our department’s approach to information systems and development of a business toolset designed to provide insight into our organization and to enhance operational performance. Very few departments attempt such ambitious tool design at Uva. The norm is for departments to look to enterprise groups within the University and Health System to provide tools and for departments to integrate the data from these disparate systems in Excel. Prior to the arrival of Bess Wildman to the DOM this was the case for us as well. We took excel dumps from Uva’s financial software, comma delimited files from our practice plan, as well as variety of local excel workbooks and would massage these to produce our financial, grants management and other reports. To understand the dynamics which motivated the DOM to undertake this project I’d like to ask Bess to talk to you for a few minutes about some of her early experiences in the DOM. We’ll then continue framing the problems faced, the desired characteristics of a solution, outcomes and illustrative business cases. Once you have an idea of what we were trying to accomplish and how that plays out in our business I’d like to give you a quick look at the scope of the standardized reports and analytic tools and wrap up with a demonstration by Russ Dinsmore of our production system and one of our analytic modules and will try and leave approximately 15 minutes for questions at the end.
- Talk about at my arrival nearly 6 years ago, the DoM was reported to be 10M in the red and when I asked the naïve question of what is our bottom line. The answer was which one? See the Dept of Medicine lives firmly in the University and in the Practice plan. Each has their own chart of accounts, fiscal years, accounting rules and data rule sets. Yet our faculty and our expenses can move freely from a practice plan account and a Uva account. The practice plans financials only include the clinical side of our business and not the teaching and research and at the University our Oracle system did not provide a single place to see the Departments financial performance. So we first built systems in excel and access to get the data to our faculty. The cost and the amount of time was both unduly burdensome so about 3 years ago after discussions with Pediatrics and Radiology who were struggling with similar issues we approached the University, School and Practice Plan. All were interested but didn’t see this as a priority and felt our challenges were unique to our Departments.
- To continue with framing the problem we hadhave three primary sources for critical business data, two financial databases, one clinical billing & productivity database, none of which talk to the other in any significant fashion. Access - access to the data is limited to a few specialist, requiring specific training, different passwordsauthentication mechanisms. Creating a natural bottle neck to the flow of information, and in all cases leaves the faculty member without direct access or timely updates on the health of their activities. Restricted access also increases the number of times that data sets are handed off from the institution, to department analysts, to divisional analysts and hopefully eventually to the faculty. This generates a variety of problems not least of which are 1) The faculty often get different versions of the same information presented in different ways and often even in different data formats which leads to a lack of trust in the data and the administrators who present them this data. 2) Also this makes it tricky for faculty and administrators alike in knowing whether they have the right answer to the question that they are trying to answer. Without the data being brought together and issues of format, date, fiscal period, etc.. Being worked out in advance it’s difficult to know whether you’re actually comparing apples to apples and actually getting a meaningful answer to the question asked.
- In the previous slide I mentioned the diversity of data sources, system access, and data manipulation & analytic techniques which inhibited the success of the system in providing insight and effectiveness to our business. I’d like to look just a little closer at some of the data issues that complicate this picture. Our two financial systems not only sit on different system with differing chart of accounts, they also work off of different fiscal years. No unique identifier exists between the systems for a faculty member, no standardization of faculty names across systems Williams, Michael ; Michael Williams M.D. , Michael A. Williams, etc… To further complicate manual marrying & analysis of these data sets different departments with in the school used the elements of the ORACLE system differently. Fortunately there was one field element in the account coding structure (TASK) was left open for departmental level interpretation. We used this to standardize our system and our data to allow us to present information to a faculty member, a division, and the Department level in a cascade manner. So for us standardizing the chart of accounts had to be a day 1 task (every pun intended) Because the manual systems and disparate reporting structure was so burdensome, the characteristics of the reports themselves did not promote good business practices. Many reports (Consolidated Financial Report and our individual faculty P&L (called FRP at UVA) were only produced yearly giving no opportunity for mid stream analysis, review, and modification of our practices. No change to intervene with a clinician who was not providing sufficient documentation and therefore having their services down coded, no opportunity for a faculty member to be made aware that she was running a deficit and needed to increase her clinical load to cover her cost, it was difficult for a PI to get real time information to realize that equipment charges had been applied to the wrong grant. To add another dimension to the problem of presenting and analyzing our business many data sets were only presented in a department aggregate, requiring the development and implementation of an often arbitrary costing splitting tool. Where our desired state is to book both revenue and expense at the faculty level whenever possible. Not to belabor the point of unproductive reporting characteristics, but even the language and descriptors of common finance elements was different between the varying systems, requiring specialized language skills to interpret reports which faculty are never going to have the time or inclination to acquire.
- Summary Slide
- Realized we didn’t want to act like a shadow system, not a system of record, chose warehousing paradigm Must be flexible to push and pull Faculty must have direct access
- Warehouse – opportunities to address, standardization of terminology, chart of accounts, design in unique identifier for faculty
- Opportunities – Self Service - allow the faculty to review their activity whenever, wherever they have the time to do so Push - when business need is a priority or where bursting and distribution saves significant admin time Alert – If the data is in the system to recognize a potential problem area, grant heading rapidly to deficit, labor not scheduled appropriately, let the system tell us not wait for someone to run a report and passively receive this message, let the system actively inform
- Access Allow all to directly access their data at anytime, with appropriate scope Scope – faculty see summary of division & department, etc… Detail – where data sets are small drill is available from summary reports to detail reports, where data sets are large reports drill into Excel where faculty and administrators can leverage a familiar set of skills in filtering, pivoting, sorting data to mine for meaningful results
- In addition to our systems methods (warehousing, modality, access) we also looked at knowledge methods. Where the systems methodologies adopted provide for data integrity and ease of access they don’t fully address the core characteristics of the value of the information provided to the individual. They don’t fully address how people interact with a data, whether people accept data, or how people interact with explicitly or implicitly communicated conclusions or actions based on an analytic tool. To address these issues we had to be particularly sensitive to issues of Transparency, Trust, and Quality. Our emphasis on these human perception factors has been pervasive throughout all phases of this project and more than any technology or methodology is responsible for the successful adoption of this toolset. So let’s look briefly at each factor and then we’d like to share some examples of how these characteristics have played out in our business.
- Transparency provides linkages, the faculty member can see their contribution to the division, the division to the department. For a department as large as Medicine working together, the left hand recognizing the right, is a continuous challenge. When reports across the missions, Education, Clinical, Research, all support the concept of being a part of the organization, the individuals start to think on multiple levels, what is the health of my activities, what is the health of my division, what is the health of my department. Without transparency reports, analytic tools tend to create an inward looking, individualistic identity. With transparency perception grows laterally, creates awareness of scope and impact on the whole.
- When our Chair sits down with his Division Chiefs to review financial performance, clinical productivity, faculty promotion & tenure, all involved know that they are working off the same data set, they no longer need to argue over who’s data is “right”, not the discussion can move to the “Whys’” and “How to Improves’”
- Compared to the strategic impact of Transparency and Trust, Quality of data may seem like a lesser tactical gain. Another way to look at this may be that in a department the size of DOM you may have 2 set of eyes at the department level, 2 set of eyes at the division level, reviewing individual data points which make up expenses on a grant or clinical production. But when you have all faculty reviewing data at regularly defined intervals within the year (quarterly for some reports, monthly for others, on demand for others) you now have hundreds of set of eyes looking for what’s right (did my clinic revenue post this month) and what’s wrong (why is that confocal microscope on my grant, that should be charged to the Center). In some ways improvements in Quality are byproduct of Transparency, Trust and Access, but it’s a HUGE tactical win each and every year. It’s a gift that keeps giving.
- At this point lets move on from Characteristics of the system and start looking at how it drives our business. Just a warning this is a byproduct that’s very similar to the old adage of “be careful what you ask for you might get it”. When you start to go down the road of transparency you also have to be ready to respond to increased quantity and increased quality of the questions that your faculty will ask. First the faculty challenge the data (I know I saw 100 patients last month the data only says I saw 88, the data is wrong). Plan to spend some time walking several faculty from the beginning to the end through the system. After a few times they will begin to trust the system. But then they challenge other peoples parts in the system. Our reimbursement rates are two low, we need to contract better. The billing staff down codes my services, they need to stop. Then finally comes acceptance that this is a tool that can help them manage their destiny and they begin to find solutions to help themselves. With clinical billing we have seen an increase in request for coders to work on the floors with physicians, we have seen docs add clinic sessions when as year end nears they haven’t gotten as close as they need to be to targets, encounter forms that used to get lost for months on end are suddenly making it to our door step with a much higher degree of certainty. We are also seeing changes in how we work together. Doctors are seeing opportunities to change process and are bringing their thoughts forward.
- Case – Faculty running a deficit – Faculty Story SOM requires all faculty to at least cover their own expenses as defined through the FRP (P&L) Reporting requirement is yearly not allowing for midstream corrections By moving to quarterly and supplying Chief and faculty access to the same report the faculty will self-elect to take corrective action and as you can see this physician has self managed his efforts to move from the red to the black.
- Case – Opportunity for an Intervention: Top Down Comparison of Peers, Allow Division Chief or Section Head to view trends in coding, side by side, of peer group and to compare to division average which makes for a defacto norm, Variances come right to the forefront, Allows opportunities for further analysis Leads to training opportunities Physicians highlighted in red have a very similar practice, both practice in the same location, share the same patient population, have the same payor mix. Division Chief can easily spot an opportunity for further analysis As you can see one of our highest volume faculty members well out of the divisional averages. Division Chief and Coding educators have met with this physician to review to see if issue is coding, documentation or both. Result was faculty member was scared to over code. Upon reviewing the data he understood and is now much more comforable with coding higher. Outcome is that upon review of coding practices with the second physician and a coding analyst the physician is comfortable that their documentation supports a level 5 and that they are within their peer group for coding practices Follow-up, Chief needs to review this graph for the next two quarters to see if intervention actually led to the agreed upon change in coding practices What is the count different, level 4 vs. level 5 $34 math works out to an opportunity cost of approximately $4255 for consults for one physician , from 12% of business at level 5 to division average 47% , documentation supports that he had been underbilling
- Now that we’ve reviewed how transparency drives a business need let’s look at a sample case for how Trust drives a business scenario.
- Several examples of faculty using the system to increase the quality of the data in the system have been worked through in the past year: Faculty gets 1 st quarter FRP, seriously in the red, drilled into expenses, found that they received a new grant and no labor had been scheduled on it effectively not showing revenue from grant for the faculty member, upon pointing this out labor was scheduled and additional revenue balanced FRP Faculty X, two weeks rotation on inpatient consult service, no ability in system of record to track consults, physician tracks this locally and can ensure that consults were captured and billed for? TRUST – back a few, physicians complaining that they were not receiving expense reports in a timely fashion, lab between 30 & 60 days, gave them the ability to pull this information wheneverfrom wherever they want on a daily basis. Number of grant accounts which go into deficit decreases.
- Quality, in the previous cases we talked about examples of Quality defined as the ability to take corrective action, now I’d like to show you an example of Quality driving performance. Here we’re not talking about correcting a data point, or taking corrective action for the next fiscal year, but driving clinical performance to meet performance based benchmarks.
- I’d like to take a moment to review what the material we’ve covered so far and now hand off the presentation to Russ Dinsmore to review the breadth and depth of our data, reports and analytics
- One stop shop, unexpected number of data sources available to add to our warehouse Abstracts network rules, VPNs, multiple passwords down to one set of access parameters for our faculty
- Russ