Business Intelligence Intelligent Business

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1 Business Intelligence Intelligent Business Cameron Cox, III, MHA, FACMPE CEO, MSOC Health

2 Learning Objectives 1. Definitions: (Big) Data, Dashboard, Analytics 2. Review effective dashboard principles 3. Understand important differences between data, analysis and presentation 4. Recognize differences in analytics 5. Review Financial Metrics, Analytics in a practice setting

3 Trending What does this graph tell us? Volume Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

4 Success! Full plane

5 What will happen in the following scenario? I am driving 80 mph in my Camaro with the windows down and sunroof open, the music blaring and my cool sunglasses on. A State Trooper has a radar gun. The radar gun is pointed directly at my Camaro. The State Trooper is also wearing cool sunglasses.

6 Nothing.I m in Montana

7 Cam s Personal Dashboard Cam's Life Cute/Sexy Smart Funny

8 Agenda What is (big) data? What is a dashboard? What is analytics? Design Principles of a dashboard Data and Analysis Design Presentation Principles of Analytics Real Time Predictive Historical Business Intelligence How to use it

9 What is (big) data?

10 Latest Buzzword

11 Who better to explain than the internet?

12 Big Data at work

13 What is a dashboard?

14 It s hard to drive without a dashboard Keep your eyes on the road but..

15 What is not a dashboard? Report Just because it s on-line or web based Just because it s real time Balanced Scorecard Tool to dive into detail Just because it has gauges and graphs

16 A dashboard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance.

17 Dashboards The Chosen Tool for Consolidating Data Simply

18 Please count the # of 7 s in this array:

19 Now count the # of 7 s:

20 This.not that

21 A Dashboard s Hierarchy of Needs Clear Presentation Formulated Analysis Large Data Set

22 Data

23 Analysis

24 Presentation

25 What is the purpose of dashboard? Mission Statement Audience Performance Measures (KPI & Metrics) What logical groupings will organize the info best? What comparisons should be made? How frequently will it be updated? What actions might be taken?

26 WATCH OUT! Potential gap ahead

27 Time understand it in your analysis. Real Time versus Time Trends Airline Pilot or ICU physician or Call Center Retail, Financial, Manufacturing Closer to real time better Understanding secular/historical trends important also

28 Trends Hour by Hour, Day by Day, Week by Week Month by Month, Quarter by Quarter Compare to prior hour, day, week, month, quarter, year Month to Date, Quarter to Date, Year to Date

29 Context/Comparisons add Perspective Historical Last period Last period 1 year ago Benchmark Goals or Budgets Relative to other providers Forecast

30 You Need Good, Unfiltered Data Available-Who did you have to toss under the bus to find this information? Reliable -Do you believe these # s? Relevant Timely-Last years data is too late. Simple, simple, SIMPLE

31 What is analytics?

32 Structured Breakdown with purpose Detailed examination of the elements Identifying the elements Separating the elements into constituent elements Measuring the elements

33 Analytic Continuum VALUE Descriptive- What happened? Diagnostic- Why did it happen? Predictive- What will happen? DIFFICULTY

34 Real Time Analytics

35 How does this work?

36 Okay how does this work in healthcare?

37 Predictive Analytics

38 How does it work?

39 How does it work in healthcare? Increase Marketing Dollars during end of season Have more open scheduling slots during end of season

40 Another example No Shows No Shows: Days from Booking Date Total # of days between Booking Date and Appt Date Double book one week follow-ups with other appointments to keep utilization high Group one week followup slot times; advertise walk in availability at same times Change booking pattern; encourage patients to selfschedule follow ups

41 Data What do we want to measure analyze present

42 Types of Data I. Volume A. Productivity (patients, encounters, days worked) B. Activities (procedures, labs, x-ray, calls) C. Hours/Shifts III. Billing & Financial A. Charge Capture & Gross Revenue B. Costs C. Collections D. Profit/Loss II. Quality & Clinical A. Clinical Quality B. Patient Satisfaction

43 Solutions (Real World Example) Customer analysis: 51% of patients are age 50 or under

44 Customer Analysis (Real World #2)

45 Customer Analysis by Location Cary location sees more Millennials than other locations. Sanford has the oldest patient population.

46 Opportunity cost Compare commercial contract proposals to other payors; is participating worth the effort?

47 Contract Value Consider all product lines dropping out means loss of Medicare Advantage patients

48 Variance Analysis Review payments to ensure payor compliance with contracted rates, identify denial trends or performance issues

49 I. Volumes Patient Encounters per day/provider/group Procedures per E&M Year to Year trends/ Seasonality Admits/Discharges By Financial Class Day of Week By CPT Code By ICD-9 (soon -10)

50 II. Quality & Clinical X-rays per ICD-10 Scripts per encounter Volume of Preventative Well Visits Vaccinations to total practice population Core Measures Nurse calls Lab Response Times Patient Education Delivery Recall rates Patient satisfaction Wait Times

51 III. Billing & Financial RVU per encounter Cost per procedure/category Code Distributions Patient Responsibility per encounter Patients by Payer Class Accounts Receivable > 90 days PQRS Capture Insurance Denials

52 Don t Let Tools Confuse You The Best Tool is Your Brain

53 Always Remember: A Dashboard is a Presentation of the Data Analytics is an interpretation of the Data Basics to not forget!!! P&L A/R Analysis Revenue Flow Financial Classification

54 Thank you for your time! Contact Cameron M. Cox, III

55 Connect with us

56 Thank You MSOC Health (866) Timber Hill Place Suite 221 Chapel Hill, NC

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