Session 12 - Introduction to Information Tools

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  • Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery June 2010October 2007
  • Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery June 2010October 2007 October 2007 Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery
  • Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery June 2010October 2007 Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery
  • Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery June 2010October 2007 Also access to appointments and services (TRICARE Online)
  • Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery June 2010October 2007 Mike: You know Dr Crawford the questions you asked, fit perfectly into the MHS Population Health Model. You asked…. Mike: Ok enough about theory. Lets look at a couple of tools the MHS supports to answer your type of questions.
  • Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery June 2010October 2007 Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery
  • Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery June 2010October 2007 Critical Decision Making for Medical Executives: Keys to Improving Healthcare Delivery
  • Session 12 - Introduction to Information Tools

    1. 1. Session 12: PerformanceImprovement Tools: Gathering theEvidence R.S. Crawford, III, MD, MBA rcrawford@usuhs.mil William Hirst, BSN, MPH, CPHQ MHirst@SouthcentralFoundation.com April 2012
    2. 2. Setting the Stage Analyst Goal with Dr Crawford • Establish a working relationship, trust and listen  What insight does he already have • Assist in decreasing his level of uncertainty  This isn’t a research study • Provide useful information for decision support • Demonstrate actionable information tools for all staff  Executives  Managers  Front-end Staff
    3. 3. Big Picture Population at Prevention Risk Recovery Incidence of Disability or Disease Case Management Level 1 Level 2 Prevalence of Level 3 Disability or Disease Level 4 Level 5 Death
    4. 4. Mean 68.13 d l e n a p m P 0 1 / t s i V R E 60 65 70 75 80 9 0 - g u A 9 0 - p e S LCL 62.4 UCL 73.9 9 0 - t c O Mean 68.190-voN 9 0 - c e D 0 1 - n a J 0 1 - b e F01-raM 0 1 - r p A01-yaM u J 0 1 - n 0 1 - l u J 0 1 - g u A 0 1 - p e S 0 1 - t c O01-voN 0 1 - c e D 1 - n a J 1 - b e F ER Visits / 1000 Pt. Empanelled1-raM 1 - r p A1-yaM u J 1 - n 1 - l u J 1 - g u A 1 - p e S 1 - t c O 75.2 77.51-voN 1 - c e D
    5. 5. % 55 60 65 70 75uA90-g90-peS LCL 60.6 UCL 67.090-tcO Mean 63.890-voNc90-eD01-naJ01-beF01-raMpA01-r01-yaM01-nuJ01-luJuA01-g01-peS01-tcO01-voNc01-eD1-naJ1-beF1-raM % ER Visits Between 0800 - 1700pA1-r1-yaM1-nuJ1-luJuA1-g1-peS1-tcO 70.31-voNc1-eD 69.8
    6. 6. c a m h A 0 1 / t s i V R E 10 15 20 25 30 35 40 4590-guA90-peS LCL 16.5 UCL 37.290-tcO Mean 26.8voN90-90-ceD01-naJ01-beF01-raM01-rpA01-yaM01-nuJ01-luJ01-guA01-peS01-tcOvoN01-01-ceD1-naJ1-beF ER Visits / 1000 Asthmatics1-raM1-rpA1-yaM1-nuJ1-luJ1-guA1-peS1-tcOvoN1- 40.21-ceD
    7. 7. Dec 11 Clinic ER Visits Total ER Visits per 1000 % of Total Empanelled Empanelled Visits Family Practice 1,844 17,500 105.37 79.31% Internal Med 97 2,500 38.80 4.17% Peds 384 10,000 38.40 16.52% Total 2,325 30,000 77.50 100.00%Dec 10 Clinic ER Visits Total ER Visits per 1000 % of Total Empanelled Empanelled Visits Family Practice 1,498 17,500 85.60 74.94% Internal Med 103 2,500 41.20 5.15% Peds 398 10,000 39.80 19.91% Total 1,999 30,000 66.63 100.00%
    8. 8. Tricare Operations Center (TOC) http://mytoc.tma.osd.mil
    9. 9. Visits with Assigned PCM(source: Tricare Operations Center) VALHALLA Family Medicine Clinic 44%
    10. 10. Provider Schedule ReportDetermine Provider Availability: # Providers with Schedules VALHALLA FMC Provider Availability 50%
    11. 11. Provider Schedule ReportClinic/Provider Specific with # of Appointments
    12. 12. Template Analysis Tool (TAT)Overall Clinic Summary Views Clinic Location Provider Sum of Count 1400 ATC Category 1200 Slot Status (blank) - (blank) (blank) - Wellness - OPEN 1000 Wellness - FROZEN Wellness - CANCELLED Wellness - BOOKED 800 Specialty - OPEN Specialty - FROZEN Specialty - CANCELLED Specialty - BOOKED 600 Routine - OPEN Routine - FROZEN Routine - CANCELLED 400 Routine - BOOKED Other - OPEN Other - FROZEN Other - CANCELLED 200 Other - BOOKED Acute - OPEN Acute - FROZEN 0 Acute - CANCELLED 0 2 1 4 1 0 2 3 4 1 0 2 5 4 1 0 2 7 4 1 0 2 9 4 0 2 1 5 1 0 2 3 5 1 0 2 5 1 0 2 7 5 1 0 2 9 5 / / / / / / / / / / 0 2 1 4 0 2 3 1 4 0 2 5 1 4 0 2 7 1 4 0 2 9 1 4 0 1 2 4 1 0 3 2 4 1 0 5 2 4 1 0 7 2 4 1 0 9 2 4 0 2 1 5 0 2 3 1 5 0 2 1 5 0 2 7 1 5 0 2 9 1 5 0 1 2 5 1 0 3 2 5 1 0 2 5 1 0 7 2 5 1 0 9 2 5 0 2 1 3 5 / / / / / / / / / / / / / / / / / / / / / Appt Date
    13. 13. 20 40 60 80 100 120 140 160 0Appt Date 1 0 2 / 4 Clinic Location 1 0 2 3 / 4 Sum of Count 1 0 2 / 4 1 0 2 5 / 4 1 0 2 6 / 4 Provider 1 0 2 9 / 4 2 0 1 / 4 0 2 1 / 4 0 2 1 / 4 0 2 3 1 / 4 0 2 6 1 / 4 0 2 7 1 / 4 0 2 8 1 / 4 0 2 9 1 / 4 1 0 2 / 4 1 0 3 2 / 4 1 0 2 / 4 1 0 5 2 / 4 1 0 6 2 / 4 1 0 7 2 / 4 Template Analysis Tool (TAT) 1 2 0 3 / 4 0 2 1 / 5 1 0 2 / 5 1 0 2 3 / 5 1 0 2 4 / 5 1 0 2 7 / 5 1 0 2 8 / 5 1 0 2 9 / 5 2 0 1 / 5 0 2 1 / 5 0 2 4 1 / 5 0 2 1 / 5 0 2 6 1 / 5 0 2 7 1 / 5 0 2 8 1 / 5 0 1 2 / 5 1 0 2 / 5 1 0 3 2 / 5 1 0 4 2 / 5 ATC Category and Slot Status Dynamic Templates 1 0 2 / 5 1 0 9 2 / 5 1 2 0 3 / 5 0 2 1 3 / 5 Slot Status ATC Category Acute - OPEN Acute - FROZEN Acute - BOOKED
    14. 14. Template Analysis Tool (TAT)Provider Specific Templates Clinic Location Provider Sum of Count 20 18 16 14 12 ATC Category Slot Status 10 Wellness - OPEN Wellness - BOOKED Routine - OPEN 8 Routine - BOOKED Acute - OPEN 6 Acute - BOOKED 4 2 0 1 0 2 4 1 0 2 3 4 1 0 2 4 1 0 2 5 4 1 0 2 6 4 1 0 2 9 4 0 2 1 5 1 0 2 5 1 0 2 3 5 1 0 2 4 5 1 0 2 7 5 1 0 2 8 5 1 0 2 9 5 / / / / / / / / / / / / / 2 0 1 4 0 2 1 4 0 2 1 4 0 2 3 1 4 0 2 6 1 4 1 0 3 2 4 1 0 2 4 1 0 5 2 4 1 0 6 2 4 1 0 7 2 4 1 2 0 3 4 2 0 1 5 0 2 1 5 0 2 4 1 5 0 2 1 5 0 1 2 5 1 0 2 5 1 0 3 2 5 1 0 4 2 5 1 0 9 2 5 1 2 0 3 5 0 2 1 3 5 / / / / / / / / / / / / / / / / / / / / / / Appt Date
    15. 15. Access Management Report VALHALLA Family Medicine No Shows 11%
    16. 16. No Show Appointments by Day CY 2011 # No-Show Appointments by Day (1 Jun 06 - 31 May 07) Family Med n=5720 (11% of 52,000 appts) 5720 100% 91% 90% 5005 81% 80% 4290 70% 66% 3575 60% Number 2860 50% 2117 40% 2145 37% 1659 30% 1430 858 20% 715 572 514 10% 0 0% Monday Friday Thursday Wednesday Tuesday
    17. 17. No Shows by Day and Hr CY 2011 Monday No-Shows Family Med (1 June 06 - 31 May 07) n=2117 100% 98% 2000 96% 93% 89% 90% 84% 80% 78% 1500 70% 70% 1270 60% 60% Number 50% 1000 40% 30% 500 20% 212 169 127 105 10% 84 64 44 42 0 0% 0800-0859 0900-0959 1700-1759 1300-1359 1500-1559 1400-1459 1000-1059 1600-1659 1100-1159 Time of Day
    18. 18. No Shows by Day and Hr CY 2011 Friday No-Shows Family Med (1 June 06 - 31 May 07) n=1659 100% 98% 96% 93% 1500 90% 90% 86% 80% 80% 70% 70% 1000 60% Number 50% 664 40% 40% 500 500 30% 20% 165 100 10% 66 50 49 34 31 0 0% 1700-1759 0800-0859 0900-0959 1300-1359 1400-1459 1000-1059 1100-1159 1600-1659 1500-1559 Time of Day
    19. 19. Tricare Operations Center (TOC)Many More Reports • 3rd Next Available – under beta testing • Appointment Utilization • Access to Care Reports • Enrollment & Population Reports • Booked Management Report • Length of Stay
    20. 20. Valhalla Findings • Provider availability ~ 50% last 12 mo • % of Appt with PCM is low (44%) • % of 3rd Next Available Acute Appointments meeting Access Standards (24hrs) is low in Family Medicine • Decrease in team continuity • Low appointment availability on peak days • Deployment in 6 months • No-show rates of 11% • Training during peak hours
    21. 21. Potential Items Affecting Capacity • Provider availability / schedules / templates • Team experience and continuity • Provider specialties & manpower issues • No-show rates • Leave, TDY, Holiday’s • Additional duty, provider call • Procedures • Facility layout & Support services • Technology • Service level agreements with referrals • Don’t rely on historic utilization patterns
    22. 22. MHS Population Health Model
    23. 23. Population Questions • Who are my patients? • What are their preventive service needs? • What conditions do they have? • Who are my high utilizers that may need case management? • How well am I doing in the management of their care? • HEDIS • Primary Care Medical Home • How do I forecast & manage the demand for services?
    24. 24. Population Identification https://carepoint.afms.mil
    25. 25. MHSPHP Data Sources DEERS M2 CHCS AdHocs Direct Care Purchased Care/Network PDTS Inpt and Outpt Inpt and Outpt TRICARE Mammography Enrollment Pap Smears Clinical Chemistry Enrollment MHS Population Health Portal
    26. 26. Population Identification
    27. 27. Population Identification
    28. 28. Population Identification
    29. 29. MHSPHP Action List
    30. 30. MHSPHP Patient Detail •Last 3 B/P’s (currently from Clinical Data Repository) •Last 6 Labs (note labs in network have no values)
    31. 31. MHSPHP Local Exclusions •Exclusions automatically expire after 1 year •Exclusions follow pt (new facility can validate or delete) •30 day flag before they expire •Different icon if exclusion was at other facility •Apply to Medical Home and Action Lists, not HEDIS
    32. 32. MHSPHP Local Entered Notes •Notes are NOT MEDICAL RECORD •Stay forever unless deleted by user •System flags not when pt changes facility, new facility can validate it or delete it •Default is current list, can choose more than 1
    33. 33. MHSPHP HEDIS & Medical Home •Score = Completed/Total as percentage •Score as compared to All HEDIS® measured health plans Green=Score is greater than 90th percentile Yellow= Score is between 50th and 90th percentile Red= score less than 50th percentile •Medical Home Completed/Medical Home Total •No benchmark for comparing medical home scores •Can be same, higher or even lower than HEDIS® score
    34. 34. MHSPHP HEDIS & Medical Home
    35. 35. Putting Carepoint to Work: Demand Forecasting
    36. 36. Demand Forecasting • Daily Demand Forecasting: • Team huddles with integrated care team • Same reasons as inpatient report • Planning, Coordination, Safety • Demand Forecasting and Planning: • Deployment coming up in 6 months in which 6 of the 20 providers will be deployed. • If we decided to contract out Well Women Exams to include pap smears. How many would we need to contract out for? • School physical demand what can we expect? Do we need to adjust schedules?
    37. 37. Population Identification
    38. 38. Demand Forecasting and Planning • Women 18 and older = 9231 9231/ @ least one Pap q3 yrs = ~3077/yr • Women 40 and older 2632/ @ least one Mammogram q 2 yrs = ~1316/yr • Children 5 years old ready to start school 256 School Physicals • 1 Jan 11 – 31 Dec 11 ~ 52,000 FMC Appts
    39. 39. Putting Carepoint to Work: Demand Management
    40. 40. High Utilizer Identification FICTITIOUS DATA
    41. 41. Evaluation:How did we do?
    42. 42. d l e n a p m P 0 1 / t s i V R E 60 65 70 75 8090-guA90-peS MEAN 68.1390-tcO LCL 62.4 UCL 73.9 Mean 68.190-voN90-ceD 0 1 - n a J 0 1 - b e F01-raM 0 1 - r p A01-yaM 0 1 - n u J 0 1 - l u J01-guA01-peS 0 1 - t c O01-voN01-ceD 1 - n a J1-beF1-raM 1 - r p A ER Visits / 1000 Pt. Empanelled1-yaM 1 - n u J 1 - l u J1-guA1-peS1-tcO 75.21-voN 77.51-ceD Mean 65.3 2 1 - n a J21-beF 64.021-raM
    43. 43. % 55 60 65 70 7590-guA90-peS LCL 60.690-tcO UCL 67.0 Mean 63.890-voN90-ceD01-naJ01-beF01-raM01-rpA01-yaM01-nuJ01-luJ01-guA01-peS01-tcO01-voN01-ceD1-naJ1-beF1-raM1-rpA1-yaM % ER Visits Between 0800 - 17001-nuJ1-luJ1-guA1-peS1-tcO 70.31-voN1-ceD Mean 62.7 69.821-naJ21-beF 64.121-raM
    44. 44. c a m h A 0 1 / t s i V R E 10 15 20 25 30 35 40 4590-guA90-peS UCL 37.2 LCL 16.590-tcO Mean 26.890-voN90-ceD01-naJ01-beF01-raM01-rpA01-yaM01-nuJ01-luJ01-guA01-peS01-tcO01-voN01-ceD1-naJ1-beF1-raM ER Visits / 1000 Asthmatics1-rpA1-yaM1-nuJ1-luJ1-guA1-peS1-tcO1-voN 40.2 Mean 24.11-ceD21-naJ21-beF 22.821-raM
    45. 45. Mar 12 Clinic ER Visits Total Empanelled ER Visits per 1000 % of Total Visits Empanelled Family Practice 1,450 17,500 82.86 75.40% Internal Med 100 2,500 40.00 5.20% Peds 373 10,000 37.30 19.40% Total 1,923 30,000 64.10 100.00%Dec 11 Clinic ER Visits Total Empanelled ER Visits per 1000 % of Total Visits Empanelled Family Practice 1,844 17,500 105.37 79.31% Internal Med 97 2,500 38.80 4.17% Peds 384 10,000 38.40 16.52% Total 2,325 30,000 77.50 100.00%Dec 10 Clinic ER Visits Total Empanelled ER Visits per 1000 % of Total Visits Empanelled Family Practice 1,498 17,500 85.60 74.94% Internal Med 103 2,500 41.20 5.15% Peds 398 10,000 39.80 19.91% Total 1,999 30,000 66.63 100.00%
    46. 46. Patient Appointments with PCM(Goal 70%) Valhalla Medical Center (Jan – Mar 2012) Source: Tricare Operations Center MEPRS Clinic % with PCM Family Practice Clinic A (BGAB) 70.1 Family Practice Clinic B (BGAC) 67.5 Family Practice Clinic C (BGAD) 68.7
    47. 47. Access to Care 3rd Next Available(Acute) - Goal 80%) Valhalla Medical Center (Jan – Mar 2012) Source: Tricare Operations Center MEPRS Clinic % @ Std Family Practice Clinic A (BGAB) 83.3 Family Practice Clinic B (BGAC) 87.2 Family Practice Clinic C (BGAD) 91.2
    48. 48. Questions ?

    ×