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Data Quality

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Data Quality Tips and Tricks Wendy Funk Kennell and Associates wfunk_at_kennellinc.com Objectives List several important MHS initiatives that rely upon good MTF data ... – PowerPoint PPT presentation

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Title: Data Quality


1
Data Quality
  • Tips and Tricks
  • Wendy Funk
  • Kennell and Associates
  • wfunk_at_kennellinc.com

2
Objectives
  • List several important MHS initiatives that rely
    upon good MTF data
  • Identify the major MTF-level data products
  • Identify common MHS Data Problems
  • 4. Utilize M2 Standard Reports to analyze DQ
    issues

3
Transformation of the MHS into a data-driven
enterprise!
Then Rudimentary funding Closed
organization Production-focused
Now Productivity Population Health PPS
Business Plans Balanced Scorecard MCS Contracts /
TFL
4
Data-Based Clinical Initiatives
5
Data-Based Clinical Initiatives
  • Disease Management Initiatives
  • Asthma and Congestive Heart Failure
  • Identification of high-risk patients using SIDR,
    SADR and Claims data
  • Pop-Health Portal
  • Preparation of action lists for providers or
    primary care managers
  • Uses SIDR, SADR, Lab, Rad, PDTS and Claims
  • HEDIS measurement, other clinical work

6
Data-Based Clinical Initiatives
  • Pharmacy Utilization Review
  • Pharmacy Data Transaction Service (PDTS) does
    real-time UR for MHS eligibles
  • Online since 2001
  • (MTF Rx, Retail, TMOP, Paper Claims)
  • Significant achievement for the MHS!

Good coding person identification
7
Data-Based Funding Initiatives
8
Data-Based Funding
  • Prospective Payment System
  • OM budgets service level
  • Built-up from Business Plans with adjustments
    later (HA later in course!)
  • Based on workload from SIDR and SADR
  • Uses private sector pricing - does not rely on
    MTF costs

Coding on SIDR SADR are important!
9
Data-Based Funding
  • Prospective Payment System
  • Inpatient Earning are based on days for mental
    health, and RWPs for all other care
  • Ambulatory earnings are based on RVUs and
    provider specialty code
  • Pay attention to procedure and diagnosis codes,
    provider specialty
  • PPS Policy continues to evolve.

10
Inpatient PPS Earnings Example
MTFs code the SIDR SADR
HA Applies PPS Rates
MDR adds RVUs and RWPs
11
Data-Based Funding
  • GWOT Funding
  • Additional funding on top of DHP to cover new
    benefits for guard/reserve
  • NDAA 2004 extended period of coverage for
    GWOT-activated members families
  • Early eligibility, screening period and extended
    transitional assistance
  • Significant increase in eligible population

12
November 2004
New Way
Extra TAMP 2-4 months
Early Elg 60 days
Screen
Mobilization Period
Routine TAMP
Old Way
Mobilization Period
Routine TAMP
Lengthened period of eligibility!!!
13
Growth in Guard and Reserve Population
14
Watch it Grow!
  • Includes all eligibles sponsored by
    guard/reserve including sponsors

15
Data-Based Funding
  • GWOT Guard/Reserve
  • The DHP earns money from the GWOT fund based on
    SIDR, SADR, PDTS, and claims data
  • Direct care costs are measured using Patient
    Level Cost Allocation (PLCA) costing methodology
  • GWOT Guard/Reserve data in M2

16
Data-Based Funding
  • TRICARE Reserve Select
  • Allows GWOT activated guard/reserve to purchase
    eligiblity after completion of TAMP.
  • Same access priority as ADFM, but no Prime.
  • Must agree to continued service and must pay
    premiums
  • Funding using same basic process as NDAA 2004
    benefits

17
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18
Data-Based Funding
  • TRICARE for Life
  • Separate fund provides for to care for Non-AD
    / ADFM Medicare eligibles
  • Medicare Eligible Retiree Health Care Fund
    (MERHCF)
  • MTF (earnings) based on SIDR, SADR, PDTS.
  • Medicare Eligibility from DEERS (from CMS)
  • More from Mr. Moss later in course

19
SIDR and SADR Full Costs for Medicare Eligibles
20
Other Funding
  • Third Party Collections
  • CMAC for outpatient and ancillaries
  • DRG based billing for inpatient
  • Billing based on CHCS or AHLTA coding
  • Venture Capital MISSY
  • Extra funding available through TMA for CHAMPUS
    Recapture
  • Models require MTF SIDR, SADR and EASIV.

21
External Business Data
22
Data-Based Contracts
  • T-Next TRICARE Managed Care Support Contracts
  • 3 U.S. At-Risk contracts
  • Enrollment Processing and PCM Assignment
  • Claims Payment
  • Managed Care Much More!
  • Ongoing provision by TMA of SIDR, SADR, PDTS,
    Claims and DEERS data

23
Data-Based Contracts
  • TRICARE Global Remote, TRICARE Overseas Prime,
    TRICARE for Life
  • Claims
  • TRICARE Retail Pharmacy
  • Claims PDTS
  • TRICARE Mail Order Pharmacy
  • Claims PDTS

24
Data-Based Contracts
  • TRICARE Dual Eligible Fiscal Intermediary
    Contract (MERHCF)
  • Claims
  • Designated Provider
  • Managed Care (Health Care)
  • Enrollment
  • Capitated with Risk Adjustment

25
Focus on Data Quality
26
Data Quality and the MHS
  • TRICARE Senior Prime
  • Very poor audits
  • DoD Financial Statement Problems
  • Poor data quality cited
  • Data problems cited repeatedly with MCS Contract
    disputes

Significant focus on DQ at TMA and Services.
27
Data Quality and the MHS
  • Data Quality Management Control
  • Data Quality Managers
  • Data Quality Course
  • Data Quality IPT (Functional)
  • Commanders statements and review lists
  • Data Quality Standard Reports for M2

28
Data Quality and the MHS
  • Redesign of IM/IT Process
  • Functional responsibility for business rules
  • Requirements vetted through IM (Services, HA/TMA,
    DEERS, Others)
  • Requirements documented
  • Significant re-engineering of data feeds
  • Reduce burden on the source systems
  • Process it once, ship it out where needed!

29
Inpatient Data Record Flow 10/98
30
Inpatient Data Record Flow 4/99
31
Inpatient Data Record Flow Today
Data Mart
M
T
F
C
H
C
Data Mart
S
Simplicity.
32
Basic Information Systems
33
Types of Systems
  • MHS is a complex business
  • Deliver healthcare
  • Process Claims
  • Managed Care
  • Complex data needs multiple ways to view the
    business
  • More than 9 million eligibles terrabytes of data

34
Types of Systems
Type Purpose Periodicity Quality Example
Transactional Run the business Real-Time No time to "clean" CHCS
Data Warehouse Store, process Batch Fix and standardize MDR
Data Mart Use the data Batch Receives data from warehouse M2
35
Types of Systems
Real-Time
Periodic Updates
Transactional
Warehouse
Data Mart
36
Types of Systems
  • Quality
  • Real time systems are harder to fix
  • Must often stop the real-time mission to correct
    known errors
  • Usually too big a price to pay for a business

Cleaning is usually designed into warehouse
functions
37
Types of Systems
  • Using the data
  • Transactional systems are not generally designed
    for analysis purposes
  • Data Warehouses are generally used by skilled
    programmers with significant data expertise
  • Data Marts are designed for analytical purposes
    generally, intended to be easy to use

38
Types of Systems
  • MHS operates a complex set of systems to meet
    different business requirements
  • New systems are generally built with routine
    systems models (transactional, warehouse, mart)
  • Older systems arent that way!

39
Types of Systems
  • MHS Data Repository
  • MHS Business Data Warehouse
  • Receives data from transactional systems and
    other data marts
  • Processes, cleans, archives
  • Limited access
  • MDR provides data to most other corporate
    business systems
  • Services and External Entities as well

40
Types of Systems
  • The M2
  • Data Mart
  • Contains a subset of MDR data
  • Contains many data files from MTFs
  • Significant functional involvement in development
    and maintenance
  • 1100 users at all levels in the MHS
  • Ad-hoc querying or Corporate Reports

41
Types of Systems
  • The M2
  • M2 contains a family of corporate reports
    designed for data quality enhancements
  • Reports are written to resemble DQ metrics
    wherever possible
  • Additional reports about important data problems
    are also included
  • Report documentation is provided in your handouts

42
Types of Systems
  • The M2
  • Most DQ reports contain data for all MTFs
  • Some have prompted filters (you tell M2 your DMIS
    ID and hit run)
  • Reports will be updated as data files are updated
  • Can also be modified and/or updated by the M2
    user
  • Examples use the reports!
  • Help Desk info provided in previous presentation

43
  • Remainder of Presentation
  • Description of systems
  • Output data files
  • DQ Issues or Considerations
  • Use of M2 Corporate Reports to aid in DQ
    Management at the MTF

44
  • The MTF Data Environment

45
MTF Data Environment
  • Many systems at each MTF
  • Service specific systems
  • TMA Systems
  • Service Systems provide data to some TMA Systems
  • Personnel
  • Financial

46
MTF Data World!
  • Composite Health Care System (CHCS)
  • Primary operational system supporting MTFs
  • Hospital Management / Administration
  • Clinical Coding
  • Communicates with DEERS, other MTF-level
    systems
  • 100 separate systems with no common database
  • Extremely important to MTF operations

47
CHCS
  • Data captured as a part of doing business

Appointing Registration Admitting Billing
(Inpat) Ordering Ancillaries Utilization
Review Workload Capture Etc
Real time data store about health care delivery,
revenues, providers, patients, clinics and wards,
etc
LOCAL DATA ONLY!
48
MTF Data World!
  • Composite Health Care System (CHCS)
  • Legacy Status
  • Much of the functionality of CHCS is being
    built in other systems
  • Enrollment Processing, Primary Care Manager
    Assignments now done with DEERS Online Enrollment
    System (DOES)
  • Deployment of AHLTA is underway to replace the
    ambulatory data module and enhance clinical data
  • Referral, Appointing underway

49
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50
CHCS is the local Hub
Financial
CHCS
Pharmacy
DEERS
AHLTA
Billing
51
CHCS Files and Tables
  • CHCS contains many tables and files (i.e.
    patient, appointment, enrollment, etc)
  • Users can query CHCS, but it isnt easy!
  • CHCS is not generally available centrally
  • CHCS databases only contain records for the
    local area.
  • CHCS provides many standardized extracts to
    external systems

52
CHCS Data Quality
  • Several CHCS extracts are important to the DQ
    program
  • Important to care for data in CHCS
  • MTF will run smoother!
  • All other systems that receive CHCS data will
    benefit
  • CHCS and Data Quality

53
CHCS Configuration Management
  • Configuration Management
  • Version control
  • Applies to software and code sets
  • Avoid problems by ensuring that you are running
    the correct versions
  • If not, problems can occur!

54
CHCS and Data Quality
  • Software Maintenance Updates
  • Changes in CHCS can affect all systems that
    receive data from it
  • Software testing assumes users have most recent
    versions operating
  • Sites with older software can get surprised
    with interface problems

55
Symptoms of CM Problems
  • Whole types of information missing from a
    record
  • Enrollment data
  • Provider data
  • Patient data
  • May suggest an interface problem
  • Check with affected systems administrators

56
Symptoms of CM Problems
  • Large numbers of rejections of data being sent
    from one system to another
  • If one systems receives a code from another
    that it isnt expecting, it may reject records
  • Some systems allow hand-jamming of data when
    this happens!
  • Check with S.A.

57
Avoiding CM Problems
  • Follow Service guidance for updates to software
    and tables
  • Plan for releases of new software coordinate
    among all systems affected
  • Document procedures
  • Monitor implementation
  • Use available resources (Help Desk, Service POCs,
    Peers, Interface Control Documents)

58
CHCS and Data Quality
  • Provider Tables
  • Pseudo provider IDs (anyprov, pttech, erdoc, etc)
  • Duplicate providers
  • 910 series providers (identify a clinic, but not
    the provider
  • PCM Tables

59
CHCS and Data Quality
  • Duplicate Records in Patient Registry
  • Records will be very similar, but not exactly
    the same
  • Will cause improper exchange of data between
    systems, etc..
  • CHCS has utilities to clean up duplicate
    records
  • Plan to run routinely. Monitor. Record.

60
CHCS Data Products in the MDR
Name Description Acronym
Standard Inpatient Data Record Inpatient Hospital Records SIDR
Standard Ambulatory Data Records Outpatient visit, t-con or inpatient rounds records SADR
Appointment Appointment records for outpatient visits None!
Ancillary Lab and Rad and Rx Procedure records None!
Worldwide Workload Report Summary workload data WWR
HL-7 also provided to EI/DS, but not in MDR due
to quality concerns
61
Standard Inpatient Data Record
  • Records about hospital stays
  • MTF care (generally)
  • Created from data collected during the stay, and
    from existing files/tables in CHCS
  • Forwarded by MTFs to Service and TMA
  • Processed in MHS Data Repository and sent to M2
    for use.
  • Very important data file. Focus of several DQ
    Checklist Items

62
Standard Inpatient Data Record
  • Information on the SIDR
  • Patient Identifier and Demographics
  • Sponsor Information
  • Diagnosis and Procedure Codes
  • Admission Disposition Dates, LOS
  • Encoder/Grouper DRG
  • Enrollment Information from DEERS check at time
    of admission
  • Administrative data, etc

63
Standard Inpatient Data Record
  • MDR Processing of SIDR
  • Person identification standardization
  • Application of DEERS attributes (including
    application of retroactive changes) GWOT data
  • DRG Grouping
  • Weighting and Costing
  • Encoder/Grouper DRG
  • Additional field derivations
  • Application of update records
  • Preparation of data for M2

64
Standard Inpatient Data Record
  • Important Uses
  • Disease Management, Case Management
  • Prospective Payment System and Business Plans
  • Balanced Scorecard
  • Medicare Eligible Retiree Healthcare Fund
  • Guard/Reserve GWOT Funding
  • Venture Capital, Resource Sharing
  • Etc..

65
Important Data
Key Data Elements Why
Patient ID DEERS App, Disease Case Mgmt, MERHCF, GWOT, PPS, Balanced Score Card, Billing
Patient Category Code Assignment of Beneficiary Category, Billing
Diagnosis Codes Procedure Codes DRG assignment, RWPs, identification of records for certain conditions or procedures, billing
Admission and Discharge Dates Length of stay, RWPs, billing
Work Centers Application of Costs, MERHCF, GWOT
66
Standard Inpatient Data Record
  • Data Issues
  • Completeness or Timeliness completed records
    due 30 days after disposition
  • IMC Checklist Item
  • Standard Report available comparing SIDRs
    reported for each MTF to Worldwide Workload
    Dispositions
  • Should be 100 except for most recent months
  • Check M2 data status table for timing to
    interpret properly

67
Compliance and Timeliness Report
  • tma.rm.dq.fyxx.dcip.rept.comp
  • Updated once per month
  • Within a few days of M2 update
  • Can be updated by users also

MTF Attributes FY FM SIDR Dispositions
WWR Dispositions Complete
68
Inpatient Reporting Compliance 30 Day Standard
69
Use Report to Identify Holes
70
30 Day Reporting Compliance?
These probably should look like the others!
71
Clinical Coding
  • Records in M2 are available at detailed level
  • One record per stay
  • Record identifiers are shared with CHCS
  • Tmt DMISID Patient Register Number
  • PRN is called Record ID in M2
  • Allows MTF staff to find records that need fixing!

72
Ungroupable DRG Report Examples
  • One sign of a poorly coded record (usually) is an
    ungroupable DRG! (469 470)
  • Ungroupable DRGs are significant because they are
    not counted for most purposes!

MTF Attributes FY FM Patient Register Number
Bed Days Estimated Full Cost
73
After logging into M2 Users go to the path
File Retrieve from Corporate Documents
74
Box pops up with all reports. Move cursor to
report of interest and click retrieve
Select tma.rm.dq.fy05.dcip.ungroupable.drg
75
Includes all MTFs. To limit to your MTF, use
SLICE AND DICE The L taking a nap!
76
Slice and Dice Panel Rearrange Sort
Filter Totals Etc Etc..
77
Rearrange Data to summarize by fiscal year, limit
to one DMISID
78
After selecting one DMISID you see a filter on
the data element. Note the calculator which will
give a grand total.
79
This MTF had an estimated 116K in ungroupable
DRGs. This care earns nothing under PPS, TRICARE
for Life or GWOT Funds (This is one record where
the coder didnt list the weight of the
baby!) Drill down to find the bad cases!
80
  • Back to slice and dice
  • Add record ID into the report
  • This is one case!
  • The record ID is the CHCS Patient Registry
    Number.
  • Can be used to pull up THIS case in CHCS.
  • If you fix and resubmit, it will show up in the
    data!

81
Standard Inpatient Data Record
  • Looking at Length of Stay
  • Query your MTF
  • Admission and Disposition Date
  • DRG
  • Not a standard report, but not hard
  • If you limit to long lengths of stay, you can
    easily find errors

82
Probably mistyped either the admission or the
disposition date. This is a delivery with a
length of stay greater than one year. Record ID
is the PRN
83
Standard Inpatient Data Record
  • Whats the RWP Impact on coding like that?
  • First, whats an RWP?
  • Basis of earnings for PPS, GWOT, TFL, etc
  • Very important
  • Depends on DRG and Length of Stay
  • Primarily!
  • DRG Weight Relative hospital costliness of that
    DRG compared with all others

84
Standard Inpatient Data Record
  • RWP DRG Weight if length of stay is normal
  • Otherwise /- credit depending on length of
    stay
  • In this case
  • RWP should likely have been 0.55
  • RWP was 98.38

85
Standard Ambulatory Data Record
  • Not really an ambulatory record!
  • Ambulatory Care (Office, ER, Same Day Surgery)
  • Inpatient Rounds
  • Telephone Consults
  • MHS does not generally capture inpatient
    procedure provider records, unlike private sector
  • (Hospital record is captured, but not a separate
    provider piece causes problems with studying
    productivity and billing)
  • Very important data file. Focus of several DQ
    Checklist Items

86
Standard Ambulatory Data Record
  • Information on the SADR
  • Patient Identifier and Demographics
  • Sponsor Information
  • Diagnosis and CPT Procedure Codes, Clinic
  • Service Date
  • Type of Appt
  • Enrollment Information from DEERS check at time
    of admission
  • Administrative data, etc
  • Provider Specialty Code

87
Standard Ambulatory Data Record
  • Major Pieces of Information not on the SADR
  • Units of Service and Modifiers associated with
    each procedure code
  • Collected in ADM or AHLTA
  • Not yet forwarded in the SADR
  • Leads to a system-wide understatement of workload
  • Change request underway
  • All SADRs since OIB began will be reharvested

88
Standard Ambulatory Data Record
  • MDR Processing of SADR
  • Due to lack of completeness of SADRs, appointment
    records are used to enhance the SADR data file.
  • For each kept appointment, if a SADR exists, it
    is used.
  • If a SADR is not collected, then the appointment
    record is used to create an inferred SADR.
  • When/if a SADR finally shows up, the inferred
    SADR is removed and the real SADR kept.

89
Standard Ambulatory Data Record
  • MDR Processing of SADR
  • Match to appointment records, include SADRs and
    kept appointments w/o a SADR
  • Application of DEERS attributes (including
    application of retroactive changes) GWOT data
  • Weighting and Costing including estimation on
    inferred records.
  • Person identification standardization
  • Additional field derivations
  • Application of update records
  • Preparation of data for M2

90
Standard Ambulatory Data Record
  • Important Uses
  • Disease Management, Case Management
  • Prospective Payment System and Business Plans
  • Balanced Scorecard
  • Medicare Eligible Retiree Healthcare Fund
  • Guard/Reserve GWOT Funding
  • Venture Capital, Resource Sharing
  • Etc..

91
Important Data
Key Data Elements Why
Patient ID DEERS App, Disease Case Mgmt, MERHCF, GWOT, PPS, Balanced Score Card, Billing
Patient Category Code Assignment of Beneficiary Category, Billing
Diagnosis Codes Procedure Codes APG/APC assignment, RVUs, identification of records for certain conditions or procedures, billing
Provider ID Specialty RVU assignment, provider productivity, practice patterns, etc
Work Centers Application of Costs, MERHCF, GWOT
92
Standard Ambulatory Data Record
  • Data Issues
  • Completeness or Timeliness completed records
    w/in 3 days for non APV, 15 for APV
  • IMC Checklist Item
  • Significant issue with SADR
  • Very large numbers of historical SADRs are
    missing
  • Compliance has improved but is still an issue
  • New appointment records offer excellent
    opportunities for managing compliance!

93
Standard Ambulatory Data Record
  • Compliance
  • IMC Checklist Item
  • Two methods for monitoring compliance
  • Two Corporate Reports available for measuring
    compliance
  • SADRWWR Comparison
  • SADRAppointment Comparison

94
Compliance and Timeliness Report
  • tma.rm.dq.fy05.dcop.rep.comp.wwr
  • Updated once per month
  • Within a few days of M2 WWR update
  • Can be updated by users also

MTF Attributes FY FM SADR Encounters
WWR Count Visits Ratio of SADR WWR
95
Standard Ambulatory Data Record
  • Compliance
  • Imprecise match
  • WWR visits are a subset of SADR encounters
  • WWR includes only those visits that the local MTF
    determines count
  • SADR includes all encounters
  • Metric should be greater than 100

96
All Encounters N 31 Million
Count Only N 29 Million
2 Million Non-Count Ambulatory Visits!
97
Greater than 100 complete --- Is this good or
bad?
Built from corporate report in M2
98
Compliance and Timeliness Report
  • tma.rm.dq.fy05.dcop.rep.comp.appt
  • Updated once per month
  • Within a few days of M2 Appointment update
  • Can be updated by users also

MTF Attributes FY FM Captured SADRs
Inferred SADRs of SADRs captured
99
Standard Ambulatory Data Record
  • Compliance
  • Record level match
  • Report is limited to ambulatory records, t-cons
    and hearing conservation clinic.
  • More precise methodology
  • Action report for drill to appointment ID,
    provider or clinic level
  • Be cautious with very recent data check data
    status table in M2 for timing info

100
Slice and Dice
101
Include year, month and percent complete to chart
out compliance metric
102
Less than 100 when compared with appointments
103
Swap out percent complete with number of
encounters, to see how many are missing
104
Number of incomplete SADRS from FY05
105
Back to slice and dice to see which clinics are
missing the most SADRs
106
Clinics with the most missing SADRS Two MEPRS
Codes make up half of whats missing!
Clinic Missing SADRs of Total Missing
Primary Care 248,664 24
Family Practice 232,662 23
Pediatrics 66,930 6
All Other Clinics 484,458 47
Total Missing (05) 1,032,714 100
107
Compliance Action Report
  • tma.rm.dq.fy05.dcop.rep.comp.actionrep
  • Updated once per month
  • Within a few days of M2 Appointment update
  • Can be updated by users also

MTF FY FM Provider ID Clinic
Appointment ID Missing Encounters Lost PPS
Earnings
108
Standard Ambulatory Data Record
  • Action Report -- Compliance
  • Record ID is appointment ID same as in CHCS,
    ADM, AHLTA, etc..
  • Provider ID MEPRS Code are from appointment
    record
  • Number of encounter is actual missing records
  • PPS Earnings estimated by applying PPS rates to
    estimated RVUs for the case (based on avg. RVUs
    in that clinic, SDS or not, and type of provider)

109
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110
Will result in a list of missing records. Record
ID is the Appointment IEN. Can be used to
retrieve records in the source system. Sorted by
descending PPS earnings low hanging fruit.
111
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112
Use provider ID to determine impact of lost
earnings under PPS.
113
Sorted list of estimated financial impact of
missing SADRs. By provider ID
114
Include Record ID to assist in locating record
that needs completing.
115
List of providers and their missing appointment
IDs.
116
Standard Ambulatory Data Record
  • Clinical Coding
  • Very important poor coding can have serious
    consequences
  • Coding problems have been cited repeatedly by
    auditors
  • Check for ungroupables
  • Evaluate coding with SADR in M2 can see
    diagnosis and procedure codes.

117
Ungroupable APG Report
  • tma.rm.dq.fy05.dcop.ungroupable.apg
  • Prompted report
  • You enter your DMISID and hit run!

MTF FY FM
Appointment ID Number of Encounters Full Cost
118
Review of coding practice using M2
  • Record level data allows for detailed analysis of
    coding practice
  • UBU Coding Guidelines published in TRICARE
    website
  • Clinical coding is what drives RVU assignment
  • Policy changes
  • Staffing changes
  • Impacts of missing records -- no count really
    does count. But not coded doesnt count at all!

119
How are RVUs assigned?
  • Done in the MDR
  • Match SADR to MHS Weight table
  • Will soon be in M2
  • For each procedure, assign work RVU from weight
    table unless
  • EM code on the same record as a significant
    procedure
  • Unspecified provider specialty (depends on the
    RVU field)
  • Some RVU fields use slight modifications to these
    rules.

120
Proc Code Description RVU
EM  99203 Office Visit  1.34 
1 92225  Ophthalmoscopy  0.38 
2 92015  Determination of Refraction  0.38 
3 76519  Ultrasound  0.54 
4      
Simple RVUs for this record Simple RVUs for this record Simple RVUs for this record 2.64
121
How are RVUs assigned?
  • MHS Weight Table
  • Mostly contains CMS weights
  • Modified for unique MHS reporting of pre and post
    operative visits
  • Some additions for things CMS doesnt cover
  • Units of Service is a critical missing data
    elements in RVU assignment.
  • Serves as a multiplier in RVU assignment logic.
  • PT, Mental Health, Dermatology, others

122
  • Typical MHS-coded same day surgery
  • Separate records for pre-op, post-op and surg
  • Private sector RVUs include the pre and post op
    work!
  • MHS weight table modified so that the procedure
    record only gets the weight for the procedure
    pre and post ops earn weight separately.

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Standard Ambulatory Data Record
  • Provider Information
  • Provider identifiers are only unique to each CHCS
    Host
  • Provider Table in CHCS
  • Name, specialty, HIPAA taxonomy, etc.
  • Some historic problems with names specialties
  • Important for productivity analysis, billing,
    provider profiling, etc.
  • 2 corporate reports in M2

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Unspecified Provider Specialty
  • tma.rm.dq.fy05.dcop.unspecified.provspec
  • Updated once per month
  • Within a few days of M2 Appointment update
  • Can be updated by users also

MTF Attributes FY FM MEPRS Code
w/ unspecified specialty w/o unspecified
specialty unspecified specialty
125
  • PPS announces future plans to discontinue
    crediting SADRs with unspecified provider
    specialties (910-999)
  • SAIC patch written for CHCS
  • Significant Improvements made in FY05

126
Standard Ambulatory Data Record
  • Invalid Provider IDs
  • Catch-all identifiers used in some clinics
  • ER Doc, PT tech, Card clinic, any provider, etc.
  • Usually not too difficult to find because these
    IDs generally hold a large amount of workload
  • M2 report sorts RVUs by provider. Can review the
    list to see if any obvious problems appear.

127
Invalid Provider IDs
  • tma.rm.dq.fy05.dcop.invalid.provid
  • Updated once per month
  • Within a few days of M2 Appointment update
  • Can be updated by users also

MTF Attributes FY FM Provider ID
RVUs
128
Invalid Provider IDs
  • Report is a list of workload by provider and MTF
  • Sort by descending workload
  • Are the most productive providers reasonable?
  • Are they real people?
  • You CANNOT bill for ER DOC Lost TPOCS
    billings.
  • Clean out provider table to remove these IDs as
    options.
  • Discuss with clinic/appointing staff to ensure
    access is not harmed, though.

129
  • Provider ID NUROBS
  • Almost 3 times the RVUs of any other provider at
    that MTF
  • Is this a real provider? Or perhaps an
    observation unit?

130
Other Important MTF Data
Pharmacy
MEPRS
Lab and Rad
131
Other Important MTF Data
  • MEPRS
  • Financial FTE Reporting
  • Covered later in the course
  • Lab and Rad Data
  • One record per outpatient procedure
  • FY2005
  • New data source. Only recently available.
  • More to come as data matures

132
Other Important MTF Data
  • Pharmacy Data Transaction Service (PDTS)
  • Drug Utilization Review system
  • Real-time communications between PDTS and CHCS
  • CHCS sends prescription info PDTS responds with
    DUR advice
  • Data files from PDTS contain data that originates
    in CHCS

133
  • Rx ordered at MTF in CHCS
  • Information stored in Rx file locally
  • Real time DUR Check
  • PDTS receives DUR requests from MTFs (and TMOP
    and Trrx)
  • Checks against rx history files to determine
    whether its okay to dispense
  • Responds back to Pharmacies with go or no go

Source for MEPRS
Source for MDR/M2 PDTS Data Table
134
Pharmacy and the MHS
  • Growing Demand
  • New expensive drugs
  • Aging population
  • Influx of new beneficiaries
  • Startling inflation in pharmaceutical industry
  • 2 product line in MHS
  • Extremely important management issue

135
Pharmacy Data Transaction Service
  • MTF Pharmacy data from PDTS is used for many
    important purposes
  • Medicare Accrual Fund, GWOT funding
  • PPS does not use pharmacy currently.
  • Very significant issues in cost data from CHCS on
    individual dispensing records.

136
Pharmacy Data Transaction Service
  • Pre-defined Units and Drug Codes dont always go
    together.
  • Ex. Birth control pills dispensed in a pack of
    28. Is this a unit of 1 or 28?
  • Rounding issues and bulk issues
  • Local pricing is not reliable
  • PDTS re-prices everything unless the MTF has set
    the local pricing flag to yes.

137
Most Expensive Drug Report
  • tma.rm.dq.fy05.rx.mostexp.drugs
  • Updated once per month
  • Toward the end of the month
  • Can be updated by users also

MTF Attributes NDC Name Cost
Days Supply Cost per Day
138
This MTF has its local pricing flag on. These
prices came from MTF Asthma medication is not
that expensive! Problems with pre-defined units
and NDC.
139
Pharmacy Data Transaction Service
  • Pre-defined Units and Drug Codes dont always go
    together.
  • Ex. Birth control pills dispensed in a pack of
    28. Is this a unit of 1 or 28?
  • Rounding issues and bulk issues
  • Local pricing is not reliable
  • PDTS re-prices everything unless the MTF has set
    the local pricing flag to yes.

140
Wrap Up
  • M2 is a useful part of a data quality managers
    tool-kit
  • Provides a good source for record level data
  • Uses the same record identifiers as the source
    systems, to allow things to get fixed faster
  • Contains lots of different data files from the
    MTF
  • Corporate Reports are easy to use.
  • Real time tools are still helpful and needed

141
Wrap Up
  • WISDOM Course for training
  • Need more than software training
  • Most important to understand the underlying data
  • For M2 accounts
  • 1-800-600-9332
  • Be sure to inquire about other standardized
    reports and such when other speakers present!

142
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