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MHS Data Sources - TRICARE

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					MHS Data Sources –
 Techniques for
     Analysis
                      Objectives
• Describe CHCS
• Describe the major central repositories that include MTF data
• Briefly describe the M2
• Identify common data quality problems
• Describe how M2 Standard Reports can be used to manage
  data quality
• Use M2 DQ Standard Reports
   – Only for attendees of hands-on session
                            The Data’s No Good!




At least I                                        And the number of
didn’t use
it! Why      Who cares if the data are            discharges we can
fix it?
             bad! We just used the old            recapture is……..
                                                                      Since the
             dartboard method!                                        data is
                                                                      not good
    Composite Health Care System
• Much longer briefing later in course on CHCS
• High level overview in this session!
• What is CHCS?
   – Primary operational system used by MTFs
   – Used for day-to-day activities within the MTF
   – Appointing, scheduling, registration, ordering of tests,
     referrals, etc..
   – Importance of CHCS cannot be stressed enough!
     Composite Health Care System

•   CHCS is the starting point for nearly all MTF data
•   Point of original capture
•   Real-time data
•   Much of the data in CHCS is captured simply because
    someone is doing their job
    – For example, when provider orders a prescription in CHCS;
      a record of that is kept in the CHCS pharmacy file
   Composite Health Care System
• CHCS has no central repository
  – Built a very long time ago
  – 100+ separate systems!
  – Significantly hampers usefulness of local data
  – Richness of CHCS data is a definite plus, but must
    remember that data are only local
  – Great for production type studies; not enough for
    person based work
                           Composite Healthcare
                           System (CHCS) Access


NCA                            San Diego
                                                  Co Springs


            Tidewater


                        No connectivity between
                        100+ separate systems!
                            Landstuhl                Etc….
Pendleton
Example: MTFs on Eisenhower CHCS Host


  DMISID   Name                Local CHCS
   0047    Eisenhower         queries only
                            retrieve data for
   0237    McPherson        care provided at
   1230    Camp Shelby        these MTFs!

   1550    TMC-4 Stockade
   7197    TMC Connelly
   7239    TMC Southcom
Example: Inpatient Data Available at EAMC
               from CHCS

  Most of the           Proportion of Bed Days for

 days of care           Eisenhow er Host Enrollees


for EAMC area
 enrollees are
 not visible in
     CHCS                               39%
                                                     Local MTFs
                                                     Other MTFs
                  53%
                                                     Purchased Care




                                  8%
   Composite Health Care System
Data Availability
• Several options for using CHCS Data:
   –   MUMPS Queries
   –   “Fileman” Queries
   –   CACHE
   –   ICDB
• Varies by MTF what can be done
   – Larger MTFs tend to have more options
• Data also available in other central systems
              CHCS Data Products
Name                    Description                    Acronym
Standard Inpatient      Inpatient Hospital Records       SIDR
Data Record
Appointment             Appointment records for         None!
                        outpatient visits
Referral                Referrals for specialty care

Standard Ambulatory     Outpatient visit, t-con or      SADR
Data Records            inpatient rounds records
Ancillary Lab and Rad   Procedure records               None!
and Rx
Worldwide Workload      Summary workload data           WWR
Report
                     CHCS & AHLTA
• AHLTA new capture system
  – Intended to be an electronic health record
  – Replaces (sort of) CHCS Ambulatory Data Module
  – Unlike ADM, AHLTA built to support provider’s activities (i.e.
    note taking, reviewing test results, etc)
  – Overly complex architecture; system problems are common
     • AHLTA writes data to CHCS, which is the used to create a SADR
       (Called writeback)
     • Still not used in all clinics
FLOW OF SADR                            MDR

SADR file
contains ADM &
AHLTA
information      SADR                               M2
        CCE



 CHCS/ADM

                        Writeback



                                              CDR
  ADM & AHLTA
  are used to           APPT
  capture                           AHLTA
  ambulatory
  data
                         Use of AHLTA for Outpatient Care
                                                                                                                                                                                                                                        10% of regular
                                                                                          % of SADRs Captured Using AHLTA                                                                                                               visits still not
100%
                                                                                                                                                                                                                                        captured in AHLTA
90%
80%
70%
60%                                                                                                                                                                                                                                                       APV
50%                                                                                                                                                                                                                                                       ER
40%                                                                                                                                                                                                                                                       Other OP

30%
20%
10%
 0%
                Nov-06




                                                                                                                            Nov-07




                                                                                                                                                                                                                                        Nov-08
                                                                                        Jul-07




                                                                                                                                                                                                    Jul-08
                                  Jan-07




                                                                               Jun-07




                                                                                                                                              Jan-08




                                                                                                                                                                                           Jun-08
                         Dec-06


                                           Feb-07
                                                    Mar-07
                                                             Apr-07




                                                                                                 Aug-07
                                                                                                          Sep-07




                                                                                                                                     Dec-07


                                                                                                                                                       Feb-08
                                                                                                                                                                Mar-08
                                                                                                                                                                         Apr-08




                                                                                                                                                                                                             Aug-08
                                                                                                                                                                                                                      Sep-08




                                                                                                                                                                                                                                                 Dec-08
       Oct-06




                                                                      May-07




                                                                                                                   Oct-07




                                                                                                                                                                                  May-08




                                                                                                                                                                                                                               Oct-08
                                                                                         Very little usage in ER and Same
                                                                                         Day Surgery Centers – more for
                                                                                         office based care
                 Clinical Data Mart
• Clinical Data Mart
  – Enables viewing of some of the more important data
    from the Clinical Data Repository (AHLTA)
  – Structured database accessible through Web version of
    Business Objects
  – Primary source of data is CDR (and CHCS indirectly)
  – Also receives nightly file from DEERS
  – Role-based access; no worldwide access available
    currently
  – Not complete enough for many purposes
  – (Not focus of DQMC for that reason)
       Expense Accounting System (EAS)
                 Repository

• EAS is the tri-Service financial system used at MTFs
• EAS is used to create MEPRS data
   – Full-Time Equivalent Staff (generally via DMHRS)
   – Workload (via CHCS)
   – Expense Information (via Service $$ system)
• MEPRS codes
   – Used in all MTF systems
• Data Availability:
   – EAS Repository
   – MDR/M2
       Pharmacy Data Transaction Service
                 Repository
• Online Drug Utilization Review System
• Used by MTFs, Mail Order Contractor and Retail Contractor
• Excellent source of information about prescription drug usage
• Data Availability:
   – Through PDTS Business Objects System
   – MDR/M2
• Reported automatically, when MTF does DUR check
             MHS Data Repository

• “Home-grown” business data warehouse
   – Developed outside normal IT process



• MDR receives and processes data from a wide variety of
  sources
   –   Data feed management
   –   File Batching
   –   Data Processing
   –   File Storage & Archiving
   –   Preparation of Extracts for Data Marts
                        Basic Data Flow
Data sent to MDR 24/7


MEPRS                 MDR Feed                    MDR Processing, File
                    Node                           Storage & Limited
                                  Batches               Access
CHCS                             Weekly
                                 Monthly

DEERS


Claims                                                                   M2


Others                                     1500+ users access in
                                                   M2
         Preparation of MDR Files
• MDR is the “workhorse” – where most of the processing
  of data occurs. Generally includes:
   –   Archiving and Storage
   –   Person Identification enhancement
   –   Application of DEERS attributes
   –   Addition of market concepts (i.e. catchment)
   –   Addition of DMISID attributes (i.e. enrollment MTF Service, etc)
   –   Grouping (DRG, APC, etc)
   –   Addition of costs and weights (RVUs, RWPs)
   –   And much, much more………
• Other systems tend to “catch, store and show”
• Cleanest, most comprehensive source of data
               The MHS Mart
• The “M2”:
  – Very popular data mart
  – Contains a subset of MDR data
  – Many data files from MTFs + other data, too!
  – Significant functional involvement in development
    and maintenance
  – 1500+ users at all levels in the MHS
  – Ad-hoc querying or “Standard Reports”
        Systems to use for Data Quality
• No one system will answer all your questions!
• Local systems:
   – Best for real time or near real time management
   – “How are we doing?”

• Corporate systems:
   – MDR/M2 used for most major initiatives and by local MTFs
   – Important that data be right there!
   – M2 Standard Reports are designed to assist with
     monitoring MTF DQ
   – “How did we do?”
       Systems to Use for DQ Mgmt

• M2 Reports:
  –   Many reports available
  –   Most resemble or are exactly the required DQMC reports
  –   Some on emerging DQ issues
  –   Easy to use
  –   Need only basic M2 knowledge
  –   Must know your MTF DMISID to use MTF Level Reports
  –   Will demonstrate throughout!
  –   Report documentation is in your notebooks
      Data Quality Monitoring and
            Improvement
• MTF Data to Review in the context of data
  quality attributes:
  – Standard Inpatient Data Records
  – Standard Ambulatory Data Records
  – Pharmacy Data Transaction Service
  – Expense Assignment System (MEPRS)
  – MTF Lab and Rad
      Attributes of Data Quality
• Completeness
  – Do I get all of the data that I need?
• Timeliness
  – Is the data I need there when I need it?
• Accuracy
  – Is the data correct, or at least “correct enough”?
Completeness
        Common Data Quality Items
• Why do you need complete data?

 800
                          Monthly Discharges

 700


 600


 500


 400


 300


 200


 100


   0
       Oct-07   Nov-07   Dec-07   Jan-08   Feb-08   Mar-08   Apr-08   May-08   Jun-08   Jul-08   Aug-08
               Common Data Quality Items
 • Why do you need complete data?
                                                                FY w/error                     FY w/o error

                                                                 7,387                          7,727
                       Monthly Discharges
800

700

600
                                                                                                   340 discharge
500
                                                                                                   records lost!
400

300

200

100

  0
      Oct-07   Nov-07 Dec-07   Jan-08   Feb-08 Mar-08 Apr-08 May-08 Jun-08   Jul-08   Aug-08
          Why does it matter?
• Missing component of health history for
  beneficiaries
• Less budget at Service level
  – Less funds for MTFs
• Appearance of quality issues
• Underestimation of productivity and efficiency
• Improper business planning; poor business
  care analysis
    Common Data Quality Items
• Why can data be incomplete & what can you
  do about it?
  – Simple lack of data capture
  – Incomplete or erroneous transmission of data
  – Improper processing & handling
               Lack of Data Capture
• Some data are captured during the business
  process
• Often sent off automatically            Daily
                                          End of Day
      – Example: Appointment file                  Processing



                                    Periodic
                                    standardized
                                    data feeds


Real-Time           Real Time
Patient Call        Using CHCS
                    to book appt
           Lack of Data Capture
• Data captured during the business process
  – CHCS tables:
     • Updated in real time while MTF staff does their jobs
     • Not generally used beyond local level
     • Lack of central warehouse makes it difficult
  – CHCS automated extracts:
     • Appointment File
     • Outpatient Lab, Rad and Rx Files
     • Referral File
          Lack of Data Capture
• Some data are captured because a policy or
  guidance requires it
  – Unified Biostatistical Utility (UBU) distributes
    health care coding policy
  – Example: SIDR - Inpatient Stays
  – Example: SADR - Completed outpatient visits and
    inpatient rounds
         Lack of Data Capture
• Some data are captured because a policy or
  guidance requires it
  – More comprehensive set of health care reporting
    in private sector; not reported = not paid!
  – MHS decides whether “juice worth squeeze” since
    budget not claim based
  – Examples of data not required:

            Inpatient Surgical CPT Records

            Ambulance Records
          Lack of Data Capture
• Some data are captured because a policy or
  guidance requires it
  – Policy gaps cause some problems analytically
  – “Lack of Capture”: When policies are not
    followed – makes analysis harder!
  – Incentives + Supporting Policy = Best availability
    of data
  – Recent improvements
         Capture Requirements
• Worldwide Workload Report
  – Earliest CHCS product with information about MTF
    care delivery
  – Monthly summary workload:
     • Visits, Days, Dispositions
     • Year, Month, MTF, MEPRS Code, Patient Category
  – Historical significance:
     • Major determinant of payments to contractors in early
       TRICARE contracts (not today!)
                Example WWR Data
MTF    CY/CM      MEPRS     Bencat    Count    Adm   Disp   Bed Days
                  Code                Visits
0001   200801      BAA        DA        66      0     0        0
0001   200801      BAA        DR       222      0     0        0
0029   200801      AAA        RET       0      90    97       339
0029   200801      AAA        ACT       0      56    252      47
0029   200801      BDA        DA       5286     0     0        0
0029   200801      BDA        DR       542      0     0        0


   B MEPRS Code (Outpatient): Visits
   A MEPRS Code (Inpatient): Adm, Disp and
   Days
        Capture Requirements
• Worldwide Workload Report
  – WWR is required by all Services for all of their
    active MTFs
  – Reports include one month of data
  – When WWR file is received, it is usually complete
  – Changes occur at times; but not common
  – Often called “gold standard”
        Capture Requirements
• Worldwide Workload Report
  – Used to measure completeness of other MTF
    workload data sources
  – Reporting of WWR part of DQMC program
  – Sent to Service Agencies and then onto MDR
                 PASBA          MDR



      AFMSSA


                 NMIC
         Capture Requirements
• Standard Inpatient Data Record
  – One coded record per inpatient stay
  – Roughly 250,000 per year
  – Contains rich detailed data on each stay
  – Can identify patient and providers; includes
    diagnosis, treatment and other administrative
    data
• Significance:
  – Primary source for most inpatient data needs.
        Some Sample Data from SIDR
MTF    Reg Num   Pat ID    Adm Date     Disch Date   Dx 1     DRG
0125   6470071    Pat #1   11/01/2008   11/03/2008    V3000     391
0117   6221377    Pat #2   10/16/2008   10/17/2008    49121     088
0117   6221596    Pat #2   10/21/2008   10/24/2008     2273     300




•Many more data elements available
on SIDR – hundreds of them
•MTF DMISID + Register Number
(PRN) is the way to identify a unique
record
         Capture Requirements
• Standard Inpatient Data Record
  – MTF Requirement since late 1980s
  – All inpatient stays must be coded
  – Stable data feed
  – Sent to MHS Data Repository / M2 and derivative
    systems
  – No inpatient data sent to Clinical Data Repository
    or CDM
        Capture Requirements
• Standard Inpatient Data Record
  – Completion of a SIDR requires more effort than
    completion of WWR
  – Much more detailed report
  – Completeness is not usually a problem, though
  – Well established reporting process
CHCS
                 Picture of SIDR flow
                                • SIDRs sent monthly
CHCS                            from local CHCS hosts
                        MDR     • Assembled into one file
                                and processed in MDR
                                • Sent to M2
          CHCS



 CHCS

                                  M2

        CHCS, etc
       MDR Processing of SIDR
• MDR processing includes:
  – Applying updates and adding new records
  – Running through DRG Grouper
  – Adding RWPs
  – Adding standardized patient information
  – Adding costs, PPS data
  – Many, many more things
• MDR enhancements are significant
  – Makes the MDR/M2 SIDR files a very useful choice
      Completeness of SIDR Data
• Required reporting element for DQMC
• Measurement:
  – Number of SIDRs / # dispositions reported in WWR
• Expressed as % Complete
• Can easily be reviewed using M2 Corporate
  Document
  – tma.rm.dq.dcip.rept.comp.rep
Step-by-Step
Retrieving a Standard Report
•Select the report you want and click retrieve!
•Use report guide in handout
•Report is already run!
•Contains monthly comparisons of
inpatient workload data
•All you have to do is look at it!
•Service Summary and MTF Detail
                    O
                     ct




                              0.00%
                                      20.00%
                                               40.00%
                                                            60.00%
                                                                         80.00%
                                                                                  100.00%
                                                                                            120.00%
                       -0
                    De 4
                      c-
                        0
                    Fe 4
                      b-
                         0
                    Ap 5
                      r- 0
                    Ju 5
                      n-
                         0
                    Au 5
                      g-
                         0
                    O 5
                     ct
                       -0
                    De 5
                      c-
                        0
                    Fe 5
                      b-
                         0




No obvious holes!
                    Ap 6
                      r- 0
                    Ju 6
                      n-
                    Au 0 6
                      g-
                         0
                    O 6
                     ct
                       -0
                    De 6
                      c-
                        0
                    Fe 6
                      b-
                         0
                    Ap 7
                      r- 0
                    Ju 7
                      n-
                         0
                                                                                                      SIDR % Complete by Service




                    Au 7
                      g-
                         0
                    O 7
                     ct
                       -0
                    De 7
                      c-
                        0
                    Fe 7
                      b-
                         0
                    Ap 8
                      r- 0
                    Ju 8
                      n-
                         0
                    Au 8
                      g-
                         0
                    O 8
                     ct
                       -0
                          8
                                                            F
                                                                     A


                                                        N
          Capture Requirements
• Standard Ambulatory Data Record
   – Record of (some) provider work
   – One coded record per outpatient visit, telephone
     consult , and inpatient round
   – No requirement for inpatient surgery SADRs
   – Roughly 30 million per year
   – Can identify patient and providers; includes diagnosis,
     treatment and other administrative data
• Significance:
   – Primary source for most ambulatory data needs.
 Some Sample Data Fields from SADR
MTF    Appt ID No   Pat ID   Appt Date    Diag 1    E&M      MEPRS
                                                    code     Code
0117    33858389    Pat #1   10/31/2008     56400    99283     BIA
0075     7106236    Pat #2   10/09/2008      7242    99441    BAA


       •Many more data elements available on
       SADR – hundreds of them
       •MTF DMISID + Appt ID Number (IEN) is
       the way to identify a unique record
        Capture Requirements
• Standard Ambulatory Data Record
  – MTF Requirement since mid 1990s
  – Significant issues with completeness
  – Reporting compliance is part of the issue (more
    later on system issues)
  – Sent to MHS Data Repository / M2 and derivative
    systems
  – SADR is not sent to Clinical Data Repository but
    some similar data is; more later
        Capture Requirements
• Standard Ambulatory Data Record
  – Completion of a SADR is entirely separate from
    WWR
  – Much more detailed report
  – Much more complex process
  – Two different data collection systems (CHCS and
    AHLTA)
       MDR Processing of SADR
• Fundamental part of MDR processing:
  – Combination of Kept Appointment File and SADR
  – Appointment file is automatically captured; where
    SADR requires additional effort at the MTF
  – Should be a SADR for each kept appointment
  – If there is an appointment record but no SADR,
    called an “inferred SADR”
  Matching SADRs to Appointment Records

• When ‘processing’ in        SADR #   APPT #
  MDR: Compare appt and
  SADR; record by record.       1        1
• Missing a SADR for Appt #
                                2        2
  4.
• #4 will be in the MDR         3        3
  database as an ‘inferred
  SADR’.                                 4

                                5        5

                                6        6

                                7        7
                 Final MDR Data Set

    Compliance
#     Status     Prov     Patient     Clinic      E&M

1      Real      JONR     MARY         BAA       99214

2      Real      JONR      JOE         BAA       99213

3      Real      JONR      JANE        BAA       99213

4    Inferred    JONR      NAN         BAA         N/A
                                      Appt # 4 has no E&M because no
5      Real      JONR       AL         BAA       99213
                                      SADR has been collected. This is
                                      an appointment-based record
6      Real      JONR      ROB         BAA       99214

7      Real      JONR     SARA         BAA       99499
         MDR Processing of SADR
• In addition to combining with appt data, MDR
  processing includes:
  –   Applying updates and adding new records
  –   Combining with appointment file to include records w
  –   Running through APG/APC Grouper
  –   Adding RVUs
  –   Adding standardized patient information
  –   Adding costs, PPS data
  –   Many, many more things
• MDR enhancements are significant
  – Makes the MDR/M2 SADR files a very useful choice
    Completeness of SADR Data
• Two common ways to measure
  – Official way is to compare WWR to SADRs
  – Method developed when appointment data was
    unavailable
  – Not a precise match
  – WWR includes only those encounters deemed
    “count”; SADR includes all appoinments
         Concept of a Count Visit
• Hash mark counting
   – Early days of MHS
   – No systems to use to report detailed data
   – Count visit used to discern between ‘real medical care’ and
     ‘not’
• Inconsistent use
   – Not recommended for analytic purposes across MTFs
   – Used by many systems
• Non-count visits DO earn RVUs
   – SADRs are expected for both count and non-count visits!
                All Encounters:
                N= 32 Million

“Count Only
N= 29 Million




                     3.5 Million
                     Non-Count Visits
                      worth almost 1
                      Million RVUs!
                     Count Visits
Care delivered where primary provider is a general
  duty nurse – FY08

 MTF Svc    Count      Non-Count     Total      % Count

 Army       197,324     150,701      348,025     57%

 AF         92,172      243,254      335,426     27%

 Navy       172,102     156,667      328,769     52%
 Total      461,598     550,622     1,012,220    46%
  Completeness of SADR Data with WWR
              Benchmark
• Required reporting element for DQMC
• Measurement:
  – Number of SADRs in B Clinics (and FBN) / # count visits
    reported in WWR
• Expressed as % Complete
• Should be greater than 100%
• Can easily be reviewed using M2 Corporate
  Document
  – tma.rm.dq.fy**.rep.comp.wwr.rep
                   Currently, each report has only one year.
                   Multi-year report under construction
     Completeness of SADR Data with
        Appointment Benchmark
                           • Combination of kept appointments
                               and SADR makes precise
                               measurement of missing SADRs
                 Final MDR Data Set
                               possible.
    Compliance
                           • Perfect compliance would be 100%
#     Status     Prov      • No Clinic           E&M
                          Patient “Inferred” Records

1      Real      JONR     MARY      BAA      99214

2      Real      JONR     JOE       BAA      99213

3      Real      JONR     JANE      BAA      99213

4    Inferred    JONR     NAN       BAA       N/A

5      Real      JONR      AL       BAA      99213
     Completeness of SADR Data with
        Appointment Benchmark
• Not a required reporting element for DQMC
• Based on the ‘by record’ match
• Gives a better answer than official metric
• And is actionable since you can identify missing records
• Measurement:
   – Number of reported SADRs in B Clinics (and FBN) / # total
     kept appointments in same clinics
• Expressed as % Complete
• Can easily be reviewed using M2 Corporate Document
   – Report Name:
     tma.rm.dq.fy**.dcop.rep.comp.apptbench.rep
Completed Outpatient Appointments with
              No SADRs
                                                                                                       Writeback
                                                 Missing SADRS
                                                                                                       Meltdown!

    120000
    100000

     80000                                                                                                         A
     60000                                                                                                         F
     40000                                                                                                         N

     20000
        0
             Oct-98

                      Oct-99

                               Oct-00

                                        Oct-01

                                                 Oct-02

                                                          Oct-03

                                                                   Oct-04

                                                                            Oct-05

                                                                                     Oct-06

                                                                                              Oct-07

                                                                                                       Oct-08
Major
Improvements
in Compliance
SADR Completeness Action Report
• Provides record level report of missing SADRs
• Includes MTF and Appointment Identifier so that MTF
  may retrieve information about missing record and fix
  the problem!
• Also includes estimate of lost PPS $$ due to lack of
  SADR
• Prompted filter report:
   – Data not already run; user is prompted to enter MTF
     DMISID; then report runs
• Can easily be reviewed using M2 Corporate Document
   – Report Name
After entering your DMISID:
Kept Appointments with No SADR
Use Slice and Dice to
determine which clinics
are losing the most PPS
$$$ due to lack of
completeness of SADR
Surgical Clinics, Primary Care, ER
Back to slice and dice to look at
lost earnings by provider
•“By Provider” list of missed earnings.
•Identifiers covered up
•EACH ROW IS A PROVIDER!…….
•The first provider listed needs to submit 300K
worth of SADRs!
Back to slice and dice to look at
which SADRs are missing.
“Record IDs” are the
appointment IENs of the
missing SADRs
Use to find the missing
records in ADM or AHLTA
                           MEPRS
• Expense Assignment System
  –   Financial Accounting
  –   Tri-Service System
  –   Expenses
  –   Workload
  –   Full Time Equivalent Staff Info
• Summary Data Only
  – Too aggregated for most business questions
  – Extremely valuable as a basis for more sophisticated
    costing methodologies
  – Only tri-Service source for FTE data
                        MEPRS Data Flow

                                        EAS IV Repository
                                             (Full MEPRS dataset)
  Workload
   (CHCS)

                                                                           MDR
 Financial Data                                                      (Large MEPRS dataset)
    (STANFINS,
    STARS/FL,
                        EAS-Internet
      BASF)

                                                                 (Monthly
                          (Nightly/Monthly                      Processing)
Personnel Data
(DMHRS,UCAPERS,             Processing)
   SPMS, EAS)


                  Monthly MEPRS data due
                  45 days after month end
                                                               M2
                                                               (Smaller MEPRS dataset)
           MEPRS Completeness
• MEPRS Policy requires submission of “MEPRS Package” from
  all fixed MTFs
• Preparation of MEPRS extract requires significant effort
   – MEPRS Manager at each MTF
• MEPRS reporting is/has been problematic recently
   – EAS-I
   – DMHRSi
• FY08 is still incomplete
   – Many very large MTFs having problems with new
     personnel system
          Example of Some MEPRS Data
    MTF     MEPRS    FY/FM    Avail Clin   Bed Days    Total      Lab
            Code                FTES                  Expense   Expense
    0024    AAAA    200901      2.89         120      295,190    4,233
    0109    BAAA    200901      6.88          0       1085948   133,779



•    MTF & MEPRS code identifies the reporting unit
•    Staff info from DMHRS (usually)
•    Workload from CHCS (usually)
•    Expenses from Service System + MEPRS Algorithms
      – Entire section on MEPRS later!
          MEPRS Completeness Issue
      •Some of the largest MTFs in the MHS have not
      completed FY08
      • Causes problems when trying to do system-wide work
      • Chart below is an attempt to track a new MEPRS code

                Available Case Manager FTEs in WTUs       Drop in reporting
350
                                                          due to
300                                                       incomplete
250                                                       MEPRS data
200                                                   A
                                                      F
150                                                   N

100

50

 0
De 0 6




De 0 7




      08
Fe 7




 Ju 7




Fe 8




 Ju 8
M 7

Ap 7




M 8

Ap 8
Au 7




Au 8
Ja 6




Se 7

O 7




Ja 7




Se 08

O 8
M 07




M 08
Ju 7




Ju 8
No 6




No 7




No 8
      0
     -0




      0
     -0
    l-0




    l-0
      0

      0




      0
      0




      0




      0




      0
     -0




     -0
      0




      0
    -0




    -0




    -0
   v-




   v-




   v-
   n-




   n-




   n-




   n-
   b-




   b-
   c-




   g-

   p-




   c-




   g-
   p-
   r-




   r-
  ar




  ar
 ay




 ay
  ct




  ct




  ct
O
Timeliness

Timeliness
       Common Data Quality Items
• Why do you need timely data?
            Reported Dispositions   •Steady trend
 400
                                    until recent
 350
                                    timeframes
 300
                                    •Includes
 250
                                    FY08 and part
 200
                                    of FY09
 150

 100

  50

   0
      Common Data Quality Items
 • Why do you need timely data?
                                   Annual Recap
           Reported Dispositions
400                                   FY           Disp
350                                  2006         4,302
300                                  2007         4,251
250                                  2008         3,862
200

150
                                    Missing data
100
                                    causes an
 50
                                    artificial year
  0
                                    to year trend
           Why does it matter?
• Completeness & Timeliness have the same
  impacts
  – Missing component of health history for
    beneficiaries
  – Less budget at Service level
     • Less funds for MTFs
  – Appearance of quality issues
  – Underestimation of productivity and efficiency
  – Improper business planning; poor business care
    analysis
          Timeliness Standards

Data Type      Standard/Note
SIDR           w/in 30 days of discharge
SADR           3 days for routine; 15 for APV
WWR            by 10th of month
MEPRS          45 days after month ends
Lab/Rad         Auto send
PDTS            Auto send
Appointment     Auto Send
                 Timeliness
• Timeliness Standards are best monitored
  locally
  – CHCS, ADM and AHLTA speakers to present
• Batch processing in MDR/M2 makes it an
  insufficient tool for monitoring timeliness
• Very useful for completeness, though
Accuracy
                   Accuracy
• Completeness and Timeliness:
  – Analysts always prefer complete data
  – When not available, common to use
    historical/available data to estimate missing data
• Inaccurate data is much more difficult to
  work with
  – Can lead to much more damage!
  – Can’t always apply “workarounds”
                         Accuracy
• Private sector health care data is reported as part of
  a payment process
   – Completeness: Not claimed means not paid!
   – Timeliness: Delays in submission mean delays in payment
   – Accuracy:
      • Data elements used to determine payments can get providers in
        trouble if they are wrong!
      • Code checking / bundling software used
                         Direct Care
• Direct Care SIDR and SADR:
• We don’t have the same stick as private sector!
   – MHS uses policies for completeness and timeliness.
   – Coding and Compliance Editor (CCE) for code edits
   – (No bundling software at all)
• Coding audits required as part of DQMC
   – Sample size often too small to spot problems
   – Sometimes, external auditors hired
   – Since data used for billing (Third Party Collections), bad coding could
     cause MTF problems, also
        Direct Care SIDR and SADR
• M2 is a wonderful tool for analyzing accuracy of data

• Contains local record identifiers to enable ACTION!

• Standard Reports for accuracy:
   – Ungroupable DRGs & APGS
   – Unlisted Provider Specialty Code
   – Potential Pharmacy Table Errors
   – Potential Provider ID Errors

• Ad-hoc possibilities are limitless
           Ungroupable DRG Report

• DRG Grouping software:
   – Assumes coding rules are followed
   – Allows for all known or potentially possible combinations of diagnosis
     and procedure codes

• Ungroupable DRG:
   – Rules are not followed in some way; or
   – Diagnosis and Procedures simply don’t make sense together

• Ungroupable DRGs receive no PPS funds for the Service
   – Significant improvement since PPS!
         M2 Ungroupable DRG Report
• Currently built with regular DRGs
   – tma.rm.dq.dcip.ungroupable.drg

• MS DRG report to be added soon
• Includes:
   –   MTF Identifier & Information
   –   Date of Care
   –   Patient Register Number (to find in CHCS)
   –   Bed Days
   –   Estimated Cost of Care
Choose Corporate Documents
Pick report name of
interest and hit
“Retrieve”
• Report is already filled with data
• Updated each month when SIDR
Table is updated
•“Record ID” is the patient
registry number from CHCS.
•Bring to coders to fix!
                     Fixing SIDRs


• The reasons a DRG is “ungroupable” are not always
  clear. Some things to look at:
   – Diagnosis and procedure codes may be unrelated
   – Information needed by the grouper may be missing or
     miscoded
   – Age and dates of service may be inconsistent.

   – Check the medical record for coding accuracy.
   – Check the date of birth, admission and discharge dates
M2 ad-hoc users can get
details associated with   Include data elements of
problem records           interest from SIDR
Limit to Tx DMISID and
Record ID with
ungroupable DRGs
Admitted and Discharged prior to BIRTH!
            Unlisted Provider Specialty on SADR
 • Provider Specialty Code:
    – Important to understand who delivered care
 • “Catch all” specialty codes vs real codes
 • No specialty code = No PPS Earnings!
 • M2 Report Name:
    tma.rm.dq.fy**.dcop.unspecified.provspec

Who delivered        Code     Description
the care when        001      Family Practice Physician
specialty is 923?     923     Family Practice Clinic
                      603     Pediatric Nurse Practitioner
                      520     Independent Duty Corpsman
   Improvement in Use of Specific
      Provider Specialty Code
               Encounters with Unspecified Provider Specialty Code

140,000                                                  Power of Budget
                                                         Incentives!
120,000

100,000

 80,000                                                                     A
                                                                            F
 60,000                                                                     N

 40,000

 20,000

     0
          Oct- Nov- Dec- Jan- Feb- Mar- Apr- May- Jun-   Jul-   Aug- Sep-
           04   04   04   05   05   05   05   05   05     05     05   05
            Invalid Provider IDs
• Provider ID is supposed to represent the person
  delivering care
• Some MTFs use “catch-all” IDs
• Easier to appoint, but makes it impossible to
  determine who did what!
• Report Name: tma.rm.dq.fy**.dcop.invalid.provid
  – Prompted filter report
                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.
• Are the daily totals reasonable?
• Clean out provider table to remove these IDs as options.
   – Discuss with clinic/appointing staff to ensure access is not harmed,
     though.
•Daily Encounters by one
provider at one MTF.
•Hundreds of daily encounters
each day!
•Mostly physicals for AD
•~7 times the RVUs of other
providers at this MTF
                             PDTS Data
• MTF Pharmacy Data is heavily used!
   – Pharmacy is the #2 product line in the MHS
   – Data comes from Pharmacy Data Transaction Service
   – Weekly extract to the MDR

Sample Pharmacy Data from an MTF
 MTF    Product Name    Issue Date    Days    Quantity   Person ID   Ordering
                                     Supply                           Clinic
 0089   Oxycodone      10/01/2008     30        10          #1         BIA
 0089     Nexium       10/01/2008     30        60          #2         FCC
                   PDTS Data Flow

CHCS Hosts
                                               PDTS Web Interface

 Retail
                   PDTS   Warehouse

                                                       MDR
Mail Order
                                      Weekly




                                                                    M2
    Paper Claims
          PDTS Data Quality Issues
• Direct Care Pharmacy Data has some problems
  – Not fixable by MTF
     • CHCS National Drug Code may not be right
     • Will hold the proper drug, but may indicate incorrect vendor, etc
• CHCS Pharmacy Table:
  – Improper definitions of default units of measure (e.g. birth
    control pills; 28 pills or 1 pack?)
  – Pricing is wrong (rounding problems, drug code problem
    and unit dose problem!)
  – (MDR does not CHCS prices – too poor of quality)
       Most Expensive Drug Report
•   When improper units of measure are in CHCS
    pharmacy tables, data is wrong
•   Easy to identify by looking at most and least
    expensive drugs and doing a reasonability test
•   Report Name:
    tma.rm.dq.fy**.pdtsrx.directcare.rxcost.rep
    – Prompted filter report
Advair at $660 per script!
Asthma medication is not that expensive!
Problems with pre-defined units and NDC.
                     Ad-Hoc Use of M2
• Robust capabilities of M2 Ad-Hoc (Full Client) Business Object Tool:
    –   Allows ad-hoc queries – you decide the question!
    –   Allows combination of data files
    –   Can write one query to use as a “filter” in another
    –   Can create new variables
    –   Can link variables
    –   Can bring in external data files and use with M2 data (i.e. link, filter,
        combine, etc)
• Very powerful and easy to use
• What follows is the use of M2 for ad-hoc analysis and identification
  of data issues.
Accuracy Problem
Used SIDR Table
Very bad data – 367 day stay for a routine c-
section!
Probably mistyped either the admission or the
disposition date.


Record ID is the PRN
    Standard Inpatient Data Record

• LOS errors affect RWP assignment, usually.
• RWP is the DRG Relative Weight
   – Unless patient stays “too long” or “too short”
   – Outliers defined as length of stay outside two standard deviations
     from the mean.
• For outlier cases, RWP is adjusted based on how different
  actual LOS is from mean.
• In this case:
   – RWP should likely have been: 0.55
   – RWP was:           98.38
                                                            O
                                                             ct




                                                                         5,000
                                                                                 10,000
                                                                                          15,000
                                                                                                   20,000
                                                                                                            25,000
                                                                                                                     30,000
                                                                                                                              35,000




                                                                     0
                                                               -0
                                                            De 4
                                                              c-
                                                                0
                                                            Fe 4
                                                              b-
                                                                 0
                                                            Ap 5
                                                              r- 0
                                                            Ju 5
                                                              n-
                                                                 0
                                                            Au 5
                                                              g-
                                                                 0
                                                            O 5




                                    •Used Radiology Table
                                                             ct




  (completeness)
                                                               -0
                                                            De 5
                                                              c-
                                                                0
                                                            Fe 5
                                                              b-
                                                                 0
                                                            Ap 6
                                                              r- 0
                                                            Ju 6
                                                              n-
                                                                 0
                                                            Au 6
                                                              g-




• Big Holes in the middle of FY07
                                                                 0
                                                            O 6
                                                             ct
                                                               -0
                                                            De 6
                                                              c-
                                                                0
                                                                                                                                       Radiology Records from one MTF




                                                            Fe 6
                                                              b-
                                                                 0
                                                            Ap 7
                                                              r- 0
                                                            Ju 7
                                                              n-
                                                                 0
                                                            Au 7
                                                              g-
                                                                 0
                                                            O 7
                                                             ct
                                                               -0
                                                            De 7
                                                              c-
                                                                07
  Ad-Hoc Report with MEPRS data at one MTF
           (beware monthly data!)
                                                         Available
                                                         Clinician   Available
 FY       FM       Dispositions   Bed Days   Total Exp     FTEs      RN FTEs
2007       1            2            4       $184,494       2          1.06
2007       2            1            1       $161,362       2          0.99
2007       3            0            0       $190,998       2          0.94
2007       4            3           12       $311,324       2          1.41
2007       5            3            3       $148,320       2          1.18
2007       6            5           11       $337,549       2          1.44
2007       7            4            6       $119,829       2          0.98
2007       8            6            9       $194,973       2          1.35
Costs less to treat patients than to not
2007        9            5          12       $300,148       2          1.59
treat patients!
2007       10           4            7       $286,248       2          1.26
2007       11           6           13       $344,088       2          0.42
2007       12           2            3       $261,216      1.79        0.16
 Ad-Hoc Report with MEPRS data at one MTF
          (beware monthly data!)
                                                  Available
                                                  Clinician   Available
 FY    FM   Dispositions   Bed Days   Total Exp     FTEs      RN FTEs
2007   1        10           23       $56,515       0.16         0
2007   2        13           22       $62,197       0.32         0
2007   3        10           14       $157,662      0.06         0
2007   4         9           13       $64,372       0.79         0
2007   5         8           11       $29,814       0.12         0
2007   6        10           14       $39,635       0.1          0
2007   7        13           27       $50,379       0.02         0
2007   8        17           40       $102,042      0.56         0
2007   9        15           36       $137,371      0.4          0
2007   10        8           11       $34,940       0.56         0
2007   11       12           16       $35,185       0.27         0
2007   12       16           30       $89,789        0           0
          Ad-Hoc Report with M2 MEPRS

      Rx Expense and Total Expense for Ambulatory Clinics in
                             FY07
                                                                                                                            Note how much larger rx
                                                                                                                            is in Sep 07 compared
$1,200,000.00
                                                                                                                            with prior months
$1,000,000.00


 $800,000.00

                                                                                                                            Rx Exp
 $600,000.00
                                                                                                                            Total Exp

 $400,000.00


 $200,000.00


       $0.00
                         Nov-06




                                                                                                 Jul-07
                                           Jan-07




                                                                                        Jun-07
                                                             Mar-07
                Oct-06


                                  Dec-06




                                                                      Apr-07
                                                                               May-07




                                                                                                          Aug-07
                                                                                                                   Sep-07
                                                    Feb-07
Ad-Hoc Report with Monthly MEPRS
           from MDR
  FY    FM   Dispositions   Bed Days      Total Exp
 2007   1        45           200      $5,639,371.42
 2007   2        40           188      ($3,010,001.83)
 2007   3        44           224      $1,362,895.50
 2007   4        55           374      $1,137,152.31
 2007   5        51           318       $868,267.19
 2007   6        66           321       $991,846.96
 2007   7        40           145       $602,137.16
 2007   8        44           151       $764,113.54
 2007   9        31           144       $660,709.34
        AD-Hoc Report with M2 Monthly MEPRS
            (Beware Across Service Lines)
MEPRS Code          Army MTFs      AF MTFs        Navy MTFs       All MTFs
BCA - Family
  Planning            3,180,304      145                             12,774

BCB - Gynecology      80,121,683     81,008,784     123,864,534      926,449

BCC - Obstetrics      81,448,763     31,887,059                      532,385

BCD - Breast Care     1,182,718      381            7,066,993        25,010
BCX - OB/GYN Cost
  Pool                -              2,109                           -

Grand Total           664,253        358,628        473,737          1,496,618

				
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