Data Quality in the MHS Tips and Tricks. Objectives Describe MTF data collection systems. Identify...

Data Quality in the MHSTips and Tricks

Objectives

• Describe MTF data collection systems.• Identify data feeds from MTFs into corporate information

systems.• Describe the MHS Data Repository and M2.• List corporate reports in M2 that can be used to assist in

managing MTF data quality.• Characterize the state of MHS data with respect to data

quality.• Describe how M2 can be used for ad-hoc data quality

analysis.

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2

Major Data Collection Systems

• Like most major organizations, the MHS uses “operational systems” to assist with day to day activities– Real-time systems that automate activities

necessary to operate a business.– Data is often collected as a by-product of “getting

business done”.

3

Example of an Automated Business Process

MD sees patient MD orders Rx in operational system

Drug Utilization Review Query sent

automatically

Order is sent to pharmacy automatically

Rx is filled

Child’s all better and back to school!

4

• In this example, data would be captured and retained when the doctor orders the prescription in the computer

• The computer automatically knows where to send the data next (“trigger architecture”)

• The data entry person here is a physician – no “cube farms” with people entering data all day

• The by-product of the business process is that the health system knows who got what drugs, when, etc…

• Data collected this way is called “operational data”

5

Example of an Automated Business Process

Major Operational Systems in the MHS

• CHCS– Primary system used at MTFs.– Automates many functions for the MTF.– Administrative functions such as registration,

appointing, billing, etc..– Clinical functions such as order entry, results

retrieval, etc…– Is not an Electronic Health Record, but is the only

system at MTFs that keeps track of all direct health care delivery provided by the MTF.

– There are more than 100 separate CHCS databases.

6

Composite Healthcare System (CHCS)

NCA

Tidewater

Pendleton

San Diego

Etc….

Co Springs

Landstuhl

No connectivity between

100+ separate systems!

7

AHLTA

• AHLTA is another operational system.• Electronic medical record system used to document

outpatient care.– Providers use AHLTA for clinical note-taking for about 80%

of outpatient encounters.– AHLTA is not generally used in ERs or APVs.– When AHLTA is used, clinical data are captured

electronically, such as vital signs, height and weight, etc..

• AHLTA receives some information from CHCS also– Laboratory, Radiology, Pharmacy, etc.

• AHLTA data are stored centrally in the “Clinical Data Repository”.

8

0%

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FYFM

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% of SADRs Captured in AHLTA

ER Other OP SDS I P

Completeness of Data in AHLTA

9

Other Important Operational Systems

• Defense Medical Human Resources System (DMHRS)– New tri-Service personnel system used by MTFs.– Used to record labor hours.– Feeds into tracking of “productivity’.– Feeds into cost allocation process in MEPRS.– Will be discussed tomorrow in the DQ Course.

10


• Pharmacy Data Transaction Service– Real-time drug utilization review system.– When MHS beneficiaries receive outpatient prescriptions, an online

check is done. – Pharmacy can only fill prescription if PDTS responds back with

“advice” indicating it is safe.– Applies to all points of care (direct + retail) worldwide, except

overseas purchased care.• That is, Landstuhl Army Hospital does use PDTS, but the off-

base civilian apothekarie would not!

11


• DEERS– Primary system with information about MHS eligible

beneficiaries and enrollment in TRICARE Programs.– Not operated by the MHS; rather, is a personnel

system.– Beneficiaries correspond directly with DEERS offices

throughout the world to update information about their status.

– DEERS also communicates with many other federal organizations, such as the Military Services, Medicare and Social Security

12


• DEERS– Another important source of information to DEERS is the

DEERS Online Enrollment System– Enrollment Management System used in TRICARE Service

Centers– Enrollment, Disenrollment, Updates of Contact Information,

PCM Assignment, “Other Health Insurance” Information Updates

• DEERS directly updates CHCS whenever a CHCS user requests an eligibility inquiry– And not otherwise, generally.– Results in inaccurate CHCS person data for some

members.

13

Benefits of Operational Systems

• Operational Systems have some key benefits:– Real time, since these systems are the point of

original entry.– Only type of system where real time data are

available.– Closest to the point of capture; means that focusing

on data quality in source systems can save time and money in reprocessing…

– And makes data more usable locally.

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Drawbacks of Operational Systems

• The main drawback of an operational system is that data problems cannot (are not) generally fixed.

• Numerous errors originate at the source.• Some input errors simply can only be fixed locally or with

patient assistance.

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MTF Gender Diagnosis Procedure

Navy MTF M Missed Abortion Ultrasound

Army MTF M Abnormal Ultrasound Detailed Ultrasound

AF MTF M Preeclampsia Fetal Monitoring

Quality in Operational Systems

• Some input errors (and other issues) can be fixed.– Usually not done in operational systems, though, because

they are too important to an organization to shut down.– (Person identification and AHLTA/CDR/CDM is a good

example).

• Instead, data from operational systems are typically exported to other systems (warehouses) for further processing.

• This processing can be critically important to using data.

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Data Warehouses

• There are two types of warehouses:• Dedicated Warehouses

– Usually receive data from one operational system only, though not always the case.

– Can be thought of as a storage silo.– Data are not generally processed, so that all the quality

weaknesses in the source system are present in the warehouse.

• Many of our operational systems have dedicated warehouses:– Clinical Data Repository, PDTS Warehouse, Purchased Care

Data Warehouse…

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MHS Data Repository

• Comprehensive Data Warehouses:– Take in data from multiple systems– Data are usually processed to standardize and enhance data

quality.• The MHS has one comprehensive data warehouse; the MHS Data

Repository (MDR). • MDR is the most popular system you never heard of!

– MDR data are used as a source of data for many commonly used applications, such as:

• M2• Population Health Portal / Care Point• MHS Insight, etc…

• Documented on http://www.tricare.mil/ocfo/bea/functional_specs.cfm – Contains an easy to use data dictionary

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MHS Data Repository

• MDR is immensely flexible– Can upload and download data– Sophisticated programming tools– Can access Clinical Data Mart (CDM) data through MDR front end

• Very difficult to use, however– No point, click, drag, drop– The mouse barely even works!– Must be a skilled programmer to use

• Most users touch MDR data in “M2”

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Basic Data Flow

TED MDR Feed Node

Data sent to MDR 24/7

CHCS/AHLTA

DEERS

PDTS

MDR File Storage & Limited Access

Data Marts

Batches

Others User Access in Data Marts

Weekly Monthly

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Some selected MDR Processing Enhancements

• Person Identification Enhancement:– “DEERS Person Identifier” is an element in the MDR that

identifies each beneficiary.– Some records come in with only partial or incorrect person

identifying information, though.– Example: Newborns have a sponsor identifier, but no

person ID.– MDR has a Master Person Index file that is used to add

missing information to every record.– Allows for consistent identification of patients, regardless

of source in the MDR.

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Question: How many well visits did person “111111111” have?

Person ID Sponsor SSN Type of Care Service Date DOB

999 99 9999 Admission 10/5/2009 10/5/2009

999 99 9999 Well Check 10/11/2009 10/5/2009

1111111111 999 99 9999 Well Check 11/4/2009 10/5/2009

1111111111 999 99 9999 Well Check 12/3/2009 10/5/2009

Person ID Sponsor SSN Type of Care Service Date DOB

1111111111 999 99 9999 Admission 10/5/2009 10/5/2009

1111111111 999 99 9999 Well Check 10/11/2009 10/5/2009

1111111111 999 99 9999 Well Check 11/4/2009 10/5/2009

1111111111 999 99 9999 Well Check 12/3/2009 10/5/2009

As receivedAfter MDR Processing

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MDR Enhancements

• Application of DEERS attributes to each data record– After correcting person ID issues, the MDR then standardizes

demographic and enrollment information.– Avoids ‘apples and oranges’.– Needed because person demographics are not always accurate on

source data or can be missing entirely.– Also, some systems only contain current demographics, while

“contemporaneous” data are usually needed.– Beneficiary Category, Enrollment Program, Primary Care Manager,

etc.– Allows for retroactive changes, also.

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Example: How many well visits did enrollees of Fort Belvoir have?

Person ID Enroll MTF Type of Care Service Date DOB

Admission 10/5/2009 10/5/2009

Well Check 10/11/2009 10/5/2009

1111111111 Fort Belvoir Well Check 11/4/2009 10/5/2009


Person ID Enroll MTF Type of Care Service Date DOB

1111111111 Fort Belvoir Admission 10/5/2009 10/5/2009




As received After MDR Processing

Newborn was retroactively enrolled in DEERS to Fort Belvoir.24

How many PDHAs?

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Person ID Procedure Code Bencat Service DateRetirement

Date*

1111111111Pre-Deployment

Health AssessmentRetired 10/7/2009 11/1/2010


Health Assessment Retired 10/12/2009 11/1/2010

Person ID Procedure Code Bencat Service DateRetirement

Date*


Health AssessmentActive Duty 10/7/2009 11/1/2010


Health Assessment Active Duty 10/12/2009 11/1/2010

As received. Likely indicates patient’s current status, when query was run.

* Retirement date from DEERS.

After MDR Processing

• Another very important application of the MDR is to add Weighted Workload Values to direct care encounter records.

– Relative Weight Products (RWPS), Relative Value Units (RVUs) and APC Weights are extremely important in the MHS.

– Serve as the basis for budgeting for most inpatient and ambulatory healthcare in MTFs.

– MTFs do not code RWPs or RVUs.– RWPs and RVUs are added to MDR records based on information that is coded

on SIDRs and SADR/CAPERs.– The logic for adding these data elements is published on the MDR website.– The RWPs and RVUs in MDR/M2 are the ones that are used for major HA/TMA

initiatives, such as PPS or Business Planning.– Will discuss derivation rules later.

MDR Enhancements

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• Another very important application of the MDR is to add cost data to direct care encounter records.

– Full and Variable cost estimates are added to each record.– These elements are used routinely by MTFs for financial decision-making.– The algorithms for creating these variables involve the combination of

SIDR/SADR/CAPER data with MEPRS cost information.– MTFs who do not record workload and labor in the same location as costs may

end up having their cost data in MDR/M2 impacted.– Will show an example of this later.

MDR Enhancements

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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.– More than 1000 users.– Ad-hoc Querying or “Standard Reports”.– M2 is currently transitioning to a new software version (the

Desk-I version is recommended).

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 can be obtained from DeskI.

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

Oct-07 Nov-07 Dec-07 Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-080

100

200

300

400

500

600

700

800

Monthly Discharges

Common Data Quality Items

• Why do you need complete data?

Oct-07 Nov-07 Dec-07 Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-080

100

200

300

400

500

600

700

800

Monthly Discharges


• Why do you need complete data? FY

w/errorFY w/o error

7,387 7,727

340 discharge records lost!

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

case analysis


• 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– Example: Appointment file

Real-TimePatient Call Real Time

Using CHCS to book appt

DailyEnd of Day Processing

Periodic standardized data feeds


• 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


• 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 (CAPER) - Completed outpatient

visits and inpatient rounds and case management acuity assessments.


• 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 entirely claim based

– Examples of data not required:

Inpatient Surgical CPT Records

Ambulance Records

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Example of Rhinoplasty• Direct Care Coding

SIDR Value

Admission Date 5/23/2009

Discharge Date 5/24/2009

DRG 056

Procedure 2188

Days 1

SADR SADR #1 SADR #2 SADR #3 SADR #4

Service Date 5/22/2009 5/22/2009 5/23/2009 5/24/2009

MEPRS Code B D A A

Procedure Code NONE NONE NONE 99024

E&M Code 99499 NONE 99499 99499

RVU 0 1.22 0 0.76

• No procedure coded on SADR

• Separate pre-op and follow up visit coded

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Example of Rhinoplasty

• Private Sector CodingTED-I Value

Admission Date 5/14/2009

Discharge Date 5/16/2009

DRG 056

Procedure 2172

Days 2

TED-N TED #1 TED #2 TED #3 TED #4 TED #5

Service Date 5/14/2009 5/15/2008 5/15/2008 5/16/2008 5/16/2008

Procedure Code 99291 99232 99255 99238 21335

RVU 2.27 4.50 1.39 1.28 8.91

• Procedure is coded in both inst and non-inst records

• No pre-op or follow up visit (bundling)


• 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 Code

Bencat Count Visits

Adm Disp Bed Days

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): VisitsA MEPRS Code (Inpatient): Adm, Disp and Days


• 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”


• 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

MDR

NMIC

AFMSSA

PASBA


• 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


• 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


• 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

Picture of SIDR flow

CHCS

CHCS

CHCS

CHCS, etc

MDR

• SIDRs sent monthly from local CHCS hosts

• Assembled into one file and processed in MDR

• Sent to M2

M2

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 DeskI

• 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

SIDR % Complete by Service

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

Oct-04

Dec-04

Feb-0

5

Apr-0

5

Jun-

05

Aug-0

5

Oct-05

Dec-05

Feb-0

6

Apr-0

6

Jun-

06

Aug-0

6

Oct-06

Dec-06

Feb-0

7

Apr-0

7

Jun-

07

Aug-0

7

Oct-07

Dec-07

Feb-0

8

Apr-0

8

Jun-

08

Aug-0

8

Oct-08

A

F

N

No obvious holes!


• Standard Ambulatory Data Record (renamed Comprehensive Ambulatory Provider Encounter 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 code

MEPRS 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


• 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


• 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 MDR: Compare appt and SADR; record by record.

• Missing a SADR for Appt # 4.

• #4 will be in the MDR database as an ‘inferred SADR’.

SADR # APPT #

1 1

2 2

3 3

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

5 Real JONR AL BAA 99213

6 Real JONR ROB BAA 99214

7 Real JONR SARA BAA 99499

Appt # 4 has no E&M because no SADR has been collected. This is an appointment-based record

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 deemed “countable”.– Method developed when appointment data was unavailable– Not always a precise match since ‘count’ status can change from

the time of appointment to the time of care delivery.• 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, however.

• 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!

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.rep.comp.wwr.rep

Completeness of SADR Data with Appointment Benchmark

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

5 Real JONR AL BAA 99213

• Combination of kept appointments and SADR makes precise measurement of missing SADRs possible.

• Perfect compliance would be 100%

• No “Inferred” Records

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 that ‘count’ (and FBN) / # total kept appointments in same clinics

• Expressed as % Complete• Can easily be reviewed using M2 Corporate Document

– Report Name: tma.rm.dq.dcop.rep.comp.apptbench.rep

Completed Outpatient Appointments with No SADRs

Missing SADRS

0

20000

40000

60000

80000

100000

120000

Oct

-98

Oct

-99

Oct

-00

Oct

-01

Oct

-02

Oct

-03

Oct

-04

Oct

-05

Oct

-06

Oct

-07

Oct

-08

A

F

N

Writeback Meltdown!

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 RVUs 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– tma.rm.dq.dcop.rep.comp.actionrep

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

Case Management SADRs

• The MHS must report to Congress the:– Number of case managers, and– The patient’s acuity, and– The number of patients in case management.

• Tri-Service agreement was obtained for the methodology for reporting of CM.– Describes in the UBU Coding Guidelines

• Tri-Service agreement was reached that MEPRS B codes would not be used for CM.– FAZ2, ELAN, and ELA2 are the only approved codes for CM.– tma.rm.dq.casemgmt.child.rep &

tma.rm.dq.casemgmt.parent.rep

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Case Management SADRs

• The chart below shows the impact of case management SADRs being recorded in “B” Codes in PPS.

• While the MTFs that use B codes for CM will receive excessive funding under PPS, there is an obvious downside:– These sites will be given no credit for doing CM in a required report to

Congress on CM services and Wounded Warriors.

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85

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

Workload(CHCS)

Financial Data(STANFINS,STARS/FL,

BASF)

Personnel Data(DMHRS,UCAPERS,

SPMS, EAS)

EAS-Internet

MDR(Large MEPRS dataset)

M2(Smaller MEPRS dataset)

(Monthly Processing)(Nightly/Monthly

Processing)

EAS IV Repository(Full MEPRS dataset)

Monthly MEPRS data due 45 days after month end

Example of Some MEPRS Data

• 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!• There are frequent timeliness problems with MEPRS data.

MTF MEPRS Code

FY/FM Avail Clin FTES

Bed Days Total Expense

Lab Expense

0024 AAAA 200901 2.89 120 295,190 4,233

0109 BAAA 200901 6.88 0 1085948 133,779

TimelinessTimeliness


• Why do you need timely data?

Date

2008

01

2008

02

2008

03

2008

04

2008

05

2008

06

2008

07

2008

08

2008

09

2008

10

2008

11

2008

12

2009

01

2009

02

2009

030

50

100

150

200

250

300

350

400

Reported Dispositions • Steady trend until recent timeframes

• Includes FY08 and part of FY09


• Why do you need timely data?

Missing data causes an artificial year to year trend

Date

2008

01

2008

02

2008

03

2008

04

2008

05

2008

06

2008

07

2008

08

2008

09

2008

10

2008

11

2008

12

2009

01

2009

02

2009

030

50

100

150

200

250

300

350

400

Reported DispositionsFY Disp

2006 4,3022007 4,2512008 3,862

Annual Recap

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/CAPER 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 in this

course.– Ask them about local tools for managing timeliness!

• 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 Accuracy

• Direct Care SIDR and SADR:– MHS uses policies for completeness and timeliness.– Coding and Compliance Editor (CCE) for code edits but is rarely

used.

CCE Status Description A F N

1Pending; Original Encounter Submitted to CCE 2,666,743 590,602 812,197

2Received Updated Encounter from CCE 4,280,679 1,449,747 1,593,678

3 Released from CCE w/ no changes 569,910 139,672 131,725

4Complete, updated encounter received and processed 345,921 134,260 71,376

5Uncertified; Released from CCE with no changes 133 2,447 1,522

Blank 12,332,403 7,036,862 8,064,037

Direct Care Accuracy

• SIDRs are typically coded by registered coders and are of higher quality that SADRs.

• SADRs have some significant issues with quality.– Compliance– Choice of CPT codes– Use of Units of Service

• Coding audits are required at MTFs but sample sizes are too small.

04/18/2023

99

100

Coding Creep in the MHS

2.70

2.75

2.80

2.85

2.90

2.95

3.00

3.05

3.10

3.15

AFNTotal

MHS Worldwide Average (non ERs), October 2005 through January 2011

Average E&M Code Intensity

101

Coding Creep in the MHS

MHS Worldwide Average (ERs), FY2006 through FY2010

2.40

2.50

2.60

2.70

2.80

2.90

3.00

AFNTotal

Average E&M Code Intensity in Emergency Rooms

Service-Wide Impact of Incorporating Unit of Service Limits in RVU Calculations

Service Simple RVU

Enhanced Simple (ES)

RVU

Enhanced Simple RVU w/

Limits

Simple vs. Enhanced

Simple

Enhanced Simple vs. Limited ES

Simple vs. Limited ES

A

16,759,382

17,576,133

17,292,735 5% -2% 3%

F

8,072,882

8,378,461

8,291,245 4% -1% 3%

N

9,408,982

9,967,646

9,867,874 6% -1% 5%

Total

34,241,247

35,922,241

35,451,855 5% -1% 4%

CPT Impacts of Unit of Service Limits

•Some selected extreme examples from SADRs•Each SADR represents care provided to one patient on one day.•The first three SADRs indicate that there were 80 patients were given more than 900 vaccinations at one visit!•The last SADR shows 159 encounters where the patients had up to 52 days of psych counseling in one day!

CPT Description UOS Raw Limit # SADRs

90471Administration of a Single Vaccine 906 1 48

90471Administration of a Single Vaccine 907 1 15

90473Administration of a Single Vaccine - Oral 906 1 17

90801 Psychiatric Eval (covers up to 24 hours) 52 2 159

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 MS-DRGs– Unlisted Provider Specialty Code– Potential Pharmacy Table Errors– Potential Provider ID Errors– Improperly Coded Case Mgmt records

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

together

• Ungroupable MS-DRGs receive no PPS funds for the Service– Significant improvement since PPS!

M2 Ungroupable DRG Report

• Report name:– tma.rm.dq.dcip.ungroupable.drg

• Includes:– MTF Identifier & Information– Date of Care– MS-DRG, Description, MDC– 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 problem records

• Limit to Tx DMISID and Record ID with ungroupable DRGs

• Must include MTF and Record ID to get unique list of records

Include data elements of interest from SIDR

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.dcop.unspecified.provspec

Code Description001 Family Practice Physician923 Family Practice Clinic603 Pediatric Nurse Practitioner520 Independent Duty Corpsman

Who delivered the care when specialty is 923?

Improvement in Use of Specific Provider Specialty Code

Encounters with Unspecified Provider Specialty Code

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

Oct-04

Nov-04

Dec-04

Jan-05

Feb-05

Mar-05

Apr-05

May-05

Jun-05

Jul-05

Aug-05

Sep-05

A

F

N

Power of Budget Incentives!

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.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

MTF Product Name Issue Date Days Supply

Quantity Person ID Ordering Clinic

0089 Oxycodone 10/01/2008 30 10 #1 BIA

0089 Nexium 10/01/2008 30 60 #2 FCC

Sample Pharmacy Data from an MTF

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.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

126

Full Time Equivalents – StaffingFTE Reporting Problem Example

FM Disp Days Total ExpMEPRS3

Code

Available Clinician

FTEsAvailable RN FTEs

Available Prof FTEs

1 75 136 $558,043.75 AAA 9.68 0 0

2 58 156 $547,937.46 AAA 9.07 0 0

3 58 105 $576,951.93 AAA 7.92 0 0

4 57 118 $495,790.59 AAA 8.39 0 0

5 61 145 $773,788.72 AAA 7.52 0 0.04

6 81 182 $553,552.20 AAA 8.2 0 0.17

7 64 133 $520,921.49 AAA 8.34 0 0.15

127

Full Time Equivalents – StaffingFTE Reporting Problem Example

Month Expense Visits Clinic

Available Clinician

FTEsAvailable RN FTEs

Available ParaProf

Available Prof FTEs

1 $30,933.36 1,697 BAB 0 0 0 0

2 $40,562.08 1,318 BAB 0 0 0 0

3 $47,311.98 1,292 BAB 0 0 0 0

4 $43,250.39 1,480 BAB 0 0 0 0

5 $30,342.45 1,008 BAB 0 0 0 0

6 $34,990.14 1,225 BAB 0 0 0 0

7 $28,174.98 1,152 BAB 0 0 0 0

128

Rx Percent of Ambulatory Expenses

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Army Air Force Navy

FM 01

FM 12

FM 01

FM 12

FM 01

FM 12

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