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Objectives Describe CHCS

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1 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

2 And the number of discharges we can recapture is……..
The Data’s No Good! And the number of discharges we can recapture is…….. At least I didn’t use it! Why fix it? Who cares if the data are bad! We just used the old dartboard method! Since the data is not good

3 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!

4 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

5 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

6 Composite Healthcare System (CHCS) Access
NCA San Diego Co Springs Tidewater No connectivity between 100+ separate systems! Landstuhl Etc…. Pendleton

7 Example: MTFs on Eisenhower CHCS Host
DMISID Name 0047 Eisenhower 0237 McPherson 1230 Camp Shelby 1550 TMC-4 Stockade 7197 TMC Connelly 7239 TMC Southcom Local CHCS queries only retrieve data for care provided at these MTFs!

8 Example: Inpatient Data Available at EAMC from CHCS
Most of the days of care for EAMC area enrollees are not visible in CHCS

9 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

10 CHCS Data Products Name Description Acronym
Standard Inpatient Data Record Inpatient Hospital Records SIDR Appointment Appointment records for outpatient visits None! Referral Referrals for specialty care Standard Ambulatory Data Records Outpatient visit, t-con or inpatient rounds records SADR Ancillary Lab and Rad and Rx Procedure records Worldwide Workload Report Summary workload data WWR

11 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

12 FLOW OF SADR MDR SADR file contains ADM & AHLTA information M2 SADR
CCE CHCS/ADM Writeback CDR Picture of CHCS Appt File; AHLTA, ADM, writeback & SADR> also CDR / CDM ADM & AHLTA are used to capture ambulatory data APPT AHLTA

13 Use of AHLTA for Outpatient Care
10% of regular visits still not captured in AHLTA These 10-20% are not b/c the AHLTA ER module works; it doesn’t. It’s there for the few MTFs that hire extra help and pay someone to hand-enter the ER visits into AHLTA, from the handwritten notes. 10% of reg vis still missing are when AHLTA sys goes down and MTFs must revert to using ADM again. Very little usage in ER and Same Day Surgery Centers – more for office based care

14 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) Add a picture of m2.

15 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

16 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

17 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 What is the mdr

18 MDR Processing, File Storage & Limited Access
Basic Data Flow Data sent to MDR 24/7 MDR Processing, File Storage & Limited Access MEPRS MDR Feed Node Batches CHCS Weekly Monthly DEERS Claims M2 1500+ users access in M2 Others

19 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

20 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”

21 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?”

22 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

23 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

24 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”?

25 Completeness

26 Common Data Quality Items
Why do you need complete data?

27 Common Data Quality Items
Why do you need complete data? FY w/error FY w/o error 7,387 7,727 340 discharge records lost!

28 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

29 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

30 Lack of Data Capture Some data are captured during the business process Often sent off automatically Example: Appointment file Daily End of Day Processing Periodic standardized data feeds Real-Time Patient Call Real Time Using CHCS to book appt

31 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

32 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

33 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 entirely claim based Examples of data not required: Inpatient Surgical CPT Records Ambulance Records

34 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

35 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!)

36 Example WWR Data MTF CY/CM MEPRS Code Bencat Count Visits Adm Disp
Bed Days 0001 200801 BAA DA 66 DR 222 0029 AAA RET 90 97 339 ACT 56 252 47 BDA 5286 542 B MEPRS Code (Outpatient): Visits A MEPRS Code (Inpatient): Adm, Disp and Days

37 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”

38 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 MDR PASBA AFMSSA NMIC

39 Capture Requirements Standard Inpatient Data Record Significance:
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.

40 Some Sample Data from SIDR
MTF Reg Num Pat ID Adm Date Disch Date Dx 1 DRG 0125 Pat #1 11/01/2008 11/03/2008 V3000 391 0117 Pat #2 10/16/2008 10/17/2008 49121 088 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

41 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

42 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

43 Picture of SIDR flow SIDRs sent monthly from local CHCS hosts MDR M2
Assembled into one file and processed in MDR Sent to M2 CHCS MDR CHCS CHCS M2 CHCS, etc

44 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

45 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

46 Step-by-Step Retrieving a Standard Report

47 Select the report you want and click retrieve!
Use report guide in handout

48 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

49 No obvious holes!

50 Capture Requirements Standard Ambulatory Data Record Significance:
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.

51 Some Sample Data Fields from SADR
MTF Appt ID No Pat ID Appt Date Diag 1 E&M code MEPRS Code 0117 Pat #1 10/31/2008 56400 99283 BIA 0075 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

52 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

53 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)

54 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”

55 Matching SADRs to Appointment Records
APPT # 1 2 3 4 5 6 7 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’.

56 Final MDR Data Set # Compliance Status Prov Patient Clinic E&M 1 Real JONR MARY BAA 99214 2 JOE 99213 3 JANE 4 Inferred NAN N/A 5 AL 6 ROB 7 SARA 99499 Appt # 4 has no E&M because no SADR has been collected. This is an appointment-based record

57 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

58 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

59 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!

60 3.5 Million Non-Count Visits worth almost 1 Million RVUs!
All Encounters: N= 32 Million “Count Only N= 29 Million 3.5 Million Non-Count Visits worth almost 1 Million RVUs!

61 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% 461,598 550,622 1,012,220 46%

62 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 100% Can easily be reviewed using M2 Corporate Document tma.rm.dq.dcop.rep.comp.wwr.rep Currently, each report has only one year. Multi-year report under construction

63 Completeness of SADR Data with Appointment Benchmark
Combination of kept appointments and SADR makes precise measurement of missing SADRs possible. Perfect compliance would be 100% No “Inferred” Records Final MDR Data Set # Compliance Status Prov Patient Clinic E&M 1 Real JONR MARY BAA 99214 2 JOE 99213 3 JANE 4 Inferred NAN N/A 5 AL

64 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.dcop.rep.comp.apptbench.rep

65 Completed Outpatient Appointments with No SADRs
Writeback Meltdown! Major Improvements in Compliance

66 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

67

68 .

69 After entering your DMISID: Kept Appointments with No SADR
.

70 Use Slice and Dice to determine which clinics are losing the most PPS $$$ due to lack of completeness of SADR

71 Surgical Clinics, Primary Care, ER

72 Back to slice and dice to look at lost earnings by provider

73 “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!

74 Back to slice and dice to look at which SADRs are missing.

75 “Record IDs” are the appointment IENs of the missing SADRs
Use to find the missing records in ADM or AHLTA

76 MEPRS Expense Assignment System Summary Data Only 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

77 MEPRS Data Flow EAS IV Repository MDR (Large MEPRS dataset)
(Full MEPRS dataset) Workload (CHCS) MDR (Large MEPRS dataset) Financial Data (STANFINS, STARS-FL, GAFS-R) EAS-Internet (Monthly Processing) Personnel Data (DMHRSi) (Nightly/Monthly Processing) Monthly MEPRS data due 45 days after month end M2 (Smaller MEPRS dataset)

78 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

79 Example of Some 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 6.88 133,779 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!

80 Timeliness Timeliness

81 Common Data Quality Items
Why do you need timely data? Steady trend until recent timeframes Includes FY08 and part of FY09

82 Common Data Quality Items
Why do you need timely data? Annual Recap FY Disp 2006 4,302 2007 4,251 2008 3,862 Missing data causes an artificial year to year trend

83 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

84 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 Appointment   Auto Send

85 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

86 Accuracy

87 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”

88 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

89 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

90 Coding Creep

91 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

92 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!

93 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

94 Choose Corporate Documents
Paste in a screen print File, retrieve from, corporate documents….

95 Pick report name of interest and hit “Retrieve”
Select: tma.rm.dq.dcip.ungroupable.drg Pick report name of interest and hit “Retrieve”

96 Report is already filled with data
Updated each month when SIDR Table is updated Replace these slides.

97 “Record ID” is the patient registry number from CHCS.
Bring to coders to fix! Replace these slides.

98 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

99 M2 ad-hoc users can get details associated with problem records
Limit to Tx DMISID and Record ID with ungroupable DRGs Include data elements of interest from SIDR

100 Admitted and Discharged prior to BIRTH!

101 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 Code Description 001  Family Practice Physician 923 Family Practice Clinic 603 Pediatric Nurse Practitioner 520 Independent Duty Corpsman Who delivered the care when specialty is 923?

102 Improvement in Use of Specific Provider Specialty Code
Power of Budget Incentives!

103 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

104 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.

105 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 Show a couple of examples

106 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 Supply Quantity Person ID Ordering Clinic 0089 Oxycodone 10/01/2008 30 10 #1 BIA Nexium 60 #2 FCC Total Pharmacy Costs for DHP 106

107 PDTS Data Flow CHCS Hosts PDTS Web Interface Warehouse Retail PDTS MDR
Mail Order Weekly M2 Paper Claims

108 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) Total Pharmacy Costs for DHP

109 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

110 Advair at $660 per script! Asthma medication is not that expensive! Problems with pre-defined units and NDC.

111 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.

112 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

113 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: RWP was:

114 Used Radiology Table Big Holes in the middle of FY07 (completeness)

115 Ad-Hoc Report with MEPRS data at one MTF (beware monthly data!)
FY FM Dispositions Bed Days Total Exp Available Clinician FTEs Available RN FTEs 2007 1 2 4 $184,494 1.06 $161,362 0.99 3 $190,998 0.94 12 $311,324 1.41 5 $148,320 1.18 6 11 $337,549 1.44 7 $119,829 0.98 8 9 $194,973 1.35 $300,148 1.59 10 $286,248 1.26 13 $344,088 0.42 $261,216 1.79 0.16 Costs less to treat patients than to not treat patients!

116 Ad-Hoc Report with MEPRS data at one MTF (beware monthly data!)
FY FM Dispositions Bed Days Total Exp Available Clinician FTEs Available RN FTEs 2007 1 10 23 $56,515 0.16 2 13 22 $62,197 0.32 3 14 $157,662 0.06 4 9 $64,372 0.79 5 8 11 $29,814 0.12 6 $39,635 0.1 7 27 $50,379 0.02 17 40 $102,042 0.56 15 36 $137,371 0.4 $34,940 12 16 $35,185 0.27 30 $89,789

117 Ad-Hoc Report with M2 MEPRS
Note how much larger rx is in Sep 07 compared with prior months

118 Ad-Hoc Report with Monthly MEPRS from MDR
FY FM Dispositions Bed Days Total Exp 2007 1 45 200 $5,639,371.42 2 40 188 ($3,010,001.83) 3 44 224 $1,362,895.50 4 55 374 $1,137,152.31 5 51 318 $868,267.19 6 66 321 $991,846.96 7 145 $602,137.16 8 151 $764,113.54 9 31 144 $660,709.34

119 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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