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.
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”.
Example of an Automated Business Process Order is sent to pharmacy automatically MD sees patient MD orders Rx in operational system Drug Utilization Review Query sent automatically Child’s all better and back to school! Rx is filled
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” 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.
Composite Healthcare System (CHCS) NCA San Diego Co Springs Tidewater No connectivity between 100+ separate systems! Etc…. Landstuhl Pendleton
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”.
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.
Other Important Operational Systems • 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!
Other Important Operational Systems • 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
Other Important Operational Systems • 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.
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.
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.
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.
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…
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
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”
Basic Data Flow Data sent to MDR 24/7 MDR File Storage & Limited Access TED MDR Feed Node Batches CHCS/AHLTA Weekly Monthly DEERS PDTS Data Marts User Access in Data Marts Others
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.
Question: How many well visits did person “111111111” have? As received After MDR Processing
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.
Example: How many well visits did enrollees of Fort Belvoir have? After MDR Processing As received Newborn was retroactively enrolled in DEERS to Fort Belvoir.
How many PDHAs? As received. Likely indicates patient’s current status, when query was run. After MDR Processing * Retirement date from DEERS.
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
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
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”?
Common Data Quality Items • Why do you need complete data?
Common Data Quality Items • Why do you need complete data? 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
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 • Example: Appointment file Daily End of Day Processing Periodic standardized data feeds Real-Time Patient Call Real Time 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 (CAPER) - Completed outpatient visits and inpatient rounds and case management acuity assessments.
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
Example of Rhinoplasty • No procedure coded on SADR • Separate pre-op and follow up visit coded Direct Care Coding
Example of Rhinoplasty • Private Sector Coding • Procedure is coded in both inst and non-inst records • No pre-op or follow up visit (bundling)
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 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 MDR PASBA 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 • Many more data elements available on SIDR – hundreds of them • MTF DMISID + Register Number (PRN) is the way to identify a unique record