Session 103 HPM HBI - Yardley Hospital Management Consulting

Session 103:
Advanced HPM/HBI
Applications (Tips
& Tricks)
Roger Crook
Casey Merickel
Yardley Management Solutions, Inc.
©2009 Yardley Management Solutions, Inc.
This material is for the sole use of attendees of Insight 2009 Pre
conference session #103. Copying or distribution to others is not
Overview: Options to Extend HPM Encounter Data
Case Study: Extended HPM Data for Implant Costs
Case Study: Extended Data to Audit HPM
Case Study: HPM Events – Creative Uses
Case Study: HPM Worksheet for Net Revenue
Case Study: Custom Object for Benchmark Data
Overview: Modeling with EBB
Case Study: Loading Model Revenue Fields for
Encounter Based Modeling with EBB
• Case Study: Synthetic charge codes for ABC costing
• Case Study: HBI Daily Update of Patient Data
• Case Study: HBI Daily Census and Productivity
Extending HPM Data
• UDA: User Defined Attributes, the original user-defined
fields that can be activated at various levels in the
encounter dataset.
• Custom Object: A user defined table that can be related
to encounter data through one or more key fields
• Extended Data: Newest way to extend existing tables or
encounter data type
Rules of Thumb
• However your HPM was built, no reason to change. All
three methods are supported.
• The real question is what to do going forward when you
have the need to add new data to the warehouse.
Pros and Cons of UDAs for new data
• UDAs are at different levels in
the data model
• Some UDAs will continue to
hold 3M grouping results and
PMOD results
• New UDA data must be
loaded with the encounter
• Not viewable in Encounter
• Once created, no provision in
the application to remove the
• Creating a UDA requires
system restart (from Extended
From Extended data.pdf:
Pros and Cons of Custom Objects
• Simple to build and load
• Good for linking based on
encounter fields like DRG and
• Good for handing benchmark
• Cannot use UDA (like UDA
DRG fields) as link/key field.
• Cannot use field in a data
extension as link/key field
• Once built, lets you delete,
but leaves remnants behind,
including old worksheets that
referenced the deleted
custom object.
Pros and Cons of Extended Data
• Newest approach, meant to
combine best of UDAs and
Custom Objects
• Can extend encounters,
procedures, reasons and
• DRG tables can be extended
with benchmark data
• Can load as part of interface
or independently
• Tracks what has been loaded
versus what did not load
• Application supports adding
and deleting extensions
• Some extensions, like service
items, do not yet work
• Some extensions can only be
loaded when encounter data
is added/replaced.
• A little convoluted in how it is
set up, until you get used to it
• Even though it will let you
change field names, doing so
is not recommended
• Not viewable in encounter
Case Study: Extended Data for Implant Costs
Background: Miscellaneous service item (6211888)
was used for approximately 2.6 million of over 6
million in implant costs in 2008, with a range per item
of 0 to $14,000
Using this data as-is, HPM would develop an average
cost and apply it to all patients, grossly overstating
and understating individual patients.
Implant Costs in Data Extension - continued
There are several approaches to handling this:
Custom interface program from McKesson to break out ranges of
charge values
– Makes new charge codes to replace old code
– Would have to reload history for these patients
– Have to process with each subsequent update
Change charge capture in STAR to include better detail
– Will not correct prior history
– Strongly recommend for going forward
Include invoice cost or a reasonable approximation for each patient
– Most control for Sample using a data extension
– Easily maintained
– You MUST include this field when reporting encounter cost
– Must remove this cost from implant to be allocated using a remap
– This is the approach we have adopted for now
Using an Encounter Data Extension
Setting up the extension
To Stage or Not to Stage
Integrating staged data
Merging staged data
Using the data in Worksheet
Setting Up The Extension
Data Integration/Data Model Extensibility
Choose staged or not staged (see next slide for more)
Choose field names and data types
System returns the format that the file for integration
must have
• MUST got to security next and enable modify access
for your account and view access for other accounts for
the extension
Setting up the data extension (1)
Your extension is already set up, you do not need to make a new
one or modify the existing. This just shows how it was done.
Setting up the data extension (2)
Extensions are set up in the data model where appropriate, this one
is in the encounter section.
Setting up the data extension (3)
When you make an extension
template you get to choose if
a staging area will be used. If
it is, a box pops up to ask how
it will link to the patient
record. See more on staging
on the next slide.
To Stage or Not To Stage
Two approaches to loading an extension:
1) You have the encounter key and can put it on each
The encounter key is complex, consisting of multiple elements,
including patient name
Using this method, you can integrate directly to the extension
2) You have the patient billing number on each record,
but not the whole encounter key
You first integrate to the staging area
Then you merge the staged data with the dataset
We used #2 because it is easier to obtain the patient
billing number in the data you want to load.
Setting up the data extension (4)
Options here allow you to create a new extension, and once
to “build” it, essentially publishing it in the data model.
Setting up the data extension (5)
One of the options on the prior screen is “Layout Report” which
18 you exactly how to format the file for the data.
Actual file for integration
This file uses “Layout Report” specifications from prior screen. The file for 2008
is complete, unless we make a better version with invoice cost. For 2009, we
should rebuild this file year-to-date with each update. You must be vigilant to
make sure this data is complete as patients are added to the dataset. The next slides
19 how the values were arrived at in this file.
Preparing the misc implant patient file (1)
Use implant.xls to determine the cost for each patient using the
markup of charges tab.
Preparing the misc implant patient file (2)
The tab “Simple HPM Load” creates the file format needed in column e.
Recap on the implant extension:
• For 2008, the data has been loaded based on the
markup and patient charges
• Need to monitor to make sure future updates to 2008 do not
change the 2.602 million
• Could make it more accurate by replacing the values with invoice
• For 2009, if the charge mechanism is now splitting out
several ranges of miscellaneous code, we could use
• Need to see when it began and how much it covers
• Should probably continue to populate the extension with invoice
for the most accurate implant cost
Add access in security
You must give yourself and others access to the extension before you
do anything else. You will not be able to integrate until you do.
Setting up the integration process
When you open the process, you can see the target is the staging
area for the extension we built.
Merge Staging Area Data
• If you picked “Integrate to the staging area” as an
option, you have one more step after integration of the
• You need to merge the data with one or more datasets.
• This makes the association to each patient record using
the linking field you specified.
• Following slides depict how this is done
Merging Staged Area Data: Choose on menu
Merging Staged Data: Choose staging area and
dataset(s). Okay button will detach automatically.
Merging Staged Data: From job menu, right
click on job to read logs files
Merging Staged Data: From job menu, right
click on job to read logs files
Merging Staged Data: Locating the data
extension in Worksheet Editor
Merging Staged Data: Seeing the results in
Merging Staged Data: Seeing the results in
Worksheet – drill to encounter
Other Notes on Using The Extended Implant
• If reporting with department drill level, qualify column for
the implant extension so that it is limited to the surgery
department (6211) so that it does not pop up in others.
• DO NOT FORGET to build this element into all P&Ls
and cost analyses, otherwise you are understating the
Using the Data: Worksheets for Cost and
Margin Analysis
• 0050 Encounter Component Costs by Dept
• 0332 Service Line Margins Template Specialty DVI
• REMEMBER: To get full cost in a worksheet, you MUST
include the extended data to pick up the full cost of
implants. The extended data is NOT in any of the
summarized cost components!
• If you do day-of-stay cost analysis, the extended data
will not be by day of stay.
0050 Encounter Component Costs by Dept
0332 Service Line Margins Template Specialty DVI
Take aways on Extended Data for Implants:
• How to implement extended encounter data
• Different ways to handle the problem of implant detail
Case Study: Extended Encounter Data for
Audit Purposes
• Instead of matching by merging two reports in Excel,
load the encounter level data to HPM and use
Worksheet to compare
Note different applications:
1. Straight from interface
2. Audit from Trendstar
3. Net revenue
4. Anything transformed, retain as original source value
Where extended data is found in the data hierarchy – it can be used in all apps
This extension contains the original source values before transformations;
Extremely helpful in proving that your have the same billed DRG, MDC and
Payor you started with.
Audit to prove balancing of detail and summary data, also correct interpretation of
payment and adjustments at detail and summary levels.
Calc to Zero
Charges – Payments – Adjustments – Balance = 0
When this result is not found, some part of the data is not
loading correctly.
Note 37.9 mill in calc to zero in new HPM data, while original, extended data is
closer to zero.
Various audits have proven useful.
Compare key encounter fields from TRENDSTAR
with HPM. More often, we identify problems that
existed in TRENDSTAR that were never detected.
Take aways of Audit Encounter Extensions
• Encounter Extensions can be added as needed
• Encounter Extensions can be loaded from flat files
• Audit handling of detailed transactions from patient
• Audit costing results pre and post HPM
• Audit pre and post HPM revenue results
Case Study: Encounter Events – Creative
• HPM encounter groupings have limitations
• No groups of groups
• No use in columns – only rows
• Makes it impossible to add new groupings at the end of HBI
encounter subsets
• Events do not have these limitations
Here you can see use
of the events, both
detail and summary in
Note initial events in “Payor Group” category effectively group them.
Events in “Summary” category group the initial events.
Caveat: Events must be manually reapplied
Events are easily defined with encounter qualifiers
This is where you will find Events
in the encounter data hierarchy
Take aways on Creative Use of Events
• It is easy to create and use Events
• Events give you powerful ways to organize and use
your HPM encounter data
• The downside, that they must be reapplied manually
seems to be offset by how powerful they are as an
alternative to the grouping application
HPM Worksheet for Net Revenue
• Using worksheet to create a hybrid revenue amount for
service line P&Ls
Actual payments
Patient accounting expected
PMOD expected
Estimate on charges and payor percent
• Which to use depends on payor, patient type, payments
and balances
• Logic we have previously done in Access or SQL
Server can be done in HPM Worksheet
• Caveats: Complexity, handling null values
Base data about the cases are at
the start of the worksheet
More useful base data.
Making Boolean columns with zeros if
false, 1 if true. If some values being
tested are null, the result value here
is still 1 or 0.
More Boolean columns
Default rates based on charges
come from a custom object, to be
used as a last resort.
Several columns then call for actual
payment if conditions in the Boolean
columns are met. In this case, higher
balance cases with significant
payments, the payments are used.
This case will use actual payments
for low balance cases
The answer column combines the other
five columns, whose answers are
mutually exclusive. It is compared with
answers from another method that are
stored in a custom object.
Take aways on Net Revenue Worksheet
• HPM Worksheet can be used to help select the most
logical value to use
• You must be aware of the effects of null values on
calculations – it is not the same thing as zero.
• Next we’ll show you how the default rate got into the
custom object.
• After that we’ll show you how to pipe the answer from
worksheet to HBI and back again to load a model
revenue field.
Custom Object for Benchmark Data
• Needed to match benchmark values to patients
• Simple way to extend the data
Locating custom object manager
With authorization, you may build new custom objects. Plan
carefully, as they cannot be deleted easily once built.
Linking fields determine how a value is “targeted” to a patient
record. The link fields are not needed in the worksheet, the
system is smart enough to link behind the scenes.
Not the header and field identifier at start of the record. This can be built in Excel
using a formula like =“CODATA~&A1&”~”&A2&”~”&A3 to concatenate the contents
of cells A1, A2 and A3 together with ~ as the delimiter
To integrate the data, you need permission to use Data Integrator
First you set up the source definition, which is where you
tell the system to use the standard custom object layout.
Then you add a process definition using that source.
By telling it the source, it knows the target is a custom object.
And lets you choose a target from among the available custom objects.
After integrating the data, be sure to audit the integration run using this option.
One header record did not integrate, as expected.
This is where the custom object is found in Worksheet’s data hierarchy.
When used in a worksheet, the data for a patient is retrieved
based on the keys and content of the custom object
Take aways from Custom Objects
• Custom objects useful for benchmark data
• Easy to format the data using Excel
• Use HPM to integrate your data instead of patching
things together in Excel or Access
• An application to support net revenue calculations
Overview: Modeling with EBB
• Strategic and tactical decision making
• Predict financial consequences of decisions
Build EBB Model from Encounter Data
Service item cost
Model revenue field filled
Service line
Payor grouping
Physician grouping
There are many more screens that set the build options.
Modify Model
• After building the model, copy it
• Save the copy to have a point of comparison in
reporting later
• Make other copies along the way as needed
Service Editor Navigation
List view shows all names underneath highlighted level
in the service tree
Patient Type
Service Key
Service Data view shows number of services, ALOS,
charges, and reimbursement
This is an example of List view
Service Utilization view shows average
service item utilization per service
Apply will
update all
of the EBB
affected by
made in
this editor
Changing Number of Services or LOS by
2. Select the service data view.
1. Select the
level in the
service tree at
which you
want to make
changes (in
this example
Angina was
3. Select which
periods you
want to make
changes for
using ctrl-left
mouse click.
4. Using either
the right
mouse menu,
or Edit menu,
“number of
services” or
LOS”. Enter
the desired
value in the
Changing Service Item Utilization
1. Select a
for a given
service /
3. Select
average units
from the Edit
menu and
make your
2. Select one or
more service
You may also…
Add service (product in a product line)
Add payor
Replace service items
Change service item utilization by service
Edit department costs and reallocate
Change the order of the dimensions
• E.g. Payor above service line means payor changes affect all service
lines for the payor
• Perform elementary revenue modeling (do detailed models first in
PMOD or 3M)
Does not use Worksheet
Has its own built in reporting tool
You choose rows, it has columns
Choice of predefined column formats
Export to Excel or Access as needed
Budget to Actual Variance Report
2 Model Variance
Multiple Models
Single Model Periodic
Single Model Drill
Service Item Detail Drill
EBB reports can be exported as delimited files, directly to HBI or to
Optional: Update Budget with Volume and Price
1. Select a Model.
2. Select an Entity from
your model.
3. Select a dataset that
contains the entity
you selected. This is
the dataset that will
be updated with the
results of your
4. Optionally,
qualify your
data that you
wish to
5. Click on Submit
Loading Model Revenue Fields
• Encounter Based Modeling with EBB
• Depends on:
Patient encounter activity
Detailed cost accounting
Revenue per case must be in expected or model payment fields
Load from PMOD or integrate from file
Loading Model Revenue Fields for EBB
• Requirement of using EBB: must have patient revenue in
expected or model payment fields
• Expected and model payment fields can be loaded by
• Not everyone owns PMOD
• Not everyone who owns PMOD tries to try to cover 100%
of cases
• Almost everyone has a report or process that derives net
revenue for each patient
• Choose among payments, PA expected, PCON expected, estimated
• Use Worksheet or Access
• Use HBI SQL Server to format and send file for HPM integration
During EBB Modeling, users may choose which iteration of net revenue they would
like to work with during this model session.
In EBB reporting, the user can choose which cost field to use. Base payment comes
from the field Expected Payment.
Record layout needed to insert model
payment values
CAUTION: If you attempt this procedure, be
sure to first test it thoroughly on a copy of your
dataset to ensure no other changes are made
You may want to consider expert assistance
on this aspect.
Tools Needed to Format Records for HPM
• Access:
• Concatenate fields using & to construct the different records
• UNION query to stack the records in order
• Export text file
• SQL Server:
Concatenate fields using + to construct the different records
UNION ALL to stack the records
A view can be used to hold the code
A DTS package can call the view
Once set up, the DTS can be called by a shortcut or it can be
• The output can be sent to HPM’s source file if the drive is mapped
Code Example in Access – shows union query to stack records, how to
place a header record at the top
To integrate the data you need access to Data Integrator, located here.
You will need a process definition referencing the source file and the target dataset.
The source step identified the file name and type
of interface. Here we define the target dataset.
Data integrator provides this screen to give extra options and allow you to
override the source file used.
Take aways from Loading Model Revenue
• Possible to load these fields in existing records
• Use caution to make sure you are not changing any
• Extremely useful if you want to use EBB for modeling
Synthetic Service Items for ABC
• Activity Based Costing seeks better match of cost and
• Example: Giving cost of the cardiology program to only
cardiology patients – treat like a direct instead of
• Service items based on charges fail us because they
are revenue center driven
• Example: Use patient days or adjusted patient days to
absorb cardiology cost for patients who were in the
cardiology service line
• Problem: There is no charge code that can track days
for a patient in the service line – the patients were on
many nursing units
• Create a set of zero-price charge codes on the CDM
and use them to record each day a patient was in a
given service line. Not a popular solution for a variety
of reasons.
• Create service items in HPM based on the patient
service line and patient days or charges or cost. The
service items do not have to be charge codes (Use
service item types nursing codes or OR codes for
example). Still extra work, but when you really need to
ABC done right, this is one way.
Ways to create service items
• Create service items in the interface
• Service line depends on your definition, usually related to DRG or
diagnosis and procedure
• Duplicating this logic in the interface would be challenging
• For many hospitals, the DRG grouping is done after HPM data is
• Create service items after encounter data is loaded
• Allows patients to be grouped to DRGs and service lines
• More control over the qualifiers to determine service items
• Orthopedic patients with heart issues could get service items for
both service lines
Steps in the process
• Encounter grouping definition and apply
• Worksheet to extract flat file by patient
• Process in Access create records for integrating to
patient records
• Add service items and departments as appropriate
• Integrate new service item data to encounters
• Create price and volume and continue second pass at
Worksheet to extract basis for service items
The HPM worksheet must contain fields needed to identify
the encounter to integrate to, and statistics for each service
line to create service items’ volume from. Note how charges
divided by 100 is used to create a unit value for the new
service item. Service items can have fractional units.
Access application
• Takes in the extract file
• Reformatting many fields, especially dates
• Creates the record types needed, inserting just the data
• Sort the records
File for integration to encounter data
Ongoing maintenance
• In ongoing updates, some of these patient records will
be replaced
• When the extract Worksheet is generated, you must be
careful that the selection criteria includes only cases
that are new or have been replaced since the last time
you generated the extract. Otherwise, you will insert
duplicate service item records in some patients.
Take aways of synthetic service items
• It is possible to insert service items just for costing
• Desirable approach if you want to undertake true
Activity Based Costing (ABC)
• Use caution
HBI Daily Update of Patient Data
• Daily discharge data along with last year’s data helps
us understand how we are doing
Volume of encounters
Payor mix
DRG for intensity
Length of stay adjusted for DRG
Activity by attending physician
• Problem: Takes a lot of processing
• Prior year data is pretty static
• Process it weekly or monthly and combine with the daily
HBI Daily Update of Patient Data
2 AMHBI1.tsv
Daily, 6:01 pm
1 PXHBI1.tsv
15th, 2:07 pm
View selects data
DTS Daily
6:12 pm
DTS Daily
6:20 pm
Daily, 6:35 pm
No overwrite
We build the view first, which compares the cases we loaded before with the
cases that are new or changed, and puts out just the cases that have are not
It does this by choosing only the cases that find no match in the new data
We use three DTS packages to update, since it is really several updates in one day
from different files. Right click on a package to schedule it.
We use the standard DTS templates supplied by McKesson, specifying the
sources file…
…and the target table to load.
If you have not used these templates, they are found in this directory on the HBI
server. You need rights to Enterprise Manager (SQL Server 2003 or earlier) or
SQL Design Studio (Server 2005)
This is where jobs are managed after they are scheduled.
Finished highlight builds everyday with more discharged and coded patients, in
this case.
HBI Daily Census and Productivity
Daily census subset by nurse unit
Daily hours subset from Kronos, using a pull from HBI
Each with own highlights and automation
SQL Server View on HBI to summarize and join them
for a third productivity subset and highlights
Uses a linked server to issue the query for data from HBI to the Kronos report
The SQL logic is stored in the DTS package which pulls back data each night
as a text file to the WTFiles directory.
This is where the logic is located. You can see it graphically by taking the logic
into a view.
The view shows the tables, some on Kronos and some on HBI that are joined.
The query is too complex to be saved in the view.
The Kronos data is very useful
The census data is also useful and is a much simpler data feed, by department
and day.
A series of views summarize the data from payroll and census to the day and
That view becomes the basis for the daily productivity highlight.
Take aways from HBI Productivity
Obtain daily updates of key data
Link it up in SQL Server on HBI
How a linked server works
Replace expensive productivity systems
Roger: [email protected]
Casey: [email protected]
(646) 221-7560
Thank you for attending, and enjoy the conference!
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