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1
#301H - It’s 5 o’clock Somewhere
and the Chief of Staff Just
Called…
Rob Silverman, PharmD
2
4:56 PM4:56 PM
• The Pharmacist CAC is logging off for the
day when the phone rings…
– “Pharmacy Informatics, how may I help you?”
– “Hi … this is Dr. Tee. Can you get me a report
of all of our Veterans that are taking
insulin?”
– “Sure … no problem. I can do that with a
FileMan report before I leave.”
–“Thanks … I appreciate it.”
3
4:57 PM4:57 PM
• The phone rings again…
– “Pharmacy Informatics, can I help you?”
– “Hi … it’s Dr. Tee again. Can I get a list of
all our diabetic Veterans?”
– “Okay. I can run this through the ARCP
reports.”
– “That’s wonderful. I’ll see you shortly.”
4
4:58 PM4:58 PM
• Guess what … the phone rings again!
– “Pharmacy Informatics”
– “Dr. Tee. On that diabetics report, just list the
new diabetics, please.”
– “Umm…”
– “Thanks. Gotta run.”
5
4:59 PM4:59 PM
• You know what happens now… <ring>
– “Informatics”
– “Tee. Scratch those first reports. Run it for
all new diabetics that are on insulin.”
– “So you mean …”
– “As soon as you can. Thanks.”
6
5:00 PM5:00 PM
• As the rest of us hear the 5 o’clock
whistle…
• <RING> <RING>
– “Hello?”
– “One more criterion. Make it a report of all
diabetics, on insulin, and whose A1c is greater
than 8%”
– “Right …” <click>
• “Now how am I going to do
THAT?”
7
Introducing…
REMINDER PATIENT LISTS!
8
AnalogiesAnalogies
• In order to picture the process of creating
Reminder Patient Lists, there are two
analogies that will be used:
– Electrical Converter Plugs
– Panning for Gold
• Just look at the pictures for now; we’ll
come back to explain how it relates
momentarily…
9
Electrical Converter PlugsElectrical Converter Plugs
10
Panning for GoldPanning for Gold
11
What makes Reminder Patient ListsWhat makes Reminder Patient Lists
so useful?so useful?
• Utilizes ^PXRMINDX, a cross-reference
(index) in VistA that is not only fast, but
allows access to many clinical domains of
patient data (labs, medications, vitals,
diagnosis codes, etc.)
• Allows you to run reports without having to
pre-define a sample (cohort) of patients
• Ideal for any time you get a request that
starts, “I need a list of all patients that …”
12
Are there RULES to the game?Are there RULES to the game?
• Patient Lists are created from RULE SETS
(or from reminder due reports…)
• Rule Sets can be created from three types of list rules
(components, widgets, whatnots…)
– FINDING RULES
– REMINDER RULES
– PATIENT LIST RULES
13
Finding RulesFinding Rules
• A Finding Rule is the connection for a
REMINDER TERM into a rule set
• Anything that can be referenced in a
reminder term can be plugged into a finding
rule
– Medications, Vitals, Labs, Orderable Items
– Diagnosis Codes
– Exception: computed findings  we’ll come back
to this later, too
• Keep picturing the chain of extension cords
and electrical converters…
14
Reminder RulesReminder Rules
• Reminder rules allow you to take the more
complex logic of a reminder definition (the
COHORT LOGIC) and plug it into a rule
set
• This is the often asked about “L” usage
type in reminder definition setup
15
Patient List RulesPatient List Rules
• A Patient List Rule is the connection that
allows you to take a previously created
patient list and plug it back into another
rule set
• This could be considered an electrical
short circuit, because you may have used
a rule set to create the patient list, and
now you’re using the patient list in another
rule set
16
Naming ConventionsNaming Conventions
• I like to suffix all components with their
type
– Allows you to use similar names for different
widgets
– VeHU Classes also use prefixes to identify
your own work; this part is not necessary for
production account work
17
Abbreviations/SuffixesAbbreviations/Suffixes
• PL – Patient List
• RS – Rule Set
• FR – Finding Rule
• RR – Reminder Rule
• PLR – Patient List Rule
• Also…
– TERM, TAXONOMY
– LL (Location List)
18
RecapRecap
• The different components give us an idea
of “what” can be plugged together
• Next, we’ll discuss “how” they are to be
plugged together
19
OperationsOperations
• There are four ACTIONS (called
‘operations’) that can be used to define a
rule set
– ADD
– SELECT
– REMOVE
– INSERT FINDING
• This is where the gold panning analogy
comes in handy…
20
Rules of OperationsRules of Operations
• The first operation (Sequence #1) must be
to ADD patients to the list  you have to put
some river water into the pan
• Subsequent operations may
– ADD more patients (bigger scoop)
– SELECT patients (shake, and your criteria define
items that STAY in the pan)
– REMOVE patients (shake, and your criteria define
items that FALL OUT of the pan)
– INSERT FINDING (adds data for use in the
demographic report)
21
Rules about Sequence #1Rules about Sequence #1
• So we know that sequence #1 must ADD
patients…
• and that the list rule used could be a FR,
RR or PLR…
• and that FRs are the connection plugs for
terms…
• and that terms can contain finding types
such as lab results or computed findings…
22
Rules about computed findingsRules about computed findings
• …but you may not use a computed finding
in sequence #1…
• because it would need to know who the
patient is in order to ‘compute’ …
• except for a particular type of computed
finding called ‘LIST’, which is made
precisely for this purpose
23
Summarizing that never-endingSummarizing that never-ending
storystory
• Computed findings of the SINGLE or
MULTIPLE type may not be connected
into sequence #1 of a rule set
• You may use computed findings of the
LIST type, because they are designed
specifically for the purpose of ADDING
patients to a list
• The typical SINGLE/MULTIPLE computed
finding can still be used to select/remove
patients in subsequent sequences
24
Designing the Report
Hands-On Preparation
Visualize the Outcome…
25
Final Output & WorkFinal Output & Work
BackwardsBackwards
• A list of patients that are
– Diabetic
– On Insulin
– Last A1c is greater than 8%
• It’s a list … so that will be a PATIENT
LIST (PL)
26
Patient ListPatient List
• To create a Patient List, one of our options
will be to use a Rule Set (RS)
– ADD Diabetics
– SELECT patients on insulin
– SELECT patients with A1c greater than 8%
• Does the sequence of the above
criteria really matter?
27
TheThe SELECTSELECT OperationOperation
A1c >
8%
On Insulin Diabetics
The
intersection
of the three
circles
represents
our final
output
Equivalent to
Boolean logical
AND
28
Rule SetRule Set
• Rule Sets are comprised of
– Finding Rules (FR), Reminder Rules (RR)
and/or Patient List Rules (PLR)
• In this case, Finding Rules can be used to
identify the three types of information
required
– Diagnosis Codes
– Medications
– Lab Results
29
Finding RulesFinding Rules
• Finding Rules are the list rule component
used to connect Reminder TERMS into
Rule Sets
• Almost anything that you can normally do
with a term can be used
– Date Ranges
– Conditions
– All the usual finding types
– Remember the exception for
Computed Findings
30
Reminder TermsReminder Terms
• Diagnosis Codes
– We’ll need a TAXONOMY
• Medications
– Can choose from VA GENERIC (DG), VA
CLASS (DC), DRUG (DR) or ORDERABLE
ITEMS (OI)
• Lab Results
– That’s the easiest … just use an LT finding!
31
Medication Findings - 1Medication Findings - 1
• National Drug File
– VA GENERIC (DG): From VA PRODUCT file
#50.68
– VA CLASS (DC): From VA DRUG CLASS file
#50.605
– Nationally standardized and easily exported
32
Medication Findings - 2Medication Findings - 2
• Local Files
– DRUG (DR): From DRUG file #50; requires
mapping when sharing between sites
• The receiving site must identify the appropriate
entries that have the same clinical meaning as the
reminder component from the sending site
– ORDERABLE ITEM (OI): From CPRS
Orderable Item File #101.43, equivalent to
Pharmacy Orderable Item File #50.7. This file
requires mapping when sharing between
sites, contains non-pharmacy items, and also
finds orders that have been placed (pending)
but not yet finished by the pharmacist
33
TaxonomiesTaxonomies
• Can find ICD-9 codes, CPT codes and
other procedure codes
• Can search problem lists, encounter
forms, radiology codes and the inpatient
diagnosis codes (PTF file)
• Utilizes coding ranges
• Diabetes is identified by the ICD-9 code
range 250.xx (specifically 250.00 through
250.93)
34
End of the Road – Turn Around!End of the Road – Turn Around!
1. Build Taxonomy
2. Taxonomy into Term, Medication into
Term, Lab Result into Term
3. Terms into Finding Rules
4. Finding Rules into Rule Set
a. INSERT FINDING Operation?
5. Rule Set used to Create Patient List
6. Display Patient List and Demographic
Report
35
Ready to try it?
Hands-On Experience
36
How the Account Was DesignedHow the Account Was Designed
There are 100 patients set up on the CNN account
A1c >
8%
Diabetics
The
intersection
of the three
circles
represents
our final
output
Patients 1 through
75 are diabetic
Even
numbered
patients
between 26
and 80
A1c values assigned as
follows:
Patients 1-25 = 6.5%
Patients 26-50 = 7.5%
Patients 51-76 = 8.5%
Patients 77-90 = 5.5%
On Insulin
37
Questions / Contact InformationQuestions / Contact Information
Rob Silverman
Robert.Silverman@va.gov
708-202-5040

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Bicpresentation14jan2010 13129467760471-phpapp02-110809224528-phpapp02

  • 1. 1 #301H - It’s 5 o’clock Somewhere and the Chief of Staff Just Called… Rob Silverman, PharmD
  • 2. 2 4:56 PM4:56 PM • The Pharmacist CAC is logging off for the day when the phone rings… – “Pharmacy Informatics, how may I help you?” – “Hi … this is Dr. Tee. Can you get me a report of all of our Veterans that are taking insulin?” – “Sure … no problem. I can do that with a FileMan report before I leave.” –“Thanks … I appreciate it.”
  • 3. 3 4:57 PM4:57 PM • The phone rings again… – “Pharmacy Informatics, can I help you?” – “Hi … it’s Dr. Tee again. Can I get a list of all our diabetic Veterans?” – “Okay. I can run this through the ARCP reports.” – “That’s wonderful. I’ll see you shortly.”
  • 4. 4 4:58 PM4:58 PM • Guess what … the phone rings again! – “Pharmacy Informatics” – “Dr. Tee. On that diabetics report, just list the new diabetics, please.” – “Umm…” – “Thanks. Gotta run.”
  • 5. 5 4:59 PM4:59 PM • You know what happens now… <ring> – “Informatics” – “Tee. Scratch those first reports. Run it for all new diabetics that are on insulin.” – “So you mean …” – “As soon as you can. Thanks.”
  • 6. 6 5:00 PM5:00 PM • As the rest of us hear the 5 o’clock whistle… • <RING> <RING> – “Hello?” – “One more criterion. Make it a report of all diabetics, on insulin, and whose A1c is greater than 8%” – “Right …” <click> • “Now how am I going to do THAT?”
  • 8. 8 AnalogiesAnalogies • In order to picture the process of creating Reminder Patient Lists, there are two analogies that will be used: – Electrical Converter Plugs – Panning for Gold • Just look at the pictures for now; we’ll come back to explain how it relates momentarily…
  • 11. 11 What makes Reminder Patient ListsWhat makes Reminder Patient Lists so useful?so useful? • Utilizes ^PXRMINDX, a cross-reference (index) in VistA that is not only fast, but allows access to many clinical domains of patient data (labs, medications, vitals, diagnosis codes, etc.) • Allows you to run reports without having to pre-define a sample (cohort) of patients • Ideal for any time you get a request that starts, “I need a list of all patients that …”
  • 12. 12 Are there RULES to the game?Are there RULES to the game? • Patient Lists are created from RULE SETS (or from reminder due reports…) • Rule Sets can be created from three types of list rules (components, widgets, whatnots…) – FINDING RULES – REMINDER RULES – PATIENT LIST RULES
  • 13. 13 Finding RulesFinding Rules • A Finding Rule is the connection for a REMINDER TERM into a rule set • Anything that can be referenced in a reminder term can be plugged into a finding rule – Medications, Vitals, Labs, Orderable Items – Diagnosis Codes – Exception: computed findings  we’ll come back to this later, too • Keep picturing the chain of extension cords and electrical converters…
  • 14. 14 Reminder RulesReminder Rules • Reminder rules allow you to take the more complex logic of a reminder definition (the COHORT LOGIC) and plug it into a rule set • This is the often asked about “L” usage type in reminder definition setup
  • 15. 15 Patient List RulesPatient List Rules • A Patient List Rule is the connection that allows you to take a previously created patient list and plug it back into another rule set • This could be considered an electrical short circuit, because you may have used a rule set to create the patient list, and now you’re using the patient list in another rule set
  • 16. 16 Naming ConventionsNaming Conventions • I like to suffix all components with their type – Allows you to use similar names for different widgets – VeHU Classes also use prefixes to identify your own work; this part is not necessary for production account work
  • 17. 17 Abbreviations/SuffixesAbbreviations/Suffixes • PL – Patient List • RS – Rule Set • FR – Finding Rule • RR – Reminder Rule • PLR – Patient List Rule • Also… – TERM, TAXONOMY – LL (Location List)
  • 18. 18 RecapRecap • The different components give us an idea of “what” can be plugged together • Next, we’ll discuss “how” they are to be plugged together
  • 19. 19 OperationsOperations • There are four ACTIONS (called ‘operations’) that can be used to define a rule set – ADD – SELECT – REMOVE – INSERT FINDING • This is where the gold panning analogy comes in handy…
  • 20. 20 Rules of OperationsRules of Operations • The first operation (Sequence #1) must be to ADD patients to the list  you have to put some river water into the pan • Subsequent operations may – ADD more patients (bigger scoop) – SELECT patients (shake, and your criteria define items that STAY in the pan) – REMOVE patients (shake, and your criteria define items that FALL OUT of the pan) – INSERT FINDING (adds data for use in the demographic report)
  • 21. 21 Rules about Sequence #1Rules about Sequence #1 • So we know that sequence #1 must ADD patients… • and that the list rule used could be a FR, RR or PLR… • and that FRs are the connection plugs for terms… • and that terms can contain finding types such as lab results or computed findings…
  • 22. 22 Rules about computed findingsRules about computed findings • …but you may not use a computed finding in sequence #1… • because it would need to know who the patient is in order to ‘compute’ … • except for a particular type of computed finding called ‘LIST’, which is made precisely for this purpose
  • 23. 23 Summarizing that never-endingSummarizing that never-ending storystory • Computed findings of the SINGLE or MULTIPLE type may not be connected into sequence #1 of a rule set • You may use computed findings of the LIST type, because they are designed specifically for the purpose of ADDING patients to a list • The typical SINGLE/MULTIPLE computed finding can still be used to select/remove patients in subsequent sequences
  • 24. 24 Designing the Report Hands-On Preparation Visualize the Outcome…
  • 25. 25 Final Output & WorkFinal Output & Work BackwardsBackwards • A list of patients that are – Diabetic – On Insulin – Last A1c is greater than 8% • It’s a list … so that will be a PATIENT LIST (PL)
  • 26. 26 Patient ListPatient List • To create a Patient List, one of our options will be to use a Rule Set (RS) – ADD Diabetics – SELECT patients on insulin – SELECT patients with A1c greater than 8% • Does the sequence of the above criteria really matter?
  • 27. 27 TheThe SELECTSELECT OperationOperation A1c > 8% On Insulin Diabetics The intersection of the three circles represents our final output Equivalent to Boolean logical AND
  • 28. 28 Rule SetRule Set • Rule Sets are comprised of – Finding Rules (FR), Reminder Rules (RR) and/or Patient List Rules (PLR) • In this case, Finding Rules can be used to identify the three types of information required – Diagnosis Codes – Medications – Lab Results
  • 29. 29 Finding RulesFinding Rules • Finding Rules are the list rule component used to connect Reminder TERMS into Rule Sets • Almost anything that you can normally do with a term can be used – Date Ranges – Conditions – All the usual finding types – Remember the exception for Computed Findings
  • 30. 30 Reminder TermsReminder Terms • Diagnosis Codes – We’ll need a TAXONOMY • Medications – Can choose from VA GENERIC (DG), VA CLASS (DC), DRUG (DR) or ORDERABLE ITEMS (OI) • Lab Results – That’s the easiest … just use an LT finding!
  • 31. 31 Medication Findings - 1Medication Findings - 1 • National Drug File – VA GENERIC (DG): From VA PRODUCT file #50.68 – VA CLASS (DC): From VA DRUG CLASS file #50.605 – Nationally standardized and easily exported
  • 32. 32 Medication Findings - 2Medication Findings - 2 • Local Files – DRUG (DR): From DRUG file #50; requires mapping when sharing between sites • The receiving site must identify the appropriate entries that have the same clinical meaning as the reminder component from the sending site – ORDERABLE ITEM (OI): From CPRS Orderable Item File #101.43, equivalent to Pharmacy Orderable Item File #50.7. This file requires mapping when sharing between sites, contains non-pharmacy items, and also finds orders that have been placed (pending) but not yet finished by the pharmacist
  • 33. 33 TaxonomiesTaxonomies • Can find ICD-9 codes, CPT codes and other procedure codes • Can search problem lists, encounter forms, radiology codes and the inpatient diagnosis codes (PTF file) • Utilizes coding ranges • Diabetes is identified by the ICD-9 code range 250.xx (specifically 250.00 through 250.93)
  • 34. 34 End of the Road – Turn Around!End of the Road – Turn Around! 1. Build Taxonomy 2. Taxonomy into Term, Medication into Term, Lab Result into Term 3. Terms into Finding Rules 4. Finding Rules into Rule Set a. INSERT FINDING Operation? 5. Rule Set used to Create Patient List 6. Display Patient List and Demographic Report
  • 35. 35 Ready to try it? Hands-On Experience
  • 36. 36 How the Account Was DesignedHow the Account Was Designed There are 100 patients set up on the CNN account A1c > 8% Diabetics The intersection of the three circles represents our final output Patients 1 through 75 are diabetic Even numbered patients between 26 and 80 A1c values assigned as follows: Patients 1-25 = 6.5% Patients 26-50 = 7.5% Patients 51-76 = 8.5% Patients 77-90 = 5.5% On Insulin
  • 37. 37 Questions / Contact InformationQuestions / Contact Information Rob Silverman Robert.Silverman@va.gov 708-202-5040

Notes de l'éditeur

  1. The receiving site must identify the appropriate entries that have the same clinical meaning as the reminder component from the sending site.