Laurel A Copeland, PhD

September 12, 2013

1 
Good Data Practices

 Series Recap

 Session 1: Early Data Planning for Research 

 Session 2: Managing and Documenting Data Workflow

 Session 3: Planning for Data Re-use

2 
Session 4: Research Application 

 Proposal planning and development

 Funding, IRB, and Study Initiation considerations

 Documentation Content and Locations

 Study Design and Implementation

3 
Poll Question #1 

 What is your primary research role? 

 Data analyst/programmer or statistician

 Research coordinator or assistant

 Student, trainee, or fellow

 Investigator with data skills

 Investigator without data skills

 Manager, policy-maker, or other non-research VA 

stakeholder 

4 
Session 4: Outline

 Proposal planning and development

 Funding, IRB, and Study Initiation considerations

 Documentation Content and Locations

 Study Design and Implementation

5 
Proposal planning and development

 Birth of a Research Project 

 During proposal development, the Aims take 1-3 months to 

develop

 Aims inform Methods and Methods inform Aims 

 Funder is identified

 Budget is proposed

6 
Session 4: Outline

 Proposal planning and development

 Funding, IRB, and Study Initiation considerations

 Documentation Content and Locations

 Study Design and Implementation

7 
Funding, IRB, and Study Initiation considerations

 Birth of Surgical Treatment Outcomes for Patients with 

Psychiatric Disorders (STOPP)

1. Systematic review of the topic

2. Knowledge gap identification 

3. IRB protocol

4. Pilot study funded 

Perioperative Outcomes and Safety in the Seriously Mentally Ill 

Elderly (POSSE)

8 
Funding, IRB, and Study Initiation considerations

 Decision: 

 Begin the work before the funding, vs 

 Get the funds to do the work

 Draft a protocol for IRB:

 Forms the basis of a fundable proposal

 Allows work to begin

 Time constraints on unfunded projects

9 
Poll Question #2

 Which best describes your research experience with VA 

administrative databases?

 Have worked directly with VA administrative data myself 

and am adept at DART process

 Have worked directly with VA administrative data myself

 Have collaborated on their analysis but have not pulled or 

manipulated them 

 Have not used VA administrative data at all

10
Funding, IRB, and Study Initiation considerations

 A Beautiful Trap: Unfunded Work

 An IRB-approved protocol can generate:

 Preliminary data

 Baseline papers

 Downside 

 Upside

11
Funding, IRB, and Study Initiation considerations

 Pilot Study - Perioperative Outcomes and Safety in the 

Seriously Mentally Ill Elderly (POSSE)

 Had drafted a protocol for the IRB (LAC, VAL)

 Wanted some funding to work on this IRB-approved 

protocol

12
Funding, IRB, and Study Initiation considerations

 Pilot Study – POSSE

 Identified: 

 VISN 17 New Investigator Award mechanism

 New Investigator – study team expands

 Other team members: what capacity do you need? 

13
Funding, IRB, and Study Initiation considerations

 Pilot Study – POSSE

 Funding was awarded to J E Zeber for 2 years (2007-2009)

 Plan: identify “major surgery” in FY2005

 Defined “inpatient surgery” 

 Worked with surgeons and long lists of CPT and ICD9A 

codes iteratively to define major surgery

14
Session 4: Outline

 Proposal planning and development

 Funding, IRB, and Study Initiation considerations

 Documentation Content and Locations

 Study Design and Implementation

15
Documentation Content and Locations

 Pilot Study – POSSE 

 Met regularly

 Documented meetings immediately with meeting minutes 

emailed to all team members

 Documented all CPT and ICD9A code lists carefully with 

footers to identify what is listed and page numbers

 Used good file names – concise but descriptive

 Saved all documents to the Project Folder

 Kept focused on the goal (define “major surgery”)

16
Documentation Content and Locations

 Project Folders & Binders 

 Research Oversight requires the PI to maintain a hard-copy 

Study Binder

 Data Security requires VA Research Data to be stored within 

VA / in locations approved by IRB

 Reason demands an organized research project directory

17
Poll Question #3

 What level of experience do you have in organizing data, 

data structures, filenames, and variable names?

 Expert, lots of experience, have worked with 1 or more 

schemas

 Moderate, have used a schema for at least one study

 Low, aware of the general idea but haven’t implemented it

 Novice, this is new to me

18
Documentation Content and Locations

19
Documentation Content and Locations

 

20
Documentation Content and Locations

 Project Folders 

 Naming conventions

 Choose one model and stick with it to make it easy for team 

members to find code or output or paper drafts

\00412 Copeland STOPP 

 Or

 \Copeland_STOPP 

 \sas_Copeland_STOPP 

 

21
Documentation Content and Locations

 Project Documentation

 Preserves decisions during study conduct and after study 

closure

 Documented decisions inform manuscripts and reports

 Documented processes allow replication

 Documentation assists in data security, data management, and 

oversight/review

22
Documentation Content and Locations

 Project Documentation: Data

 Save program files (SAS code) in a logical place (e.g., 

Copeland_STOPP\DATA\DERIVE) 

 Document the (SAS) program files

 Filename

 Date initiated

 Programmer(s)

 Brief study description including PI name

 Within the program, tell what you are doing and why

 The next programmer may not have access to the original programmer

 Study must be replicable

23
Documentation Content and Locations

 

*prediabetes.sas*; 

*28feb2008: this setup*; *l a copeland*; *parent setup: schizdiabva.sas*;

* SECTION I ANALYSIS

* SECTION II BUILD DATASET

* VA HSRD IIR 05-326-02: Patterns of Care Veterans with Schizophrenia and/or Diabetes;

* DX Schizophrenia: 295xx omit 295.5;

* DX Diabetes Mellitus: 250.xx 357.2x, 362.0x, 366.41;

* DATA SOU: PM/XM/NM, SE, LAR, PHA, BIRLS, VITALMINI, ENONEPER, SHEP - fy02-fy05;

LIBNAME SD '\\vhastxsas\sas_Copeland_Patterns\DATA'; LIBNAME shep '\\vhastxsas\sas_Copeland_Patterns\DATA\SHEP';

OPTIONS nofmterr nocenter errors=4 mergenoby=warn;

OPTIONS msglevel=i FORMCHAR='|-----+-' formdlim=' ' ps=68 ls=100 nocenter; options font="Lucida console" 8; 

*******************************************; 

   SECTION I ** **; 

   ANALYSIS: PRE-DIABETES STUDY ** **;

*******************************************; 

DATA predm (DROP=priority);

MERGE sd.predm (DROP=priocat:)

 sd.prediab_lac(IN=in1)

 sd.szdm(KEEP=scrssn SELIM_PHYS02 ptsd NCLASSVA02 AOD02-AOD05 prio use_after_death any: hispanic races black)

 sd.labs_gluldl; 

 BY scrssn;

 IF in1;

* study inclusion / exclusion criteria *;

IF rxdiab=1 THEN DELETE; * 39904 ;

IF dmdx=1 THEN DELETE; * 39825 ;

IF prio>.; * 39731 if first (so, 94) ...else 39711 ;

IF use_after_death^=1; * 39804 if first (so 21) ...else 39711 (so an additional 20 over prio=.);

IF anytotcl02=1; * lose 485 ;

 * recodes *;

 prio23678=(prio IN(2,3,6,7,8)); prio4=(prio=4); prio5=(prio=5);

 test02=MAX(fg02,a1c02); test03=MAX(fg03,a1c03); test04=MAX(fg04,a1c04); test05=MAX(fg05,a1c05);

RUN; *this version has the followup a1c/glu vars* 26sep08*17jul09* 264 vars 39226 was 39711 obs *; 

24
Session 4: Outline

 Proposal planning and development

 Funding, IRB, and Study Initiation considerations

 Documentation Content and Locations

 Study Design and Implementation

25
Study Design and Implementation

 From Pilot to Merit Award 

 Aims – the larger study built on lessons learned from Pilot

 Methods – informed by experience

 Preliminary data – available from POSSE for STOPP 

proposal

 Weaknesses of Pilot methods/staffing could be addressed

in larger proposal

26
Study Design and Implementation

 STOPP Aims 

 AIM 1: Compare rates of surgery among VA patients by preexisting severe mental illness status (SMI) status over the period 

FY06-FY09

 AIM 2: Assess 30-day, 90-day, and 1-year postoperative mortality

by pre-existing SMI status (covariate-adjusted models)

 AIM 3: Assess 30-day, 90-day, and 1-year postoperative 

complications (MI, ACS, DVT-PE, ICU admission, pneumonia, 

respiratory failure, sepsis, wound infection, readmission)

27
Study Design and Implementation

 STOPP methods

 Inpatient and outpatient files (PM/XM, SE): dx variables to 

define prior-year Severe Mental Illness (schizophrenia, bipolar 

disorder, PTSD, MDD)

 Inpatient and outpatient files (PM/XM, SE): dx variables to 

define prior-year comorbidity (Charlson; Selim)

 Inpatient and outpatient files (PM/XM, SE, PS/XS, PP/XP): 

procedure codes defined Major Surgery type(s), admission 

defined date of 1st qualifying op

 Inpatient files (PM/XM, PB/XB): postoperative events were 

identified by dx variables (ICD9 codes) for 30-day, 90-day, and 1- year postoperative complications (MI, ACS, DVT-PE, ICU 

admission, pneumonia, respiratory failure, sepsis, wound 

infection, readmission)

28
Study Design and Implementation

 STOPP Methods 

 September PSSG files: contribute VA Priority Status [e.g., 

MDPPRD.MDP.SAS.NED.MAIN.SEP08.VSA.PSSG]

 MINI-VITALS: Best Sex, Best DOB, Best DOB, and 

“use_after_dth_flg” 

 Inpatient and outpatient (PM/XM, SF) files: Period of 

Service

 OEFOIF ROSTER file: OEF/OIF status (special DART 

application required)

29
Study Design and Implementation

 STOPP Methods 

 DSS NDE LAR files: used to define lab-related process 

measures such as “had high cholesterol”

 DSS NDE PHA files: used to define pharmacy-related 

covariates such as “using corticosteroids within 21 days 

prior to admission for surgery”

 NB: DSS NDE’s are now incorporated into Corporate Data 

Warehouse (CDW) and are no longer generated as separate 

SAS datasets

30
Study Design and Implementation

 STOPP Methods 

 Used Encounter (IE) files to determine whether they could 

provide CPT codes for qualifying operations (they could not

be so used)

31
Study Design and Implementation

32 STOPP Methods
Study Design and Implementation

 STOPP Methods

 SAS copies of the flat files 

 Stored the binary versions at our “EXTRACT” level

(COMPRESS=YES)

33
Study Design and Implementation

 STOPP Methods 

 Also because of the size of the files, we converted 

algorithms for race, ethnicity, Selim comorbidity scores, and 

Charlson comorbidity index to macros

 We experimented with various approaches to data 

aggregation and asked HSRData listserv for input

34
Study Design and Implementation

 STOPP Progress

 Each paper has a sub-folder within \REPORT

 All abstracts are in a single sub-folder within \REPORT

\Copeland_STOPP 

 \DATA

 \DOCS

 \REPORT 

 \ABSTRACTS

 \MORTCARD 

 \SUICIDE

 Most papers needed a tailored analytic database as well, saved 

within \DATA (upper level)

35
Study Design and Implementation

 STOPP Progress

 Team meetings to develop definitions, study designs, and 

papers 

 Data core meetings to monitor implementation of team 

decisions and generate patient-level dataset(s)

 Aims determine primary papers

 Mentees/colleagues determine secondary papers

36
Study Design and Implementation

 Single-site to Dual-site

 STOPP funded April 2010

 PI & co-Inv moved to a different VAMC in August 2010

 Prior to the move:

 Decided whether data would stay put

 Filed an application with the new VA IRB

 Began discussions with new VA’s AO regarding moving funds

37
Study Design and Implementation

 A Dual-site Study Meets ORO

 Or, how to attract unwanted attention...

 ORO visited CTVHCS 3x in 2012

 CTVHCS converted from using Policies to using SOP’s

 ORO reviewed our SOP’s and our studies and requested many 

changes 

 ORO noted that some IRB-approved studies “sounded like” data 

repositories were being proposed

 I thought STOPP would be a good source of a Data Repository

38
Study Design and Implementation

 STOPP Data Repository

 STOPP concluded funding in March 2013

 Drafted the SOP and then STOPP Data Repository Protocol

 Will permit use of the massive dataset to address aims not 

related to Surgical and Post-operative experiences of Veterans 

with Severe Mental Illness

 VINCI as a data storage location was added to STOPP 

Protocol by IRB amendment and is specified in the Data 

Repository Protocol

39
Contact Information

Laurel A Copeland, PhD MPH

Center for Applied Health Research

A research center sponsored by Central Texas Veterans Health 

Care System jointly with Scott & White Healthcare

2102 Birdcreek Drive

Temple TX 76502

Laurel.Copeland@va.gov

254-215-9880 

40
41
Session 4: Research Application

 Recap

 Proposal planning and development

 Funding, IRB, and Study Initiation considerations

 Documentation Content and Locations

 Study Design and Implementation

42
Session 5: Research Application

 Preview

 Planning for documentation of study design & 

measurement

 Data cleaning

 Construction of cohort

 Outcomes construction

 Covariate construction

 Linkage of primary (survey) data & VA secondary data

 Summary: Value of documentation

43