# Presentation: 139335

## Validating the Patient Safety Indicators (PSIs) in the VA: a Multi-Faceted Approach 

**Funding: VA Health Services Research **
**and Development (HSR&D) Service **
**SDR 07-002 : 10/01/07- 9/30/11**
***Amy Rosen, Ph.D., Principal Investigator***

**Notes:**
Would also like to thank my MANY collaborators across multiple VA centers: Bedford VA Center of Excellence, Boston VA, and also Boston University,  AHRQ, etc.

## Project Team

- Collaboration among
- VA’s HSR&D Service
- National Center for Patient Safety (NCPS) and
- AHRQ (QI team and individual investigators)
- VA and non-VA clinicians, surgical experts, nurse abstractors
- National steering committee:
- Representatives from VA Office of Quality Performance, NCPS
- Nursing Services, Surgery, Patient Care Services
- Selected members of the AHRQ QI team
- Selected Patient Safety/QI Managers and other potential end-users

**Notes:**
Health services researchers, methodologists, clinicians, key stakeholders in VA and outside VA

## Overall Project Goal 

- Develop a validated and reliable set of patient safety measures that broadly reflect the interests of key VA stakeholders, *but that are* *generalizable beyond the VA.*
- Specific Objectives:
- Develop collaborations with key stakeholders to guide in PSI selection and validation
- Investigate the criterion validity of the PSIs by review of the VA’s EMR
- Identify processes and structures of care associated with individual PSIs
- Revise and improve the PSIs using multiple data sources and settings of care
- Assess the utility validity of the PSIs for QI and performance measurement

**Notes:**
I presented these goals last year, and thought I’d present them again so you can see what we have done and what we have left to do

## Goal 1: Develop Stakeholder Collaboration

- Stakeholders’ meeting (Dec, 2007):
- Approved selection of PSIs
- Approved plan to validate AHRQ’s Phase I/Phase II PSIs
- Reviewed field consultation interview questions
- Recommended focus on general questions on patient safety
- Suggested less attention on specific PSIs in field consultations
- Field consultations held to examine the validity of the PSIs, not to judge facilities’ performance
- Contact with stakeholders subsequent to meeting
- Approved final interview protocols “TO/THRU” memo to sites asking them to participate

**Notes:**
FOR NOTES: 
Stakeholder role is very important to this project and VA wants research to collaborate actively with key stakeholders who might use PSIs or advise on their use. The group acts as an oversight group. Therefore, our mandate was to meet regularly throughout project (face-to-face annually, by phone as needed). We had our first face to face meeting in Dec- here’s what we did (read bullets). We met with about 8 stakeholders including 
 Ana Alt-White Nursing, Len Pogach, Peter Almenoff, Carol Bills, Lisa Mezzia, AHRQ QI folks, Vickie Montague, Ralph De Palma.
They approved selection of PSIs, etc. Meeting very successful but also interesting in terms of their guidance related to site visits. Because of their concerns, we decided to call the site visits “field consultations” rather than site visits in order to soften what we were doing- prevent judging.

## Goal 2: Identify False Positives Are Cases Flagged by the AHRQ PSIs Present in the EMR? 

- Obtained national access to EMR: “VistaWeb”
- Hired and trained two nurse abstractors to conduct chart abstraction
- Modified AHRQ Phase I and Phase II chart abstraction tools for VA
- Pilot testing and clinician review
- Five tools “ready for prime time,” five almost ready, five being developed de novo
- Completed validation of PE/DVT
- Currently abstracting charts for iatrogenic pneumothorax
- Currently piloting web-based application (InfoPath) for gathering and entering chart-abstracted data

**Notes:**
NOTES: 
Validating 15 PSIs (except obstetric ones, transfusion reaction)
Modified tools primarily to help abstractors- this was done iteratively thru pilot testing, nurse suggestions, and then clinician review. Most modifications related to the logic of the questions, such as the order, clarification of meanings of terms, etc. Pneumothorax currently being abstracted, so far getting good IRR, also few false positives. 
We have created an electronic chart abstraction tool using InfoPath software. In addition to eliminating the use of paper, privacy risks associated with patient data are significantly reduced and also it reduces abstractor error.
-the next slide gives an example. Still working out the kinks but this will allow us to dump data from chart into database.

## Slide 6

**Notes:**
This slide shows the conditional formatting features of InfoPath.
CLICK #1
When “yes” is selected, additional fields for data entry appear.
CLICK #2
In the bottom section here, when “not excluded” is checked, none of the other answers (outlined in red) are available. 
CLICK #3
These features enable more efficient chart abstraction. 

## Hospital Selection 

- Ran PSI software (v. 3.1a) on VA inpatient data (2003-2007)
- Obtained rates of individual PSIs and PSI composites
- Used 12 PSIs
-  PSIs 1-15
-  Excluded PSIs 1, 5, 8
- Population:
-  158 VA hospitals
- Sample for chart abstraction:
-  28 hospitals, 112 charts per PSI

**Notes:**
NOTES: 
Ran PSI software on VA data...using only 12 PSIs
Hospitals in sample were somewhat “representative” of all VA hospitals --couldn’t sample all 158 hospitals so we had to select a reasonable # that would provide some representation of VA hospitals, geographic distribution, and also allow for coding variation.
We excluded PSIs that were not frequent and ran software on 12 PSIs 

## Sample Selection Methodology

- Stratified population by observed and expected #s of PSIs
- Group 1: at least 4 observed and 4 expected  (n =28)
- Group 2: at least 2 observed and 2 expected  (n=33)
- Group 3: at least 1 observed and 1 expected  (n=18)
*Total for Groups 1-3: *_*79 hospitals*_
- Ranked 79 by AHRQ PSI composite (denominator weights)
- Chose top 3 and bottom 3 from each group
- Randomly selected from remaining hospitals within each group: group 1=4, group 2=4, group 3=2 to obtain 28 hospitals (10, 10, and 8, respectively)
- Geographic distribution and ICU severity taken into account
- Selected 6 hospitals for field consultations and ranked them based on PSI composite
- Geographic location and size taken into account

**Notes:**
We calculated observed and expected PSI rates across all VA hospitals and divided hospitals into 3 groups based on specific criteria. Group 2 excludes Group 1
Group 3 excludes Groups 1,2.
(Expected: calculated as overall VA rate * individual facility PSI denominator)
For PSIs 1,5,8, we take wherever we can. We want 4 charts per PSI in each of the 28 facilities (4 * 15* 28= 1680 charts). If facility does not have 4 charts, we borrow from other facilities-no more than 4 extra per facility
For 6 hospitals for field consultations, we used denominator weights from PSI composite from 79 facilities and 2006-2007 data

## Chart Abstraction

- _PE/DVT_
- Conducted retrospective EMR review of 112 flagged cases
- Conducted inter-rater reliability (IRR) throughout EMR review
- 28 cases (25% of all charts) reviewed for IRR due to:
- large numbers of exclusions
- IRR > 90%
- 89% agreement rate achieved with 1st IRR, 94% with 2nd IRR
- Issues
- length of time to complete chart abstraction (11⁄2 hours for full record; 20 minutes for false positives)
- problems with accessing VistaWeb

**Notes:**
( during pilot –every 5 charts or so, before formal abstracting, and then periodically throughout abstraction until we reached agreement above 90%)
IRR: looked at core questions as well as individual items. Looked at agreement on true positives and false positives. IRR between 2 nurses/nurse did IRR

## Technical Specifications of PE/DVT

- Numerator:
- Discharges among cases meeting the inclusion and exclusion rules for denominator
- ICD-9-CM codes for PE/DVT in any secondary diagnosis field
- Denominator:
- All surgical discharges age 18 and older
- defined by specific DRGs and an ICD-9-CM code for an OR procedure
- Exclusion criteria for all cases:
- preexisting (principal diagnosis or secondary diagnosis present on admission, if known) PE/DVT
- procedure for interruption of vena cava the only OR procedure
- procedure for interruption of vena cava occurs before or on the same day as first OR procedure
- MDC 14 (pregnancy, childbirth, and puerperium)

**Notes:**
Definition:
Cases of deep vein thrombosis (DVT) or pulmonary embolism (PE) per 1,000 surgical discharges with an operating room procedure

## Post-operative PE/DVT Validation Results

**Total # of cases: 112**

**Notes:**
A few issues are crucial in these definitions:
1) The differentiation between POA, Pre-Procedure and Old History was based on the diagnosis date not the suspected diagnosis date. A Pre-Procedure label does not mean that the DVT or PE was not present on admission, but it means that the diagnosis of PE or DVT was made after the admission, but before the procedure.
2) Old History was defined as the diagnosis being made > 6 months before admission, irrespective of whether this history of PE/DVT affected the admission management or not.
3) Present on Admission was defined as the diagnosis being made < 6 months before admission, irrespective of whether this history of PE/DVT affected the admission management or not.
4) Any thrombosis at the brachial vein or distal to it was considered part of the superficial not deep venous system
5) The postoperative period was defined as 30 days from the procedure or until the end of the same admission, which ever came later.

## False Positives: A Comprehensive Analysis

| Classification of False Positives | Number of cases | Percentage |
| --- | --- | --- |
| DVT/PE Present on Admission (POA) | 16 | 25.4% |
| Pre-Procedure Diagnosis of PE/DVT | 13 | 20.6% |
| Remote History of DVT or PE (> 6 months) | 10 | 15.9% |
| Arterial (not venous) thrombosis* | 4 | 6.4% |
| Negative PE/DVT workup * | 4 | 6.4% |
| “Rule out PE” as cause of death * | 3 | 4.8% |
| Superficial (not deep) thrombosis or thrombophlebitis * | 3 | 4.8% |
| Miscellaneous * | 10 | 15.9% |
| Total | 63 | 100% |

*** **Represents coding-related inaccurate diagnosis

## Coding-Related Inaccurate Diagnosis:Miscellaneous Category

| Classification of False Positives | Number of cases |
| --- | --- |
| Vein stenosis (no thrombosis) | 1 |
| PE stands for Physical Exam not Pulmonary Embolus | 1 |
| Low dose Coumadin prophylactic not therapeutic | 1 |
| Surgery done at outside hospital | 1 |
| Cerebral embolization of AVM | 1 |
| Prophylactic heparin mistaken for therapeutic heparin | 1 |
| RLE U/S ordered to r/o abscess at surgical site | 1 |
| Unknown  | 3 |
| Total | 10 |

## PE/DVT Results: Comparison of Studies

|  | Our study | Zhan study | AHRQ study | NSQIP and PTF study | UHC study |
| --- | --- | --- | --- | --- | --- |
| N | 112 | 20,868 | 155 | 55,682 | 1022 |
| PPV | 44% | 29%  | 68% | 22% | 61% |
| Sensitivity | -- | 68% | -- | 66% | -- |

**Notes:**
CI for PPV of 30% with 95% CI (Binomial exact is 22%, 40%) Mention that we first got a PPV of 30% when nurses reviewed, then it was 44% after physician review
CI for PPV of 43.8% (95% CI, 34.4-53.4%)

## Problems in Coding PE/DVT 

-  PE/DVT PSI designed as initial screen
-  Accuracy of method to detect true positives using administrative data affected by:
- Standards used to assign codes for “other” or secondary conditions  based on the Uniform Hospital Discharge Data Set (UHDDS)
- “Other” conditions: those that coexist at the time of admission, develop sequentially, affect the treatment received and/or length of stay, or affect patient care
- Definition of PE/DVT relative to
- UHDDS coding standards,
- ICD-9-CM Official Coding Guidelines for Coding and Reporting
- Coding Clinic published by the American Hospital Association (AHA)

**Notes:**
For “other conditions, affecting patient care can mean
clinical evaluation 
therapeutic treatment
diagnostic procedures
extended length of stay
increased nursing care and/or monitoring

Note: according to UHDDS, postoperative PE/DVT is coded with a code from the 997 category, with an additional code to identify the PE/DVT. This method of identifying the Post operative PE/DVT is not part of the PSI algorithm

## Problems in Coding PE/DVT, cont’d

- False Positive 1: chart review does not document a PE/DVT
- Code was present on admission (POA) and meets UHDDS definition of “other” diagnosis
- Code assigned as a current condition
- Should have been coded as a “history of” with a V code
- It was still a “rule out” condition at the time of discharge
- Coding system issue
- Was miscoded (superficial vein and not deep vein) due to coding invention and ICD-9-CM alphabetic index
- Coder did not identify the correct vein anatomically
- Should not have been coded at all
- False Positive 2: chart review documents a PE/DVT, but it is not a _**postoperative **_PE/DVT:
- Diagnosis of PE/DVT occurred after admission but before surgery

**Notes:**
According to the UHDDS conditions that are “rule out” at the time of discharge are coded as if they exist. Note: this is rare.
Miscoding (superficial and not deep vein) can be influenced by the structure of the ICD-9-CM alphabetic index. For example,  DVT NOS defaults to DVT of lower extremities

## Recommendations for Improving  PE/DVT

- Modify coding rules:
- Use NSQIP definitions to influence the coding rules
- Specify the circumstances when the PE/DVT should be coded and publish them in Coding Clinic and Official Guidelines
- as “current conditions” or “history of”
- Begin using POA in VA
- Explore use of “997” complication code as part of the PSI algorithm to capture post-operative PSIs
- Explore expansion of POA to include a special character denoting “POA prior to surgery”
- Undertake targeted education to help coders, researchers, and healthcare professionals understand the use of coding guidelines for “PE/DVT”

## Objective 3

*Question: Do High-Performing Facilities Have Higher Rates on Structures and Processes of Care than Lower-Performing Facilities?*
- Conduct two _pilot_ field consultations locally
- determine feasibility and logistical problems
- test interview questions
- add/delete selected staff
- Conduct field consultations at 6 facilities
- Perform structured interviews with selected staff
- Gather data on safety and quality
- Assess differences between sites on structures and process using qualitative methods and ratings

**Notes:**
Problems with EMR 
lacks information on structural characteristics of hospitals
documentation on processes of care may be incomplete
Similar to NSQIP process
 2 interviewers will go to each site; will interview each staff person/group together. One interviewer will be clinician, one will be researcher.
In process of obtaining IRB approvals from all sites

## Selected Staff for Interviews

- Individual Interviews
- Executives
- Service Chiefs
- Other Middle Managers
- Other Non-Managers
- Group Interviews
- Surgical Service
- Medical Service
- Non-Managers

**Notes:**
Executives — 30 MIN (max) INDIVIDUAL INTERVIEWS
Quadrad Members
Hospital Director
Associate Director
Chief of Staff
Chief Nursing Officer (Nurse Executive) 
Service Chiefs — 30 MIN (max) INDIVIDUAL INTERVIEWS
Chief of Medicine
Chief of Surgery 
Chief of Anesthesiology 
Other Middle Managers — 1-HOUR INDIVIDUAL INTERVIEWS (except as noted)
Manager of Performance Improvement / Quality Improvement 
Patient Safety Manager
Nurse Manager (PCTC)/Associate Director of Nursing/Associate Nurse Executive  
Risk Manager — 30 MIN INDIVIDUAL INTERVIEW
Surgical Service — 1-HOUR GROUP INTERVIEW WITH THESE INDIVIDUALS
Staff surgeon
OR nurse manager 
SICU nurse manager 
Surgical floor nurse manager
PACU nurse manager 
Medical Service — 1-HOUR GROUP INTERVIEW WITH THESE INDIVIDUALS
Medical ICU nurse manager 
Medical floor nurse manager 
Staff internist 
Chief pharmacist 
Skin care specialist 
Non-Managers — 1-HOUR GROUP INTERVIEW WITH THESE INDIVIDUALS 
Chief resident, surgical service
Chief resident, medical service
Staff nurse, surgical service (SICU nurse + possibly regular floor nurse)
Staff nurse, medical service (MICU nurse + possibly regular floor nurse)
Respiratory therapist
Other Non-Managers
NSQIP nurse — 1-HOUR INDIVIDUAL INTERVIEW
Infection control nurse — 30 MIN INDIVIDUAL INTERVIEW
Coding department staff member—30 MIN INDIVIDUAL INTERVIEW 

## Interview Domains

- Organization, Structure, and Culture
- Coordination of Work and Communication
- Interface within Service
- Monitoring Quality of Care
- Quality Improvement
- General Clinical Topics
- Coding
- Technology and Equipment
- Technical Competence of Staff
- Leadership
- Interface with Other Services
- Systems Issues and Human Factors
- Staffing
- Summary Evaluation of Service Overall

**Notes:**
NOTES: Domains are based on NSQIP questions, the AHRQ report on "Making Health Care Safer: A Critical Analysis of Patient Safety Practices," and the Safety Attitudes Questionnaire. 
Total of 14 questions
Before interview begins, hand out list of PSIs and read definitions of PSIs and patient safety to interviewee. 

## Domain: Monitoring Quality of Care / Quality Improvement

- In your facility, what are some of the initiatives related to improving patient safety that you know about?
- On what does it focus?
- What facilitated its implementation?
- What were the implementation obstacles?
- How effective do you think it is?
- What are some of the most common adverse events that you see in your day-to-day work? Please refer to the list provided.
- What is being done now to reduce the incidence of this complication?
- What do you think would be helpful in further reducing the incidence of this?
- Is there anything not on the list we provided you that you believe is a concern?

## Domain: Coding

- Who is involved in assigning ICD-9 and procedure codes to adverse events?
- Are physicians involved in reviewing the event codes?
- Do you think there is a concern about the accuracy of coding relating to adverse events?
*If yes*: What is the concern?
- How is this addressed?

## Domain: Technology and Equipment / Technical Competence of Staff

- I am curious to hear about what problems, if any, you or others have had with the technology and/or equipment on the service.
- What problems have you had with the _**accessibility**_** **or _**availability**_, or both, of technology and/or equipment?
- What problems you have had with the _**quality**_ or _**functioning**_, or both, of the technology and/or equipment?
- What problems, if any, have you or other staff had being properly trained to use the technology and/or equipment?
- What technology and/or equipment, if any, does not exist at your hospital that would help improve patient safety?

**Notes:**
By accessibility I mean having equipment “where you need it when you need it” and by availability I mean “equipment existing somewhere in the hospital”
By quality I mean “the age and features of the equipment” and by functioning I mean “how well the equipment works

## Capturing Initial Impressions 

- Immediately after each _pilot_ field consultation, each interviewer summarizes her/his
- Impressions of each domain in a paragraph
- Overall impressions of the site
- in both cases giving specific examples
- Soon afterwards, all interviewers and other members of the PSI validation team meet to discuss the impressions
- These discussions will be used to generate a protocol for capturing initial impressions for study’s six field consultations
- We may rate sites, creating examples for an “ideal” site
- We may decide to use only written impressions

**Notes:**
For the pilot sites, ratings will be used to guide interviewers in capturing specific impressions in writing, but we will not be using these ratings to “rate” sites.

## Rating Category Possibilities 

- Some numeric scale
- NSQIP rating (1 to 9; 1=poor and 9=excellent)
- Other model rating (0 to 4)
- Some hierarchy scale:
- Poor, fair, good, very good, excellent
- Some recognition scale:
- Bronze, silver, gold

**Notes:**
We haven’t decided which scale or ratings will we use and how they will be used.

## Example of Rating: NSQIP 

|  | PoorFairGoodVery goodExcellent
1      2      3      4      5      6      7      8     9 |
| --- | --- |
| Technology and Equipment |                            |
| Technical Competence of Staff |                                    |
| Interface with Other Services |                         |
| Relationship with Affiliated Institution |                                 |

## Initial Impressions of Pilot Sites 

| Domains | Rating* | Evidence Narrative | Examples |
| --- | --- | --- | --- |
| Monitoring Quality of Care Questions 1, 3, 4 |  |  |  |
| Quality Improvement 
Questions 1, 3 |  |  |  |
| Leadership 
Questions 2, 4 |  |  |  |
| Systems Issues and Human Factors 
Question 4 |  |  |  |

- * Our initial rating scale: Excellent, Very good, Good, Fair, Poor

**Notes:**
This is the form we will use for capturing initial impressions of pilot sites. Discuss evidence narrative and examples

## Next Steps (1)

**Identify False Negatives**
- Use an existing “gold standard” (e.g., VA NSQIP) for 5 surgical PSIs
- Identify risk factors by estimating logistic regression models for each of the PSIs
- Use propensity score stratification to generate propensity class strata for each of the PSIs
- Use AHRQ Composite Tool to review medical records of “high-risk” cases for PSIs
- Screen EMRs of high-risk cases using keyword searches (selected “hits” will have chart review)
- Explore machine language processing as an informatics tool to search for false negatives

## Next Steps (2)

**Examine association between explicit processes of care and individual PSIs**
- Match 1,680 flagged PSI cases with 1,680 controls (unflagged cases matched on demographic and clinical characteristics) to determine whether flagged cases are more likely to experience “process failures”
- Use propensity score methodology to perform matching; chi-square tests used to examine proportion of failure rates among cases and controls

**Notes:**
NOTES: USE OLD SLIDE

## Next Steps (3) 

**Revise and Improve the PSIs**
- Add additional data elements to inpatient data:
- Present-on-admission (POA) diagnoses, do-not-resuscitate (DNR) codes, selected clinical, laboratory and pharmacy data elements
- Link inpatient data with outpatient/inpatient data 30/60 days preceding index hospitalization (obtain POA diagnoses)
- Link inpatient data with outpatient/inpatient data 30/60 days following index hospitalization to evaluate whether additional PSIs are detected
- Link VA and Medicare data to examine PSI readmission in private sector
- Improve coding by implementing coding changes
- Modify PSI numerators and denominators on inclusion/exclusion criteria
- Recalculate false positives and negatives

## THANK YOU!

## CONTACT INFORMATION:

**Amy Rosen, Ph.D.**
**Center for Health Quality, Outcomes & Economic Research **
**(VA Center of Excellence) **
**Boston University Schools of Public Health and Medicine, Departments of Health Policy and Management and Family Medicine**
**Phone #: (781) 687-2960**
**E-mail: akrosen@bu.edu**