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All About Surgical Site Infections
Lessons learned from the SSI surveillance
pilot, SSI mini grant program, and the data
presentation collaborative
Andrea Alvarez, MPH
HAI Program Coordinator
Virginia Department of Health
Jacqueline P. Butler, CIC
Dir, Infection Prevention & Control
Sentara Healthcare
November 10, 2011
SSI Surveillance Pilot:
Purpose
Public reporting expectations increasing
 Multiple factors to consider when choosing
a SSI for public reporting
Troubleshoot issues with surveillance
definitions
Quantify time requirements for
surveillance
Gather lessons to help prepare other
facilities for reporting
Perceived Pilot Benefits
Increase awareness of SSIs
 More focus on prevention practices, monitoring
associated outcomes, physician awareness of
surveillance definitions
High profile, high risk, high priority procedures
Providing standardized benchmark data
Prepare for future reporting requirements
 Gain more experience in NHSN data entry
 Increase upload or electronic capabilities
 Quantify the time associated with procedure
surveillance
 Identify demands for reporting to facilitate
processes to reduce burden
Feed data back to those who can make a
difference
SSI Pilot: Methods – Selecting
Hospitals and Procedures
Coronary artery bypass graft (CABG), hip
replacement (HPRO), knee replacement
(KPRO) surgeries
 Consumer interest, experiences of other states,
morbidity
Surgical Care Improvement Project (SCIP)
antibiotic measures
 Align process measures with outcome measures
 Pilot feasibility of publicly reporting procedure-
specific SCIP data
18 hospitals
 Randomly selected by bedsize category and number
of procedures performed
Voluntary participation
 Incentives: educational stipend (conferences, journal
subscriptions, etc.)
Pre-Survey
18/18 facilities responded (100%)
Well prepared:
 100% enrolled in NHSN and used NHSN definitions
 94% calculated SSI rates
Relatively well prepared:
 2/3 currently collected patient-level information
 Prevention efforts already underway
 SSI surveillance deemed high or medium priority
Not well prepared:
 One facility was currently entering data into NHSN for
the pilot procedure
 No facilities currently uploaded denominator data
 Limited communication between surgical and IP
databases
 50% perceived surveillance to be somewhat or very
difficult
Methods - Training
Partnership with APIC-VA for training
and distribution of incentives
One-day training (June 9, 2010)
 Case studies prepared by APIC-VA
Monthly conference calls
 Surveillance Q&A
 Data import discussions
 Feedback of data
Some Surveillance Pointers
Definitions – Ensure the latest version of the
definitions are being used
 Deep incisional vs. organ space
 Increases consistency and standardization
SSIs are attributed to the date of the operation
 For SSIs identified on readmission, on the event form
use the date of admission and discharge for the surgery
visit
All surgical procedures must be entered into NHSN
 Not only procedures with an event (like CLABSIs)
Only need to report the required sensitivities
To report a pathogen that is not on the list of common
pathogens, right-click in pathogen field
NHSN Clarifications
Deep incisional vs. organ space
 If an incision is opened, the infection is
counted as deep incisional no matter where it
travels
A knee that has never been operated on
before is always a primary regardless of
whether it is a total or partial surgery
Transplant
 Includes internal staples
 Does not include a blood transfusion
SSI standardized infection ratios (SIRs)
only include primary sites
Methods – Data Reporting
Monthly entry of procedures and
infection events into NHSN
 Procedures from July – Dec 2010 with 6
months of post-discharge surveillance
Quarterly submission of SCIP data
 Jan-June 2010 (baseline), July-Dec 2010
(pilot)
Time and effort
 Time spent on surveillance
 Number of staff involved with surveillance
Electronic Upload Methods:
ASCII File
Comma delimited ASCII file (.txt or .csv)
created by the facility
 Can be generated from different external
sources, such as infection prevention databases
or hospital information systems
 Requires assistance of operating room and/or IT
staff
 Specifications for values, format, and data
requirements must be followed
Specifications and instructions available on
NHSN website:
 http://www.cdc.gov/nhsn/PDFs/ImportingProced
ureData_current.pdf
Electronic Upload Methods: CDA
 Clinical Document
Architecture (CDA)
 Health Level 7 (HL7)
standards used to provide a
consistent format framework
for electronic documents
 Not all vendors have the
capacity to create
documents in this HL7
framework
 Specifications and
instructions available on
NHSN website
 http://www.cdc.gov/nhsn/
CDA_eSurveillance.html
 Examples of vendors*
with CDA compatibility:
 Atlas Development
Corporation
 BD Diagnostics (formerly
known as AICE or ICPA)
 CareFusion / MedMined™
from Cardinal Health
 Cerner Corporation
 EpiQuest
 ICNet International Limited
 RL Solutions
 SafetySurveillor® by
Premier
 Sentri7 by PharmacyOne
 TheraDoc Hospira, Inc.
 Vecna Technologies
 VigiLanz Corporation
*List compiled by APIC
SSI Pilot: Time and Effort per
Facility
0
5
10
15
20
25
30
35
Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun
Hours
per
facility
(avg)
CABG
HPRO
KPRO
2010 2011*
*Readmission/post-discharge only
SSI Pilot: Time and Effort per
Person
0
2
4
6
8
10
12
14
16
18
Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun
Hours
per
staff
member
(avg)
CABG
HPRO
KPRO
2010 2011*
*Readmission/post-discharge only
Results: SCIP Data
 SCIP 1: Timely receipt of antibiotic prior to surgery
 SCIP 2: Receipt of appropriate antibiotic
 SCIP 3: Timely discontinuation of antibiotic after surgery
Procedure
SCIP1
(%) SCIP2 (%)SCIP3 (%)
Total
(%) Minutes
CABG 98.6 100.0 97.2 98.6 19
HPRO 99.4 100.0 97.0 98.8 8
KPRO 97.2 99.9 96.9 98.0 12
Total 98.4 100.0 97.0 98.5 13
Results: SSIs Identified
 2,388 procedures conducted
 25 SSIs included in SIR calculation
 Secondary infections are not included in SIR
- All CABG (N=5)
 64% CABG, 24% KPRO, 12% HPRO
 ASA score and duration of procedure highest for
CABG
 3 occurred > 30 days after procedure (all KPRO)
 SIR = 0.72
 Interpretation: The pilot facilities identified
28% fewer SSIs than expected based on the
national experience.
 Not statistically significant
Post-Survey
14/18 facilities responded (78%)
Facilities more prepared for public
reporting
 Staff review SSI definitions more closely
IT changes
 Many facilities changing or considering
changing vendors
Changes to administration’s prioritization
of SSI surveillance (4 facilities)
No change in IPs’ perspective of the
magnitude of the problem of SSIs in their
facility
Benefits to Participation
93% - Helped to prepare for future
reporting requirements
79% - Gained more experience in NHSN
data entry
57% - Facilitated process needed to
meet pilot demands and future reporting
50% - Demonstrated how much time was
associated with HAI surveillance to find
ways to decrease burden on workload
43% - Automated upload and/or
increased electronic capabilities
43% - Increased awareness of SSIs
Barriers Encountered
50% Learning curve
 Data entry
 Importing data
43% Time/resource limitations
 Data entry
 Staffing
29% No barriers
14% Post-discharge surveillance
14% Consistency between facilities
Electronic Upload to NHSN
Pre-survey: 0 facilities End of pilot: 9 facilities (50%!)
6 facilities submitted feedback on upload process
 4 used Clinical Document Architecture (CDA) technology
- 3 BD/AICE, 1 unspecified vendor
- Decreases in monthly surveillance effort after implementing
CDA
 8 hours to 2 hours
 8 hours to 1 hour
- Time required to set up import averaged several months
 2 used .CSV file
- Decreased monthly surveillance effort in one hospital from 5
hours to 1 hour
- Took 2 months for one hospital to set up its file transmission
 2 hospitals used DICON to help with their electronic import
 4 of these hospitals used Meditech for their patient medical
records
Electronic medical record system (EMR)
is necessary for the electronic upload
and any movement towards increased
use of EMR would be of help to the
facility
Helpful to talk to other facilities using the
same systems and see if they have been
able to set up a file transfer
 Sometimes easier for facility IT staff to talk to
each other rather than IP trying to explain to
IT what is needed
Importance of monitoring all exported
data for quality
Lessons Learned / Challenges
Lessons Learned / Challenges
Operating room system capability and
compatibility
Writing the data dictionaries – challenge!
 Concern about changing
dictionaries/remapping elements if NHSN
amends definitions or changes required
fields
Team approach required (quality, IT,
other departments)
 Establish importance of support of the
infection prevention program on a local level
first
 IT support is critical for implementation and
to address data quality
PERSPECTIVES FROM
THE PARTICIPANTS
Experiences of a Large
System
Sentara Healthcare (SH):
 >23,000 staff, >100 care giving sites, including 10
acute care hospitals with a total of 2,349 beds
Sentara Norfolk General Hospital / Sentara Heart
Hospital
 Patients receive comprehensive cardiac services -
from diagnostics to open heart surgery and
transplants.
 State-of-the-art hospital features all-private rooms,
including 112 inpatient beds and 45 pre/post
procedural rooms for patients undergoing
interventional cardiac procedures.
 Houses 5 cardiac operating rooms designed to
accommodate 2,000 cardiac surgeries a year.
Timeline of Sentara’s Pilot Period
 Calm down
 Education – June 9, 2010
 Define current surveillance process for CABG
 Develop a Team (IT, Contracted Vendor, Cardiac
Auditors, Leadership, IP&C) to research ability to
electronically export denominator surgical data to
NHSN
 Contracted Cardiac Vendor building a background
program to develop a report off the STS Cardiac
Surgery Database (CSD) for exporting
 Began reporting requirements for pilot project
(numerator data, denominator data export, SCIP
measure data, time & effort measures) – September
1, 2010 for July 2010 data
 Completion – ongoing…Why stop a good process?
Sentara’s Experiences
Pit Falls:
Took time to map SH surgical
denominator components (STS CSD) to
NHSN template for export
Time allotment for cardiac abstractors to
review surgical patients
Contracted vendor - Armus
Experience:
Positive
Demonstrated SH’s ability to address
issues of mandatory reporting
Building in a Collaborative
Requirement of ARRA funding
Create a project to be flexible and
responsive to acute care IPs’ workload
 Collecting data presentation templates
 Sharing best practices for data feedback
Monthly conference calls
Survey given to IPs and unit-specific
staff to capture the various
perceptions of data utility
Data Presentation Survey
 Collect baseline of knowledge regarding data
presentation practices targeted to direct care staff
 Sent to IPs, direct care staff in a selected unit/area
 18 facilities (100%): 17 IPs and 84 staff
 General statements about use of data to lower HAI
rates or impact infection prevention compliance
 Types of staff and their perceived awareness of HAI
data and compliance with infection prevention
practices
 Outcome and process measures staff want to see
and are currently provided
 Types of data and whether they are easy to
understand, useful, and currently presented
Data Presentation Survey
Results: IP and Staff
Perceptions
Awareness of HAI data promotes
dialogue among staff and impacts
infection prevention compliance
IPs more likely to think that SSI rates
were improving (65% vs. 48%)
Most respondents thought unit-specific
HAI data were valid and reliable, easy
to understand, timely, and shared at
least quarterly
Survey Results (cont’d)
Color coding, comparisons (to average,
benchmark) most useful to staff
Color coding, comparisons, HAI rates,
number of HAIs, and number of days
since last infection were most easy to
understand
SIR – used in some hospitals (20%),
useful (38%), easy to understand (26%)
HAI data most often presented: HH,
CLABSI
Staff want environmental cleaning
Survey Results (cont’d)
 Differences in awareness of what data are
presented (IPs vs. staff receiving data)
 Perceived differences in awareness of data
and infection prevention compliance by type of
staff
 Most aware and compliant: nursing leadership, unit
nurses
 Least aware and compliant: physicians
 IPs share data most often with units and
Infection Control Committee
 >75% of respondents present HH, BSIs, SSIs, UTIs,
VAPs
 >75% of respondents present comparison HAI data
More infections than predicted (statistically significant)
Observed number of infections similar to predicted
Fewer infections than predicted (statistically significant)
No infections
---SIR = 1.00 when observed = predicted
SSI Pilot SIR by Time Period
0.00 0.50 1.00 1.50 2.00
July-Dec
(H2)
July-Sept
(Q3)
Oct-Dec
(Q4)
SIR and 95% confidence interval
SSI Mini-Grant Program
Any activities that support implementation of
the NHSN Procedure-Associated Module,
including but not limited to:
 Equipment and services, such as administrative
and informatics costs
- Example: upgrading or modifying internal systems
 Training and education
- Example: training for staff responsible for collecting and/or
entering surgical site infection surveillance data
 Consultative and technical assistance
- Example: programmer support to help create an electronic
file to upload surgical procedure data directly into NHSN
 Administrative support
Awardees
Applications reviewed by VDH and
Virginia Hospital & Healthcare
Association (VHHA)
22 hospitals
Total of ~$290,000
Monies dispersed by July 2011
PERSPECTIVES FROM
THE PARTICIPANTS
Sentara: A Systems Approach
Total funding: $145,000 for System
Technical assistance (IT) – $124,000
Training [Infection Prevention & Control (IP&C), Data
Auditors] - $21,000
Implementation goals:
Develop and implement an electronic export process
for reporting of surgical procedure data directly into the
NHSN database
Provide training / technical assistance to staff to
facilitate successful implementation of the exporting
process
Create “super users / trainers” who will disseminate the
process throughout the Sentara Healthcare System
Sentara: A Systems Approach
Time Line:
Awarded mini-grants - May 2011
Immediately developed Team (IT, Leadership, Finance, IP&C) to
address goals of funding
IT Team began meeting with an action plan based on
components (IT, Training) - June 2011
Hired Consultant to develop IT components from PICIS OR
Manager and “background” data fields - July 2011
Pit Falls:
Other IT priorities (“EPIC Go Live”)
Contracted IT staff
Time line – finances
Experience:
Frustration
Next Steps for Sentara
Activity reports (facility-specific) and unused
funding submitted to VDH/VHHA
 November 15, 2011
Implementation of final IT product
 November 2011
Trial use of IT product by IP&C
 December 2011
Validation of process by IP&C
 December 2011 - January 2012
Use of product beginning with Jan 2012
surgical patient population with successful
export of data to NHSN
 February 2012
Lessons Learned: Other
Facilities
Electronic medical records are great but
present documentation challenges
Surgeons do not use ICD-9 codes
“Mapping” of required denominator
components time consuming
IT needs “special handling”
Resources/Take Home
Messages
Challenge of converting CPT codes to
ICD-9 codes
 Crosswalk soon available!
NHSN forms for Procedure-Associated
Module
 http://www.cdc.gov/nhsn/psc_pa.html
Map entire facility in NHSN – infections
can happen anywhere
Resources to Help Build Business Case
for Electronic Upload (VDH document)
Future training opportunities – APIC-VA
and NHSN
Acknowledgments
VDH: Dana Burshell, Carol Jamerson,
Diane Woolard
VHHA: Barbara Brown
APIC-VA
SSI pilot participants
SSI mini-grant recipients
The Purpose of Our Work:
“The names of the patients
whose lives we save can never
be known. Our contribution will
be what did not happen to them”
Donald M. Berwick, MD, MPP
Former President and CEO of IHI
Current Administrator of CMS
Andrea.Alvarez@vdh.virginia.gov: 804-864-8097
JPButler@sentara.com: 757-388-3949

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AlvarezButler_All-About-SSIs.ppt

  • 1. All About Surgical Site Infections Lessons learned from the SSI surveillance pilot, SSI mini grant program, and the data presentation collaborative Andrea Alvarez, MPH HAI Program Coordinator Virginia Department of Health Jacqueline P. Butler, CIC Dir, Infection Prevention & Control Sentara Healthcare November 10, 2011
  • 2. SSI Surveillance Pilot: Purpose Public reporting expectations increasing  Multiple factors to consider when choosing a SSI for public reporting Troubleshoot issues with surveillance definitions Quantify time requirements for surveillance Gather lessons to help prepare other facilities for reporting
  • 3. Perceived Pilot Benefits Increase awareness of SSIs  More focus on prevention practices, monitoring associated outcomes, physician awareness of surveillance definitions High profile, high risk, high priority procedures Providing standardized benchmark data Prepare for future reporting requirements  Gain more experience in NHSN data entry  Increase upload or electronic capabilities  Quantify the time associated with procedure surveillance  Identify demands for reporting to facilitate processes to reduce burden Feed data back to those who can make a difference
  • 4. SSI Pilot: Methods – Selecting Hospitals and Procedures Coronary artery bypass graft (CABG), hip replacement (HPRO), knee replacement (KPRO) surgeries  Consumer interest, experiences of other states, morbidity Surgical Care Improvement Project (SCIP) antibiotic measures  Align process measures with outcome measures  Pilot feasibility of publicly reporting procedure- specific SCIP data 18 hospitals  Randomly selected by bedsize category and number of procedures performed Voluntary participation  Incentives: educational stipend (conferences, journal subscriptions, etc.)
  • 5. Pre-Survey 18/18 facilities responded (100%) Well prepared:  100% enrolled in NHSN and used NHSN definitions  94% calculated SSI rates Relatively well prepared:  2/3 currently collected patient-level information  Prevention efforts already underway  SSI surveillance deemed high or medium priority Not well prepared:  One facility was currently entering data into NHSN for the pilot procedure  No facilities currently uploaded denominator data  Limited communication between surgical and IP databases  50% perceived surveillance to be somewhat or very difficult
  • 6. Methods - Training Partnership with APIC-VA for training and distribution of incentives One-day training (June 9, 2010)  Case studies prepared by APIC-VA Monthly conference calls  Surveillance Q&A  Data import discussions  Feedback of data
  • 7. Some Surveillance Pointers Definitions – Ensure the latest version of the definitions are being used  Deep incisional vs. organ space  Increases consistency and standardization SSIs are attributed to the date of the operation  For SSIs identified on readmission, on the event form use the date of admission and discharge for the surgery visit All surgical procedures must be entered into NHSN  Not only procedures with an event (like CLABSIs) Only need to report the required sensitivities To report a pathogen that is not on the list of common pathogens, right-click in pathogen field
  • 8. NHSN Clarifications Deep incisional vs. organ space  If an incision is opened, the infection is counted as deep incisional no matter where it travels A knee that has never been operated on before is always a primary regardless of whether it is a total or partial surgery Transplant  Includes internal staples  Does not include a blood transfusion SSI standardized infection ratios (SIRs) only include primary sites
  • 9. Methods – Data Reporting Monthly entry of procedures and infection events into NHSN  Procedures from July – Dec 2010 with 6 months of post-discharge surveillance Quarterly submission of SCIP data  Jan-June 2010 (baseline), July-Dec 2010 (pilot) Time and effort  Time spent on surveillance  Number of staff involved with surveillance
  • 10. Electronic Upload Methods: ASCII File Comma delimited ASCII file (.txt or .csv) created by the facility  Can be generated from different external sources, such as infection prevention databases or hospital information systems  Requires assistance of operating room and/or IT staff  Specifications for values, format, and data requirements must be followed Specifications and instructions available on NHSN website:  http://www.cdc.gov/nhsn/PDFs/ImportingProced ureData_current.pdf
  • 11. Electronic Upload Methods: CDA  Clinical Document Architecture (CDA)  Health Level 7 (HL7) standards used to provide a consistent format framework for electronic documents  Not all vendors have the capacity to create documents in this HL7 framework  Specifications and instructions available on NHSN website  http://www.cdc.gov/nhsn/ CDA_eSurveillance.html  Examples of vendors* with CDA compatibility:  Atlas Development Corporation  BD Diagnostics (formerly known as AICE or ICPA)  CareFusion / MedMined™ from Cardinal Health  Cerner Corporation  EpiQuest  ICNet International Limited  RL Solutions  SafetySurveillor® by Premier  Sentri7 by PharmacyOne  TheraDoc Hospira, Inc.  Vecna Technologies  VigiLanz Corporation *List compiled by APIC
  • 12. SSI Pilot: Time and Effort per Facility 0 5 10 15 20 25 30 35 Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun Hours per facility (avg) CABG HPRO KPRO 2010 2011* *Readmission/post-discharge only
  • 13. SSI Pilot: Time and Effort per Person 0 2 4 6 8 10 12 14 16 18 Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun Hours per staff member (avg) CABG HPRO KPRO 2010 2011* *Readmission/post-discharge only
  • 14. Results: SCIP Data  SCIP 1: Timely receipt of antibiotic prior to surgery  SCIP 2: Receipt of appropriate antibiotic  SCIP 3: Timely discontinuation of antibiotic after surgery Procedure SCIP1 (%) SCIP2 (%)SCIP3 (%) Total (%) Minutes CABG 98.6 100.0 97.2 98.6 19 HPRO 99.4 100.0 97.0 98.8 8 KPRO 97.2 99.9 96.9 98.0 12 Total 98.4 100.0 97.0 98.5 13
  • 15. Results: SSIs Identified  2,388 procedures conducted  25 SSIs included in SIR calculation  Secondary infections are not included in SIR - All CABG (N=5)  64% CABG, 24% KPRO, 12% HPRO  ASA score and duration of procedure highest for CABG  3 occurred > 30 days after procedure (all KPRO)  SIR = 0.72  Interpretation: The pilot facilities identified 28% fewer SSIs than expected based on the national experience.  Not statistically significant
  • 16. Post-Survey 14/18 facilities responded (78%) Facilities more prepared for public reporting  Staff review SSI definitions more closely IT changes  Many facilities changing or considering changing vendors Changes to administration’s prioritization of SSI surveillance (4 facilities) No change in IPs’ perspective of the magnitude of the problem of SSIs in their facility
  • 17. Benefits to Participation 93% - Helped to prepare for future reporting requirements 79% - Gained more experience in NHSN data entry 57% - Facilitated process needed to meet pilot demands and future reporting 50% - Demonstrated how much time was associated with HAI surveillance to find ways to decrease burden on workload 43% - Automated upload and/or increased electronic capabilities 43% - Increased awareness of SSIs
  • 18. Barriers Encountered 50% Learning curve  Data entry  Importing data 43% Time/resource limitations  Data entry  Staffing 29% No barriers 14% Post-discharge surveillance 14% Consistency between facilities
  • 19. Electronic Upload to NHSN Pre-survey: 0 facilities End of pilot: 9 facilities (50%!) 6 facilities submitted feedback on upload process  4 used Clinical Document Architecture (CDA) technology - 3 BD/AICE, 1 unspecified vendor - Decreases in monthly surveillance effort after implementing CDA  8 hours to 2 hours  8 hours to 1 hour - Time required to set up import averaged several months  2 used .CSV file - Decreased monthly surveillance effort in one hospital from 5 hours to 1 hour - Took 2 months for one hospital to set up its file transmission  2 hospitals used DICON to help with their electronic import  4 of these hospitals used Meditech for their patient medical records
  • 20. Electronic medical record system (EMR) is necessary for the electronic upload and any movement towards increased use of EMR would be of help to the facility Helpful to talk to other facilities using the same systems and see if they have been able to set up a file transfer  Sometimes easier for facility IT staff to talk to each other rather than IP trying to explain to IT what is needed Importance of monitoring all exported data for quality Lessons Learned / Challenges
  • 21. Lessons Learned / Challenges Operating room system capability and compatibility Writing the data dictionaries – challenge!  Concern about changing dictionaries/remapping elements if NHSN amends definitions or changes required fields Team approach required (quality, IT, other departments)  Establish importance of support of the infection prevention program on a local level first  IT support is critical for implementation and to address data quality
  • 23. Experiences of a Large System Sentara Healthcare (SH):  >23,000 staff, >100 care giving sites, including 10 acute care hospitals with a total of 2,349 beds Sentara Norfolk General Hospital / Sentara Heart Hospital  Patients receive comprehensive cardiac services - from diagnostics to open heart surgery and transplants.  State-of-the-art hospital features all-private rooms, including 112 inpatient beds and 45 pre/post procedural rooms for patients undergoing interventional cardiac procedures.  Houses 5 cardiac operating rooms designed to accommodate 2,000 cardiac surgeries a year.
  • 24. Timeline of Sentara’s Pilot Period  Calm down  Education – June 9, 2010  Define current surveillance process for CABG  Develop a Team (IT, Contracted Vendor, Cardiac Auditors, Leadership, IP&C) to research ability to electronically export denominator surgical data to NHSN  Contracted Cardiac Vendor building a background program to develop a report off the STS Cardiac Surgery Database (CSD) for exporting  Began reporting requirements for pilot project (numerator data, denominator data export, SCIP measure data, time & effort measures) – September 1, 2010 for July 2010 data  Completion – ongoing…Why stop a good process?
  • 25. Sentara’s Experiences Pit Falls: Took time to map SH surgical denominator components (STS CSD) to NHSN template for export Time allotment for cardiac abstractors to review surgical patients Contracted vendor - Armus Experience: Positive Demonstrated SH’s ability to address issues of mandatory reporting
  • 26. Building in a Collaborative Requirement of ARRA funding Create a project to be flexible and responsive to acute care IPs’ workload  Collecting data presentation templates  Sharing best practices for data feedback Monthly conference calls Survey given to IPs and unit-specific staff to capture the various perceptions of data utility
  • 27. Data Presentation Survey  Collect baseline of knowledge regarding data presentation practices targeted to direct care staff  Sent to IPs, direct care staff in a selected unit/area  18 facilities (100%): 17 IPs and 84 staff  General statements about use of data to lower HAI rates or impact infection prevention compliance  Types of staff and their perceived awareness of HAI data and compliance with infection prevention practices  Outcome and process measures staff want to see and are currently provided  Types of data and whether they are easy to understand, useful, and currently presented
  • 28. Data Presentation Survey Results: IP and Staff Perceptions Awareness of HAI data promotes dialogue among staff and impacts infection prevention compliance IPs more likely to think that SSI rates were improving (65% vs. 48%) Most respondents thought unit-specific HAI data were valid and reliable, easy to understand, timely, and shared at least quarterly
  • 29. Survey Results (cont’d) Color coding, comparisons (to average, benchmark) most useful to staff Color coding, comparisons, HAI rates, number of HAIs, and number of days since last infection were most easy to understand SIR – used in some hospitals (20%), useful (38%), easy to understand (26%) HAI data most often presented: HH, CLABSI Staff want environmental cleaning
  • 30. Survey Results (cont’d)  Differences in awareness of what data are presented (IPs vs. staff receiving data)  Perceived differences in awareness of data and infection prevention compliance by type of staff  Most aware and compliant: nursing leadership, unit nurses  Least aware and compliant: physicians  IPs share data most often with units and Infection Control Committee  >75% of respondents present HH, BSIs, SSIs, UTIs, VAPs  >75% of respondents present comparison HAI data
  • 31. More infections than predicted (statistically significant) Observed number of infections similar to predicted Fewer infections than predicted (statistically significant) No infections ---SIR = 1.00 when observed = predicted SSI Pilot SIR by Time Period 0.00 0.50 1.00 1.50 2.00 July-Dec (H2) July-Sept (Q3) Oct-Dec (Q4) SIR and 95% confidence interval
  • 32. SSI Mini-Grant Program Any activities that support implementation of the NHSN Procedure-Associated Module, including but not limited to:  Equipment and services, such as administrative and informatics costs - Example: upgrading or modifying internal systems  Training and education - Example: training for staff responsible for collecting and/or entering surgical site infection surveillance data  Consultative and technical assistance - Example: programmer support to help create an electronic file to upload surgical procedure data directly into NHSN  Administrative support
  • 33. Awardees Applications reviewed by VDH and Virginia Hospital & Healthcare Association (VHHA) 22 hospitals Total of ~$290,000 Monies dispersed by July 2011
  • 35. Sentara: A Systems Approach Total funding: $145,000 for System Technical assistance (IT) – $124,000 Training [Infection Prevention & Control (IP&C), Data Auditors] - $21,000 Implementation goals: Develop and implement an electronic export process for reporting of surgical procedure data directly into the NHSN database Provide training / technical assistance to staff to facilitate successful implementation of the exporting process Create “super users / trainers” who will disseminate the process throughout the Sentara Healthcare System
  • 36. Sentara: A Systems Approach Time Line: Awarded mini-grants - May 2011 Immediately developed Team (IT, Leadership, Finance, IP&C) to address goals of funding IT Team began meeting with an action plan based on components (IT, Training) - June 2011 Hired Consultant to develop IT components from PICIS OR Manager and “background” data fields - July 2011 Pit Falls: Other IT priorities (“EPIC Go Live”) Contracted IT staff Time line – finances Experience: Frustration
  • 37. Next Steps for Sentara Activity reports (facility-specific) and unused funding submitted to VDH/VHHA  November 15, 2011 Implementation of final IT product  November 2011 Trial use of IT product by IP&C  December 2011 Validation of process by IP&C  December 2011 - January 2012 Use of product beginning with Jan 2012 surgical patient population with successful export of data to NHSN  February 2012
  • 38. Lessons Learned: Other Facilities Electronic medical records are great but present documentation challenges Surgeons do not use ICD-9 codes “Mapping” of required denominator components time consuming IT needs “special handling”
  • 39. Resources/Take Home Messages Challenge of converting CPT codes to ICD-9 codes  Crosswalk soon available! NHSN forms for Procedure-Associated Module  http://www.cdc.gov/nhsn/psc_pa.html Map entire facility in NHSN – infections can happen anywhere Resources to Help Build Business Case for Electronic Upload (VDH document) Future training opportunities – APIC-VA and NHSN
  • 40. Acknowledgments VDH: Dana Burshell, Carol Jamerson, Diane Woolard VHHA: Barbara Brown APIC-VA SSI pilot participants SSI mini-grant recipients
  • 41. The Purpose of Our Work: “The names of the patients whose lives we save can never be known. Our contribution will be what did not happen to them” Donald M. Berwick, MD, MPP Former President and CEO of IHI Current Administrator of CMS Andrea.Alvarez@vdh.virginia.gov: 804-864-8097 JPButler@sentara.com: 757-388-3949

Editor's Notes

  1. The goals of the SSI Pilot Project were to develop best practices for the prevention of healthcare-associated surgical site infections, to determine what would be feasible for public reporting, and how best to accomplish the mandated public reporting of healthcare-associated infections (HAIs) in the Commonwealth of Virginia Consider morbidity, mortality, burden, ease of surveillance, etc.
  2. Procedures chosen align with risk assessment priorities Providing benchmark data (with other like facilities) to support improvement initiatives Standardized reporting system for comparison Feeding data back to those who can make a difference Ability to impact decision making in reference to policy development at the state level
  3. Eighteen hospitals were selected to participate in the SSI Pilot Project; six for coronary artery bypass graft (CABG), six for hip arthroplasty and six for knee arthroplasty. The aim was to have equal representation from all bed sizes. For hip and knee arthroplasty, 2 hospitals from each of these bed sizes were chosen: ≤ 200 beds, 201 to 500 beds, and > 500 beds. For CABG, 3 hospitals from each of these bed sizes were chosen: 201 to 500 beds and > 500 beds.
  4. In order to collect patient-level data (not mutually exclusive) 58% reviewed surgical procedures database, 33% reviewed electronic charts, 17% imported/downloaded, and 22% used other databases (OR software, DICON, downloads into database)
  5. Case studies, broke into small procedure-specific groups for discussion and then brought everyone back together to discuss. Also reviewed surveillance definitions and had a lively debate with Maggie Dudeck from CDC
  6. As of Nov 2011, most recent SSI definitions are from August 2011. Need to be consistent with how definitions are applied and follow NHSN’s definitions, no matter how each hospital may have defined it before Only need to report the required sensitivities for identified pathogens, even if thelaboratory has reported more All surgical procedures must be entered into NHSN Not only procedures with an event (like CLABSIs) Ensures optimal risk adjustment specific to the procedure
  7. An organ/space SSI involves any part of the body, excluding the skin incision, fascia, or muscle layers, that is opened or manipulated during the operative procedure.
  8. With the ARRA funds, we originally had an idea to have a centralized IT person who could work individually with hospitals to help set up the file imports but we couldn’t figure out a way to make that happen. So with the pilot, we discussed the two ways to import data into NHSN and then, depending on their systems and available resources, some of the hospitals were able to successfully set up their imports.
  9. Participants in 2007-2008 CDC pilot activities for BSI and SSI reporting with CDA capacity: MedMined™ from Cardinal Health EpiQuest ICPA (now BD Diagnostics) – also known as AICE Premier TheraDoc Vecna Technologies
  10. This graph depicts the average number of surveillance hours per month spent per facility for each of the pilot procedures. Separate lines of the graph show the trends for coronary artery bypass graft (CABG), hip replacement, and knee replacement surgeries. The vertical dotted line differentiates the two phases of the pilot – when the procedures were conducted (July 2010-Dec 2010), and the post-discharge surveillance period (Jan – Jun 2011). All procedures were followed for 6 months to see if a post-discharge infection was identified. On average, the CABG facilities spend the greatest number hours on surveillance (25 hours during 2010, 17 hours during the post-discharge time period). Hip replacement and knee replacement hospitals spent a similar number of hours on surveillance in 2010 (about 7 hours), with one outlier among the hip replacement hospitals where it took the facility some additional time to establish surveillance procedures in the first month. In the post-discharge period, hip replacement hospitals spent less time on surveillance (~3 hours) than knee replacement (~7 hours) or CABG (17 hours) hospitals. Average of hours spent (min, max) CABG 25? ( , ) Hip 7 (1, 66) Knee 7 (1, 25)
  11. This graph depicts the average number of surveillance hours per month spent per staff member for each of the pilot procedures. Separate lines of the graph show the trends for coronary artery bypass graft (CABG), hip replacement, and knee replacement surgeries. The vertical dotted line differentiates the two phases of the pilot – when the procedures were conducted (July 2010-Dec 2010), and the post-discharge surveillance period (Jan – Jun 2011). All procedures were followed for 6 months to see if a post-discharge infection was identified. In 2010, on average, staff in CABG hospitals spent the greatest amount of time on surveillance per month (10 hours per person), followed by hip replacement hospitals (6 hours per person), and knee replacement hospital (2 hours per person). Hip replacement and knee replacement hospital staff spent similar amounts of time conducting surveillance for their pilot procedure in the post-discharge period (~2 hours per month) whereas staff in the CABG hospitals spent about 6 hours per month.
  12. This table describes the percentage of pilot facilities that met each SCIP (Surgical Care Improvement Project) measure and the amount of time required to submit the SCIP data to VDH, stratified by pilot procedure. Performance on each of the SCIP measures was extremely high (97% or greater) for all three pilot procedures. On average, reporting took between 8 and 19 minutes per quarter.
  13. If you remember, the SIR is a metric that adjusts for several risk factors. A SIR of 1 means that the experience of your population is the same as the baseline (in this case, the national experience using data from NHSN). The pilot facilities identified fewer infections than expected, for a SIR of 0.72. This finding was almost statistically significant, but not quite…
  14. Other benefits included: 36% Fed back data to those who can make a difference 21% Ability to impact decision making in reference to policy development at state level 29% Provided benchmark data to support improvement initiatives 14% Continuous monitoring of outcomes associated with procedure, aligned with risk assessment priorities, different way of reviewing data, knowing rates helped providers focus on better practices 7% standardized reporting system for comparison, discussion/clarification of definitions, increase consistency in interpreting definitions Other: spurred us to start a business case for a data mining company
  15. Other barriers: time associated with pilot (one facility indicated that it took away from other infection prevention activities), surgeons not accepting the data as credible There was also concern that more active surveillance by specific clinicians and/or facilities may ultimately appear as an increase in rates.
  16. Just because the import is established doesn’t mean it’s going to be smooth going – checks are needed to make sure that all of the procedures are imported and the variables are coming through as you think they are. NHSN has some checks for part of this process, but it also takes a watchful eye on your part.
  17. One hospital noted that it was beneficial that the operating room system already collected the required NHSN variables One hospital reported that the biggest challenge was writing the data dictionaries – needed to set up the various components at the same time and assure the dictionaries were written to include all those elements needed for NHSN download, which may be problematic as NHSN continues to make changes to the definitions and required fields
  18. Purposes of survey: - To provide a baseline of knowledge regarding data presentation practices targeted to direct care staff - To help the Virginia Department of Health (VDH) Healthcare-Associated Infections (HAI) Program develop data presentation templates and recommendations for hospitals, long-term care facilities, and other healthcare facilities - To provide a flexible tool that IPs can customize and use in their facility - To fulfill the ARRA grant requirement of participating in a prevention collaborative while placing a minimal amount of time and burden on IPs
  19. Question 1 – yes/no questions about awareness of HAI data and its affect on outcome and process measures Question 2 – asks about staff member’s perception of whether various types of staff are aware of HAI data and if they are generally compliant with infection prevention practices Question 3 – asks about the ease of understanding and usefulness of various data presentation techniques and whether these techniques are presented to the survey respondent’s area/unit/team Question 4 – asks about various types of outcome and process measures  whether the survey respondent wants to know about the data and whether those data are currently provided
  20. IP respondents = 17 Staff respondents = 84 Percentages indicate the proportion of respondents that agreed with the statement. Awareness of HAI data promotes dialogue among staff 94% (IP) 87% (staff) Area/unit-specific HAI data are presented 94% (IP) 81% (staff) Awareness of HAI data impacts infection prevention compliance 88% (IP) 92% (staff) If staff improve their infection prevention practices, lower HAI rates will result 88% (IP) 80% (staff) If I improve my infection prevention practices, lower HAI rates will result 76% (IP) 82% (staff) Surgical site infection rates are improving 65% (IP) 48% (staff) Other healthcare-associated infections (HAIs) are a problem 53% (IP) 48% (staff) Surgical site infections are a problem 29% (IP) 30% (staff) Data are valid and reliable 94% (IP) 88% (staff) Data are easy to understand 88% (IP) 81% (staff) Data are timely 81% (IP) 79% (staff) Data are shared at least once per quarter 81% (IP) 84% (staff)
  21. IPs provided HH and BSI data most often to units (88%), followed by VAPs and UTIs (82%), then SSIs, MRSA, and lastly C. difficile.  They were least likely to share SCIP and environmental health data. 54% of staff respondents want to know about environmental cleaning data. Hand hygiene and VAP were the measures that staff were least likely to say they wanted to know about.
  22. A higher percentage of IPs compared to staff respondents perceived data for all infection types were available to the unit.  A higher percentage of staff respondents, as compared to IP respondents, perceived SCIP measures and environmental cleaning compliance data were available to the unit. Through the data presentation survey process, IP found out that staff at the bedside were not getting the HAI data and on unit bulletin boards there was only very old data  now is focusing more on email distribution of the data to address the issues identified such as: 1) lack of color copiers; 2) not wanting to expose unit HAI data to vendors and other visitors; and 3) unit directors are busy and HAI data distribution may not be their priority Ideas: Bulletin boards Powerpoint presentation Screen-savers with HAI data Dedicated monitors to display HAI data Multi-targeted infection control dashboard developed by facility staff
  23. While there is no requirement to use or report SIR data and it is not prescribed how to display SIR data, VDH shared examples from other states to provide Virginia facilities options of how they may want to start using the SIRs within their facilities The graph above shows the SIR for the pilot facilities by three time periods – October to December (2010Q4), July to September (2010Q3), and the whole pilot period (July to December). The green bar for 2010Q4 means that there were fewer infections than predicted, based on a comparison to the reference population (in this case, national data from the National Healthcare Safety Network), and the finding was statistically significant. The SIR for this time period was 0.52 with a 95% confidence interval from 0.24 to 0.98. Although the point estimates for both 2010Q3 (0.92) and 2010H2 (0.72) was less than 1, the yellow bar indicates that the number of infections observed by the pilot facilities was similar to the experience of the reference population. If there were more infections than predicted, based on a comparison to the reference population, and the finding was statistically significant, the bar would have been colored red. Time pd procedures infections Number SSIs expected SIR p-value 95% CI 2010H2 2388 25 34.801 0.718 0.0519 0.460, 1.068 2010Q3 1172 16 17.438 0.918 0.4262 0.518, 1.503 2010Q4 1216 9 17.363 0.518 0.0216 0.237, 0.984
  24. One of the main lessons learned was that hospitals do not use ICD-9 codes for surgical procedures and that surgeons call the procedures different things than what the ICD-9 codes call it. Also, electronic medical records are nice but they are only as good as what gets documented on specific flowsheets. In other words, reports cannot be written from free text and just because the rows are there on the flowsheets doesn't mean that staff use them.
  25. Issue of physicians and credibility of data/surveillance definitions has been brought up and we’re brainstorming ways to work with physician associations or have conversations at the national level so that each hospital doesn’t have to wage the same war with their physicians.