1. CDC’s National Healthcare Safety Network (NHSN): Past, Present, and Future
Daniel A. Pollock, M.D.
Surveillance Branch Chief
Division of Healthcare Quality Promotion
Alabama Hospital Association Quality Forum
Sheraton Hotel - Birmingham, Alabama
April 4, 2017

2. Objectives
Provide an overview of NHSN, outlining CDC’s role in healthcare surveillance, NHSN’s scope and uses, and challenges facing NHSN in the current policy environment
Describe NHSN’s strategy for leveraging advances in information technology, focusing on use of electronic healthcare data sources for antimicrobial use and resistance (AUR) surveillance
Conclude with some observations about healthcare report cards and the mounting expectations for healthcare quality measures

3. A Brief History of CDC’s Role in Disease Surveillance and Healthcare Surveillance
Malaria, in 1950, became the first disease that CDC – then the Communicable Disease Center – brought under national surveillance
By 1970, CDC had worked with state and local health departments to establish surveillance of nearly 30 communicable diseases, with approximately 60 diseases added since then
CDC’s first system for surveillance of healthcare-associated infections (HAIs) was launched in 1970, when hospitals began reporting to the National Nosocomial Infection Surveillance (NNIS) system
In 2005, CDC replaced the NNIS system with the National Healthcare Safety Network (NHSN), a healthcare surveillance system in which approximately 21,000 U.S. healthcare facilities currently participate

4. A Web-Based Healthcare Surveillance System
CDC’s NHSN –
A Web-Based Healthcare Surveillance System
Healthcare facilities: (1) Join NHSN, (2) complete an annual survey of their care capacities,
(3) submit process and outcome data manually or electronically to one or more NHSN
components, and (4) use their own data and NHSN benchmarks for analysis and action
Patient
Safety
Component
Healthcare
Worker
Safety
Component
Dialysis Component
Blood Safety Component
Long Term Care
Component
Outpatient
Procedure
Component
(Planned)
Neonatal
Component
(Planned)
CDC: Collects, analyzes, summarizes, and provides data
on healthcare-associated infections (HAIs), other adverse healthcare events, antimicrobial use and resistance, adherence to prevention practices, and use of antimicrobial stewardship programs

5. A CDC Surveillance System With Multiple Users and Uses
Facilities: Use NHSN’s tools to analyze their own data, compare their summary statistics to national benchmarks, and apply their analyses to prevention efforts and antimicrobial stewardship
CDC: Uses healthcare-associated infection (HAI), antimicrobial use, and related data for surveillance and prevention purposes
Centers for Medicare and Medicaid Services (CMS): Uses facility-level, healthcare quality measure data in its public reporting and payment programs
36 states and Washington, DC: Require facilities to report to NHSN; most state and local agencies publicly disclose facility-specific data and use the data in prevention programs

6. The HAIs Reported to NHSN Account for Substantial Morbidity and Mortality
Central line associated
bloodstream infections
(CLABSIs)
Surgical site
infections (SSIs)
Ventilator associated events (VAEs)
Bacteremia in dialysis patients
Clostridium
difficile laboratory
identified events
Catheter associated urinary tract infections (CAUTIs)

7. Some Resistant Pathogens Are Reported to NHSN As Laboratory Identified Events*
Methicillin resistant S. aureus
Vancomycin resistant Enterococcus
Multi-drug resistant Acinetobacter
Cephalosporin resistant Klebsiella
Carbapenem resistant Enterobacteriaceae
*Positive laboratory results that do not require associated clinical findings of infection for reporting purposes

8. Healthcare Process Data is Reported Because of the Links to HAI Prevention and Antimicrobial Stewardship
Central line
insertion
practices (CLIP)
Healthcare worker influenza
vaccination
coverage
Antimicrobial use and resistance (AUR)

9. NHSN’s Scope Extends Beyond HAIs to Other Adverse Events
Blood transfusion
Adverse reactions
Incidents

10. NHSN Protocol and
Data Collection Form

11. NHSN Web-based Application
HAI Data Submitted to NHSN are Entered into a CDC Database and Are Available for Immediate Analysis by NHSN Users
Healthcare Facility
CDC
Data Submission
NHSN
Database
Data Analysis
NHSN
Application
Server
NHSN Web-based Application
NHSN Web-based Application
NHSN Web-based Application

12. NHSN CLABSI Criteria
Microbiologic confirmation – A bloodstream infection that is laboratory confirmed (i.e., positive blood culture results)
Timing – Infection occurs on or after the 3rd calendar day of admission to a hospital inpatient location
Other infection source ruled out – Not secondary to an infection at another site, such as a urinary tract infection or pneumonia
Associated with central line use – A central line or umbilical catheter was in place for more than 2 calendar days and on the date of the infection event or the day before

13. NHSN CLABSI Healthcare Quality Measure Data
Numerator data – Total number of observed healthcare-associated CLABSIs among patients in inpatient care locations during the data period
Denominator data – Total number of central line days for each patient care location brought under surveillance during the data period
Data analyses – The standardized infection ratio (SIR) is the quantitative centerpiece of the CLABSI healthcare quality measure endorsed by the National Quality Forum (NQF). The SIR is calculated by dividing the number of observed CLABSIs by the number of predicted CLABSIs, producing a ratio of observed to predicted infections. The number of predicted CLABSIs is calculated using probabilities estimated from risk models that adjust for differences in patient and hospital characteristics known to contribute to CLABSI risk.

14. Standardized Infection Ratio (SIR) – The Basics
A summary statistic used to track HAIs at the healthcare facility, state, and national levels
A single SIR can provide a composite quality measure by combining HAI data across multiple strata, e.g., patient care locations, into one summary statistic, e.g., a hospital’s CLABSI SIR
A SIR value greater than 1.0 indicates more HAIs were observed than predicted
A SIR less than 1.0 is better than a SIR above 1.0

15. Standardized Infection Ratio (SIR) Table Standardized Infection Ratio
NHSN User-Generated
Standardized Infection Ratio (SIR) Table
Predicted
CLABSIs
CLABSI denominator
data
Standardized Infection Ratio

16. CLABSI Healthcare Quality Measure Data Publicly Reported as SIRs at CMS Hospital Compare Web Site
Hospital A
Hospital B
Hospital C
Georgia

17. CMS and States Require Hospitals to Report CLABSI Data to CDC’s NHSN for a Variety of Programmatic Purposes
CMS Program
Effective Date
Hospital Inpatient Prospective Payment System
2011 Acute Care Hospital ICUs
2015 Acute Care Hospital Wards
Long Term Care Hospital Prospective Payment System
2012
Cancer Hospital (Prospective Payment System Exempt)
2013
Hospital-Acquired Condition (HAC) Reduction
2015
Hospital Value Based Purchasing (HVBP)
2015
States (34)
Effective Date
AK, AL, AR, CA, CO, CT, DE, GA, HI, IL, IN, KY, MA, MD, ME, MS, NC, NE, NH, NJ, NM, NV, NY, OK, OR, PA, SC, TN,TX, UT, VA, VT, WA, WV
2006 (VT, NY) to 2017 (NE) with other states’ requirements starting between those dates

18. HAI Measurement via NHSN in the Current Policy Environment
Current Environment
Public reporting
Pay for reporting
Pay for performance
NHSN at Launch
˜ 300 hospitals
NHSN at Age
˜ 21,000 facilities
Purely voluntary and confidential system
Healthcare facilities initially enrolled had all participated in legacy CDC system(s)
Primary motivation for facilities is internal quality of care improvement
Expectation that facilities are motivated to submit data to CDC that are high quality and complete
Predominantly mandatory and public reporting system
Vast majority of healthcare facilities enrolled had not participated in legacy CDC system(s)
Primary motivation for facilities is compliance with reporting requirements
External data validation becomes more important
Impact
Changes in NHSN’s purposes, infrastructure, and operations
Intense scrutiny of HAI
case criteria, surveillance practices, and analytic methods
Pressure to simplify HAI definitions and move to electronic HAI detection and reporting

19. Hospitals and Health Networks October 2012; pages 24-26, 29-20
Gap Between How Healthcare Quality Measures Are Written and How Electronic Health Record Systems Work
Hospitals and Health Networks October 2012; pages 24-26, 29-20

20. “The Old is Dying and the New is Not Yet Born”
The Transition from Paper-Based to Electronic Health Record Systems: What’s Next and What are the Implications for Healthcare Surveillance? ?
Past
Present
Future
“The Old is Dying and the New is Not Yet Born”

21. AUR Surveillance Using NHSN: AU Data Supply Chain
Extract, transform and load AU data by means of a vendor or homegrown IT solution
Numerator: Antimicrobial days aggregated monthly by drug and patient care location
Denominator: Days present and admissions per month
AU report in
standard electronic
message
eMAR/BCMA
Systems
Hospital ADT
System
NHSN
Servers
Local AU data access via NHSN’s web interface
Analysis, visualization, and reporting AU data

22. AUR Surveillance Using NHSN: AR Data Supply Chain
Extract, transform and load AR data by means of a vendor or homegrown IT solution
Laboratory Information System (LIS),
Electronic Health Record
System (EHRs), and Admission/ Discharge/Transfer (ADT) System
Numerator: Patient-specific, isolate-based reports
Denominator: Patient days and admissions
AR report in
standard electronic
message
Hospital-wide antibiogram and additional analytic outputs
Local AR data access via NHSN web interface for analysis, visualization and data sharing
NHSN
Servers

23. AUR Surveillance Using NHSN: Serving Clinical and Public Health Purposes
Antimicrobial Use
Measurement of AU enables detection of overuse or misuse of antimicrobials for prophylaxis and treatment purposes
Antimicrobial stewardship programs (ASPs) use AU data in organized efforts to optimize drug selection, dose, duration, and route of administration
Antimicrobial Resistance
AR monitoring enables identification of drug resistance that calls for immediate control measures and provides data to evaluate interventions
AR data inform individual therapy, treatment guideline development, drug formulary decision making, and broader policy responses

24. AUR Surveillance Using NHSN: The Standardized Antimicrobial Administration Ratio (SAAR)
Measure development – CDC developed a new metric, the SAAR, to provide a set of risk-adjusted AU summary statistics that hospitals can use to compare their AU data with national benchmarks and help guide antimicrobial stewardship programs. The National Quality Forum (NQF) endorsed the measure in 2015.
O-to-E ratio - Each SAAR is an observed to predicted ratio. The observed number of antimicrobial days (i.e., reported count) is the numerator. The predicted number of antimicrobial days is statistically estimated from nationally aggregated data using a negative binomial regression model that takes into account differences in patient mix and hospital characteristics.
Interpretation - A high SAAR value (> 1.0) that achieves statistical significance (i.e., different from 1.0) indicates more AU than predicted and can serve as a signal that warrants further investigation. The SAAR is a starting point for evaluation and not a definitive measure of judiciousness or appropriateness of AU.

25. AUR Surveillance Using NHSN: SAAR Example
Calculated
SAAR values
Significantly high
SAAR values
Sample SAAR values - NHSN table, produced using synthetic data, displaying quarterly SAAR values for antimicrobials predominantly used to treat hospital onset, multi-drug resistant infections in a single hospital’s adult medical, surgical, and medical/surgical wards. Agents in this category include aminoglycosides, carbapenems (except ertapenem), 4th and 5th generation cephalosporins, penicillin B-lactam/b-lactamase inhibitor combinations, and other antimicrobials.

26. AUR Surveillance Using NHSN: Investigating High SAARs
CDC and Pew Charitable Trusts. Strategies to Assess Antibiotic Use to Drive Improvements in Hospitals

27. NHSN Antimicrobial Use Measure – NQF #2720
Current and Planned Use of the Measure: 
Public health/disease surveillance 
Quality improvement (internal to the specific organization) 
Quality improvement (external benchmarking involving multiple organizations)
Public reporting
Payment program
Regulatory and accreditation programs
Professional certification or recognition program

28. Healthcare Report Cards: Some Medical Experts Give Them Low Marks
Robert
Wachter
“ the measurement fad has spun out of control We need more targeted measures, ones that have been vetted to ensure they really matter for example, measuring the rates of certain hospital-acquired infections has led to greater emphasis on prevention and has most likely saved lives.”
The New York Times January 17, 2016

29. NQF Video Uses the NHSN CLABSI Measure to Illustrate How Measure Data Can Help Improve Care

30. More Targeted Measures
NHSN is Evolving Amid a Broad Challenge: A Tension Between Two Aspirations for Healthcare Surveillance
More Measures
Mounting societal expectations for greater transparency and accountability in healthcare via measurement of patient safety and clinical quality
More Targeted Measures
Measures and measurement systems that healthcare practitioners and organizations can use for prevention and quality improvement
Tension

31. Healthcare Report Cards: Catalyst for Change or Cause for Concern?
Positive change in clinical performance is most likely to occur if healthcare quality measurement data is:
Actionable
Complete, reliable, and valid
Deemed credible by healthcare facilities and care teams being assessed
Understood in broad terms by the public and policymakers
Concerns are most likely to be allayed by safeguards against:
Unacceptably burdensome reporting requirements
Gaming the data by providers
Inappropriate focus on what is measured and incentivized at the expense of other important aspects of healthcare
Distortions of clinical priorities or practices

32. Summing Up
The past as prologue – NHSN’s current role in surveillance of HAIs, other adverse healthcare events, antimicrobial use and resistance, adherence to prevention practices, and use of antimicrobial stewardship is the result of a decades-long growth process that began well before the system’s launch and continues today
Mounting pressure for measurement – Increasing use of healthcare surveillance in the U.S. – including monitoring and publicly reporting HAI metrics – reflects a societal trend toward greater transparency and accountability in healthcare
NHSN’s future – As NHSN evolves, the main opportunities and challenges are to help meet the rising expectations for healthcare quality measurement in ways that maximize benefits for patient care and public health while mitigating the risks of unintended, adverse consequences

33. Please contact me at dap1@cdc.gov For more information about NHSN:
Thank You!
Please contact me at
For more information about NHSN: