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National Center for Emerging and Zoonotic Infectious Diseases

National Healthcare Safety Network Working to Automate Healthcare Quality Surveillance

Greater Atlanta APIC

Katherine Allen-Bridson RN, BSN, MScPH, CIC

Nurse Consultant

Surveillance Branch

Division of Healthcare Quality Promotion

Centers for Disease Control and Prevention

DATE: May 19, 2021

The findings and conclusions in this presentation are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry.

Special thanks to Daniel Pollock, MD for mentorship and slides

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Objectives§ By the end of the presentation, participants will be able to:

– Define data automation in relation to healthcare quality surveillance

– Identify current NHSN surveillance automation

– Outline NHSN’s plans for automating pandemic surveillance

– Identify future NHSN automated healthcare measures

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Data Automation- DefinitionA technique, method, or system for enabling computers or other machines to operate or control a process that eliminates or reduces the need for human intervention

Automated healthcare quality surveillance: use of computers to collect and exchangehealthcare data for purposes of (1) identifying opportunities for improvement in healthcare processes or outcomes or (2) measuring the success of healthcare improvement initiatives.

THERE ARE DEGREES OF AUTOMATION and becoming fully-automated is not a single step journey

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Healthcare-associated Infection Reporting in NHSN

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Current state§ 37,381 Active NHSN facilities (4/21/2021)§ Manual or IC software data collection and IP verification data

feed to NHSN – Manually, or– CSV import, or– CDA Import

§ NHSN DIRECT CDA Automated send

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Automated Surveillance Requirements and Challenges

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MMWR July 27, 2012 Supplement Vol 61 page 6

CDC’s Vision for Public Health Surveillance in the 21st

Century

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Harnessing data that is universally….§ Recognized§ Objective§ Consistent§ Electronically accessible

To develop healthcare surveillance definitions and quality metrics which can be tested, endorsed and used by healthcare facilities to optimize patient outcomes.

Examples of types of data:• Laboratory results• Treatment-e.g. medications• Isolation orders

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Big Data and Big Data Analytic Techniques Are Enormous Opportunities for Advances in Healthcare Surveillance and Quality Measurement

Modified from Roski J, Bo-Linn GW, Andrews TA. Creating value in health care through big data: opportunities and policy implications. Health Aff (Millwood). 2014 Jul;33(7):1115-22. doi: 10.1377/hlthaff.2014.0147. PMID: 25006136.

Big Data andPredictive Analytics

(BDPA)Fusing different datatypes on a massivescale and applying

predictive and real-timeanalysis capabilities

Data LakeA large, open information space thatcan accommodate differently formatteddata elements. For example:

• Diagnoses• Problem lists and

progress notes• Laboratory results• Medication administrations• Patient Generated Health

Data

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Efforts to Introduce, Revise, and Extend HAI and AUR MeasuresMust Contend with the Limitations of Healthcare IT

Hospitals and Health Networks October 2012; pages 24-26, 29-30

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B asic EHR C om pre he nsiveEHR fo r

p erfo rman ceme asu rem en t

Percent Adoption

U.S. Hospitals with Electronic Health Records, 2016

Non -cri tical Ac cess Ho spi ta ls

C ritica l Acce ss Hosp i tals

Ju lia A d le r-M ilste in , A Jay H o lm g re n , P e te r K ra lo ve c, C h an ta l W o rza la , T a lish a S e arcy , V a ish a li P ate l, E le ctro n ic h e a lth re co rd ad o p tio n in U S h o sp ita ls: th e e m e rg e n ce o f a d ig ita l “ad van ce d u se ” d iv id e , Jo u rn a l o f th e A m erica n M ed ica l In fo rm a tics A sso cia tio n , V o lu m e 2 4 , Issu e 6 , N o ve m b e r 2 0 1 7 , P ag e s 1 1 4 2 – 1 1 4 8 , h ttp s://d o i.o rg /1 0 .1 0 9 3 /jam ia/o cx0 8 0

P <.001

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Mostly EHRs Have Served Frontline Practitioners Poorly, But EHRs Do Gather Patient Data in One Place and Have Led to Some Notable Benefits

New York Times Magazine May 20, 2018; pages 57-60

Abraham Verghese

What the EHR has done is help reduce medication errors; it is a wonderful gathering place for laboratory and imaging information; the notes are always legible. But . . . our daily progress notes have become bloated cut and paste monsters that are inaccurate and hard to wade through . . . so much of the EHR, but particularly the physical exam it encodes, is a marvel of fiction

Abraham Verghese

Machine Medicine

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Advances in Healthcare IT Facilitate Reuse ofClinical and Laboratory Data for NHSN’s Surveillance Purposes

Laboratory results:From paper printouts to

electronic laboratory reporting

Medication administrations: From peel away labels to

bar code scans

Medical records and databases: From paper-based to

electronic systems

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Current NHSN Data Automation

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NHSN Antimicrobial Use Option of the Antibiotic Use and Resistance Module§ Antimicrobial Use Option

– Summary-level data– Numerator:

• Antimicrobial (specific) Days – monthly– Sub-stratified routes– Totals

– Denominators-monthly for location and facility• Days present (unique for AU)• Admissions

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Clinical Document Architecture (CDA)§ Health Level 7 (HL7) standard§ Provides facilities with standardized

way to package & upload data– HAI, AU, AR, Hemovigilance,

Dialysis§ CDA ≠ CSV(Excel)

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Clinical Document Architecture (CDA) cont.§ Users must have administrator or customized rights to upload CDAs

– NHSN User Rights document: https://www.cdc.gov/nhsn/acute-care-hospital/aur/index.html

§ Each CDA file contains a single event or summary for one facility § CDAs must be uploaded in a zip file

– Can contain one or many CDA files– Less than 2 MB or contain less than 1,000 files

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NHSN’s Antimicrobial Use Data Supply Chain

Numerator: Antimicrobial days aggregated monthly by agent and patient care locationDenominator: Days present and admissions per month

Electronic Medication Administration Record (eMAR), Bar Code Medication Administration (BCMA), and Hospital Admission, Discharge, Transfer (ADT) Systems

AU report in standard electronic

format

NHSN ServersLocal AU data access via

NHSN’s web interfaceAnalysis, visualization, and reporting AU data

Extract, transform and load AU data by means

of a vendor or homegrown IT solution

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Delivering AU Data to NHSN – Automation is an Option§ Clinical Document Architecture (CDA)

– For some facilities = manual CDA upload

– For some facilities = automatic CDA upload via NHSN DIRECT2,536 facilities have reported at least one month of data as of 4/14/2021

THERE ARE DEGREES OF AUTOMATION and becoming fully-automated is not likely to be a single step journey

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NHSN Plans for Automating Pandemic Surveillance

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A Slimmed Down and Automated Approach§ Daily measures that could be automated to be sent to NHSN

§ Line level data that would be pulled from the EMR and provide supplemental information about the individual, their medical history, their location, etc.

THERE ARE DEGREES OF AUTOMATION and becoming fully-automated is not likely to be a single step journey

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COVID-19 Measure Reports and Supplementary Data- Draft Examples -

Daily Measure Reports− Laboratory-Confirmed COVID-19 Inpatients

All Inpatients

− COVID-19 Inpatients Admitted From Nursing HomesAll COVID-19 Inpatients

− Mechanically Ventilated COVID-19 Inpatients All COVID-19 Inpatients

− COVID-19 Inpatients in Intensive Care UnitsAll COVID-19 Inpatients

− COVID-19 Inpatients in Isolation StatusAll COVID-19 Inpatients

Supplementary, Line-Level Data− Age

− Gender

− Race/Ethnicity

− Hospital Admission Date

− Ward or Intensive Care Unit Location

− SARS-CoV-2 Vaccination Status

− Mechanical Ventilation Status

− Co-morbidities

− Complications

− Hospital Discharge Date

− Hospital Discharge Disposition

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The Future is Nigh- Other NHSN Automation To Come

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Signed into law onDecember 13, 2016

21st Century Cures Act Provides an Important Impetus forData Automation and Interoperable Healthcare IT Systems

• Primarily designed to accelerate development and access to new drugs• Title IV includes provisions aimed at achieving

widespread interoperability among health IT systems • Requires health IT suppliers to make “all data elements”

of a patient’s record available “without special effort” via Application Programming Interfaces (APIs) • Federal rules require use of the Health Level Seven

(HL7) Fast Healthcare Interoperability Resources (FHIR) standard for data elements made accessible via APIs

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Health Level Seven’s (HL7’s) FHIR Standard

F H I R

– Fast (to design and implement)– Healthcare– Interoperability– Resources (core healthcare information elements)

• Focus is on easy implementation • Standardizes core healthcare data elements (known as FHIR resources), such as

patients, admissions, diagnostic reports, and medications• Combines features of prior HL7 versions, such as data format standards, with web

service technologies, namely APIs, that have gained wide, cross-industry use

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EHR Systems and Data Automation for NHSN Surveillance:Following the FHIR Path

FHIR Resources*Patient Encounter Vitals Order Observation Medications

Health Care Facility FHIR Server

EHR and EHR Database

Data UpdatesEHR refreshesFHIR Resources for Individual Patients

NHSN

Data PushEHR Delivers FHIR Resource Bundles –

HAI & AUR Numerator, Denominator, Line-Level Patient Data - to NHSN

(Near Term Goal)

Data PullNHSN API Calls Query

the FHIR Server for HAI & AURNumerator, Denominator,

and Line-Level Patient Data (Longer Term Goal)

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*Patient-level data that can be culled using automated processes and included in numerator, denominator, and line-level reports .

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NHSN Plans to Use the FHIR Standard for Automating HospitalHAI and AUR Data Collection and Reporting

Hospital Systems

FHIR Bundles that Deliver Num erator, Denom inator and Supplem entary Data

NHSN

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2

Local, State, and Federal Partners

FHIR-Based HAI and AUR DataCollection and Reporting

Requirem entsData Sets, Dashboards, and other

Data Provisioning

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Direct Access to HAI and AUR Data Reported to NHSN

HAI & AUR Implementation

Guide

NHSN Uses andContributes to the

FHIR Standard

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NHSN’s Current CLABSI Criteria: A Legacy of Surveillance Specifications Introduced in the 1980s

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 locationOther infection source ruled out – Not secondary to an infection at another site, such as a urinary tract infection or pneumoniaAssociated 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

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AGAIN…..Harnessing data that is universally….§ Recognized§ Objective§ Consistent§ Electronically accessible

To develop healthcare surveillance definitions and quality metrics which can be tested, endorsed and used by healthcare facilities to optimize patient outcomes.

Examples of types of data:• Laboratory • Treatment

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NHSN’s Near-Term Plans To Automate Use of Microbiology Results and Antimicrobial Use Data for HAI Surveillance and Quality Measures

• Hospital onset bacteremia

• Clostridioides difficile (C. diff.) identified from a diagnostic laboratory test and concurrent antimicrobial treatment

• Late Onset Sepsis and Meningitis in Neonates

Note: Hospital and patient-care location data reported to NHSN are available for risk adjustment now, with collection and use of patient-level data envisioned for future use

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Summary

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NHSN Data Automation Priorities and Plans§ Priorities

– Develop and deploy machine executable processes for data collection and reporting by healthcare facilities that are more timely, accurate, and scalable than manual methods

– Focus first on pandemic reporting, then healthcare-associated infection surveillance – Lead the way with standards-based, vendor-neutral interoperability solutions and guidance

§ Plans

– Begin with automated, machine-machine (M2M) reporting that enable hands-free data transmission of simple files from healthcare facilities or intermediaries to NHSN

– Advance to M2M reporting that use more sophisticated, electronic messages based on the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard

– Add automated case finding using a decision support engine embedded in the electronic case reporting infrastructure and automate assembly of FHIR-based summary measures for cases and patient-level data for M2M transmissions to NHSN in standard bundles

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Question and AnswerNHSN@cdc.gov

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Continuing Education Credit§ CEU: The Centers for Disease Control and Prevention is authorized by

IACET to offer 0.1 CEU's for this program.§ In order to receive continuing education (CE) for course # WC4480, NHSN

Electronic Reporting Involving EMR Integration please visit TCEO, https://www.cdc.gov/getCE, and follow these 9 Simple Steps before 06/19/2021.

§ The course access code is NERIEI21 (to access the post-assessment)§ Attend or listen to the presentation§ Complete the Evaluation at www.cdc.gov/GetCE§ Pass the posttest at 75% at www.cdc.gov/GetCE

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