Fillable SAFER Patient Identification General Instructions (Office of the National Coordinator)

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SAFER Patient Identification General Instructions (Office of the National Coordinator)

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SAFER
Safety Assurance Factors
for EHR Resilience
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Self-Assessment
Patient Identification
General Instructions
for the SAFER Self-Assessment Guides
The SAFER Guides are designed to help healthcare
organizations conduct self-assessments to optimize
the safety and safe use of electronic health records
(EHRs) in the following areas.
Each of the nine SAFER Guides begins with a Checklist
of “recommended practices.” The downloadable SAFER
Guides provide fillable circles that can be used to indicate the
extent to which each recommended practice has been
implemented. Following the Checklist, a Practice Worksheet
gives a rationale for and examples of how to implement each
recommended practice, as well as likely sources of input into
assessment of each practice, and fillable fields to record team
members and follow-up action. In addition to the
downloadable version, the content of each SAFER Guide,
with interactive references and supporting materials, can also
be viewed on ONC’s website at www.healthit.gov/SAFERGuide.
The SAFER Guides are based on the best evidence available
at this time (2016), including a literature review, expert
opinion, and field testing at a wide range of healthcare
organizations, from small ambulatory practices to large health
systems.
The recommended practices in the SAFER Guides are
intended to be useful for all EHR users. However, every
organization faces unique circumstances and will implement a
particular practice differently. As a result, some of the specific
examples in the SAFER Guides for recommended practices
may not be applicable to every organization.
The SAFER Guides are designed in part to help deal with
safety concerns created by the continuously changing
landscape that healthcare organizations face. Therefore,
changes in technology, practice standards, regulations and
policy should be taken into account when using the SAFER
Guides. Periodic self-assessments using the SAFER Guides
may also help organizations identify areas in which it is
particularly important to address the implications of change
for the safety and safe use of EHRs. Ultimately, the goal is to
improve the overall safety of our health care system.
The SAFER Guides are not intended to be used for legal
compliance purposes, and implementation of a recommended
practice does not guarantee compliance with HIPAA, the
HIPAA Security Rule, Medicare or Medicaid Conditions of
Participation, or any other laws or regulations. The SAFER
Guides are for informational purposes only and are not
intended to be an exhaustive or definitive source. They do not
constitute legal advice. Users of the SAFER Guides are
encouraged to consult with their own legal counsel regarding
compliance with Medicare or Medicaid program requirements,
HIPAA, and any other laws.
For additional, general information on Medicare and Medicaid
program requirements, please visit the Centers for Medicare &
Medicaid Services website at www.cms.gov. For more
information on HIPAA, please visit the HHS Office for Civil
Rights website at www.hhs.gov/ocr.
▪ High Priority Practices
▪ Organizational Responsibilities
▪ Contingency Planning
▪ System Configuration
▪ System Interfaces
▪ Patient Identification
▪ Computerized Provider Order Entry
with Decision Support
▪ Test Results Reporting and Follow-up
▪ Clinician Communication
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SAFER
Safety Assurance Factors
for EHR Resilience
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Self-Assessment
Patient Identification
Introduction
The Patient Identification SAFER Guide identifies
recommended safety practices associated with the reliable
identification of patients in the EHR. Accurate patient
identification ensures that the information presented by and
entered into the EHR is associated with the correct person.
Processes related to patient identification are complex and
require careful planning and attention to avoid errors. In the
EHR-enabled healthcare environment, providers rely on
technology to help support and manage these complex
identification processes. Technology configurations alone
cannot ensure accurate patient identification.
1
Staff also must
be supported with adequate training and reliable procedures.
This self-assessment can help identify and evaluate where
breakdowns related to patient identification occur in the
healthcare setting. The self-assessment focuses on
processes within organizations related to the creation
of new patient records, patient registration, retrieval
of information on previously registered patients, and other
types of patient identification activities. The recommended
practices can help prevent or detect and mitigate problems
caused by duplicate records, patient mix-ups, and
“comingled” (or “overlay”) records.
2, 3, 4, 5, 6, 7, 8, 9, 10, 11
This guide is meant to support and enable patient matching
technology and capabilities, focusing on best practices for
improving data accuracy, which is the first necessary step to
ensuring accurate patient matching. However, patient
matching between organizations is not the focus of this guide.
The recommended practices in this Patient Identification
SAFER Guide provide support for many, varied patient
matching technologies, as well as alternatives and best
practices on specific patient attributes for patient matching,
which are likely to change over time.
Completing the self-assessment in the Patient Identification
SAFER Guide requires the engagement of people both within
and outside the organization (e.g., EHR technology
developers). Because this guide is designed to help
organizations prioritize EHR-related safety concerns,
clinician leadership in the organization should be engaged in
assessing whether and how any particular recommended
practice affects the organization’s ability to deliver safe, high
quality care. Collaboration between clinicians and staff
members while completing the self-assessment in this guide
will enable an accurate snapshot of the organization’s patient
identification status (in terms of safety), and even more
importantly, should lead to a consensus about the
organization’s future path to optimize EHR-related safety and
quality: setting priorities among the recommended practices
not yet addressed, ensuring a plan is in place to maintain
recommended practices already in place, dedicating the
required resources to make necessary improvements, and
working together to prevent and mitigate the highest priority
patient identification-related safety risks introduced by the
EHR.
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Safety Assurance Factors
for EHR Resilience
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Self-Assessment
Patient Identification
Table of Contents
General Instructions
Introduction
About the Checklist
Checklist
Team Worksheet
About the Recommended Practice Worksheets
Worksheets
References
1
2
4
5
7
8
9
23
The SAFER Self-Assessment Guides were developed by health IT safety researchers and informatics experts:
Joan Ash, PhD, MLS, MS, MBA, Professor and Vice Chair, Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon
Health & Science University;
Hardeep Singh, MD, MPH, Associate Professor of Medicine at the Michael E. DeBakey Veterans Affairs Medical Center and Baylor College of
Medicine and Chief of the Health Policy, Quality and Informatics Program at the Houston VA HSR&D Center of Excellence, and Director of the Houston
VA Patient Safety Center of Inquiry; and
Dean Sittig, PhD, University of Texas School of Biomedical Informatics at Houston, UT–Memorial Hermann Center for Healthcare Quality & Safety.
This guide was developed under the contract Unintended Consequences of Health IT and Health Information Exchange, Task Order HHSP23337003T/HHSP23320095655WC.
The ONC composite mark is a mark of the U.S. Department of Health and Human Services. The contents of the publication or project are solely the responsibility of the authors and do not necessarily represent the
official views of the U.S. Department of Health and Human Services, Office of the National Coordinator for Health Information Technology.
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Self-Assessment
Patient Identification
About the Checklist
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
>Practice Worksheets
The Checklist is structured as a quick way to enter and print your self-assessment.
Your selections on the checklist will automatically update the related section of the
corresponding Recommended Practice Worksheet.
The Domain associated with the Recommended Practice(s) appears at
the top of the column.
The Recommended
Practice(s) for the
topic appear below
the associated
Domain.
Select the level of
implementation
achieved by your
organization for each
Recommended
Practice.
Your Implementation
Status will be
reflected on the
Recommended
Practice Worksheet in
this PDF.
To the right of each Recommended Practice is a link
to the Recommended Practice Worksheet in this
PDF.
The Worksheet provides guidance on implementing
the Practice.
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Self-Assessment
Patient Identication
Checklist
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practices for Domain 1 — Safe Health IT
1.1
An enterprise-wide master patient index that includes
patients’ demographic information and medical record
number (or multiple numbers if used by different parts
of the same organization, along with primary number/
key) is used to identify patients before importing data.
Worksheet 1.1
Implementation Status
Fully
in all areas
Partially
in some areas
Not
implemented
reset
1.2
To facilitate correct patient identification, clinicians
have the ability to create personalized electronic lists
of their patients according to several criteria (e.g., user,
location, time, service).
Worksheet 1.2
1.3
Information required to accurately identify the patient
is clearly displayed on all portions of the EHR user
interface, wristbands, and printouts.
Worksheet 1.3
1.4
Patient names on adjacent lines in the EHR display are
visually distinct.
Worksheet 1.4
1.5
Medical record numbers incorporate a “check digit” to
help prevent data entry errors.
Worksheet 1.5
1.6
Users are warned when they attempt to create a record
for a new patient (or look up a patient) whose first and
last names are the same as another patient, or attempt to
look up a patient and the search returns multiple patients
with the same or similar names.
Worksheet 1.6
Recommended Practices for Domain 2 — Using Health IT Safely
2.1
Patients are registered in a centralized, common
database using standardized procedures.
Worksheet 2.1
Implementation Status
Fully
in all areas
Partially
in some areas
Not
implemented
reset
2.2
The user interfaces of the training, test, and read-only
backup environments of the EHR are clearly different
from the production (i.e., "live") version to prevent
inadvertent entry or review of patient information in the
wrong system.
Worksheet 2.2
reset
reset
reset
reset
reset
2.3
The organization has a process to assign a “temporary”
unique patient ID (which is later merged into a
permanent ID) in the event that either the patient
registration system is unavailable or the patient is not
able to provide the required information.
Worksheet 2.3
reset
reset
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Patient Identication
Checklist
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practices for Domain 2 — Using Health IT Safely
2.4
Patient identity is verified at key points or transitions
in the care process (e.g., prior to procedures and
surgeries, rooming patient, vital sign recording,
order entry, medication administration, check out).
Worksheet 2.4
Implementation Status
Fully
in all areas
Partially
in some areas
Not
implemented
reset
2.5
The EHR limits the number of patient records that can
be displayed on the same computer at the same time
to one.
Worksheet 2.5
2.6
Patients who are deceased are clearly identified as
such.
Worksheet 2.6
2.7
The use of test patients in the production (i.e., “live”)
environment is carefully monitored. When they do
exist, they have unambiguously assigned “test”
names (e.g., including numbers or multiple Z’s) and
are clearly identifiable as test patients (e.g., different
background color for patient header).
Worksheet 2.7
Recommended Practices for Domain 3 — Monitoring Safety
3.1
The organization regularly monitors its patient
database for patient identification errors and
potential duplicate patients or records.
Worksheet 3.1
Implementation Status
Fully
in all areas
Partially
in some areas
Not
implemented
reset
reset
reset
reset
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Self-Assessment
Patient Identication
Team Worksheet
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
reset page
A multi-disciplinary team should complete this self-assessment and evaluate potential health IT-related patient safety risks
addressed by this specific SAFER Guide within the context of your particular healthcare organization.
This Team Worksheet is intended to help organizations document
the names and roles of the self-assessment team, as well as
individual team members’ activities. Typically team members will
be drawn from a number of different areas within your
organization, and in some instances, from external sources. The
suggested Sources of Input section in each Recommended
Practice Worksheet identifies the types of expertise or services to
consider engaging. It may be particularly useful to engage
specific clinician and other leaders with accountability for safety
practices identified in this guide.
The Worksheet includes fillable boxes that allow you to document
relevant information. The Assessment Team Leader box allows
documentation of the person or persons responsible for ensuring
that the self-assessment is completed. The section labeled
Assessment Team Members enables you to record the names of
individuals, departments, or other organizations that contributed
to the self-assessment. The date that the self-assessment is
completed can be recorded in the Assessment Completion Date
section and can also serve as a reminder for periodic
reassessments. The section labeled Assessment Team Notes is
intended to be used, as needed, to record important
considerations or conclusions arrived at through the assessment
process. This section can also be used to track important factors
such as pending software updates, vacant key leadership
positions, resource needs, and challenges and barriers to
completing the self-assessment or implementing the
Recommended Practices in this SAFER Guide.
Assessment Team Leader
Assessment Completion Date
Assessment Team Members
Assessment Team Notes
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About the Recommend
Practice Worksheets
>Table of Contents
>About the Checklist
>Team Worksheets
>About the Practice Worksheets
>Practice Worksheets
Each Recommended Practice Worksheet provides guidance on implementing a specific
Recommended Practice, and allows you to enter and print information about your self-
assessment.
The Rationale
section provides
guidance about
"why" the safety
activities are
needed.
Enter any notes
about your self-
assessment.
Enter any follow-up
activities required.
Enter the name of
the person
responsible for the
follow-up activities.
The Suggested
Sources of Input
section indicates
categories of
personnel who can
provide information
to help evaluate
your level of
implementation.
The Examples section
lists potentially useful
practices or scenarios
to inform your
assessment and
implementation of the
specific
Recommended
Practice.
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Self-Assessment
Patient Identication
Recommended Practice 1.1
Worksheet
Domain 1 —
Safe Health IT
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
1.1
An enterprise-wide master patient index that includes patients’
demographic information and medical record number (or multiple numbers
if used by different parts of the same organization, along with primary
number/key) is used to identify patients before importing data.
12, 13
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Duplicate patient records are a common problem and can
cause harm when clinicians lack complete information on
their patients.
14
Harm can also result when two patients’
records are co-mingled. An enterprise-wide master patient
index reduces the occurrence of duplicate patient records
by increasing the likelihood that patients with previous
encounters are identified.
Suggested Sources of Input
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ The master patient index employs a probabilistic matching
algorithm that uses patients' first and last names, date
of birth, gender, and other attributes (e.g., zip code, telephone
number, the last four digits of the Social Security number).
15
▪ The organization has policies and procedures to identify and
prevent duplicate patient record creation and to integrate
unintentional duplicate records into one complete record.
14, 16
▪ Organizational policies address how to ensure correct patient
identification of information from external sources (e.g.,
external labs, pharmacies, healthcare providers).
▪ As new recommended practices are defined, the organization
updates its policies and procedures related to the use of the
master patient index.
14
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
reset page
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Recommended Practice 1.2
Worksheet
Domain 1 —
Safe Health IT
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
1.2
To facilitate correct patient identification, clinicians have the
ability to create personalized electronic lists of their patients
according to several criteria (e.g., user, location, time, service).
17
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Selecting a patient from a shorter list of
relevant patients reduces the risk of selecting
the wrong patient.
18
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ Patient lists can be automatically generated in several
formats to provide information relevant to a clinical or
administrative need: person-specific (e.g., all patients that
a clinician is responsible for), location-specific (e.g., all
patients on a particular nursing unit or clinic), time-specific
(e.g., all patients on today's schedule), and service- or
clinician-specific (e.g., all patients being cared for by a
particular specialty, service, or clinician).
13
▪ Clinicians can view (i.e., read), edit (i.e., write: create,
modify, delete), and use (i.e., execute: select a patient)
patient lists related to their own clinical purposes.
▪
▪
Patient lists should by sorted in a clinically relevant order
by default (e.g., by room number, appointment time),
rather than alphabetically, to reduce the chance of look-
alike or sound-alike names appearing close together.
13
There are two or more patient identifiers included with
each patient on the list (e.g., name, date of birth, medical
record number, gender).
13, 19, 20
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
reset page
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Recommended Practice 1.3
Worksheet
Domain 1 —
Safe Health IT
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
1.3
Information required to accurately identify the patient is clearly
displayed on all portions of the EHR user interface,
wristbands, and printouts.
13, 21
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Providing medical services to the wrong patient is a
common, preventable source of patient harm.
18, 22
Steps
should be taken to ensure that the person using an EHR to
care for a patient is addressing the intended patient. Doing
so reduces the risk of "wrong patient" errors.
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ All computer-generated EHR user interface windows
incorporate the following information to facilitate patient
identification, with appropriate exceptions for individuals
for whom such information could create other risks (e.g.,
victims of domestic violence):
13
▪ Last name, first name, date of birth (with calculated age)
▪ Gender
▪ Medical record number
▪ In-patient location (or home address or ZIP code)
▪ Recent photograph (recommended)
▪ Responsible physician (optional)
▪ Organizational policies and workflows incorporate use of
the EHR into ensuring correct patient identification.
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
reset page
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Recommended Practice 1.4
Worksheet
Domain 1 —
Safe Health IT
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
1.4
Patient names on adjacent lines in the EHR display are
visually distinct.
13
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Keeping patient names visually distinct in the EHR
reduces the likelihood of unintentionally selecting the
wrong patient. This is a basic good usability practice.
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ On all patient lists containing two or more patients with the
same last name, the names in common are displayed in a
visually distinct manner (e.g., bold, italics, different color).
13
▪ Use alternate line colors for adjacent patients.
13
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
reset page
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Patient Identication
Recommended Practice 1.5
Worksheet
Domain 1 —
Safe Health IT
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
1.5
Medical record numbers incorporate a “check digit” to help
prevent data entry errors.
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
A “check digit” program for reducing common errors in
number sequences used in patient records greatly
reduces data entry errors.
23
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ To minimize human-generated number insertion, deletion,
substitution, or transposition errors or their effects,
optimize processes for correct patient identification (e.g.,
two-person sign-off before administration of blood
transfusions).
▪ One example of a "check digit" program is the "Verhoeff
algorithm," which works with strings of decimal digits of
any length and detects all single-digit errors and all
transposition errors involving two adjacent digits.
24
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
reset page
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Patient Identication
Recommended Practice 1.6
Worksheet
Domain 1 —
Safe Health IT
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
1.6
Users are warned when they attempt to create a record for a new
patient (or look up a patient) whose first and last names are the
same as another patient, or attempt to look up a patient and the
search returns multiple patients with the same or similar names.
13
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Using automated EHR processes to prevent duplicate
records can prevent unintentional human errors that could
lead to patient harm. Creating a duplicate (i.e., split) record
or commingling two different patient records results in a
serious patient safety risk.
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ During the creation of a new patient record, a phonetic
algorithm, such as Soundex, is used to display an alert or
warning if the patient, or a patient with similar
demographic data, exists in the system.
▪ When looking up a patient, if the results list returns
multiple patients with similar demographic data, the
names are displayed in a visually distinct manner.
▪ The system monitors for similar names (i.e., nicknames),
or changed last names (e.g., marriage, divorce, adoption),
when other demographics match.
▪ An alert provides additional demographic information
context for the existing patient to help the user confirm or
rule out that it is the same patient.
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
reset page
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Recommended Practice 2.1
Worksheet
Domain 2 —
Using Health IT Safely
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
2.1
Patients are registered in a centralized, common database
using standardized procedures.
14
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Nonstandard registration practices and lack of access to
a common database are common causes of duplicate
medical records on the same patient.
Suggested Sources of Input
Clinicians, support staff, and/or
clinical administration
Health IT support staff
EHR developer
Examples of Potentially Useful Practices/Scenarios
▪ Organizational policy establishes standardized
registration procedures involving the EHR and a common
database to serve as the “source of truth” on whether a
record already exists on a person who presents for
services.
▪ The organization requires a picture ID
25
when verifying
the identity of new patients, with appropriate alternatives
for minors and others who do not have official picture IDs.
▪ The organization uses a picture ID, or appropriate
alternative when an official picture ID is not available,
or uses biometric attributes (e.g., iris or vein scan) to
authenticate the identity of established patients.
▪ Registration clerks are trained in consistent patient entry
practices across portals of entry (e.g., ER, inpatient,
clinic, phone, internet).
▪ Registration clerks are trained to look up patients using
the enterprise master patient index before creating
a new record.
▪ When new patient records are being created during the
registration process, the registrar is prompted to consider
potential matches in the existing database.
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
reset page
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Recommended Practice 2.2
Worksheet
Domain 2 —
Using Health IT Safely
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
2.2
The user interfaces of the training, test, and read-only backup
environments of the EHR are clearly different from the production (i.e.,
"live") version to prevent inadvertent entry or review of patient
information in the wrong system.
13
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
If a clinician logs into and begins using the training,
test, or read-only backup versions of the EHR by
mistake, any information he or she attempts to enter
will be lost.
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ Upon logging into a non-production environment or
whenever they "sign" orders or notes, users are reminded
(e.g., pop-up alert) that they are in a non-production
environment (i.e., their orders will NOT be carried out).
▪ The screen background color on the production (i.e.,
"live") EHR is different from all other EHR environments to
reduce the chances that a clinician will inadvertently enter
orders or document their findings on a patient in a non-
production (e.g., test) environment.
▪ EHR users are trained to understand the meaning of the
visual differences between the different environments.
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
reset page
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Recommended Practice 2.3
Worksheet
Domain 2 —
Using Health IT Safely
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
2.3
The organization has a process to assign a “temporary” unique
patient ID (which is later merged into a permanent ID) in the
event that either the patient registration system is unavailable
or the patient is not able to provide the required information.
26
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
In certain cases, care needs to be delivered to patients
not yet registered or where identity cannot be confirmed
(e.g., those who are incapacitated). Processes must be
in place to ensure that they soon have a permanent ID
and to merge records to avoid duplicate or incomplete
records.
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ A process (automated or manual, such as naming
conventions) is in place to assign temporary IDs to
newborns and patients arriving at the Emergency
Department unable to provide their demographic
information.
27
▪ Staff members are trained in areas where temporary IDs
may be required (e.g., blood banking) to ensure that
temporary records are integrated into permanent ones.
▪ Any downstream use of a temporary ID within a facility, or
in transfers between facilities, is tracked and corrected in
all electronic systems, including at transfer facilities.
▪ The organization monitors resolution of temporary IDs.
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
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SAFER
Self-Assessment
Patient Identication
Recommended Practice 2.4
Worksheet
Domain 2 —
Using Health IT Safely
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
Implementation Status
2.4
Patient identity is verified at key points or transitions in the care
process (e.g., prior to procedures and surgeries, rooming
patient, vital sign recording, order entry, medication
administration, check out).
13
Checklist
Rationale for Practice or Risk Assessment
To avoid "wrong patient" errors, care must be taken to check
the patient’s identification at all critical points in the
healthcare process and to ensure that EHR use is integrated
into workflows that support correct patient identification.
Suggested Sources of Input
Clinicians, support staff, and/or
clinical administration
Examples of Potentially Useful Practices/Scenarios
▪ Before opening a specific patient record or signing an
order, the user is shown a picture, or the name, gender,
and age of the patient.
22
▪ Clinicians are asked to “re-enter” the patient’s initials
before signing an order.
▪ Workflow, including for example, use of barcodes and
two-person sign-off, related to verification of patient
identity is evaluated to optimize use of the EHR to
prevent "wrong patient" errors.
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
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SAFER
Self-Assessment
Patient Identication
Recommended Practice 2.5
Worksheet
Domain 2 —
Using Health IT Safely
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
2.5
The EHR limits the number of patient records that can be displayed
on the same computer at the same time to one.
13, 28
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Distractions while documenting or reviewing information in
the EHR are common.
18, 22
EHRs should be designed to
reduce the likelihood of working with the wrong patient’s
record as the result of distractions. When working on
multiple patients, potential gains in efficiency might be
outweighed by the risks associated with entering or
reviewing data on the wrong patient.
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ Clinicians are engaged in developing EHR configuration
and policies to prevent errors due to distractions and the
resulting danger of working on the wrong patient chart
when several records are open.
▪ Workflow is evaluated to ensure that clinicians are able
to respond to urgent situations in which they may need
to look at a new record without completing review of a
first patient's record. The practice environment should be
designed to minimize the need to open and actively use
multiple patients' records on the same computer.
▪ Before allowing the user to change the current patient,
the system checks that all entered data has been saved
(i.e., signed) or deleted (e.g., the user recognizes that
they are entering data on the wrong patient) before
allowing the system to display a different patient’s data.
29
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
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SAFER
Self-Assessment
Patient Identication
Recommended Practice 2.6
Worksheet
Domain 2 —
Using Health IT Safely
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
Implementation Status
2.6
Patients who are deceased are clearly identified as such.
Checklist
Rationale for Practice or Risk Assessment
In many instances, selection of a deceased patient
represents a “wrong patient” error. Clinicians should be
reminded that the patient they have selected is dead.
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ The system clearly identifies when a deceased patient's
record is accessed (e.g., through a pop-up alert when
opening the record or a different background color for the
deceased patient header in the EHR).
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
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SAFER
Self-Assessment
Patient Identication
Recommended Practice 2.7
Worksheet
Domain 2 —
Using Health IT Safely
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
2.7
The use of test patients in the production (i.e., “live”) environment is carefully
monitored. When they do exist, they have unambiguously assigned “test”
names (e.g., including numbers or multiple Z’s) and are clearly identifiable
as test patients (e.g., different background color for patient header).
13, 30
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Test patients in the production system are necessary
to facilitate end-to-end testing, but care must be
taken to ensure that they are not mistaken for real
patients.
Suggested Sources of Input
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ Test patients should have names that clearly identify
them as such: BWH17, ZZZOrders or MGH23zz,
ZResults (examples are last name, first name).
▪ “Cute” names (e.g., Marcus Welby, Jim Test) should
not be used as test patients as there could be real
patients with those names.
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
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SAFER
Self-Assessment
Patient Identication
Recommended Practice 3.1
Worksheet
Domain 3 —
Monitoring Safety
> Table of Contents > About the Checklist > Team Worksheet > About the Practice Worksheets
> Practice Worksheets
Recommended Practice
3.1
The organization regularly monitors its patient database for
patient identification errors and potential duplicate patients or
records.
11, 14, 16, 31, 32
Checklist
Implementation Status
Rationale for Practice or Risk Assessment
Avoidable patient identification errors are a risk both to patients
and to the organization. Monitoring reduces the likelihood that
patients will be misidentified and harmed as a result.
Suggested Sources of Input
EHR developer
Health IT support staff
Examples of Potentially Useful Practices/Scenarios
▪ The organization has a policy to periodically monitor its
EHR database for common scenarios related to wrong
patient identification (e.g., changes in patient blood type
over time).
▪ The NQF-endorsed "order–retract–reorder" algorithm can
be used to measure the rate of erroneous orders due to
patient ID errors (NQF #2723: Wrong Patient Retract and
Reorder [WP-RAR]).
16, 22
▪ The “inconsistent gender algorithm” (e.g., use of female
pronouns in progress note of male patient) can be used to
estimate the number of erroneous freetext notes due to
patient ID errors.
31
▪ The EHR has a mechanism to run a report listing
potential duplicate patient records (e.g., records that
contain virtually the same clinical and demographic
information for patients with different names).
▪ Once identified through monitoring, duplicate records are
detected and merged.
14, 16
▪ Industry standards for duplicate record error rates are
available. The organization consistently monitors its own
duplicate record error rate, and ensures that it remains at
or below industry standards.
11, 14, 16, 32
Assessment Notes
Follow-up Actions
Person Responsible for Follow-up Action
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SAFER
Safety Assurance Factors
for EHR Resilience
References
1. Kowalczyk, L. (2013, March 7). Brigham and Women’s Hospital video uses slapstick to promote patient safety. Retrieved August
8, 2016, from Boston.com.
2. Bittle, M. J., Charache, P., & Wassilchalk, D. M. (2007). Performance improvement: registration-associated patient misidentification in
an academic medical center: causes and corrections. The Joint Commission Journal on Quality and Patient Safety, 33(1), 25-33.
3. DuVall, S. L., Kerber, R. A., & Thomas, A. (2010). Extending the Fellegi–Sunter probabilistic record linkage method for approximate
field comparators. Journal of Biomedical Informatics, 43(1), 24-30.
4. Miller, P. L., Frawley, S. J., & Sayward, F. G. (2001). Exploring the utility of demographic data and vaccination history data in the
deduplication of immunization registry patient records. Journal of Biomedical Informatics, 34(1), 37-50.
5. Lee, A. C., Leung, M., & So, K. T. (2005). Managing patients with identical names in the same ward. International Journal of Health
Care Quality Assurance, 18(1), 15-23.
6. Arellano, M. G., & Weber, G. I. (1998). Issues in identification and linkage of patient records across an integrated delivery system.
Journal of Healthcare Information Management, 12(3), 43-52.
7. Henneman, P. L., Fisher, D. L., Henneman, E. A., Pham, T. A., Campbell, M. M., & Nathanson, B. H. (2010). Patient identification
errors are common in a simulated setting. Annals of Emergency Medicine, 55(6), 503-509.
8. O'Neill, K. A., Shinn, D., Starr, K. T., & Kelley, J. (2004). Patient misidentification in a pediatric emergency department: patient safety
and legal perspectives. Pediatric Emergency Care, 20(7), 487-492.
9. Ranger, C. A., & Bothwell, S. (2004). Making sure the right patient gets the right care. Quality and Safety in Health Care, 13(5),
329-329.
10. Sideli, R. V., & Friedman, C. (1991). Validating patient names in an integrated clinical information system. Proceedings of the
Annual Symposium on Computer Application in Medical Care (p. 588). American Medical Informatics Association.
11. McCoy, A. B., Wright, A., Kahn, M. G., Shapiro, J. S., Bernstam, E. V., & Sittig, D. F. (2013). Matching identifiers in electronic health
records: implications for duplicate records and patient safety. BMJ Quality & Safety, 22(3), 219-224.
12. American Health Information Management Association. Reconciling and managing EMPIs (Updated). (2010). Journal of the
American Health Information Management Association, 81(4), 52-57.
13. Lowry, S. Z., Quinn, M. T., Ramaiah, M., Schumacher, R. M., Patterson, E. S., North, R., ... & Abbott, P. (2012). Technical
evaluation, testing, and validation of the usability of electronic health records. National Institute of Standards and Technology.
14. Dooling, J. A., Durkin, S., Fernandes, L., Just, B., Kotyk, S., Karl, E. S., & Westhafer, K. (2014). Managing the integrity of patient
identity in health information exchange (updated). Journal of the American Health Information Management Association, 85(5), 60.
15. Smith, J.A. (2010). Fundamentals for building a master patient index/enterprise master patient index. Journal of the American
Health Information Management Association.
16. Identification and prioritization of health IT patient safety measures. (February, 2016). National Quality Forum.
17. Understanding file permissions on Unix: a brief tutorial. (n.d.). Darthmouth.
18. Mardon, R., Olinger, L., Szekendi, M. (2014). Health information technology adverse event reporting: analysis of two databases.
ECRI, Westat, UHC, editors. Office of the National Coordinator for Health Information Technology.
19. National patient safety goals effective January 1, 2016. (2016). The Joint Commission.
20. Valenstein, P. N., & Sirota, R. L. (2004). Identification errors in pathology and laboratory medicine. Clinics in Laboratory Medicine,
24(4), 979-996.
21. NHS CUI design guide workstream design guide entry - patient banner version 4.0.0.0 baseline. (2015). Health & Social Care
Information Centre.
22. Adelman, J. S., Kalkut, G. E., Schechter, C. B., Weiss, J. M., Berger, M. A., Reissman, S. H., ... & Southern, W. N. (2013).
Understanding and preventing wrong-patient electronic orders: a randomized controlled trial. Journal of the American Medical
Informatics Association, 20(2), 305-310.
23. Kirtland, J. (2001). Identification numbers and check digit schemes. The Mathematical Association of America.
24. Salomon, D. (2006). Coding for data and computer communications. Springer Science & Business Media.
25. Hyman, D., Laire, M., Redmond, D., & Kaplan, D. W. (2012). The use of patient pictures and verification screens to reduce
computerized provider order entry errors. Pediatrics, 130(1), e211-e219.
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SAFER Self-Assessment | Patient Identification
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SAFER
Safety Assurance Factors
for EHR Resilience
References
26. Sittig, D. F., Ash, J. S., Zhang, J., Osheroff, J. A., & Shabot, M. M. (2006). Lessons from “Unexpected increased mortality after
implementation of a commercially sold computerized physician order entry system.” Pediatrics, 118(2), 797-801.
27. Adelman, J., Aschner, J., Schechter, C., Angert, R., Weiss, J., Rai, A., ... & Racine, A. (2015). Use of temporary names for
newborns and associated risks. Pediatrics, 136(2), 327-333.
28. Paparella, S. F. (2012). Accurate patient identification in the emergency department: meeting the safety challenges. Journal of
Emergency Nursing, 38(4), 364-367.
29. Sittig, D. F., Teich, J. M., Yungton, J. A., & Chueh, H. C. (1997). Preserving context in a multi-tasking clinical environment: a pilot
implementation. Proceedings of the AMIA Annual Fall Symposium (p. 784). American Medical Informatics Association.
30. Wright, A., Aaron, S., & Sittig, D. F. (2016). Testing electronic health records in the “production” environment: an essential step in
the journey to a safe and effective health care system. Journal of the American Medical Informatics Association.
31. Wilcox, A. B., Chen, Y. H., & Hripcsak, G. (2011). Minimizing electronic health record patient-note mismatches. Journal of the
American Medical Informatics Association, 18(4), 511-514.
32. Zech, J., Husk, G., Moore, T., & Shapiro, J. S. (2016). Measuring the degree of unmatched patient records in a health information
exchange using exact matching. Applied Clinical Informatics, 7(2), 330-340.
September 2016
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