The document discusses challenges faced by healthcare organizations during electronic health record (EHR) transitions and standardization. It outlines eight common challenges, including shortage of trained resources, complex data mapping between systems, lack of test data, over-reliance on new EHR features, differing requirements across multiple sites, issues with data migration, deciding whether to retrofit old or build new dashboards, and establishing common foundational measures. For each challenge, it provides mitigation steps such as contracting new resources, detailed data mapping, using rapid prototyping, evaluating EHR and dashboard integration options, standardizing processes and involving key stakeholders. The conclusion emphasizes the need for organizations to anticipate obstacles and avoid disruptions during an EHR transition.

1. January 2019
8 Electronic
Health Record (EHR)
Downstream Challenges
White Paper
(and approaches to mitigate them)

2. The successful implementation of HITECH Act in this
decade led to an extraordinarily wide scale adoption of
EHRs across hospitals. A decade later, the industry has
a new obsession – EHR standardization. Here, a
healthcare organization makes a conscious effort to
choose and move to its existing EHRs or adopt an
entirely new one. The benefits are multifold - A single
EHR leads to optimization and ease of interoperability
across different partners in an organization. EHR
standardization aims to regulate protocols, streamline
documentation and workflow processes for physicians,
analysts, and other stakeholders.
Furthermore, it aids in quick decision making,
compares different sites and offers recommendations
while ensuring ubiquitous, high-quality patient care.
These and several other administrative, clinical, and
operational goals are achieved through EHR
standardization.
Quality of care has several dimensions such as being
effective, patient centered, timely, efficient and
equitable. Healthcare organizations are always
challenged to provide high quality of care at
affordable costs. Effective management and correct
performance measurement of healthcare reporting
systems require identification and optimization of
multiple variables.
To achieve this, leaders in healthcare need transparent
access to clinical, operational, and financial
performance data aggregated from multiple source
systems and delivered in real time. Reporting systems
and dashboards play a pivotal role in overcoming
these challenges and help in assimilating data from
multiple sources and displaying the assessment in an
easily consumable format. Such downstream
dashboards feed on the data derived from EHR
applications and are helpful in:
▪ Effective monitoring of hospital / department’s
performance and KPIs
▪ Strategic assessment of data from different
sources, leading to improved decision making
▪ Comparative analysis of hospital’s performance
with benchmarks and historical reports
OVERVIEW
1

3. 2
▪ Efficient tracking of workflow changes
▪ Gamification
The healthcare organization that undergoes an EHR
transition maintains a long laundry list of activities. The
list is consolidated, prioritized, and bucketed under
several categories. While setting the operational and
clinical process excellence takes higher priority,
retrofitting of downstream applications with the new
EHR data is secondary.
There are several other challenges encountered by
healthcare organizations that affect the retrofit of
downstream applications with new EHR data. Below
are some of the significant challenges, potential
solutions, and mitigation guidelines.
Challenge 1: Certified Resources
Most healthcare organizations that undergo EHR
transition often face shortage of trained resources to
work on the new EHR. This is often due to budget and
time constraints and limits the number of trained
professionals.
Mitigation Steps
▪ Contract new EHR resources based on domain
areas
▪ Plan the first phase of training appropriately. Create
an effective list of modules that are required for
downstream dashboards and bucket them as per
priority. Group the modules and divide them
amongst existing resources to ensure that the
department has one resource per module
▪ Cross train other members of the team after the
first phase of training is complete
Challenge 2: Data Mapping
Data mapping is the fundamental step in dashboard
design. It’s defined as the process of creating data
element mappings between two distinct data models.
In all dashboard designs, data is mapped from
multiple sources with EHR being primary source of
information. Hence, in an event of consolidation/
transition of EHR, dashboards need to be retrofitted
and the data mapping exercise becomes critical.

4. 3
Below are few challenges that may be encountered
during this process:
▪ Multiple sets of information are present for the
same data. For e.g., multiple lists of providers can
be present based on the service they perform, viz.
OPD, IPD, etc. making one-to-one mapping
difficult
▪ Understanding the context in the which the data is
used. For e.g., a dashboard may require provider
data for billing, supervising, and/or performing.
▪ Some data elements which aren’t easily identified
and are present in the default configuration of EHR
require a custom build to pinpoint them
▪ Old EHRs were simple and had several other
supporting systems, vis-à-vis present EHRs which
are sophisticated and perform complex operations
than their predecessors. During their transition /
consolidation, many other applications become
obsolete. These add an additional level of
complexity since data mapping needs to be
performed for all data elements
Mitigation Steps
▪ Define specific role of Data Analyst (DA)
responsible for data analysis
▪ Specify an assessment phase before retrofitting
begins where DA teams up with Business Analysts
to understand the requirements and perform the
mapping process
▪ Create detailed documentation of current
dashboards, such as Business Requirements
Document (BRD), S2T mapping, bus matrix, etc.
which maps across different phases of dashboard
development
▪ Check for simplification of requirements – look for
goals to achieve rather than the algorithm / path
used in legacy systems to achieve the goals. With
the new EHR, there may be new definitions
available for simplification
Challenge 3: Presence of Test Data
Data driven testing is essential for development of any
dashboard since it checks the sanctity of input data
and verifies the validity of output data. With the EHR

5. 4
transition / consolidation, it is necessary to test the
retrofitted applications with “real” test data. This helps
to:
▪ Understand the structure / format of each data
element
▪ Generate reliable test results
▪ Increase flexibility in test executions
▪ Test data under appropriate context
▪ Maintain integrity of the environment / database
▪ Verify output of dashboards
▪ Understand complexity of retrofit activities for
better planning
▪ Reduce confusion between stakeholders and
understand what is achievable
However, in a pragmatic situation, the presence of test
data is rare. A potential data dump by the EHR vendor
might arrive only halfway through the build process
and not be used at all. Given the complexity of EHR
workflows along with the custom builds, misplaced
data elements can significantly jeopardize the effective
assessment of dashboard’s retrofit activity.
Mitigation Steps
Although, obtaining “real” test data is a challenge,
teams retrofitting can build dashboards with limited
relevant data provided by the EHR vendor. Teams
should assess the situation and build a working model
using “Rapid Pretotype and Prototyping” methods.
Pretotyping and Prototyping provides the ability to
gather and document the right requirements to
sustainably build analytics solutions based on business
priority. This model technique allows teams to:
▪ Fail quickly and provide the ability to dig the right
data
▪ Raise issues with respective stakeholders when
data is incorrect or doesn’t answer relevant
business needs
This acts as a stop-gap arrangement before investing
all resources in retrofitting the dashboard.

6. 5
Challenge 4: Over-reliance on New
EHR features
Clinical teams which consume data from dashboards
may find it difficult to prioritize EHR and downstream
applications. They can either go with:
EHR: Majority of the dashboard features are built in
the new EHR and are customized for the clinical team
to use. However, there are additional source systems
or datasets which can’t be integrated / interfaced with
new EHR and are then managed by analytics team to
build a lighter version of the existing dashboard
Traditional Downstream Applications: The
dashboards are not custom built in the new EHR, but
analytics team can retrofit the existing dashboards
with the new EHR downstream data.
The primary goal is to integrate the clinical team’s
entire data (at a single location) with the new EHR. This
may prove difficult since:
▪ Clinical teams are familiar with the current
dashboard’s design and the customized EHR
reports may not meet their needs
▪ The grid, format, graphs, printable formats of the
new EHR reports aren’t desirable
▪ In the new EHR, a moderate change in calculating
measures may not align with current
methodologies
▪ Seamless integration with other data sources
remains a challenge
The above challenges can be resolved by a
combination of the two approaches – A section of the
dashboard is built in the new EHR and the remaining
section is a custom-built solution based on the
downstream data.
Mitigation Steps
Before taking a decision, a systematic and in-depth
analysis needs to be conducted. Few pointers to
consider are:
▪ Evaluate dashboards which can be directly hosted
in EHR
▪ Check for source systems which can (or can’t) be
integrated with EHR

7. 6
▪ Categorize metrics into two groups – metrics that
can and can’t be built in the new EHR since the
source systems can’t be integrated
▪ Assess “live” samples of EHR reports and validate it
with the team’s expectations
Challenge 5: Multiple Sites with
Multiple Requirements
With inorganic growth of hospitals where parent
organizations acquire new entities (hospitals / clinics),
there can be major differences in the way these new
entities operate. The differences can be attributed to
standards, people, process, or technology. The
reporting criteria, business rules, and methodologies
can be entirely different.
During EHR consolidation / transition, the processes
are standardized across organizations. The criteria,
business rules, and methodologies used in reporting
need to exactly mirror each other, irrespective of
location / site. Initially, the process of standardization
may be overwhelming for staffs but gradually, it will
start presenting results..
Mitigation Steps
1. Create a comprehensive forum for members to
voice their opinions before each dashboard is
retrofitted
2. The forum should have key representatives from
each location along with analytics team members
3. The objective of the forum should be to build
consensus among key members on the list of
metrics and the methodology used
4. The meetings should also have strong
representation from the Data Governance team to
help achieve standardization in metrics across
locations
Challenge 6: Data Migration in the
New EHR
Most of the health systems undergoing transitions
have operated the EHR systems from several years,
some spanning more than a decade. During the EHR
transition, it’s almost impossible to migrate all patient

8. 7
data from old EHR to the new one. With the rapid
increase in data volume, few years of data (e.g. 5 years
of patient’s clinical data like LABS, RADS, Pharmacy,
Vitals, etc.) loaded in the new HER may bring severe
limitations on dashboards, which need trending for
more than 5 years. The absence of active data may
lead to void in data analysis and assessment.
Mitigation Steps
Generally, all active patient clinical entities like
diagnosis, medications, allergies, etc. are planned to
be ported to new EHR. The analytics department
responsible for building dashboards, should be taken
into confidence while overarching decisions on
historical data load are made. The requirement from
the analytics department should be articulated to the
core EHR team. For e.g., need for additional sets of
data which includes more than 5 years of data or
inactive diagnosis, medications, or allergies data.
There may be use cases where the dashboards need to
be retrofitted with new data. In such scenarios,
dashboards include historical data from legacy EHR
systems and new dataset gets added to existing ones.
However, there can be several challenges:
▪ Including new sites while extending dashboards
▪ Building new dashboards / reports which require
legacy data
▪ Ad-hoc analysis for comparison of data across
years
Challenge 7: Retrofit or New
Dashboard
Retrofit of downstream applications which gather data
from EHR is demanding and can face multiple
challenges:
▪ Data changes when moved from old to new system
▪ Changes in clinical element’s definition (e.g.
surgical cases had different business rules in old
EHR compared to new EHR) at a conceptual level
▪ Upgradation of technology since the legacy
dashboard was built
▪ Trending of data across different measures with
legacy and new EHR data is unpredictable

9. 8
Because of these challenges, it’s more efficient to build
a new dashboard with new business rules, concepts
and datasets instead of retrofitting old dashboards
with new data.
Mitigation Steps
▪ For such projects, the most crucial aspect is the
data assessment phase. Based on the outcome of
the data assessment, a decision can be made to
either retrofit old dashboards or choose new
dashboards entirely.
▪ For retrofit, teams should be prepared to face
sudden drop / increase in counts, while in new
dashboards, teams will need to refer to two
dashboards – one containing legacy data and the
other with new EHR data.
Challenge 8: Set up common
foundation measures
A healthcare organization has varied requirements for
building dashboards. The needs can be of
administrative, clinical, operational, or financial in
nature. The business requirements for building these
dashboards varies. However, there are always some
base measures that remain the same. These measures
define the foundation of reporting and are standards
across all measures. Few of the base measures can be:
▪ Definition of region, location, campus, buildings,
departments, units.
▪ Unique identification of providers / patients.
▪ Requirement of general ledger rollup structure of
reporting
The foundations need to be standardized and any
deviation will affect the entire dashboard platform.
With new EHR implementation in place, there are high
chances that these foundational measures will be
affected and they either need to be updated or
replaced with appropriate ones.
Mitigation Steps
▪ The dashboard teams should list down the
common foundation measures which can be
utilized across projects.
▪ Foundation measures should be discussed between
the EHR implementation and dashboard teams to
ensure they are included in the EHR.

10. 9
Migration to a new EHR is a significant shift for any healthcare
organization. It provides immense potential for organizations to
standardize processes for effective management and performance of
reporting systems.
During the EHR transition phase, it’s difficult to anticipate all the
obstacles and healthcare organizations need to determine the features
or requirements which suit their needs, and avoid any undesirable
blackout period. It is paramount that healthcare organizations are
prepared to handle any forthcoming fall or blackout days in the course
of this transition.
CONCLUSION

11. 10
▪ https://www.cmcrossroads.com/sites/default/files/article/file/2012/XDD3202filelistfilename1_0.pdf
▪ https://www.idashboards.com
▪ https://www.nordicwi.com/blog/consolidating-your-ehr
▪ https://www.beckershospitalreview.com/healthcare-information-technology/jumping-ship-why-hospitals-
switch-ehr-vendors-how-to-handle-the-aftermath.html
▪ https://www.beckershospitalreview.com/healthcare-information-technology/when-ehrs-collide-dealing-
with-multiple-systems-after-mergers-acquisitions.html
▪ https://www.beckershospitalreview.com/healthcare-information-technology/ssm-health-to-consolidate-
ehrs-onto-1-epic-system.html
▪ https://www.healthcatalyst.com/value-of-healthcare-dashboards
▪ https://www.healthcatalyst.com/leading-wisely-better-executive-decision-support/
▪ http://www.healthcareitnews.com/blog/unsung-benefits-hit-dashboards
▪ http://www.oakleigh.co.uk/page/1427/White-Papers/Whitepaper-Articles/Dashboards-in-Healthcare
REFERENCES

12. 11
ABOUT THE AUTHOR
Amit Kumar
Senior Healthcare Consultant, CitiusTech
amit.kumar@citiustech.com
Amit has 10+ years of experience in the Provider and Life Sciences domain in consulting, business analytics,
product management, solution designing and enterprise level dashboards. He has extensive experience in
surgical, medication surveillance, financial operation, HIE, interoperability and EHR projects, including
meaningful use, ICD9-10 transition, EHR workflows and retrofit of downstream applications.
Amit has worked on several consulting, analytical and IT projects for leading healthcare organizations in the
US and Middle East markets. He holds an Engineering degree in Computer Science and a Master’s degree in
Business Administration from IIT Bombay.

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