CitiusTech:

Showcase

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Index (1/2)

CitiusTech Showcase Page #

BI-Clinical: Audit 360 1

H-Scale: Standard Supplemental Data 2

H-Scale: Data Profiling and Aggregates 3

H-Scale: FHIR Interoperability Solution 4

Score+: Clinical Data Abstractor 5

Score+: Year-Round Campaign using Predictive Scoring 6

Score+: HCC/ Risk 7

Smart De-Identifier 8

Clinical NLP Extractor 9

SMART on FHIR: Gaps in Care Mobile App 10

Product Engineering Demo 11

Index (2/2)

CitiusTech Showcase Page #

Data Management Demo 12

Integration Demo 13

Serviceability Demo 14

DevOps Demo 15

RPA Demo 16

Cloud Managed Services Demo 17

Data Science (AI/ML) Demo 18

Clinical Data De-id Demo 19

Smart Scheduler Demo 20

Predictive Maintenance Demo 21

BI-Clinical: Audit 360
Maintain population compliance reports against measures, and
validate how/why patients have fallen in/out of compliance​. Give Value Proposition
organizations an user-friendly view of member-level, measure- ▪ Visual tree view for easy comprehension- break
level and comparison reports for a population. down the compliance information at a condition
level
▪ Better analyze differences caused due to
upgrades or implementations
▪ Business user-friendly UI for instantaneous
feedback and action
▪ Use additional outputs for a measure to answer
ad-hoc requests of why a patient fell in/out of
compliance​
▪ Reduce dependency on technical team member
to manually generate information and save time
in the process
▪ Get reports at the speed of business
▪ Support for both Provider and Payer measures
(MIPS and HEDIS)

1
H-Scale: Standard Supplemental Data
NCQA Certified Standard Supplemental Data solution Value Proposition
Take CCDA data from EHRs and process through eCDS rules
automatically to be recognized as standard data ▪ Industry-recognized certification assures data
accuracy for HEDIS

▪ Reduced audit burden and cost, increased

compliance

▪ Standard Data Integration approach increases

operational efficiency

▪ Significant cost savings due to reduced charts

chase

▪ Configurable Data and Analytics strategy to

scale operational efficiency across all
initiatives – Quality/ Cost/ Operational
beyond HEDIS

2
H-Scale: Data Profiling and Aggregates
Identify quality issues early in the data lifecycle Value Proposition
Examine, analyze and create useful summary information
of data ▪ Extract maximum value of data to gain
competitive advantage with early-assessment
of data quality
Library of Profiling and
Aggregate Functions

▪ Improved decision-making via continuous

cleansing and updating of data, to provide
critical insights

▪ Automatically identify quality issues and

Validate against
thresholds within same
business rules to rectify them using trending
file or different file reports and auto-validation

3
H-Scale: FHIR Interoperability Solution
Power seamless exchange of data on universal standard
Enable FHIR enabled data interoperability to comply with Value Proposition
CMS’ proposed IPAP rule, integrated with H-Scale
▪ Improved care co-ordination due to
availability of information at required place
and time, improving user satisfaction

▪ Unified data exchange strategy for all data

exchange needs by scaling FHIR
Interoperability across Clinical, Claims and
Operational data

▪ Seamless exchange of data to enable easy

transition to Value-Based Care

4
Score+: Clinical Data Abstractor
Use Natural Language Processing (NLP) to identify hidden
opportunities (close gaps / identify risks) in medical records Value Proposition
and improve efficiency of chart abstraction
▪ Scale up processes by reducing manual inputs
required for chart abstraction

▪ Reduce the turnaround time for each

abstraction

▪ Retrieve more value per medical record with

ability to utilize all clinical data vs only
Pre-filled values with confidence targeted ones
score suggested by NLP
Pre-annotated value
▪ Improve compliance driven by number of gaps
suggested by NLP
closed with readily available data

▪ Optimize reimbursements with accurate HCCs

capture
Additional values
found by NLP

5
Score+: Year-Round Campaign using Predictive Scoring
Improve year- round HEDIS season efficiency and maximize Value Proposition
success by targeting right set of measures, providers,
members at the right time of the year ▪ Predictive analytics based guidance to help
organizations focus energy and resources,
by matching operational efforts to value
which will be delivered

▪ Guided campaign creation with a list of

measures​

▪ Improved HEDIS / STAR ratings​

▪ Improved Operational Efficiency​

6
Score+: HCC/ Risk
Value Proposition
Help health plans identify patient risk scores both
▪ Manage Quality (HEDIS) & Risk (HCC) campaigns on
prospectively and retrospectively single platform for real-time risk scores of each
patient, to power better management of quality of
care that eventually translates into higher revenues

▪ Co-ordinate all chase efforts in unified solution,

leading to efficiency improvement and lower
provider abrasion
Pre-filled values with confidence
score suggested by NLP
▪ Improved cost control due to better management of
Pre-annotated value
suggested by NLP
patient population with prospective risk assessment

Add diagnosis codes found in medical records ▪ Better reimbursement from CMS with accurate
and create annotations for easy QA
retrospective risk assessment

▪ Comprehensive solution covering scheduling visits/

Additional values
See existing diagnosis codes in the system retrospective data collection/ prospective data
found by NLP
and validate/edit/ delete codes based on collection
information found

7
Smart De-Identifier
Generate high-utility, low-risk de-identified data
with end-to-end platform for creating, optimizing and managing Solution Highlights
de-identified data sets, supporting both Safe Harbor & Expert ▪ Support multiple data input format, including csv,
database connection etc.
Determination methods
▪ Support multi-batch processing mode with
optional linkage switch(tokenization)

▪ Provide data insights for both raw input and de-

identified output

▪ Provide risk analysis and data utility analysis

▪ Support both auto-creation and customization of

generalization rules, based on data characteristics

▪ Support De-id report generation

▪ Provide data de-identification task dashboard,

quickly showing the summary of previous tasks

8
Clinical NLP Extractor
Unlock the value of clinical notes with NLP based data
extractions to support key healthcare use cases: Solution Highlights
• Extract SNOMED codes from unstructured clinical note for cohort
building for providers Entity extraction
▪ Clinical concepts( Diagnosis, observations,
• Extract data for HEDIS measure (ABA, CBP) abstraction for payers Medications, Procedures)
▪ Numerical values(Vital signs, Lab results)
▪ Coding support- Integration with UMLS and custom
dictionaries with semantic search capability

Content extraction and contextualization

▪ Automated spell check
▪ Attribute detection - Negation, History, Subject
association in clinical entities
▪ Word sense disambiguation- correct meaning of the
abbreviation based on surrounding context
▪ Coreference resolution - detects which mentions refer
to the same entity in a text

Operationalization
▪ Efficient data labelling tool using weak supervision
▪ Model monitoring with retraining and evaluation
pipelines

9
SMART on FHIR: Gaps in Care Mobile App
Industry Challenges CitiusTech Solutions
▪ Address gaps in care to help ▪ Enable payers & providers to adopt latest web based secured FHIR standard based on REST
improve quality measures, thus architecture to exchange healthcare data in terms of FHIR resources.
significantly impacting a payer’s
▪ Data is dynamically authorized & secured using OAuth2
quality metrics
▪ Vendor neutral app can be plugged into any EHR.
▪ Improve collaboration of payers ▪ Accelerated closure of gaps improves payer quality metrics
with providers for quality
measures which payers are
tracking, enabling providers to
help close the gaps on time and
reduce payer outreach effort
Demo Details
▪ Fetch open gaps in near real ▪ Gaps-in-Care Mobile App sends patient records
time and missing details about from EHR to payer management systems for
the gaps which enables identifying gaps for patients associated with quality
providers to share relevant measures, using FHIR resources
information for closure of gaps ▪ List of open gaps and impacted measures are
fetched from Gaps Rule engine & displayed on
mobile screen, so provider can prioritize actions
based on gap expiry date

10
Product Engineering Demo

Business Scenario CitiusTech Solutions

▪ Customer has numerous legacy ▪ CitiusTech did data assessment and planned to move patient datasets in phases to minimize disruption​
systems and databases across ▪ CitiusTech engaged with the customer and suggested architecture to migrate data​
provider geographies​
▪ Architecture design ensure business continuity during on-premise to cloud transition periods​
▪ These legacy systems are
▪ Suggested options to migrate datasets in phases e.g. patient, demographics, medication etc.​
roadblocks in customers long-
term modernization & cloud ▪ ePHI security handled through Spanner IAM permissions, at-rest AES-256 encryption with Google Key
strategy​ Management Service​

▪ Started with a 2-month POC before migrating all data​

▪ They wanted to migrate
existing patient data from ▪ Migrated 22 patients with 110 patient notes, across 10 facilities, as part of the POC.
legacy DB2 to GCP Cloud​

▪ Customer reached out to Demo Details

CitiusTech for viable options ▪ CitiusTech will demonstrate the capability of migrating
and roadmap patient clinical notes to GCP and the capability to
monitor scheduled jobs through GCP console

11
Data Management Demo

Business Context CitiusTech Solutions

▪ Customer has large portfolio of ▪ CitiusTech helped develop a device communication module leveraging embedded development
expertise
medical devices installed in
hospitals across the US ▪ This module enable the devices to transmit data Ethernet & Wi-Fi channels

▪ The module also enables translation of binary device data to HL7 and JSON
▪ These medical devices are
directly interfaced with Hospital ▪ The data was ingested using Azure IoT for customer’s custom Azure-based analytics cloud
EHRs through Serial ports and
▪ A GUI portal developed enables access to device clinical and operational data for a remote admin
highly localized
▪ This design enabled device data to be accessible anywhere within a timeframe of 12 hours
▪ Customer wanted device data
to be available outside the
hospital scope for analytics Demo Details
▪ Customer also wanted the ▪ CitiusTech will demonstrate the capability of
devices to be remotely extracting clinical & operational data from medical
accessible outside of hospital device and generate patient care & device analytic
dashboards for facilities & care managers
premises

12
Integration Demo

Business Context CitiusTech Solutions

▪ Customer provides services in ▪ CitiusTech suggested the deployment of Data quality platform H-IQM for customer systems
health management, medical ▪ H-IQM was installed in parallel to the existing Mirth Integration Engine without affecting any workflow
coding, imaging and clinical
abstraction ▪ More than 30 data quality rules pertaining to Provider, patient name, MRN, DoB etc. were configured

▪ Detailed real-time dashboards developed to give daily and weekly insights into the issues in real-time
▪ Clinical abstraction has
Appointment Scheduling where ▪ H-IQM installation lead to a 98% reduction in error detection times with over 11000 error caught/month
delimited files are received
from multiple clients

▪ These files have patient

Demo Details
demographics and appointment ▪ CitiusTech will demonstrate H-IQM platform with
details and received in CSV its scalable, interoperable data quality engine that
format helps healthcare organizations manage real-time
data quality through seamless system integration
▪ There is no mechanism to
identify data quality issues in
the files leading to rejections at
destination

13
Serviceability Demo

Business Context CitiusTech Solutions

▪ Customer has a large business ▪ CitiusTech setup a dedicated ODC at Mumbai for managing Interfaces for hospitals with over 90 FTEs
of cloud-based EHR and ▪ This team handles the end-to-end requirement, development, testing and monitoring of HL7 interfaces
Practice Management systems
▪ Another CitiusTech team for 32 FTEs is setup in Chennai to manage over S1-S4 defects
▪ These systems need interfacing ▪ This team also managed product enhancements UI changes, WF enhancements, code refactoring etc.
with Hospitals during
installation but with varying ▪ The combined teams are managing over 1300 live interfaces and have resolved 2000+ defects till date
data field requirements

▪ Customer also has a large

backlog of defects for their Demo Details
systems with increasing counts ▪ CitiusTech will demonstrate an app highlighting
various types of operations metrics for monitoring
▪ A large, dedicated team was legacy healthcare applications and interfaces
needed for long-term
sustenance and reducing
operating costs

14
DevOps Demo

Business Context CitiusTech Solutions

▪ Customer is a leading benefit ▪ CitiusTech leveraged both its DevOps expertise and deep healthcare domain and regulation knowledge
management organization ▪ Goals were improving build quality, reducing manual activities, faster releases & process improvement
covering 100 million lives and
140+ health plans ▪ Lean-mgmt. methods like Value Stream Mapping used, to identify inefficiencies within deployment pipeline

▪ Standardization of OS, SQL, Visual Studio and .NET versions, POCs for tool selection and implemented SQL
▪ Customer wanted improvement CI/CD using SSDT tools
in release mgmt. and
▪ Improved code and build quality using tools like SonarQube and application monitoring
deployment activities for case
mgmt. application

▪ Application comprised of Demo Details

multiple components
developed with varied MS ▪ CitiusTech will demonstrate its Qops accelerator,
technologies such as ASP, which is an automated DevOps capability for
complete development life cycle with infrastructure
ASP.net, WinForms, MVC etc.
deployment, automated CI/CD, automation test
cases execution, DevOps Dashboard and
infrastructure de-provisioning

15
RPA Demo

Business Context CitiusTech Solutions

▪ Customer has a Revenue ▪ CitiusTech did a process assessment and prioritization for Robotic Process Automation
Cycle Management services ▪ CitiusTech began a phased implementation of RPA implementation in these processes
ecosystem for providers
▪ An Automation Anywhere bot was developed to log on payor websites & capture authorization for patients
▪ There are multiple processes ▪ 5-6 bots running for around 22 hours checked over 3500 records per day, leading to 60% FTE cost reduction
like patient authorization
checks, posting EOB, edit on ▪ Robust security i.e. separate bot credentials, RBAC, audit logging & encryption was implemented for ePHI
claims etc. in workflow

▪ All these processes are Demo Details

manual leading to repetition
of effort, low productivity and ▪ CitiusTech will demonstrate the use of Automation
higher costs Anywhere RPA bots to optimize the patient
payment authorization process for Providers
▪ Customer is looking to
introduce efficiencies and
enhancing productivity on
these processes

16
Cloud Managed Services Demo

Business Context CitiusTech Solutions

▪ Customer has cloud infrastructure ▪ CitiusTech recommended the use of Integrated Cloud Suite for multi-cloud monitoring & compliance
for administration and reporting ▪ ICS enabled monitoring idle resources, over-provisioning and billing mgmt. for both Azure and AWS
spread across both AWS and
Azure ▪ ICS also checks for all HIPAA technical controls i.e. encryption, MFA on cloud services

▪ A single dashboard for monitoring all services, costs, resources and compliance lead to high productivity
▪ Individual teams manage the
infrastructure and cloud apps ▪ ICS led to a cost reduction of $159K in the first month and 86% reduction in operational costs
using AWS and Azure monitoring
tools

▪ There are multiple inefficiencies

Demo Details
due to idle resources, over ▪ CitiusTech will demonstrate ICS and its
provisioning & multi-tool capability of managing cost, operations &
monitoring healthcare compliance of Multiple cloud
deployments (AWS, Azure, GCP etc.) for a
healthcare organization
▪ There is also a concern for HIPAA
compliance on cloud due to multi-
service deployment

17
Data Science (AI/ML) Demo

Business Context CitiusTech Solutions

▪ Customer is a leading ▪ CitiusTech designed a unified environment on Azure for storage and aggregation of
healthcare datasets
biopharmaceutical company,
providing therapeutic solutions ▪ Development & deployment of advanced analytics and ML solutions integrated with
and medicines custom visualizations

▪ Azure blob storage used for raw data, Azure SQL Data Warehouse to host multiple
▪ Current challenges included a proprietary data sets in a common data model
non-integrated approach to
▪ Scalable H2O.ai and Microsoft R-server for ML model development and deployment
analytics and segregation of
operations ▪ Azure API Management to publish, manage, secure and analyze model API

▪ Power-BI to report data statistics and data mining

▪ Customer wanted to develop an
integrated platform for
research analytics and provide
data-driven insights Demo Details
▪ CitiusTech will demonstrate MLOps platform
for monitoring healthcare models in
production. The platform has various model
evaluation techniques for Business experts,
Data Scientists & IT operations team

18
Clinical Data De-id Demo

Business Context CitiusTech Solutions

▪ Customer is a leading provider ▪ CitiusTech used Safe Harbor method for data de-identification before use by customer
systems
of physicians, advanced
practice providers and support ▪ Profiles all the tables/columns were profiled to determine the PHI nature of the data
teams to health systems and identified to be part of the 18 fields recommended by Safe Harbor.

▪ CitiusTech implemented data masking logic for each of those fields in all tables
▪ Customer wanted to use clinical
data for downstream ▪ Created mapping table & rules in PHI data env. to generate a Unique ID to point to the
meaningful date
processing but faced ePHI
challenges in export

▪ There are multiple use cases

Demo Details
which depend on population
statistics i.e. analytics but not ▪ CitiusTech will demonstrate our De-ID
individual identifiers platform that enables business users to mask
PHI data elements using Expert determination
and Safe harbor techniques and accelerate AI
model development without ePHI concerns

19
Smart Scheduler Demo

Business Context CitiusTech Solutions

▪ Customers face uncaptured ▪ Leveraged deep understanding of domain and use of technology and AI to help increase patient-
provider coordination through a no-show PoC
revenue due to missed
appointments by patients ▪ Developed an AI program to predict no-shows based on parameters like age, marital status, distance,
social determinants like income, insurance etc., along with past no-show history
▪ Increased Patient waiting time ▪ Operationalized the models into appointment scheduling system/HIS and capturing the feedback
due to no-show appointments
▪ Developed advanced visualizations to track no-show trends and model efficiency
▪ Underutilization of the staff and
resources due to late
cancellations
Demo Details
▪ CitiusTech will demonstrate an application to help
scheduling systems to optimize the scheduling process
for critical appointments like radiation therapy, CTs, etc.
by predicting Patient No shows for such slots and
enable schedulers to take smart decisions during
appointment scheduling

20
Predictive Maintenance Demo

Business Context CitiusTech Solutions

▪ Customers face cost of untimely ▪ CitiusTech leveraged its medical device expertise and understanding of AI use-cases to develop a predictive
maintenance PoC
maintenance & time sensitive
repairs for on-field devices ▪ The model takes in multiple parameters such as device logs, maintenance history, error and repair logs,
machine utilization, coolant levels etc. to predict probability of failure
▪ There are limited human ▪ Advanced dashboards showing KPIs such as Mean Time Between Failure (MTBF), Repeated Failures,
experts with accurate failure Response times, downtimes, Field-visit avoided, cost saved etc.
prediction skills

▪ There is high capital tie-up for

maintenance of spare parts Demo Details
▪ CitiusTech will demonstrate an application to help
▪ The device downtime penalties medical device service operations team with a
are tied to tight SLAs capability to proactively monitor device
performance for failure, replacements, anomalies
etc. with an intent to improve service operations
and optimize cost of service.

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