“8th National Biennial Conference on Medical Informatics 2012”

Making Healthcare Accessible – Role of
Comprehensive Health IT Systems

Arvind Saraf

Problem
● Healthcare costs in India are prohibitively high
● Most (76%) of it is Out of pocket
● 6.3 Crore Indians pushed into poverty (in 2004) due
to healthcare costs
● 14% of rural households / 12% of urban households
spent >10% of income on healthcare (2004)
● Well designed preventive / early diagnosis
interventions required to reduce cost
● Intervention choice varies by context
● Lack of effective universe set of interventions
● Government interventions are usually designed in
vertical silos, not effectively evaluated

Industry looks upon its own narrow
operational requirements
● IT platforms follow the industrywise vertical perspective (Eg Open source
platforms - OpenEMR, Clearhealth, Trilonis)
Independent
Hospitals Clinics Labs
/ Pharmacies

Insurance
Companies Government
/ NGO / Private
Awareness / Preventive
interventions
TPAs

Beneficiary

Need to look at Health system in its entirety
● Link up health behavior, outpatient visits,
diagnostics and hosptitalization history of an
individual
● Eg Reduction in illnesses amongst anaemic women
diagnosed and educated about it
● Inferring community level causality linkages better
● Understanding key local factors to select the right
intervention for the area / community. Eg:
● Locations with higher incidence of water-borne diseases
may require intervention on chlorine tablets for safe
drinking water
● Locations where very high fraction of cases escalate
from primary care providers to hospitals may need
better primary care providers

IT System design that allows the Complete
Systems perspective
Monitoring and Evaluation
Create, Conduct Surveys. Add Survey data
Export data for analysis

Insurance
CHW Preauthorizations
OPD
Training Claim line items, review tracking
Medical History
Activities Visits by Provider
Followups or Location Hospitalization
Sales Hospitalization details
Counsellings (consultations, tests,
Medications), Cost items

Demographic Administration
People and households Organization, staff members, schemes
Geography Family / individual Enrollment in the schemes

One such live system – Swasth Live
● Developed by Swasth India, a social business that
aims at ensuring access to healthcare for the poor
● Open-source platforms – LAMP, hosted on Amazon
EC2
● Used for:
● Insurance claims management for ~10,000 people across
~200 villages of Maharashtra and urban Bangalore
● Used in 7 clinics (and 3 organizations) across Mumbai, Delhi
and Tamil Nadu
● Why a new system?
● Hard to put together existing systems – different platforms,
lack of standards, lack of unifying services or organization

Swasth India as the Service Integrator
● Training institutes
Where applicable -
● Actuarians
● Insurance companies
● Medical protocol developers
● Social Re-insurers
Risk ● Rural Marketeers
Technical
Management
Partners
Organisations
D
es
C
on ign

d
ic lise
tr &
ac

a
Se eci

es
tin

Sp
g ● NGO's

rv
● Micro Finance
Empanelment Partner Institutions
Healthcare Community
Co-operatives
Swasth India
●

Providers & Quality support Aggregators
● Employers
Fa
● Hospitals cil Last-mile reach
it a
s

Fe tio
ic

Doctors ed n&
st

●
ba
gi

ck
Lo

● Diagnostic labs
● Pharmacies

End
Drug Suppliers Consumers
● Pharma Companies
● Distributors
7

System Components
Module Data structures Functionality
Demographic Geography – states, districts, blocks, cities and Add / edit / delete households, families,
villages, households, families, person individuals; Update master geography
information
Admin Ecosystem – organizations, staff members and Add / edit / delete organization, staff members
schemes, Enrollment into schemes and schemes; Enroll individuals or families
into schemes
Hospitalization Hospitals, Hospitalization summaries (diagnosis, Add / edit / delete hospitals, hospitalization
proposed procedures and current status), cases, hospital records, bills
Hospital records (notes, diagnostic reports,
medication administrations), Bills
Insurance Preauthorizations, Claims, Claim status Add / edit / review preauthorization, claims
Outpatient Patient visit records, Lab reports, Medical Add / edit / delete outpatient clinics and
summary, Immunization history doctors, patient visits, lab reports,
immunization
Community health Community health workers (CHW), Community Add / edit / delete CHWs, community health
health projects, Training modules and sessions projects, training modules, projects; Add
training sessions, including individual CHW
evaluations for the ssesions
Monitoring and Surveys, Reports Create and Run surveys; Enter survey data
Evaluation point; Create and Generate reports

Business Analytics on the fly
for Healthcare Enterprises
using the Cloud Model

( NCMI 2012 )
5th Feb 2012
Indrajit Bhattacharya 1, 2,

Anandhi Ramachandran2, B.K.Jha1

1 Birla Institute of Technology,( Noida Campus ), Mesra , Ranchi
2 International Institute of Health Management and Research, New Delhi

Health 2.0 India 2012
“ Healthcare today is receiving a tsunami
of data .

We are data rich but care poor.

The challenge today is transforming
data to actionable care.”

Roadblock to eHealth : Data is
fragmented & changes over time
• Data can be turned to intelligence that
can make difference between effective
and timely care versus costly and
ineffective or even inappropriate action.”

– Hospital and Healthcare Management
Nov 2011

“As providers increasingly get information and
more clinical data into their repositories from
the use of new technologies … coming as a
result of the meaningful use requirements,
they’re coming up with new applications for
analytics.”
—Judy Hanover, Research Director,
IDC Health Insights

Analytics Value across Healthcare
Ecosystem
Healthcare Providers
• Clinical quality initiatives and reporting
• Operational efficiencies
• Financial performance management
• Pay-for-performance initiatives
Pharmaceutical / Biotechs
• Comparative effectiveness
• Adaptive trials to support personalized medicine
• Consumer and physician engagement and decision support
Academic Medical Centers
• Translational, clinical and comparative effectiveness research
• Collaborative and extra-enterprise research
Public Health
• Disease surveillance
• Comparative effectiveness and clinical utility studies

Business Intelligence (BI )
• Business intelligence (BI) tools for hospitals ; such as
those offered by SAS Institute Inc. to develop
scorecards to track quality indicators across EHR
systems.
• Advantages ( not limited to ) :
– tune up bed and inventory utilization and staffing
– Provide predictive trends for cost effective decision making
– access to actionable knowledge that can measurably
demonstrate ROI helping in driving operational efficiency
and optimizing patient care

• Limitation
– Cost of procurement and maintenance

What is Business Analytics on SaaS?
• A delivery model for business intelligence in
which applications are typically deployed
outside of a company’s firewall at a hosted
location and accessed by an end user with a
secure Internet connection.
• The vendors provide it either on subscription
or on pay - as - you - go model
– (http://www.saas-showplace.com)

Basic BI Architecture on Cloud
Data warehousing Business Performance
tools OLAP Data Mining Reporting Management

Software as a Service - SaaS

Data Warehouses
( Platform as a Service - PaaS)

Processing Power and Source Data Storage
( Infrastructure as a Service – IaaS )

OLAP : Online Analytical processing
Source : Stevan Mrdalj, 2011,
“Would Cloud Computing Revolutionize Teaching Business Intelligence Courses”,
Issues in Informing Science and Information Technology, Vol. 8

Characteristics of good BI
• Structured or Unstructured Data
• Data Quality and Integration
– for converting data into a format readable by the database
• Healthcare Data Warehouse
– for storing data used by BI
• Healthcare Business Intelligence & Analytics Engine
• Healthcare Portal
– for display of data for healthcare customers

Business Intelligence on Demand

Source : ( Willem 2010)

SaaS model of BI in Healthcare

• Hospital Information Systems
• ERP
•Legacy Systems
•Documents
Source : Ideal Analytics 2012

Benefits of adopting cloud computing
to healthcare
• Supply chain Management and Capacity building
• Scalable Infrastructure
• Collaboration with companies offering similar
services
• Accessing Insurance details
• Fast and Easy access of health records
• Standard Integration
• Report generation using dashboards and KPI
• Increased Customer Service Quality

Benefits
VISIBILITY
Different faces View the data from various angles, needs and
of the same data aspects

GRANULARITY
Deep dive into Drill down, roll up, slice and dice, group and
the data find hidden correlations

Accessing any
AVAILABILITY data, any time, Data anywhere, anytime to the authorized user
any where
Can be used Data, information and knowledge at the
very well by a
SIMPLICITY
non-technical
disposal of the user instantly without any
person special training!

FLEXIBILITY
Integration, Cut n Slice, ship out chunk, integrate, cube It,
externalization and show selectively!

WHAT-IF- The change
ANALYSIS effect
What –happen-when something should occur!

PREDICTABILITY
Forecast and View the future and view it with little changes
Trend Analysis too!

Key Differentiators
On-Demand Self-Serving Analytics

Large Data Handling

Performance

Data Load and View Update Strategy

Enterprise Scalability

Flexibility in Analysis

Externalization

Implementation Time and Cost

Measuring Performance : NQF-Endorsed® Standards

NQF ( National Quality Forum ) Reports

Billing of different specialty

Billing of different specialty - II

Evidenced Based Benefits ( EBB)
@ NCMI 2012
• “ Cloud Benefits : 50 – 70% IT Cost reduction,
30% power saving , efficient and effective
resource allocation” : Dr. Jack Li, TMU

• “ BI Benefits : Demonstrate benefits of HIS /
EMR adoption” : Dr. Karanvir Singh , SRGH

• Privacy enhanced – change future delivery of
HIT delivery

Conclusion
• Options for Analytics for M&E of health
indicators in MDG , NCD as well as
environmental and climatic studies

• Implementing BI in Cloud would help in
reducing Capital investments and
tremendously improve in decision making by
Healthcare and Public health organizations
– Reduce cost of care
– Improve health outcomes

NCMI-2012 3-5 Feb 12,N Delhi

LEVERAGING DATA ANALYTICS
IN HEALTHCARE –SOME
SUCCESS STORIES

Gp Capt ( Dr) Sanjeev Sood
MD,Mphil (HHSM)
Hosp & Health Systems Administrator

Introduction
• Breakthroughs in data-capturing technologies,
data standards, data storage, health
management information systems (HMIS) and
modelling and optimization sciences have
created opportunities for large-scale analytics
programs.
• Several HCOs in the private sector have not only
leveraged fact based decision making, but also
created sustained competitive advantage from
data-based analytics.
• They have their business strategies at least in
part-around their analytical capabilities.

Defining Data Analytics
• The science of extensive use of data, statistical and
quantitative analysis, explanatory and predictive
models, and fact-based management to drive decisions
and actions.
• Analytics is a subset of what has come to be called
business intelligence: a set of technologies and
processes that use data to understand and analyze
business performance.
• The term “business analytics” now defines technology
that uses data analysis to understand business issues
in a way that can guide decision-making.
• The approach starts with a good quality data. This data
is manipulated or processed into information that is
valuable, timely, accurate, rational, feasible and reliable
for decision making.

Data Analytics Vs Data Mining
• Data analytics is distinguished from data
mining by the scope, purpose and focus
of the analysis.
• Data miners sort through huge data sets
using sophisticated SW to identify
undiscovered patterns and establish
hidden relationships.
• Data analytics focuses on inference, the
process of deriving a conclusion based
solely on what is already known by the
researcher.

• “As a general rule, the most
successful organisation today is the
one with the best information”

• We are drowned in data,but starved
of knowledge -John Gaisnitt

Indian scenario-basics first
• Most Indian H C O are yet to embark on analytics journey or are still in
early stages of it. They need to generate and compile good quality
data by structured and reliable reports and returns from multiple
sources. This data needs to be transformed into intelligence to guide
decision and policy makers, administrators and health care
personnel.

• Availability of quality data on morbidity patterns and patient safety
are grossly inadequate in India to design innovative health insurance
products for population and institutionalize effective patient safety
programmes in hospitals.

• Currently, most HCOs are data poor, some are data rich, but
information poor; very few could be data and information rich.

Typical Applications of Data Analytics in
Healthcare
• Practice of evidence based medicine –
Adhering to online clinical protocols. The
Department of Veterans Affairs is currently
using this approach extensively.
• Early detection of emerging disease vectors,
spotting outbreak of epidemic
• Prevention of fraudulent health insurance
claims.
• Data mining is being used by hospitals to
predict the ALOS, which helps them better
manage the patients, physicians and the

Typical Applications of Data
Analytics in Healthcare
• Capacity management is among hospitals’
key challenges. When hospitals do not
successfully manage capacity assets, they
suffer by way of revenue loss, operational
inefficiency, delay and patient
dissatisfaction.
• Advanced Analytics can impact the way
hospitals manage their capacity and other
processes by enabling forecasting and
scheduling for the immediate and longer
term.

NRHM – Gets the IT Edge
• Health Statistics Information Portal – a web based
MIS – facilitates speedy & efficient flow of
information from periphery to centre
• Tools for advanced data analysis, reporting,
monitoring, evaluation & programme
management
• More efficient public health planning &
forecasting for service provisioning, emergency
preparedness ,resources mobilization
• Objective – data for Action

Sir Ganga Ram Hospital
• SGRH, a pioneer in health informatics, has
been using data mining with SpeedMiner, a
data mining SW product by Hesper.
SpeedMiner was installed as an adjunct to HIS
at SGRH
• An effective business intelligence tool which
helps in data analytics and real time
monitoring of the KPIs, query handling , and
serves as a quality dashboard through the
various data collated over a period of time
under specific heads.

Tracking Infection control data
• Each of the hospitals in the Apollo group tracks
infection control parameters month after month and
these are benchmarked with standards and variations
and values are thoroughly analyzed. Periodically
clinical studies on infection control, pathogens and
other related areas are also carried out .
• All infection control parameters are tracked as part of
the ACE 25 CLINICAL EXCELLENCE initiative of Apollo
hospitals where key Quality parameters of each
hospital in the Apollo group are entered on an Online
Dashboard, scored and reviewed by the highest
Leadership of the group each month

Comprehensive Unit-Based
Safety Program (CUSP)

• . CUSP lets hospital identify safety
concerns, learn about successful
approaches, develop and initiate solutions,
and perform regular safety assessments
based on data analytics.

HealthMap- Tracking Emerging Health Threats
Through Online Database

• . HealthMap is one such innovation that is
a freely accessible, automated electronic
data-mining project for monitoring,
organizing, and visualizing reports of
global disease outbreaks according to
geography, time, and infectious disease
agent.

HealthMap
• In operation since 06, and created by John
Brownstein, and Clark Freifeld of Children's
Hospital Boston and Harvard Medical School,
HealthMap acquires data from a variety of freely
available electronic media sources (e.g. ProMED-
mail, Euro surveillance, Wildlife Disease
Information Node to obtain a comprehensive view
of the current global state of infectious diseases.
Thus, HealthMap is a public website bringing
together disparate data sources to achieve a
unified view of the current global state of
infectious diseases.

Decision Analysis Helps Allocate Health
Care Funds in the UK

• . In some cases, decision-making
techniques can be used to maximize
allocatory efficiency
– The UK’s National Health Service (NHS) is
funded through general tax revenues. The funds
are dispersed to about 105 different local health
authorities, amounting to annual funding for
approximately $35 billion. With such a large sum
of national funds going to such an important
area, the decision-making process to justly
allocate funds can be difficult indeed.

The Use of Goal Programming for
Tuberculosis Drug Allocation in Manila
• The objective function of the model was to meet the
target cure rate of 85% (which is the equivalent of
minimizing the underachievement (saticficing) in the
allocation of anti-TB drugs to the 45 centres).
• Four goal constraints considered the interrelationships
among variables in the distribution system.
– Goal 1 was to satisfy the medication requirement (a six-month
regimen) for each patient.
– Goal 2 was to supply each health centre with proper allocation.
Goal 3 was to satisfy the cure rate of 85%.
– Goal 4 was to satisfy the drug requirement of each health
centre.

Using Bayes’ theorem to develop
a decision tree
• A group of medical professionals is considering the
construction of a private clinic.
• If the medical demand is high (i.e, there is a favourable
market for the clinic), the physicians could realize a net
profit of $ 100,000.
• If the market is not favourable, they could lose
$40,000. Of course, they don’t have to proceed at all,
in which case there is no cost. In the absence of any
market data, the best the physicians can guess is that
there is a 50-50 chance the clinic will be successful.
The market research team using the Bayes’ theorem of
probability constructed a decision tree to help analyze
this problem and take best course of action for the
medical professionals.

Conclusion
• Data analytics focuses on inference, the process of
deriving a conclusion based solely on scientific
knowledge and facts.
• More recently, the data has been increasingly used
by health care organizations as a part of Business
Intelligence, to make strategic decisions and
choices, and to gain competitive advantage in
market.
• Today, analytic strategy is viewed as a key engine of
a dynamic capability of an organization.
• Indian HCOs need to generate quality data first and
then analyze this for strategic decisions and
research.

The difficulty lies not so much in
developing new ideas…
…………….. as in escaping from the
old ones

If you are not riding the wave of change…
…. then you will find yourself beneath it.

Role of IT in Analytics
• Having a strong analytical orientation would
seem to be a function of data and information
technology (IT), and indeed those resources
are critical for analytical success.
• . Providing data for analytical applications
mean that it must be of high quality,
separated from transaction systems in a data
warehouse or single-purpose “mart” and
consistent throughout the organization.

Leveraging analytics in Health care
• Health information and analytics have been
extensively used in healthcare to measure health
status of the population, to assess their health
problems, for making comparisons for health status,
for planning and administration of quality health
services and for carrying out scientific research.

• The data has been increasingly used by health care
organisations as a part of BI, to make strategic
decisions and choices, and to gain competitive
advantage in market.

• Today, analytic strategy is viewed as a key engine of a
dynamic capability of an organization.

DELTA- Model for Assessing
Analytical Capability
• Data: should be discrete, granular, and clean (with no missing values or
outliers) and standardised across the health care organizations. Data quality
is no longer a technical matter but rather a vital enterprise discipline with
discernible consequences for the organizational productivity and efficiency.
• Enterprise: An enterprise approach to analytics implies that organizations
work across functions in a unified manner rather than fragmented nature of
information held in disparate silos.
• Leadership: The leadership should be committed to use analytic tools and
techniques to achieve strategic goals. Leadership analytic focus is as
important as technological innovations to achieve strategic objectives.
• Target: The healthcare organizations must have a long term strategic
target with a broad based strategic intent followed by analytics focused
strategy. The leadership must commit adequate recourses to achieve
strategic targets.
• Analysts: The healthcare organizations must have analytic talent, either
in house, or consultants to provide continuous high quality advice.

FUNCTION DESCRIPTION EXEMPLARS
Supply chain Simulate and optimize supply chain flows; reduce
Dell,Wal-Mart, Amazon
inventory and stock-outs.
Customer selection, Identify customers with the greatest profit
potential; Harrah’s, Capital One,
loyalty, and service increase likelihood that they will want the
product or Barclays
service offering; retain their loyalty.
Pricing Identify the price that will maximize yield, or profit.
Progressive, Marriott
Human capital Select the best employees for particular tasks or
jobs, New England Patriots,
at particular compensation levels. Oakland A’s, Boston Red Sox
Product and service Detect quality problems early and minimize
them. Honda, Intel
quality
Financial Better understand the drivers of financial performance
MCI, Verizon
performance and the effects of nonfinancial factors.
Research and developmentImprove quality, efficacy, and, where
applicable, safety Novartis, Amazon, Yahoo

TELE HEALTH CENTRE
FOR
RURAL INDIA

A bottom to top approach for
improving health care
Dr. Shilpa facilities at rural remote areas.
Dr. Neha Asija 1
ID no.-96

Dr. Shilpa, 96

OVERVIEW OF PRESENTATION

2

Dr. Shilpa, 96

Rural development: A Prerequisite
for National development

• 68.84 % of India’s population resides in rural areas.

• Most of Secondary & Tertiary care facilities are in cities and towns.

• Low penetration of healthcare services.

• Lack of investment in health care.

• Problem of retention of doctors in rural areas.

• Inadequate medical & diagnostic facilities in rural areas.

3

Dr. Shilpa ,96

HEALTH CARE PARADOX

4

Dr. Shilpa ,96
TELE -MEDICINE

According to World Health Organization (WHO)

Telemedicine is defined as “the delivery of healthcare services,
where distance is a critical factor, by all healthcare professionals using
information and communication technologies for the exchange of valid
information for diagnosis, treatment and prevention of disease and
injuries, research and evaluation and for continuing education of
healthcare providers, all in the interests of advancing the health of
individuals and their communities”.

5

Dr. Shilpa ,96

TYPES OF TELEMEDICINE

TELE
MEDICINE

Store Two-Way
& Interactive
Forward Television

Tele-radiography, Video conferencing
Non-emergency a face to face
&
situations ‘real time’
Tele-dermatolgy consultation
6

Dr. Shilpa ,96
Point • One patient connected to
to one doctor
• Within same hospital
Point

Point • One patient end at a time
connected to many
to specialist doctors
VARIOUS WAYS
OF Multi Point • Within the same hospital
COMMUNICATION

• Several patient ends
connected to several
Multipoint
different specialist doctors
to
• At different hospitals, in
Multipoint different geographical
distances 7

Dr. Shilpa ,96
SWOT ANALYSIS

STRENGTHS WEAKNESSES
• Improved accessibility • Limited awareness of tele
• Continuous medical health and its benefits
education • Sustainability of the model

OPPORTUNITIES THREATS
• Continue technical • Concern associated with
development and standardization
innovations
• Medico legal aspects
• Expanding internet
literacy and usage

8

Dr. Shilpa ,96
BARRIERS TO IMPLEMENTATION

SOCIO-
CULTURAL

TECHNO- LEGAL
BARRIERS
LOGICAL ISSUES

ECONOMIC
ISSUES
9

Dr. Shilpa ,96
Proposed modified model

Primary
Health
Centre
Outsourcing

Source : Indian Space Research Organization(ISRO) 10

Dr. Shilpa ,96
Super

Level 3
Specialty
Hospital

State
Medical

Level 2
College

District
Hospital

Level 1 / M
MOBILE
CHC

PHC 11

Data • Patient’s medical record and related
preparation images are transferred from consultancy
centre to specialty centre.
&
P Transfer phase
• Tele- consultation date is fixed.

H • Depending on the availability of the
requested doctor the appointment is
A Consultation accepted, rejected or kept pending.

phase
S • The appointment details are sent to
the consultation center.

E
• After the consultation the doctor
S Post gives his opinion on the case and
instructions through a post
consultation consultation page.

phase • Patient’ information is stored.
Dr. Shilpa ,96
12

Dr. Shilpa ,96

A way forward

13

1

Emerging role of Informatics to improve
Population Health

Ashish Joshi M.D., M.P.H., PhD
Assistant Professor
Center for Global Health and Development and Department of
Health Services Research Administration
College of Public Health, University of Nebraska Medical Center

Email: ashish.joshi@unmc.edu
Phone: 402-559-2327

Presentation Format
2

 Defining Informatics and its categories

 Role of Informatics in Disease Prevention and Management

 Human Centered Informatics Platform

 Case studies

 Future work

Ashish Joshi M.D., MPH

Research Map
Evidence based
Management
Health
Outcomes (Clinical training)

Informatics

Technology
Evaluation
Prevention/Population
(Public Health Training)

3

Informatics: Any activity that relates to computing or science
of information where information is defined as data with
meaning.

Biomedical Informatics: Science of information applied to or
studied in the context of biomedicine.

Bernstam et al Journal of Biomedical Informatics, 43
(1):104-110

Bio Informatics Imaging
(Molecular and cellular Informatics
processes) (Tissue)

Biomedical
Informatics

Public Health Clinical
Informatics Informatics
(Populations) (Individuals)

Public Health Informatics

 Systematic application of information and
computer science and technology to public
health practice, research, and learning.
(Yasnoff, 2003)

Informatics in Disease Prevention
and Management

Data acquisition Information Analysis

Informatics

Health Outcomes Knowledge
Dissemination Representation

Multi-dimensional Human Mind
Health Data Processing Data
Information
lost
Time
data
(When)
Information
retained
Attribute
data
(Who, What
& How) Information
Aid
overload

Place
Decision
data Human Centered
(Where) Making
Informatics
approaches

8

End users

•Demographic
•Cultural
•Behavioral
•Contextual
•Clinical
•Technology
•Access
•Cost
•Infrastructure
•Reimbursement

Technology Mediated Intervention
Framework
Attribute data
“How, why, who, Spatial data
Temporal data
what” “Where”
“When”

Population health data

Human Centered Informatics methods to support
Multidimensional, Multifactorial and Evidence based interventions

Prevention Monitoring Referral Management

Health Lifestyle Social Clinical
Education Modification Support Management

Improve healthcare Improve population health Provide cost effective,
10
access outcomes sustainable solutions

Computer Psychologists
science Doctors

Information Nurses
INFORMATICS
systems

Dietitian
Public Health
Allied healthcare
professionals
11

Manifold needs of individuals

Information about
the illnesses

Treatment Social and
Options Interactive Health Decision making
Available Technologies support

Lifestyle and
behavior support

Challenges of using Health
Information Technology

Access to
technology and
skills

Financial
Lack of and
awareness Challenges technical
barriers

Privacy and
Quality

Human Centered Informatics Platform

•User age, gender, • Set of input attributes
education • If-then decision rule
•User clinical variables algorithm
•User Knowledge,
Attitudes & Practice (KAP)

Data Information
Acquisition Processing
User interaction Library of Health
metrics Information
Information seeking Disease specific
behavior modules
Knowledge
Evaluation
Representation

• ↑access to health
information • Multiple content layout
• ↑ Knowledge and • Multimedia visualization
attitude change
• Better Health Outcomes
14

Variables U.S.A. Brazil India
Geographic disparity X X X

Cultural disparity X X X

Income disparity X X X

Health Education X X X

Chronic disease X X X

Healthcare access X X X

Healthcare cost X X X

Internet access XXX XX X

Cell Phone use X X X

Health reimbursement Insurance Public/Private/out of Out of pocket costs/Public
pocket costs
Costs of Technology X XX XXX

Cell phone
Portable enabled
Electronic Mobile Health
Telehealth disease
Medical Record Ambulance Information prevention and
Kiosk monitoring

Develop a reimbursable and sustainable cost effective population based Innovative HC Technology
15 adoption model to reduce health disparities and improve population health outcomes

Consumer
Health
Information
Platform

Cell phone
Portable
enabled
Health
disease
Information
prevention and
Kiosk
monitoring

16

Health Education Modalities

Internet
Individual Face to Printed
Group Video CD/DVD
Face material

Educator Educator
Limited Evaluation e.g. Google

U U U
U

E.g. type in
“hypertension”
Material not Tailored
Limited Time

65,100,000 results
Information
Overload Feb 4 2012

Interactive Health Information Platform

 Allow users to self-pace the program.

 Materials targeted or tailored.

 Material presented in multiple formats
including graphics, text and audio.

 Allows optimization of form, duration and
content of the educational modules.

Information Flow within IHIP

Content attribute

Technology Platform Usage
User e.g. cell phone, Outcomes
data
Features computer Assessment

Interface attribute

• Emergency room • Asthma (6)
• Primary care clinics • Influenza (7)
• Clinic waiting rooms • Multiple Myeloma (8)
• Multiple Sclerosis
• Metabolic Syndrome
• Rural • Breast Feeding Nutrition
• Slum (9)
• Tribal
Settings Medical
Conditions

Outcomes Target
Assessed populations
• Knowledge
• Children
• Attitudes
• Adults
• Practices
• Veterans
• CVD Screening
• Spanish speaking mothers

20

Acceptance of Interactive Health
Information Program

97 % 94%
91% 89%
75%

Easy to use Interesting Enjoyable Easy to Use it in
navigate future

A. Joshi et al. A Pilot study to evaluate self initiated computer patient education in children. Technol Health Care.
2007;15(6):433-44

Improvement in Asthma Knowledge
Scores

15%
13%

5%

Total study subjects Those age ≤ 11 years Those age ≥ 11 years

A. Joshi et al. A Pilot study to evaluate self initiated computer patient education in children. Technol Health Care. 2007;15(6):433-44

Change in Attitudes towards
Influenza Vaccine

67.78%
63.3%

42.2%
Before
30% After

14.4%
8.89%

The child does not need Worried that child may get Child could get bad
flu shot flu once flu shot is given reaction after getting flu
shot

A. Joshi et al. Evaluation of computer-based Patient Education and Motivation tool on
KAP Influenza Vaccination. 2009;12:1-15

28

29

30

EVALUATION
OUTCOMES
IMPROVEMENT SUSTAINABILITY

Existing
TARGETED
USERS challenges REIMBURSABLE
AND SERVICES

COST
EFFECTIVENESS

31

Future Directions

 Design and evaluate HC informatics mediated
interventions that are;
 Sustainable
 Multifaceted
 Accessible
 Reimbursable
 Tailored

 Create practice based informatics solutions through
effective collaborations among different stakeholders
for improving health outcomes.

Related Publications
 A Joshi et al. A Pilot Study to Evaluate SELF INITIATED COMPUTER Patient
Education in Children with ACUTE Asthma in Pediatric Emergency Department.
Technol Health Care. 2007; 15 (6):433-44
 A Joshi. A Prototype Evaluation of a Computer-Assisted Physical Therapy System for
Osteoarthritis. Journal of Geriatric Physical Therapy: 2008 - Volume 31 - Issue 2 - p
71–78
 A Joshi, et al. Prospective tracking of a Pediatric Emergency Department E-kiosk to
deliver Asthma Education. Health Informatics Journal. December 2009 vol. 15 (4) 282-
295
 A Joshi, et al. Usability of a Patient Education and Motivation tool using Heuristic
Evaluation JMIR 2009 Nov 6; 11(4):e47.
 A Joshi, et al. Evaluation of a Computer-based Patient Education and Motivation Tool
on Knowledge, Attitudes and Practice towards Influenza Vaccination. International
Electronic Journal of Health Education, 2009; 12:1-15
 A Joshi et al. Design and Development of a Computer based Multiple Myeloma
Educational Kiosk in VA settings. 2009 International Cancer Education Conference &
AACE-CPEN-EACE Joint Annual Meeting.
 A Joshi et al. Use of Medical Education Computer Kiosks in Different Clinical Settings.
Pediatric Academic Societies’ Annual Meeting in Baltimore, Maryland, May 2-5, 2009

34

Thanks and Questions!!!


Perceived benefits of hospital
information system & EMR by
end users

Presented By:
Anindam Basu & Dr. Anandhi Ramachandran

8th IAMI Biennial Conference (Improving Health Through
IT)

3rd to 5th February 2012. AIIMS, New Delhi 1

Role of ict in healthcare…
 Information Systems acts as a Support to the Healthcare
Industry.

 Lots and Lots of Data present in the Healthcare Industry.

Knowledge
Information

Data 2

 Studies describes about ICT systems as follows:
ICT implementation is an organization process

Substantial potential
To improve patient safety
Increase Organizational Efficiency
Increasing Patient Satisfaction

Wrong perception
ICT overcomes the role of people involved
Patient Care is Hindered

3

Classes to determine the success of
ict system

 User Attitudes and Perception.

 Use of the System itself (80/20 Rule)

 User Performance with the system.

4

literature behind the study…
 Delpierre C et al, 2004: Provided Systematic Review of 26 Papers.
 Focusing on User perceptions using EHR.
 Increases patient as well as user satisfaction.
 Qualitative Nature.

 Hier DB et al, 2004: Physicians Perception across one hospital in Chicago.
 80% acceptance rate (out of 191 physicians).

 O’ Connell RT et al, 2004: Survey done in two specialties (medicine and
pediatrics)
 Satisfaction level was high.
 Others were not satisfied.

 Kimiafar K, 2006: Hospital Information System
 57.7 % of the users were satisfied

5

types of perceived benefits…

 Direct
Benefits: Reduced Medical Errors; Paper
Reduction etc.

 Indirect Benefits:
Improve quality of care;
Improve access to data; Increased Patient
Satisfaction.

 Strategic Benefits:
Improve Patient Safety;
Improve Organization Image.

6

objectives behind the study…
 Studythe Perception of the Hospital Staff towards the ICT
system.

 Study the kind of problems faced by the staff of the Hospital.

 Government Hospital
 Location: Delhi
 152 Inpatient Beds
 30 Casualty and 26 ICU Beds
 9 Departments
 Presently has HIS for Administrative Purpose & EMR for
Clinical Purpose.
 ICT systems working more than 1.5 Years.
7

Ict Applications used in the
hospital…
 Open Source EMR & Lab Module
 PACS from GE Centricity
 Telemedicine Centre
 Access and Biometric Control (for attendance and security)
 Hospital Information System
 Patient Registration
 Patient Appointment System for OPD with Queue Management System
 Cashiering Module (Billing Module)
 Surgery Module
 Inventory Management System

 Computerized MLC Report (From EMR Template).

8

Methodology…
 Definition of the Sample: The respondent should be a regular
staff of the Hospital & should be using either the HIS/EMR
application.
 Sample Size: 52
 Questionnaire Based Study (13 Questions)
 Random Sampling
 SPSS Version 16.0 used.
 Study Conducted: May 2011

 Limitations:
 Less number of Respondents
 Open Ended Questions for taking the Holistic Views.
9

Profile of the respondents
No. of Respondents Experience
30 No. of Respondents

20
20
18
16
16
14
12
13
10
13 8
6

9 4 3
2
0
Less than
6-12
6 months 1-3 years
months More
than 3
years

Physicians Nurses Other Staff 10

It importance for the hospital

1 5 Less Important

25;17

Moderate

Important

21;20
Very Important

11

Finding HIS/EMR
1 1
4
18 Very Easy

Easy

Moderate

Difficult

Very
28 Difficult

12

Average time spend to the
application

More than 3 Hrs 10,2
Average Time Spend

1-3 hrs 7,6

30min to 1 Hr 10,3
25,2;3(O)

Less than 30 minutes

0 5 10 15 20 25

No. Of Respondents 13

Improvement after the
implementation
Neutral Improved a little bit
Satisfactory Improvement Tremendously Improved

8%
14%

40%
38%

14

Major issues faced by theM…
 Technology Issues:
Computer and Application getting hanged
Application takes longer time to open
Less support from the vendor
Lesser GUIs in the application

 Process Issues:
Manual and Electronic Record is to be maintained.
Training issues to the new employees.

 ICT System Rating: 7/10
15

Benefits perceived
Benefit Type Perceived Benefit
Direct 1) More Easy Follow up visits in OPD
2) Reduction in Turn Around Time in
OPD
3) Reduction in Medical Errors

Indirect 1) Easy Accessible data of Patient anytime
2) Increase patient satisfaction
3) Employees more accountable
4) Improved Documentation
5) Increase efficiency and effectiveness of
the employees

Strategic 1) PACS & EMR: Faster Decisions
2) Increase Patient Safety
3) Faster response to physicians clinical
orders
4) Improved Hospital Image
16

Conclusion and discussion

17

recoMMendations…
 Regular Monthly assessment.
 Updation of the technology used (thin clients &
server).
 Vendor support is a must
 Process changes: Electronic Record
 Staff should be aware of the interfaces
 GUI interfaces in the application wherever possible.

 People are important asset for any ICT system,
but processes and Technology also plays a
significant role for the success.
18

“8th National Biennial Conference on Medical Informatics 2012”

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