TO ANALYZE THE SCOPE AND ACCEPTANCE OF ELECTRONIC MEDICAL RECORDS AMONG DOCTORS IN INDIA A Project of Summer Training Submitted in partial fulfillment of the Requirements for the award of the Post-Graduate Diploma in Business Management Batch: 2009-11 SUBMITTED TO: SUBMITTED BY: Dr. Sudhir Ranjan Dash Fozia Afreen Professor and Project Guide (IMS) BM-09071 (IV Trimester) INSTITUTE OF MANAGEMENT STUDIES LAL QUAN, GHAZIABAD 1
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TO ANALYZE THE SCOPE AND ACCEPTANCE OF
ELECTRONIC MEDICAL RECORDS AMONG DOCTORS IN INDIA
A Project of Summer Training
Submitted in partial fulfillment of the
Requirements for the award of the
Post-Graduate Diploma in Business Management
Batch: 2009-11
SUBMITTED TO: SUBMITTED BY:
Dr. Sudhir Ranjan Dash Fozia Afreen
Professor and Project Guide (IMS) BM-09071 (IV Trimester)
INSTITUTE OF MANAGEMENT STUDIES
LAL QUAN, GHAZIABAD
1
TOPIC: TO ANALYZE THE SCOPE AND ACCEPTANCE
OF ELECTRONIC HEALTH RECORDS AMONG
DOCTORS IN INDIA
2
DECLARATION
I hereby declare that this submission is my own work and to the best of my
knowledge and belief, it contains no material previously published or written by
another person, nor material which to a substantial extent has been accepted for the
award of any other degree or diploma of the university or other institute of higher
learning except where due acknowledgement has been made.
Fozia Afreen (BM-09071)
Date:
3
CERTIFICATE
This is to certify that the Project entitled “The Scope and Acceptance of Electronic
Health Records among Doctors in India”, which is being submitted by Fozia
Afreen, a student of PGDM, IMS- Ghaziabad is a record of the candidates own work
carried by her under my supervision. The matter embodied in this report is original
and has not been submitted for the award of any other degree.
Project Guide:
Dr. Sudhir Ranjan Dash Date:
4
EXECUTIVE SUMMARY
As a part of PGDM Program, all the students have to undertake a project, which
should be duly approved by the faculty concern. I had the privilege of undertaking the
project on “The Scope and Acceptance of Electronic Health Records among Doctors
in India” in the organization “Religare Technova”.
The main aim of the project is to study the physician’s perception about Electronic
Medical Records and what benefits they desire from the same. For this purpose I
prepared a questionnaire and got them filled by physicians.
Based on the statistical analysis, we find that the awareness about EMR is very low in
homeopathic, ayurvedic doctors as well as therapist. On the other hand majority of the
allopathic doctors are aware of EMRs functions and benefits. It is also seen that
customers seek four major kinds of benefits from EMRs which are Time saving,
decision making, social and administrative benefits. It has also been found that
physicians in India are ready to welcome EMRs, but they also feel that its use should
not be mandated.
From the analysis of secondary research, it has been observed that inspite of being an
early adopter the extent of IT penetration in India is very low because of lack of
government initiatives. There are also many medico-legal complications involved
with the use of EMRs; Hence India needs a uniform law to avoid these complications.
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ACKNOWLEDGEMENT
The success of any research study depends upon various factors among which the
proper guidance from the experts in the industry and faculty plays an important role. I
would like to take the opportunity to thank everybody who was involved with me and
helped to make this project a success.
I would like to thank our project guide Dr. S. R. Dash for helping me and carefully
guiding me during the course of the project. He was there for me every time I had
difficulties and I greatly appreciate the useful suggestions provided by him.
Next, I would like to thank Mr. Aakash Bindal for assigning me the project and for
his proper guidance and cooperation. Without his useful tips the project would have
been incomplete.
I would also like to thank Mr. Kapil Munjal, Mr. Rajan Goyal, Mr. Amit Arora
and Mr. Rashmikant Mohanty for their useful advice and expert guidance, which
helped me in completing this project successfully.
I am also indebted to all staff members of the company for their kind and friendly
attitude and immense cooperation.
And last but not the least, I would like to thanks my Parents, Friends and
Colleagues for their constant support and encouragement.
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CONTENTS
Chapter Topic Page no.
Cover page 1
Title of project 2
Declaration 3
Certificate 4
Executive summary 5
Acknowledgement 6
Contents 7-8
List of tables and figures 9-10
1 INTRODUCTION 12-22
1.1) Company profile 12-15
1.2) Indian Healthcare Industry
15-17
1.3) SWOT Analysis of Healthcare Industry
18
1.4) Healthcare and IT 19
1.5) Electronic Health Records
20
1.6) Benefits of EHR 20-21
1.7) EHR acceptance 21-22
7
1.8) Medico-Legal aspects 22
2 OBJECTIVES OF THE STUDY
24
3 RESEARCH METHODOLOGY
26
4 LITERATURE REVIEW 28
5 DATA ANALYSIS 30-58
6 FINDINGS AND CONCLUSIONS
60-61
7 RECOMMENDATIONS 63
BIBLIOGRAPHY 65
ANNEXURE 67-89
8
LIST OF TABLES AND FIGURES
List of Tables:
List of Tables Page No
i) India’s Healthcare Indicator 16
ii) India’s growing middle class population
16
iii) Cost of key healthcare procedures in India and other countries.
17
1.1) Frequency table for Gender 30
1.2) Frequency table for Age 31
1.3) Frequency table for Area of Practice 32
1.4) Frequency table for Qualification 33
1.5) Frequency table for Years of Experience
34
1.6) Frequency table for Familiarity with EMR
35
2.1) Cross-tab between Gender and Familiarity with EMR
36
2.2) Cross-tab between Age and Familiarity with EMR
37
2.3(i) Cross-tab between Area of Practice and Familiarity with EMR
39
2.3(ii) Cross tab between Area and Familiarity with EMR
41
2.3(ii) A) Chi square test 42
2.3(ii) B) Contingency test 42
2.4(i) Cross-tab between Years of Experience and familiarity with EMR
44
2.4(ii) Years and Familiarity with EMR 46
2.4(ii) A) Chi square test 47
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2.5) Cross-tab between Qualification and Familiarity with EMR
48
3.1) Table representing KMO and Bartlett’s test
49
3.2) Table representing Communalities 50
3.3) Table representing total variance explained and extracted factors
51
3.4) Table representing Component Matrix
52
3.5) Table representing Rotated Component Matrix
53
4.1) Table representing Physician attitudes and beliefs towards EMRs
55-56
4.2) Table representing importance of EMR functions
57-58
List of Figures:
List of Figures Page No
1.1) Pie chart representing frequency of Gender
30
1.2) Bar diagram representing frequency of Age
31
1.3) Bar diagram representing frequency of Area of Practice
32
1.4) Bar diagram representing frequency of Qualification
33
1.5) Bar diagram representing frequency of Years of Experience
34
1.6) Bar diagram representing frequency of Familiarity with EMR
35
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CHAPTER 1
INTRODUCTION
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1. INTRODUCTION
1.1. Company profile:
Name: Religare is a Latin word that translates as ‘to bind together’. This name has been chosen to reflect the integrated nature of the financial services the company offers.
Symbol- The Religare name is paired with the symbol of a four-leaf clover. Traditionally it is considered good fortune to find a four-leaf clover, as there is only one four –leaf clover for every 10,000 three-leaf clovers found.
For Religare each leaf of the clover has a special meaning. It is a symbol of Hope, Trust, Care, Good Fortune.
Vision: To build Religare as a globally trusted brand in the financial services domain and present it as the ‘Investment Gateway of India’.
Mission: Providing complete financial care driven by the core values of diligence and transparency.
Brand Essence: Core brand essence is Diligence and Religare is driven by ethical and dynamic processes for wealth creation.
Religare technova Ltd. is the holding company of the IT business of a large diversified Indian translational promoter group, with business interest in Financial Services, Healthcare, Wellness, Pharmaceuticals, Aviation and Travel. Other group entities include Religare Enterprises, Fortis HealthCare, Religare Wellness (Formerly Fortis HealthWorld), Super Religare Laboratories (Formerly SRL Ranbaxy) and Religare Voyages.
The offerings of the company is divided into Products and Services. The Religare Technova umbrella includes Religare Technova Global Solutions (formerly Asian CERC information Technology Ltd and Capital Market solutions Pvt Ltd.), a global leader in providing Enterprise Software Solutions to the Capital and Financial markets; Religare Technova It services Limited, which provides Enterprise IT Solutions and Religare Technova Business Intellect Ltd, which provides knowledge Management Solutions.
Currently with over 2000 employees and presence in over 10 countries, Religare Technova is poised to be a leader in the global IT space. Religare Technova focuses
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on clients in key verticals such as Banking and Financial Services, Insurance, Capital Markets and Health Sciences (Healthcare and Pharmaceuticals)
Religare Groups:
Fortis Healthcare: Fortis Healthcare Ltd, established in 1996 was founded on the vision of creating an integrated healthcare delivery system. With 22 hospitals in India, including multispecialty and super specialty centres, the management is aggressively working toward taking this to a significant level in the next few years to provide quality healthcare facilities and services across the nation.
Religare: Religare is a global financial services group with a presence across Asia, Africa, Middle East, Europe and the Americas. The group offers a wide array of products and services ranging from insurance, asset management, broking and lending solutions to investment banking and wealth management. The group has also pioneered the concept of investment in alternative asset classes such as arts and films. With over 10,000 employees across multiple geographies, Religare serves a million clients including corporates and institutions, high net worth families and individuals, and retail investors.
Religare SRL Diagnostics: Super Religare Laboratories Ltd (formerly SRL Ranbaxy) with 11 years of inception has become the largest pathological laboratory network in South Asia. It started a revolution in diagnostic services in India by ushering the most specialized technologies, backed by innovation and diligence. The current footprint extends well beyond India in the Middle East and parts of Europe.
Religare Wellness: Religare Wellness Limited (formerly Fortis Healthworld) is one of the leading players in the wellness retail space with a footprint of 100 stores across India. The group envisages setting up a pan India world class retail network of wellness stores that would provide comprehensive solutions under one roof.
Religare Voyages: The group also operates in the domain of Integrated Air Charter and Travel, anchored under the holding company Religare Voyages Ltd. The Air Charter business is one of the largest in the non-scheduled space in the country with its own top-of-the-line fleet that comprises jets, helicopters and turbo props. The travel business is duty accredited for complete management of both in-bound and out-bound Domestic and International travel.
Religare Health
The latest venture of Religare technologies is into the Healthcare information service whose aim is enabling better healthcare through information.
Objectives:
To provide healthcare information at the right time and place, in the way users want it.
To reduce the information asymmetry in the healthcare ecosystem.
To bring together all stakeholders in healthcare, on a common platform
To offer transparent and powerful information exchange in the healthcare ecosystem.
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Features:
i. Search and Select
ii. Facilitates better healthcare
iii. Electronic health records for patients and healthcare service providers.
iv. Content on Disease, Drugs and Preventive Healthcare.
Benefits to healthcare Services
i. Opportunity to be present on Largest Healthcare Eco system in India
ii. Increases visibility and awareness on patient friendly platforms.
iii. A great tool for doctors and hospitals to regulate and schedule patient traffic
iv. Help towards achieving better diagnosis and treatment.
Board of Directors of Religare Technova
Mr. Sunil Godhwani: Chairman and Managing director of Religare enterprise.
Mr. Padam Bahl: Practicing chartered accountant and an income tax advisor.
Mr. Vikram Sahgal: Senior engineer with an experience of 27 years.
Dr. Preetinder Singh Joshi: Dr. Joshi, an eminent cardiologist, has 32 years of experience in medical profession in India and abroad.
Mr.Harpal Singh: Mr. Singh has a 26 years of experience in the corporate sector. He holds the position of senior advisor at Religare Enterprise.
Mr. Maninder Singh Grewal: Mr. Garewal, a veteran of IT industry, has an experience of 26 years and is the managing director of Religare Technova.
Mr. J. W. Balani: Mr.Balani is engaeged with the export and import of whit goods. He has more than 39 years of work experience.
Ms. Sunita Naidu: Ms.Naidu specializes in orthodontics and has a work experience of more than 15 years.
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Awards and recognition:
Recently Religare Technova has been honoured with the following prestigious awards:
Membership of the elite Microsoft Dynamics President’s Club 2008.
Star emerging SI Sales Award by Microsoft in 2008.
Mantel of Cisco Premier Certified Partner in India subcontinent.
1.2. India’s healthcare industry:
Talking about India, when it comes to healthcare there are two India: one that provides high quality middle care to middle class Indians and medical tourists and the other (in which the majority of the population lives) in which limited or no access to safe, quality care is available.
The Indian healthcare industry is seen to be growing at a rapid pace and is expected to become a US$280 billion industry by 2020.The Indian healthcare market was estimated at US$35 billion in 2007 and is expected to reach over US$ 70 billion by 2012 and US$145 billion by 2017.According to the investment commission of India healthcare sector has experienced phenomenal growth of 12 % per annum in the last four years. Rising income level and growing elderly population are all factors that are driving this growth. In addition, changing demographics, disease profiles and the shift from chronic to lifestyle diseases in the country has led to increased spending on healthcare delivery.
Even so, the vast majority of the country suffers from a poor standard of healthcare infrastructure, which has not kept up with the growing economy. Despite of having centre of excellence in healthcare in healthcare delivery, these facilities are limited and are inadequate in meeting the current healthcare demands. Nearly one million Indians die every year due to inadequate healthcare facilities and 700 million people have no access to specialist care and 80% of specialist lives in urban areas. In order to meet manpower shortages and reach world standards India would require investment of up to $20 billion over the next five years.
India has approximately 600,000 allopathic doctors registered to practice medicine. This number is however higher than the actual number practicing because it include doctors who have immigrated to other countries as well as doctors who have died. India license 18,000 new doctors a year. With a world average of 3.96 hospital beds per 1000 population India stands just a little over 0.7 hospital beds per 1000 population.
Despite of all theses drawbacks, healthcare in India is booming and is poised to become a pillar of the Indian economy over the next few decades.
The role of privatization has been crucial in the development of Indian health services. Besides providing 70% of hospitals and 40% of the hospital beds, the private sector has fully revamped the industry. Funds are more readily available,
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infrastructure and technology have drastically improved, and political issues in public hospitals have ceased.
Medical tourism has succeeded by offering high quality services at third world prices. Dental tourism has gained an especially strong reputation. Growing at 25% a year, medical tourism will easily become a $2 billion industry by 2012.
India has been known for alternative medicine for over forty years, but traditional medicine is losing popularity. Ayurveda centers are thriving due to standardization and licensing. With an emphasis on rejuvenation and detoxification, Ayurveda is gaining popularity overseas as well. This along with yoga is earning India tourists and patients worldwide. The city of Kerala has become a destination for its high-end resorts that specialize in Ayurveda.
Table i: India’s Health Indicators
No. of Doctors 5,03.900
Hospitals 15,097
No of Beds 8,70161
No. of Medical colleges 162
No of Nurses 7,37,000
Source: IndianBusiness.com/ Healthcare Industry
Revolution in the Indian healthcare industry
The two important factors that has caused a revolution in the healthcare industry of India are:
Economic Factors:
Since healthcare is dependent on the people served, India’s huge population of a billion people represent a big opportunity.
The expanding middle class has more disposable income to spend. Hence they demand for better healthcare facilities.
Table ii:
Middle class %of entire population
1998-99 44.92
2001-2002 50.53
2009-10 62.95
Source: CRIS infac,
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Today people are spending more on healthcare and preferring private services to government ones.
Hospitals in India are running at 80-90% occupancy. With the demanding for healthcare for exceeding supply,India's healthcare industry is expected to grow by around 15% a year for the next six years.
Hospitals in India conduct the latest surgeries at a very low cost. Medical tourism is also booming in India.
Cost of key Healthcare Procedures (Currency USD)
Procedure US Thailand India
Cardiac surgery 50,000 14,250 4,000
Bone marrow
transplant
62,500 62,500 30,000
Liver transport 500,000 75,500 45,000
Orthopaedic
surgery
16,000 6,900 4,500
Source: India Brand Foundation report, IBEF Research
Corporate entities entering the healthcare sector, introducing managerial practices and tools are showing a marked preference for professionals leading to the expansion of the hospital management education industry.
Government factors:
To encourage R&D government extended tax holiday to R&D companies. The benefit of full custom duty exemption for specific equipment is available for manufacturing activity to the extent of 25% of the previous year’s export turnover. This will help the research based companies.
All drugs and materials imported or produced domestically for clinical trials will be exempted from custom and excise duties. This will encourage foreign companies to produce drugs in India.
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1.3. SWOT Analysis of Healthcare Industry of India:
Strength:
Expertise in reverse technology
Support at the state government level
Emergence of biotech parks
Incentives to develop business
Natural competitive advantages of language
Low cost and ever-expanding educated workforce
Weaknesses
The rising cost of healthcare delivery
Limited access to life saving drugs
Majority of private hospitals are expensive for normal middle class family
Government is responsible to improve primary healthcare infrastructure
Opportunities
Greater incentives for original drug discovery will create opportunities for Indian companies to develop new competencies through collaborative research and global alliances.
Big pharma and biotech companies to choose India as the preferred hub for their global R&D and manufacturing operations.
Threats
The increasing cost of drug discovery and development and the increasing time to market
Declining R&D productivity
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1.4. Healthcare and IT
When it comes to the use of IT in Healthcare, the Indian government positioned itself as one of the early adopters of healthcare IT among developing countries when it launched its “Development of Telemedicine Technology” project in 1997. In 2002, the Department of Information Technology established the committee for the Standardization of Digital information in order to facilitate the implementation of telemedicine systems. In 2003,the Department published a framework for “Information Technology Infrastructure for Health in India.” This framework is centered on the philosophy that “information is determined of health” and that “healthcare is one of the keys that can benefit from the use of IT.” The framework encompasses:
Inspite of being an early adopter, India is not completely utilizing the benefits of IT in healthcare. The key IT application that are being implemented in the private healthcare sector include hospital IS, PACS and telemedicine programs. So far there are no instances of EHRs that completely integrate clinical information. The use of EHR for reporting, modeling and improving clinical decision-making is not yet a priority.
Challenges:
Policy Absence of clear, coordinated government policy to promote HIT adoption
Government funding Almost non existent government funding for HIT has resulted in lack of HIT adoption in government health facilities and a lack of trained medical informatics professionals.
Computer literacy Low computer literacy among the government staff, and to a large extent in the private provider community
Infrastructure and coordination
Lack of supporting infrastructure and coordination between public and private sector
Legacy systems Except for a few privately owned large hospitals, most patient records are paper based and very difficult to convert to electronic format.
Standards Local HIT systems that do not adhere to standards for information representation and exchange. This could be further complicated because of the use of multiple local languages by patients and some health workers
Privacy Patient confidentiality is an open area. The Supreme Court of India has not addressed the specific right of privacy issue with respect to health information
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1.5. Electronic Health Record (EHR)
An electronic health record (EHR) is a collection of data and information gathered or generated to record clinical care rendered to an individual. It is a comprehensive, structured set of clinical, demographic, environmental, social and financial data and information in electronic form, documenting the healthcare given to an individual.
The primary purpose of the electronic health record is for the ongoing care of the patient. The EHR should incorporate all significant clinical and administrative information pertaining to a given patient, thereby rendering it sufficient to enable the attending clinician to provide effective continuing care and to determine the patient’s condition at any given time. All activities that physician perform with paper records should be capable of being carried out using electronic records. The EHR should also enable healthcare providers other than the attending clinician to review the patient and render his/her opinion or assume the patients care at any time.
The secondary purposes are research/historical, epidemiology/public health, statistics, education, peer review, utilization studies, quality assurance, legal document (used as evidence) and healthcare policy development.
1.6. Benefits of EHR
EHR enables sharing of patient information any place at any time.
It reduces cost by shortening billing cycles and other core administrative and clinical operations- including storage and copying cost of medical records.
Direct data entry by clinician and staff greatly reduces transcription cost.
Create higher quality documentation (auditable, legible and organized charts and records)
Improves the accuracy of coding at the appropriate level.
Minimize the issues of incorrect and conflicting drug prescription.
EMR system greatly aids clinicians in immediate patient treatment and in capturing key information’s.
More complete records help clinicians and staffs to avoid mistakes.
Research and decision support are key uses for patient related data.
Obstacles
Startup cost of implementing such a system is high
The user needs to have some technical knowledge to use the system effectively and efficiently.
Confidentiality and security issues associated with the use of EHR.
Portability of the equipment is an issue associated with the use of EHR.
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Lack of standardized terminology, system architecture and indexing.
1.7. EHR acceptance
Many hospitals are maintaining electronic records locally. The scope of data captured however is limited to basic demographics, registration and billing. Larger hospitals that store clinical data electronically store discharge summaries with information on procedures, orders and investigation reports. Despite the system’s ability to also store detailed reports and clinical interpretation electronically, many hospitals do not use it. As a result, clinical follow-up is either very limited or not feasible. Industry analyst feel that the goal of hospitals in India is more to adopt the general concept of EHRs but that they are not utilizing all of its capabilities.
Adoption- National (Public sector)
Because of EHR implementation is not federally mandated, public sector hospitals have been slow to adopt EHRs.Although the first EHR implementation in public sector hospitals began in the late 1990s, few hospitals have implemented a system. Most EHR adoption occurs voluntarily in large tertiary level centers.
The ministry of health is turning its attention towards the lack of government policies for HER adoption. Based on the rate at which development in the domain are taking place, it is likely that publicly owned health sector will soon mandate for a quick widespread adoption of IT.
Adoption- National (Private sector)
Unlike the slow rate of EHR adoption in the public sector, privately owned hospitals are implementing them aggressively. They use their system to capture all relevant patient data, unlike public hospitals that tend to use only parts of the systems. Private hospitals maintain the data in a repository so that it can be readily available once a once a universal interoperable EHR initiative is mandated by the government.
EHR implementation at various hospitals in the private sector can be classified as follows:
Small hospitals (Upto 100 beds):
IT applications are virtually non-existent. Although some hospitals are using computers and customized simple IS for administrative work, they are not used for processing clinical information.
Medium hospitals (more than 500 beds):
This hospital has the fastest growing rate of IT adoption, but hospitals are still mainly adopting low cost quasi-HIS for billing, registration, pharmacy and other basic modules.
Tertiary hospitals (more than 500 beds):
Most of these hospitals already have HIS implementation in place. If not efforts are underway.
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Super-specialty hospitals:
Some superspeciality hospitals are demanding specific EMR systems that have the functionality to provide clinical information such as vital signs and clinical images (radiographical and analytical).
India has not yet felt the pressing need nor it has addressed the drivers for the implementation of a uniform, interoperable, national EHR system. The country has not even clearly defined the stakeholders who would benefit from such a system.
1.8. Medico legal aspects of the usage of EHR
If the hospital or healthcare delivery organizations violate standard of care (through inadequate oversight of its staff physicians) by allowing EHR or other technology of its choice to be used in such a way to harm patients, it might become a subject of corporate negligence action. The case of vicarious liability occurs when there is a design or other type of flaw in the technology that causes harm to the patients even though the physicians or other caregivers who uses the technology committed no negligence.
The unauthorized access to patient’s private information results in the privacy violation. User negligence, misdirected information flow or intentional security breach by a third party etc. could be some of the reasons for this information leakage.
Medical liability actions may also arise from acts of commission, which breach the standard of care and result in injury and damages to patients. Physicians could also find themselves in trouble by failing to use diagnostic and treatment modalities suggested by the embedded best practice guidelines in certain types of EMR. Here there could be an act of omission contributing to patient injury.
Preventative measures:
Some of the preventative measures suggested in the course of medical liability are the selection of appropriate healthcare information system, proper training of staff to ensure efficient use of system, documenting all information with justification (whether or not care provided), and preventing any further alteration to this records without proper documentation etc.
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CHAPTER 2
OBJECTIVES OF THE STUDY
23
2. OBJECTIVES
To study the extent of IT penetration in the healthcare industry of India.
To analyze the level of awareness of doctors towards Electronic Medical
Records.
To study the factors affecting the level of awareness of doctors towards the
usage of EMR.
To identify the major benefits the users will seek from an EMR system
To study the perception of doctors towards the usage of Electronic Medical
Records.
To study the various anticipated utilization of EMR and to study their
importance.
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CHAPTER 3
RESEARCH METHODOLOGY
25
3. RESEARCH METHODOLOGY
3.1 Research Design
Type of Research: Exploratory and Descriptive Research
3.2 Sample Design
Sample Unit: The doctors from Aligarh (Uttar Pradesh) region, (which
included doctors of Aligarh medical college and hospital, dental college and
hospital, tibia college and hospital as well as the individual practitioners)
who belong to different areas of practice (allopathic, homeopathy, ayurvedic,
therapist and unani doctors)
Sample Size: 73 doctors from Aligarh gave response, out of 11 responses
were incomplete or erroneous so they were eliminated. Hence the final
sample size was 62.
Sampling Technique: Judgmental Sampling
Sampling Area: Aligarh
3.3 Data Collection
Sources
1. Primary Data: Data was collected through structured questionnaire over
email responses and direct interview.
2. Secondary Data: Available on Internet and journals.
Tools
The data was collected through email responses and personal interview.
3.4 Data Analysis
Statistical analysis
Techniques: Frequencies, Cross-tabs, Factor analysis and Mean
3.5 Limitations of Study
1.Getting response from a large number of doctors under time constraints was difficult. Hence small sample size was one the limitation for this study.
2.Involving doctors from different parts of the country could have given a more meaningful and accurate analysis. But this was not possible due to time constraints. This was another limitation of this study
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CHAPTER 4
LITERATURE REVIEW
27
4. LITERATURE REVIEW
4.1 HIMSS Electronic Health records- A global perspective
This is an abstract from the work done by HIMSS Enterprise System Steering Committee and the Global Enterprise task force. This paper explains the extent of acceptance of Electronic Health Records by different countries of the world. It also analyses the scope of HER in different countries and the legal issues involved with it.
4.2 NBR centre for Health and Ageing (Health Information Technology and Policy Lab)
It is a case study on the extent of IT penetration in the Indian Healthcare Industry. It analyses the framework for information technology in India. This article throws light on the Government funding in the field of HIT and the role of the private sector in giving boost to HIT in India. It also analyses the future opportunities and obstacles in the field of HIT.
4.3 Healthcare informatics
Thursday, September 10, 2009
This article throws light on medico-legal aspects of using Electronic health Records and could be the possible preventive measures.
4.4 Emerging Market Report- Health in India 2008-09, PricewaterhouseCoopers
This article throws light on the opportunities in the healthcare sector in India. It traces
the growth in the healthcare sector over the past few years. It also compares the cost
of some of the major healthcare procedures in India with that of other developed and
developing countries. This article also throws light on the emergence and scope of
medical tourism in India
4.5 India HIT Case Study, Virk Pushwaz, Fellow, Harvard University
This case study throws light on the adoption of IT in the healthcare sector of India and
the government initiatives taken in this field. It also talks about the role of private
players in Indian Healthcare Industry in the promotion of the use of IT.
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CHAPTER 5
DATA ANALYSIS
29
1. ANALYSIS BY FREQUENCY DISTRIBUTION
Table 1.1: Representing the frequency of gender
Gender
Frequency Percent
Valid Percent
Cumulative Percent
Valid Male 42 67.7 67.7 67.7
Female 20 32.3 32.3 100.0
Total 62 100.0 100.0
Fig. 1.1: Representing the frequency of gender
Analysis 1.1: The table shows that there were 42 males and 20 females out of 62 on whom the survey was conducted.
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Table 1.2: Representing the frequency of age
Age
Frequency Percent
Valid Percent
Cumulative Percent
Valid 20-30 years
20 32.3 32.3 32.3
30-40 years
25 40.3 40.3 72.6
40-50 years
9 14.5 14.5 87.1
Above 50 years
8 12.9 12.9 100.0
Total 62 100.0 100.0
Fig. 1.2: Bar diagram representing the frequency of age
Analysis 1.2: The above table and figure shows that there were 20 doctors of the age group 20-30 years, 25 doctors of the age group 30-40 years, 9 doctors of the age group 40-50 years and 8 doctors of the age group 50 and above, out of 62 doctors on whom the survey was done.
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Table 1.3: Representing frequency of area of practice
1. Area of practice:
Frequency Percent
Valid Percent
Cumulative Percent
Valid Allopathic 23 37.1 37.1 37.1
Dental 18 29.0 29.0 66.1
Homeopathy
3 4.8 4.8 71.0
Therapist 9 14.5 14.5 85.5
Others 9 14.5 14.5 100.0
Total 62 100.0 100.0
Fig. 1.3: Bar diagram representing the frequency of area of practice
Analysis 1.3: The above table and figure shows that there were 23 allopathic doctors, 18 dentist, 3 homeopathic doctors, 9 therapist and 9 doctors from others category (unani, ayurveda etc.), out of 62 doctors on whom the survey was conducted.
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Table 1.4: Representing the frequency of qualification
2. Qualification
Frequency Percent
Valid Percent
Cumulative Percent
Valid Medical graduate
40 64.5 64.5 64.5
Specialist 18 29.0 29.0 93.5
Superspecialist
4 6.5 6.5 100.0
Total 62 100.0 100.0
Fig. 1.4: Bar diagram representing the frequency of qualification
Analysis 1.4: The above table and figure shows that there were 40 medical graduates, 18 specialists and 4 superspecialist, out of 62 doctors on whom the survey was done.
33
Table 1.5: Representing the frequency of years of experience
3. Years of experience
Frequency Percent
Valid Percent
Cumulative Percent
Valid 1-5 years 15 24.2 24.2 24.2
5-10 years
17 27.4 27.4 51.6
10-15 years
15 24.2 24.2 75.8
15-20 years
5 8.1 8.1 83.9
>20 years 10 16.1 16.1 100.0
Total 62 100.0 100.0
Fig. 1.5: Bar diagram representing the frequency of experience
Analysis 1.5: The above table and diagram shows that there were 15 doctors with experience of 1-5 years, 17 with experience of 5-10 years, 15 with experience of 10-15 years, 5 with experience of 15-20 years and 10 with experience of above 20 years, out of the 62 doctors on whom the survey was conducted.
34
Table 1.6: Representing the frequency of familiarity/non familiarity with EMR function and benefits.
4. Are you familiar with EMR function and benefits?
Frequency Percent
Valid Percent
Cumulative Percent
Valid Yes 47 75.8 75.8 75.8
No 15 24.2 24.2 100.0
Total 62 100.0 100.0
Fig. 1.6: Bar diagram representing the frequency of familiarity/non familiarity with EMR function and benefits.
Analysis 1.6: The above table and figure shows that 47 doctors said that they are familiar with EMR function and benefits and 15 doctors said that they are unfamiliar with EMR function and benefits, out of 62 doctors on whom the survey was conducted.
35
2. ANALYSIS BY CROSS -TAB
2.1) Gender and Familiarity with EMR
Table 2.1
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Gender * 4. Are you familiar with EMR function and benefits?
62 100.0% 0 .0% 62 100.0%
Gender * 4. Are you familiar with EMR function and benefits? Crosstabulation
4. Are you familiar with EMR function and benefits?
1 2 Total
Gender 1 Count 32 10 42
% within Gender
76.2% 23.8% 100.0%
2 Count 15 5 20
% within Gender
75.0% 25.0% 100.0%
Total Count 47 15 62
% within Gender
75.8% 24.2% 100.0%
Analysis 2.1: The above crosstabulation shows that: -
out of 42 males, 32(76.2%) were familiar and 10(23.8%) were unfamiliar with EMR benefit and functions.
Out of 20 females, 15(75.0%)were familiar and 25(25.0%) were unfamiliar with EMR benefit and functions.
Inference: The familiarity of doctors towards the EMR benefit and functions is independent of gender.
36
2.2) Age and familiarity with EMR
Table 2.2
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Age * 4. Are you familiar with EMR function and benefits?
62 100.0% 0 .0% 62 100.0%
Age * 4. Are you familiar with EMR function and benefits? Crosstabulation
In years 4. Are you familiar with EMR function and benefits?
Yes No Total
Age 20-30 Count 15 5 20
% within Age
75.0% 25.0% 100.0%
30-40 Count 19 6 25
% within Age
76.0% 24.0% 100.0%
40-50 Count 7 2 9
% within Age
77.8% 22.2% 100.0%
Above 50
Count 6 2 8
% within Age
75.0% 25.0% 100.0%
Total Count 47 15 62
% within Age
75.8% 24.2% 100.0%
37
Analysis 2.2: The above crosstabulation shows that:
1. In the 20-30 years age group, 15(75%) were familiar and 5(25.0%) were unfamiliar with EMR function and benefits.
2. In the age group 30-40 years, 19(76%) were familiar and 6(24%) were unfamiliar with EMR function and benefits.
3. In the age group 40-50 years, 7(77.8%) were familiar and 2(22.2%) were unfamiliar with EMR function and benefits
4. In the age group of above 50 years, 6(75%) were familiar and 2(25%) were unfamiliar with EMR function and benefits.
Inference: The above crosstabulation proves that age of doctors does not affect their familiarity level with EMR function and benefits.
38
2.3(i) Area of practice and familiarity with EMR
Table 2.3(i)
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
1. Area of practice: * 4. Are you familiar with EMR function and benefits?
62 100.0% 0 .0% 62 100.0%
1. Area of practice: * 4. Are you familiar with EMR function and benefits? Crosstabulation
Count
4. Are you familiar with EMR function and
benefits?
Yes No Total
1. Area of practice:
Allopathic 22 1 23
Dental 16 2 18
Homeopathy
1 2 3
Therapist 4 5 9
Others 6 3 9
Total 47 15 62
39
Analysis 2.3(i): The above crosstabulation shows that:
Out of 23 allopathic doctors, 22(95.6%) are familiar and 1(4.3%) are unfamiliar with EMR function and benefits.
Out of 18 dental doctors, 16(88.8%) are familiar and 2(11.12%) are unfamiliar with EMR function and benefits.
Out of three homeopathy doctors, 1(33.3%) were familiar and 2(66.6%) were unfamiliar with EMR function and benefits.
Out of 9 therapists, 4(44.4%) were familiar and 5(55.5%) were unfamiliar with EMR function and benefits.
Out of 9 doctors in the others category (unani, ayurvedic doctors), 6(66.6%) were familiar and 3(33.3%) were unfamiliar with EMR function and benefits.
Inference: Area of practice influences the familiarity level of doctors with EMR function and benefits.
40
2.3(ii): For further validating the above inference, the five areas of practice is merged into a dichotomous variable and hypothesis testing is done.
Allopathic and dental doctors= 1
Homeopathy, therapist and others= 2
Table 2.3(ii)
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Area * 4. Are you familiar with EMR function and benefits?
62 100.0% 0 .0% 62 100.0%
Area1 * 4. Are you familiar with EMR function and benefits? Crosstabulation
4. Are you familiar with EMR function and benefits?
1 2 Total
Area1 1 Count 38 3 41
% within Area1
92.7% 7.3% 100.0%
2 Count 9 12 21
% within Area1
42.9% 57.1% 100.0%
Total Count 47 15 62
% within Area1
75.8% 24.2% 100.0%
41
Table 2.3(ii)-A
Chi-Square Tests
Value doAsymp. Sig.
(2-sided)Exact Sig. (2-sided)
Exact Sig. (1-sided)
Pearson Chi-Square 1.880E1 1 .000
Continuity Correctionb 16.180 1 .000
Likelihood Ratio 18.462 1 .000
Fisher's Exact Test .000 .000
Linear-by-Linear Association
18.495 1 .000
N of Valid Cases 62
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.08.
b. Computed only for a 2x2 table
Table 2.3(ii)-B
Symmetric Measures
ValueApprox.
Sig.
Nominal by Nominal
Contingency Coefficient
.482 .000
N of Valid Cases 62
Analysis 2.3(ii):
Ho: There is no significant association between the area of practice and familiarity with EMR
H1: There is significant association between the area of practice and familiarity with EMR
Analysis: Since p value (0.00) < 0.05, hence null hypothesis is rejected.
Alternate hypothesis is accepted. Hence there is association between the area of practice and familiarity.
Contingency coefficient value is 0.482, which shows the association is fairly strong.
Inference: Area of practice influences the familiarity with EMR but the association between the two variables is not very strong.
42
2.4(i) Years of experience and familiarity with EMR
Table 2.4(i)
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
3. Years of experience * 4. Are you familiar with EMR function and benefits?
62 100.0% 0 .0% 62 100.0%
43
3. Years of experience * 4. Are you familiar with EMR function and benefits? Crosstabulation
In years 4. Are you familiar with EMR function and benefits?
Yes No Total
3. Years of experience
1-5 Count 12 3 15
% within 3. Years of experience
80.0% 20.0% 100.0%
5-10 Count 13 4 17
% within 3. Years of experience
76.5% 23.5% 100.0%
10-15 Count 10 5 15
% within 3. Years of experience
66.7% 33.3% 100.0%
15-20 Count 5 0 5
% within 3. Years of experience
100.0% .0% 100.0%
>20 years Count 7 3 10
% within 3. Years of experience
70.0% 30.0% 100.0%
Total Count 47 15 62
% within 3. Years of experience
75.8% 24.2% 100.0%
44
Analysis 2.4 (i): The above crosstabulation shows that:
3. Out of doctors with 1-5 years of experience, 12(80%) are familiar and 3(20%) unfamiliar with EMR.
4. Out of doctors with 5-10 years of experience, 13(76.5%) are familiar and 4(23.5%) were unfamiliar with EMR benefit and function.
5. Out of doctors with 10-15 years of experience, 10(66.7%) are familiar and 5(33.3%) are unfamiliar with EMR function and benefits.
6. Out of doctors with 15-20 years of experience, 5(100%) are familiar and 0(0.0%) are unfamiliar with EMR function and benefits.
7. Out of doctors with >20 years of experience, 7(70.0%) are familiar and 3(30%) are unfamiliar with EMR function and benefits.
Inference: The above crosstabulation shows that years of experience do not influence the familiarity level of doctors towards the function and benefits of EMR.
45
2.4. (ii) For further analysis the five groups in the years of experience has been converted into the dichotomous variableLess than and equal to 10 years= 1More than 10 years= 2
Table 2.4(ii)
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Years * 4. Are you familiar with EMR function and benefits?
62 100.0% 0 .0% 62 100.0%
Years * 4. Are you familiar with EMR function and benefits? Crosstabulation
Count
4. Are you familiar with EMR function and benefits?
1 2 Total
Years 1 25 7 32
2 22 8 30
Total 47 15 62
46
Table 2.4(ii)-A
Chi-Square Tests
Value dfAsymp. Sig.
(2-sided)Exact Sig. (2-sided)
Exact Sig. (1-sided)
Pearson Chi-Square .194a 1 .660
Continuity Correctionb .021 1 .886
Likelihood Ratio .194 1 .660
Fisher's Exact Test .770 .442
Linear-by-Linear Association
.191 1 .662
N of Valid Cases 62
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 7.26.
b. Computed only for a 2x2 table
Analysis 2.4(ii):
Ho: There is no association between the years of experience and familiarity with
EMR function and benefits.
H1: There is association between the years of experience and familiarity with EMR
function and benefits.
Observation: The p value > 0.05, hence the null hypothesis is accepted.
Inference: There is no association between the years of experience of doctors and
familiarity with EMR function and benefits.
47
2.5) Qualification and familiarity with EMR function and benefits.
Table 2.5
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
2. Qualification * 4. Are you familiar with EMR function and benefits?
62 100.0% 0 .0% 62 100.0%
2. Qualification * 4. Are you familiar with EMR function and benefits? Crosstabulation
Count
4. Are you familiar with EMR function and benefits?
Yes No Total
2. Qualification
Medical graduate
29 11 40
Specialist 15 3 18
Superspecialist
3 1 4
Total 47 15 62
Analysis 2.5: The above crosstabulation shows that:
Out of 40 medical graduates, 29(72.5%) are familiar and out 11(27.5%) are
unfamiliar with EMR functions and benefits.
Out of 18 specialists, 15(83.3%) are familiar and 3(16.6%) are unfamiliar with
EMR function and benefits.
Out of 4 superspecialists, 3(75%) are familiar and 1(25%) are unfamiliar with
EMR function and benefits.
Inference: The familiarity of doctors with EMR is more or less similar in all the three
48
categories. Hence it can be inferred that qualification does not influence the
familiarity of doctors with EMR function and benefits.3) FACTOR ANALYSIS:
Table 3.1: Representing KMO and Bartlett’s test
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.550
Bartlett's Test of Sphericity
Approx. Chi-Square 80.532
df 36.000
Sig. .000
Analysis 3.1: KMO is an index used to examine the appropriateness of factor analysis. The value between 0.5 and 1.0 indicates that factor analysis is appropriate. Since KMO value is 0.550(which is greater than 0.50), hence factor analysis is appropriate.
49
Table 3.2: Representing Communalities
Communalities
Initial Extraction
6a. Display of clinical notes and reports.
1.000 .687
6b. Display of lab results.
1.000 .824
6c. Display of radiology images
1.000 .598
6d. Entry and Display of diagnosis and medications
1.000 .683
6e. Display of height, weight and allergies.
1.000 .806
6f. Prescription writing.
1.000 .719
6g. Decision support (Guidelines, expert logic, reminders/alerts)
1.000 .537
6h. Display of structured documentation.
1.000 .832
6i. Display of demographics.
1.000 .774
Extraction Method: Principal Component Analysis.
Analysis 3.2: Communality of each statement refers to the variance being shared or which is common by other statement also. With reference to the first statement, the extraction is 0.687 which indicates that 68.7% of the variance is being shared or common to other statements.
50
Table 3.3: Table showing the total variance explained and the extracted factors.
Total Variance Explained
Component
Initial EigenvaluesExtraction Sums of Squared Loadings
Rotation Sums of Squared Loadings
Total
% of Varianc
eCumulativ
e % Total
% of Varianc
eCumulativ
e % Total
% of Varianc
eCumulativ
e %
1 2.323
25.807 25.8072.32
325.807 25.807
1.828
20.314 20.314
2 1.806
20.071 45.8781.80
620.071 45.878
1.792
19.907 40.222
3 1.309
14.547 60.4251.30
914.547 60.425
1.439
15.991 56.213
4 1.021
11.348 71.7731.02
111.348 71.773
1.400
15.560 71.773
5 .730 8.112 79.885
6 .670 7.449 87.334
7 .488 5.427 92.761
8 .352 3.911 96.672
9 .299 3.328 100.000
Extraction Method: Principal Component Analysis.
Analysis 3.3: About 71.773% of total variance in the 9 variables is attributable to the first four components. Also we can judge how well the ten-component model describes the original variables, by examine the above table and concluded that Component 1 explains a variance of 1.826, which is 20.314 % of total variance of 9, Component 2 explains a variance of 1.792, which is 19.907% of total variance, Component 3 explains a variance of 1.1.439, which is 15.991% of total variance, Component 4 explains a variance of 1.400, which is 15.560% of total variance. The amount if variance by the four components is 6.459, which is 71.773% of the total variance in the 9 components. The rest five components together accounts for 28.227% of the total variance.
51
Table 3.4: Table representing Component Matrix
Component Matrixa
Component
1 2 3 4
6a. Display of clinical notes and reports.
-.612 .345 -.309 .313
6b. Display of lab results.
-.529 .568 .317 .349
6c. Display of radiology images
-.384 .594 -.291 .112
6d. Entry and Display of diagnosis and medications
-.512 -.121 .567 -.293
6e. Display of height, weight and allergies.
.095 .569 -.399 -.559
6f. Prescription writing.
.654 .237 .075 .479
6g. Decision support (Guidelines, expert logic, reminders/alerts)
.673 .070 .067 .273
6h. Display of structured documentation.
.137 .509 .734 -.127
6i. Display of demographics.
.592 .593 .000 -.265
Extraction Method: Principal Component Analysis.
a. 4 components extracted.
52
Table 3.5: Representing rotated component matrix
Rotated Component Matrixa
Component
1 2 3 4
6a. Display of clinical notes and reports.
-.171 .794 -.051 -.159
6b. Display of lab results.
-.062 .745 -.151 .492
6c. Display of radiology images
-.052 .717 .286 -.012
6d. Entry and Display of diagnosis and medications
-.625 -.046 -.233 .486
6e. Display of height, weight and allergies.
-.085 .138 .882 -.045
6f. Prescription writing.
.839 -.038 -.021 .116
6g. Decision support (Guidelines, expert logic, reminders/alerts)
.687 -.246 .022 .059
6h. Display of structured documentation.
.124 -.005 .150 .891
6i. Display of demographics.
.451 -.104 .691 .287
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
53
Analysis 3.5: In table 3.5, factor 1 has high coefficient for variable 6 (Prescription
writing) and variable 7 (Decision support) and a negative coefficient for variable
(entry and display of diagnosis and medication is negatively related). Both
prescription writing and expert guidelines and alerts will help the physicians save
their time, hence Factor 1 can be termed as Time saving factor. Factor 2 has high
coefficient for variable 1 (display of clinical notes and reports), variable 2 display of
lab results and variable 3 (display of radiology images). Factor 2 will help the
physicians in decision making and will help reduce error. Hence factor 2 can be
termed as Decision making Factor. Factor 3 has high coefficient for variable 5
display of height, weight and allergies and variable 9 (display of demographics).
Factor 3 will help in keeping a record of the people of the area so that better
healthcare facilities can be provided to them in short time. This factor is related to the
society hence can be termed as Social factor. Factor 4 has high coefficient for
variable 8(display of structured documentation). This factor will help in
administrative works. Hence can be termed as Administrative Factor.
Further, it is observed that the first three factors are helpful in clinical works. Hence
it can together be termed as clinical factor. And the last factor is helpful in
administrative work. Hence it can be termed as administrative factor.
54
4. ANALYSIS BY MEAN
4.1) Physician attitudes and beliefs
Table 4.1
One-Sample Statistics
N MeanStd.
DeviationStd. Error
Mean
5a.EMR improves quality of care and reduces error
47 2.57 1.037 .151
5b.EMR improves quality of practice.
47 2.17 .892 .130
5c. EMR increases practice productivity.
47 1.83 .481 .070
5d. EMR usage should be mandated.]
47 2.81 1.076 .157
5e. Doctors will devote the time required for the EMR training ]
47 2.23 .598 .087
5f. EMR benefits outweigh the cost.]
47 2.43 .801 .117
55
Variables Mean % agreeing % disagreeing
a) EMR improves
quality of care and
reduces error
2.57 61.7 38.9
b) EMR improves
quality of practice
2.17 76.6 23.4
c) EMR increases
practice productivity
1.83 95.7 4.3
d) EMR usage should
be mandated
2.81 44.7 55.3
e) Doctors will
devote the time
required for the EMR
training
2.23 76.6 23.4
f) EMR benefits
outweigh the cost
2.43 51.1 48.9
Analysis 4.1Table 4.1 summarizes respondents general attitudes and beliefs regarding EMRs, including familiarity with function and benefits, impacts, usage/training and overall value and need for adoption. Both the mean rating for each item and percentages “agreeing” and “disagreeing” are presented. These percentages were calculated by collapsing a five point likert scale from (1) strongly agree to (2) strongly disagree to create a dichotomous variable, “agree” and “disagree”.
A majority (95.7%) of the respondent feels that EMR would increase practice productivity. 76.6% of the doctors feel that EMR will improve the quality of practice and the doctors will devote the time required for the EMR training.61.7% of the respondents feel that EMR will improve quality of care and will reduce error.Almost half of the respondents (51.1%) feel that EMR benefits outweigh the cost.Very less that is only 44.4% of the respondents feels that EMR usage should be
56
mandated.
2) Importance of EMR functions
Table 4.2
One-Sample Statistics
N MeanStd.
DeviationStd. Error
Mean
6a. Display of clinical notes and reports.
47 1.49 .547 .080
6b. Display of lab results.
47 1.89 .667 .097
6c. Display of radiology images
47 1.91 .717 .105
6d. Entry and Display of diagnosis and medications
47 1.40 .614 .090
6e. Display of height, weight and allergies.
47 2.15 .551 .080
6f. Prescription writing.
47 2.02 .794 .116
6g. Decision support (Guidelines, expert logic, reminders/alerts)
47 2.00 .466 .068
6h. Display of structured documentation.
47 1.98 .489 .071
6i. Display of demographics.
46 2.91 .985 .145
57
FUNCTION MEAN SCORE RANK
Entry and display of diagnosis and medication
1.40 1
Display of clinical notes and reports
1.49 2
Display of lab results 1.89 3
Display of radiology images
1.91 4
Display of structured documentation
1.98 5
Decision support (guidelines, expert logic, reminders/alerts)
2.00 6
Prescription writing 2.02 7
Display of height, weight and allergies
2.15 8
Display of demographics 2.91 9
Analysis 4.2
Table 4.2 summarizes the respondent’s perception regarding the importance of specific EMR functions. The respondents were presented a list of nine functions.
Respondents considered all of the nine functions to be atleast slightly important (mean=< 3.0). The mean response for the nine EMR functions ranged from 1.40 (very important to quite important) to 2.91 (important to slightly important)As noted in the above table, the entry and display of diagnosis and medication was of greatest importance to doctors. Display of demographics was rated as the least important function. Display of clinical notes and reports was rated second with a
58
mean of 1.49.Display of structured documentation, inspite of being a very useful function for hospitals and nursing homes, was rated fifth with a mean of 1.98.Decision support, prescription writing and display of height, weight and allergies was sixth, seventh and eighth with the mean of 2.00,2.02 and 2.15 respectively.
CHAPTER 6
FINDINGS AND CONCLUSION
59
FINDINGS:
From the study conducted it has been found that, inspite of being a very early
adaptor in the field of HIT, the total penetration of IT in the Indian healthcare
industry is still very low as compared to other industries.
IT has been observed that out of the total respondents, majority of the
physicians (75.8%) are familiar with EMR function and benefits and only 24.2
% said that they are unfamiliar with EMR function and benefits.
From the above study it has been observed that gender, age, years of experience
and qualification has no association with familiarity of doctors with EMR
function and benefits.
From the above study it has been observed that area of practice has a moderately
good association with familiarity of doctors with EMR. It has been further
observed that allopathic and dental doctors are more familiar with EMR
function and benefits as compared to homeopathic, therapist and other
practitioners.
From the above study it has been found that the majority of physician (95.7%)
agree with the statement that EMR will increase practice productivity, but on
the other hand the majority (55.3%) disagree with the statement that EMR
usage should be mandated.
From the above study it has been found that the clinical functions of EMR
(Entry and display of diagnosis and medication, display of clinical notes and
reports display of lab results and display of radiology images) were given
higher rating (ranked 1st, 2nd, 3rd and 4th respectively) by the physician in terms
of their importance. Whereas on the other hand display of structured
documentation and display of demographics were given comparatively lower
rating (ranked 5th and 9th respectively). The lower rating of prescription writing
60
is somewhat surprising, but it can be explained by the familiarity of physician
with and use of paper based writing of prescription. So they feel at ease with
this method and are reluctant in using the new method. Physicians also use
several abbreviations while writing a prescription and this consumes less time,
on the other hand they will not be able to use them while writing a prescription
with the help of a computer.
From the factor analysis it has been found that customer will seek four major
kinds of benefits from EMR: Time saving, Decision making benefits, Social
benefits and administrative benefits.
CONCLUSION
From the secondary research it can be concluded the extent of IT penetration in the
healthcare industry of India is very low because of lack of government initiatives.
There are also many medico-legal complications involved with the use of EMR, so
the government should take initiatives in framing a standard set of rules to avoid these
issues.
From the primary research it can be concluded that the awareness of EMR among
allopathic doctors and dentist is more as compared to other practitioners. It has also
been found that consumer will seek four major kinds of benefits from an EMR, which
are time saving benefit, decision-making benefit, social benefit and administrative
benefits. The first three can be clubbed together into clinical benefits and the last one
as administrative benefits Clinical benefits were rated higher in term of importance.
So the kind and need of the end user should be kept in mind while designing the EMR
system.
It has been found that the clinical functions of EMRs were ranked higher by
physicians as compared to administrative functions in terms of importance and
majority of physicians are ready to welcome the EMR system in India, but they feel
that its use should not be mandated.
61
CHAPTER 7
RECOMMENDATIONS
62
7. RECOMMENDATIONS:
Instead of mandating the use of EMR, the physician perception about EMR should be understood first. This will allow for the development of targeted education to demonstrate the advantage of EMRs and to further improve their perception. This will lead to widespread adoption and successful implementation of EMRs.
Instead of designing a standard system for all, the need of the end users should be identified and the EMRs should be customized as per their needs and requirements.
63
BIBLIOGRAPHY
64
BIBLIOGRAPHY
Emerging market report 2008, Healthcare in India, PriceWaterhouseCooper
Framework for Information Technology for Health in India, Department of IT, Ministry of communication and IT, May 2003.
Healthcare in India, Emerging market report 2007, pp. 1-26
HIMSS, August 2008, EHR- A Global Perspective, pp. 70-77
India HIT Case Study, NBR Centre for Health and Ageing, Pushwaz Virk, Sharib Khan, Vikram Kumar, pp.1-4
Malhotra Naresh K. “Marketing Research” Pearson Education 5th edition, pp.
454-635
The Telegraph, Opportunities in Indian Healthcare Industry, July 7, 2010