EHR based Data Grid Architecture for Indian Rural HealthCare

Transcription

1 Abstract: Accessibility either to hospitals or medicines would remain a distant dream for about 70% of India's population, particularly in rural areas until at least 2040, according to a report by the ASSOCHAM (The Associated Chambers of Commerce and Industry of India) council on Healthcare and Hospitals. The report points out that India has an average 0.6 doctors per 1000 population against the global average of 1.23, which suggests an evident manpower gap. The Twelfth five year plan started in April 2012 will see the country through the 2015 deadline for achieving the Millennium Development Goals (MDG). But due to poor Indian rural healthcare delivery system the deadline for reducing MMR (Maternal Mortality Rate per 100,000 live births) and IMR(Infant Mortality Rate)will not be met as per the UNDP report 2012 on progress of MDG. In this paper we have given a design of EHR (Electronic Health Record) standardization and Integration of EHRs in the form of Data Grid Architecture to meet the MDG by Keywords: SWAN, Grid environments, Data Grid, Health Grid, EHR, MDG, IMR, MMR, Distributed data mining. 1. INTRODUCTION EHR based Data Grid Architecture for Indian Rural HealthCare P.Vishvapathi 1, Dr.S.Ramachandram 2 and Dr.A.Govardhan 3 In India we have the Right to Education and Right to Information but we do not have the RIGHT TO HEALTHCARE. The national Millennium Development Goals (MDG) Report [1][2] released in 2011 reveals that India is on track of achieving targets on poverty reduction, education, and HIV at aggregate levels. But much work remains to be done in reducing hunger, improving maternal mortality rates and enabling greater access to water and sanitation targets as well as reducing social and geographic inequalities in achieving these targets. Further, rising gender inequality continues to hamper progress on development goals. Women continue to be excluded in social, economic and political domains. Home to 1.21 billion people, India s lack of progress affects the global achievement of the MDGs. The fourth Millennium Development Goal aims to reduce mortality among children under five by two-thirds. India s Under Five Mortality (U5MR) declined from 125 per 1,000 live births in 1990 to 74.6 per 1,000 live births in U5MR is expected to further decline to 70 per 1,000 live births by This means India would still fall short of the target of 42 per 1,000 live births by 2015[2]. In view of these statistics, child survival in India needs sharper focus. This includes better managing neonatal 1 CMR Engineering College, Hyderabad, India, 2 College of Engineering, Osmania University,Hyderabad,India 3 JNT University,Hyderabad,India and childhood illnesses and improving child survival, particularly among vulnerable communities. Survival risk remains a key challenge for the disadvantaged who have little access to reproductive and child health services. Major states in the heartland of India are likely to fall significantly short of these targets, by more than 20 points. Key to significant progress in reducing U5MR and infant mortality rates rests with reducing neonatal deaths, that is, infant deaths that occur within a year of birth at a fast pace [2]. From a Maternal Mortality Rate (MMR) of 437 per 100,000 live births in , India is required to reduce MMR to 109 per 100,000 live births by Between 1990 and 2006, there has been some improvement in the Maternal Mortality Rate (MMR) which has declined to 254 per 100,000 live births as compared to 327 in 1990.However, despite this progress, India is expected to fall short of the 2015 target by 26 points. Safe motherhood depends on the delivery by trained personnel, particularly through institutional facilities. However, delivery in institutional facilities has risen slowly from 26 percent in to 47 percent in Consequently, deliveries by skilled personnel have increased at the same pace, from 33 percent to 52 percent in the same period. By 2015, it is expected that India will be able to ensure only 62 percent of births in institutional facilities with trained personnel [3]. This paper proposes standardization of Electronic Health Record (EHR) design and how the integration of EHR into a Data Grid can be formulated. The stored patient EHR (Electronic Health Record) can be shared by the participating hospitals over the grid framework thereby facilitating examination performed in one location with diagnosis and better treatment plan by the specialists at the other location.the rest of paper is organized as follows: Section II presents Indian Rural Healthcare delivery system and its deficiencies. Section III Design of Electronic Health Record System. Section IV presents the EHR based Data Grid Architecture and Section V concludes the paper. 2.INDIAN RURAL HEALTHCARE DELIVERY SYSTEM AND THE DEFICIENCIES Ministry of Health & family Welfare is instrumental and responsible for implementation of various programmes on a national scale in areas of Health & Volume 2, Issue 3 May June 2013 Page 267

2 Family Welfare, prevention and control of major communicable diseases. Public Health, Hospitals, sanitation fall in the state list. Family welfare and population control, medical educations are included in the concurrent list. Rural Health Services: The Health & Family Welfare programme in the country is being implemented through PRIMARY HEALTH CARE SYSTEM as shown in Figure 1.In rural areas primary health care services are provided through a network of 14,5894 sub-centers,23391 Primary Health centers and 4510 Community Health centers as on march 2009 as per Annual Report of Ministry of Health & family Welfare,GOI[4]. Department of Health & Family Welfare Special/Genera l/district/talu k Hospital Directorate of Health Services (DHS) DMO CHC Block PHC Table 1: The population norms for /PHC/CHC PHC PHC Figure 1 HealthCare Delivery System Sub-Center (): It is the first peripheral contact point between PHC system and the community. It is manned by one female(anm) and one male Health worker and LHV for 6 such. are assigned the tasks related to maternal and child health, family welfare, nutrition, immunization, diarrhea control and control of communicable diseases. Primary Health Center (PHC): It is the first contact point between village community and the medical officer. It is manned by medical officer and 14 other staff. It acts as a referral unit for 6 and has 4-6 beds for patients. It performs CURATIVE, PREVENTIVE, PROMOTIVE and FAMILY WELFARE SERVICES. DMO = District Medical Officer, CHC = Community Health Center, PHC = Primary Health Center, = Sub- Center Supply and Demand of Health services in India: As per the RHS march2010 report[5] the number of s are 1,47,089,PHCs are 23,673, and CHCs are 4535.At level the HW(F)/ANM shortfall of 8.8% of total requirement due to major shortfall in the states of Bihar,Chattisgarh,Gujarat,HP,J&K,Kerala,Orissa, Tripura and UP.A total of 10.3% of total requirement shortfall in Doctors at PHCs in the states of Assam,Bihar,Mp,Orissa,Uttarkhand and UP added to this a 20.7% Doctors posts are vacant as shown in Figure 2. Block PHC/CHC: It is manned by 4 medical specialists i.e. surgeon, physician, gynecologist and pediatrician supported by 21 paramedical and other staff. 30 indoor beds, one OT,X-Ray and Labour room and lab facilities and serves as a referral centre for 4PHCs.Taluk Hospital may provide the entire basic specialty services expected at the first referral level. District Hospital provides all types of tertiary level services. Expected to provide super specialty services like Cardiology, Neurology, Plastic Surgery, Urology and Paediatric surgery and orthodontic. General Hospital provides super specialty services in addition to that of the services of a district Hospital. Specialty Hospitals like Women and Child Hospital, District TB center, Leprosy, Mental Hospital etc. Figure 2 Doctors Shortage at PHC At CHC level shortfall of 62.8% of Surgoens,55.2% of Obstetricians&Gynaecology,72% of Physicians and 69.5% of Paediatricians resulting in overall 62.6% of shortfall with 42.3% vacancy a shown below. As per the SRS bulletin dated Jan 2011 of Registrar General of India, Ministry of Home Affairs,GOI the IMR total is 50(Rural IMR=55,Urban IMR=34) due to high IMR in the states of Assam, Chattishgarh, Haryana, MP,Rajasthan,Meghalaya and UP. Volume 2, Issue 3 May June 2013 Page 268

3 From the above statistics we can depict the picture of Healthcare services demand vs. HealthCare supply in India as follows [5]. Figure 3 Supply and Demand of Health services in India 3. ELECTRONIC HEALTH RECORD SYSTEM In India healthcare information systems have been driven mainly by the need to report aggregate statistics to the government and the funding agencies but not for providing effective healthcare to the citizens. As per the WHO EHR manual for developing countries 2006[6] defines EHR: The Electronic Health Record includes all information contained in a traditional health record including a patient s health profile, behavioral and environmental information. As well as the content of the EHR also includes the dimension of time, which allows for the inclusion of information multiple episodes and providers, which will evolve into a lifetime record (Mon 2004, Amatayakul 2004) The World Health Organization s declaration of Health for All by the year 2000 highlighted the need for better Healthcare services not only at the hospital (Secondary) level but also at the Primary Healthcare and Community Health Services. This has required a change of focus in Healthcare in many areas to ensure, if possible, that the implementation of Electronic Health Record covers Healthcare Delivery Services across a broad spectrum of Healthcare. As per the recommendations on Electronic Medical Records Standards in India 2013 by Ministry of Health & Family Welfare, Government of India[7]:Healthcare systems are highly complex, fragmented and use multiple information technology systems. With vendors incorporating different standards for similar or same systems, it is little wonder that all-round inefficiency, waste and errors in healthcare information and delivery management are all too commonplace an occurrence. Consequently, a patient s medical information often gets trapped in silos of legacy systems, unable to be shared with members of the healthcare community. These are some of the several motivations driving an effort to encourage standardization, integration and electronic information exchange amongst the various healthcare providers. In order to be meaningful, the health record of an individual needs to be from conception (better) or birth (at the very least). As one progresses through one s life, every record of every clinical encounter represents an event in one s life. Each of these records may be insignificant or significant depending on the current problems that the person suffers from. Thus, it becomes imperative that these records be arranged chronologically to provide a summary of the various clinical events in the lifetime of a person. Electronic health records are a summary of the various electronic medical records that get generated during any clinical encounter. Without standards, a lifelong summary is not possible as different records from different sources spread across ~80+ years will potentially need to be brought into one summary. To achieve this, a set of pre-defined standards for information exchange that includes images, clinical codes and a minimum data set is imperative [7]. Electronic health records [7] can improve care by enabling functions that paper medical records cannot deliver: EHRs can make a patient s health information available when and where it is needed too often care has to wait because the chart is in one place and needed in another. EHRs enable clinicians secure access to information needed to support high quality and efficient care. EHRs can bring a patient s total health information together to support better health care decisions, and more coordinated care. EHRs can support better follow-up information for patients for example, after a clinical visit or hospital stay, instructions and information for the patient can be effortlessly provided and reminders for other follow-up care can be sent easily or even automatically to the patient. EHRs can improve patient and provider convenience patients can have their prescriptions ordered and ready even before they leave the provider s office, and insurance claims can be filed immediately from the provider s office. The design of database tables and their relationships, data model, is the core of the EHR/EMR model. The following Figure 4 and Figure 5 shows proposed possible data set that may be included in any of the several files located in a typical health record. They include [8] Patient Master Index, Hospitalisation History, Medical History, Medication Treatment, Medication Details, Pregnancy History, Pregnancy Outcome, PNC Details, Infant Details, Child Immunisation, Surgical History Allergy History, Disease Information Lookup, and Drug Prescription. Volume 2, Issue 3 May June 2013 Page 269

4 Figure 4 Electronic Health Record Database Schema Figure 5. Electronic Health Record Database Schema with Mother and Child tables The resources in the health grid are the databseses,computing power, medical expertise and medical devices as per Health grid associations [10]. The basis for the proposed architecture is as follows: IT connectivity backbone in the Indian states : SWAN : The network would have a minimum bandwidth 2 Mbps connectivity between the state head quarters and the district head quarters, the network would provide high uptime (>99%), redundancy, backup etc. The SWAN deployment takes place both vertically and horizontally. The main backbone of SWAN connects the State Head quarters PoP(Point of Presence) with the PoPs at district head quarters which in turn are connected to the respective PoPs at sub district/ Manual level headquarters. Moreover the various state offices are also connected horizontally with the closest respective PoPs. State Wide Area (SWAN) has been implemented in 30 states. Andhra Pradesh State Wide Area Network Architecture [11]: Entire APSWAN is logically divided into two network segments. 1. Vertical segment 2. Horizontal segment. The Vertical segment of APSWAN is composed of a total of 1112 PoPs(Point of Presence) spread across the State. These PoPs are classified as: a. 1 SHQ PoP (State Head Qtr) b. 23 DHQ PoPs (District Head Qtr) c MHQ PoPs (Mandal Head Qtr). Under the Vertical segment of the APSWAN:1. SHQ PoP shall be linked with all the DHQ PoPs using Point to Point (PTP) 8 Mbps Leased circuits from Bandwidth Service provider.2. Each DHQ PoP shall be linked with all the respective MHQ PoPs over Point to Point (PTP) 2 Mbps Leased circuits from the Bandwidth Service Provider. The Horizontal segment of APSWAN [11] is composed of horizontal offices spread across the State. All vertical PoPs of APSWAN will have various Horizontal connectivity facilities.shq 75 offices, DHQ 25 offices at each DHQ, MHQ 5 offices at each MHQ, Wi-Max Radio connectivity min.9 Nodes. Types of Connectivity for Horizontal Offices: Type I: CAT 6 Ethernet, Type II: Optical Fiber - Type III: Leased line, Type IV: WiMax. 4. EHR BASED DATA GRID ARCHITECTURE Grid Technologies support the sharing and co-ordinated use of diverse resources in dynamic Virtual Organisations -that is, the creation, from geographically and organizationally distributed components, of virtual computing systems that are sufficiently integrated to deliver desired QOS [9],as per Ian Foster and Carl Kesselman. Data Grid is a technological paradigm for the seamless access to through virtual middleware the heterogeneous and distributed data storages. Health grids are grid infrastructures comprising applications, services or middleware components that deal with the medical data. Figure 4 APSWAN Detailed Network Architecture Volume 2, Issue 3 May June 2013 Page 270

5 The Proposed Architecture: The social demographic data has been collected under the AADHAAR and each and every individual is given an AADHAAR number UID, similarly we need to collect the personal healthcare data of all the citizens and make it into Health database of EHR data grid and give them UHID(Unique Health ID) and this data will help in giving preventive care prescription by a specialist at the other end to rural doctor. The standardized EHR system to be implemented in all the PHC/CHC/District Hospitals of the rural healthcare delivery system.the EHR data of all the villages falling under a particular Mandal to be integrated at that level so that we have the Mandal EHR Data. All the Mandal EHR data to be integrated into the District EHR Data of that district.all the District EHR data to be integrated into State EHR Data.We can formulate a Data grid of these EHR as shown in the Figure 5 below facilitating examination of Electronic Health Record of a patient at the village level PHC by the specialist doctors at the mandal,district and state hospitals and give the prescription for better healthcare. Figure 5 EHR based DATA GRID Architecture for Andhra Pradesh state, india 5. CONCLUSIONS AND FUTURE WORK In this paper we have shown how to standardize the Electronic Health Records to be used in the Indian Rural Healthcare delivery system and how these in turn can be integrated in the form of a Data Grid on the existing IT SWAN, State Wide Area Network, infrastructure, thereby facilitating provision of specialist services to the rural population. We are working out to simulate this framework and also how a Distributed Data Mining algorithm could be used for predictive analysis of Health data so as to give a treatment plan for most of the preventive diseases of Mother and Child in turn helping us to reach the MDGs by REFERENCES [1] Millennium Development Goals mdgs.un.org. [2] MDG-India country report-2011 [3] [4] Annual Report ,Ministry of Health and Family Welfare,GOI, mohfw.nic.in [5] RHS Bulletin-March 2010 [6] WHO EHR Manual for developing countries [7] Recommendations On Electronic Medical Records Standards In India 2013, Ministry of Health & Family Welfare, Government of India [8] Operational Plan for Mother and Child Tracking System, Ministry of Health and Family Welfare,GOI [9] Foster I, Kesselman C. The GRID 2. SFO, CA, Morgan Kaufman [10] Health Grid White Paper of Healthgrid.org [11] APSWAN RFP AP_SWAN_RFP,APTS, Hyderabad [12] ASSOCHAM Report 2012 on HealthCare and Hospitals. AUTHORS.P.Vishvapathi received his B.E degree in Electronics and Communications Engineering from Osmania University in the year 1988 and M.Tech degree in Computer Science from University of Hyderabad in the year 1990.He is presently working as the Computer Science faculty in the CMR Engineering College,Hyderabad,india. Dr.S.Ramachandram received his B.E degree in Electronics and Communications Engineering from Osmania University in the year 1983 and M.Tech (CSE), 1985, Osmania University, Hyderabad. Ph.D (Processing of Read-Only Transactions in Mobile Broadcast Environment), June 2005, Osmania University, Hyderabad.He is presently working as the professor in the department of CSE,University college of Engineering,Osmania University,Hyderabad. Dr.A.Govardhan did his Intermediate from APRJC Nagarjuna Sagar, during , B.E in Computer Science and Engineering from Osmania University College of Engineering, Hyderabad in 1992, M.Tech from Jawaharlal Nehru University(JNU), Delhi in 1994 and he earned his Ph.D from Jawaharlal Nehru Technological University,Hyderabad in 2003.Presently he is working as the professor in CSE in JNT University,Hyderabad Volume 2, Issue 3 May June 2013 Page 271