Showing posts with label statistical data mining. Show all posts
Showing posts with label statistical data mining. Show all posts

Wednesday, March 2, 2011

Real-Time Biosurveillance Pilot - Technical Report

The Real-Time Biosurveillance Program (RTBP) was a multi-partner initiative to study the potential for new Information and Communication Technologies (ICTs) to improve early detection and notification of disease outbreaks in selected regions of Sri Lanka and India. Experts in the field of biosurveillance and health informatics have argued that improvements in disease detection and notification can be achieved by introducing more efficient means of gathering, analyzing, and reporting on data from multiple locations. New ICTs are regarded as an important means to achieve these efficiency gains. The primary research objective of RTBP was to examine these claims more closely by producing evidence to indicate in what ways and to what extent the introduction of new ICTs might achieve efficiency gains when integrated with existing disease surveillance and detection systems.

The project achieved a number of key objectives at the outset, including the development of a Java-based application for collecting patient data using low cost mobile phones; the successful implementation of Auton Lab’s analytic software and T-Cube Web Interface for analyzing patient records and near real-time prediction of disease outbreaks; and the adoption and implementation of Common Alerting Protocol for multi-channel health alerting. Moreover, the project team successfully integrated each of these three key components into an operational system that collected individual patient records, over 330,000 in Sri Lanka and over 130,000 in India, over a 15 month course of study. Over the life of the project, the system identified over a dozen instances of potential disease outbreaks, with four of those (Chicken Pox, Acute Diarrheal Disease, Respiratory Tract Infection, and Mumps) being confirmed by health authorities. The project demonstrated that new ICTs can dramatically reduce turnaround time for outbreak detection and alerting, from current period of weeks to a matter of days or even hours. The project also demonstrated the feasibility of using low cost mobile phones and existing commercial cellular infrastructure and services to enable affordable, real-time reporting of patient records from frontline health centers.

Overall results from our work demonstrate the feasibility of introducing an RTBP from a technical and operational standpoint. Initial findings show significant efficiency gains in terms of disease reporting, outbreak detection, and health alerting; with cost savings over 35% in both countries when compared to the existing systems. However, further research is needed to better understand the challenges associated with scaling such a system up to a regional or national level of implementation. In particular, further work needs to be done to optimize data entry over low cost mobile devices, to address usability and training requirements for the analytics platform, and to continue to enhance and integrate health alerting into national and regional systems and practices. Moreover, extensive stakeholder consultation will be necessary to ensure the various policy, legal, and operational implications of a national or regional RTBP are better understood, addressed, and effectively managed in the future.

It was a tiring and exciting experience but helped towards change adaptation whereby health professionals in the respective pilot countries were exposed to new ways of public health maintenance. I am delighted to have developed the proposal, gotten funding, and directed the project in achieving in terms of important empirical findings on the usefulness of this type of system, as well as achieving impressive outcomes around the greater adoption of the RTBP.

This project was made possible through a grant from the International Development Research Center of Canada. This project recently ended in December of 2010. This blog is to share the final technical report with researchers and practitioners.

Click to view the Real-Time Biosurveillance Program Final Technical Report.

Wednesday, July 2, 2008

Healthcare Worker based mobile Sensor Systems

The aim of the real time biosurveillance program is to mobilize Healthcare Workers in the rural settings with mobile phones to record and submit patient counts for the purpose of consolidating national health data for surveillance of unusual patterns (headsup). Problem that this real-time biosurveillance program (RTBP) promises to solve is to strengthen existing disease surveillance and detection communication systems, reduce latencies in detecting and communicating disease information, and set a stand interoperable protocol for sharing disease information with national and international health-related organizations in the region.

My role in the RTBP is working in the capacity of a Researcher and Project Director. The grant has been approved by IDRC but the administrative work remains to be completed before funds can be transfered and work can begin

RTBP shares many similarities with the small study working in (somewhat) rural Tanzania focus on guiding health care workers through medical algorithms, with the primary goal of improving care and the secondary goal of collecting data. In particular, it is automated with the IMCI protocols for classifying and treating childhood illness. If you are interested, an online paper titled "e-IMCI: Improving Pediatric Health Care in Low-Income Countries" describes the project and lessons learned.

The design of RTBP using mobile phones is in par with this abstract from the IEEE Internet Computing article titled - The Rise of People-Centric Sensing - "Technological advances in sensing, computation, storage, and communications will turn the near-ubiquitous mobile phone into a global mobile sensing device. People-centric sensing will help drive this trend by enabling a different way to sense, learn, visualize, and share information about ourselves, friends, communities, the way we live, and the world we live in. It juxtaposes the traditional view of mesh sensor networks with one in which people, carrying mobile devices, enable opportunistic sensing coverage. In the MetroSense Project's vision of people-centric sensing, users are the key architectural system component, enabling a host of new application areas such as personal, public, and social sensing."

Thursday, June 12, 2008

QR Codes for Health Information Exchange

Yesterday night's skype meeting with Gordon Gow brought forth the idea of using QR codes to code and decode health information in relation to the next research in many aspects, a research him and I plan to start shortly; i.e. the RTBP. Refer to his blog for a note on QR Codes and application for mobile phones for emergency managers - Barcodes meet cellphones: intriguing possibilities.

The Real-Time Biosurveillance Program (RTBP) is a research that envisions pilot testing mobile phones for collecting health-related information and applying AutonLab's suite of statistical data mining algorithms for fetching anomalies in the health datasets. The Healthcare-Workers will be provided with mobile phones and a Java application, a rendition of openROSA suit of applications. Indian Institute of Technology - Madras will be developing the mobile applications.

The health information will be mostly patient counts with similar symptoms. We discussed the possibility of using QR codes during transport and storage of information:

1) the Healthcare-Worker recorded data on the mobile handhelds can be encoded as a QR Code prior to transmitting the information to central repository (database). Since the QR Codes use the Reed-Solomon error correction method the misinterpretation of health information during transport and storage is further reduced


2) Given, that a QR codes are already encoded in binary form, the possibility of increasing the speed of the statistical data mining algorithms are worth testing


3) encoding communicable diseases and other known diseases with symptoms in QR Code form printed as hard copy for Healthcare Workers to use for entering information by simply scanning the QR code with the mobile phone camera instead of typing the lengthy string with the possibility of misspelling


4) In the event the Java application residing on the handheld fails the Healthcare Workers can use the hard copy QR code version to scan predefined health information strings to record the information on the handheld, then use Email, MMS or SMS to transit the information over any technology that allows the standard Email, SMS, MMS applications, making it easier for the database to also decipher and parse the information before storing in the relevant attributes (fields)


5) The Healthcare Workers can store the patient information in QR Code form as a hardcopy as a backup. Since it is in a human unreadable form the possibility of an unauthorized random individual reading the confidential patient information is null


These are thoughts that came up during our discussion and look forward to testing the concepts with the RTBP.