Crowdsourcing may prove vital to track health statistics
A recent study aimed at measuring and recording causes of death worldwide, revealed astonishing information that seems to suggest that statistics pertaining to causes of death in most underdeveloped countries seem to be skewed. The study conducted by a group of Canadian researchers and published in Lancet determined that while World Health Organization (WHO) estimated the annual rate of malaria related deaths in India at 15,000, the correct figures seem to be 13 times higher. The study concluded that over 2,00,000 people die of malaria every year in India. They posted their confidence interval levels between 125,000 and 277,000.
The reasons for the skewed figures stem from the fact that 90% of these deaths occurred in rural areas, with 86% of them outside hospitals, but WHO statistics are generally based on medical data collected from the national hospital reporting systems. Moreover, autopsies are not a common phenomenon for deaths in many countries.
The wide margin of error in WHO data raises several other alarming issues. Statistics for other major illnesses are also likely to be skewed which means the funds allocated to tackle the issue will also prove to be insufficient. More alarming is the fact that ratios for HIV/AIDS is also likely to be much higher than what was initially estimated, making any effort in tackling the spread of this disease inefficient.
In the digital era, is it possible to harness medical data via cell phones and Internet? Already innovative organizations like InSTEDD is working on technology aimed at getting ordinary citizens with smart phones to provide crucial information on health issues, prompting researchers to wonder if similar mechanisms could be developed to record mortality causes.
The Lancet report included meticulous research and study of medical records by trained experts. Similarly researchers could analyze data sent by citizens over their cell phones and get a more accurate determination of death statistics.
While some hope crowdsourcing, vital health related matters, and causes of death may prove helpful to combat the lack of sufficient credible information, others believe crowdsourced data may be unreliable. Moreover, there is a probability of an overload of data, making it difficult for medical analysts to sift through for meaningful information.
