Data science and social good: Stronger communities, better healthcare

community-healthcare-outcomes

This is the first part of a two-part series that explores connections between advanced analytics and corporate responsibility.

If businesses can use analytics to calculate millions of credit scores, predict churn rates and accurately project sales growth, then shouldn’t data science also have the potential to help us address societal challenges with facts and insights? Across today’s complex civic landscape, connections between data science and stronger communities, more effective public policy and better healthcare outcomes continue to emerge. Here are three examples of how transforming raw information into actionable knowledge can actually change lives:

1. Saving distressed neighborhoods with data

According to the nonprofit Urban Institute, data science is increasingly guiding how governments address challenges faced by distressed neighborhoods after recession. While governments have historically found it difficult to gather and interpret community information, today’s policymakers and social scientists can harness analytics tools to better understand key statistics such as property tax delinquency rates as they seek to identify localities in need of intervention.

Automated administrative systems that collect and report data efficiently, along with improvements in geographic information systems and digital recordkeeping, have made a major difference in enabling policymakers to take action based on objective indicators.

Analytics can reveal everything from patterns of violence within a city to rates of diabetes incidence in specific neighborhoods. Newer technology tools, from so-called “3-1-1” systems to citizen engagement portals, continue to drive down the costs of data collection while other solutions make it possible to process ever-greater amounts of information. The result is that legislators, government workers and community organizations are better able to wield data as a tool in the effort to improve the lives of low-income and disadvantaged citizens affected by global economic turmoil.

2. Quantifying what works in social change

The Impact Genome Project applies data analysis to influence social outcomes even more broadly by equipping governments and researchers with the information they need to better address all kinds of civic challenges and opportunities. Through this project, analysts crunch numbers from a massive array of community programs to demystify the core attributes, or “genomes,” that make some efforts at intervention and improvement more effective than others.

By identifying which programs have worked best, and why, the Impact Genome Project works to save government and its allies vast amounts of time and energy as they seek to pinpoint the right approach to alleviating poverty and other ills. Program designers can quickly and precisely search the project’s analyses to find best practices, academic researchers can identify gaps in knowledge about key problems and nonprofits can standardize reporting to stakeholders.

If someone wants to know what type of social program has the greatest likelihood of making a difference, the Impact Genome Project, with its large and continually expanding data archive, is a logical resource to investigate. More than 75,000 data points and 125 types of social outcomes are now available for exploration.

3. Improving community health with artificial intelligence

Experts suggest that data science in combination with artificial intelligence holds exceptional promise as a tool for transforming patient outcomes and public health. For example, according to some estimates, more than 30 percent of antibiotics are currently over-prescribed in outpatient scenarios. Using data analytics and advanced algorithms, DXC is collaborating with Singapore General Hospital (SGH) to harness artificial intelligence in ways that  help doctors more accurately prescribe these powerful, life-saving drugs. The project recently received an award from the Singapore Ministry of Health.

In another instance, as the UK National Health Service (NHS) seeks to control costs and reduce wait times, thought leaders believe that advanced analytics can drive valuable efficiency gains without harming quality of care. Using machine learning, caregivers may soon be able to harness data from fitness trackers, electronic health records and even implanted devices to identify patients at risk of health crises. In another instance, University of Tokyo researchers used a sophisticated algorithm to detect rare gene mutations and correctly diagnose an unusual form of leukemia in an elderly cancer patient.

And the U.S. Centers for Disease Control has deployed enhanced data collection, analysis and visualization techniques to strengthen its mission of public health surveillance. Through next-generation data initiatives, the agency has realized a 40-percent improvement in its reporting on causes of death, enhanced a nationwide system for reducing healthcare-associated infections and made environmental hazard data more widely available to the public.

New possibilities

Where will creative, technologically advanced projects like these ultimately take governments, caregivers, researchers and others working to strengthen communities and improve individuals’ health? The more data science evolves and gains new possibilities from advances in artificial intelligence, the fewer limits there will likely be on its power to deliver social goods that benefit everyone.

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