March/April 2014 Issue

Big Data’s Impact on Social Services
By Lindsey Getz
Social Work Today
Vol. 14 No. 2 P. 28

The amount of data being produced and used on a daily basis has exploded, and that increasing volume has required new solutions for processing and managing it. Nicknamed “Big Data,” the generation of all this information and how to analyze it have implications that affect the social work profession.

The best way to define Big Data is “the ever-growing amount and complexity of information that all of us create and consume every day,” says Charlie Schick, PhD, director of Big Data solutions for health care and life sciences at IBM. “In fact, each day we create 2.5 quintillion bytes of data generated by a variety of sources, from purchase transaction records to health care medical images and from scientific research findings to social media messages.”

As a result, the way in which data are stored and accessed is changing, says Andrew Wong, president of AJW Inc., a public policy and business development consulting firm that focuses on enhancing opportunities and removing barriers for innovative technologies. That change, in turn, is altering how we think about data capture, input, and access.

“Search engines and now social media [Twitter in particular] have created the new paradigm of small bits of data being collected on a large scale,” Wong says. “This, too, has changed how we think of collecting and managing data. As a result, our culture is changing so that we think of exchanging data in small bits. The current culture is to consume large quantities of these small data pieces in short periods of time. All of this has created huge challenges as well as exciting opportunities for data management. For business to succeed, we need to be able to process larger and larger quantities of data, captured in small and increasingly diverse ways.”

Social Services Applications
This already is happening in many ways. One is using collected data for targeted marketing. When shopping for a specific item online, it’s now common to get suggestions for other items that might interest you. Those suggestions aren’t randomly generated. In fact, they’re based on processing huge amounts of data about purchasing practices, Wong says, including when you bought a particular item, where you live, and your economic status. “This is driving products to you before you even think about what you need,” he says. “So the thought is, can this be done for public services as well? Can we drive services to the client rather than wait for them to come to us?”

Mike Meikle, CEO of the Hawkthorne Group and an IT consultant with experience in the social services sector, says health care already is trying to hop on the Big Data bandwagon in the hopes of delivering better outcomes. “By aggregating all of the information and looking at it across patient populations, there is the possibility of achieving better outcomes,” he says. “This ties into the social services sector. For example, in order to request funding, they may need to start looking at the data collected from at-risk populations. Supplying that data allows a look at the bigger picture.”

However, the challenge is not only in how that information is collected but how it’s processed. These are the areas where the overloaded but underfunded social services agency likely will fall behind. Keeping up with data analytics is a huge endeavor, but it can have positive outcomes for the health care and social services world.

“From a health care and social services perspective, it can be difficult for payers, providers, and other health care stakeholders to keep up with the avalanche and complexity of medical information in order to glean actionable insights that improve patient care,” Schick says. “From medical literature to clinical records and research studies, medical information is doubling every five years. Big Data analytics can help turn this information into insights so that doctors, patients, social workers, researchers, and payers can all make better decisions.”

Like any care provider today, a social worker has more data available to him or her than ever before, Schick says. “But often they’re unable to easily and securely share that data with other care providers when appropriate,” he adds. “There is too much information for any single person to process. The key is to access and make sense of Big Data in a way that improves decision making and care.”

Meikle recommends organizations have at least one analyst in-house if possible or partner with a third party that can do system checks and recommendations. “It’s critical to make sure the business process is aligned with the technology so that you’re not just spinning your wheels and collecting data that is not valuable to you,” he says.

Making Sense of Data Collection
Because there simply isn’t enough time to process all of the information in paper records, it’s a given that technology must be used to collect and process all of these data. Electronic health records (EHRs) are one way of collecting patient information, but it’s also where things can get challenging.

“What we’ve seen in health care, and social services in particular, is that the data being collected is very dirty,” Meikle says. “What I mean by that is that there is a lot of unnecessary information, incorrect entries, and even duplicate information in these systems because they’ve never really been customized for the social services world. When the data is extracted, there’s often a lot of trash in it, and that data needs to be cleansed before it can be used successfully.”

Schick adds that not all the data required are in the EHR, as EHRs capture only a part of the care process. “Today’s health care systems can no longer afford to provide care in a vacuum,” he says. “They must coordinate with one another to ensure the best possible delivery of care and the best use of health care resources. Patients today are more empowered to take control of their health and are becoming an increasingly important part of the care team. Big Data analytics can help make use of fast-changing information that comes from many different sources. In addition to the EHR, data can be collected from patients entering information into health care apps, lab technicians recording test results, or even providers writing prescriptions. The care systems of the future will use the EHR as one data source. By mixing, correlating, and presenting EHR data alongside other sources in a single view, care providers will be able to quickly extract and understand the relevant patient and care information, and make informed decisions on the path of care.”

However, Wong points out that the social worker culture also will be a hurdle to overcome to successfully utilize Big Data for positive outcomes. “It is a challenge to think about spending time inputting data when you can be servicing a client,” he says. “Social workers gain expertise in talking to real people with real problems as opposed to interfacing with a computer. There will need to be some shifts in what service providers are capable and willing to do around data.”

This also poses a challenge to vendors to modify their solutions, Wong says. They must find easier ways to collect these data so that staff doesn’t have to expend too much time collecting and inputting it themselves. “Finding valid ways of collecting data directly from clients by using mobile devices, QR [quick response] codes, and even RFID [radio-frequency identification] technology may speed things up,” he adds.

Big Data and the Future
Going forward, Schick believes that caregivers who can find ways to take advantage of Big Data will be able to make more evidence-based decisions. He says using Big Data can provide answers to some important questions for the social services sector. For example, Schick says Big Data could be analyzed to answer the following series of questions and ultimately provide a better patient outcome: “What is the correlation between readmission and access to social services? Can we see a correlation between the length of stay and the effectiveness of intervention? What is the connection between home address and frequency of visit? Can we find a connection between family status, truancy, interventions, and outcomes that can help us identify similar intervention candidates as they enter the care system? Is there an insight into a segment of the population that guides us to tweak our programs to either respond to or, even better, get ahead of a negative trend like teen pregnancy or domestic violence?”

Wong agrees that utilizing Big Data in the social services sector possibly could allow social workers to get ahead of negative trends. “If we are able to identify needs before the client themselves even knows this, and drive, in a safe and secure way, tailored services to them, we can see more effective gains and improved outcomes faster,” he says.

He uses dropping out of school within the youth sector as a possible example. “If we identify ways in which youth disengage from school or demonstrate actions that tend to lead towards greater at-risk behavior or educational underperformance—when data clearly shows higher potential—then we can intervene with preventative measures that may not cost more but are more effective and can be driven to the client.”

Schick says it comes down to the importance of the big picture. “Caregivers, agencies, and social service support organizations all have the patient’s well-being in mind but many times do not have the tools to mine data and gain insight to see the bigger picture,” he says. “Informed by Big Data analytics, social workers can play a larger and more active role in ensuring overall care outcomes.”

— Lindsey Getz is a freelance writer based in Royersford, PA, and a frequent contributor to Social Work Today.