By Mary Velan
Gov1
Local governments are overflowing with data that spans all departments and services. This information provides valuable insights that aid in decision making - such as department performance, project outcomes and community trends. The key to extracting these insights lies in how government agencies choose to analyze the data and how it is tangibly applied.
Child Protection Services
One example of the use of data analytics to improve public services can be seen in state child welfare agencies which are implementing sophisticated computer models to better predict where children are most likely to suffer abuse. By leveraging a computer algorithm, social services use predictive analytics to identify homes and communities with red flags suggesting they are more prone to child abuse and neglect. The agencies can then pay closer scrutiny to these households to ensure children are safe and protected, the Boston Globe reported.
The computer models were first launched in Hillsborough County, Florida, and have spread to five states including Maine, Connecticut, Pennsylvania and Massachusetts. The data-driven predictions generated from the computer models are designed to aid overworked social services teams by prioritizing the most important cases in the community. Social services can then make better use of scarce resources to provide services where children are most at risk, the Boston Globe reported.
Because each household is unique, the computer models are used to help guide social service workers when deciding where to focus their attention. The analytics are not used to make any final decisions regarding child safety, but rather point social workers in the right direction to then investigate further into specific households and communities.
The systems work by gathering all available data on local child abuse cases in the past, and extracting key data points to categorize the cases - such as age of the child, drug use, domestic violence, etc. When factors or red flags appear in any upcoming abuse cases, they are singled out by the computer system and subjected to a review by a quality assurance team. The review includes scrutinizing the response by the front-line social worker to ensure high-risk cases are handled quickly and efficiently. When a call comes into the child abuse hotline, call screeners will enter the name, address and other information of the alleged perpetrator into the system. The computer will then place a higher risk score on the individual in the records system, as well as others in the home if there is a criminal history, the Boston Globe reported.
School Districts
Many cities nationwide are linking student data across several government agencies to extract valuable insights into children’s experiences in the community. These integrated data systems connect children’s educational records with data from a variety of public agencies including healthcare, child welfare placements and involvement in the juvenile justice system. The goal of the data sharing and analytics initiative is to improve public policy, service delivery and program evaluation so students are more likely to succeed, ED Week reported.
In Allegheny County, Pennsylvania, officials are using an integrated data system to analyze the experiences of homeless students and children in foster care. The county discovered more than half of all students in Pittsburgh public schools have experience in community human-services programs - suggesting students are in dire need of services. The county initiated a cross-sector effort to combat chronic absenteeism through collaboration between community and school agencies. Child welfare case workers will receive alerts when children in their caseloads are suspended or miss several days of school. District officials and school counselors will receive similar notices when students are found in homeless shelters or run into legal trouble.
The goal is for all agencies servicing students be on the same page and working collaboratively to improve child success and wellbeing. This can be achieved through tailored services, increased outreach, updated policies or other community-level changes, ED Week reported.
All 50 states have developed statewide longitudinal-data systems filled with anonymous information on students from preschool through college. Of these systems, 19 connect educational data to workforce information, while another 30 link education records with profiles from other public agencies in the community. Integrated data systems go a step further to analyze the cross-sector data to find patterns and opportunities to improve policies, ED Week reported.
Campaign Finance
The Illinois Sunshine campaign finance transparency site recently launched in an effort to educate the public on political and public policy issues using State Board of Elections open data. The website’s API and data dictionary allow users to query data about Illinois candidates, committees and committee finances dating back to 1994. Users can search all donations and expenditures made over the past 20 years, as well as examine committee net funds and candidates supported by them.
The goal of the website is to keep public officials accountable by making all finances transparent and open to citizen inquiry. If citizens understand how campaign finances may influence elections and public policy, they can make more informed decisions at the polls and advocate for change in the community.
Furthermore, citizens can use the API to design their own software and mobile applications using the available data, as well as the data dictionary to explain what the information means.