社会创新

We have the data to improve social services at the state and local levels. So how do we use it?

05.25.23 | 4 min read | 文字卡琳娜·格哈特(Karinna Gerhardt)&Faith Savaiano

共同19岁的大流行揭露了一些人已经知道的东西:我们国家依靠提供关键社会服务和福利的系统一直是过时,undersupported, 和provide atrocious customer experiences这很快将导致大多数私营企业失败。

从签署失业保险到管理医疗补助福利或提交年度纳税申报表,可以通过使用来自用户经验的数据并使用类似计划在上下文中对其进行评估,从而可以改善与政府服务的许多令人沮丧的互动。人们如何使用这些服务?客户在哪里反复沮丧?这些服务在什么时候失败了,从不同程序的比较结果我们可以学到什么?全国许多机构已经收集了有关其运行计划的大量数据,但没有充分利用这些数据来改善各种社交计划的服务。评估计划数据对于提供有效的社会服务是必要的,但是地方和州政府面临着长期的能力问题和高官僚障碍,以评估他们已经收集的数据,并将评估结果转化为多个计划的改进结果。金博宝正规网址

In a recent paper, “Blending and Braiding Funds: Opportunities to Strengthen State and Local Data and Evaluation Capacity in Human Services,” researchers Kathy Stack and Jonathan Womer deliver a playbook for state and local governments to better understand the limitations and opportunities for leveraging federal funding to build better integrated data infrastructure that allows program owners to track participant outcomes.

良好的数据是从地方到联邦一级提供有效的政府服务的关键组成部分。Right now, too much useful data lives in a silo, preventing other programs from conducting analyses that inform and improve their approach – state and local governments should strive to modernize their data systems by building a centralized infrastructure and tools for cross-program analysis, with the ultimate goal of improving a wide range of social programs.

The good news is that state and local governments are authorized to use federal grant money to conduct data analysis and evaluation of the programs funded by the grant. However, federal agencies typically structure grants in ways that make it difficult for states and localities to share data, collaborate on program evaluation, and build evaluation capacity across programs.

Interviews with leading programs in科罗拉多州,印第安纳州iana,Kentucky,俄亥俄州,罗德岛, 和Washington尽管面临多种政府计划的挑战,但揭示了州和地方政府用来建立和维护综合数据系统的许多不同方法。这些方法范围包括:采用强大的执行愿景,与外部合作伙伴(例如研究小组和大学)合作,投资于建立基准能力,以实现更高级别的分析工作,进行至关重要的初步分析,以激发决策者直接提供直接州资金,以及(最著名的)弄清楚如何从多个联邦赠款来源编织和融合资金。这些州中的计划证明,可以建立一个集中式系统,以评估各种政府服务的结果和影响。

随着数据通过IDS的方式,将其清洁,验证并与其他数据匹配。

Stack和Womer列出了他们的推荐选项菜单,各州和地区可以追求的选择,以便获得联邦资金以建立数据和评估能力。这些选项包括:

  1. stimulus funding根据美国救援计划的州和地方财政回收基金以及《基础设施投资与就业法》;
  2. program-specific funding that funds centralized capacity;
  3. 直接的州或地方拨款;
  4. 根据项目为项目提供资金;
  5. 成本分配计费计划;和
  6. hybrid funding models.

作者倡导各州和地区blend funds and braid funds在适当的情况下,为了充分利用联邦资金机会。混合资金are sourced from multiple grants but lose their distinction upon blending; this type of federal funding requires statutory authority, and may have uniform reporting requirements. Alternatively,braided fundsalso come from separate sources, but remain distinct within the braided pot, with the original reporting, tracking, and eligibility requirements preserved from each source. Financing projects and programs via braiding funds is far more time-consuming, but it does not require special statutory authority.

While states and localities can strengthen and expand integrated data systems alone, the federal government should also take important steps to accelerate state and local progress. Stack and Womer point out a number of options that do not require legislative action. For example, the Office of Management and Budget (OMB) and other federal agencies could issue clear guidance that recipients of federal grants must build and maintain efficient data infrastructure and analytics capacity that can support cross-program coordination and shared data usage. Regulatory and administrative actions like this would make it easier for states and localities to finance data systems via blending and braiding federal funds.

综合数据系统是政府越来越重要的工具,可以实现影响目标,避免冗余并跟踪结果。州和地方政府应从Stack和Womer的剧本中获取页面,并寻求使用联邦赠款将现有数据基础架构建立为支持交叉程序分析的现代系统的创新方式。