Four Elements that Bridge the Gap Between Using Data and Becoming Data-Driven

医疗保健组织经常面临新的压力，这对他们的护理提供和财务可持续性提出了挑战，并要求制定一项基于数据的战略。数据驱动的卫生系统——那些依靠准确、最新的数据来指导和决定决策的系统——比那些仅仅使用数据来做决策的组织更有可能成功。数据驱动的医疗保健组织使用数据最大化其有限的资源并实现其目标(从临床结果到收费捕获过程)。

Although many healthcare organizations strive to be data driven, barriers, including a lack of leadership support, data-driven culture, or sufficient data access, keep them from fully leveraging data. Organizations can navigate these barriers by investing in data infrastructure that supports systemwide data reach, including one source of data truth, enabling data to inform processes and culture.

Four Elements of a Data-Driven Healthcare Organization

To determine where they are on the journey to become data driven, health systems can consider four foundational elements of a data-driven organization:

Element 1: Invest in One Source of Data Truth

Data-driven healthcare organizations have to manage increasing amounts of data (inside and outside of the hospital) and make these large amounts of data available to team members. Systemwide access meansone source of data truth, such as theHealth Catalyst Data Operating System (DOS™)，允许所有用户在做决策时引用相同的数据，避免部分数据集。

Many health systems rely on EHRs as their source of data truth, but EHRs are limited platforms that can’t aggregate multiple data sources, organize the data, and then distribute it. A robust enterprise data platform (e.g., DOS) with supporting analytic infrastructure delivers relevant data to the right team member at the right time. Delivering analytic insight to end users when they need it enables and supports data-informed decision making, a core part of a data-driven organization.

Element 2: Apply a Data Governance Strategy

To effectively leverage data to improve operational, clinical, and financial processes, organizations need adata governancestrategy. Data-driven organizations implement a data governance strategy to monitor the use of data, oversee the quality of the data, and distribute relevant data to team members. Because data is arguably a healthcare organization’s most valuable asset, a data governance strategy that ensures data veracity is key. However, data governance can be overwhelming and with increased access to data, many health systems don’t know where to begin a governance strategy.

Organizations can start their data governance strategy to optimize data use by following five steps:

1. Identify the organizational priorities to ensure the data governance strategy supports high-level organizational priorities.
2. Identify the data governance priorities and opportunities that are not part of the organization’s priorities.
3. Identify and recruit leaders who are likely to be early adopters of data governance.
4. Identify the scope of the opportunity appropriately to avoid doing too much too soon.
5. Enable early adopters to become enterprise data governance leaders and mentors for other team members.

Element 3: Promote Systemwide Data Literacy

Health systems can improve data use among team members by promotingdata literacy. Data literacy means that users understand the role data plays in decision making and rely on that data to guide the best decision. If team members value and prioritize data in decision making, organizations are more likely to be data driven. On the contrary, organizations can’t become data driven if their team members don’t trust data or lack understanding about the value of data in decision making. With many team members at differing levels of data competency, organizations can improve data literacy by generating leadership support and creating data literacy programs.

High-level support allows team members to see that data is a priority, enabling the data-centric mindset to trickle down. Data literacy programs assess data literacy levels and allow improvement teams to create custom programs to increase data literacy among team members, and therefore, the likelihood that users will leverage data in everyday decisions.

Element 4: Implement a Cybersecurity Framework

Lastly, data-driven healthcare organizations protect their data and ensure the highest quality data with a strongcybersecurity framework. Interoperability and rising amounts of data leave more opportunities for cyberattacks and data theft. A cyberattack could result in an organization losing data, a disruption in the enterprise data platform, and compromised patient privacy and safety.

组织可以通过考虑谁对网络安全负责来开始他们的网络安全方法:供应商(例如，Health Catalyst)还是卫生系统?世界杯葡萄牙vs加纳即时走地通常，网络安全是供应商和健康系统之间的共同责任。Next, security leaders can perform third-party audits and obtain certifications (e.g.,Systems and Organizations Controlscompliance) to assess and understand the current level of cybersecurity and opportunities to strengthen it.

Data-Driven Healthcare Organizations Achieve Sustainable Improvement

From patient outcomes to operational processes, health systems need data to implement meaningful improvements. However, simply using data in one-off situations is different from being data driven. Organizations can be more effective if they achieve the latter. Becoming a data-driven healthcare organization requires more investment and resources—a data infrastructure, data-driven processes, a data-centric culture, and a supporting cybersecurity framework—allowing team members to make the most informed decision and the organization to reach its goals.

Additional Reading

Would you like to learn more about this topic? Here are some articles we suggest:

1. How to Build a Healthcare Data Quality Coalition to Optimize Decision Making
2. Three Must-Haves for a Successful Healthcare Data Strategy
3. Why Data-Driven Healthcare Is the Best Defense Against COVID-19
4. The Healthcare Cybersecurity Framework: A Top Defense Against Data Breaches and Attacks
5. Healthcare Data Quality: Five Lessons Learned from COVID-19