Data-Driven Decision-Making, Types of Data Used for Making Decisions in Health Care, and the Importance of Using Data in Decision Making

Data-driven decision-making (DM) involves making decisions with experiential and empirical data rather than using feelings, instincts, observations, or conjecture. Healthcare professionals and leaders can utilize various data types to support their decisions. Healthcare providers can use surveys and review data sources to collect data to form the basis of their decisions. The main types of data used for making decisions in health care include claims data, safety and quality outcomes data, utilization rate data, patient outcomes and experience data, research data, organization operational data, process data, organizational financial data, disease surveillance data, and patient assessment data. These data types can be obtained from a review of the existing patient medical records, administrative and other vital organizational operations records, interviewing patients and the community, disease registries, and review of existing literature.

The use of data by leaders when making decisions is important as it helps identify scientifically plausible approaches to improve the efficiency of operations in healthcare organizations. Improved efficiency due to data use is one notable application leaders can use to reduce operational costs. Integrating data in decisions can also help leaders identify and resolve critical gaps and improvement barriers within healthcare organizations to meet the expectations of patients and communities, hence helping the organization improve services and provide personalized care (Dash et al., 2019).