Healthcare Data Foundations Chapter 1

Healthcare data is used to improve the quality and safety of care, decrease costs, introduce changes to practice, prevent healthcare disparities, and approach populations with a focus on addressing population-based clinical conditions.

Nurses use data to monitor patient health, identify trends, evaluate interventions, and make informed decisions about care plans. Data helps them track patient progress and optimize their care.

Data transforms through stages, starting as raw observations, then becoming organized information, evolving into actionable knowledge, and finally culminating in wisdom that guides healthcare decision-making.

Nursing informatics focuses on merging technology, healthcare data, and nursing practices to enhance patient care delivery.

Data analysis helps identify patterns, trends, and areas for improvement in patient care.

Data can be used to track patient outcomes, evaluate the effectiveness of treatments, and measure the impact of care interventions.

Data is valuable for consumers as it allows them to make informed choices about their health and healthcare.

Data-informed decision-making involves using data analysis and insights to guide healthcare choices for better patient outcomes.

Clinical decision support (CDS) systems are designed to deliver patient-specific information to healthcare providers during their workflow to aid in making better clinical decisions.

CDS systems are widely believed to have a positive impact on patient safety, specifically by improving medication safety.

The "five rights" of CDS refer to providing the correct information to the right people, through the right channels, in the right format, at the right time, and within the appropriate workflow.

Data plays a vital role in CDS systems, enabling them to provide personalized and data-driven insights to enhance clinical decision-making.

CDS systems aim to improve patient safety by providing evidence-based recommendations across a wide range of clinical conditions.

Electronic health records (EHRs), computerized provider order entry (CPOE), patient progress notes, and medication records.

Raw facts or figures about a patient, such as name, age, weight, and vital signs.

Data that has been processed and organized to give it meaning, such as a patient's medical history or lab results.

Information that helps us understand relationships and patterns, such as the connection between nurse-patient ratios and patient outcomes.

A framework that describes the progression of data into information, knowledge, and wisdom, which can be used to improve patient care.

A standardized language for healthcare data, used by nurses and other healthcare providers.

A standardized way of describing a patient's condition, used by nurses.

A system that helps providers make better clinical decisions by providing them with relevant information at the point of care.

A system that allows providers to order medications and other services electronically.

A tool that allows healthcare organizations to collect and analyze data to improve care.

The use of technology to improve patient safety and reduce medical errors.

Nurses who specialize in using technology to improve patient care and health outcomes.

The use of data to identify and understand trends in healthcare, such as the prevalence of certain diseases or the effectiveness of treatments.

The use of technology to improve communication and collaboration among healthcare providers.

The accuracy and trustworthiness of healthcare data are critical for making sound decisions and ensuring patient safety.

A computer system's built-in feature that prompts users to complete a task, verify information, or prevent incorrect input.

Health data collected from individuals about their health status, behaviors, and access to care.

Detailed records of patient encounters, including diagnoses, treatments, and medications.

Data gathered from insurance claims, providing insights into healthcare utilization and costs.

Official records of births, deaths, and other vital events, used for population health analysis.

Systematic monitoring of diseases and health events, often used to detect and respond to outbreaks.

A collection of information about a particular disease, condition, or population.

Gathering data directly from individuals using questionnaires or interviews.

A process of using data to inform decision-making and improve healthcare outcomes.

A type of research that focuses on understanding the effectiveness of healthcare processes and interventions.

The goal is to enhance the quality of care by examining how different healthcare practices affect patients' outcomes.

A patient-centered approach to healthcare that emphasizes the patient's needs and preferences.

A healthcare payment model that rewards healthcare providers for delivering high-quality care at a lower cost.

Using data to meet payment models that reward value and quality over volume in the US healthcare system.

Data that helps measure the quality of healthcare delivery to determine whether planned improvements are effective.

The study and practice of using technology, healthcare data, and nursing science to enhance patient care. It's like a bridge between nurses and technology.

The use of health information, technology, and data to guide decision-making and improve patient care.

A system of data collection and analysis that focuses on improving patient care by identifying patterns, trends, and areas for improvement.

A healthcare reform that rewards providers for delivering high-quality care, rather than simply the volume of services provided.

The knowledge and skills needed to effectively search, evaluate, and use healthcare information.

A collection of health data from various sources, often too large and complex to be analyzed by traditional methods.

A healthcare policy that focuses on using data to improve patient care and measure the effectiveness of interventions.

Tracking patient outcomes to assess the effectiveness of treatment plans and measure the impact of care interventions.

The use of data to understand and address health issues that affect specific groups of people.

A healthcare policy that encourages healthcare providers to work together to coordinate care and improve outcomes for a specific population.

The science and practice of protecting sensitive health information.

A national organization that provides evidence-based information and resources to improve the quality of healthcare.

A significant event that disrupts healthcare delivery, requiring immediate action and data analysis.

Gathering information from various sources to form a comprehensive understanding of a healthcare issue.

A trigger is an event, like ordering an antibiotic, that sets off a CDS algorithm to provide relevant information.

Input data refers to the information gathered about the patient, such as lab results, medications, and medical history, used by a CDS algorithm.

Interventions are different actions suggested by a CDS algorithm based on the input data and trigger, like altering the medication dose or choosing a different antibiotic.

The action step is the decision made by the clinician based on the suggested interventions, reflecting their clinical judgment and expertise.

Medication alerts warn clinicians about potential drug interactions, allergies, or dose adjustments based on patient-specific factors.

Alert fatigue occurs when clinicians are bombarded with too many alerts, some of which might be irrelevant, leading to decreased attention to important warnings.

Order sets provide clinicians with pre-defined, evidence-based orders tailored to specific patient conditions for streamlined and efficient ordering.

Workflow support tools help clinicians manage the flow of patient care efficiently, such as for discharging a patient or coordinating care transitions.

Medication reconciliation tools ensure that patient medications are accurately tracked, reviewed, and adjusted throughout their care journey.

CDS tools are valuable for advanced practice nurses because these technologies can facilitate the translation of research findings and best practices into clinical decision-making, leading to improved patient outcomes.

Advanced practice nurses can use their expertise to ensure that CDS tools are kept up-to-date with current evidence and implemented effectively in their clinical settings.

CDS tools are often integrated into electronic health records (EHRs), providing personalized insights and recommendations during patient care.

Each electronic health record (EHR) vendor may configure their CDS tools differently, presenting challenges for standardizing and maintaining up-to-date information.

The use of CDS tools and related interventions is still relatively new and evolving. As these technologies mature, advanced practice nurses will play a key role in incorporating them into clinical practice and ensuring their effectiveness.