The Importance of a Nursing Data Framework
By Dr. Luann Whittenburg, RN, PMP, FHIMSS
A Nursing Data Framework can give healthcare providers a way to garner business intelligence to save money and reduce risk by improving workflows, load leveling personnel schedules, and improving patient safety.
With more than 4 million nurses in the U.S., nurses are the largest clinical segment of the U.S. healthcare sector. Nurses have indisputably demonstrated an ability to improve healthcare outcomes. We are just beginning to utilize data from healthcare information technologies and to employ Artificial Intelligence (AI) to improve patient outcomes. One of the key benefits of AI will be the ability to leverage the data from nursing care plans and nursing diagnoses to perform work load balancing for nursing staff. This is a key solution to future management of the problem of the shortage of nurses.
Another problem which needs attention is the possible disconnects that can result from nurse to nurse handoffs with the use of virtual nurses who remotely monitor patients. They can remotely enter data into their own Electronic Health Record (EHR) system. These EHR systems are generally not the same as those in use by the hospital where the patient is located.
Here we will discuss solutions for staffing, interoperability and workflow improvements that can be leveraged to provide better quality patient care. We will address the nature of the data, underlying technologies and frameworks for a nursing information model, and the structure of the data elements needed to implement these solutions for staffing, interoperability and workflow improvements.
The National Academy of Medicine’s committee background report on the Future of Nursing 2020-2030, Activating Nursing to Address Unmet Needs in the 21st Century, found that the worsening health profile in the United States requires “more than a traditional medical response”.
Nurses are key professionals in the care team. For this reason nursing documentation requires a standardized framework to achieve consistent data quality in healthcare communications about the work of nurses. The standardized framework recognized for professional nursing documentation is the American Nurses Association (ANA) Nursing Process. This ANA framework is essential to nurses for managing and improving healthcare outcomes, safety and reimbursement as proposed by the Institute for Healthcare Improvement (IHI).
In most electronic health information record systems, the standard nursing data implemented (sometimes called the system terminology, data dictionary, or nomenclature) is proprietary with a pre-existing data structure / framework. The proprietary framework acts as a barrier to nursing documentation by constraining the available concepts for nursing documentation and the nursing care plan fields.
Without interoperable electronic data concepts, nursing care notes become unstructured free-text and are not included in coded health data exchanges. Due to the highly structured design of EHR systems, nursing practice is determined by the system’s terminology and ontology framework configuration. If nurses do not select the ANA framework, nursing care data takes on the sedentary shape of the local proprietary data structures, rather than nesting in a flexible, portable and universal tool to enable nurses and other episodic care providers to improve future nursing interventions, practice and care outcomes.
The American Nurses Association (ANA) describes the common nursing framework of the documentation of professional nursing practice as the Nursing Process. The Nursing Process is the foundation for the documentation of nursing care. Yet, in the EHR system, nursing documentation is reused during the patient’s stay, over and over, with the documentation being done from the nursing assessment as if the documentation was a template.
The Nursing Process is the framework and essential core of practice for the registered nurse to deliver holistic, patient-focused care” (source: ANA, 2019). Producing effective EHR systems for nursing requires a deep understanding of how nurses create and conduct cognitive documentation as well as task-oriented documentation. Most EHR systems dictate rather than adapt to nursing workflows and nursing information is not organized to fit the ANA model of care.
The EHRs often assume a nursing care delivery model that is represented as algorithmic sequences of choices, yet nursing care is iterative with reformation of patient goals, revising interventions and actions and updating care sequences with individual patients based on encountered condition changes and constraints. In the dictated workflow of EHRs, nursing data is collected as care assessments with nursing diagnoses, interventions and actions in formats used to create single patient encounters.
Yet, EHRs, the communication tool for health information exchange (HIE), do not collect standardized nursing data. Data quality in healthcare communication is essential to promote the necessary changes in performance delivery among the nation’s healthcare providers of care. In order to obtain transparent and complete clinical communications and data quality, EHRs must collect and document the variations in data elements following the American Nurses Association (ANA) Nursing Process framework. A standard, coded, structured nursing documentation standard is needed to exchange nursing communication to bring transparency to the contributions of nursing to patient care continuity and the quality of health outcomes.
This article describes the purpose, value and benefit of implementing nursing terminology in nursing documentation systems. The Clinical Care Classification (CCC) System facilitates nursing documentation at the point-of-care and allows nurses to communicate three aspects of care:
- The nursing diagnoses of patients
- The nursing interventions performed
- The resulting care outcomes.
The CCC System is a “research-based, coded terminology standard that identifies the discrete data elements of nursing practice-the essence of care. The CCC System includes a holistic framework and coding structure of diagnoses, interventions, and outcomes for assessing, documenting, and classifying care in all healthcare settings” (Hunter & Bickford, 2011, p. 183).
The CCC research project was conducted under a Federal grant to develop a methodology for classifying patients and measuring outcomes. The research project represented every state in the United States, including Puerto Rico and the District of Columbia (Saba, 1992). The CCC System uses the six steps of the nursing process to describe nursing practice in a coding structure designed for retrieving data from computer information systems. See www.clinicalcareclassification.com and Wikipedia.org/Clinical_Care_Classification_System.
When electronic nursing documentation systems use coded, standardized nursing language, nurse managers are able to query the electronic nursing documentation application about nursing workload, the actions required to provide care, and evaluate the outcomes of nursing care and examine what nursing actions result in improved care.
EHR documentation applications of the future that use standard nursing terminology and follow the nursing process will be sufficiently flexible to meet the professional documentation needs of both nursing and allied health professionals in all clinical settings. The 2001 Institute of Medicine’s (IOM’s) Committee on the Quality of Health Care in America report, ‘Crossing the Quality Chasm: A New Health System for the 21st Century’ concluded only real-time access to appropriate healthcare knowledge will provide clinicians with the information required to make well-informed decisions.
Nursing documentation completed in a structured text must incorporate a nursing terminology standard following the Nursing Process for a useful, common representation of all pertinent nursing documentation. The retrieval of nursing documentation can then be exchanged among HIEs for patient care continuity and outcomes analysis. Standardized nursing data allows information from disparate locations to deliver data for evidence-based practice to improve the nation’s health profile and the data quality of exchanged healthcare information.
In summary, the usability of EHR systems, alignment to the nursing workflows and the meeting of nursing information needs are key for successfully designing and implementing EHRs to improve the nation’s healthcare profile, achieve consistent HIE data quality and retrieve and mine the comprehensive workflow data needed using the Nursing Process framework to improve care coordination and demonstrate nursing’s impact on outcomes.
The money saving potential of AI is only possible if the right standardized and coded data structures are there to mine. Standardized frameworks, the use of data exchange standards and coded reference terminologies set the data free from proprietary and sedentary non-coded text. Only then can AI reasoners reach useful conclusions and calculate reliable results.
Pittman, P. (2018). Activating Nursing to Address Unmet Needs in the 21st Century report.GW Health Workforce Institute, Milken Institute School of Public Heath, George Washington University, Washington, DC. https://publichealth.gwu.edu/sites/default/files/downloads/HPM/Activating%20Nursing%20To%20Address%20Unmet%20Needs%20In%20The%2021st%20Century.pdf
American Nurses Association, Nursing Process. https://www.nursingworld.org/practice-policy/workforce/what-is-nursing/the-nursing-process/
Institute for Healthcare Improvement, Triple Aims. http://www.ihi.org/engage/initiatives/TripleAim/Pages/default.aspx
Saba, V. K. (2007). Clinical Care Classification (CCC) System manual: A guide to nursing documentation. New York: Springer Publishing.