Exploring Nurse Case Managers' Language Describing Health Needs and Interventions with Populations

Abstract

Major advances in health information technologies, safety and quality initiatives, and health policy changes have fueled the development and implementation of the Electronic Health Record (EHR). Any discipline’s work and contribution to patient care exist in the EHR only as they are coded. Thus, coding nursing’s knowledge, work and contribution to patient care in meaningful ways requires nurses to have a language that defines nursing concepts and works consistently and reliably. Currently the American Nurses Association (ANA) recognizes twelve (12) nursing languages being used in the EHR. Over the last forty years many research efforts have validated these nursing languages and mapped the languages to each other and to other clinical terminologies. Although these nursing languages exist and are in use, they were developed and are used primarily for describing nursing care to individual clients and occasionally extended to families and groups. Nursing languages describing the care of populations has not been well researched. Thus, the purpose of this study was to identify the descriptors and names nurse case managers used to refer to subpopulations, the data elements they used to assess subpopulations, the descriptors and names did nurse case managers use to refer to interventions for the subpopulation, and the descriptors and names used to refer to outcomes of the interventions. The study was designed to investigate language used by nurses doing population based care. Participants were nurse case managers who were members of the Case Management Society of New England. A questionnaire was distributed in both online and written formats; 19 participants answered questions based on a case study about subscribers of an insurance company with diabetes mellitus. A tentative folk taxonomy was generated from responses to the questionnaire. Although the tentative folk taxonomy requires further investigation, it identified ten categories labeled utilization, cost, disease-related, treatment-related, people factors, living factors, education, support/coach/care coordination, and type of interactions. Thirty-nine subcategories were associated with the five categories and gave more specificity to the language in the categories. Further investigation of the folk taxonomy with different samples is needed to validate the categories and subcategories followed by additional research with different diseases and conditions.