Test of the nursing minimum data set: availability of data and reliability

An initial study of the availability of the elements in the Nursing Minimum Data Set (NMDS) and intercoder reliability across four types of clinical settings is reported. These clinical settings included an acute care hospital, a nursing home, a home health care agency, and two ambulatory care clinics. The health records of 116 randomly selected subjects were reviewed to determine the availability of the NMDS elements. A randomly selected subset of 23 of these records provided data on intercoder agreement. All but four of the NMDS elements were available for 85% or more of the subjects. The average intercoder agreement across all NMDS elements was a satisfactory 91%. However, the intercoder agreement on some NMDS elements was much lower, suggesting a need to refine the definitions and procedures for collecting some of the NMDS elements. Where appropriate, coefficient Kappa and Pearson product moment correlation statistics for reliability are reported on individual NMDS elements.     

Nursing Intervention Classification Systems

Purpose: To analyze the features, development, and research of the Omaha System, the Iowa Nursing Intervention Classification, and the Home Health Care Classification and provide a critical review of the unique components of each.
Organizing Framework: Five elements: achievement of original purpose, language used, ease of computerizing format, clinical utility, and linkage of the Nursing Minimum Data Set (NMDS) nursing care elements.
Conclusions: Further testing and development of nursing classification systems should be done to determine the general value of nursing classification, the extent to which the original goals and purposes of classification are met, and to identify the unique features and contributions of each system. Further testing is important to determine the strengths, weaknesses, and applicability of the various systems for capturing the elements of the NMDS for different care settings, care givers, and patient populations.
Implications: Nursing classification may eventually lead to naming and describing the work of nurses. Research findings will continue to provide information leading to a unified nursing language system that describes the practice of nursing in local, regional, national, and international health-care data sets used for research, clinical, education, policy, and administrative purposes.     

Nursing Minimum Data Set development and implementation in Thailand

BACKGROUND: In 1997, the Thai Ministry of Public Health began planning to implement a national health information system. Development of the nursing component of this system is an ongoing process. The first step in developing a nursing information system is to identify an essential Nursing Minimum Data Set (NMDS). AIM: To describe the development of a NMDS in Thailand and explore the challenges of implementing it, including the issue of the comparability with data sets in other countries, primarily the United States of America. METHODS: The process of developing a NMDS specific to Thailand is reviewed. Strategies for implementing this data set and important issues related to it are then discussed. FINDINGS: Although a preliminary Thai NMDS has been identified, challenges associated with its development and implementation within the Thai National health information system remain. CONCLUSION: A Thai NMDS and its elements have been identified. The International Classification of Nursing Practice was translated and is to be used to implement the data set describing the nursing care of patients and their families. However, many issues, such as the need for conceptual translation and increasing nurses' involvement in the process, still need to be addressed in order to implement the data set successfully.     

Nurse autonomy,nurse job satisfaction and client satisfaction with nursing care: their place in nursing data sets

Many changes have taken place in the healthcare system that have influenced nurse autonomy, job satisfaction and client satisfaction. Standardized language facilitates communication within the discipline of nursing. Examples of such language include the Nursing Intervention Classification (NIC) and the Nursing Outcomes Classification (NOC) systems as well as the Nursing Minimum Data Set (NMDS), which provides a formal structure for electronic data sets to support nursing care. The Nursing Management Minimum Data Set (NMMDS) was designed to identify variables to guide nurse managers in evaluating the impact of nursing interventions on client outcomes. Gaps within NMDS and NMMDS are discussed, and solutions are proposed.     

Use of the Nursing Minimum Data Set to Describe Nursing Interventions for Select Nursing Diagnoses and Related Factors in an Acute Care Setting

This study describes the prevalence of nursing interventions across six nursing diagnoses and their related factors using the framework of the Nursing Minimum Data Set (NMDS). Six nursing diagnoses (pain, potential for injury, anxiety, decreased cardiac output, potential for infection, and knowledge deficit) were among the most prevalent in an acute care setting studied in 1992. The NMDS and a nursing information system using standardized classification systems for nursing diagnoses and interventions provided an opportunity to describe nursing practice. Multiple related factors were identified across all six nursing diagnoses; three or four were selected frequently within each diagnostic category. The related factors also influenced the selection of interventions. Implications for the development of nursing classification systems and recommendations for further research are described .     

Classifying Nursing-Sensitive Patient Outcomes

This report describes research at the University of Iowa College of Nursing to develop a comprehensive classification of nursing-sensitive patient outcomes. The Nursing-Sensitive Outcomes Classification (NOC) completes the nursing process elements of the Nursing Minimum Data Set (NMDS). We describe resolution of conceptual and methodological problems that define the inductive approach taken to develop the NOC. Strategies used to develop NOC included review of the literature, clinical databases and instruments; concept analysis; and surveys of nurse experts. Examples of outcomes, definitions, and indicators are presented. The NOC provides standardized patient outcomes for determining the effectiveness of nursing interventions and enables inclusion of these data in data sets for healthcare effectiveness research.     

Measuring the intensity of nursing care: making use of the Belgian Nursing Minimum Data Set

BACKGROUND: The Belgian Nursing Minimum Data Set (B-NMDS) is a nationwide registration of 23 nursing activities. It was developed for the measurement of nursing care in acute hospitals. It is used to support healthcare management & policy decision making such as hospital financing and nurse staffing decisions. OBJECTIVE: To develop a measure of the intensity of nursing care based on information that is available in the B-NMDS. DESIGN-SETTING-PARTICIPANTS: Retrospective analysis of the B-NMDS from all Belgian acute hospitals (n=115) for the year 2003. The sample included 690,258 inpatient days for 298,691 patients that were recorded from 1637 acute care nursing units. METHODS: The 23 nursing activities were synthesized into one new latent variable by PRINQUAL analysis. This variable was evaluated as a measure of nursing care intensity using key characteristics of the San Joaquin patient classification system, which was designed to measure the intensity of nursing care. RESULTS: The main NMDS component from the PRINQUAL analysis accounted for 26.8% of the variance. The distribution of inpatient days over all four San Joaquin categories is: 11.1% (self-care); 40.4% (average care); 30.8% (above average care); 17.7% (intensive care). In 97.5% of the nursing units the intensity of nursing care score of the B-NMDS (main NMDS component) followed the ordinality of the San Joaquin classification system. Furthermore, the San Joaquin categories alone explained more variability--70.2% in the intensity of nursing care measure (main NMDS component) than did other determinants, such as department type, age, diagnostic-related groups (DRG) and severity of illness, hospital type and hospital size together. CONCLUSION: The B-NMDS is an instrument that produces a measure of the intensity of nursing care in acute hospitals.     

Genetics and genomics in nursing: evaluating Essentials implementation

The goal of the present study was to determine how well selected essential knowledge elements and practice indicators from the Essential Nursing Competencies and Curricula Guidelines in Genetics and Genomics (Essentials) were being achieved. A cross-sectional survey design was used. Eligible participants were recruited from a convenience sample of attendees at a national nursing conference in October 2008. Of the 200 surveys distributed, 47 usable surveys (24%) were returned. The majority of respondents were current nursing faculty (45.7%). Only 36% of all respondents had read the Essentials document. Less than 30% of respondents had attended any recent genetic/genomic content continuing education. There were significant associations between having read the Essentials document and obtaining both recent genomic continuing education and conducting genetic research (p<0.01). The results from this survey indicate that the Essentials have not been well disseminated outside of those primarily interested in the subject matter. They further indicate that respondents were not well prepared to respond to patient queries about genetic testing. Nurse educators must be adequately educated to address genomics as it will eventually become commonplace, with global applications in health promotion, disease prevention, and diagnostic and treatment strategies.     

Use of NIDSEC-compliant CIS in community-based nursing-directed prenatal care to determine support of Nursing Minimum Data Set objectives

If the Nursing Minimum Data Set elements, specifically the nursing care elements, are included in a clinical information system, nursing will be able to measure outcomes and contributions to both healthcare and nursing to build knowledge using clinical data. The purpose of the reported study was to determine whether a Nursing Information and Data Set Evaluation Center-compliant clinical information system using the Omaha System could support the Nursing Minimum Data Set goal to describe nursing care in a community health setting. The secondary data set analysis was conducted. The findings showed that although the clinical information system was compliant with the standard, used a recognized American Nurses Association nursing vocabulary, and supported the collection of the Nursing Minimum Data Set, the data were not sufficient to address the purposes of the Nursing Minimum Data Set. The implications for nursing research and clinical practice are outlined.     

Hidden outpatient oncology Clinical Nursing Minimum Data Set: Findings from an Italian multi-method study

PurposeThe main aim of this study was to present the hidden Clinical Nursing Minimum Data Set adopted by Italian nurses in outpatient oncology settings.MethodsA multi-method study design articulated in three phases was conducted from November 2009 to December 2010. A cross-sectional study design involving outpatient oncology centres located in the 20 Italian regions was undertaken in order to collect structured nursing records used by nurses in the documentation of daily nursing care. An evaluation of the items contained in each nursing record was performed in order to individuate homogeneities. A content analysis of the items was therefore undertaken in order to categorise them in assessment, problems, intervention, and outcomes.ResultsA total of 1080 different items from the structured nursing records were counted, comprising on average 29 items (range 8–175; ±40.4) for each record. A total of 330 (30.6%) out of 1080 were categorised as assessment items, 146 (13.5%) as problems, 583 (54.0%) as interventions and 21 (1.9%) as outcomes items.ConclusionItalian nurses have developed a micro-system Clinical Nursing Minimum Data Set capturing and documenting several types of clinical data, following their implicit representation of what it is important to document: much consideration is given to nursing surveillance/monitoring and to at-risk problems, indicating the importance of the nursing role in the prevention and early recognition of a patient's clinical deterioration. However, there is a need to develop a macro-system national NMDS which will be useful for evaluating nursing outcomes and making decisions on workforce resources.     

Computerized databases: privacy issues in the development of the nursing minimum data set.

Nursing leaders promoting the development and use of computerized databases such as the Nursing Minimum Data Set (NMDS) have not adequately addressed the complex ethical issues involved with computerized information systems. The purpose of this article is to describe the privacy issues involved with the NMDS. Moral considerations and principles guiding resolution of ethical issues concerning violations of patient privacy are discussed. A paradigm case is used to demonstrate the significance of privacy violations in computerized databases. Two security systems currently being considered in other disciplines are included for their relevance to the development of the NMDS. The broader implications concerning the impact of technology on preservation of human dignity and the quality of life are addressed.     

A survey of nurses' views on indicators for continuing competence in nursing.

The study, commissioned by the Australian Nursing Council Inc. (ANCI), sought to develop an approach to the maintenance of continuing competence in nursing broadly acceptable to nurses in all States and Territories and included the conduct of a postal survey of registered nurses (RNs) throughout Australia. An options booklet and accompanying questionnaire were posted to a random sample of 2 % of RNs from all Sates and the Northern Territory in Australia. The sample consisted of 4,133 RNs and 1,005 completed questionnaires were returned representing a 24.3% response rate. Data were analysed using SPSSX. The results suggest that respondents most favoured the introduction of a signed declaration of competence for all nurses seeking annual relicensing and the conduct of random competency audits by nursing regulatory authorities.     

Attitudes of Australian nurses to information technology in the workplace: a national survey

This article reports on the views of Australian nurses as to their use of computers in the workplace. Data were collected by questionnaires mailed to 10,000 members of the 150,000-member Australian Nursing Federation, which represents 60% of the Australian nursing workforce. The response rate was 43.3%. Computer use was 20% by assistants in nursing, rising to 75% by enrolled nurses and to more than 95% by RNs. Principal uses for the computers by the nurses were for access to patients' records and for internal communication. Most respondents (79%) agreed that the use of computers had improved information access. Only 9.4% considered that adoption of a national electronic health record would not be useful to healthcare. Fewer than 5% stated that they have no interest in computers, and 87% considered that their age was never or rarely a barrier to their use of the technology. However, not all aspects of computer introduction to nursing were positive. The proportions of respondents who considered that the use of computers had made their work easier, reduced duplication of data entry, and reduced errors in handing patient data were only 42%, 32%, and 31%, respectively. Results demonstrate a positive attitude toward information technology by Australian nurses but identify issues that must be addressed to support continued interest and engagement.     

Validating impaired physical mobility.

The clinical presence of impaired physical mobility documented for acute-care patients was studied. The frequency, individual, and group sensitivity levels of the defining characteristics documented as empirical referents for the diagnosis were examined. The frequency of the related factors associated with the diagnosis, patient demographics, length of stay (LOS), discharge destination, and diagnostic-related groups (DRGs) were also examined. Data were obtained from electronic tapes of patient information. Support was found for impaired mobility, as a high-frequency diagnosis, in heterogeneous acute-care patients. No support was found for any major defining characteristics across the heterogeneous sample. A cluster of three defining characteristics: (a) inability to purposefully move within the environment; (b) decreased muscle strength, control, or mass; and (c) imposed restrictions of movement was supported by group sensitivity measures. Major defining characteristics were supported in two DRG subsets. Clusters of defining characteristics varied among four DRGs. The NANDA-preidentified related factors were associated with the diagnosis. Electronic storage and retrieval of computerized nursing data, including the elements of the Nursing Minimum Data Set (NMDS), was an effective, efficient method for data collection and analysis.     

Exploring the nursing minimum data set for The Netherlands using multidimensional scaling techniques

RATIONALE: To fulfil the need for a systematic collection of nursing data that give insight in nursing care and its benefits and costs, a nursing minimum data set (NMDS) has been developed and validated for Dutch general hospitals. A NMDS provides data describing the diversity in patient populations and variability in nursing activities that can be analysed in various ways. AIM OF THE STUDY: To explore and compare the fundamental underlying dimensions describing patient problems and nursing interventions in Dutch general hospital wards. METHODS: Data of predominantly nominal and ordinal measurement level that were collected with the NMDS for The Netherlands on 15 Dutch hospital wards underwent two consecutive steps: first, they were transformed into metric data by means of RIDIT (relative to an identified distribution) analysis; secondly, they were analysed by means of multidimensional scaling. RESULTS: Multidimensional scaling techniques yielded a fairly good three-dimensional solution of the NMDS data. Hospital wards could be distinguished from each other on the basis of patient problems and nursing interventions most common on some wards but not on others. The core aspects underlying patient problems concerned dependency problems, life threatening problems and endogenous-exogenous problems, while discriminating nursing interventions were cure-care activities, internally-externally oriented activities and psychosocial-physical interventions. LIMITATIONS: Not all types of hospital wards were represented, which limits the representativeness of the results for Dutch general hospitals. Furthermore, the patient sample size over the 15 wards was relatively small. CONCLUSION: The constructs are consistent with NMDS findings in Belgium and findings from practice, which contributes to their content validity.     

Benchmarking nurse staffing levels: the development of a nationwide feedback tool

Title. Benchmarking nurse staffing levels: the development of a nationwide feedback tool. Aim. This paper is a report of a study to develop a methodology that corrects nurse staffing for nursing care intensity in a way that allows nationwide benchmarking of nurse staffing data. Background. Although nurse workload measurement systems are recognized to be informative in nurse staffing decisions, they are rarely used. When these systems are used, however, it is only possible to compare units within hospitals, because currently available instruments are not standardized for comparisons beyond hospital boundaries. The Belgian Nursing Minimum Dataset (B‐NMDS) contains uniformly measured data about the intensity of nursing care and nurse staffing levels for all hospitals in Belgium. Method. We conducted a retrospective multilevel analysis of the B‐NMDS for the year 2003. The sample included 690,258 inpatient days for 298,691 patients, recorded from 1637 acute care nursing units in 115 hospitals. We corrected the number of nursing staff by using different covariates available in the B‐NMDS: intensity of nursing care, type of day (week vs. weekend), service type (general vs. intensive) and hospital type (academic vs. general). Findings. The multilevel approach allowed us to explain about 70% of the variability in the number of nursing staff per nursing unit using hospital type (P = 0·0053); intensity of nursing care (P < 0·0001) and service type (P < 0·0001) as the only covariates. Conclusion. The feedback tool we developed can inform nurse managers and policymakers about nursing intensity‐adjusted nurse staffing levels according to different benchmarks. Our study demonstrates that investing in large nursing datasets is appropriate for the international nursing community.