Carolyn E. Aydin

Impact of California’s Licensed Nurse-Patient Ratios on Unit-Level Nurse Staffing and Patient Outcomes

This article presents the first analysis of the impact of mandated minimum-staffing ratios on nursing hours of care and skill mix in adult medical and surgical and definitive-observation units in a convenience sample of 68 acute hospitals participating in the California Nursing Outcomes Coalition project. Findings, stratified by unit type and hospital size, reveal expected changes as hospitals made observable efforts toward regulatory compliance. These data cannot affirm compliance with ratios per shift, per unit, at all times; however, they give evidence of overall compliance. Assessment of the impacts of the mandated ratios on two common indicators of patient care quality, the incidence of patient falls and the prevalence of pressure ulcers, did not reveal significant changes despite research linking nurse staffing with these measures. These findings contribute to understanding unit level impacts of regulatory staffing mandates and the preliminary effect of this legislation on core quality of care indicators.

Mandated Nurse Staffing Ratios in California: A Comparison of Staffing and Nursing-Sensitive Outcomes Pre- and Postregulation:

This article examines the impact of mandated nursing ratios in California on key measures of nursing quality among adults in acute care hospitals. This study is a follow-up and extension of our first analysis exploring nurse staffing and nursing-sensitive outcomes comparing 2002 pre-ratios regulation data to 2004 postratios regulation data. For the current study we used postregulation ratios data from 2004 and 2006 to assess trends in staffing and outcomes. Findings for nurse staffing affirmed the trends noted in 2005 and indicated that changes in nurse staffing were consistent with expected increases in the proportion of licensed staff per patient. This report includes an exploratory examination of the relationship between staffing and nursing-sensitive patient outcomes. However anticipated improvements in nursing-sensitive patient outcomes were not observed. This report contributes to the growing understanding of the impacts of regulatory staffing mandates on hospital operations and patient outcomes.

Nursing Documentation Time During Implementation of an Electronic Medical Record

Objective To determine, within the context of all nursing duties, the amount of time nurses spend on documentation during the implementation of an electronic medical record (EMR) on an intrapartum unit. Background Increased documentation needs during EMR implementation may necessitate increased staffing requirements in an already labor-intensive and demanding environment. Methods A work-sampling study was conducted over a 14-day study period, and 18 of 84 (21%) potential 4-hour observation periods were selected. During each period, a single observer made 120 observations and, on locating a specific nurse, immediately recorded that nurse’s activity on a standardized and validated instrument. Categories of nursing activities included documentation, bedside care, bedside supportive care, nonbedside care, and nonpatient care. Results A total of 2160 observations were made. The total percentage of nursing time spent for documentation was 15.8%, 10.6% on paper and 5.2% on the computer. The percentage of time spent on documentation was independently associated with day versus night shifts (19.2% vs 12.4%, respectively). Conclusions Despite charting concurrently on both paper and computer, the amount of time spent on documentation was not excessive, and was consistent with previous studies in which neither electronic nor “double charting” occurred.

Evaluating the Impact of Health Care Information Systems

Evaluating the impact of computer-based medical information systems requires not only an understanding of computer technology but also an understanding of complex social and behavioral processes. This essay discusses the need for evaluation of health care information systems, a set of evaluation questions based on assumptions about the impact of technology on organizations, and recommendations for reducing barriers to the implementation of health care information systems.

Social worlds, individual differences, and implementation: predicting attitudes toward a medical information system

Abstract Implementation research has identified a wide variety of factors, such as individual differences, implementation practices, and system usage, that influence the success or failure of information systems. The present research proposes that, especially in health care organizations, both occupational and departmental social worlds are additional, important predictors of individual reactions to medical information systems. Quantitative and qualitative methods were used to investigate the two-year process of implementing a computerized medical records information system in one health care organization. Results support the importance of social worlds, as well as some of the traditional implementation influences (but not individual differences such as cognitive style, prior computer experience, age) in understanding individual attitudes toward the computer system. The study also highlights current implementation issues and their implications for system planners and managers. The research adds to our understanding of the complexity of attitudes toward technological innovations, and the importance of membership in social worlds in influencing those attitudes.

How Many Nurses per Patient? Measurements of Nurse Staffing in Health Services Research

OBJECTIVE To compare alternative measures of nurse staffing and assess the relative strengths and limitations of each measure. DATA SOURCES/STUDY SETTING Primary and secondary data from 2000 and 2002 on hospital nurse staffing from the American Hospital Association, California Office of Statewide Health Planning and Development, California Nursing Outcomes Coalition, and the California Workforce Initiative Survey. STUDY DESIGN Hospital-level and unit-level data were compared using summary statistics, t-tests, and correlations. DATA COLLECTION/EXTRACTION METHODS Data sources were matched for each hospital. When possible, hospital units or types of units were matched within each hospital. Productive nursing hours and direct patient care hours were converted to full-time equivalent employment and to nurse-to-patient ratios to compare nurse staffing as measured by different surveys. PRINCIPAL FINDINGS The greatest differences in staffing measurement arise when unit-level data are compared with hospital-level aggregated data reported in large administrative databases. There is greater dispersion in the data obtained from publicly available, administrative data sources than in unit-level data; however, the unit-level data sources are limited to a select set of hospitals and are not available to many researchers. CONCLUSIONS Unit-level data collection may be more precise. Differences between databases may account for differences in research findings.

Evaluating the organizational impact of healthcare information systems

Evaluating Healthcare Information Systems: A Multimethod Approach.- Overview: Theoretical Perspectives and Methodologies for the Evaluation of Healthcare Information Systems.- Qualitative Research Methods for Evaluating Computer Information Systems.- Multiple Perspectives: Evaluating Healthcare Information Systems in Collaborative Environments.- Survey Methods for Assessing Social Impacts of Computers in Healthcare Organizations.- Using the Internet for Surveys and Research.- Cognitive Approaches to the Evaluation of Healthcare Information Systems.- Work-Sampling: A Statistical Approach to Evaluation of the Effect of Computers on Work Patterns in Health Care.- Evaluation in Health Informatics: Social Network Analysis.- Evaluation in Health Informatics: Computer Simulation.- Evaluating Healthcare Information Systems: Applications.- Computers in the Consulting Room: A Case Study of Clinician and Patient Perspectives.- Introducing Physician Order Entry at a Major Academic Medical Center: Impact on Organizational Culture and Behavior.- Introducing Physician Order Entry at a Major Academic Medical Center: Impact on Medical Education.- Evaluating the Capability of Information Technology to Prevent Adverse Drug Events: A Computer Simulation Approach.- Implementing Computers in Ambulatory Care: Implications of Physician Practice Patterns for System Design.- Nursing Documentation Time During Implementation of an Electronic Medical Record.- Computer Charting: An Evaluation of a Respiratory Care Computer System.- Research and Evaluation: Future Directions.

Leveraging nurse-related dashboard benchmarks to expedite performance improvement and document excellence

Using nursing quality benchmarks in operational dashboards and translating those data to drive performance excellence is a strategic imperative. Since access to unit-level, hospital-generated nurse-related benchmarks is an emerging arena, the authors provide an overview of aggregated trends and benchmarks gleaned from the California Nursing Outcome Coalition acute care database for 2 established nurse-related quality indicators—patient falls incidence and hospital-acquired pressure ulcer prevalence. Integrating these acute care benchmarks into clinical dashboards can be invaluable to clinicians, administrators, and policy makers who share a common commitment to expediting evidence-based improvement in patient care safety, outcomes, and excellence.

Bringing social worlds together: computers as catalysts for new interactions in health care organizations.

In this case study, computer systems are explored as catalysts for new interactions between departments in health care organizations. Hypotheses investigated changes in the extent to which members of different departments (1) exchange information and (2) understand each others work following implementation of an integrated medical information system. Analyses showed that communication-based forms of involvement in implementation (communicating with systems personnel and trainers, communicating about new ways to use the system, and receiving support from supervisors for doing so) were overwhelmingly more important than either general participation or computer use in predicting increases in interdepartmental interaction. Changes in tasks and roles also led to new, informal, face-to-face contacts to support computer system use, as well as greater administrative control over the organization as a whole. In addition, results of interviews and observations over the two-year study period illustrate the importance of work group identification in predicting changes accompanying computerization.

Nurse staffing and patient perceptions of nursing care.

Objective To examine the relationship between nurse staffing and patient perceptions of nursing care in a convenience sample of 40 California hospitals. Background Growing concern about the adequacy of nurse staffing has led to an increased emphasis on research exploring the relationships between nurse staffing and patient outcomes. Patient satisfaction with nursing care is one of the 21 indicators identified by the American Nurses Association as having a strong “theoretical link to the availability and quality of professional nursing services in hospital settings.” This prospective study examined the relationship between nurse staffing and patient perceptions of nursing care in multiple hospitals using common definitions of both nurse staffing and patient perceptions of care. Methods Nurse staffing (structural variables) and patient perceptions of nursing care (outcome variables) from hospitals participating in both the ongoing California Nursing Outcomes Coalition statewide database project and the statewide Patients’ Evaluation of Performance in California project, with data available on both measures for the same time periods, were examined. Analytic methods included both descriptive and inferential statistics. Results Hospitals with wide ranges of staffing levels showed similar results in patient perceptions of nursing care. Regression analysis revealed a statistically significant relationship between nursing hours per patient day, and 1 of the 6 dimensions of care measured (“respect for patient’s values, preferences, and expressed needs”). Conclusions Nurse staffing alone showed a significant but weak relationship to patient perceptions of their care, indicating that staffing is likely only one of several relevant variables influencing patient perceptions of their nursing care. This research contributes data to the body of knowledge regarding nurse staffing. It is essential that nurse executives integrate results from this and other studies in developing strategic and tactical staffing plans that yield positive patient care outcomes.