LR25 / Possible adverse patient outcomes and the nursing workforce

Romania




Type of Patient Safety Practice
Clinical Risk Management Practice (CRMP)
Related practices from PaSQ database
"Best fit" category of the reported practice
Human factors/System resillience
Patient safety theme the SCP/clinical risk management practice is aimed at
A CRM practice focused on the effects of hospital reengineering may had on adverse patient outcomes and the nursing workforce in New Zealand (NZ), in all NZ’s public Hospitals, from 1989 through 2000.
Objective of the CRM practice
The purpose of this study was to examine the relationship between NZ hospital reengineering and adverse patient outcome rates. The availability of comprehensive longitudinal administrative data on NZ nurses and hospital discharges offered a unique opportunity [1,2,8,9]. This study is the first to examine the effect hospital reengineering may have had on the quality of care and nursing workforce in NZ hospitals, the relationship between nursing and outcomes in the context of hospital reengineering, and the effect of reengineering on quality of care in hospitals in a country other than the United States[p.1140, 1].
Short description of the CRM practice, including any references for further information
The government of New Zealand (NZ) implemented policies aimed at making its public health care system more efficient, cost effective, and consumer-oriented. NZ health care reform was similar to the hospital “reengineering” that occurred in the United States during the 1990s. Because nursing represents a large portion of operating costs, reengineering efforts often are associated with reducing the number of nurses and collapsing nursing management structures [p.1140, 1]. New hospital management structures in NZ were held accountable for meeting organizational efficiency and financial performance targets. NZ reengineering reduced hospital nursing staffs and dismantled nursing leadership structures in hospitals. Control over nursing budgets was handed over to non-nursing managers, clinical areas lacked supplies and equipment, and many senior nurses were replaced by new graduates, leaving few mentors and clinical experts on hospital nursing units. The study’s purpose was to examine the effects hospital reengineering may have on adverse patient outcomes and the nursing workforce. The study was a retrospective, longitudinal analysis of administrative data. Relationships between adverse outcome rates and nursing workforce characteristics were examined using auto regression analysis. Measures included the frequency of 11 nurse sensitive patient outcomes, average length of stay, and mortality along with the number of nursing full time equivalents (FTEs), hours worked, and skill mix. All medical and surgical discharges from NZ’s public hospitals (n = 3.3 million inpatient discharges) from 1989 through 2000 and survey data from the corresponding nursing workforce (n = 65,221 nurse responses) from 1993 through 2000 were examined. The study provides insight into unintended consequences of health care reengineering and market approaches in health, showing that nurses are integral in the delivery of safe patient care and that tinkering with nursing FTEs and hours without a monitoring mechanism may lead to significant quality problems [p1140; p.1141; p1146, 1].
Innovator of the SCP, country of origin
Country of origin was New Zealand [p.1140, 1].
Involved health care staff
The nursing workforce, (65,221 inpatient and outpatient hospital nurses responses) from medical and surgical NZ’s public Hospitals, were analyzed [p.1140, 1].
Tested in which countries/health care systems, health care context(s) and/or clinical specialty/specialties, including references
Country: New Zealand. All public hospitals. All medical and surgical discharges from 1989 to 2000[p.1140, 1].
Summary of evidence for effectiveness, including references
After 1993, nursing FTEs and hours decreased 36% and skill mix increased 18%. Average length of stay decreased approximately 20%. Adverse clinical outcome rates increased substantially. Mortality decreased among medical patients and remained stable among surgical patients. The relationship between changes in nursing and adverse outcomes rates over time were consistently statistically significant. In the chaotic environment created in NZ by reengineering policy, patient care quality declined as nursing FTEs and hours decreased. The study provides insight into the role organizational change plays in patient outcomes, the unintended consequences of health care reengineering and market approaches in health care, and nursing’s unique contribution to quality of care [p1140,1]. Although it is widely recognized that a great deal of change in nurse staffing has occurred within the context of hospital reengineering, few well-designed studies have assessed the impact of reengineering on quality of care [1,2,8,9]. The findings from this study contribute to the continually growing body of evidence that nurses are integral in the delivery of safe patient care and that tinkering with nursing FTEs and hours without a monitoring mechanism may lead to significant quality problems [p.1146,1].
Summary of evidence for transferability (transferability across health care systems or health care contexts or clinical specialties), including references
These findings suggest that the introduction of NZ’s health care reengineering policies significantly influenced the frequency of adverse outcomes among hospitalized patients with the effect occurring at the same time the nursing workforce decreased in size The reengineering efforts focus hospital on cost control and efficiency and often lead to declines in patients’ lengths of stay and numbers of nurses. Managerialism is concerned with rational analysis of organizational inputs and outputs, routine efficiency, direct line management, and close supervision of personnel[5]. Thus, the new hospital management structures in NZ were held accountable for meeting organizational efficiency and financial performance targets. However, accountability for clinical outcomes was not a priority specified under the new structures, and few quality monitoring practices were in place in NZ hospitals before, during, or in the immediate aftermath of Reengineering[9]. The decline in ALOS after reengineering in NZ, can be explained by the implementation of a DRG-based budgeting system, designed to decrease the cost of care by decreasing lengths of stay. Declining ALOS increases the number of acute versus non acute patient days, which increases nursing workload as overall patient acuity increases. At the same time, the decline in the number of nurses increases the number of patients per nurse. Lower staffing levels caused by reengineering and the associated increased nursing workload can lead to hurried, delayed, omitted, fragmented, or erroneous care. Inadequate nurse staffing precipitates errors reduces opportunities to detect errors before they occur, and increases miscommunications between staff. The increased workload forces nurses to prioritize their interactions with patients, potentially causing them to omit important monitoring and clinical interventions that prevent adverse outcomes [p.1145, 1]. The study provides insight into unintended consequences of health care reengineering and market approaches in health care along with the importance of ongoing quality management during organizational change. Secondly, it highlights the value of using administrative datasets to identify potential systematic quality and safety problems within organizations particularly when other data are unavailable. Finally, it demonstrates that the current focus on patient safety and quality of care may be best addressed through an investment in nursing. [p.1146, 1].
Summary of available information on feasibility, including references
After health care reengineering began in 1993, medical and surgical nursing FTEs and nursing hours in NZ’s public hospitals decreased 36%. Although the skill mix rose from 74% to 93%, the increase was more than likely influenced by the nursing profession’s decision to phase out the EN role in hospitals rather than a conscious effort to employ a higher mix of RNs. [p.1144, 1]. The increased workload forces nurses to prioritize their interactions with patients, potentially causing them to omit important monitoring and clinical interventions that prevent adverse outcomes. Increases in adverse clinical outcomes and declines in mortality seem counterintuitive. First, work prioritization may have led nurses to concentrate on lifesaving interventions rather than focus on clinical surveillance activities aimed at averting adverse clinical outcomes. Second, the shorter inpatient lengths of stay may have shifted patient deaths to settings outside the hospital such as long term care or the patient’s home. Third, other lifesaving interventions such as new technology, medications, or other improvements in hospital procedures may have improved mortality rates from 1989 to 2000. Fourth, the aggregated analysis of yearly mortality rates for all NZ public hospitals may have smoothed the overall rate, failing to reflect what might be improvements in some facilities and concentrations of patient deaths in others. Two findings are inconsistent with those of other studies that analyzed nursing’s influence on patient outcomes. The first has to do with the number of outcomes found to be sensitive to nursing. The nurse sensitive outcomes analyzed in this study were developed and tested by Needleman in a cross-sectional study using U.S. hospital data. These investigators found 5 of the 11 associated with nurse staffing in medical and surgical populations while this longitudinal study found 3 were sensitive among medical patients and 8 were sensitive among surgical patients, suggesting more of the outcomes may be sensitive to nursing. The second inconsistent finding was that in this study adverse patient outcomes increased as skill mix increased whereas others have found adverse outcomes decreased when skill mix increased, suggesting that in nurse work environments characterized by heavy workloads, overextended or absent nursing leadership, and poor morale, quality of patient care may not necessarily benefit from a richer skill mix [7,9,10]. Although NZ’s databases of nurses and patient discharges offer unusually comprehensive and clean data for a large scale longitudinal study, there were still methodological limitations and interpretative problems attributable to both datasets that others conducting studies using administrative data have also identified. In the NMDS data, secondary diagnosis codes do not specify whether a diagnosis was present on admission so despite the algorithms intent to identify only hospital-acquired adverse outcomes, some diagnoses may have been present on admission. An increasing numbers of secondary diagnoses codes recorded with each discharge over time increase the likelihood that an adverse outcome may be identified. This limitation was addressed by counting only the discharges with outcome-qualifying ICD codes in the first 3 secondary diagnosis spaces of the discharge abstract. Methodological limitations with the nursing workforce data arose due to missing data and the inability to differentiate inpatient and outpatient hospital nurses. Others have developed models to account for the percentage of outpatient nurses in samples of inpatient and outpatient nurses. One group allocated staff based on inpatient to outpatient gross revenue. Another group found that method substantially underestimated inpatient staffing and developed their own model based on hospitals’ outpatient revenue share. Revenue data were not available for the NZ discharges. Several models were constructed to determine how the inclusion of outpatient nurses in the sample would influence results. The only scenario that affected the relationship between nursing and outcomes was one in which outpatient nurse staffing dramatically decreases over the study years while smoothing the year to year variation in inpatient nurse hours and FTEs. Therefore, eliminating an arbitrary number of outpatient nurses would only decrease the numbers of sample nurses, thereby strengthening what are already strong and statistically significant relationships. The decision to eliminate EN employment in hospitals also undoubtedly masks how much of the overall decline in the number of ENs was attributable to Reengineering [p1145; p1146,1].
Existing implementation tools, including references
All medical and surgical discharges from NZ’s public hospitals (n = 3.3 million inpatient discharges) from 1989 through2000 and survey data from the corresponding nursing workforce (n = 65,221 nurse responses) from 1993 through 2000 were examined. Measures: Measures included the frequency of 11 nurse sensitive patient outcomes, average length of stay, and mortality along with the number of nursing full time equivalents (FTEs), hours worked, and skill mix. [p.1140, 1].
Potential for/description of patient involvement in the CRM practice, including references
No direct patient involvement. Was a analysis of administrative data based on all medical and surgical discharges from NZ’s public hospitals [p.1140,1].
Bibliography (for each reference: author(s), year, title, journal/internet link, page(s))
[1] McCloskey, Barbara RN, DNSc; Diers, Donna RN, PhD, FAAN (November 2005): Effects of New Zealand’s Health Reengineering on Nursing and Patient Outcomes. Medical Care; Volume 43; Number 11. REFERENCES [2]. Leatt P, Baker GR, Halvorson PK, et al. Downsizing, reengineering, and restructuring: long-term implications for healthcare organizations. Frontiers of Health Services Manage. 1997;13:4 –37. [3]. Aiken LH, Clarke SP, Sloane DM. Hospital reengineering: does it adverse affect care and outcomes? J Nursing Admin. 2000;30:457– 465. [4]. Lichtig LK, Knauf RA, Milholland DK. Some impacts of nursing on acute care hospital outcomes. J Nursing Admin. 1999;29:25–33. [5]. Kovner C, Gergen PJ. Nurse staffing levels and adverse events following surgery in U.S. hospitals. Image. 1998;30:315–321. [6]. Sovie MD, Jawad AF. Hospital restructuring and its impact on outcomes: nursing staff regulations are premature. J Nursing Admin. 2001; 31:588–600. [7]. Needleman J, Buerhaus PI, Mattke S, et al. Nurse staffing and quality of care in inpatient units in acute care hospitals. Boston, MA: Health Resources Services Administration; Contract No. 230-99-0021, 2001. [8]. Blegan MA, Goode CJ, Reed L. Nurse staffing and patient outcomes. Nursing Res. 1998;47:43–50. [9]. Aiken LH, Clarke SP, Cheung, et al. Educational levels of hospital nurses and surgical patient mortality. JAMA. 2003;290:1617–1623. [10]. Iezzoni LI. Risk Adjustment for Measuring Health Care Outcomes. Chicago: Health Administrative Press; 2003:107–120.
Reviewer
Dr. Teodora Ciolompea,
National School of Public Health and Management, Romania
Organisation
National School of Public Health and Management
Any additional information on the CRM (e.g. implementation barriers and drivers)
Abreviations used in the original text: (FTE) - Full-time equivalent is a unit that indicates the workload of an employed person (or student) in a way that makes workloads comparable [1] across various contexts. FTE is often used to measure a worker's involvement in a project, or to track cost reductions in an organization. An FTE of 1.0 means that the person is equivalent to a full-time worker; while an FTE of 0.5 signals that the worker is only half-time. (RNs) -Registered nurses (ENs)- enrolled nurses (DVTs) - deep vein thromboses (PE) -pulmonary emboli pneumonia; (UGI) - upper gastrointestinal bleeding; (UTI)- urinary tract infection (ALOS)- average length of stay (ICD) -International Classification of Diseases (DRGs) -Diagnosis Related Groups (MDC)- Major Diagnostic Categories
Top
izmit escort
usak escort elazig escort
vidio bokep
antep escort escort bayan