Manual of Critical Care Nursing - Elsevieron VitalSource: Nursing Interventions and Collaborative Ma
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I am in my last block of my BSN program. This has been a lifesaver for critical care assignments. Great supplement for the drug guide. I'm in Critical Care Nursing student and this book was one of our textbooks. It's very small with very small print. It's written for someone who needs a refresher, not a student. Unless you are a critical care nurse already and want a reference manual to have on the floor, don't bother with this book.
Informative, concise, no excessive unimportant information, just the critical care facts! Handy portable size, really helpful to take along during clinical. I rented this for the semester, but would consider purchasing this just to have as reference. One person found this helpful. This book is perfect!!! Simple, clear, and easy to use Packed with information needed to treat patients with certain conditions but not all conditions are referenced. I did not like this book.
I had to have it for school but its hard to read. The book is small and paperback and the reading is hard to read compared to another book I had. It goes on and on. See all 41 reviews. Most recent customer reviews. Published 1 year ago. Published on May 29, Published on March 4, Published on February 17, Published on September 15, Published on June 20, Only downfall encountered so far is it Published on May 4, Published on April 2, Pages with related products. See and discover other items: There's a problem loading this menu right now.
Get fast, free shipping with Amazon Prime. Your recently viewed items and featured recommendations. View or edit your browsing history. The Australian and New Zealand context Chapter 2: Contemporary Australian and New Zealand midwifery and maternity services Chapter 3: Human rights in childbirth Chapter 4: Fear and risk Chapter 5: Midwifery as primary health Chapter 6: Birth place and birth space Chapter 7: Social and environmental determinations of women's health Chapter 9: Midwives and Maori women: Professional frameworks for practice in Australia and New Zealand Chapter Legal frameworks for practice in Australia and New Zealand Chapter Supporting midwives, supporting each other Chapter Midwifery partnership Chapter Working in collaboration Chapter Overview of reproductive physiology Chapter Nutrition and physical activity foundations for pregnancy, childbirth and lactation Chapter Screening and assessment Chapter Working with women in pregnancy Chapter In the end, if outcomes information is available only for the hospital as a whole which is the case in discharge abstracts, for instance , data linkage can happen only at the hospital level, even if staffing data were available for each unit in a facility.
Similarly, if staffing data are available only as yearly averages, linkage can be done only on an annual basis, even if outcomes data are available daily or weekly. Linkages can be done only at the broadest levels on the least-detailed basis or at the highest level of the organization available in a dataset. Many patient outcomes measures such as potentially preventable mortality may actually be more meaningful if studied at the hospital level, while others such as falls may be appropriately examined at the unit level.
One should recognize that common mismatches between the precision of staffing measures and the precision of outcome measures i. This finding is particularly relevant when staffing statistics span a long time frame and therefore contain a great deal of noise—information about times other than the ones during which particular patients were being treated.
High-quality staffing data, as well as patient assessment and intervention data—all of which are accurately date-stamped and available for many patients, units, and hospitals—will be necessary to overcome these linkage problems. Such advances may come in the next decades with increased automation of staffing functions and the evolution of the electronic medical record. Recent prospective unit-level analyses, now possible with datasets developed and maintained by the NDNQI, CalNOC, and the military hospital systems, make it possible to overcome some of these issues.
These databases, although not risk adjusted, stratify data by unit type and hospital size and have adopted standardized measures of nurse staffing and quality of care. The resulting datasets provide opportunities to study how variations in unit-level staffing characteristics over time can influence patient outcomes for instance, pressure ulcers and falls, as discussed later.
As data sources do not exist for all types of staffing and outcomes measures at all levels of hospital organization nor will they ever , research at both the unit level and the hospital level will continue, and both types of studies have the potential to inform understanding of the staffing-outcomes relationship. Perhaps staffing and outcomes research has such importance and relevance for clinicians and educators as well as for managers and policymakers, staffing-outcomes research is a frequently reviewed area of literature. As was just detailed, a diversity of study designs, data sources, and operational definitions of the key variables is characteristic of this literature, which makes synthesis of results challenging.
Many judgments must be made about which studies are comparable, which findings if any contribute significantly to a conclusion about what this literature says, and perhaps regarding how to transform similar measures collected differently so they can be read side by side.
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The review of evidence here builds on a series of recent systematic reviews with well-defined search criteria. These findings have appeared in studies conducted using a variety of designs and examining hospital care in different geographical areas and over different time periods. The evidence table summarizes four major systematic reviews of the literature, approaches, and conclusions regarding the state of the evidence for specific outcomes or outcome types. In these papers, reviewers identify specific measurement types and established criteria for study inclusion in terms of design and reporting and examined a relatively complete group of the studies one by one to provide an overview of the state of findings as an integrated whole.
The contrasts in the conclusions are interesting but are probably less important than the overall trend: An additional important point is that nearly all studies connecting staffing parameters with outcomes have been conducted at the hospital rather than the unit level. In a 2-year AHRQ Working Conditions and Patient Safety study built on the work of CalNOC, Donaldson and colleagues 17 engaged acute care hospitals using ANA nursing indicators for reporting staffing, patient safety, and quality indicators in a research, repository development, and benchmarking project.
Data were drawn from 25 acute care, not-for-profit California hospital participants in the regional CalNOC. The sample included urban and rural hospitals with an average daily census from to more than patients. The aims of the study were to test associations between daily nurse staffing on adult medical-surgical units and hospital-acquired pressure ulcers, patient falls, and other significant adverse events, if they were of sufficient volume to analyze. A prospective, descriptive, correlational design tested associations between patient outcome measures and daily unit-level nurse staffing, skill mix, hours of care along with hours covered by supplemental agency staff , and workload.
Unit activity index and hospital complexity measured by bed size were also significant predictors of falls. In another analysis, Donaldson and colleagues 39 traced daily, unit-level direct care nurse staffing in 77 units across 25 hospitals over a 2-month period using data on staffing effectiveness the match between hours of care and hours provided. By law in California, each hospital unit uses an institutionally selected, acuity-based workload measurement system to determine required hours of care for each patient.
For each patient-care unit, the ratio of actual to required hours of care, was expressed as both a mean ratio and as a percentage of days on which required hours exceeded actual hours over the 7 days prior to a pressure ulcer prevalence study. These analyses linked unit-level staffing and safety-related outcomes data, and measured for time periods at the unit level closely and logically connected staffing measures relevant to conditions before the outcome occurred.
Both researchers and research consumers need to reflect on the time frames involved in the evolution of various outcomes when assessing the validity of data linkages across time and units. For instance, in contrast to the lags between quality problems in care and evidence of their impact on outcomes such as infections and pressure ulcers, practice conditions will tend to have more immediately observable impacts on outcomes like falls with injury and most adverse drug reactions. Recent legislation in California that introduced mandated nurse-to-patient ratios at the unit level provides an interesting context for studying the association of staffing and outcomes.
CalNOC has reported early comparisons of staffing and outcomes in medical-surgical and step-down units in 68 California hospitals during two 6-month intervals Q1 and Q2 of and Q1 and Q2 of before and after introduction of the ratios. Data were stratified by hospital size and unit type. On medical-surgical units, mean total RN hours per patient day increased by However, there were no statistically significant changes in the rate of patient falls or pressure ulcers on these units.
Researchers have generally found that lower staffing levels are associated with heightened risks of poor patient outcomes. Staffing levels, particularly those related to nurse workload, also appear related to occupational health issues like back injuries and needlestick injuries and psychological states and experiences like burnout that may represent precursors for nurse turnover from specific jobs as well as the profession. Associations are not identified every time they are expected in this area of research. Other aspects of hospital working conditions beyond staffing, as well individual nurse and patient characteristics, affect outcomes since negative outcomes are relatively uncommon even at the extremes of staffing and do not occur in every circumstance where staffing is low.
A critical mass of studies established that nurse staffing is one of a number of variables worthy of attention in safety practice and research. There is little question that staffing influences at least some patient outcomes under at least some circumstances. Future research will clarify more subtle issues, such as the preferred methods for measuring staffing and the precise mechanisms through which the staffing-outcomes relationship operates in practice. Nurse executives and frontline managers make decisions about numbers of staff to assign to the various areas of their facilities.
They also establish models of care to be used in caring for patients in terms of the constellation of nursing staff and distribution of responsibilities among professional nurses and other types of nursing staff.
Manual of Critical Care Nursing: Nursing Interventions and Collaborative Management Manual of Critical Care Nursing - Elsevier eBook on VitalSource ( Retail. The compact, yet comprehensive, Manual of Critical Care Nursing: Nursing Interventions and Collaborative Management, 7th Edition is your students'a go-to .
Policymakers want assurances that the nursing workforce in their jurisdictions is adequate; they also want to know whether or not regulatory intervention is necessary to ensure acceptable staffing levels and desirable patient outcomes. Staffing researchers are ultimately constrained by the limitations of their data in answering many questions of relevance to the real worlds of health care delivery and public policy.
Investigators most commonly examined the correlations of complex patient outcomes with staffing measures derived at some distance from the delivery of care perhaps aggregated over time. Researchers then asked whether measures of staffing and outcomes were statistically associated with each other. A clear distinction between direct conclusions from research findings and the opinions of particular authors or interest groups must be made.
It is impossible to specify parameters for staffing that will ensure safety based on current evidence without many qualifiers. The adequacy of staffing the degree to which staffing covers patient needs even for the same patients and nurses may change from hour to hour, particularly in acute care settings. Nurse-to-patient ratios and skill mixes in specific settings that are too low for safety still cannot be identified on the basis of the research literature, but decisions must be made on the basis of the judgments by frontline staff and their managers. On a related note, the specific nursing care processes that are more likely to be omitted or rendered less safe under different staffing conditions are not well understood, empirically speaking, and deserve further attention.
A number of other areas identified in the staffing literature are relatively underdeveloped. Most research on staffing has been conducted in acute care settings; however, not all clinical areas within acute care have been equally well studied. Data regarding settings for the care of children, childbearing families, and patients with mental health problems are currently very thin.
The majority of nurses working in hospitals in the United States are, of course, registered nurses. Available evidence suggested that patients in hospitals that use more licensed practical nurses LPNs or vocational nurses may see worse outcomes. There is no direct evidence that it is unsafe to employ LPNs in acute care settings, 42 , 43 nor is there empirical support that the use of unlicensed personnel is intrinsically related to poor outcomes. Use of practical nurses and UAPs can be driven by any and all of the factors outlined in Figure 2. The models of care under which LPNs and unlicensed care providers are employed i.
While RNs have the broadest scope of practice of frontline nursing workers, it is far from established that percent RN staffing is effective in all situations. Until then and even when it does , local labor market realities, experience, and judgment will need to be used by leaders to establish skill mix and to define the models of care under which RNs, LPNs, and UAPs work.
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Early studies have offered early, tantalizing insights regarding a number of variables conceptually close to staffing. These findings include the educational preparation of RN staff in hospitals. Two recent studies 44 , 45 found that mortality in surgical and medical patients was lower in hospitals where higher proportions of staff nurses held baccalaureate degrees. Additionally, in this latter work, units where higher percentages of RNs held specialty certification had lower proportions of restrained patients.
Should these findings be borne out in future studies, there are important potential local and national policy implications. There is a clear need for more research. Similarly, while many feel experience and specialty training have logical associations with quality of care and patient safety, empirical data regarding their impact are very limited at present. Yet another area where data related to patient outcomes are thin relates to the impact of specific types of work environments on nurse-sensitive outcomes, and in particular the impact of the Magnet hospital model, which has been argued to produce superior patient outcomes and safer care.
To our knowledge, there are no studies yet to directly support a connection between safety and specific managerial approaches or to link Magnet status with patient outcomes in the current era of certification. However, early findings with respect to questions around the outcomes of the program are expected in the coming years.
There has been intense interest in identifying staffing-outcomes relationships in long-term care settings. RNs are, of course, in the minority among the nursing staff in long-term care, with unlicensed providers providing the bulk of physical care in these facilities. There are many challenges in using existing documentation and databases to measure outcomes in long-term care facilities, 48 some of which are shared with outcomes measurement in acute care.
Long-term care researchers face special issues, specifically with respect to data reliability and measure stability, skewedness of measures, and selection and ascertainment bias where types of patients at high risk for poor outcomes or who are more closely observed are concentrated in certain nursing homes. Despite these problems, a critical mass of studies suggests that long-term care facilities with the lowest licensed and unlicensed staffing levels among their peers show disproportionately worse patient outcomes.
A study sponsored by the Centers for Medicare and Medicaid Services CMS suggested that among short-stay patients, skilled nursing facilities with the lowest staffing levels were 30 percent more likely to fall in the worst 10 percent of facilities for transfers to acute care for acute heart failure, electrolyte imbalances, sepsis, respiratory infection, and urinary tract infection. Facilities with staffing below thresholds of 2.
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In 1, residents of 82 long-term care facilities, patients in facilities with more direct RN time 30—40 minutes per patient day and more had fewer pressure ulcers, acute care hospitalizations, urinary tract infections, and urinary catheters, and less deterioration in ability to perform activities of daily living. These researchers suggested that administrative practices other than staffing may play an important role in determining long-term care quality. Home health is a growing sector in U. Staffing models fall somewhere between acute care hospitals and long-term care in terms of the proportions of unlicensed personnel and practical nurses.
Allocation of nursing time to patients presumably influences quality and thoroughness of nursing acts and assessments. There may be skill-mix issues as well. However, to date there have been no studies of home health agency staffing models, nurse workloads, or skill mix. OASIS Outcomes Assessment and Information Set data gathered by home health providers by mandate from the Medicare program, skillfully analyzed and interpreted, will offer opportunities to examine safety in home care in relation to staffing decisions.
The general conclusion of these studies conducted in various settings is that differences in outcomes are often observed between situations or institutions where staffing is high and those where it is low. A critical mass of data suggests that staffing at the lower end of the continuum may place patients and nurses at heightened risk of poor outcomes.
Therefore, it appears hazardous to patients and staff to staff at the lowest levels relative to peer units and health care organizations. Limitations of cross-sectional observational designs that predominate in this literature have been reviewed extensively in the chapter. Prominent among these is that there is no guarantee that increasing staffing alone improves the process or outcomes of care. Nonetheless, it would appear wise to continue the widespread practice of adjusting staffing levels for setting, specialty, model of care, client needs, special circumstances, and trends in the frequency of outcomes potentially sensitive to nurse staffing.
A key implication arising from this review is that as much as possible, investigators should align their studies with emerging taxonomies and specifications of measures promulgated by authoritative sources e. Continued proliferation of measures is slowing progress in this field.
Standardized measurement will advance meta-analytic efforts and facilitate aggregation of data across studies. As hospitals and health systems are inundated with data-reporting demands, wise investigators will leverage ongoing measurement efforts by selecting core measures and common metrics already collected by hospitals. There is value for researchers to forge strategic partnerships with professional sponsors of public and private data repositories. Agencies and researchers alike will be served well by study designs that use already de-identified data and make minimal use of protected health information, particularly since the Health Insurance Portability and Accountability Act took effect in Likewise, both researchers and clinical administrators must fully harness the potential of new health information systems to capture clinical data.
Some authors suggested that competing on the analytics is a characteristic of high-performing organizations. Leaders at all levels in the health care system must decide how to apply the findings of this literature. It is impossible to read and discuss this area of research without considering whether regulation of nurse staffing is a valid application of the findings, especially in the current climate in health care.
As in all aspects of health care management, empirical evidence needs to be interpreted in the context of local data and experience. Even absent any specific legal mandates to do so, benchmarking staffing and outcomes against peers and attempting to avoid extremes of low staffing and high adverse events, keeping in mind important contextual factors when making comparisons, is undoubtedly the best administrative practice.
Executives and managers make a host of decisions beyond those involving staffing that affect the clinical effectiveness of nursing staff. Thought leaders in the arena of patient safety practices have identified a number of organizational strategies that may constitute better practice in managing the impact of nurse staffing on patient care quality and safety. For example, efforts to optimize clinical, throughput flow and reduce practice variability may reduce threats to staff and patients due to system and personnel overload. Engaging staff in self-governance related to patient flow has also been cited as a promising best practice.
Considered key to safe staffing, professional judgment as the gold standard establishes the threshold for safe patient care in a given clinical setting, 59 as nurses use a systematic decision matrix to determine if the staff on a particular unit can accept responsibility for additional patients. Informed by understanding of scientific conclusions linking staffing and patient outcomes in comparable settings, the self-governing and administrative teams of the future may use internally generated data to support decisions related to staffing adequacy and effectiveness.
As clinicians and administrators in clinical settings gain greater access to real-time data that enable them to explore links between structure, process, and outcomes, increasingly sophisticated tools such as virtual dashboards are promising. There are a great many questions in this field that are still unanswered.