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Major Methodological Considerations in This Literature Staffing Staffing levels can be reported or calculated for an entire health care organization or for an operational level within an organization a specific unit, department, or division. Specific time frames at the shift level and as a daily, weekly, or yearly average must be identified to ensure common meaning among collectors of the data, those analyzing it, and individuals attempting to interpret results of analyses.
In many cases, staffing measures are calculated for entire hospitals over a 1-year period. It is fairly common to average or aggregate staffing across all shifts, for instance, or across all day shifts in a month, quarter, or year and sometimes also across all the units of hospitals.
However, staffing levels on different units reflect differences in patient populations and illness severity the most striking of which are seen between general care and critical care units. Furthermore, in practice, staffing is managed on a unit-by-unit, day-by-day, and shift-by-shift basis, with budgeting obviously done on a longer time horizon.
For these reasons, some researchers argue that at least some research should be conducted where staffing is measured on a shift-specific and unit-specific basis instead of on a yearly, hospitalwide basis.
A distinct, but growing, group of studies examined staffing conditions in subunits or microsystems of organizations such as nursing units within hospitals over shorter periods of time for example, monthly or quarterly.
The first type divides a volume of nurses or nursing services by a quantity of patient care services. Common examples include patient-to-nurse ratios, hours of nursing care delivered by various subtypes of personnel per patient day HPPDand full-time equivalent FTE positions worked in relation to average patient census ADC over a particular time period.
Commonly, the composition of the nursing staff employed on a unit or in a hospital in terms of unlicensed personnel, practical or vocational nurses, and registered nurses RNs is calculated. The specific types of educational preparation held by RNs baccalaureate degrees versus associate degrees and diplomas have also begun to be studied.
Additional staffing-related characteristics studied include years of experience and professional certification. The incidence of voluntary turnover and the extent to which contract or agency staff provide care have also been studied. As will be discussed, the majority of the evidence related to hospital nurse staffing focuses on RNs rather than other types of personnel.
For the most common measures, ratios and skill-mix, determining which staff members should be included in the calculations is important, given the diversity of staffing models in hospitals. Most researchers feel these statistics should reflect personnel who deliver direct care relevant to the patient outcomes studied.
Whether or not to count charge nurses, nurse educators involved in bedside care, and nurses not assigned a patient load but who nevertheless deliver important clinical services can present problems, if not in principle, then in the reality of data that institutions actually collect.
Outcomes research examining the use of advanced practice nurses in acute care—for instance, nurse practitioners and nurse anesthetists—to provide types of care traditionally delivered by medical staff and medical trainees has been done in a different tradition analyzing the experiences of individual patients cared for by specific providers and does not tend to focus on outcomes relevant to staff nurse practice; therefore these studies are not reviewed here.
No studies were found that examined advanced practice nurse-to-patient ratios or skill mix in predicting acute care patient outcomes. There have been calls to examine advanced practice nurses supporting frontline nurses in resource roles for instance, clinical nurse specialists who consult and assist in daily nursing care, staff development, and quality assurance and their potential impact on patient outcomes.
No empirical evidence of this type was found. Outcomes Clearly, capturing data about patient outcomes prospectively i. This approach is the most challenging because of practical, ethical, and financial considerations.
However, researchers can sometimes capitalize on prospective data collections already in progress.
For instance, hospital-associated pressure ulcer prevalence surveys and patient falls incidence are commonly collected as part of standard patient care quality and safety activities at the level of individual nursing units in many institutions. Patients are not all at equal risk of experiencing negative outcomes.
Elderly, chronically ill, and physiologically unstable patients, as well as those undergoing lengthy or complex treatment, are at much greater risk of experiencing various types of adverse events in care.
For instance, data on falls may be consistently collected for all hospitalized patients but may not be particularly meaningful for obstetrical patients. Accurately interpreting differences in rates across health care settings or over time requires understanding the baseline risks patients have for various negative outcomes that are beyond the control of the health care providers.
Ultimately this understanding is incorporated into research and evaluation efforts through risk adjustment methods, usually in two phases: Without sound risk adjustment, any associations between staffing and outcomes may be spurious; what may appear to be favorable or unfavorable rates of outcomes in different institutions may no longer seem so once the complexity or frailty of the patients being treated is considered.
However, as was noted earlier, quality of care and clinical outcomes and by extension, the larger domain of nursing-sensitive outcomes include not only processes and outcomes related to avoiding negative health states, but also a broad category of positive impacts of sound nursing care.
Knowledge about positive outcomes of care that are less likely to occur under low staffing conditions or are more likely under higher levels is extremely limited.
The findings linking functional status, psychosocial adaptation to illness, and self-care capacities in acute care patients are at a very early stage 37 but eventually will become an important part of this literature and the business case for investments in nurse staffing and care environments.
Linkage In staffing-outcomes studies, researchers must match information from data sources about the conditions under which patients were cared for with clinical outcomes data on a patient-by-patient basis or in the form of an event rate for an organization or organizational subunit during a specific period of time.
Ideally, errors or omissions in care would be observed and accurately tracked to a particular unit on a particular shift for which staffing data were also available. Most, but not all, large-scale studies have been hospital-level analyses of staffing and outcomes on an annual basis and have used large public data sources.
Linkages of staffing with outcomes data involve both a temporal time component and a departmental or unit component. These include some types of complications as well as patient deaths. Attribution of outcomes is complicated by the reality that patients are often exposed to more than one area of a hospital.
For instance, they are sometimes initially treated in the emergency department, undergo surgery, and either experience postanesthesia care on a specialized unit or stay in an intensive care unit before receiving care on a general unit.
Unfortunately, in hospital-level datasets, it is impossible to pinpoint the times and locations of the errors or omissions most responsible for a clinical endpoint.The importance of nurse staffing to the delivery of high-quality patient care was a principal finding in the landmark report of the Institute of Medicine’s (IOM) Committee on the Adequacy of Nurse Staffing in Hospitals and Nursing Homes: “Nursing is a critical factor in determining the quality of care in hospitals and the nature of patient outcomes” 1 (p.
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Does do not assess the full extent of the patient experience.