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Record W3203549741 · doi:10.1097/nur.0000000000000638

Is Staffing Really the Problem?

2021· editorial· en· W3203549741 on OpenAlexaboutno aff
Janet S. Fulton

Bibliographic record

VenueClinical Nurse Specialist · 2021
Typeeditorial
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsnot available
Fundersnot available
KeywordsOfficerStaffingNursingWorkforceHealth careNurse AdministratorEmergency departmentPsychologyMedicinePolitical scienceMEDLINE

Abstract

fetched live from OpenAlex

“Nursing Is in Crisis: Staff Shortages Put Patients at Risk” was the title of an August 21, 2021 article in the New York Times.1 Citing rising hospital admissions, reporter Andrew Jacobs probed the impact of the COVID-19 Delta variant surge on nurse staffing in hospitals. An interesting and informative article, yet something about it has been gnawing on me. While the piece opened with a quote from a nurse likening the hospital’s emergency department to a war zone, the focus was on problems related to adequately staffing hospitals with nurses. In addition to the opening comment, nine additional persons were cited in the article but none were identified as nurses though four of them are or most likely are nurses including a professor with expertise in nursing workforce economics, a chief nursing officer, a person who “oversees nursing,” and a director at the American Nurses Association. Five additional persons cited were identified as hospital chief executive, a medical center’s top executive, a chief operating officer, a president of a nurse recruitment agency, and a professor and director of a healthcare workforce research center. A couple of thoughts about why this is gnawing on me. The only person identified as a nurse is the nurse working in the emergency department. Her engagement in clinical practice is clear; she does things for patients in the hospital and therefore fits the stereotype of nurses as doers. Nurses in non-clinical roles like professors, administrators, or leaders are somehow different and estranged from real nursing, which presumably consists only of nurses who are doers of clinical things. As currently designed, hospitals function because nurses staff them and COVID is making this abundantly clear. Because hospitals are staffed by nurses but not controlled by nurses, others in authority must be consulted as experts on nurse staffing. Nurses are a commodity to be managed by others. Nurses are expected to do things at the direction of others; nurses are not viewed as holding authority and autonomy over designing systems, identifying the priorities, managing outcomes, or controlling costs. During this pandemic, clinical nurse specialists and other advanced practice nurses stepped up and led at clinical and systems levels. At the 2021 National Association of Clinical Nurse Specialist annual conference, offered virtually, about 25% of the presentations dealt with clinical nurse specialist leadership in the design, implementation, and management of care models and system initiatives for accommodating demands created by patients with COVID. At the 2021 International Council of Nurses’ Advanced Practice Nursing Network Conference, offered virtually, the Canadian Centre for Advanced Practice Nursing Research presented preliminary findings from their work exploring the global impact of advanced practice nurses on health/health systems in response to the COVID pandemic. The researchers interviewed clinical nurse specialists and nurse practitioners from 36 countries representing North America, Latin America, Caribbean, Europe, Middle East, Africa, Asia, and Australia. The study findings reflected content similar to the clinical nurse specialists’ presentations. Globally, in this time of crisis, advanced practice nurses are leading in the design, implementation, and management of models of care to accommodate the demands for health and nursing care in hospitals and community settings. The Canadian Centre went one step further, gathering data about barriers to continuing nursing practice with expanded autonomy and authority after the pandemic. No nurse will be surprised by the findings. Within healthcare there is a deeply engrained imbalance of power and nurses lack opportunities to influence healthcare policy and decision making, which is grounded in insufficient and inequitable funding and reimbursement models. Nurses are viewed as a commodity to be managed by others. Shortly after graduating from my initial nursing preparation in a hospital-based diploma program I realized that nurses were expected to be doers, not thinkers. My diploma program did not emphasize thinking; the faculty emphasized doing things correctly, which meant doing as told, usually by physicians. As a student, my practice was expected to be in compliance with the hospital’s procedure book where, notably, each individual procedure was approved and signed by the chief medical officer. Having been trained by the hospital, administrators expected graduates to become the workforce for the hospital. Thankfully nursing education has moved away from hospital-based apprentice education and into university-based academic preparation. Yet still, nurses are largely seen as a commodity, the doers of deeds to be managed by others. The pandemic has highlighted the consequences of designing health and hospital systems dependent on a marginalized workforce. The doers are leaving. It is long past time to recognize nurses as thinkers, as judgment workers, as leaders, theorists, scientists, administrators, educators, innovators, entrepreneurs, colleagues, and expert clinicians whose interventions reduce health risk, prevent disease, enhance function, manage symptoms, and provide care and comfort. Nurses can and should design and manage the systems in which nursing care is delivered. Yes, nurses have many different roles, we do a lot of things, and we can contribute so much more – in addition to staffing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0070.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.103
GPT teacher head0.518
Teacher spread0.416 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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