Evidence-Based Patient-Centered Needs Assessment
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NurseBiasandNursingCareDisparities.pdf
J Clin Nurs. 2021;30:3385–3397. wileyonlinelibrary.com/journal/jocn | 3385© 2021 John Wiley & Sons Ltd
Received: 12 February 2021 | Revised: 22 April 2021 | Accepted: 1 May 2021
DOI: 10.1111/jocn.15861
R E V I E W
Nurse bias and nursing care disparities related to patient characteristics: A scoping review of the quantitative and qualitative evidence
Patricia S. Groves PhD RN, Assistant Professor1 | Jacinda L. Bunch PhD RN, Assistant Professor1 | Janice A. Sabin PhD MSW, Research Associate Professor2
1University of Iowa College of Nursing, Iowa City, IA, USA 2School of Medicine, University of Washington, Seattle, WA, USA
Correspondence Patricia S. Groves, University of Iowa College of Nursing, 50 Newton Rd, Iowa City, IA, 52242 – 1121, USA. Email: [email protected]
Abstract Introduction: Investigations of healthcare workers’ implicit attitudes about patient char- acteristics and differences in delivery of healthcare due to bias are increasingly common. However, there is a gap in our understanding of nurse- specific bias and care disparities. Aims: To identify (a) the types of available evidence, (b) key factors and relationships identified in the evidence and (c) knowledge gaps related to nurse bias (nurse atti- tudes or beliefs towards a patient characteristic) and nursing care disparities (health- care disparities related specifically to nursing care). Methods: Authors completed a scoping review using the Joanne Briggs Institute method and PRISMA- SCR checklist. Five databases were searched. After screening, 215 research reports were included and examined. Data were extracted from research reports and assessed for thematic patterns and trends across multiple characteristics. Results: Nurse bias and/or care disparity investigations have become increasingly common over the 38- year span of included reports. Multiple patient characteristics have been investigated, with the most common being race and/or ethnicity, gender and age. Twenty- nine of 215 studies identified a potential relationship between nurse bias regarding a characteristic and nursing care of individuals with that characteristic. Of these studies, 27 suggested the bias was associated with a negative disparate im- pact on nursing care. Only 12 reports included evaluating an intervention designed to reduce nurse bias or nursing care- related healthcare disparities. Conclusions: Despite increasing research focus on individual bias and disparities in healthcare, the accumulated knowledge regarding nurses has not significantly advanced past a descriptive, exploratory level. Nor has there been a consistent focus on the role of nurses, who represent the largest component of the professional healthcare workforce. Relevance to clinical practice: National and international codes of ethics for nurses require provision of care according to individual, unique patient need, disregarding bias and incorporating patient characteristics into their plan of care.
K E Y W O R D S healthcare disparities, implicit bias, nurse attitudes, nurses, patient characteristics, review
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1 | INTRODUC TION
In June of 2020, tragic events, including the disproportionate COVID- 19 deaths among Black, Indigenous, and People of Color (BIPOC) and racist violence towards Black Americans and others, have served to bring long- standing issues of racism and other types of bias to international attention (Horowitz et al., 2020; Pappas, 2020). Protests for social justice and equity continue to grow around the world. Healthcare is not immune to problems such as systemic racism and individual bias towards healthcare recipients based upon social characteristics (Artiga et al., 2020). The IOM report Unequal treatment: Confronting racial and ethnic disparities in health care in 2003 brought the issue of healthcare disparities to global attention (Institute of Medicine, 2003). In fact, there is an increasingly large body of research that examines individual provider's attitudes to- wards patient characteristics and differences in the quality of care those persons receive; this research examines healthcare disparities as well as provider bias.
Healthcare disparities refer to differences among groups “in health insurance coverage, access to and use of care, and quality of care… that cannot be explained by variations in healthcare needs, patient preferences, or treatment recommendations” (Artiga et al., 2020). For example, differences in quality- of- pain treatment associ- ated with race or ethnicity would be a healthcare disparity. Note this differs from a health disparity, which indicate difference in health states or outcomes— “a higher burden of illness, injury, disability, or mortality experienced by one group relative to another” (Artiga et al., 2020). In this review, we are particularly interested in nurs- ing care disparities, which we define as healthcare disparities related specifically to nursing care.
Disparities in quality measures have been noted by patient race and ethnicity, socioeconomic status (SES), age, sexual orienta- tion and gender (Agency for Healthcare Research & Quality, 2020; CMS Office of Minority Health & RAND Corporation, 2017; Kates et al., 2018; U.S. Department of Health & Human Services Office of Minority Health, 2011). Healthcare disparities have sometimes been used in conjunction or interchangeably with discrimination, or “differences in care that result from biases, prejudices, stereotyp- ing, and uncertainty in clinical communication and decision- making” (Institute of Medicine, 2003, p. 4). In response to these trends in quality measure disparities, Kilbourne and colleagues have created a useful three- phase framework for advancing disparity research, be- ginning with detection and ending with interventions aimed and re- ducing and eliminating health and healthcare disparities (Kilbourne et al., 2006).
Implicit bias is a contributing factor to healthcare disparities. Implicit bias refers to attitudes and beliefs about patient charac- teristics that exist outside of conscious awareness, influencing be- haviour without acknowledgement, control or volition (Hall et al., 2015; Ranganath & Nosek, 2007). Implicit bias is more readily ac- tivated under conditions of high cognitive load such as fatigue, high workload or distraction, and time pressure (Byrne & Tanesini, 2015; Greenwald & Banaji, 1995; Hall et al., 2015), which are
common conditions for direct- care nurses (Agency for Healthcare Research & Quality, 2019; Teng et al., 2010). Explicit bias, by con- trast, results from conscious thoughts and beliefs that individu- als deliberately think about and report (Hall et al., 2015). Related broad terms seen in the literature include prejudice, stereotyping and stigma, while terms specific to characteristics include those such as racism, homophobia and sexism. Because terminology varies over time, and only recently has bias been categorised as implicit versus explicit, we will use the term bias to encompass any attitude or belief towards a patient characteristic, whether it be explicit or implicit.
Bias towards patient characteristics is as real and as prevalent in healthcare providers as it is in the general population. Early studies and more recent systematic reviews revealed healthcare profession- als have low- to- moderate implicit bias scores in relation to race and ethnicity, similar to the general population (FitzGerald & Hurst, 2017; Hall et al., 2015; Sabin et al., 2008, 2009), as measured by methods such as the Implicit Association Test (Greenwald et al., 1998). Implicit biases can impact quality of care for already vulnerable individu- als, such as those belonging to health disparity populations (Hart & Mareno, 2014). Implicit bias is thought to be particularly salient during one- on- one interactions with healthcare recipients, lessening communication quality and effectiveness in subtle ways, contribut- ing to healthcare disparities (Cooper et al., 2012; Hall et al., 2015; Sabin & Greenwald, 2012; Wyatt et al., 2016).
Despite the vast and varied amount of interaction that occurs between nurses and recipients of care, there is a critical gap in our understanding of bias in nurses and healthcare disparities related to the delivery of nursing care. Understanding the types of bias held by nurses (nurse bias) and the potential impacts on healthcare dispar- ities will enable pursuit of strategies to mitigate bias and enhance nursing education. Understanding the science related to nurse bias and nursing care disparities is also critical to ethical nursing prac- tice as indicated by nursing codes of ethics (e.g. American Nurses Association [ANA], 2015; International Council of Nurses [ICN],
What does this paper contribute to the wider global clinical community?
• This scoping review presents the international state of the science regarding nurse attitudes or beliefs towards a patient characteristic (nurse bias) and healthcare dis- parities related specifically to nursing care (nursing care disparity).
• The findings indicate that individual nurse bias and nurs- ing care disparities in healthcare are not uncommon and are reported in multiple countries and clinical settings.
• The findings support the need to advance accumulated knowledge around nurse bias and nursing care dispari- ties past a descriptive, exploratory level; a research agenda is offered.
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2012; Nursing & Midwifery Council [NMC], 2018). In this paper, our purpose is to comprehensively review published research related to nurse bias and nursing care disparities.
2 | AIMS
The aims of this systematic scoping review were to identify (a) the types of available evidence, (b) key factors and relationships identi- fied in the evidence and (c) knowledge gaps related to nurse bias (nurse attitudes or beliefs towards a patient characteristic) and nursing care disparities (healthcare disparities related specifically to nursing care). Specifically, our questions were as follows:
• What forms of nurse bias and nursing care disparities have been investigated?
• What potential relationships between nurse bias and nursing care have been identified or examined?
• What strategies have been implemented and evaluated to address issues related to nurse bias and nursing care disparities?
3 | METHODS
3.1 | Design
Because of the potential breadth and diversity of research related to bias and healthcare disparities in nursing care, we chose to complete a scoping review. The general purposes of scoping reviews in a given field, according to Munn are to: identify types of evidence available, clarify key concepts, examine the research methods, identify key related factors or characteristics, identify knowledge gaps, analyse knowledge gaps and provide the foundation for a traditional system- atic review (Munn et al., 2018). Thus, the scoping review approach was very well- suited to our review questions. We followed the Preferred Reporting Items for Systematic reviews and Meta- Analyses extension for Scoping Reviews (PRISMA- ScR) Checklist (File S1).
We used the Joanne Briggs Institute method (Peters et al., 2015) in order to provide systematic rigour to our scoping review, which included, in addition to the aim and review questions above, the el- ements of concept, context and inclusion criteria. The scoping re- view protocol was developed and approved by the review team prior to searching the literature. The principal focus that delineates the scope and breadth of the review, or key concept, was the scope and impact of nurse bias and nursing care disparities. The context was identified as wherever nursing care is delivered by registered nurses. Therefore, we identified three types of inclusion criteria: types of participants, the phenomena/interventions of interest and types of studies. Types of outcomes were unknown so were not limited in any way. Study participants could either be (1) registered nurses (or international equivalent) in any setting who deliver care, excluding providers such as nurse practitioners or midwives or (2) recipients of nursing care (excluding from nursing providers) providing data
regarding care received from nurses. The phenomena of interest were any implicit or explicit bias and/or any type of healthcare disparity associated with nursing care, including interventions ad- dressing these phenomena, as defined above. All quantitative and qualitative research design reports were included, excluding articles that did not report primary research. Because it was not relevant to the review questions or required for scoping reviews, a quality assessment of the research reports was not conducted (Peters et al., 2015; Tricco et al., 2018). Screening questions were developed to reflect these inclusion/exclusion criteria.
3.2 | Search strategy
In consultation with a health sciences librarian experienced in sys- tematic review searching, search strategies were devised for the following databases: CINAHL (EBSCO), PubMed, Business Source Complete (EBSCO), Scopus (Elsevier) and Dissertations and Theses (ProQuest). Identifying search terms began in December 2018 and were finalised in late February 2019. Developing the database searches required extensive review of relevant records for term gathering, as well as extensive testing and revision of strategies. A sensitive approach, comprised of both subject terms and keyword terms, was used for all the platforms with subject searching capabil- ity. The English language filter was applied, as translation of stud- ies was not an option. Although pre- set search filters were mostly avoided, the large yield required some narrowing, including a cus- tomised filter for identifying studies. The full search strategy for CINAHL that follows (conducted 14 February 2019) was adapted for use in all the mentioned databases. All search strategies are available from the corresponding author upon one's request.
#1. MH "Healthcare Disparities" OR MH "Race Factors" OR MH "Sex Factors" OR MH "Prejudice" OR MH "Skin Pigmentation" OR MH "Stereotyping" OR MH "Stigma" OR MH "Individuality" OR MH "Racism" OR MH "Homophobia" OR MM "Cultural Bias" OR MM "Ethnic Groups+" OR TI (disparit* OR bias OR racism OR racial OR "race factor*" OR prejudice OR stereotyp*)
#2. MH "Nurses+" OR MH "Nurse Attitudes" OR MH "Nursing Interventions" OR MH "Nursing Manpower+" OR MH "Nursing Care+" TI (nurs* OR RN* OR BSN OR ADN) OR AB (nurs* OR RN* OR BSN OR ADN) OR MW nurs*
#3. MM "Patient Safety+" OR MH "Quality of Health Care+" OR MM "Patient Centered Care" OR MH "Health Services Accessibility+" OR MM "Accidental Falls" OR MH "Patient Safety+" OR MM "Decision Making+" OR MM "Pain+" OR MH "Patient Care+" OR MM "Outcomes (Health Care)+" OR TI ("patient satisfaction" OR "medical error*" OR "treatment error*" OR equit* OR "nursing care" OR quality N3 care OR access* N3 care OR "pain treat- ment" OR "missed care") OR AB ("patient satisfaction" OR "medi- cal error*" OR "treatment error*" OR equit* OR "nursing care" OR quality N3 care OR access* N3 care OR "pain treatment" OR "missed care")
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#4. MH "Study Design+" OR TI (study OR studies OR trial* OR quan- titative OR qualitative OR empirical OR intervention* OR experi- ment*) OR AB (study OR studies OR trial* OR quantitative OR qualitative OR empirical OR intervention* OR experiment*)
#5. MH "Education, Nursing+" OR MH "Students, Nursing+" OR MH "Caregivers+" OR MH "Nurse Practitioners+" OR MH "Advanced Practice Nursing+"
(#1 AND #2 AND #3 AND #4) NOT #5, limited to English language = 3872.
3.3 | Study selection process
Duplicates were removed from the combined searches and the titles and abstracts were copied into an Excel spreadsheet. One report identified during the process of search development but not cap- tured via the search strategies was added. Two reviewers screened the remaining 4,635 titles and abstracts for possible inclusion. The reviewers completed two test runs of over 150 abstracts to refine the screening criteria wording and to compare and discuss differ- ing screening decisions. Once the reviewers felt confident that the
screening criteria were useful and usable and that the criteria were being used similarly by both reviewers, all titles and abstracts were screened by each reviewer. Reviewers screened each item indepen- dently, selecting either (a) “maybe” or (b) “no” with an exclusion rea- son. Screening decisions of the two reviewers were then compared within a single Excel spreadsheet, and each disagreement was dis- cussed and a consensus decision made. Final screening criteria for exclusion included:
• Not in English • Not a research report • Does not involve (1) licensed RNs as participants OR (2) licensed
RN care as part of findings (i.e. we excluded nursing students and APRNs)
• Does not include either (1) implicit/explicit bias in nurses towards a patient characteristic OR (2) healthcare disparities related to nursing care
• Study duplicate
The two reviewers then each independently screened each of the remaining 371 items with “maybe” decisions, this time using the full text. An Excel spreadsheet was again used to compare
F I G U R E 1 PRISMA diagram: Identification and selection of studies [Colour figure can be viewed at wileyonlinelibrary.com]
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screening decisions of (a) “yes” or (b) “no” with an exclusion reason. Disagreements were again resolved by consensus, resulting in 215 included articles for the review (see Table S1 and Appendix S1 for all included reports). The Preferred Reporting Items for Systematic Reviews and Meta- Analyses (PRISMA) diagram illustrating the screening process can be found in Figure 1.
3.4 | Data charting and analysis
Data were extracted from the research reports using a charting tool. The charting tool was initially created prior to article screening, based on the review questions. Following screening, the two review- ers revised the tool based on characteristics of the articles they had observed during full- text screening. With the assistance of a data manager, the charting tool was built in REDCap, a secure online data collection tool (University of Iowa, 2018). The two reviewers worked together to chart the first five included research reports, using the REDCap charting tool. Based on discussions during data extraction, the charting tool was revised for clarity and to offer more categori- cal selections for some questions (e.g. geographical location of study). Fields included items describing the publication (e.g. author, publica- tion year), the study (e.g. purpose, setting, sample, design), findings (e.g. outcome measurement, results) and review- specific elements (e.g. area of bias/disparity, intervention). The two reviewers then charted the same next ten research reports independently and then compared and discussed their results, and revised the charting tool again (final charting tool can be seen in the Figure S1). The remaining research reports were then divided between the reviewers for charting.
When charting was completed, the data were exported from REDCap into an Excel worksheet, where it was checked for miss- ing values and other errors. Once these were resolved, free- text fields such as the setting and the type of bias or healthcare dispar- ity were examined and those items were further categorised for
consistency. For example, setting entries such as “primary care” and “clinic” were categorised as “outpatient,” and bias entries such as “homelessness,” “unemployed” and “class” were categorised as “socioeconomic.” At this point, the research reports could be sorted and analysed according to multiple characteristics. Using the Excel spreadsheet functions, multiple data visuals were created to use in conjunction with the tabular data to assess for thematic patterns and trends.
4 | RESULTS
4.1 | Studies included
Ultimately, 215 studies were included and used to address our re- view questions. Publication dates ranged from 1981– 2018, with one report captured from the beginning of 2019 when we ended literature searches (see Table S1 and Appendix S1 for all included reports). A plurality of studies took place in the USA (n = 100; 47%) followed by Europe (n = 49; 23%), with the majority in a hospital set- ting (n = 123; 57%). Most studies used a quantitative design (n = 127; 59%) and examined some type of nurse bias (n = 202; 94%), with considerably fewer examining some type of healthcare disparity re- sulting from nursing care (instead of or in addition to bias; n = 36; 17%). Twenty- three categories of bias and fifteen categories of nurs- ing care- related disparities were identified in the included reports, as discussed below. Of the 215 studies, 166 studies (77%) obtained data relevant to the review from clinicians including nurses, 38 stud- ies (18%) obtained relevant data from healthcare recipients, medi- cal records or community members, and 11 studies (5%) obtained data from both nurses and healthcare recipients, medical records or community members. Of the 215 included reports, 64 (30%) did not report results separately as they related to nurses and instead re- ported results as a group for multiple clinicians that included nurses.
F I G U R E 2 Publication dates of included studies [Colour figure can be viewed at wileyonlinelibrary.com]
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4.2 | Narrative description
What forms of nurse bias and nursing care disparities have been investigated? Over nearly 40 years, researchers have investigated the presence of nurse bias regarding many patient characteristics as well as the presence of healthcare disparities as a result of dis- parate (possibly biased) nursing care. These studies have become increasingly frequent over time, as can be seen in Figure 2. Table 1
shows the wide variety of categorised patient characteristics that were investigated as a potential trigger for nurse bias or related to a healthcare disparity resulting from nursing care. Several cat- egories of nurse bias targeting patient characteristics were un- common, seen in five or less reports over the 38 included years: personality (e.g. emotionality of caregivers, niceness of patients in pain), religion, disability, immigrant status, victim of domestic violence, physical attractiveness, do not resuscitate status, fam- ily structure, health literacy or education and accusation of child abuse or neglect. Five categories of nurse bias were more com- mon, represented in ten to nineteen reports: gender identity or sexual orientation, medical diagnosis (e.g. Hansen's disease, tu- berculosis), socioeconomic (e.g. homelessness, impoverishment), overweight and obesity, and substance misuse.
The most common targets for bias were race and/or ethnicity, present in 61 of the 215 studies, gender (n = 43) and age (n = 41). The fourth and fifth most common patient characteristics were the stigmatising conditions of a diagnosis of human immunodeficiency virus (HIV) or acquired immunodeficiency syndrome (AIDS) and a psychiatric diagnosis or behaviour, respectively. The trend of these “top five” in publications over time can be seen in Figure S2. Nurse bias categories for each article are indicated in the Table S1.
The nursing care- related healthcare disparities explored were nearly as diverse, with fifteen categories identified. The most com- monly investigated areas of nursing care disparities were seen in nine reports each: caring and respectful communication and behaviour, interaction time and pain management. Disparities in general quality of care provided by nurses were investigated in five reports. Less commonly investigated areas of nursing care disparities were seen in two reports each: clinical interventions, documentation of key assessments, patient- centred care and triage management. Finally, each of the following areas was investigated in one report each: de- pression screening, diagnosis, dignity management, documentation of symptom distress, fertility counselling, patient education and vio- lent incident management. Nursing care disparity categories by arti- cle are indicated in the Table S1. Frequency of nursing care disparity categories is also indicated in Table 1.
What potential relationships between nurse bias and nursing care have been identified or examined? We identified research re- ports in the final sample that collected data on both (1) nurse bias (or attitudes) regarding one or more patient characteristics, and (2) quality of nursing care related to that bias. These data were broadly characterised. Nurse bias data could have been collected in a study- specific survey instrument, an established instrument or through a narrative qualitative response to a question. Quality of nursing care could be measured via observation, medical record or administrative data, nurse- reported intent for care, nurse self- report of actual care or narrative qualitative response to a question.
Out of the 215 included reports, 29 (13%) examined or identified a potential relationship between one or more nurse biases and nurs- ing care provided to individuals with the characteristic(s) in question (see Table 2). For example, in the western region of Ghana, Dodor and Kelly (2010) found tuberculosis (TB) stigma was associated with
TA B L E 1 Frequency of nurse bias and nursing care disparity categories
Nurse bias categories Frequency
Race/ethnicity 61
Gender 43
Age (older, younger or unspecified) 41
Diagnosis of human immunodeficiency virus or acquired immunodeficiency syndrome (HIV/AIDS)
34
Psychiatric diagnosis or behaviour 24
Gender identity or sexual orientation 19
Medical diagnosis 18
Socioeconomic 17
Overweight and obesity 11
Substance misuse 10
Personality 5
Religion 4
Disability 3
Immigrant status 3
Victim of domestic violence 2
Physical attractiveness 2
Do not resuscitate status 1
Family structure 1
Health literacy or education 1
Accusation of child abuse or neglect 1
Nursing care disparity categories Frequency
Caring and respectful communication and behaviour 9
Interaction time 9
Pain management 9
General quality of care 5
Clinical interventions 2
Documentation of key assessment 2
Patient- centred care 2
Triage management 2
Depression Screening 1
Diagnosis 1
Dignity management 1
Documentation of symptom distress 1
Fertility counselling 1
Patient education 1
Violent incident management 1
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behaviours such as maltreatment and shunning of patients with TB. Of these 29 reports, 22 offered results specific to nurses alone, and all collected data only from clinicians. Approximately half of the re- ports (n = 15) were from studies based in the USA. The majority of nursing care settings were in the hospital (n = 17), though the spe- cific hospital setting varied. Most studies used quantitative designs (n = 17), with eight studies using qualitative designs and four studies using mixed methods. Only one of the studies, a laboratory experi- ment, employed an intervention (an empathy- inducing, perspective- taking simulation; Drwecki et al., 2011).
The 29 studies examining a relationship between a nurse bias and a nursing care disparity addressed 13 categories of bias or nurs- ing care disparity, with the most frequent being bias towards persons living with human immunodeficiency virus or acquired immunodefi- ciency syndrome (n = 7) or another medical diagnosis (n = 5). These studies were heterogeneous in terms of not only design and nurse bias target of interest, but also care setting (e.g. hospital, long- term care, community), methodology (e.g. cross- sectional descriptive, phenomenology, factorial vignette), outcomes measured for indica- tions of disparity (e.g. intention to provide culturally congruent care, planned interventions to promote mothering role, pain management decisions, clinical decision- making) and instrumentation (e.g. semi- structured interviews, new or established scales and questionnaires, observations). However, with two exceptions (Early, 1998; Haider et al., 2015), study results suggested an association between a nurse bias and a negative impact on nursing care, resulting in disparity.
What strategies have been implemented and evaluated in care settings to address issues related to nurse bias and nursing care disparities? Of the 215 reports included in the review, 12 (6%) re- ported evaluation of an intervention to address issues related to bias and/or nursing care disparities. For example, Gallop and colleagues (1992) used educational videos, medical experts, group discussion and the video or presence of a person living with AIDS in an attempt to impact AIDS- related knowledge, attitude, concerns and empathic behaviours. (See Table 3 for full list of reports with intervention evaluations; note that additional interventions and outcomes within the studies unrelated to the review question are not included). Of these 12 reports, 6 provided results specific to nurses alone, and all collected data from clinicians alone. Slightly more than half of the reports (n = 7) were from studies based in the USA. Most nursing care settings were again in the hospital (n = 8). Two studies used mixed- methods designs, one study used a qualitative design, and the majority used quantitative designs (n = 10). Once again, these studies are quite heterogeneous, with eight categories of bias/dis- parities addressed. A plurality of studies addressed the issue of bias towards or healthcare disparities of persons living with HIV/AIDS (n = 5). Interventions and intervention bundles varied widely, ranging from wearing an obesity suit to programmes developed on an inter- national scale (see Table 3), though most used some type of knowl- edge or skills- based training (n = 8). Four studies used contact with the target patient population as part of the intervention.
Of the 12 studies reporting an intervention to address issues re- lated to bias and/or nursing care disparities, eight studies reported
some degree of success with the intervention(s), with two multi- programme interventions reporting mixed success. Success for the purposes of this review was designed as a measurable, but not necessarily statistically significant, improvement in the targeted outcome. However, due to the wide variation in setting, samples, interventions, implementation, time frames, instrumentation and outcomes, it is not possible to draw conclusions about the relative success of interventions.
5 | DISCUSSION
Investigations of nurse bias or nursing care disparities have become increasingly common. In the 38 complete years spanning the located reports, 20 reports were published in the first 13 years (1981– 1993), 58 reports in the second 13 years (1994– 2006) and 136 reports in the final 12 years (2007– 2018). A wide variety of patient character- istics has been investigated as they relate to nurse bias or nursing care disparities. The most common of these has been race and/or ethnicity, gender and age, which together accounted for nearly half the incidences of bias/disparity categories examined in the included research reports. It is particularly interesting that 54 reports were published prior to the IOM report Unequal treatment: Confronting ra- cial and ethnic disparities in health care in 2003, which brought global attention to healthcare disparities (Institute of Medicine, 2003).
Relatively, few investigators examined or identified a potential relationship between nurse bias (explicit or implicit) regarding a par- ticular social characteristic and nursing care of individuals with that characteristic. Only 29 studies reported data for both (1) nurse bias regarding one or more patient characteristics and (2) quality of nurs- ing care related to that bias. Nearly half of this set of heterogeneous studies were focused on persons living with HIV/AIDS or another medical diagnosis. However, 27 of the 29 studies suggested an asso- ciation between a nurse bias and a negative impact on nursing care resulting in disparity, such as the relationship between race/ethnic- ity bias and level of pain treatment (Drwecki et al., 2011).
Even fewer investigators reported evaluating an intervention de- signed to reduce nurse bias or nursing care disparities; these were published mainly within the past ten years. This was a quite varied set of 12 studies, of which only six studies provided results specific to nurses alone. This made it difficult to identify trends or common- alities in the interventions. The studies located for this review drew upon interventions from other fields, such as intergroup contact in- terventions from psychology (personal interaction between group members; Pettigrew & Tropp, 2006), but inconsistent use and re- porting makes it difficult to draw conclusions about the success of individual interventions.
5.1 | Implications
The first study to apply the nascent social psychology science of implicit bias to healthcare for any health profession was reported
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by Green & colleagues in, 2007, who examined implicit bias regard- ing race among physicians using case vignettes (Green et al., 2007). Investigators have increasingly recognised that nurses are also prone to the biases that impact other providers and the general popula- tion (FitzGerald & Hurst, 2017; Hall et al., 2015; Maina et al., 2018). This may be reflected in the upward trend of published studies over time. The remarkable number of patient characteristics examined in terms of nurse bias reflects the diverse populations for whom nurses care. Likewise, nurses provide care within diverse settings and cul- tures. The sheer number and variety of research reports located for this scoping review preclude a systematic review of similar scope. However, specifically nurse- focused integrative or systematic re- views may be warranted for research reports of the most frequently explored categories of patient characteristics, such as race and/or ethnicity, gender, age, diagnosis of HIV or AIDS, or psychiatric diag- nosis or behaviour. Though systematic reviews have already been conducted in many of these areas, often nursing has not been a focus (e.g. Dehon et al., 2017; Failla & Connelly, 2017; Hall et al., 2015; Mather et al., 2014), though there have been recent excep- tions (Rush et al., 2017).
What is less clear is the everyday practical impact of nurse bias or the actual source of nursing care disparities. The field of implicit bias in healthcare care is in its early stages of development, with the vast majority of studies in this review still being descriptive, fo- cusing either on identifying, examining and/or measuring a bias, or identifying, examining and/or measuring a healthcare disparity re- lated to nursing care. Kilbourne and colleagues (2006), who devel- oped the previous referenced framework for research in health and healthcare disparities, refer to these studies as being in phase one, or “detection.” Most studies did not attempt to link a nurse bias to an impact on the quality of nursing care. Studies of this type would belong to phase two, or “understanding,” in the Kilbourne research framework. The limited number of studies in this second research phase makes it difficult to determine if nurses practice equitably even when they are biased against or have negative attitudes about a patient characteristic. Likewise, it is difficult to determine what role nurse bias may play in nursing care disparities versus factors such as health care policy, access to care, organisational characteris- tics, inadequate education, cultural competence or clinical evidence. It is difficult to intervene in the suggested nurse bias →nursing care disparity →poorer patient outcome sequence (Institute of Medicine, 2003) when these relationships are poorly understood. Further de- velopment of the theoretical model of nurse bias and healthcare dis- parities is needed.
Finally, despite the breadth of nurse bias and nursing care dis- parity research in the past 38 years, there is a lack of intervention and implementation research. This is perhaps a natural conse- quence of the limited research exploring the why and how of the proposed relationship between bias and healthcare disparity (phase two; Kilbourne et al., 2006). Kilbourne and colleagues (2006) refer to the research phase including studies that involve development, implementation and evaluation of interventions as phase three, or “reduction or elimination” of health and healthcare disparities. These A
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research topics are in the earliest stages of development, perhaps also reflecting how implicit bias in healthcare is a relatively new spe- cific field of study. Certainly, the ultimate aim of this body of re- search should be to improve the care and outcomes of healthcare recipients and the community.
In summary, it is promising that a wide range of potential nurse biases and nursing care disparities have been investigated. However, there is not a clear trend towards locating relationships among these factors and testing interventions to improve care and patient out- comes. As this field of research matures, not only is it important to move the field towards intervention, but it is important to collect outcome data from the healthcare recipients and community them- selves, not only the clinicians as seen in this review (Kilbourne et al., 2006).
5.2 | Strengths and limitations
Reducing the influence of bias on healthcare and outcomes and elim- inating healthcare disparities is a priority for many organisations, in- cluding the U.S. National Institute on Minority Health and Health Disparities (2020), U.S. Department of Health and Human Services
(2020), Agency for Healthcare Research and Quality (2020), Institute for Healthcare Improvement (2020), Centers for Medicare and Medicaid Services (2020), ANA (2020) and the American Hospital Association (2020). This scoping review thus addresses a critical issue in nursing, health and society. The review was strengthened by a systematic and transparent review process. We have presented a broad overview of published research related to bias and healthcare disparities in nursing care, providing the reader with a starting guide to the literature and identifying both progress and gaps in the field.
Despite the comprehensive search strategy and broad defini- tions of terms, it is still possible that eligible studies were missed. Indeed, the use of multiple bias- and disparity- related terms such as healthcare disparities, race factors, sex factors, prejudice, skin pigmentation, stereotyping, stigma, individuality, racism, homopho- bia, cultural bias and ethnic groups made it difficult at times to de- termine eligibility. Including only studies published in English may have resulted in omitting international studies. Reports unavailable in full text were also not incorporated into the review. We did not examine reference lists due to the high number of publications al- ready captured by the electronic search methods. The nature and size of a scoping review also preclude providing details about each included study while making synthesis challenging. While the recent
TA B L E 3 Research reports evaluating interventions to address issues related to bias and healthcare disparities in nursing care
Author(s) Year Study location Setting Population Study design Nurse- only results Intervention type Bias category Outcome target
Outcome improvement
Gallop et al. 1992 Canada Hospital Clinicians Quantitative No Educational video, question period with an AIDS medical expert, 1- hr group discussion, video or presence of person living with AIDS
HIV/AIDS diagnosis AIDS- related knowledge, attitude, concerns and empathic behaviours
Yes
Kemppainen et al. 1996 U.S. Hospital Clinicians Quantitative Yes Basic HIV training, peer group discussions, individual patient contact training
HIV/AIDS diagnosis Prejudice and attitudes towards caring for persons with AIDS
No
Uys et al. 2009 Africa National Clinicians Quantitative Yes 5 unique programmes all including information, skill building and contact interventions
HIV/AIDS diagnosis Nurse HIV/AIDS stigmatising behaviours No
Drwecki et al. 2011 U.S. Simulation Laboratory
Clinicians Quantitative Yes Simulated perspective- taking Race/ethnicity Socioeconomic
Pain treatment bias Yes
Falker & Sledge 2011 U.S. Hospital Clinicians Quantitative No Educational self- learning module Overweight and obesity
Weight stigmatisation Yes
Blair Irvine et al. 2012 U.S. Long- term care Clinicians Quantitative No Internet video- based behavioural skills and knowledge training
Psychiatric diagnosis or behaviour
Attitudes and stigmatisation Yes
Lohiniva et al. 2016 Africa Hospital Clinicians Quantitative Yes Interactive training modules (discussion, practice, contact intervention)
HIV/AIDS diagnosis HIV stigma Yes
Edwards et al. 2016 Africa, Caribbean Hospital Clinicians Quantitative Yes 4 multi- stakeholder leadership hub programmes HIV/AIDS diagnosis Socioeconomic
Nurse HIV/AIDS stigmatising behaviours Mixed
Pelts & Galambos 2017 U.S. Long- term care Clinicians Mixed methods No Intergroup contact via storytelling video Gender identity or sexual orientation
Attitudes related to serving lesbian and gay older adults
Yes
Traister 2018 U.S. Hospital Clinicians Mixed methods Yes 1- hr unspecified educational intervention Gender identity or sexual orientation
Nursing attitudes about LQBTQ community Yes
Weech- Maldonado et al.
2018 U.S. Hospital Clinicians Quantitative No 2 hospital programmes including infrastructure development, executive coaching, training and individual- level action plans
Race/ethnicity Age Gender
Diversity attitudes, implicit bias, and racial/ ethnic identity status
Mixed
Hales et al. 2018 New Zealand Hospital Clinicians Qualitative No Simulated obesity suit Overweight and obesity
Attitudes towards people with extreme obesity Yes
Note: Diagnosis of human immunodeficiency virus or acquired immunodeficiency syndrome is indicated by the abbreviation HIV/AIDS diagnosis. United States is indicated by the abbreviation U.S.
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s-and-conditions) on W iley O
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coronavirus pandemic has brought the problem of health and health- care disparities to international attention (Pappas, 2020) and Black Lives Matter protests have done the same for societal racism and bias, these current events are not included in our review because they are not yet reflected in a substantial body of literature. Finally, we did not appraise the quality of research due to the heterogeneity of the methods, which is considered acceptable for scoping reviews (Arksey & O'Malley, 2005; Munn et al., 2018; Peters et al., 2015).
6 | CONCLUSIONS
Individual provider bias and disparities in healthcare are not uncom- mon. Despite an increasing research focus in this field of research, the accumulated knowledge has not significantly advanced past a descriptive, exploratory level. Nor has there been a consistent focus on the role of nurses, who represent the largest component of the professional healthcare workforce. This review also reveals the wide variety of patient characteristics examined in relation to nurse bias and nursing care disparities. This heterogeneous, primarily de- scriptive work not only provides a number of avenues for further investigation but reveals limited lines of research progressing from
detection to understanding and ultimately reduction or elimination of disparities. We thus recommend the following research agenda: (1) explore the content and frequency of implicit and explicit bias among nurses, (2) examine implicit and explicit bias among nurses, specifically in the context of the 2020 coronavirus pandemic and societal racism and bias, (3) identify mechanisms by which these bi- ases may or may not impact quality of nursing care (nursing care disparities), (4) identify areas where implicit and explicit biases im- pact health outcomes (health disparities) and (5) further develop and evaluate educational interventions and curriculum to mitigate the impact of bias among nurses on patient care and health.
7 | RELE VANCE TO CLINIC AL PR AC TICE
The ICN’s international Code of Ethics for Nurses argues “nursing care is respectful of and unrestricted by considerations of age, colour, creed, culture, disability or illness, gender, sexual orientation, nation- ality, politics, race, or social status” (2012, p. 1). The first provision of the US’s ANA Code of Ethics for Nurses concurs, instructing nurse to provide care according to individual, unique patient need, disre- garding bias and incorporating patient characteristics into their plan
TA B L E 3 Research reports evaluating interventions to address issues related to bias and healthcare disparities in nursing care
Author(s) Year Study location Setting Population Study design Nurse- only results Intervention type Bias category Outcome target
Outcome improvement
Gallop et al. 1992 Canada Hospital Clinicians Quantitative No Educational video, question period with an AIDS medical expert, 1- hr group discussion, video or presence of person living with AIDS
HIV/AIDS diagnosis AIDS- related knowledge, attitude, concerns and empathic behaviours
Yes
Kemppainen et al. 1996 U.S. Hospital Clinicians Quantitative Yes Basic HIV training, peer group discussions, individual patient contact training
HIV/AIDS diagnosis Prejudice and attitudes towards caring for persons with AIDS
No
Uys et al. 2009 Africa National Clinicians Quantitative Yes 5 unique programmes all including information, skill building and contact interventions
HIV/AIDS diagnosis Nurse HIV/AIDS stigmatising behaviours No
Drwecki et al. 2011 U.S. Simulation Laboratory
Clinicians Quantitative Yes Simulated perspective- taking Race/ethnicity Socioeconomic
Pain treatment bias Yes
Falker & Sledge 2011 U.S. Hospital Clinicians Quantitative No Educational self- learning module Overweight and obesity
Weight stigmatisation Yes
Blair Irvine et al. 2012 U.S. Long- term care Clinicians Quantitative No Internet video- based behavioural skills and knowledge training
Psychiatric diagnosis or behaviour
Attitudes and stigmatisation Yes
Lohiniva et al. 2016 Africa Hospital Clinicians Quantitative Yes Interactive training modules (discussion, practice, contact intervention)
HIV/AIDS diagnosis HIV stigma Yes
Edwards et al. 2016 Africa, Caribbean Hospital Clinicians Quantitative Yes 4 multi- stakeholder leadership hub programmes HIV/AIDS diagnosis Socioeconomic
Nurse HIV/AIDS stigmatising behaviours Mixed
Pelts & Galambos 2017 U.S. Long- term care Clinicians Mixed methods No Intergroup contact via storytelling video Gender identity or sexual orientation
Attitudes related to serving lesbian and gay older adults
Yes
Traister 2018 U.S. Hospital Clinicians Mixed methods Yes 1- hr unspecified educational intervention Gender identity or sexual orientation
Nursing attitudes about LQBTQ community Yes
Weech- Maldonado et al.
2018 U.S. Hospital Clinicians Quantitative No 2 hospital programmes including infrastructure development, executive coaching, training and individual- level action plans
Race/ethnicity Age Gender
Diversity attitudes, implicit bias, and racial/ ethnic identity status
Mixed
Hales et al. 2018 New Zealand Hospital Clinicians Qualitative No Simulated obesity suit Overweight and obesity
Attitudes towards people with extreme obesity Yes
Note: Diagnosis of human immunodeficiency virus or acquired immunodeficiency syndrome is indicated by the abbreviation HIV/AIDS diagnosis. United States is indicated by the abbreviation U.S.
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of care (ANA, 2015). The professional standards of the NMC in the UK supports these ideas as well, charging nurses to prioritise peo- ple and “avoid making assumptions and recognise diversity and indi- vidual choice” (2018, p. 6). Thus, understanding the science related to nurse bias and nursing care disparities is critical to ethical nurs- ing practice. Due to the inequitable impact of the coronavirus pan- demic and the widespread global embrace of the Black Lives Matter movement, society, including the research enterprise, may be ready to quickly move forward towards healthcare equity. Deliberative ef- forts to advance the study of nurse bias and nursing care disparities with the goal of increasing equitable care are critical to this cause.
ACKNOWLEDG MENT We would like to thank our health sciences librarian, Jennifer DeBerg, MLIS for her assistance with search strategies and conduct of the search; our data manager, Maria Hein, for her assistance with the REDCap coding tool; and Janet K. Williams, PhD, RN, FAAN, for her editorial assistance.
DATA AVAIL ABILIT Y S TATEMENT Data sharing not applicable – no new data generated.
ORCID Patricia S. Groves https://orcid.org/0000-0002-2312-0676
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SUPPORTING INFORMATION Additional supporting information may be found online in the Supporting Information section.
How to cite this article: Groves PS, Bunch JL, Sabin JA. Nurse bias and nursing care disparities related to patient characteristics: A scoping review of the quantitative and qualitative evidence. J Clin Nurs. 2021;30:3385–3397. https://doi.org/10.1111/jocn.15861
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