How does a mindfulness-based program affect nurse burnout in a home health setting?

  

This 15-slide PowerPoint with VoiceOver recording will display the integration of your DNP clinical question and technology/informatics, including:
1. An introduction of your DNP clinical question
2. Definition of your stakeholders
3. The benefits of your chosen technology
4. A SWOT diagram outlining the internal and external forces that could affect your project
5. What benefits or barriers (include cultural, ethical, financial, regulatory and legal) might the occur as a result of your chosen technology?
6. What can/will you do to overcome these barriers?
YOU MUST USE THE ATTACHED RUBRIC TO COMPLETE THE ASSIGNMENT

MY DNP CLINICAL QUESTION-
Among nurses experiencing burnout in a home health setting, how does introduction of a mindfulness-based program(I) as compared to no mindfulness-based program (C) affect nurse burnout(O) within 6 months (T)
My Stakeholders are-
Director of Nursing, the administrative team of Mercris Home health, the nursing staff, and the nurse practitioner.

Don't use plagiarized sources. Get Your Custom Essay on
How does a mindfulness-based program affect nurse burnout in a home health setting?
Just from $13/Page
Order Essay

READING FOR THE ASSIGNMENT:
McBride and Tietze (2022)
Chapter 14: Privacy and Security
Chapter 15: Personal Health Records and Patient Portals
Additional resources
Harris, D., Haskell, J., Cooper, E., Crouse, N, and Gardner, R. (2018). Estimating the association between burnout and electronic health record-related stress among advanced practice registered nurses. EHR-1.related.stress.among.APNs.pdf (ATTACHED)
Hilliard, R., Haskell, J., & Gardner, R. (2020). Are specific elements of electronic health record use associated with clinician burnout more than others? Available at https://pubmed-ncbi-nlm-nih-gov.northernkentuckyuniversity.idm.oclc.org/32719859/.
Rubric for Week 6 PowerPoint Assignment

Final Project

Final Project

Criteria

Ratings

Pts

This criterion is linked to a Learning Outcome Introduction of Clinical Project

5pts

Full Marks

Provide a brief introduction of self and discussion of your DNP clinical question/project.

3pts

Partial

0pts

No Marks

5pts

This criterion is linked to a Learning Outcome Stakeholders

5pts

Full Marks

Define the stakeholders involved with and impacted by your clinical project.

3pts

Partial

0pts

No Marks

5pts

This criterion is linked to a Learning OutcomeTechnology

10pts

Full Marks

Describe your chosen technology and define the benefits of this technology’s interaction in your clinical project.

5pts

Partial

0pts

No Marks

10pts

This criterion is linked to a Learning OutcomeSWOT

30pts

Full Marks

Create a SWOT diagram and discuss the internal and external forces that could affect your project. Include cultural, ethical, financial, regulatory and legal concerns.

8pts

Partial

0pts

No Marks

30pts

This criterion is linked to a Learning OutcomeSolutions

20pts

Full Marks

What possible solutions could you implement to overcome any perceived barriers or challenges as identified in your SWAT analysis?

10pts

Partial

0pts

No Marks

20pts

This criterion is linked to a Learning Outcome Critical Thinking/Synthesis

5pts

Full Marks

Thoughtfully and accurately interprets results, shows in-depth under-standing of major ideas.

3pts

Partial

0pts

No Marks

5pts

This criterion is linked to a Learning OutcomeQuality of Information

5pts

Full Marks

Covers topic thoroughly, includes details that support the topic in audio/video presentation.

3pts

Partial

0pts

No Marks

5pts

This criterion is linked to a Learning OutcomeOrganization

5pts

Full Marks

Well organized and coherent, topics are in logical sequence, includes clear introduction and conclusions.

3pts

Partial

0pts

No Marks

5pts

This criterion is linked to a Learning OutcomeVisual Design

5pts

Full Marks

All grammar and spelling are correct; Slides are visually appealing, clean simple layout, text is limited to main bullet points & easy to read, graphics enhance under-standing of ideas; good use of color and space

3pts

Partial

0pts

No Marks

5pts

This criterion is linked to a Learning OutcomeOral Presentation

5pts

Full Marks

Well prepared, speaks clearly, makes eye contact with audience, as appropriate if on video, delivers with ease, audio/speech is understandable ; details bullet/main points

3pts

Partial

0pts

No Marks

5pts

This criterion is linked to a Learning OutcomeAPA/References

5pts

Full Marks

APA format, grammar, spelling, and/or punctuation are accurate, or with zero errors. Information is referenced as appropriate on slides

3pts

Partial

0pts

No Marks

5pts

Total Points:100 Contents lists available at ScienceDirect

Applied Nursing Research

journal homepage: www.elsevier.com/locate/apnr

Original article

Estimating the association between burnout and electronic health record-
related stress among advanced practice registered nurses

Daniel A. Harris, MPHa,c, Jacqueline Haskell, MSc, Emily Cooper, MPHc,, Nancy Crouse, CNSd,
Rebekah Gardner, MDb,c

a Department of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
bWarren Alpert Medical School, Brown University, Providence, RI, United States of America
cHealthcentric Advisors, Providence, RI, United States of America
d Boston Medical Center, Boston, MA, United States of America

A R T I C L E I N F O

Keywords:
APRN
Burnout
Electronic health record
Health information technology

A B S T R A C T

Background: Health information technology (HIT), such as electronic health records (EHRs), is a growing part of
the clinical landscape. Recent studies among physicians suggest that HIT is associated with a higher prevalence
of burnout. Few studies have investigated the workflow and practice-level predictors of burnout among ad-
vanced practice registered nurses (APRNs).
Aim: Characterize HIT use and measure associations between EHR-related stress and burnout among APRNs.
Methods: An electronic survey was administered to all APRNs licensed in Rhode Island, United States
(N= 1197) in MayJune 2017. The dependent variable was burnout, measured with the validated Mini z
burnout survey. The main independent variables were three EHR-related stress measures: time spent on the EHR
at home, daily frustration with the EHR, and time for documentation. Logistic regression was used to measure
the association between EHR-related stress and burnout before and after adjusting for demographics, practice-
level characteristics, and the other EHR-related stress measures.
Results: Of the 371 participants, 73 (19.8%) reported at least one symptom of burnout. Among participants with
an EHR (N=333), 165 (50.3%) agreed or strongly agreed that the EHR added to their daily frustration and 97
(32.8%) reported an insufficient amount of time for documentation. After adjustment, insufficient time for
documentation (AOR=3.72 (1.787.80)) and the EHR adding to daily frustration (AOR=2.17 (1.024.65))
remained predictors of burnout.
Conclusions: Results from the present study revealed several EHR-related environmental factors are associated
with burnout among APRNs. Future studies may explore the impact of addressing these EHR-related factors to
mitigate burnout among this population.

1. Introduction

Resulting from chronic job-related stress, burnout is characterized
by emotional exhaustion, depersonalization, and decreased job sa-
tisfaction (Maslach, Schaufeli, & Leiter, 2001). Given the high-stress
nature of clinical environments, burnout among healthcare workers has
been shown to exceed that of the general population (Shanafelt, Boone,
Tan, et al., 2012). Among physicians, the first published report of
burnout emerged in 1981 (Pines, 1981). A nationally representative
survey of United States physicians revealed that nearly half (45.8%)
experienced at least one symptom of burnout (Shanafelt et al., 2012;
Shanafelt, Hasan, Dyrbye, et al., 2015). Moreover, results indicated that
over 50% of physicians in front line specialties (e.g., emergency

medicine and general internal medicine) reported one or more symp-
toms of burnout (Shanafelt et al., 2012). Several studies have identified
associations between physician burnout and poorer quality of care
(Melville, 1980; Yuguero, Marsal, Esquerda, & Soler-Gonzalez, 2017),
reduced patient satisfaction (Haas et al., 2000), and increased risk of
turnover (Williams, Konrad, Scheckler, et al., 2001). However, despite
the breadth of literature investigating burnout among physicians, sig-
nificantly fewer studies have explored burnout among advanced prac-
tice registered nurses (APRNs) (Hoff, Carabetta, & Collinson, 2017).

In 2010, the Agency for Healthcare Research and Quality estimated
that over 100,000 APRNs practice in the United States, with over half
(52.0%) working in primary care (Agency for Research Health and
Quality, 2012). As of 2017, the number of APRNs has grown to 234,000

https://doi.org/10.1016/j.apnr.2018.06.014
Received 4 March 2018; Received in revised form 19 June 2018; Accepted 23 June 2018

Corresponding author at: 235 Promenade Street, Suite 500, Providence, RI, United States of America.
E-mail address: [emailprotected] (E. Cooper).

Applied Nursing Research 43 (2018) 3641

0897-1897/ 2018 Elsevier Inc. All rights reserved.

T

http://www.sciencedirect.com/science/journal/08971897

https://www.elsevier.com/locate/apnr

https://doi.org/10.1016/j.apnr.2018.06.014

https://doi.org/10.1016/j.apnr.2018.06.014

mailto:[emailprotected]

https://doi.org/10.1016/j.apnr.2018.06.014

http://crossmark.crossref.org/dialog/?doi=10.1016/j.apnr.2018.06.014&domain=pdf

in the United States (American Association of Nurse Practitioners, 2017;
Hoff et al., 2017). Similar growth of the APRN workforce has been
observed in the Netherlands, Canada, Australia, Ireland and New
Zealand from 2005 to 2015 (Maier, Barnes, Aiken, & Busse, 2016).
APRNs comprise a large and crucial component of the clinical work-
force especially as physician shortages in both primary and specialized
care settings continue to increase (Hoff et al., 2017; Norful, Swords,
Marichal, Cho, & Poghosyan, 2017). Despite the growth of the APRN
workforce in the United States and internationally, few studies have
investigated the work-related psychological outcomes experienced by
this population. One study showed that compared to emergency nurses
and nurse managers, APRNs tend to experience less burnout (Browning,
Ryan, Thomas, Greenberg, & Rolniak, 2007). The authors suggested
that lower burnout among APRNs may be because they enter the field
to gain more autonomy (Whelan, 1997), a job characteristic that is
typically associated with greater job satisfaction (Tri, 1991). A recent
review of job satisfaction, burnout, and job turnover among APRNs and
physician assistants revealed that although APRNs generally report high
job satisfaction, considerable variation exists across studies (Hoff et al.,
2017). The authors also noted that the literature examining burnout
among APRNs has a number limitations: 1) many studies with sample
sizes of less than<200, 2) a predominance of univariable and bivari- able analyses, as opposed to multivariable statistical methods, and 3) a limited consideration of work setting and organizational factors (Hoff et al., 2017). In the United States, recent changes in the payment landscape (e.g., Meaningful Use and the Physician Quality Reporting System) and their connection to HIT have drawn investigators to explore potential asso- ciations between HIT and burnout among physicians (Shanafelt et al., 2012; Shanafelt, Dyrbye, Sinsky, et al., 2016). One recent survey of a nationally representative sample of United States physicians reported that overall satisfaction with electronic health records (EHRs) was ty- pically low and that physicians who used EHRs had higher odds of burnout (Shanafelt et al., 2016). Dissatisfaction with HIT has also been observed among physicians and nurses internationally (Griffon et al., 2017; Leslie & Paradis, 2018; Ologeanu-Taddei, Morquin, & Vitari, 2017). Similar to physicians, APRNs engage with HIT as part of their practice (Bowles, Dykes, & Demiris, 2015; Cooper, Baier, Morphis, Viner-Brown, & Gardner, 2014; Fund TC, 2017); however the re- lationship between HIT and burnout among this population remains unstudied. Therefore, the current study's primary aim is to address several of the limitations in the literature by estimating the association between EHR-related stress and burnout among APRNs, while adjusting for demographic and organizational factors using multivariable methods. To further describe APRN engagement, attitudes and per- ceptions about HIT, our study's secondary aim is to characterize other dimensions of HIT and EHR use (e.g., office communication). We hy- pothesize that EHR-related stress will be significantly associated with burnout. 2. Methods Administered by the Rhode Island Department of Health, a state- wide electronic survey was sent to all 1197 APRNs licensed and in practice in Rhode Island. The survey period was from May 8th, 2017 to June 12th, 2017. As part of a legislative mandate (State of Rhode Island Plantations, 1998), the survey measures and publically reports ag- gregated measures of HIT use among physicians, physician assistants and APRNs in the state. A description of the publically reported mea- sures and survey process has been previously reported (Cooper et al., 2014). A total of 371 APRNs contributed data for a response rate of 31.0%. The present study was reviewed by the Rhode Island Depart- ment of Health's Institutional Review Board (IRB) and deemed exempt. 2.1. Sample characteristics Participant age and gender were obtained through the Rhode Island Department of Health's publically available APRN licensure file and matched using the participant's self-reported APRN license number. Age was categorized into three groups (2440; 4160; and 6180 years of age). Participants also provided information regarding their specialty, practice setting (outpatient/office or inpatient/hospital), practice size, whether they provide primary care and whether they use a medical scribe (Shanafelt et al., 2012; Shanafelt et al., 2015; Shanafelt et al., 2016). Practice size was categorized into four groups (13 clinicians; 49 clinicians; 1015 clinicians; 16+ clinicians). Due to the small number of Neonatal specialists (n= 5), their specialty was combined with Pediatrics. 2.2. Dependent variable Burnout was measured using a single question item from the Mini z, a 10-item survey developed from the Physician Work Life Study (McMurray et al., 2000; Puffer, Knight, O'Neill, et al., 2017; Williams, Konrad, Linzer, et al., 1999). Using a 5-point likert scale, participants were asked to identify their symptoms of burnout (Maslach et al., 2001): 1) I enjoy my work. I have no symptoms of burnout; 2) I am under stress, and dont always have as much energy as I did, but I dont feel burned out; 3) I am definitely burning out and have one or more symptoms of burnout, e.g., emotional exhaustion; 4)The symptoms of burnout I am experiencing wont go away. I think about work frustra- tions a lot; 5) I feel completely burned out. I am at the point where I may need to seek help. Similar to previous studies, we dichotomized this measure into no symptoms of burnout (2) and 1 or more symp- toms of burnout (3) (McMurray et al., 2000; Schmoldt, Freeborn, & Klevit, 1994). This single-item measure has been previously validated for physicians (Rohland, Kruse, & Rohrer, 2004) and shown to have a sensitivity of 83.2% and specificity of 87.4% when compared to the Maslach Burnout Inventory (Dolan, Mohr, Lempa, et al., 2015). 2.3. Independent variables The present study's main independent variables of interest are three EHR-related stress measures: 1) whether the EHR adds to daily frus- tration, 2) sufficiency of time for documentation, and 3) the amount of time spent on the EHR at home. As with the outcome of interest, the three EHR-related stress measures were adopted from the Mini z (Williams et al., 1999; Williams et al., 2001). For the first measure, participants rated how much they agreed that EHRs add to their daily frustration using a 4-point likert scale (strongly agree, agree, dis- agree, or strongly disagree). We dichotomized these responses into two categories: agree (combining agree with strongly agree) and disagree (combining disagree with strongly disagree). The second EHR-related stress measure assessed sufficiency of time for doc- umentation using a 5-point likert scale (poor, marginal, satisfac- tory, good, optimal). Responses were dichotomized into either insufficient (poor and marginal) or sufficient (satisfactory, good, and optimal) time for documentation. Last, for the third measure, participants were asked to rate how much time they spend on the EHR at home using a 5-point likert scale (excessive, moderately high, satisfactory, modest, or minimal/none). Responses were categorized into three groups: 1) minimal/none, 2) modest and satisfactory, and 3) moderately high and excessive. 2.4. Additional health information technology use measures As few studies have explored the distribution, attitudes, and per- ceptions of HIT among APRNs, we included a number of HIT use- and perception-related survey questions. Any EHR use, either at a main or secondary practice site, was measured with a binary yes/no response. D.A. Harris et al. Applied Nursing Research 43 (2018) 3641 37 Survey questions regarding EHR use were only administered to parti- cipants who reported yes to using an EHR. Using a 4-point scale (strongly agree, agree, disagree, or strongly disagree), partici- pants were instructed to judge if EHRs 1) improve their clinical work- flow, 2) improve patient care, 3) improve job satisfaction, and 4) im- prove communication among providers and staff. Participants were asked if they have remote access to their EHR and if they used it, and among participants who use remote EHR access, the reasons for remote use. Last, as medical scribes have been shown to mitigate the burdens of HIT use among physicians, participants were asked if they used a medical scribe using a dichotomous yes/no response (Gidwani, Nguyen, Kofoed, et al., 2017). 2.5. Data analysis Bivariable chi-square and Fisher's exact tests were used to measure associations between burnout, participant demographics, practice characteristics, EHR use, and EHR-related stress. Fisher's exact tests were used to measure the association between categorical variables with a small number (5) of participants in a category. Logistic re- gression was used to measure the unadjusted associations between burnout, participant demographics (age and gender), practice char- acteristics (practice setting, practice size, use of a medical scribe), and the three EHR-related stress measures of interest. Multivariable logistic regression was then used to measure the associations between burnout and each measure of EHR-related stress while controlling for partici- pant demographics, practice characteristics, and the other EHR-related stress measures. As the three independent measures of interest require the use of an EHR, the regression models only included APRNs who reported using an EHR (N=333). All statistical analyses were con- ducted using Stata version 14.0 (Stata Statistical Software, 2015). 3. Results Among the 371 APRN participants in our sample, 73 (19.8%) ex- perienced one or more symptoms of burnout and 333 (89.9%) reported using an EHR. Fig. 1 displays the distribution of each APRN specialty among those reporting one or more symptoms of burnout. Among the 73 APRNs reporting at least one symptom of burnout, 34 (46.6%) were Family/Individual APRNs and 16 (21.9%) were Adult/Gerontology APRNs. Among APRN participants who use EHRs, 64 (19.3%) reported spending a moderately high to excessive amount of time on their EHR at home, 165 (50.1%) agreed or strongly agreed EHRs add to their daily frustration, and 97 (32.8%) reported insufficient time for documenta- tion. Table 1 stratifies demographic traits, practice characteristics and burnout by EHR use. We note several significant differences in EHR use across age, practice setting, practice size, specialty, and the ordinal measure of burnout (i.e., the 5-point scale identifying symptoms of 0.0% 6.9% 11.0% 13.7% 21.9% 46.6% 0% 20% 40% 60% 80% 100% Non-prescriptive (n=0) Women's Health (n=5) Prediatric (n=8) Psychiatric (N=10) Adult/Gerontology (n=16) Family/Individual (n=34) APRNs reporting burnout Fig. 1. Distribution of Advanced Practice Registered Nurse (APRN) specialties reporting one or more symptoms of burnout (n=73). Table 1 Sample characteristics of the advanced practice registered nurse (APRN) par- ticipants (N= 371). Characteristic Does not have an EHR (N=38) n (%) Has an EHR (N=333) n (%) p Age, years 0.001 2440 4 (10.5) 104 (31.2) 4160 17 (44.7) 160 (48.1) 6180 17 (44.7) 69 (20.7) Gender 0.285 Male 2 (5.3) 41 (12.3) Female 36 (94.7) 292 (87.7) Practice setting 0.015 Office/outpatient 33 (86.8) 108 (32.4) Hospital/inpatient 5 (13.2) 225 (67.6) Practice size 0.001 13 clinicians 22 (57.9) 74 (22.4) 49 clinicians 12 (31.6) 96 (29.0) 1015 clinicians 1 (2.6) 43 (13.0) 16 or more clinicians 3 (7.9) 118 (35.7) Primary care provider No 22 (66.7) 116 (51.6) 0.104 Yes 11 (33.3) 109 (48.4) Specialty/degree type 0.001 Adult/Gerontology 6 (15.8) 91 (27.8) Family/Individual 12 (31.6) 154 (46.3) Non-prescriptive 5 (13.16) 2 (0.6) Psychiatric 14 (36.8) 47 (14.1) Women's health/gender related 1 (2.6) 15 (4.5) Pediatric 0 (0.0) 24 (7.2) Burnout 0.001 1. I enjoy my work. I have no symptoms of burnout 28 (73.7) 109 (32.9) 2. I am under stress, and don't always have as much energy as I did, but I don't feel burned out 6 (15.8) 153 (46.2) 3. I am definitely burning out and have one or more symptoms of burnout, e.g., emotional exhaustion 4 (10.53) 59 (17.8) 4. The symptoms of burnout I am experiencing won't go away. I think about work frustrations a lot 0 (0.0) 8 (2.4) 5. I feel completely burned out. I am at the point where I may need to seek help 0 (0.0) 2 (0.6) Burned out 0.195 No 34 (89.5) 262 (79.2) Yes 4 (10.5) 69 (20.9) EHR= electronic health record. Notes. Burnout was measured via the Mini z questionnaire. Responses of 3 or above were considered burned out. D.A. Harris et al. Applied Nursing Research 43 (2018) 3641 38 burnout). For example, there are a greater proportion of psychiatric nurse practitioners without EHRs (36.6%), compared to APRNs with EHRs (14.1%). We also observed significant differences in the ordinal measurement of burnout when stratified by EHR use, such that APRNs who use EHRs had a greater presence of burnout compared to APRNs who do not use EHRs. Table 2 presents attitudes and perceptions about EHRs among APRNs. More than half of participants agreed or strongly agreed that EHRs 1) improve their clinical workflow (82.5%), 2) improve patient care (63.4%), and 3) improve communication among providers and staff (77.8%). However, less than half of APRNs reported that EHRs improve their job satisfaction (48.0%). We also noted that among the 217 (65.6%) APRNs with remote EHR access, 160 (81.6%) use remote EHR access because they are unable to complete work during regular work hours. Table 3 includes results from both the unadjusted and adjusted lo- gistic regression procedures. All three EHR-related stress measures were significantly associated with burnout in the unadjusted model, and two remained significant after adjusting for confounding factors. In the unadjusted model, participants who agreed that EHRs added to their daily frustration had 3.60 (95%CI: 2.06.51) times the odds of burnout compared to APRNs who disagreed EHRs add to their daily frustration. Similarly, APRNs who reported moderately high to excessive use of their EHR at home had 5.02 (95%CI: 2.649.56) times the odds of burnout compared to ARPNs who reported minimal to no use of their EHR at home before adjustment. In the unadjusted model, APRNs who reported insufficient time for documentation had 5.15 (95%CI: 2.849.33) times the odds of burnout compared to APRNs who reported a sufficient time for documentation. Remote EHR access was also sig- nificantly associated with burnout (OR=2.19, 95%CI: 1.174.08) be- fore adjustment. After adjusting for demographic traits, practice characteristics, and the three EHR-stress measures, both insufficient time for documenta- tion (AOR=3.72 95%CI: 1.787.80) and agreeing that the EHR adds to daily frustration (AOR=2.17, 95%CI: 1.024.65) remained sig- nificantly associated with burnout. No other significant effects were observed in the adjusted model. 4. Discussion This study has several key and unique findings. First, to our knowledge, this is the first study among a growing body of physician- focused literature to characterize HIT use, attitudes, and perceptions among APRNs. The APRNs in our sample reported high use of EHRs (90%), similar to that of their physician counterparts (Centers for Disease Control and Prevention, 2017). Second, we estimated the Table 2 Sample characteristics of electronic health record use among advanced practice registered nurses who use an EHR (APRNs) (N=333). EHR characteristic n (%) EHR adds to the frustration of my day Strongly disagree 29 (8.8) Disagree 134 (40.6) Agree 125 (38.1) Strongly agree 40 (12.0) EHR improves my clinical workflow Strongly disagree 26 (7.9) Disagree 90 (27.4) Agree 182 (55.5) Strongly agree 30 (9.2) EHR improves patient care Strongly disagree 20 (6.1) Disagree 100 (30.5) Agree 180 (54.9) Strongly agree 28 (8.5) EHR improves my job satisfaction Strongly disagree 53 (16.2) Disagree 117 (35.8) Agree 133 (40.7) Strongly agree 24 (7.3) EHR improves communication among the providers and staff in my unit or practice Strongly disagree 16 (4.9) Disagree 57 (17.3) Agree 210 (63.8) Strongly agree 46 (14.0) Remote EHR use No, I do not have remote access 77 (23.3) No, I have remote access, but do not use it 37 (11.2) Yes, I use remote EHR access 217 (65.6) Reason for remote EHR use Unable to complete work during regular work hours 160 (81.6) Have the opportunity to work from home (e.g., to achieve work/ life balance) 36 (18.4) Time spent on the EHR at home Minimal/None 174 (52.6) Modest/Satisfactory 93 (28.1) Moderately high/Excessive 64 (19.3) Sufficiency of time for documentation Insufficient 97 (32.8) Sufficient 199 (67.2) EHR= electronic health record; HIT=health information technology. Table 3 Unadjusted and adjusted odds ratio estimates of the association between elec- tronic health record-related stress and burnout among advanced practice re- gistered nurses (APRNs) with EHRs (N=333). Characteristic Unadjusted OR (95%CI) p Adjusted ORa (95%CI) p Age, years 2440 Ref Ref 4160 1.00 0.99 0.68 (0.301.57) 0.368 6180 1.07 0.86 0.46 (0.161.27) 0.132 Gender Male Ref Ref Female 2.59 (0.987.54) 0.081 1.37 (0.355.33) 0.646 Practice setting Hospital/inpatient Ref Ref Office/outpatient 1.76 (0.953.26) 0.070 1.30 (0.533.24) 0.567 Practice size 13 clinicians Ref Ref 49 clinicians 1.48 (0.693.16) 0.314 1.41 (0.553.63) 0.476 1015 clinicians 2.03 (0.844.9) 0.116 2.11 (0.666.74) 0.210 16 or more clinicians 0.98 (0.452.11) 0.954 1.59 (0.544.63) 0.400 Uses a medical scribe No Ref Ref Yes 0.46 (0.161.36) 0.162 0.35 (0.091.34) 0.125 EHR adds to daily frustration Strongly disagree/ disagree Ref Ref Strongly agree/agree 3.60 (2.06.51) 0.001 2.17 (1.024.65) 0.045 Remote EHR use No Ref Ref Yes 2.19 (1.174.08) 0.014 1.38 (0.513.72) 0.531 Time spent on the EHR at home Minimal/none Ref Ref Modest/satisfactory 0.93 (0.451.90) 0.832 0.53 (0.181.54) 0.244 Moderately high/ excessive 5.02 (2.649.56) 0.001 2.66 (0.917.80) 0.075 Sufficiency of time for documentation Sufficient Ref Ref Insufficient 5.15 (2.849.33) 0.001 3.72 (1.787.80) 0.001 Notes: Odds Ratio (OR); Confidence interval (CI); Electronic health record (EHR); Pseudo-R2=0.21. a Factors in the adjusted model included age, gender, practice setting, practice size, use of a medical scribe, EHR adding to daily frustration, remote EHR use, time spent on the EHR at home, and sufficiency of time for doc- umentation. D.A. Harris et al. Applied Nursing Research 43 (2018) 3641 39 associations between demographic traits, practice characteristics, EHR- related stress, and burnout among APRNs. The unadjusted regression results revealed several EHR-related factors that were associated with burnout, such as remote EHR use, the EHR adding to daily frustration, substantial time spent on the EHR at home, and an insufficient amount of time for documentation. After adjusting for confounding factors, insufficient time for documentation and negative attitudes towards EHR remained strongly associated with burnout. Interestingly, and unlike previous physician studies, our results did not indicate any significant effects between demographic traits or practice characteristics and burnout (Shanafelt et al., 2016). According the Office of the National Coordinator for Health Information Technology (ONC), part of the United States Department of Health and Human Services, EHRs are designed to improve billing and to have additional co-benefits, such as improvements in patient care and information accessibility (Office of the National Coordinator for Health Information Technology, 2014). Although some studies have shown improvements to patient care and associated financial savings from EHRs (Chaudhry, Wang, Wu, et al., 2006; Shekelle, Morton, & Keeler, 2006), the results are mixed (Black, Car, Pagliari, et al., 2011). Moreover, EHRs have been shown to increase the odds of burnout among physicians (Shanafelt, Dyrbye, Sinsky, et al., 2016) and nega- tively impact patient-provider interactions (Pelland, Baier, & Gardner, 2017). The results from the present study are the first to investigate HIT use among APRNs, a growing and critically important component of the healthcare delivery system. Compared to physicians, our results indicated that the APRNs in our sample have more favorable attitudes and perceptions of EHRs. A re- cent study of EHR use and physician burnout indicated that only 36% of physicians agreed or strongly agreed that EHRs improve patient care (Shanafelt et al., 2016). However, over 60% of APRNs in our sample agreed or strongly agreed that EHRs improve patient care. While these differences may be attributed, in part, to differences in training, patient panel size, and job responsibilities across the provider types, further research is needed to identify why APRNs may have more favorable opinions of EHRs compared to physicians. However, similar to physi- cians, our results indicated that EHRs and EHR-related stress are asso- ciated with burnout among APRNs. Results from the bivariable analyses revealed that APRNs with EHRs reported a greater proportion of burnout symptoms compared to APRNs without EHRs. Additionally, among APRNs with EHRs, results from the regression analyses revealed several EHR-related factors were asso- ciated burnout. First, 217 (66%) of APRNs in our sample indicated they use remote EHR access. Before adjusting for other factors, remote EHR use was significantly associated with burnout. We predict this finding is related to the fact that 82% of APRNs reporting remote EHR use do so because they are unable to complete patient documentation at work, not for reasons such as improving work/life balance. This interpretation is supported by the relatively high and significant measure of associa- tion between an insufficient amount of time for documentation and burnout in both the unadjusted and adjusted results. Our results high- light the high prevalence of remote EHR use due to insufficient time for documentation and its relationship to burnout among APRNs. Similar results are echoed in the physician literature (Shanafelt et al., 2016). Fortunately, these results do highlight opportunities for quality im- provement, as the conditions of EHR use are modifiable. For example, identifying ways to decrease documentation requirements or to make documenting in EHRs less time consuming by making the electronic interface more provider-friendly. In the physician literature, medical scribes have been shown to have several significant beneficial effects on overall workplace satisfaction, patient-physician interactions, time for documentation, and doc- umentation quality and accuracy (Gidwani et al., 2017). We did not observe a significant relationship between the use of a medical scribe and burnout. However, post-hoc bivariable analyses revealed that the proportion of burnout symptoms tended to be lower in APRNs reporting the use of a medical scribe compared to APRNs who do not use a medical scribe (p=0.055). Our lack of statistical significance may be due to a small number of APRNs using medical scribes (n=34). However, positive findings from the physician literature and the results from our post-hoc analyses suggest that scribes may mitigate the burnout associated with documentation. Given these data, future re- search on the use of scribes among APRNs is likely warranted, espe- cially because nearly 20% of APRNs in our sample reported at least one symptom of burnout. Burnout among APRNs in our sample appears to be lower than what has been previously reported in physician samples (Puffer et al., 2017; Shanafelt et al., 2012; Shanafelt et al., 2015). However, the prevalence of burnout among physicians has been shown to vary widely, from 25% (Puffer et al., 2017) to 46% (Shanafelt et al., 2012). Due to the limited number of studies directly quantifying burnout among APRNs (Hoff et al., 2017), it is challenging to report a range. However, one study of 48 nurse practitioners reported that 96% reported their job as stressful (Casida & Pastor, 2012). Similarly, emotional exhaustion scores on the Maslach Burnout Inventory were moderately high for nurse practi- tioners in one study, albeit still lower than those of emergency nurses and nurse managers (Browning et al., 2007). The observed variation in physician and APRN burnout is likely attributed to a number of in- dividual- and practice-level factors, as well as methodological differ- ences across studies. For example, although a validated measure of burnout, the burnout item from the Mini z has been shown to report lower rates of burnout compared to the Maslach burnout inventory (Linzer & Poplau, 2017; Linzer, Poplau, Babbott, et al., 2016). We suspect that the present study's use of the Mini z and the fact that our survey was not anonymous, likely contributed to underreporting of the prevalence of burnout among our sample. As investigators in the phy- sician literature have noted, burnout levels of 20% among healthcare providers is still high and warrants significant attention from re- searchers as well as payers and policy makers (Linzer & Poplau, 2017; Puffer et al., 2017). The results from the present study underscore the need to develop resources for APRNs experiencing significant burnout symptoms. The American Medical Association (AMA) not only recognizes widespread burnout among physicians, but also provides a number of resources for those experiencing burnout (American Medical Association, 2015), as does the American College of Physicians (American College of Physicians: New Mexico Chapter, n.d.). To date, we were not able to identify any publically available and evidence-based resources to ad- dress burnout that are specific to APRNs. The present study has several limitations. First, the survey was ad- ministered through the Rhode Island Department of Health's legisla- tively mandated healthcare quality reporting program and requires participants to use personal identifiers. Therefore, although individual burnout responses are not publically reported, we predict that some participants may not report the extent of their burnout symptoms. Specifically, we predict that our estimation of the prevalence of burnout is likely lower than truly experienced. Second, although our survey had a response rate typical of electronic surveys, 31% remains less than preferred and limits the analytical potential of the data and the gen- eralizability of the results. Last, although over 300 APRNs contributed data, a larger sample size across more diverse geographic regions will increase the generalizability of the results. The present study adds to the field by addressing many of the lim- itations present in the burnout literature. A recent review of studies highlighted the need for future research to include samples of> 200,
use rigorous multivariable statistical techniques, and address organi-
zational factors that may be associated with burnout (Hoff et al., 2017).
The present study accomplishes these aims and, by estimating the as-
sociation between EHR-related stress and burnout, adds to a growing
body of investigation. In addition to the suggestions previously noted,
future research should consider potential causal associations between
HIT use and burnout among all clinician types and should test HIT-

D.A. Harris et al. Applied Nursing Research 43 (2018) 3641

40

related interventions to improve burnout among APRNs.

Acknowledgments

The authors report no potential conflicts of interest. Authors DH,
EC, and RG participated in the design and dissemination of the survey
instrument. Authors DH and JH participated in the analysis of the
survey results. All authors participated in the writing and review of the
manuscript. The authors thank Blake Morphis for his invaluable ex-
perience with the HIT survey, Chantal Lewis for providing thoughtful
comments and Samara Viner-Brown from the Rhode Island Department
of Health for reviewing the manuscript.

Funding

This research did not receive any specific grant from funding
agencies in the public, commercial, or not-for-profit sectors.

References

Agency for Research Health and Quality (2012). The Number of Nurse Practitioners and
Physician Assistants Practicing Primary Care in the United States. Retrieved from
https://www.ahrq.gov/research/findings/factsheets/primary/pcwork2/index.html
AHRQ Pub. No. 12-P001-3-EF.

American Association of Nurse Practitioners (2017). NP Fact Sheet. https://www.aanp.
org/all-about-nps/np-fact-sheet, Accessed date: 7 December 2017.

American College of Physicians: New Mexico Chapter. Physician burnout and wellness
resources. n.d.; https://www.acponline.org/system/files/documents/about_acp/
chapters/nm/phys_burnout.pdf.

American Medical Association (2015). Preventing physician burnout. https://www.
stepsforward.org/modules/physician-burnout.

Black, A. D., Car, J., Pagliari, C., et al. (2011). The impact of eHealth on the quality and
safety of health care: A systematic overview. PLoS Medicine, 8(1), e1000387.

Bowles, K. H., Dykes, P., & Demiris, G. (2015). The use of health information technology
to improve care and outcomes for older adults. Research in Gerontological Nursing,
8(1), 510.

Browning, L., Ryan, C. S., Thomas, S., Greenberg, M., & Rolniak, S. (2007). Nursing
specialty and burnout. Psychology, Health & Medicine, 12(2), 248254.

Casida, J. M., & Pastor, J. (2012). Practice pattern and professional issues of nurse
practitioners in mechanical circulatory support programs in the United States: A
survey report. Progress in Transplantation, 22(3), 229236.

Centers for Disease Control and Prevention. Electronic Medical Records/Electronic Health
Records (EMRs/EHRs). (2017). https://www.cdc.gov/nchs/fastats/electronic-
medical-records.htm (Accessed December 7, 2017).

Chaudhry, B., Wang, J., Wu, S., et al. (2006). Systematic review: Impact of health in-
formation technology on quality, efficiency, and costs of medical care. Annals of
Internal Medicine, 144(10), 742752.

Cooper, E., Baier, R., Morphis, B., Viner-Brown, S., & Gardner, R. (2014). HIT im-
plementation by Rhode Island physicians, advanced practice registered nurses and
physician assistants, 2014. Rhode Island Medical Journal, 97(10), 5759 (2013).

Dolan, E. D., Mohr, D., Lempa, M., et al. (2015). Using a single item to measure burnout in
primary care staff: A psychometric evaluation. Journal of General Internal Medicine,
30(5), 582587.

Fund TC (2017). International Profiles of Health Care Systems. Commonwealth Fund.
Gidwani, R., Nguyen, C., Kofoed, A., et al. (2017). Impact of scribes on physician sa-

tisfaction, patient satisfaction, and charting efficiency: A randomized controlled trial.
Annals of Family Medicine, 15(5), 427433.

Griffon, N., Schuers, M., Joulakian, M., Bubenheim, M., Leroy, J. P., & Darmoni, S. J.
(2017). Physician satisfaction with transition from CPOE to paper-based prescription.
International Journal of Medical Informatics, 103, 4248.

Haas, J., Cook, E., Puopolo, A., Burstin, H., Cleary, P., & Brennan, T. A. (2000). Is the
professional satisfaction of general internists associated with patient satisfaction?
Journal of General Internal Medicine, 15(2), 122128.

Hoff, T., Carabetta, S., & Collinson, G. E. (2017). Satisfaction, burnout, and turnover
among nurse practitioners and physician assistants: A review of the empirical lit-
erature. Medical Care Research and Review, 129 (1077558717730157).

Leslie, M., & Paradis, E. (2018). Is health information technology improving inter-
professional care team communications? An ethnographic study in critical care.
Journal of Interpersonal Education and Practice. 10, 15.

Linzer, M., & Poplau, S. (2017). Building a sustainable primary care workforce: Where do
we go from Here? Journal of American Board of Family Medicine, 30(2), 127129.

Linzer, M., Poplau, S., Babbott, S., et al. (2016). Worklife and wellness in academic
general internal medicine: Results from a national survey. Journal of General Internal
Medicine, 31(9), 10041010.

Maier, C. B., Barnes, H., Aiken, L. H., & Busse, R. (2016). Descriptive, cross-country
analysis of the nurse practitioner workforce in six countries: Size, growth, physician
substitution potential. BMJ Open, 6(9), e011901.

Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of
Psychology, 52, 397422.

McMurray, J. E., Linzer, M., Konrad, T. R., Douglas, J., Shugerman, R., & Nelson, K.
(2000). The work lives of women physicians results from the physician work life
study. The SGIM career satisfaction study group. Journal of General Internal Medicine,
15(6), 372380.

Melville, A. (1980). Job satisfaction in general practice: Implications for prescribing.
Social Science & Medicine. Medical Psychology & Medical Sociology, 14A(6), 495499.

Norful, A. A., Swords, K., Marichal, M., Cho, H., & Poghosyan, L. (2017). Nurse practi-
tioner-physician comanagement of primary care patients: The promise of a new de-
livery care model to improve quality of care. Health Care Management Review. http://
dx.doi.org/10.1097/HMR.0000000000000161 [Epub ahead of print].

Office of the National Coordinator for Health Information Technology (2014). Why Adopt
EHRs? https://www.healthit.gov/providers-professionals/why-adopt-ehrs.

Ologeanu-Taddei, R., Morquin, D., & Vitari, C. (2017). Perceptions of an electronic
medical record (EMR): Lesson from a French longitudinal study. Procedia Computer
Science. 100, 574579.

Pelland, K. D., Baier, R. R., & Gardner, R. L. (2017). It’s like texting at the dinner table:
A qualitative analysis of the impact of electronic health records on patient-physician
interaction in hospitals. Journal of Innovation in Health Informatics, 24(2), 894.

Pines, A. (1981). Burnout: A current problem in pediatrics. Current Problems in Pediatrics,
11(7), 132.

Puffer, J. C., Knight, H. C., O’Neill, T. R., et al. (2017). Prevalence of burnout in board
certified family physicians. Journal of American Board of Family Medicine, 30(2),
125126.

Rohland, B. M., Kruse, G. R., & Rohrer, J. E. (2004). Validation of a single-item measure of
burnout against the Maslach burnout inventory among physicians. Stress and Health,
20(2), 7579.

Schmoldt, R. A., Freeborn, D. K., & Klevit, H. D. (1994). Physician burnout:
Recommendations for HMO managers. HMO Practice, 8(2), 5863.

Shanafelt, T. D., Boone, S., Tan, L., et al. (2012). Burnout and satisfaction with work-life
balance among US physicians relative to the general US population. Archives of
Internal Medicine, 172(18), 13771385.

Shanafelt, T. D., Dyrbye, L. N., Sinsky, C., et al. (2016). Relationship between clerical
burden and characteristics of the electronic environment with physician burnout and
professional satisfaction. Mayo Clinic Proceedings, 91(7), 836848.

Shanafelt, T. D., Hasan, O., Dyrbye, L. N., et al. (2015). Changes in burnout and sa-
tisfaction with work-life balance in physicians and the general US working popula-
tion between 2011 and 2014. Mayo Clinic Proceedings, 90(12), 16001613.

Shekelle, P. G., Morton, S. C., & Keeler, E. B. (2006). Costs and benefits of health in-
formation technology. Evidence Report/Technology Assessment (Full Rep). 132, 171.

Stata Statistical Software (2015). Release 14 [computer program]. College Station, TX:
StataCorp LP.

State of Rhode Island Plantations (1998). Chapter 2317.17: Health Care Quality Program.
Tri, D. L. (1991). The relationship between primary health care practitioners’ job sa-

tisfaction and characteristics of their practice settings. The Nurse Practitioner, 16(5),
46 (49-52, 55).

Whelan, M. (1997). Self-esteem and competitiveness among nurse practitioner students.
Abstracts International: Section B: The Sciences & Engineering. Vol. 57(7-B)Columbia
University Teachers College.

Williams, E. S., Konrad, T. R., Linzer, M., et al. (1999). Refining the measurement of
physician job satisfaction: Results from the Physician Worklife Survey. SGIM Career
Satisfaction Study Group. Society of General Internal Medicine. Medical Care, 37(11),
11401154.

Williams, E. S., Konrad, T. R., Scheckler, W. E., et al. (2001). Understanding physicians’
intentions to withdraw from practice: The role of job satisfaction, job stress, mental
and physical health. Health Care Management Review, 26(1), 719.

Yuguero, O., Marsal, J. R., Esquerda, M., & Soler-Gonzalez, J. (2017). Occupational
burnout and empathy influence blood pressure control in primary care physicians.
BMC Family Practice, 18(1), 63.

D.A. Harris et al. Applied Nursing Research 43 (2018) 3641

41

https://www.ahrq.gov/research/findings/factsheets/primary/pcwork2/index.html

https://www.aanp.org/all-about-nps/np-fact-sheet

https://www.aanp.org/all-about-nps/np-fact-sheet

https://www.acponline.org/system/files/documents/about_acp/chapters/nm/phys_burnout.pdf

https://www.acponline.org/system/files/documents/about_acp/chapters/nm/phys_burnout.pdf

https://www.stepsforward.org/modules/physician-burnout

https://www.stepsforward.org/modules/physician-burnout

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0015

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0015

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0020

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0020

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0020

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0025

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0025

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0030

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0030

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0030

https://www.cdc.gov/nchs/fastats/electronic-medical-records.htm

https://www.cdc.gov/nchs/fastats/electronic-medical-records.htm

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0040

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0040

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0040

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0045

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0045

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0045

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0050

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0050

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0050

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0055

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0060

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0060

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0060

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0065

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0065

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0065

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0070

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0070

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0070

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0075

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0075

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0075

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0080

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0080

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0080

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0085

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0085

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0090

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0090

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0090

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0095

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0095

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0095

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0100

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0100

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0105

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0105

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0105

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0105

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0110

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0110

http://dx.doi.org/10.1097/HMR.0000000000000161

http://dx.doi.org/10.1097/HMR.0000000000000161

https://www.healthit.gov/providers-professionals/why-adopt-ehrs

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0125

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0125

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0125

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0130

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0130

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0130

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0135

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0135

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0140

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0140

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0140

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0145

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0145

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0145

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0150

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0150

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0155

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0155

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0155

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0160

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0160

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0160

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0165

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0165

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0165

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0170

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0170

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0175

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0175

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0180

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0190

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0190

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0190

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0195

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0195

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0195

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0200

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0200

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0200

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0200

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0205

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0205

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0205

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0210

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0210

http://refhub.elsevier.com/S0897-1897(18)30135-6/rf0210

Estimating the association between burnout and electronic health record-related stress among advanced practice registered nurses

Introduction
Methods

Sample characteristics
Dependent variable
Independent variables
Additional health information technology use measures
Data analysis

Results
Discussion
Acknowledgments
Funding
References

Introduction:

In today’s healthcare system, technology and informatics are playing an increasingly significant role in the delivery of care. In this PowerPoint presentation, we will be discussing the integration of a DNP clinical question with technology and informatics. Specifically, we will examine the impact of a mindfulness-based program on nurse burnout in a home health setting and the stakeholders involved in this project. We will also explore the benefits of technology in this clinical project and potential barriers that may arise, as well as solutions to overcome these challenges.

Stakeholders:

The director of nursing, administrative team of Mercris Home Health, nursing staff, and nurse practitioner are all stakeholders in this project. Each stakeholder will have a different role to play and will be impacted differently by the introduction of a mindfulness-based program to address nurse burnout.

Technology and Benefits:

The technology chosen for this clinical project is the mindfulness-based program. Mindfulness-based interventions have been shown to be effective in reducing burnout in a variety of healthcare settings. The benefits of this technology include improving nurse well-being, reducing turnover rates, and ultimately improving patient care.

SWOT Analysis:

A SWOT diagram will be used to identify the internal and external forces that could affect this project. We will consider cultural, ethical, financial, regulatory, and legal concerns in our analysis. This will help us to understand the potential barriers to implementation and develop solutions to overcome them.

Solutions:

Finally, we will discuss the possible solutions that could be implemented to overcome any perceived barriers or challenges as identified in the SWOT analysis. By anticipating potential challenges and developing solutions in advance, we can ensure the success of this clinical project and improve the well-being of nurses and, ultimately, patient care.

Objectives:
– To create a PowerPoint presentation integrating the DNP clinical question and technology/informatics.
– To introduce the DNP clinical question and stakeholders involved.
– To define the chosen technology and its benefits.
– To create a SWOT diagram outlining the internal and external forces that could affect the project.
– To identify potential benefits or barriers (including cultural, ethical, financial, regulatory, and legal) of the chosen technology.
– To propose solutions to overcome perceived barriers or challenges as identified in the SWOT analysis.

Learning Outcomes:
– Students will be able to define stakeholders involved with and impacted by clinical projects.
– Students will be able to describe and define the benefits of technology in clinical projects.
– Students will be able to create a SWOT diagram outlining the internal and external forces that could affect a project.
– Students will be able to identify potential benefits or barriers (including cultural, ethical, financial, regulatory, and legal) of the chosen technology in clinical projects.
– Students will be able to propose solutions to overcome potential barriers or challenges in clinical projects.

Solution 1: Implementing a Mindfulness-Based Program in Home Health Settings

Introduction:
Nurses working in home health settings often experience burnout due to the high workload and emotional demands of their job. This project aims to improve the well-being of home health nurses by introducing a mindfulness-based program as an intervention.

Stakeholders:
The stakeholders involved in this project include the Director of Nursing, administrative team of Mercris Home Health, nursing staff, and nurse practitioner.

Technology:
The chosen technology in this project is a mindfulness-based program that includes meditation, breathing exercises, and self-awareness techniques. The benefits of this technology include improved emotional regulation, reduced stress and anxiety, and increased job satisfaction among nurses.

SWOT Analysis:
Strengths: Improved well-being and job satisfaction among nurses, potential cost savings from reduced staff turnover.
Weaknesses: Resistance to change from staff, lack of resources for implementing the program.
Opportunities: Developing a more positive culture of nursing care, attracting and retaining high-quality nurses.
Threats: Regulatory and legal challenges, potential cultural and ethical concerns.

Possible Barriers and Solutions:
Cultural barriers: Provide education and training on the benefits of mindfulness to increase buy-in from staff.
Financial barriers: Seek funding from external sources to cover the cost of implementing the program.
Regulatory barriers: Work with legal and regulatory experts to ensure compliance with applicable laws and regulations.
Ethical barriers: Develop guidelines and protocols for maintaining confidentiality and privacy of participants.

Solution 2: Improving Electronic Health Record (EHR) Use to Reduce Nurse Burnout in Home Health Settings

Introduction:
Nurses working in home health settings often experience burnout due to the high workload and stress associated with using electronic health records (EHRs). This project aims to reduce nurse burnout by improving EHR use.

Stakeholders:
The stakeholders involved in this project include the Director of Nursing, administrative team of Mercris Home Health, nursing staff, and nurse practitioner.

Technology:
The chosen technology in this project is the electronic health record system used by Mercris Home Health. Improvements to this technology will include user-friendly interfaces, streamlined documentation processes, and increased training opportunities for staff.

SWOT Analysis:
Strengths: Improved EHR use and reduced burnout among nurses, potential cost savings from increased efficiency.
Weaknesses: Resistance to change from staff, lack of resources for implementing improvements.
Opportunities: Developing a more positive culture of nursing care, attracting and retaining high-quality nurses.
Threats: Regulatory and legal challenges, potential cultural and ethical concerns.

Possible Barriers and Solutions:
Cultural barriers: Provide education and training on the benefits of EHR improvements to increase buy-in from staff.
Financial barriers: Seek funding from external sources to cover the cost of implementing EHR improvements.
Regulatory barriers: Work with legal and regulatory experts to ensure compliance with applicable laws and regulations.
Ethical barriers: Develop guidelines and protocols for maintaining confidentiality and privacy of patient records.

Suggested Resources/Books:
1. “The Mindful Nurse” by Carmel Sheridan
2. “The Mindful Way Workbook: An 8-Week Program to Free Yourself from Depression and Emotional Distress” by John Teasdale, Mark Williams, and Zindel Segal
3. “Mindfulness-Based Stress Reduction: The MBSR Program for Enhancing Health and Vitality” by Jon Kabat-Zinn
4. “The Oxford Handbook of Mindfulness-Based Therapy” edited by Rebecca Crane, Mark Williams, et al.

Similar asked questions:
1. How does mindfulness-based stress reduction affect burnout in physicians?
2. Can technology be used to monitor nurse burnout in a home health setting?
3. How can a nurse practitioner utilize technology to improve patient care while reducing burnout?
4. What cultural barriers may impact the success of implementing a mindfulness-based program for nurse burnout prevention?
5. What are the financial implications of introducing a mindfulness-based program for nurse burnout in a home health setting?

Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Read more

Privacy policy

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

Read more
× How can I help you?