screening for intimate partner and sexual violence in a ......>1/2 experienced their first violent...
TRANSCRIPT
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Methods
Conclusions
Results
Bibliography
Results
Problem StatementIntimate partner violence (IPV) and sexual violence (SV) are serious, preventable public health problems that affect millions of Americans.1/3 of women and men experiencing IPV/SV in their lifetime. >1/2 experienced their first violent incident before 25 years old9% college students experienced an abusive relationship9% students report having been sexually touched without consentNegative health impacts: physical/mental medical conditions, death, increased risky behaviors, higher medical costs
Purpose of the ProjectUnder Title IX, University Health Services (UHS) health care providers (HCPs) are Confidential Resources for students. Previously, screening
for IPV/SV was routine, not universal.
E-HITS (Sherin,1998) is a well-studied and validated screening tool used to identify those at risk for IPV/SV. The screening questionnaire asks if their partner has “Hit, Insult, Threaten, Scream or Forced
Sexual Activities” in the past 12 months1.
“it is important to universally screen for trauma and trauma symptoms”American College Health Association (2016) Trauma-Informed Toolkit2
Background
Objectives
Development
Theoretical FrameworkFisher & Fisher’s (1992) information-motivation-behavioral (IMB) skills
model was used as the theoretical framework toward implementing screening within UHS3.
Short-Term Goals
By December 20, 2019, the HCPs will screen
70% of their patients for IPV and SV.
By December 20, 2019, eighty percent of patients who screen positive for
IPV/SV will receive counseling and referrals, if
appropriate.
By December 2020, there will be 85% of patients screened for IPV/SV in the college health clinic and 100% who screen positive will receive counseling and referrals, if appropriate.
Long-Term Goals
Screening for Intimate Partner and Sexual Violence in a College Health ClinicToni Boyajian, MSN, CRNP, Claire Bode, DNP, CRNP
University of Maryland School of Nursing
Setting: On-campus college health clinic (CHC) medium size universityPopulation: College students seen for office visit at the CHC
•Students completed the screening questionnaire alone in exam room on the computer, which then provides a score for the HCP prior to visit•Students acknowledged statements of confidentiality prior to answering•State coalitions and community partners provided trauma-informed trainings to HCPs with regards to IPV and SV•HCPs were provided a variety of resources—brochures, referral options (both on & off campus), follow up•HCPs completed the “disposition” section for tracking and documentation
Over 13 weeks (9/9/2019-12/6/2019)2 MAs, 1 RN, 3 NPs
and 2 MDs Total # of students seen:
1,416
HCPs screened 65-96% with a median of 90% of their
students for IPV/SV. There was an upward trend within the first 6 weeks then
sustained screening until week 13.
The rate of positive screenings was 0-8%with a median of 3%.
The peak rate of positive screenings
(8%) was on week 2.
DiscussionTargeting HCP knowledge gaps encourages screening Integrating screening facilitates change in the organization•Example: patient preparation and electronic health recordCampus/community partners ensures a “warm” referralScreening efforts should be targeted within “The Red Zone”“The Red Zone” is the first day freshman come to campus until Thanksgiving, which had the most positive screeningsHCPs should be aware of the possible complex connection between IPV/SV, anxiety, depression and substance use.
LimitationsEHITS Language was a barrier, patients were not sure what to sayIPV/SV rates low in CHCs. Work needed in peer-peer disclosureStudents in IPV/SV may not feel safe or be ready to discloseUse of information technology has potential of malfunctionAdd an alert to the EHR if the screen is positive
1Sherin, K. M., Sinacore, J. M., Li, X. Q., Zitter, R. E. & Shakil A. (1998). HITS: A short domestic violence screening tool for use in a family practice setting. Journal of Family Medicine, 30(7), 508-5122American College Health Association (2016). ACHA guidelines: Addressing sexual and relationship violence on college and university campuses. Retrieved from https://www.acha.org/documents/resources/Addressing_Sexual_and_Relationship_Violence_A_Trauma_Informed_Approach.pdf3Fisher, J. D., Fisher, W. A., Misovich, S. J., Kimble, D. L., & Malloy, T. E. (1996). Changing AIDS risk behavior: Effects of an intervention emphasizing AIDS risk reduction information, motivation, and behavioral skills in a college student population. Health Psychology, 15, 114-123
Monthly IPV/SV trauma-informed trainings
(Information)
Screening questionnaire embedded in current workflow & electronic
health record(Motivation)
Screening, identifying and
supporting students
(Behavioral Skills)
HCPs universally screen, counsel and provide resources
(Behavioral Change)
HCPs supported 50-100% of students who reported IPV/SV with a median of 100%. The lowest rate of support
was in Week 11 at 50%.
https://www.acha.org/documents/resources/Addressing_Sexual_and_Relationship_Violence_A_Trauma_Informed_Approach.pdf
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Implementation of a Multidisciplinary Approach to Mass Casualty Incident Response
Theresa DiNardo MSN RN CCRNLinda Cook, PhD RN CCNS ACNP
University of Maryland School of Nursing
• There were 2,430 ACTIVE SHOOTER mass casualty victims between 2000-2018. (Federal Bureau of Investigation. Active Shooter Report 2018)
• Increases in TERRORISM attacks were demonstrated with a 6% to 35% increase in right-wing extremists and a 9% to 53% increase by religious extremists between 2000-2017. (University of Maryland, 2017)
• There were 203 NATURAL DISASTERS in the United States (US) between 1980 to 2016 (Climate.gov, 2016)
Problem Description
Background Knowledge• Adini, Goldberg, Cohen, Laor, and Bar-Dayan (2012) suggested that
preparing first receiver staff using SOP’s will improve knowledge of staffs’ role and function during an MCI. A random sample of 30 emergency physicians and nurses showed that the effectiveness of SOP’s correlated with all types of emergencies (rho=.854), as well as correlations with training and drills (rho=.934, p=.000).
• Park & Kim (2017) identified essential factors which influenced core competencies in disaster preparedness in emergency nurses. A Pearson’s correlation and multiple-regression analysis demonstrated that experience (β = 0.355, p < 0.001), followed by knowledge (β = 0.182, p = 0.003) were the two essential factors that influenced disaster preparedness for nurses.
• The Doctor of Nursing Practice project was developed to improve staff’s knowledge of their role and function during a mass casualty incident (MCI) specific to their work environment
• The immediate aim was to improve staff’s knowledge of what is specific for them to know in their role during an MCI as it relates to (1) rapid staff recall, (2)Triage (3) rapid patient registration and tracking, (4) surging to expand beds quickly, and (5) performing rapid life-saving interventions for multiple casualties simultaneously
• The long term aim was to improve staff’s knowledge and skill during an MCI response and to validate role-specific knowledge and skill during tabletop and functional exercises
Project purpose and specific aims
Implementation Methods• Develop a Short Messaging System (SMS) text group for rapid staff
recall for first receiver staff. • Perform the key features of hospital-mass casualty triage for multiple
victims. • Establish a unique rapid registration and tracking system unique for each
patient during an MCI.• Initiate rapid reverse triage and expand bed capacity within the first
minutes of an MCI alert. • Teach first receiver staff the critical tasks for rapid set-up of satellite
pharmacy and blood transfusion services for the provision of emergency care during an MCI.
Results
• Staff recall demonstrated a > 90% response rate within the 1st hour.• Nurses demonstrated improvement in both role and function during the MCI
tabletop and functional exercises• The first receiver staff in resuscitation and emergency services demonstrated a
shift towards independent performance (needing much help versus needing some help) in their role and function during the tabletop and functional exercise
• Registration staff and admitting staff demonstrated a unified approach and improvement during rapid patient admissions
• Pharmacists demonstrated proficiency and response during satellite improvement although more work is needed regarding documentation of controlled substances
• Blood bank demonstrated improvement in satellite set-up and distribution of blood products Conclusions
• SMS devices are efficient as a means for staff recall in the initial response phase• A standard approach to triage reduces the “bottlenecking” at the front door and
facilitates patient dispositioning• Rapid registration systems using non-numbering processes are quick and
unique for each patient• Deploying staff to perform reverse trial in the early 1st phase of an MCI activation
enables the intake of multiple casualties • Using satellite pharmacies and blood banks creates a team-centered and
efficient methods for the delivery of care to mass casualty victims
References
Discussions/Limitations• The approach was not to challenge professional credibility but to share
evidence of lessons learned from other institutions. • Satellite pharmacy and blood bank stations in the resuscitation department
facilitated access to medications and blood products bypassing the usual process.
• The development of a rapid registration system and tracker board required time consuming changes in both structure and process
• Running table top and functional exercises are time and resource intensive• Preparing and executing structure and process changes may impact hospital
costs and department workflows.
Jacqueline Brown RN, Amy Caldwell RN, Kristen George RN, June Guadalupe RN, Heidi Halterman RN, Bridget Kelsey RN, Jay Menaker MD, Karen McQuillan RN, Ellen Plummer RN, Lewis Rubinson MD, Paul Thurman RN, Erika Rychwalski BBA EMT-B
Department Unable Much Help Some Help Self Much Help Some Help Self Much Help Some Help Self Much Help Some Help Self Much Help Some Help SelfAdult ED Physicians Table Top 2 0 2 0 2 0 2 2 0
Functional Exercise 0 3 0 3 0 3 3 0 3Adult ED Registered Nurses Table Top 10 0 *** 10 0 *** 10 0 *** 10 0 *** 10 0 ***
Functional Exercise 0 8 0 8 0 8 0 8 0 8Blood Bank Table Top 2
Functional Exercise 4Emergency Management Table Top 1 0 1 0 1 0 1 0 1 0
Functional Exercise 0 3 0 3 0 3 0 3 0 3Pharmacy Table Top 4 0 *
Functional Exercise 0 5Maryland Express Care Table Top 2 0
Functional Exercise 0 2Simulation Center Table Top 1 1 0
Functional Exercise 4 0 4Registration Table Top 3 0
Functional Exercise 0 3TRU Registered Nurses Table Top 15 0 *** 15 0 *** 15 0 *** 15 0 *** 15 0 ***
Functional Exercise 0 12 0 12 0 12 0 12 0 12
ED, Emergency Department; TRU, Trauma Resuscitation UnitFisher's Exact Test used for significance
Blood Bank Pharmacy Triage Surge Registration
* p < .05, *** p < .001
Acknowledgements
Smith, A.B. (2017). 2016: A historic year for billion-dollar weather and climate disasters in U.S. Retrieved from www.climate.gov › news-features › blogs › beyond-data › 2016-histo...University of Maryland (2017). START Background report. Retrieved from www.start.umd.edu › pubs › START_IdeologicalMotivationsOfTerrorFederal Bureau of Investigation (2018). A study of Active Shooter Cases in the United States. Retrieved from ovc.ncjrs.gov › fact_sheets › 2018NCVRW_MassCasualty_508_QAdini, B., Goldberg, A., Cohen, R., Laor, D., & Bar-Dayan, Y. (2012). Evidence-based support for the all-hazards approach to emergency preparedness. Israel Journal of Health Policy Research. 1(40). pp. 1-7Park H.Y., & Kim, J.S. (2017. Factors Influencing disaster nursing core competencies of emergency nurses. Applied Nursing Research. 37. pp. 1-5
https://www.start.umd.edu/pubs/START_IdeologicalMotivationsOfTerrorismInUS_Nov2017.pdfhttps://ovc.ncjrs.gov/ncvrw2018/info_flyers/fact_sheets/2018NCVRW_MassCasualty_508_QC.pdf
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• The Center for Disease Control, the World Health Organization and The Joint Commission endorse the use of non-pharmacological pain interventions in palliative care1,3,4
• Current research supports the effectiveness of therapeutic music (TM) to reduce chronic pain in palliative care patients5
Background
The purpose of this doctoral project is to improve the quality of pain management for palliative care patients suffering from chronic pain by implementing a therapeutic music (TM) program in an urban long-term care facility
• Short term goal: 70% of facility staff will be trained in the efficacy of TM for palliative care residents and 100% of activities staff will be trained to provide and accurately document TM sessions.
• Long term goal: 90% of PC residents receiving TM will report a significant decrease in chronic pain levels and a high degree of enjoyment with the TM program
Objectives
Methods
Results
Discussion
1. Center for Disease Control and Prevention [CDC]. (2016). Guidelines for prescribing opioids for chronic pain. Retrieved from https://www.cdc.gov/drugoverdose/pdf/guidelines
2. Dowell, D., Haegerich, T.M. & Chou, R. (2016). CDC guideline for prescribing opioids for chronic pain – United States, 2016. JAMA, 315 (15), 1624-1645. doi: 10.1001/jama.2016.1464
3. King, S. E., Hawkins, J. P., & Valentine, J. M. (2016). Management of pain in the terminally ill. Anesthesia and Intensive Care Medicine, 17(11), 555-559. doi: 10.1016/j.mpaic.2016.08.012
4. The Joint Commission. (2017). Pain assessment and management standards for hospitals. R3 Report: Requirement, Rationale, Reference: A complementary publication of The Joint Commission, 11. Retrieved from https://www.jointcommission.org/assets/1/18/R3_Report_Issue_11_Pain_Assessment_8_25_17_FINAL.pdf
5. Wood, C., Cutshall, S. M., Wiste, R. M., Gentes, R. C., Rian, J. S., Tipton, A. M., … & Strand, J. J. (2019). Implementing a Palliative Medicine Music Therapy Program: A Quality Improvement Project. American Journal of Hospice & Palliative Medicine, 36(7), 603–607. https://doi-org.proxy-hs.researchport.umd.edu/10.1177/1049909119834878
References
Figures
Ms. Dawn Worsley, ADC/EDU/MC,CADDCT,CDP, Project Champion
Acknowledgements
• Ten residents were identified for participation in the TM program
• Average participation rate was 50% (n=5), however there was an upward trend from 33% to 69% over the seven-week implementation period
• 100% of participating residents reported a significant decrease in chronic pain (mean 44.3%; p
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• Individuals who have a mental illness have an average 10-year reduction in life expectancy (DHHS, NIH & NIMH, 2015; Walker, McGee, & Druss, 2015)
• Some studies have found a reduction in life expectancy of up to 25 years related to obesity and metabolic syndrome (MS) (Bradshaw & Mairs, 2014)
• Multimodal strategies, including exercise and nutrition interventions, are recommended to improve life expectancy (Ilyas, Chesney & Patel, 2017)
Background
Short-term goal: at least 75% of nursing staff will be trained to facilitate exercise and nutrition groups
Mid-term goals: At least 80% of patients who are obese with a BMI ≥ 30 will:
(1) Verbalize at least one healthy behaviorchange to reduce health risks
(2) Attend at least one exercise group and one nutrition group
(3) Receive an information packet
Long-term goal: improve cardiovascular health among behavioral health patients and reduce premature morbidity and mortality associated with obesity and MS
Goals & Objectives
Methods
Results
Conclusions
Bradshaw, T., & Mairs, H. (2014). Obesity and serious mental ill health: A critical review of the literature.Healthcare (Basel, Switzerland), 2(2), 166–182. doi: 10.3390/healthcare2020166
Ilyas, A., Chesney, E., & Patel, R. (2017). Improving life expectancy in people with serious mental illness: Should we place more emphasis on primary prevention? The British Journal Of Psychiatry: The Journal Of Mental Science, 211(4), 194–197. https://doi.org/10.1192/bjp.bp.117.203240
U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Mental Health. (2015). Post by Former NIMH Director Thomas Insel: Mortality and mental disorders. Retrieved from https://www.nimh.nih.gov/about/directors/thomas-insel/blog/2015/mortality-and-mental-disorders.shtml
Walker, E. R., McGee, R. E., & Druss, B. G. (2015). Mortality in mental disorders and global disease burden implications: A systematic review and meta-analysis. JAMA Psychiatry, 72(4), 334– 341.doi:10.1001/jamapsychiatry.2014.2502
References
Can a multimodal wellness plan be successfully implemented in an inpatient behavioral health unit (BHU)?
Practice QuestionPatient Characteristics (n=251 discharged patients)
Pay special attention to the implementation and data collection barriers identified during this project:• Emphasize empowering nurses for group leader role; • Promote self-confidence and role efficacy for leading groups; • Provide role modeling and frequent coaching; • Ensure that scheduled groups occur as planned; • Provide close monitoring of data collection; • Improve data collection by transitioning from paper audit form to
electronic health record
Nursing Implications
BMI of all discharged patients: (n=251)• Mean = 28.1; SD=6.6; Median= 27.2 ; range= 17.0-48.9
Group Attendance, all discharged patients (n=251)• Attended an exercise group: 25.1% • Attended a healthy nutrition group: 41.0% • Attended both an exercise and a healthy nutrition group: 15.5%• Verbalized intention to make a healthy behavior change: 37.1%
Group Attendance, among obese patients only: BMI ≥ 30 (n=92)• Attended an exercise group: 19.6%• Attended a healthy nutrition group: 39.1% • Attended both an exercise and a healthy nutrition group: 14.1%• Verbalized intention to make a healthy behavior change: 28.3%
No significant relationship between BMI status & group attendance• BMI and Exercise Group: χ² (21, N= 251) = 4.96, p > 0.05• BMI and Nutrition Group: χ² (21, N= 251) = 6.84, p > 0.05• BMI and Both Groups: χ² (21, N= 251) = 2.75, p > 0.05
Longer LOS was associated with higher rates of group attendance • LOS and Exercise Group: χ² (36, N= 251) = 22.46, p < 0.001• LOS and Nutrition Group: χ² (36, N= 251) = 24.57, p < 0.001 • LOS and Both Groups: χ² (36, N= 251) = 23.80, p < 0.001
Higher BMI was associated with lower rates of having verbalized an intention to make a healthy behavior change
• χ² (21, N= 251) = 10.72, p < 0.05Longer LOS was associated with higher rates of patients having verbalized an intention to make a healthy behavior change
• χ² (36, N= 251) = 25.36, p < 0.001
Evidence-based multimodal wellness plan implemented over 12-weeks: • Nurse-led exercise group 3x/ week via chair exercise videos• Nurse-led healthy nutrition group 3x/ week using scripted curriculum• Distribution of exercise & nutrition information packets on admissionData recorded on audit sheet included:• Patient’s first and last initials• Admission and discharge dates• Body mass index (BMI)• Check mark for: Attendance - at least one (1) exercise group Attendance - at least one (1) healthy nutrition group Verbalized intention to make at least one (1) healthy behavior change Receipt of information packet
Implementing Exercise and Healthy Nutrition Groups in an Inpatient Behavioral Health Setting
3.6
35.1
24.7
36.7
Percent (%) of Patients by Body Mass Index (BMI)
Underweight Normal Overweight Obese
• A multimodal wellness plan can be implemented in an inpatient BHU with some benefit
• Despite weekly coaching, staff did not consistently record admission/discharge and group attendance on audit form, which required retrospective chart review to capture missing data (“We recorded our group notes in the EHR, but forgot to completethe audit sheet”)
• Despite administrative leadership, nurse manager support, and assigned groups, nurses did not consistently lead all groups as planned (“too busy on unit”)
• Some nurses expressed lack of confidence in their ability to lead groups (“not our role”; “the psychologist leads groups”)
• Nurses shared that patients enjoyed attending the groups.
Search Strategy/Evidence Appraisal• Search: Non-pharmacological methods to reduce
obesity & MS in people with mental illness (10 studies)• Search Platform: OneSearch, from the University of
Maryland Health Sciences and Human Services Library • Appraisal of level & quality of evidence: Johns
Hopkins Nursing Evidence-based Practice Rating Scale (Newhouse, et al., 2006)
• Project Development: Seven Steps of Evidence-based Practice Model (Melnyk & Fineout-Overholt, 2011)
• Project Implementation: Mobilize, Assess, Plan, Implement and Track (MAP-IT) Framework
Lisa Hoffmann, RN, BSN; [email protected] Fornili, DNP, MPH, RN, CARN, FIAAN ; [email protected]
Evidence Table
12.9
28.9 26.7 30
64.7
24.7
40.8
55.6 55
76.5
4.3
17.122.2 20
47.1
0
10
20
30
40
50
60
70
80
90
0-3 days 4-6 days 7-10 days 11-19 days 20 + days
Perc
ent A
tten
ded
(%)
Group Attendance by LOS
Exercise Nutrition Both Groups
AUTHOR/YEAR
PURPOSE RESULTS EVIDENCE LEVEL/QUALITY
Caemmerer, et al., 2012
To evaluate non-pharmacological interventions for antipsychotic-associated weight gain
Lifestyle interventions were effective; ▼ BMI▼ Waist circumference, percent body fat, weight gain▼ Insulin and Glucose levels▼ Blood lipids▼ Systolic BP Irrespective of duration, individual or group, cognitive behavioral or nutritional interventions, or preventative vs. intervention trials
I (Meta-analysis)A (High Quality)
Magni et al., 2017
To assess a cognitive-behavioral therapy-based intervention on weight gain in patients being treated with antipsychotic medications
Cognitive-behavioral therapy-based intervention was effective;▼ BMI▼ Metabolic risk
III (Controlled Trial)C (Low Quality)
Naslund, et al., 2017
To evaluate lifestyle interventions on weight in overweight and obese adults with mental illnesses using nutrition education with instruction and encouragement to increase physical activity
▼ Weight Irrespective of ≤6-months duration or ≥12-months duration
I (Meta-analysis)A (High Quality)
Singh, et al., 2018
To update the recent evidence on effectiveness of lifestyle intervention for MS in patients with severe mental illness
Lifestyle interventions were effective; ▼ BMI▼ Waist circumferenceIrrespective of duration or treatment setting
I (Meta-analysis)A (High Quality)
Teasdale, et al., 2017
To conduct a systematic review and meta-analysis of nutrition interventions, and to measure anthropometric and biochemical parameters and nutritional intake
Nutrition- based interventions were effective; ▼ BMI▼ Waist circumference▲ effects w/ Dietician led interventions
I (Meta-analysis)B (Good Quality)
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• 96% of anesthesia providers will incorporate theCPG to their patients from PFQ results.
• Limitation is only a few anesthesia providers at thehospital are assigned to robotic surgery OR roomsso sample size will be small.
• The CPG was based on evidence ranging from levelI to level V.
• The POVL CPG is not generalizable and is onlyintended for quality improvement at the institution.
Post-operative Visual Loss Clinical Practice Guideline in the Preoperative Arena
Ming Li, MSN, FNPVeronica Gutchell, DNP, RN, CNS, CRNP
• Post-operative visual loss (POVL) definitiono Unpredictable and devastating injury involving the
patient’s visual system that causes permanent damage ortotal blindness
• 1.9 events per 10,000 case• Cost patients 8.6 days in the hospital vs. 4.1 days• Average hospital cost for patient with POVL is $49,532 vs.
$22,697 for patient without POVL.• Due to the influx of patients undergoing robotic surgeries at
a local hospital, POVL is becoming a critical issue inanesthesia, and a guideline is needed to standardize care.
Background and Problem Statement
The purpose of this doctorate in nursing practice (DNP)project is to implement a evidence-based clinical practiceguideline (CPG) to prevent POVL during the preoperativephase at a local hospital in Baltimore, Maryland.
Purpose
Methods
Results
DiscussionPreoperative POVL CPG
• 90% continued compliance by anesthesia providers to thePOVL prevention clinical practice guideline at the hospital.
• The POVL prevention clinical practice guideline will be apolicy at the hospital and its affiliate hospitals.
• POVL prevention clinical practice guideline will be a newpolicy in the hospital.
Goals
Figures
• Alwon, K., & Hewer, I. (2016). Perioperative vision loss: Considerations and management. AANA Journal, 84(5), 363-370.
• Anesthesiology. (2019). Practice advisory for perioperative visual loss associated with spine surgery 2019: An updated report by the American Society of Anesthesiologists Task Force on perioperative visual loss, the North American Neuro-Ophthalmology Society, and the Society for Neuroscience in Anesthesiology and Critical Care. Retrieved from https://anesthesiology.pubs.asahq.org/article.aspx?articleid=2718348
• Molloy, B. L. (2011). Implications for postoperative visual loss: Steep Trendelenburg position and effects on intraocular pressure. AANA Journal, 79(2), 115-121.
References
The sample size from the PFQs obtained from grand round was n=25. Years ofexperience varied with majority having 5-10 years.AGREE II tool• Domains
• Scope and Purpose (100%), Stakeholder involvement (100%), Rigor ofdevelopment (100%), Clarity of presentation (100%), Applicability (87%), andEditorial Independence (100%)
PFQ• 100% of the providers said the rationale for developing a guideline is clear.• 88% of anesthesia providers strongly agree that the guideline is suitable for patients.• Approval of practice guideline is 84% accepted by anesthesia providers.
• The setting is a local hospital in Baltimore, Maryland.• Developed in collaboration with an expert panel consisting of chief
anesthesiologist, chief CRNA, and doctorate in nursing practice (DNP) students.• The Appraisal of Guidelines for Research, and Evaluation (AGREE) II tool was
used by the expert panel to analyze the quality and applicability of the CPG.• Once finalized by the expert panel, the CPG was presented to the local hospital’s
anesthesia providers at a grand round.• A Practitioner Feedback Questionnaire (PFQ) was distributed and feedback was
collected anonymously to determine the usefulness of the CPG.• The responses and recommendations analyzed• A finalized POVL prevention CPG was presented and disseminated to the local
hospital’s anesthesia department.
Conclusion• Anesthesia providers at the site are more aware of the
risk factors associated with POVL during roboticsurgeries.
• Educated the providers on evidence-based solutionsthat can be applied to their practices in regards toPOVL prevention in the preoperative phase.
• Expert panel are assigned as change champions tohelp promote usage of POVL prevention CPG.
• New quality improvement project will be theimplementation of CPG.
• Yearly survey of literature should be conducted tohelp improve the POVL CPG.
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Electronic Patient Acuity Scoring Scale to Improve Falls and Call Light Responsiveness
Sasha Nanji, BSN, RNRosemarie DiMauro Satyshur PhD, RN
University of Maryland School of Nursing
• Falls affect about 700,000 to 1,000,000 patients a year in hospitals in the United States (AHRQ, 2013). Over one-third of falls end in injury, such as broken
bones and head injury (AHRQ, 2013) Healthcare care system in the United States spent about
$50 billion on falls (CDC, 2019). Decreased patient falls and injury rates are correlated
with quicker call light responsiveness time (Tzeng, Titler, Ronis, & Yin, 2012).
• Charge nurses on an in-patient medicine unit at a large academic hospital use an inadequate patient acuity tool to make nursing assignments, increasing beside nurses’ workload, and affecting patient outcomes.
Background
Methods
• Patient falls affect millions of people nationwide, cost billions of dollars annually, and lead to serious injury.
• E-PASS lead to reduced patient falls and improved nurse responsiveness to call lights.
• The findings of this study are consistent with other studies in which patient acuity tools are essential to decrease patient falls and improve timeliness of patient care.
• The participants in this QI project were a convenience sample of 36 nurses from an in-patient medicine unit specializing in telemetry within a large academic hospital setting. Findings are not generalized to other settings.
• Recommendations: Inter-rater reliability should be considered to ensure accuracy when completing the tool. Data should be collected over a longer period of time. Further inquiry into the nature of patient falls, and why they are occurring may be necessary.
Discussion
Conclusions
References
• The E-PASS was developed by the Armstrong Institute and the Department of Medicine at the hospital (Johns Hopkins Hospital, 2019).
• The QI project was conducted over 12 weeks. Staff education was completed in the first 4 weeks. Nurse competency checklist was conducted to ensure
competency on use of the E-PASS. Implementation of E-PASS took place over the next 8 weeks. Audit tools were used to evaluate the effects of E-PASS
throughout implementation and to track compliance.
• Nurses’ knowledge improved after an education session on the benefits of using the E-PASS, goals of the project, and how to use the tool.
• 100% of nurses completed the nurse competency checklist, suggesting that the E-PASS was easy to use and implement.
• The number of patient falls a month into implementation (October,2019) was 2 falls, lower than the previous month (September, 2019) 5 falls.
• The rate of nurse responsiveness to call lights when patients wanted a month into implementation (October, 2019) was 100%, greater than the previous month (September, 2019) 0%.
• Showed feasibility of the E-PASS to create nurse assignments to improve patient falls and nurse responsiveness to call lights.
• Further education is necessary to ensure proper knowledge and usage of the tool to ensure sustainability and efficacy of the tool and nurse assignments based on acuity to improve patient outcomes.
.
• Agency for Healthcare Research and Quality (AHRQ). (2013). Preventing falls in hospitals. Retrieved from https://www.ahrq.gov/professionals/systems/hospital/fallpxtoolkit/fallpxtkover.html
• Centers for Disease Control and Prevention (CDC) (2019). Falls data. Retrieved from https://www.cdc.gov/homeandrecreationalsafety/falls/fallcost.html
• Sobaski, T. (2018). Addressing patient acuity and nurse staffing issues in the acute care setting: A review of the literature. International Journal of Nursing Studies. 3.10.20849/jjsnv3i3431
• Tzeng, H. M., Titler, M. G., Ronis, D. L., & Yin, C. Y. (2012). The contribution of staff call light response time to fall and injurious fall rates: an exploratory study in four US hospitals using archived hospital data. BMC health services research, 12, 84. https://doi.org/10.1186/1472-6963-12-84
Objectives• The purpose of this quality improvement (QI) project is to
implement the revised version of the Electronic Patient Acuity Scoring Scale (E-PASS) to improve charge nurses’ ability to create nurse-patient assignments thus decreasing the number of patient falls and improving nurse responsiveness to call lights on an inpatient medicine unit.
• Short-Term Goals: Educate 100% of registered nurses on the E-PASS. 100% of nurses will complete the E-PASS by week 5. 100% of charge nurses will use E-PASS scores to create
nurse registered assignments by week 5.
• Long-Term Goals: Implementation of the E-PASS will result in decreased
patient falls and increased nurse responsiveness to call lights by week 12.
E-PASS will be implemented as the standard of practice on the in-patient medicine unit.
Figures
Results• 80% of staff nurses completed the education training (goal 100%)
100% of nurses completed the nurse competency checklist• Short-term goals to be achieved by week 5
100% of nurses will complete the E-PASS (goal 100%) 100% of charge nurses will use E-PASS scores to make nurse assignments
(goal 100%)• Long-term goals to be achieved by week 12
E-PASS will decrease patient falls and increase nurse responsiveness to call lights (goal achieved)
E-PASS will be implemented as the standard of practice on the in-patient medicine unit (goal achieved)
• The number of patient falls for three months prior to the E-PASS (July, August, and September, 2019) was 0, 3, and 5 falls respectively. The number of falls for October and November 2019 was 2 and 1 falls respectively.
• The average number of patient falls prior to implementation was 2.67 compared to 1 patient fall after implementation. Patient falls scores ranged from 0-5.
• The rate of nurse responsiveness to call lights when patients wanted for three months prior to the E-PASS (July, August, and September 2019) was 70%, 0%, and 0% respectively. The rate of nurse responsiveness to call lights when patients wanted for October and November 2019 was 100% and 50% respectively.
• The average rate of nurse responsiveness to call lights when patients wanted prior to implementation was 23% compared to 75% after implementation. Nurse responsiveness to call lights when patients wanted scores ranged from 0-100.
https://www.ahrq.gov/professionals/systems/hospital/fallpxtoolkit/fallpxtkover.htmlhttps://www.cdc.gov/homeandrecreationalsafety/falls/fallcost.htmlhttps://doi.org/10.1186/1472-6963-12-84
-
Implementing Posttraumatic Stress Disorder Screening at an Adult Substance Use Disorder Clinic
Jemima Pierre-Jacques, BSN, RN, Kristen Rawlett PhD, FNP-BC, Lisa Crear Carrier MSW, LCSW-C, and Johari M. Massey PhD
Problem Statement
PurposeImplementation of the PC-PTSD-5 tool among substance use disorder adult patients to evaluate its effectiveness to trigger referral for additional mental health assessment.
Short Term Goals• By December 13th 2019, champions will perform PTSD screening on
100% of eligible patients enrolled in the substance use disorder clinic, provide PTSD education to 100% of patients screened, and appropriately refer 100% of eligible patients based on PC-PTSD-5 scores for further mental health assessments.
Long Term Goals• Within one year post implementation, PTSD screening and score-based
mental health referral will become standard practice.
Methods
• Of the 116 eligible patients, 62 were screened for PTSD.
• A chi-square test of independence was performed to examine the relation between PC-PTSD-5 score and referral for further health assessment.
• Patients with a higher PC-PTSD-5 score were more likely than those with a lower score to receive a referral. The relation between the variables was significant, X2 (2, N = 62) = 11.2, p= .0037.
• Education was provided to 98% of the patients screened for PTSD.
Results
Discussion
Figures References
Design: Quality improvement
Setting: An urban substance use disorder clinic within an integrated behavioral health center
Population: Adults 18 years and older enrolled in substance use treatment.
Screening Tool: The Primary Care PTSD Screen for DSM-5 (PC-PTSD-5)
Implementation Procedures:
• Timeframe: Twelve weeks, from September 23, 2019 to December 13, 2019
• Screening: New patients received PC-PTSD-5 screening during the intake process, previously enrolled
patients during individual sessions with substance use counselors.
• Education: Patients screened received education on PTSD symptoms.
• Referral: PC-PTSD-5 scores of 3 or greater warranted referral for additional mental health assessment
within 48 hours, scores less than 3, within 7 business days.
• Obtain buy-in from stakeholders.
• Identify possible causes of
resistance from staff.
• Identify Implementation
champions.
• Assess education needs of team.
• Identify appropriate PTSD
screening tool.
• Develop referral protocol and
audit tool for progress monitoring.
Unfreeze
• Champions training.
• Implement PC-PTSD-5 screening
tool.
• Implement PC-PTSD-5 score
based referral to behavioral health
treatment.
• Continue assessing and addressing
barriers to implementation.
• Performing chart audits to evaluate
effectiveness of referral process.
Change • Integrate PTSD screening in routine assessment protocol.
• Include PTSD screening
education as part of annual
competency for clinicians.
• Develop Trauma-Focused
Therapy Groups.
Refreeze
Lewin’s Change Theory Gielen, N., Havermans, R. C., Tekelenburg, M., & Jansen, A. (2012). Prevalence of post-traumatic stress disorder among patients with substance use disorder: It is higher than clinicians think it is. European Journal ofPsychotraumatology. doi:10.3402/ejpt.v3i0.17734
Prins, A., Bovin, M. J., Smolenski, D. J., Marx, B. P., Kimerling, R., Jenkins-Guarnieri, M. A.,… Tiet, Q. Q. (2016). The Primary Care PTSD Screen for DSM-5 (PC-PTSD-5): Development and evaluation within a veteran primary care sample. Journal of General Internal Medicine. doi:10.1007/s11606-016-3703-5
van Dam, D., Vedel, E., Ehring, T., & Emmelkamp, P. M. G. (2012). Psychological treatments for concurrent posttraumatic stress disorder and substance use disorder: A systematic review. Clinical Psychology Review. doi:10.1016/j.cpr.2012.01.004
• Champions reported that the PC-PTSD-5 tool was easy to administer, time efficient, did not impede workflow, and was well received by most patients.
• Screening promoted discussions about available mental health services and provided objective data for skeptical clients.
• Resistance from patients due to self-stigma, and lack of screening compliance of some counselors were among identified barriers.
Project Purpose & Goals
Patients with substance use disorders are three times more likely to have co-occurring posttraumatic stress disorder (PTSD). Unaddressed PTSD has been linked to increased symptoms severity and adverse outcomes.
An urban substance use disorder clinic within an integrative behavioral health center lacked screening for PTSD. Low utilization of mental health services due to lack of a formal referral process was revealed by internal evidence obtained in February 2019. A need for PTSD screening was identified to close this practice gap.
The Primary care PTSD screen for the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (PC-PTSD-5) was identified as an evidenced-based, cost-efficient, reliable and valid instrument to identify patients at risk for PTSD.
Early identification of PTSD risk may facilitate referral to mental health services and improve treatment outcomes in substance use disorder patients.
High PC-PTSD-5 (Score ≥ 3)
Low PC-PTSD-5 score (Score1-2)
PC-PTSD-5 Score Zero (Score= 0)
42%
21%
37%
PERCENTAGE OF PC-PTSD-5 SCORES
AcknowledgementsCassandra Williams, CPRS; Sharon Servance, CAC-AD; Kem Johnson, M.Ed., CSC-AD;
and George Barksdale CSC-AD.
Theoretical Framework
Table 2.
Observed Data
Zero PC-PTSD-5
Score (N) Low PC-PTSD-5 Score (N)
High PC-
PTSD-5
Score (N)
Grand
Total
MH
Referral
Received 8 (23%) 6 (17%) 21 (60%)
35
(100%)
No MH
Referral 15 (55.5%) 7 (26 %) 5 (18.5%)
27
(100%)
Grand
Total 23 (37%) 13 (21%) 26 (42%)
62
(100%)
Median
Goal
0
20
40
60
80
100
120
8/30/2019
9/6/2019
9/13/2019
9/20/2019
9/27/2019
10/4/2019
10/11/2019
10/18/2019
10/25/2019
11/1/2019
11/8/2019
11/15/2019
11/22/2019
11/29/2019
12/6/2019
12/13/2019
% Eligible Screened Patients Referred to Behavioral Health
% Referral
Conclusions• Implementation of PC-PTSD-5 screening tool and score-based mental health
referral recommended as standard practice throughout the organization.
• Digitalization and integration of tool in the electronic health record could facilitate compliance and ensure sustainability.
• Future projects may assess the effectiveness of trauma specific interventions to decrease symptoms severity in patients with high PC-PTSD-5 scores.
Chart1
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% of Eligible SUD Patients screened for PTSD
Values
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Median
Goal
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Run Chart
Run Chart Template
v. 2.0 · 5-30-2016Developed by Richard Scoville, PhD. ([email protected])
Vertical Axis Label% of Eligible SUD Patients screened for PTSD
Graph LabelPTSD Screening among Substance Use Disorder Patients
Date / ObservationValueMedianGoalExtend Phase = 'x'New Phase = 'n'
8/30/1904010023
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&R&F!&A&D &T • Page &P of &N
Enter dates or observation numbers into the green cells at right. (clear the sample data before you begin)
Enter your data values into the blue cells. Goal values are optional.
Don't leave any blank cells in the Date/Observation column.
Enter an 'X' into the orange column to freeze and extend the median
Enter a 'N' into the orange column to create a new median (phase)
Enter your graph title and y axis label into the cells provided.
Use regular Excel commands to configure the graph.
See sheet 'Interpreting Charts' for information about interpreting your charted data
Run Chart
40
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40
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40
% of Eligible SUD Patients screened for PTSD
Values
Median
Goal
Extend
PTSD Screening among Substance Use Disorder Patients
Median
Goal
Interpreting Run Charts
Interpreting Run Charts
Run Charts Rules Summary
Signals of non-random patterns:
1.Shift -6 or more consecutive points either all
above or all below the median
2.Trend -5 or more consecutive points all going
up or all going down.
3.Runs -Too few or too many runs. 4.Astronomical point -A point obviously different
from the rest, "everyone agrees." This rule is subjective, unlike rules 1 -3, which are probability based.
1/3/20153
See Perla et al. (2010) for further explanation and details
Expected Runs Table
1/3/20152
1039
11310
12311
13411
14412
15512
16513
17513
18614
19615
20616
21716
22717
23717
24818
25818
Total number of
data points on
the run chart
that do not fall
on the median
Lower limit for
the number of
runs (< than this
number runs is
'too few')
Upper limit for
the number of
runs (> than this
number runs is
'too many')
N not on medianLower limitUpper limit
26919
271019
281020
291020
301121
311122
321123
331223
341224
351224
361325
371325
381426
391426
401527
411527
421628
431628
441729
451730
461731
471831
481832
491932
501933
512033
522034
532134
542135
552235
562235
572336
582337
592438
602438
Checking for too many or too few runs on a run chart. Table is based on about a 5% risk of failing the run test for random patterns of data.Source: Table 1, Perla et al. (2010), p. 49.
Chart1
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4379850100
4380550100
4381250100
% Referral
Values
Median
Goal
Extend
% Eligible Screened Patients Referred to Behavioral Health
Median
Goal
0
0
0
0
100
80
50
100
80
50
75
67
75
50
33
50
Run Chart
Run Chart Template
v. 2.0 · 5-30-2016Developed by Richard Scoville, PhD. ([email protected])
Vertical Axis Label% Referral
Graph Label% Eligible Screened Patients Referred to Behavioral Health
Date / ObservationValueMedianGoalExtend Phase = 'x'New Phase = 'n'
8/30/1905010023
9/6/19050100
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0100
&R&F!&A&D &T • Page &P of &N
Enter dates or observation numbers into the green cells at right. (clear the sample data before you begin)
Enter your data values into the blue cells. Goal values are optional.
Don't leave any blank cells in the Date/Observation column.
Enter an 'X' into the orange column to freeze and extend the median
Enter a 'N' into the orange column to create a new median (phase)
Enter your graph title and y axis label into the cells provided.
Use regular Excel commands to configure the graph.
See sheet 'Interpreting Charts' for information about interpreting your charted data
Run Chart
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
% Referral
Values
Median
Goal
Extend
% Eligible Screened Patients Referred to Behavioral Health
Median
Goal
Interpreting Run Charts
Interpreting Run Charts
Run Charts Rules Summary
Signals of non-random patterns:
1.Shift -6 or more consecutive points either all
above or all below the median
2.Trend -5 or more consecutive points all going
up or all going down.
3.Runs -Too few or too many runs. 4.Astronomical point -A point obviously different
from the rest, "everyone agrees." This rule is subjective, unlike rules 1 -3, which are probability based.
1/3/20153
See Perla et al. (2010) for further explanation and details
Expected Runs Table
1/3/20152
1039
11310
12311
13411
14412
15512
16513
17513
18614
19615
20616
21716
22717
23717
24818
25818
Total number of
data points on
the run chart
that do not fall
on the median
Lower limit for
the number of
runs (< than this
number runs is
'too few')
Upper limit for
the number of
runs (> than this
number runs is
'too many')
N not on medianLower limitUpper limit
26919
271019
281020
291020
301121
311122
321123
331223
341224
351224
361325
371325
381426
391426
401527
411527
421628
431628
441729
451730
461731
471831
481832
491932
501933
512033
522034
532134
542135
552235
562235
572336
582337
592438
602438
Checking for too many or too few runs on a run chart. Table is based on about a 5% risk of failing the run test for random patterns of data.Source: Table 1, Perla et al. (2010), p. 49.
-
• Hypoglycemia in newborns 37- 40 weeks gestation contributes to poor neurodevelopment outcomes and affects 15 out of 100 newborns.
• First line treatment is formula feeding, and/or transfer to the Neonatal Intensive Care Unit (NICU) for intravenous (IV) glucose.o These options are costly and disrupt the
breastfeeding dyad.
Background Results Findings with Implications
Goals
Bennett, C., Fagan, E., Chaharbakhshi, E., Zamfirova, I., & Flicker, J. (2016). Implementing a Protocol Using Glucose Gel to Treat Neonatal Hypoglycemia. Nursing for Women’s Health, 20(1), 64–74.Harris, D. L., Weston, P. J., Signal, M., Chase, J. G., & Harding, J. E. (2013). Dextrose gel for neonatal hypoglycemia (the Sugar Babies Study): a randomized, double-blind, placebo-controlled trial. Lancet (London, England), 382(9910), 2077–2083.
Conclusions
Implementation Methods
Bibliography
Implementation of Dextrose Gel for AsymptomaticHypoglycemiaAnjana Solaiman, RN, MS, IBCLC
Barbara Wise, PhD, RN, CPNP-AC/PCJennifer Fitzgerald, DNP, NNP-BC
q Short Term - Implement 40% buccal dextrose gel (200mg/kg) in conjunction with feeding as the first line treatment of asymptomatic hypoglycemia in newborns >37 weeks in the newborn nursery at an academic medical center in the Mid-Atlantic.
q Long Term - Achieve treatment success in all newborns who receive dextrose gel.
• Quality improvement (QI) project alignment with organizational breastfeeding goals
• Modified neonatal hypoglycemia clinical practice guideline (CPG) to include dextrose gel
• Developed order set and documentation in electronic health record (EHR)
• Collaborated with pharmacy to stock gel• Created and launched online training with post
test utilizing hospitals educational platform• In person buccal gel trainings• QI data collected during a 12-week period
• Nurses hesitant to utilize buccal gel due to lack of experience and knowledge.o Training sessions offered in person.
• Treatment success was attained in 87.5% of newborns. o Treatment failure occurred in newborns who
did not meet the CPG inclusion criteria with initial blood glucose levels of
-
Problem Description
Short Term Goals:• Conduct literature search to determine best
practices for optimal recovery following cesarean delivery
• Create CPG with stakeholder support and acceptance among staff
Long Term Goals:• Reduce length of hospital stay• Reduce incidence of postoperative complications• Improve maternal satisfaction scores
Purpose and Anticipated Outcomes
CPG: Postoperative Recommendations PFQ Results
Discussion
Implementation Strategies
AGREE II Tool Results
Conclusion
Enhanced Recovery After Cesarean DeliveryClinical Practice Guideline (CPG): Postoperative Interventions
Alexandra Wali, BSNProject Faculty Advisor: Veronica Amos PhD, CRNA, PHCNS-BC
Clinical Site Representative: Christina Mack, MDUniversity of Maryland, Baltimore, School of Nursing
Suggested Next Steps:• Evaluate implementation
Plans for Sustainability:• Continued stakeholder support• Ongoing staff education • Auditing/Data collection/Feedback• Appoint change champions to facilitate long-term adherence• Revise CPG if new evidence supports modification of current recommendations
Phase I• Setting: Tertiary hospital in Maryland• Population: Women undergoing elective, uncomplicated cesarean deliveries• Stakeholders:
• Director of Obstetrical Anesthesia• Director of Maternal & Fetal Medicine
• CPG Evaluation: AGREE II Tool• CPG presented to stakeholders for evaluation/feedback via AGREE II Tool• Incorporated recommendations from stakeholders into CPG
Phase II• Anesthesia Staff Education + Survey
• Practitioner Feedback Questionnaire (PFQ) and demographic survey to determine usability and acceptance of CPG
Phase III• Data analysis: AGREE II Tool results, PFQ results, and demographic data• Descriptive and statistical analysis
Cesarean Deliveries:• The most common surgical procedure • Each year in the United States, cesarean deliveries account for 30% of all births• Cesarean deliveries are associated with:
• Prolonged length of stay • Maternal dissatisfaction• Postoperative complications• Delayed functional and physiological recovery
Enhanced Recovery After Surgery (ERAS)• Perioperative interventions proven to:
• Improve surgical outcomes• Decrease length of stay• Reduce hospital costs• Optimize perioperative care
PFQ Demographic Data:• 39 surveys distributed to staff during grand rounds (Anesthesiologists, Certified Registered Nurse Anesthetists, Student Registered Nurse Anesthetists)• 17 surveys completed• Years of anesthesia experience:
• 0-3 years: 64.7% of respondents• ≥ 4 years: 35.3% of respondents
Strengths:• Evidence Strength and Quality• Strong stakeholder support• Widespread acceptance
Limitations:• Institution specific• 43.6% response rate• Lack of feedback generated from ancillary specialties: Obstetrical surgeons; Labor & Delivery staff; Nursing staff
Purpose:• Create and evaluate an enhanced recovery after caesarean delivery
clinical practice guideline (CPG) to optimize recovery and standardize postoperative care
Early Foley Catheter Removal:Evidence: Reduction of urinary frequency and incidence of microscopic hematuria; Earlier onset time for postop mobilization Recommendation: Remove the urinary catheter within 2 hours following cesarean delivery
Early Oral Intake:Evidence: Bowel sounds returned 9.2 hrs earlier, time to passing flatus occurred 10 hrsearlier, and bowel evacuation occurred 14.6 hrs earlier Recommendation: Initiate a solid diet within 2 hours after cesarean delivery, as tolerated by the parturient
Gum Chewing:Evidence: Improves GI recovery with faster return of bowel movements, intestinal sounds, passing of flatus, and passing of feces; Reduced postoperative length of stayRecommendation: Initiate sugar-free gum chewing 2 hours after cesarean delivery as tolerated by the parturient
97.91%87.5%
39%
75% 78%
Quality Acceptance Applicability ComparativeValue
OutcomeVariable
Perc
enta
ge
References • El-Mazny, A., El-Sharkawy, M., & Hassan, A. (2014). A prospective randomized clinical trial comparing immediate versus
delayed removal of urinary catheter following elective cesarean section. European Journal of Obstetrics and Gynecology, 181, 111–114. https://doi-org.proxy-hs.researchport.umd.edu/10.1016/j.ejogrb.2014.07.034
• Hsu, Y.-Y., Hung, H.-Y., Chang, S.-C., & Chang, Y.-J. (2013). Early oral intake and gastrointestinal function after cesarean delivery: a systematic review and meta-analysis. Obstetrics and Gynecology, 121(6), 1327–1334. https://doi-org.proxy-hs.researchport.umd.edu/10.1097/AOG.0b013e318293698c
• Completed by stakeholders with favorable results• Stakeholders strongly recommend utilization of CPG in clinical practice
AGREE II Tool Domain Percentage Score
Scope & Purpose 91.7%
Stakeholder Involvement 94.4%
Rigor of Development 86.4%
Clarity of Presentation 91.7%
Applicability 83.3%
Editorial Independence 100%
Overall Guideline Assessment Score 91.7%
PresenterPresentation NotesFinal (as of now)
Boyajian Toni Final DNP Project PosterSlide Number 1
DiNardo Theresa Final DNP Project PosterSlide Number 1
Goode Julie Final DNP Project PosterHoffmann Lisa Final DNP Project PosterSlide Number 1
Li Ming Final DNP Project PosterSlide Number 1
Nanji Sasha Final DNP Project PosterSlide Number 1
Pierre-Jacques Jemima Final DNP Project PosterSlide Number 1
Solaiman Anjana Final DNP Project PosterWali Alexandra Final DNP Project PosterSlide Number 1