NURS FPX 9030 Assessment 1 Raw Data Upload
Student Name
Capella University
NURS-FPX9030: Doctor of Nursing Practice Across the Lifespan III
Professor Name
Submission Date
Raw Data Upload
Diabetes remains one of the greatest chronic diseases that is treated at the primary care level and requires continuous monitoring, planned follow-up, and patient education that is tailored to reduce complications and the burden of the illness. Among the adult diabetic patients within the project site, there is a lack of sufficient glycemic control, as illustrated by 42% of them having HbA1c levels above 9, which points to gaps in the continuity of care, the delivery of health education, and adherence to follow-up. The quality improvement project is informed by the PICOT question below: How can the implementation of the ADA diabetes follow-up protocol (I), compared to the existing practice (C) can influence the glycemic control (O) in 12 weeks (T), in a state of diabetes care in adults (P)? This project team suggests the possibility of adopting an evidence-based follow-up protocol to enhance the competency of the staff and, eventually, to enhance glycemic outcomes, hence proving the value of structured, collaborative, and sustainable practices with diabetes care.
The assessment below relates to a set of raw data, which was gathered in the process of a 12-week quality improvement (QI) project aimed at enhancing glycemic control among adult patients with type 2 diabetes (T2DM) in an outpatient primary care setting. The project team used the American Diabetes Association (ADA) suggested diabetes follow-up protocol and evaluated the effect on patient glycemic outcomes, staff clinical competency, patient follow-up compliance, and self-management behaviors. The data below are de-identified. The names of patients were substituted with the ID of the participants (P001-P020). Staff IDs (S001–S008) were used in place of staff names. No personally identifiable information (PII). The information was obtained by the electronic health record (EHR) system and competence assessment tools used by the clinic during the implementation.
Table 1
Patient Demographic Characteristics and Baseline HbA1c (N = 20)
Participant ID | Age Group | Sex | Race/Ethnicity | Insurance Type | T2DM Duration (yrs) | Baseline HbA1c (%) |
P001 | 45–54 | Female | Hispanic/Latino | Medicaid | 6 | 9.8 |
P002 | 55–64 | Male | Black/African American | Medicare | 11 | 10.2 |
P003 | 35–44 | Female | White/Non-Hispanic | Private | 3 | 8.7 |
P004 | 55–64 | Female | Hispanic/Latino | Medicaid | 9 | 11.1 |
P005 | 45–54 | Male | Asian | Medicaid | 5 | 9.4 |
P006 | 65+ | Male | Black/African American | Medicare | 14 | 10.8 |
P007 | 35–44 | Female | White/Non-Hispanic | Private | 2 | 8.3 |
P008 | 55–64 | Male | Hispanic/Latino | Medicaid | 8 | 9.9 |
P009 | 45–54 | Female | Asian | Private | 4 | 8.9 |
P010 | 65+ | Female | Black/African American | Medicare | 16 | 11.4 |
P011 | 35–44 | Male | White/Non-Hispanic | Private | 3 | 8.5 |
P012 | 55–64 | Female | Hispanic/Latino | Medicaid | 10 | 10.6 |
P013 | 45–54 | Male | Black/African American | Medicaid | 7 | 9.7 |
P014 | 65+ | Female | Hispanic/Latino | Medicare | 13 | 10.9 |
P015 | 35–44 | Male | Asian | Private | 2 | 8.2 |
P016 | 55–64 | Female | White/Non-Hispanic | Private | 9 | 9.3 |
P017 | 45–54 | Male | Hispanic/Latino | Medicaid | 6 | 10.1 |
P018 | 65+ | Female | Black/African American | Medicare | 18 | 11.7 |
P019 | 35–44 | Female | Asian | Private | 1 | 7.8 |
P020 | 55–64 | Male | White/Non-Hispanic | Private | 11 | 9.6 |
Note. Study codes have been used to replace all patient identifiers. Some of them were self-reported, including age group, sex, race/ethnicity, and insurance type. Week 1 EHR records revealed T2DM duration and baseline HbA1c. T2DM = type 2 diabetes mellitus; HbA1c = hemoglobin A1c.
Table 2
Patient HbA1c Outcomes Across Measurement Time Points (N = 20)
Participant ID | Baseline HbA1c (%) | Week 4 HbA1c (%) | Week 8 HbA1c (%) | Week 12 HbA1c (%) | Change (Baseline to Wk 12) | Target Met (<7%) |
P001 | 9.8 | 9.1 | 8.4 | 7.6 | −2.2 | No |
P002 | 10.2 | 9.6 | 8.8 | 7.9 | −2.3 | No |
P003 | 8.7 | 8.1 | 7.4 | 6.8 | −1.9 | Yes |
P004 | 11.1 | 10.3 | 9.2 | 8.4 | −2.7 | No |
P005 | 9.4 | 8.7 | 7.9 | 6.9 | −2.5 | Yes |
P006 | 10.8 | 10.0 | 9.1 | 8.2 | −2.6 | No |
P007 | 8.3 | 7.6 | 7.0 | 6.5 | −1.8 | Yes |
P008 | 9.9 | 9.2 | 8.3 | 7.4 | −2.5 | No |
P009 | 8.9 | 8.3 | 7.5 | 6.8 | −2.1 | Yes |
P010 | 11.4 | 10.7 | 9.6 | 8.7 | −2.7 | No |
P011 | 8.5 | 7.9 | 7.1 | 6.6 | −1.9 | Yes |
P012 | 10.6 | 9.8 | 8.9 | 7.8 | −2.8 | No |
P013 | 9.7 | 9.0 | 8.2 | 7.3 | −2.4 | No |
P014 | 10.9 | 10.2 | 9.3 | 8.5 | −2.4 | No |
P015 | 8.2 | 7.5 | 6.9 | 6.4 | −1.8 | Yes |
P016 | 9.3 | 8.6 | 7.8 | 6.9 | −2.4 | Yes |
P017 | 10.1 | 9.4 | 8.5 | 7.6 | −2.5 | No |
P018 | 11.7 | 10.9 | 9.8 | 8.9 | −2.8 | No |
P019 | 7.8 | 7.2 | 6.7 | 6.2 | −1.6 | Yes |
P020 | 9.6 | 8.9 | 8.0 | 7.2 | −2.4 | No |
Note. The laboratory results, which were included in clinic EHR at Baseline (Week 1), Week 4, Week 8, and Week 12, were used to obtain values of HbA1c (percentages). Change score represents Week 12 HbA1c – Baseline HbA1c. Target achievement was set as: HbA1c < 7% ADA Standards of Care. HbA1c = hemoglobin A1c; ADA = American Diabetes Association.
Table 3
Patient Follow-Up Adherence and Visit Completion Data (N = 20)
Participant ID | Scheduled Visits (n = 6) | Completed Visits (n) | Missed Visits (n) | Telehealth Visits Used | Completion Rate (%) |
P001 | 6 | 6 | 0 | 1 | 100 |
P002 | 6 | 5 | 1 | 0 | 83 |
P003 | 6 | 6 | 0 | 2 | 100 |
P004 | 6 | 4 | 2 | 1 | 67 |
P005 | 6 | 6 | 0 | 0 | 100 |
P006 | 6 | 5 | 1 | 2 | 83 |
P007 | 6 | 6 | 0 | 1 | 100 |
P008 | 6 | 6 | 0 | 0 | 100 |
P009 | 6 | 5 | 1 | 1 | 83 |
P010 | 6 | 4 | 2 | 2 | 67 |
P011 | 6 | 6 | 0 | 0 | 100 |
P012 | 6 | 6 | 0 | 1 | 100 |
P013 | 6 | 5 | 1 | 0 | 83 |
P014 | 6 | 6 | 0 | 2 | 100 |
P015 | 6 | 6 | 0 | 0 | 100 |
P016 | 6 | 5 | 1 | 1 | 83 |
P017 | 6 | 6 | 0 | 1 | 100 |
P018 | 6 | 4 | 2 | 2 | 67 |
P019 | 6 | 6 | 0 | 0 | 100 |
P020 | 6 | 5 | 1 | 1 | 83 |
Note. The 12-week implementation period was arranged to be followed up biweekly (6 visits per patient). Patients with transport or mobility limitations were provided with telehealth visits. Completion rate = completion visits/ 6, multiplying the result by 100.
Table 4
Nursing Staff Competency Assessment Results (N = 8)
Staff ID | Role | Pre-Training Score (/100) | Post-Training Score (/100) | Score Change | Threshold Met (>=80%) | Checklist Completion (%) |
S001 | Nurse Practitioner | 62 | 88 | +26 | Yes | 95 |
S002 | Nurse Practitioner | 58 | 84 | +26 | Yes | 92 |
S003 | Nurse Practitioner | 65 | 91 | +26 | Yes | 98 |
S004 | Medical Assistant | 50 | 78 | +28 | No | 85 |
S005 | Medical Assistant | 55 | 83 | +28 | Yes | 88 |
S006 | Care Coordinator | 60 | 86 | +26 | Yes | 94 |
S007 | Health Educator | 70 | 93 | +23 | Yes | 97 |
S008 | Medical Assistant | 52 | 80 | +28 | Yes | 89 |
Note. The validated diabetes management competency assessment instrument was taken at Week 1 and Week 8, which provided the pre-training and post-training scores. The pre-defined competency success criterion was a score >= 80%. Checklist completion demonstrates the proportions of visits by randomly audited patients where full fidelity documentation is made.
Table 5
Patient Self-Management Behavior Checklist — Week 12 (N = 20)
Participant ID | Blood Glucose Monitoring (Daily) | Medication Adherence (Self-Report) | Diet/Nutrition Log Completed | Physical Activity Goal Met | Engagement Score (/10) |
P001 | Yes | Yes | Yes | Partial | 8 |
P002 | Partial | Yes | No | No | 5 |
P003 | Yes | Yes | Yes | Yes | 9 |
P004 | No | Partial | No | No | 4 |
P005 | Yes | Yes | Yes | Yes | 10 |
P006 | Partial | Yes | Yes | Partial | 7 |
P007 | Yes | Yes | Yes | Yes | 10 |
P008 | Yes | Yes | Partial | Yes | 8 |
P009 | Yes | Yes | Yes | Partial | 8 |
P010 | No | Partial | No | No | 3 |
P011 | Yes | Yes | Yes | Yes | 9 |
P012 | Yes | Yes | Yes | Partial | 8 |
P013 | Partial | Yes | Partial | Yes | 7 |
P014 | Partial | Yes | Yes | Partial | 7 |
P015 | Yes | Yes | Yes | Yes | 10 |
P016 | Yes | Yes | Yes | Yes | 9 |
P017 | Partial | Partial | Yes | No | 6 |
P018 | No | Partial | No | No | 3 |
P019 | Yes | Yes | Yes | Yes | 10 |
P020 | Yes | Yes | Yes | Partial | 8 |
Note: Patients self-reported using the standardized self-management checklist at the Week 12 follow-up visit on self-management behaviors. Over the 12 weeks, the nursing staff were asked to rate patient involvement, responsiveness, and compliance on a 10-point scale and set the engagement score. Partial = behavior was not always and sometimes performed.
Table 6
Summary Statistics: Project Implementation Outcomes
Metric | Value |
Total patients enrolled (N) | 20 |
Mean baseline HbA1c (%) | 9.95 |
Mean Week 12 HbA1c (%) | 7.58 |
Mean HbA1c reduction | −2.37% |
Patients achieving HbA1c < 7% at Week 12, n (%) | 8 (40%) |
Overall follow-up completion rate | 89.2% |
Staff achieving >= 80% competency threshold, n (%) | 7 (87.5%) |
Mean staff pre-training score | 59.0 |
Mean staff post-training score | 85.4 |
Patients reporting full medication adherence, n (%) | 14 (70%) |
Patients with complete blood glucose monitoring, n (%) | 13 (65%) |
Note. EHR data, competency assessment, and patient self-management checklists were summarised based on the data sources collected throughout the 12 weeks of implementation. HbA1c = hemoglobin A1c; T2DM = type 2 diabetes mellitus.
Data Collection Notes
EHR queries and standardized competency measurement and patient self-management checklists were used to prospectively gather data in three measurement intervals: baseline (Week 1), midpoint (Week 8), and post-intervention (Week 12). P004, P010, and P018 attended four visits (67% completion). Transportation barriers were encountered by these patients who received telehealth, yet refused or had connectivity problems. The data on HbA1c were on hand at three of the three time points through the in-person visits. The 20 audited patient records were checked against documentation. The ≥80% post-training threshold was not met by one of the staff members (S004); the staff member was given remedial coaching, and a follow-up assessment was planned. All the information included here was anonymised under the HIPAA requirements. The original records with patient names and medical record numbers are stored in encrypted and password-secured clinic servers found by the project team and preceptor.
Step By Step Instructions To Write
NURS FPX 9030 Assessment 1
Contact us today and receive expert step-by-step instructions for NURS FPX 9030 Assessment 1.
Instructions File For
NURS FPX 9030 Assessment 1
Contact us to get the instruction file.
Scoring Guide for
NURS FPX 9030 Assessment 1
Contact us to get the scoring guide.
References in APA Format For
NURS FPX 9030 Assessment 1
References coming soon.
Best Capella Professors To Choose From For NURS-FPX9030 Class
- Nicole Aclin, DNP, RN, CNE.
- Adriane Stasurak, DNP, RN, ANP-BC.
(FAQs) related to
NURS FPX 9030 Assessment 1
Question 1: What is NURS FPX 9030 Assessment 1 about?
Answer 1: It’s about uploading raw patient data from a 12-week diabetes QI project.
Question 2: Where can I get expert help with NURS FPX 9030 Assessment 1?
Answer 2: Get expert guidance for NURS FPX 9030 Assessment 1 by visiting TutorsAcademy.co.
Do you need a tutor to help with this paper for you within 24 hours
- 0% Plagiarised
- 0% AI
- Distinguish grades guarantee
- 24 hour delivery
Next Assessment:

