Benchmark – DPI Project Milestone 10 Strategic Points for the Direct Practice Improvement Project

Sample Answer

The 10 Strategic Points

Title of Project 1) Title of Project

Use of Telehealth Messaging to Improve Outcomes among People with Type 2

• Diabetes
  
• Background
  
• Theoretical Foundation
  
• Literature
  
• Synthesis
  

Practice Change Recommendation

Background to Chosen Evidence-Based Intervention Background of the practice problem/gap at the project site

Diabetes is one of the several chronic conditions that have been shown to adversely impact patients’ quality of life and functionality. Its negative impact largely emanates from potential conditions which may result due to diabetes, such as stroke, heart disease, kidney disease, and blindness (Skinner et al.,2020).

Diabetes impacts millions of life, limiting their ability to lead normal lives and prompting a need to come up with better strategies to prevent, manage and treat the condition (Zhang et al., 2020). Even though various approaches have been applied in efforts to minimize the adverse impacts of the condition, diabetes still ranks high among the most disabling and prevalent diseases (Zakin et al., 2019).

The limited success in previous interventions creates the need for more efforts towards the management of the disease. Recent statistics showed that the world’s diabetes prevalence stands as high as close to 10% (Khan et al., 2019). Due to its chronic nature, the major interventions used in managing patients with diabetes aim at ensuring that the patients have better patient outcomes relative to factors such as glycemic control and reducing the indulgence in risky lifestyle behaviors.

Such risky lifestyle behaviors have a huge potential to negatively impact the appropriate management of the disease (Maiorino et al., 2020). Even though the normal strategies have been applied at the practice site, the outcomes have not been as desired as patients still present with poorly controlled HbA1c, which exposes them to other comorbidities.

As such, there is a need to focus more on diabetes management and apply more robust strategies that can help the patient better manage their HbA1c levels. Diabetes self-management education and support have been shown to improve diabetes-related patient outcomes (Azami et al., 2018). In addition, with the advancement of technology, integrating aspects like telehealth with DSMES is proving to be more promising in terms of helping patients with diabetes have better HbA1c and other diabetes-related outcomes (Nelson et al.,2021).

However, the use integration of telehealth aspects such as telehealth messages is still minimal or absent in some practice settings such as the practice site. Therefore it is expected that improved patient outcomes will be the result of the integration of DSMES and telehealth messages.

Significance of the practice problem/gap at the project site

The chronic nature of diabetes means that the patients have to spend a lot of money yearly to ensure improved outcomes. As such, there have been efforts to use more robust approaches, such as leveraging technological advancements to formulate better diagnosis, prevention, management, and treatment strategies (Teymourian et al.,2020).

Nonetheless, individuals who are diagnosed with the condition annually are millions, while many others die yearly (Khan et al.,2019). As such, nursing has a role to play in coming up with appropriate nursing interventions which can be used to improve diabetes management, such as integrating DSMES with telehealth messages.

Such strategies can go a long way toward helping the patient develop better self-management strategies to improve diabetes-related outcomes such as HbA1c levels. This is significant to the practice site as positive outcomes would mean that the practice site will develop the use of DSMES with telehealth as the standard diabetes management strategy.

The implication is that the practice site will need to adopt this strategy to help improve patients’ HbA1c; on the contrary, failure to address the problem would mean that patients with diabetes would continue having poorly controlled HbA1c hence poorer health outcomes. Implementing the project is important because it could offer effective intervention on type 2 diabetes which is a significant health challenge in the American population.

Other studies done using different programs of telehealth messaging suggest that they are instrumental in the management of type 2 diabetes (Fortmann et al., 2017; Dobson et al., 2020; Vinitha et al., 2019). Conducting the project is significant in confirming the importance of the proposed intervention.

Theoretical Foundations

Nursing theories are important in guiding nursing interventions focused on improving patient outcomes since, through their frameworks, facets of proposed interventions can appropriately be implemented. Therefore, the nursing theory chosen to guide this project is Dorothea Orem’s self-care theory; the major claim of the theory involves assisting others by giving them and maintaining self-care with the major focus of improving the individual’s home-level effectiveness and functioning.

Orem argued that every individual can perform self-care, which entails a host of activities that the person starts to maintain their well-being, health, and life (Orem & Calnan, 1972). This theory is composed of three major supporting sub-theories. They include the theory of nursing systems, the self-care deficit theory, and the theory of self-care (Orem & Calnan, 1972).

The theory will be used as a supporting theory in the implementation of the DNP project on diabetes management. As earlier indicated, the chronic nature of diabetes requires that individuals undertake self-management activities for better outcomes. Therefore, the theory supports actions to be taken by the individuals, such as performing actions learned through educational initiatives and attending to the self-care needs for better outcomes.

According to the theory, self-care is more natural to adults and can be taught; as such, this underpinning will be key in guiding the DNP project in the promotion of self-care and self-maintenance among patients living with diabetes through the DSMES integrated with telehealth messages. Another aspect of the theory is that it indicates the possibility of the patients and the caregivers having deficits in terms of sufficient information and resources.

For example, the patient’s inability to undertake self-care makes them in need of support. This theory helps the project by linking what the patients need to do for better outcomes. This, therefore, fits the use of the proposed intervention to help the patients have better outcomes. Participating in the telehealth-supported diabetes self-management education program will ensure that the patients have a diminished incidence of emergency room visits.

Evidence-based change models are also important in patient intervention projects or initiatives as they help in the appropriate management of the change. As such, Kurt Lewin’s change theory was chosen to be used as part of this DNP project. The theory will be key in addressing the stakeholder concerns, attitudes, and fears. This theory has three major phases which can be used in guiding a change initiative. The three stages include unfreezing, change, and refreezing phases (Lewin, 1947).

In addition, the theory states that during a change process, there are two predominant forces; the restraining and the driving forces, which bar change and foster change, respectively. As such, a change can only occur successfully when the driving forces overcome the restraining forces. The first phase of the theory is the unfreezing stage, where an urgent need or urge for change is created (Hussain et al.,2018).

This stage helps the project by linking the urgent need for change and ensuring that the patients and the nurses see the urgent need to improve their patient’s HbA1c levels. Therefore, the nurses will help the patient see the need to use more effective strategies to improve their HbA1c levels hence the importance of participating in the project.

The change stage involves implementing the proposed change, which involves rolling out the DSMES integrated with telehealth messages to help improve outcomes. The third stage, which is the refreezing stage, will entail making use of the intervention to be part and parcel of the normal management strategy at the practice site. As such, the healthcare professionals involved in diabetes management will be required to use the intervention and support the patients for improved outcomes.

Annotated bibliography

Nelson, L. A., Greevy, R. A., Spieker, A., Wallston, K. A., Elasy, T. A., Kripalani, S., … & Mayberry, L. S. (2021). Effects of a tailored text messaging intervention among diverse adults with type 2 diabetes evidence from the 15-month REACH randomized controlled trial. Diabetes Care, 44(1), 26–34. https //doi.org/10.2337/dc20-0961

The major aim of this study was to examine the efficacy of tailored text messages addressing medication adherence and self-care behaviors among patients with diabetes in improving their HbA1c levels. This study, known as Rapid Education and Communication for Health (REACH), was a randomized controlled trial performed in Tennessee, USA. A total of 506 participants were recruited in the study, with 253 randomized into the control group while 253 were in the intervention group (REACH).

The intervention group was further randomized into the REACH-only group (127) or REACH with Family-Focused Add-on for Motivating Self-care (FAMS)- 126. The intervention group was offered monthly phone coaching delivered through text messages regarding self-care. Upon the use of the intervention, the HbA1c levels among the intervention group were found to reduce more than the intervention group (p=0.049) at six months of the study.

Fortmann, A. L., Gallo, L. C., Garcia, M. I., Taleb, M., Euyoque, J. A., Clark, T., … & Philis-Tsimikas, A. (2017). Dulce Digital an mHealth SMS-based intervention improves glycemic control in Hispanics with type 2 diabetes. Diabetes Care, 40(10), 1349–1355. https //doi.org/10.2337/dc17-0230

Fortmann et al’s. (2019) research had the main aim of examining the efficacy of text messaging in delivering diabetes care messages among patients with diabetes in lowering the HbAlc levels. This was a randomized controlled trial performed in California, United States. A total of 126 patients with poorly controlled diabetes were recruited, with 63 randomized into the intervention group while the remaining were randomized into the control group.

The intervention group received text messages with calls detailing a culturally appropriate DSME. The messages were sent two to three times a day for six months. The control group only watch videos on diabetes management at the start of the study. At baseline, both groups had poor glycemic control.

Upon the use of the intervention, the intervention group showed a greater reduction in HbA1c both at three months (p=0.03) and six months (p=0.03) as compared to the control group

Dobson, R., Whittaker, R., Jiang, Y., McNamara, C., Shepherd, M., Maddison, R., … & Murphy, R. (2020). Long‐term follow‐up of a randomized controlled trial of a text‐message diabetes self‐management support program, SMS4BG. Diabetic Medicine, 37(2), 311–318. https //doi.org/10.1111/dme.14182

This research was carried out with the major aim of examining the efficacy of individually tailored text-message diabetes self-management support programs on patients’ HbA1c levels among patients with type 2 diabetes. The study was conducted in New Zealand. This was also a randomized controlled trial where a total of 293 patients were included in the study, with 177 randomized into the intervention group while 116 were randomized into the control group.

The intervention group received automated text-messages self-management support on how to successfully manage diabetes. At the end of the study, there was a bigger reduction in HbA1c levels among the intervention group as compared to the control group (p<0.0001), showing the efficacy of the intervention.

Vinitha, R., Nanditha, A., Snehalatha, C., Satheesh, K., Susairaj, P., Raghavan, A., & Ramachandran, A. (2019). Effectiveness of mobile phone text messaging in improving glycaemic control among persons with newly detected type 2 diabetes. Diabetes Research and Clinical Practice, 158, 107919. https //doi.org/10.1016/j.diabres.2019.107919

Vinitha et al. (2019) conducted a study with the aim of evaluating the impact of text messaging in improving glycemic control among patients with type 2 diabetes. This was a multicenter randomized controlled trial study conducted in India. The researchers recruited a total of 248 patients, where 122 were randomized into the control group, and 126 were randomized into the intervention group.

While the control group was offered the standard care, the intervention group received care supported with customized text messages three times a week. The analysis of the data showed that the intervention was efficacious. Both group groups had a significant drop in HbA1c levels (p<0.0001). However, the reduction observed in the intervention group was greater than that of the control group (p=0.044)

Riangkam, C., Sriyuktasuth, A., Pongthavornkamol, K., Kusakunniran, W., & Sriwijitkamol, A. (2021). Effects of a mobile health diabetes self-management program on HbA1C, self-management and patient satisfaction in adults with uncontrolled type 2 diabetes a randomized controlled trial. Journal of Health Research, (ahead-of-print). https //doi.org/10.1108/JHR-02-2021-0126

The aim of this study was to determine the impact of a mobile health diabetes program (MHDSMP) intervention on diabetes self-management behavior and outcomes among patients with type 2 diabetes. This study was conducted in Thailand and was a three-arm parallel group randomized controlled trial.

A total of 129 patients were recruited to take part in the study. Forty-three participants were randomized in each of the three groups; MHDSMP, telephone follow-up, and usual care. The intervention received diabetes management through text messages and telephone coaching. The study went on for three months, and by the end of the study, analysis of the data showed that there was a statistically significant reduction in HbA1c levels in the intervention group (p<0.001)

Practice Change Recommendation Validation of the Chosen Evidence-Based Intervention

The usual care approaches have been applied at the practice site to manage patients with diabetes. However, patients continue to have undesirable effects, such as poor glycemic control. Therefore, this project proposes the use application of a DSMES integrated with telehealth text messages to help patients have well-controlled HbA1c levels, as indicated in research done by Nelson et al. (2021).

In this research, a randomized controlled trial was used, and the patients in the intervention group who had diabetes education supported with telehealth messages had a greater reduction in HbA1c levels ((p=0.049) at six months). The results show that the intervention used by Nelson et al. (2021) is effective in reducing patients’ HbA1c levels hence a recommendation for practice change from the usual care to telehealth-supported DSMES.

Summary of the findings.

The adverse impacts of diabetes as a chronic condition mean that various researchers have embarked on finding the best solutions to the condition. From the research articles in the annotated bibliography, it has been shown that the use of telehealth-supported DSMES improves patients’ HbA1c levels.

In all the articles, a comparison in HbA1c levels between the intervention groups and control groups revealed that the intervention groups experienced a more significant reduction in the HbA1c levels; for instance, Nelson et al. (2021) observed a statistically significant difference (p=0.049), Fortmann et al. (2017); p=0.03, Dobson, et al. (20200; p=0.0001, Vinitha et al. (2019); p=0.004 and Riangkam et al.(2020); p=0.001

Problem Statement 2) Problem Statement

It is not known if the implementation of DSMES with telehealth messages would impact Hb1Ac levels among adult patients with type 2 diabetes.
PICOT to Evidence-Based Question 3) PICOT Question Converts to Evidence-

Based Question

Among patients with type 2 diabetes in a nursing home, will the translation of Nelson et al’s research on diabetes self-management education and support with telehealth messages compared to the current practice improve patient HbA1c levels in 12 weeks?

Evidence-Based Question

To what degree will the implementation of Nelson et al’s research on diabetes self-management education and support with telehealth messages impact HbA1c levels among adult patients with type2 diabetes in a nursing home in Maryland?

• Sample
  
• Setting
  
• Location
  

Inclusion and Exclusion Criteria 4) Sample, Setting, Location

Sample and Sample Size The sample will be obtained through convenient sampling, where a total of 30 patients with type 2 diabetes will be recruited to take part in the study. A sample calculator is to be used to get the correct number of participants.

Necessary sample= (Z-score)2*StdDev*(1-StdDev)/(Margin of error)2
One of the possible biases is selection bias, as patients to participate in the study are ones known to the nursing home. There is a potential for lack of generalizability as patients will be drawn from a single center.

• Setting Skilled Nursing Facility
• Location The nursing home is located in Maryland in the USA
  

Inclusion Criteria

• Adult patients
  
• Patients that are alert and oriented to person, place and time.
• Patients with type 2 diabetes.
• Patients not part of another chronic disease study.
• Patients willing to participate.
  

Exclusion Criteria

• Patients below the age of 18 years
  
• Patients that not alert and oriented to person, place and time.
  
• Patients that are not diabetes
  
• Patients participating in another study.
  
• Patients who are unwilling to take part will also be excluded
  

Define Variables 5) Define Variables

• Independent Variable (Intervention) diabetes self-management education and support with telehealth messages
  
• Dependent Variable (Measurable patient outcome) HbA1c levels
  Project Design 6) Project Design
  

Quality Improvement quality improvement refers to a project or initiative aiming at improving patient outcomes. They are formulated to help minimize the chances of errors and improve patient outcomes. They are also started to help fill care gaps that have been observed in the patient care strategies.

Application of quality improvement in this project will consider existing research and translate the best evidence to help improve HbA1c levels among patients with type 2 diabetes in the practice site. In contrast to research, quality improvement involves the application of the already existing evidence to boost patient outcomes.

Research Research is a process of coming up with new ideas or knowledge to improve the current knowledge and standards of practice. It involves a systematic study of an existing problem or a clinical concern and coming up with hypotheses which are then tested to yield novel knowledge (Glasofer & Townsend).

The importance of research emanates from the fact that it helps in producing scholarly evidence. Such evidence is applied in formulating guidelines and standards for nursing practice. Research is also used to come up with quality improvement efforts and initiatives.

Summarize Both quality improvement and research are key in patient care as they both focus on improving patient outcomes. Nonetheless, the two are distinct from each other. Research focuses on new knowledge creation as well as coming up with new theories. Quality improvement translates the findings from research into practice.

Purpose Statement 7) Purpose Statement

The purpose of this quality improvement project is to determine if the implementation of diabetes self-management education and support with telehealth messages would impact HbA1c levels among patients with type 2 diabetes. The project was piloted over an eight-week period in an urban Maryland nursing home.

Data Collection Approach 8) Data Collection Approach

A RedCap database will be applied to measure the patient information. The baseline characteristics and demographic data, such as the patient’s comorbidities, ethnicity, race, age, and gender, will all be recorded for every participant. The baseline HbA1c data for the patients will be obtained from the facilities, electronic health records.

The Redcap database will be used to enter all the information related to the patient.

The collected data will be protected from unauthorized access using the pass-worded RedCap database. Access will only be granted to those who have the provided secret password. In addition, a number will be assigned to every medical record as a way of de-identification. Use of standardized surveys and questionnaires that are reliable and valid may help to collect the data to be used in the study.

Step-by-step process of data collection

• The baseline HbA1c level data for the participants will be obtained from the facility’s EHR
  
• The patients will use phones to receive interactive text messages on diabetes management.
  
• The patients will be expected to send back text messages if they have understood the contents of what has been sent.
• The HbA1c levels will be measured at the end of the intervention, and the data will be entered into the RedCap database.
  

Various steps will be taken to ensure that the patient’s rights are not infringed, and the data remains confidential. Participation will remain open and voluntary, as no patient will be coerced. The data will be de-identified, while the database with the patient data will be password protected. The data will be stored for one year after graduation, followed by disposal to protect patients further.

This project also intends to follow the Belmont principles. Hence, it will ensure that harm is prevented. Participation will also remain totally voluntary. The patients will also be treated with respect while respecting their autonomy. To adhere to the principles by remaining open to the participants and sharing every information that concerns them.

Data Analysis Approach 9) Data Analysis Approach

• The data will be analyzed using suitable software. Central measures of tendency, such as average, mean, and median, will be applied to summarize the patient’s characteristics.
• Descriptive statistics will be used to analyze the demographic data, the mean, median and standard deviations.
  
• While some data will be obtained from the EHR, the project data for comparison will be measured by the nurses, and comparison will be made to determine the efficacy
  
• Paired sample t-test will be used to obtain the differences between pre and post-intervention
  
• A statistician will be used in the statistical analysis and appropriate interpretation.
  

Various biases are expected in this project. For example, in case a positive effect is observed, there could be a possibility that such results may not be all down to the intervention. Therefore, as a way of mitigating this, a study design will be used to ensure that the patients only used the indicated intervention.

References

• Azami, G., Soh, K. L., Sazlina, S. G., Salmiah, M., Aazami, S., Mozafari, M., & Taghinejad, H. (2018). Effect of a nurse-led diabetes self-management education program on glycosylated hemoglobin among adults with type 2 diabetes. Journal of diabetes research, 2018. https //doi.org/10.1155/2018/4930157
  
• Dobson, R., Whittaker, R., Jiang, Y., McNamara, C., Shepherd, M., Maddison, R., … & Murphy, R. (2020). Long‐term follow‐up of a randomized controlled trial of a text‐message diabetes self‐management support program, SMS4BG. Diabetic Medicine, 37(2), 311–318. https //doi.org/10.1111/dme.14182
  
• Fortmann, A. L., Gallo, L. C., Garcia, M. I., Taleb, M., Euyoque, J. A., Clark, T., … & Philis-Tsimikas, A. (2017). Dulce Digital an mHealth SMS-based intervention improves glycemic control in Hispanics with type 2 diabetes. Diabetes Care, 40(10), 1349–1355. https //doi.org/10.2337/dc17-0230
  Glasofer, A., & Townsend, A. B. (2021). Determining the level of evidence. Nursing, 51(2), 62–65. https //doi.org/10.1097/01.nurse.0000731852.39123.e1
  Hussain, S. T., Lei, S., Akram, T., Haider, M. J., Hussain, S. H., & Ali, M. (2018). Kurt Lewin’s change model A critical review of the role of leadership and employee involvement in organizational change. Journal of Innovation & Knowledge, 3(3), 123-127. https //doi.org/10.1016/j.jik.2016.07.002
  
• Maiorino, M. I., Signoriello, S., Maio, A., Chiodini, P., Bellastella, G., Scappaticcio, L., … & Esposito, K. (2020). Effects of continuous glucose monitoring on metrics of glycemic control in diabetes a systematic review with meta-analysis of randomized controlled trials. Diabetes Care, 43(5), 1146-1156. https //doi.org/10.2337/dc19-1459
  
• Nelson, L. A., Greevy, R. A., Spieker, A., Wallston, K. A., Elasy, T. A., Kripalani, S., … & Mayberry, L. S. (2021). Effects of a tailored text messaging intervention among diverse adults with type 2 diabetes evidence from the 15-month REACH randomized controlled trial. Diabetes Care, 44(1), 26–34. https //doi.org/10.2337/dc20-0961
  
• Orem, D. E., & Calnan, M. E. (1972). NURSING. Nursing Management (Springhouse), 3(1), 43-46. https //doi.org/10.1097/00006247-197201000-00013
  
• Skinner, T. C., Joensen, L., & Parkin, T. (2020). Twenty‐five years of diabetes distress research. Diabetic Medicine, 37(3), 393-400. https //doi.org/10.1111/dme.14157.
  
• Teymourian, H., Barfidokht, A., & Wang, J. (2020). Electrochemical glucose sensors in diabetes management An updated review (2010–2020). Chemical Society Reviews, 49(21), 7671–7709. https //doi.org/10.1039/D0CS00304B
  
• Zakin, E., Abrams, R., & Simpson, D. M. (2019, October). Diabetic neuropathy. In Seminars in neurology (Vol. 39, No. 05, pp. 560–569). Thieme Medical Publishers. DOI 10.1055/s-0039-1688978
  
• Zhang, Y., Lazzarini, P. A., McPhail, S. M., van Netten, J. J., Armstrong, D. G., & Pacella, R. E. (2020). Global disability burdens of diabetes-related lower-extremity complications in 1990 and 2016. Diabetes Care, 43(5), 964–974. https //doi.org/10.2337/dc19-1614