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Using the approach of epidemiological for diabetes education in the population

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Explanation of the use of the data

The data of the epidemiological assessment is necessary that offer the rate of frequency, and the characteristics of demographics who have been diagnosed with type 2 Mellitus of diabetes. This is necessary for the evaluation of the requirements of diabetes. The rate of percentage in the given group who have been identified with this disorder at a specific time is referred to as the prevalence rate (Gruss et al. 2019, 1-1). The age group of 50-59 highlights the importance of chosen medications and the great help of the physician. It's major to recognize this are good presumptions, d?p?nd?nt upon variety affected by program practicability, medical services supplier limit, and the particular n?c?ssiti?s of our population. Here the variation of gender is necessary for regulating the initiatives of education.

Identification of the source of data

The identification of data based on this is very crucial in this study where the rate of prevalence, and the sex-specific information along the age are very necessary techniques to estimate the yearly demands of the people of the specific group (Mirzaei et al. 2020, 1-9). It can calculate the maximum number of people diagnosed with T2DM by multiplying the rate of the prevalence for each age group. After that, this can combine the individual group of age with the sex of the population. More precise data can be collected from the dataset which is maintained by the World Health Organization or WHO (Correia et al. 2019, 1-20). The sources of data which are collected from the various sites regarding this fact can contribute to more understanding of this education.

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Calculation of the annual need for this education

For calculating the annual need for this education the prevalence rate is necessary. The rate of prevalence can be assumed of 0.05. The rate of incidence is also necessary in this calculation. The annual need provides the concept of diabetes education which maintains the requirement of this education in that given group of people who have been diagnosed with this disorder (Selvin et al. 2020, 1;43). So the requirements of this education can be annually measured with the help of the prevalence rate and the rate of incidence. Here the prevalence rate is mentioned as 0.05. The formula to get the annual need for this education is the sum of the prevalence and the incidence which is multiplied by the total population of the group.

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Calculation of the annual need for education

Figure 1: Calculation of the annual need for education

The total population in this assessment is 1,000,000. So applying the formula the annual need for this education is obtained. From the formula (0.05+0.01) by multiplying 1,000,000 gives the result of 60,000.

Estimation of the annual number of hours of staff time

This estimation to measure the time of the staff members for this purpose can be calculated. For this measurement, the average time duration of the individual is required along with the annual need of this education. Here from the population which helps to determine the rate of prevalence and incidence, the annual need for this education can be acquired (Wong TY. 2020, 9-20). The next is the average hours of the individual which can be assumed here.

Estimation of the annual number of hours

Figure 2: Estimation of the annual number of hours

So applying the formula; 60000 *5 which gives the result of 300000 hours. So this is required for this assessment.

Calculation of the proportion and explanation

The proportion of gender-based education can be calculated by the formula. The proportion of males can be measured from the total population of males out of the total population. Here the total population of males is 494000 and the total population of males and females is 1000000. The proportion of females also be evaluated from the given number of females (Avilés-Santa ML et al.2020, 1-44). The population of females here is 505600. So from this, the proportion of the female can be obtained.

The proportion of the males and females

Figure 3: The proportion of the males and females

From this, the proportion of age of people whose age is greater than or equal to 65 can also be evaluated. So here are the people whose age is equal to or greater than the age of 65 out of the total population.

Using the approach of epidemiological for annual reviews of the population

Explanation of the use of the data

The estimation of the annual requirements of this education can gather feedback annually. So this method is very essential to understanding the affliction of this disorder which gives the rate of prevalence and guide to recognize the population who have experienced the disease. The rate of incidence helps to understand the time period of the new cases that have arisen among the population (Lazarus et al. 2022, 60-78). From the data, the characteristics of demographics which include sex and age within the various age groups also make an impact for getting the annual reviews. It can be estimated here that the number of people who have the type 2 diabetes by multiplying the rate of prevalence for the specific group of age. The epidemiological data demonstrate the inconsistent frequencies of T2DM to consider the requirement of the annual purpose which is needed in the training of diabetes training education. It can fluctuate according to the age group. So education about diabetes self-management and support which can be referred to as DSMES can be recommended at crucial times including the annual valuation. The patient with type 2 diabetes can be taken here to determine the annual requirement of the education. As precise individual opinions to profit from no less than on informative medication annually, this lines up with the recommended clinical audits.

Identification of the source of data

The d?p?ndabl? resources for ?pid?miological information incorporate public well-being overviews, diabetes libraries, and well-being data sets which are observed by government well-being agencies (McKeigue et al. 2020,17). The sources of choosing the data are crucial for keeping a record of this and determining the proper medication for the specific group of people. These sources gather and scatter ?xt?nsiv? data on diabetes regularity, frequency, and socioeconomics. Public well-being studies, for example, frequently lead to huge opportunity evaluations to give agent information on the well-being status of the populace. 

Determination of the annual need for reviews

The determination of the annual requirements can be evaluated with the rate of prevalence. When this rate is multiplied by the population the total number who have diabetes can evaluate the standard point of the new cases which need the review (Iida et al. 2019,1;26). The approach of the epidemiological helps to evaluate the cases that are already in the record and the cases that are new in the population that experienced the disease.

Estimation of the annual number of hours of staff time needed for annual reviews

This section of the assessment helps to estimate the annual hours of the time duration of the staff for the purpose of education training. Here the rate of prevalence, average hours which are required per review, and the rate of incidence are required. In this part, the rate of prevalence can be assumed as 0.1 which is 10%. The rate of incidence can be hypothetically assumed as 0.02 which is 20%. The average hours taken per feedback can be assumed as 1 hour (Leslie et al. 2021, 1;44). So from this, the annual hours of the review can be evaluated by adding the two rates of prevalence and incidence by multiplying the total population which is 1000000.

Estimation of the annual number of staff time

Figure 4: Estimation of the annual number of staff time

So the result will be (0.1+0.02) =0.12 which gives 120000 after being multiplied by the total population or 1000000. So this section gives results that 120000 hours are needed for the staff yearly.

Evaluation of the evidence for the diabetes program

Description of the strategy

The effective writing survey on systematized diabetes schooling programs for Type 2 Diabetes Mellitus (T2DM) uncovered indisputable proof, which can be evaluated precisely by the new and important randomized controlled preliminary (RCT) distributed in a r?sp?ctabl? diabetes diary. This RCT was intended to assess the ?ff?ct of an organized diabetes training program on glycemic control, patient information, and self-administration ways of behaving among people with T2DM. The review’s resources add to the power of the proof (Lakshmi. 2020, 2;13). First and foremost, the application of a randomized measured introductory plan is a huge strength, guarant??ing a thorough assessment by controlling for puzzling factors and laying out a more exact causal connection between the organized training system and results. The findings’ result is further ?nhanc?d by including an acceptable number of age groups and socioeconomic circumstances in the sample size. 

The strength of the evidence

This strategy can highlight the significance of the study which structured the program in a systematic manner that includes the program, the arrangement of the execution, and the time period of the assessment. The program also experienced obstacles during the process of the assessment and the limitations of the program which needed to be modified. Diagnosing the review’s impairments for a reasonable interpretation is significant. The prospective absence of generalizability since the review’s particular geographic area raises examinations about the appositeness of the locations to assorted populaces worldwide. Besides, the observed stable loss over the consequent period r?pr?s?nts a test, requiring a thoughtful assessment of member failure reasons and attention to potential inclinations pr?s?nt?d by awakening. During the enhancement of knowledge, the program possesses some barriers along with limitations.

Responsibility of the one staff member for evaluating the diabetes education

Explanation of the stage evaluation and application of the appropriate evaluation

The evaluation of the stage activity can present the scenario of this assessment which can monitor this phase of assessment. The areas that need to be identified require improvement and also need concentration to increase the efficiency of the plan of the initiative of this education program (Cheng et al. 2021, 1;44). This program can improve the results and also help to support the judgment. This needs the constant assembly of the data and also requires analysis. The choice of the Kirkpatrick model can be suitable for this assessment which emphasizes the two levels of process; one is for the reaction and the other is for the learning process. This model provides a synchronized process for evaluating the responses of the participants and gaining knowledge through the process. So it is very applicable for this assessment to proceed with the movement.

Specification of the data

Here is the part of gathering the data, the quantitative data can gather various factors which are the pleasure of the participants which is referred to as level 1 of the assessment, and the gaining of knowledge which is referred to as level 2. The surveys based on this assessment of the various participants can satisfy all of the people in the given group of people and provide the satisfaction among them. The gaining of knowledge can evaluated by the post and prior tests of the participants who can gain the level of knowledge after attending the education program. This type of primary data can be gathered from the assessments which makes it effective for the education program and also enhance the understanding of the content among the participants. The participants who want to attend the assessment program can enhance their engagement in the program which is very necessary for the assessment. The data can also be gathered in a qualitative manner which includes the debates of the group, the analysis of the documentation with the observation, and the reviews of the staff members (Leslie et al. 2021, 1;44). The debate participants of the specific group can conduct a conversation with the members of the group also can make it effective. The review section of the staff members can also gather feedback which is answerable for determining the programs of the education which provides some barriers and the achievements which they have experienced. The programs of assessment can evaluated by using the study materials and schedule of the lesson during the education. This can enhance the productivity of the implementation plan that they have taken for best delivery.

Description of the control chart

Control Chart

Figure 5: Control Chart

The above control chart represents the measurement of the patients who have been diagnosed with type two diabetes Mellitus and also took the nine annual examinations of checking in the general practices of hundred. The data in the chart displays the proportion of sufferers increasing. From the chart, it has been observed that some of the practices were very good and the other practices were not done in so effective way (Lakshmi. 2020, 2;13). Observing the chart it can be concluded that this approach is appropriate for the study to raise awareness among the patients. The green line of the chart shows that this is the upper of the control of the limit and the red line describes the lower of the control of the patients.

References

Journal

  • Avilés-Santa ML, Monroig-Rivera A, Soto-Soto A, Lindberg NM. Current state of diabetes mellitus prevalence, awareness, treatment, and control in Latin America: challenges and innovative solutions to improve health outcomes across the continent. Current diabetes reports. 2020 Nov;20:1-44.
  • Cheng HT, Xu X, Lim PS, Hung KY. Worldwide epidemiology of diabetes-related end-stage renal disease, 2000–2015. Diabetes Care. 2021 Jan 1;44(1):89-97.
  • Correia JC, Lachat S, Lagger G, Chappuis F, Golay A, Beran D, COHESION Project David Beran Jaime Miranda Albertino Damasceno Claire Somerville L. Suzanne Suggs. Interventions targeting hypertension and diabetes mellitus at community and primary healthcare level in low-and middle-income countries: a scoping review. BMC public health. 2019 Dec;19:1-20.
  • Gruss SM, Nhim K, Gregg E, Bell M, Luman E, Albright A. Public health approaches to type 2 diabetes prevention: the US National Diabetes Prevention Program and beyond. Current diabetes reports. 2019 Sep;19:1-1.
  • Iida M, Harada S, Takebayashi T. Application of metabolomics to epidemiological studies of atherosclerosis and cardiovascular disease. Journal of atherosclerosis and thrombosis. 2019 Sep 1;26(9):747-57.
  • Lakshmi Priyadarsini S, Suresh M. Factors influencing the epidemiological characteristics of pandemic COVID 19: A TISM approach. International Journal of Healthcare Management. 2020 Apr 2;13(2):89-98.
  • Lazarus JV, Mark HE, Anstee QM, Arab JP, Batterham RL, Castera L, Cortez-Pinto H, Crespo J, Cusi K, Dirac MA, Francque S. Advancing the global public health agenda for NAFLD: a consensus statement. Nature Reviews Gastroenterology & Hepatology. 2022 Jan;19(1):60-78.
  • Leslie RD, Evans-Molina C, Freund-Brown J, Buzzetti R, Dabelea D, Gillespie KM, Goland R, Jones AG, Kacher M, Phillips LS, Rolandsson O. Adult-onset type 1 diabetes: current understanding and challenges. Diabetes Care. 2021 Nov 1;44(11):2449-56.
  • McKeigue PM, Weir A, Bishop J, McGurnaghan SJ, Kennedy S, McAllister D, Robertson C, Wood R, Lone N, Murray J, Caparrotta TM. Rapid epidemiological analysis of comorbidities and treatments as risk factors for COVID-19 in Scotland (REACT-SCOT): a population-based case-control study. PLoS medicine. 2020 Oct 20;17(10):e1003374.
  • Mirzaei M, Rahmaninan M, Mirzaei M, Nadjarzadeh A, Dehghani Tafti AA. Epidemiology of diabetes mellitus, pre-diabetes, undiagnosed and uncontrolled diabetes in Central Iran: results from Yazd health study. BMC public health. 2020 Dec;20:1-9.
  • Selvin E, Juraschek SP. Diabetes epidemiology in the COVID-19 pandemic. Diabetes care. 2020 Aug 1;43(8):1690-4.
  • Wong TY, Sabanayagam C. Strategies to tackle the global burden of diabetic retinopathy: from epidemiology to artificial intelligence. Ophthalmologica. 2020 Aug 13;243(1):9-20.

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