Population Health Data Brief Paper

Population Health Data Brief Paper

Population Health Data Brief Paper

Nurses are frontline professionals in assessing population health and implementing corrective interventions that ensure quality outcomes. Data collection, analysis, and presentation require extensive research from reliable databases. Data collected from the public can be analyzed to provide a clear picture of the current health of a state. The State of interest is Florida, and the selected County is Miami-Dade. This essay explores data on the local geographical distribution of health-related factors and their significance in illustrating the selected County’s population health.

Sociodemographic Profile

Key Findings

         Miami-Dade County is categorized as one of the healthiest counties in Florida. The County boasts a healthy population, reflected in most health outcomes, health factors, and trends. Most health outcomes and factors are doing well, except for a few. The rate of uninsurance is significantly high in the County, and the mammogram screening rates are very low compared to the State and the United States. In addition, the severe housing problem is rampant in the County, showing that individuals have less access to affordable and quality housing with all amenities needed.

Figure 1

Miami-Dade County Map

Florida USA

 [Note. Miami-Dade County, United States County Map (Maps of World, n.d.]

Introductory Paragraph

Miami-Dade County, Florida state is the focus of this assessment. The County is found in the area of Florida State and is one of the most common and densely populated counties in the State. This essay will present county health data for analysis and outcome evaluation. The socio-demographic profile and analysis of health outcomes and factors compared to the State will give a clear picture of the County’s health and influence changes to improve population health.

The data used in the County Health Rankings were collected from various medical associates such as insurance films, the Centers for Medicaid and Medicaid, and the United States government census website. A document review was used to select and utilize appropriate and needed data for this study. The sociodemographic profile of the State shows that the County had experienced a negative population change. There are fewer persons under 18 compared to the United States. The females are closely similar in the State and the United States. Their percentage of African Americans is higher than that of the United States and Florida. The County diversified, with many individuals from other cultures. The homes with languages other than English are significantly high, supporting the assertion. The per capita income and poverty rate are high in the County compared to the country. Analysis of this data will help implement desired change and influence outcomes.

Sociodemographic Profile Table

Table 1

Sociodemographic Profiles for Miami-Dade County, Florida, and the United States

         

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Population Characteristics	County	United States
Population Estimates	2,673,837	333,287,557
Population Percent Change	-1.0%	0.6%
Percent of Persons Under the Age of 18	9.8%	21.7%
Percent of Persons 65 Years and Over	17.2%	17.3%
Percent of Female Persons	50.9%	50.4%
Percent White alone	79.4%	75.5%
Percent Black or African American alone	17.1%	13.6%
Percent American Indian and Alaska Natives alone	0.3%	1.3%
Percent Asian alone	1.7%	6.3%
Percent Native Hawaiian and Other Pacific Islander alone	0.1%	0.3%
Percent Two or More Races	1.3%	3.0%
Percent Hispanic or Latino alone	69.1%	19.1%
Percent White alone, not Hispanic or Latino	13.8%	58.9%
Language Other Than English Spoken at Home, Percent of  persons 5 years +	75.1%	21.7%
Percent of Houses with a Computer	94.1%	93.1%
Percent with High School Graduate or Higher	82.5%	88.9%
Percent with a Disability, Under Age 65 Years	5.8%	8.7%
Percent without Health Insurance, Under Age 65 Years	17.6%	13.6%
Percent in Civilian Labor Force Age 16 Years+	63.6%	63.1%
Percent of Females in Civilian Labor Force Age 16 Years+	57.8%	58.7%
Total Healthcare and Social Assistance Revenue	21,236,142	2,527,903,275
Total Retail Sales Per Capita	45,110,749	4,949,601,481
Per Capita Income in the Past 12 Months	$31,813	$37,638
Percent of Persons in Poverty	15.2%	11.6%
Population Per Square Mile	1,422.1	93.8

 County Health Trends and Rankings

Introductory Paragraph

These health outcomes are significant influencers of population health and safety. These health outcomes of significance are highly manageable and significantly affect population health, and some interventions can help address these health factors. Data was collected to help counties, states, and cities understand their health outcomes compared to national data and oversee changes to improve the health outcomes (County Health Ranks & Roadmaps, n.d.). Data is also collected for analysis purposes and to help.

Data was collected from the most recent census and the Centers for Medicare and Medicaid. Data was collected indirectly from secondary sources and analyzed to help address the research objectives. Archival or document reviews were used to identify reliable and relevant data for specific purposes. These reliable data sources collect first-hand data from facilities, and utilization of the data help save on primary data collection costs and improve analysis efficiency.

Discussion of Health Outcome Trends

Trend graphs help visualize change over time and show a health factor’s progress over time. The trend graphs also help plan and implement changes to improve worsening trends and sustain changes in improving health-related factors. Data presented here are sourced from the County Health Ranks & Roadmaps. Miami-Dade is ranked as among the healthiest counties in Florida (75-100%). Figure 2 shows that the rate of premature death in the County is lower at 5443 per 100000 compared to the United States rate of 7282 per 100000deaths and Florida State at 7478 per 100000.

Figure 3 shows that the sexually transmitted infections overall rate in Miami Dade County is lower at 460.8 per 100000 than in Florida State at 465.7 per 100000 and in the United States at 481.3 per 100,000. Figure 4 shows that rate of Alcohol-Impaired Driving Deaths in Miami -Dade County (13%) is significantly low compared to Florida (23%) State and Unites States (26%). The percentage of uninsured individuals in Miami Dade County is considerably higher (10) than the rate in Florida State (15%) and the United States (18%), indicating a need for improvement (County Health Ranks & Roadmaps, n.d.). The population ratio to primary care physicians in the County was 1210:1 compared to the States 1380:1 and the United States ratio of 1310:1. The ratio indicates access to healthcare services and availability of healthcare professionals for quality and safe care delivery. The mammogram screening rate in Miami-Dade County is 22%, which is significantly low compared to Florida State’s rate of 40% and the United States 37% (County Health Ranks & Roadmaps, n.d.).

Health Outcome Trends (Visual Graphs)

Figure 2 Sexually Transmitted Infections in Miami-Dade County FL, State, and National Trends

Note: This graph indicates that Miami-Dade County had an overall rate of 460.8 per 100000, better than the State’s 465.7 per 100000 and the United States’ 481.3 per 100,000. The rate in Miami Dade County has dropped from 540 to 460.8 per 100000, 516 to 465.7 per 100000 I the State, and 551 to 481.3 per 100000 in the United States (County Health Rankings & Roadmaps, n.d.)]

Figure 3

Premature Death in Miami-Dade County, FL

Years of Potential Life Lost (YPLL): County State and National Trends

Note: The graph indicates that the rate of premature death in the County has increased from 5186 to 5443 per 100000, compared to the increase in the Florida State rate from 7188 to 7478 per 100000 and the United States rate from 6907 to 7282 per 100000 (County Health Ranks & Roadmaps, n.d.).

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Figure 4

Alcohol-Impaired Driving Deaths in Miami-Dade- County, FL State, and National Trends

Note: The rate of alcohol-impaired deaths in Miami-Dade County has increased from 9% to 13% compared to the State rate, which increased from 21 to 23%, and the United States rate, which has stagnated at 26% (County Health Ranks & Roadmaps, n.d.).

Figure 5

Uninsured Miami-Dade County, FL State, and the United States

Note: The percentage of uninsured individuals in Miami-Dade County has slightly decreased from 19% to 18%, the Florida State from 16% to 15%, and the United States from 11% to 9%. However, the high number of uninsured individuals is of great significance to the health of the Miami-Dade County population (County Health Ranks & Roadmaps, n.d.)

Figure 6

The Ratio of Primary Care Physicians to Population/Patients

Note: Miami-Dade County is getting in the primary care physician to population ratio, and the graph shows that the percentage of the population to primary care physicians has not changed in the last year for the County and the United States compared to the State ratio, which has increased from 1370 to 1380 in the previous year (County Health Ranks & Roadmaps, n.d.)

Figure 7

Preventable Hospital Stays in Miami-Dade County, FL, County, State, and National Trends

Note: This graph shows that preventable hospitals per 100 000 Medicare enrollees are higher at 3867 per 100000 enrollees compared to Florid State at 3186 per 100000 and Unites States rate of 2809. The rate of preventable hospital stay in Miami-Dade County is decreasing gradually, and data from the County Health Rankings show that the rate of preventable hospital stays in the County decreased from 5721 to 3867 per 1000000, 4203 to 3186 in Florida State, and 3867 to 2809 in United States (County Health Ranks & Roadmaps, n.d.).

Figure 8

Mammography Screening in Miami Dade County- County, State, and National Trends

Note: The mammogram screening rate among Medicare enrollees decreased from 29% to 20% in Miami-Dade County, 44% to 37% in the State, and 43% to 37% in the United States. The low rate is also a significant population health issue for this County (County Health Ranks & Roadmaps, n.d.).

Health Outcome Trends Discussion

The data described in B2 and the graphs above provide vital data on health outcomes in Miami-Dade County compared to Florida State and the United States. Figure 2 shows that sexually transmitted infections have been high over the last twelve years but declined significantly over the previous year, showing improved health efforts. Figure 3 shows that premature deaths in Miami-Dade County are lower than the state and national rates and have stabilized in the last nine years. The oscillation between increase and decrease in the rates shows a need for strengthening or replacing current policies to address the issue more effectively.

Figure 4 demonstrates how impaired driving deaths have declined gradually, and the burden in Miami-Dade County is significantly lower than the national and State hence improved outcomes. Figure 5 illustrates how Miami-Dade County uninsurance rates (18%) are about twice those of the national rates (10%) and 1.5 times the Florida (15) state levels, placing Miami-Dade county residents at risk for poor healthcare access. Figure 8 also shows that the mammogram rates among Medicare enrollees are very low, about half the national and State, which places them at risk for severe cancers, poor quality outcomes, ad high healthcare costs. Figure 6 demonstrates that the low population-to-physician ratio has been dropping gradually in Miami-Dade County compared to the State and the United States. This shows that the population has more access to care providers and associated health outcomes than the State and United States. Figure 7 demonstrates that preventable hospital stays have dropped significantly in the County, states, and nation, which signifies better healthcare services delivery.

Health Factors

Health Factors Table

Table 2

Factors Influence Health Profiles for Miami-Dade County, Florida, in the United States

Factors Influencing Health	County  Data	State Data	United States   Data
Percent Smoking	15	16	16
Percent with Access to Exercise Opportunities	98	88	84
Percent Excessive Drinking	15	17	19
Primary Care Physicians (Ratio of Population to 1 Physician)	1210	1380	1310
Percent with High School Completion	82	89	89
Percent with Some College	64	64	67
Percent with Unemployment	5.2	4.6	5.4
Percent of Children in Single-Parent Households	31	28	25
Social Associations (Number of Associations Per 10,000)	5.2	7.0	9.1
Children in Poverty	18	18	17
Injury Deaths (Number of Injury Deaths Per 100,000)	53	87	76
Percent of Children Eligible for Free or Reduced-Price Lunch	74	54	53
Air Pollution (Average Daily Density of Air Pollutants)	7.7	7.8	7.4
Percent with Severe Housing Problems	30	19	17

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Comparison of Data

Comparing county data to the State and the top performers helps policymakers determine the effectiveness of their interventions in addressing these factors. It also helps develop corrective interventions at the county level. Each County is affected differently by these factors, and comparing the data supports the County in identifying and addressing factors affecting their health for better population health outcomes (County Health Ranks & Roadmaps, n.d.). The County appears to be doing well against the State and United States data. The factors affecting health vary between the County, State, and nation, and the County is performing better than the nation in some areas and failing in some. The adult smoking rate among adults is closely similar between the County, State, and the United States. The number of individuals with access to exercise resources is significantly higher in the County than in the Florida State and United States data.

The excessive drinking rate is slightly lower than Florida and United States data. The population-to-primary care provider ratio in the County is smaller than those of the State and nation, meaning the County has more physicians relative to the population. The number of individuals with s a high school degree and some college education is relatively similar to that of the State and United States. The unemployment rate is higher in the County than in the State but lower than in the United States. The percentage of children in single-parent families is slightly higher in the County than in the State and the nation. Social association density is significantly lower in the County than in the State and the country. More associations are necessary to meet this target. The percentage of children in poverty is the same for the County and State but slightly higher than the national percentage. The rate of injury death in the County is significantly lower than in the State and the nation, which shows that the County has exceeded its expectations in injury deaths. The number of children eligible for free or reduced free lunch is significantly higher per 100000 children in the County than in the State and nation, showing that there are more needy children or less stringent inclusion criteria. The air pollution rate is closely similar to the State but slightly higher than the nation, and the County is close to or has met this parameter’s targets. The rate of individuals with severe housing problems is almost double that of the State and the nation, indicating a need for addressing the issue.

Summary

Significant Findings

The rate of insurance is also significantly low in the County, with a significant percentage of individuals having healthcare insurance coverage (18%) compared to the State (15%) and the nation (10%) (County Health Ranks & Roadmaps, n.d.). The mammogram screening rate is lower in the County than in the State, and very few Medicare enrollees have accessed mammogram services. The State has severe housing problems, with the number of individuals experiencing severe housing problems almost double that of the State and the nation. These are the most significant problems that should be addressed to help improve the population’s health. One of the main health trends is the decreasing rate of mammography scanning in the County, State, and nation (County Health Ranks & Roadmaps, n.d.). The rate among Medicare enrollees has decreased significantly over the past few years. It is at its all-time low over the last eight years and should be addressed promptly.

Action Plan(s)

The low and decreasing mammography screening rate is of interest to the County. The interventions to address the problem will be primarily based on a model of change, the DMAIC process. According to dos Reis et al. (2022), the DMAIC process is widely implemented in healthcare facilities and helps ensure organization and success in care interventions. The first step is to define the trend, population mammography screening rate by data, and analysis of reports by the CMS, which is the source of the data. Defining data targets will help determine the extent of change needed, informing the selected intervention. The next step is to research the significance/impact of the low screening rate nationwide and in the County and identify their causes. The next step is to identify interventions that can help address the issues and improve the mammography scanning rate. The last step is to identify/select the best intervention and implement and control it. These steps will help address the trend and improve health outcomes in the County.

Services or Programs

Services and programs that could be introduced into the County for quality outcomes include population education and mobile clinics. Mass education through community education programs and print and electronic media helps deliver messages to the entire population and can be useful in improving outcomes (Mateus-Coelhoet al., 2021). Educating the public increases their knowledge of healthcare interventions, increasing their awareness and ensuring quality health outcomes.

Mobile clinics are widely sued in communities to take services to patients at their most convenient and accessible locations. The intervention requires collaboration with community health workers who educate and mobilize patients to attend the clinic. Mobile clinics offer services in the community and are some of the most effective interventions to address population health in remote areas with poor access to healthcare services.

Raise Public Awareness and Promote Public Engagement

Technologies that can help improve public awareness and promote public engagement. Advanced practice nurses should utilize technology to integrate informatics into practice. The advanced practice nurse should use technology to communicate with the population (Agbo et al., 2019). For example, they can use telehealth and m-health apps to speak to and inform them of upcoming mobile clinics in their area to access and utilize these services. They should also use technology to promote communication, coordination, and collaboration in the execution team. Technology will help communicate with all team members and ensure collaboratively implement effective change in healthcare.

Another way of using technology is by delivering education and increasing awareness through the technologies (Agbo et al., 2019). E-health and m-health technologies are a crucial part of integrating informatics into practice. Mateus-Coelho et al. (2021) note that e-health technologies, such as organizational websites, are robust platforms institutions can use to educate the public. Institutions have established their presence in areas such as social media and have gained familiarity. Government-owned websites are also crucial in information dissemination and should be used to share information with the public. M-health apps can also be integral in providing education to patients, thus using these technologies to deliver education and improve awareness (Mateus-Coelhoet al., 2021). Thus, advanced practice registered nurses should use technology to communicate with patients, collaborate, communicate and coordinate efforts, and deliver population education for their engagement.

Monitoring and Evaluating Action Plan

The elements of the proposed actions will be monitored to ensure quality outcomes and optimal resource use. The first intervention is to prepare a process map and a critical path to outline the purpose of activities, timelines, and parties responsible for these activities. The step will help all stakeholders understand the change, follow the proposed guidelines for quality outcomes, and avoid unnecessary delays and resource wastage (Petroutsatou, 2022). Another plan is advanced reports and monthly meetings to monitor progress. After initiating the action plans, monthly meetings with advanced reporting will help oversee the change’s implementation. The plan’s effectiveness will be implemented after six months after the beginning of the proposed changes.

Data Sources and Methods

The data used for this assignment was selected from the County Health Rankings and Roadmaps. The website utilizes data from various reliable sources that collect primary or secondary healthcare data. These sources include the census and the Centers for Medicare and Medicaid. A document review was the method used to collect and analyze the data. Other data sources included a literature review for evidence-based practices associated with the need identified. The resources used were peer-reviewed and current. The data collected from this assigned and proposed strategies will help improve care delivery and better population health outcomes.

References

Agbo, C. C., Mahmoud, Q. H., & Eklund, J. M. (2019, April). Blockchain technology in healthcare: a systematic review. In Healthcare (Vol. 7, No. 2, p. 56). MDPI. http://dx.doi.org/10.5937/fme2104876M

County Health Ranks & Roadmaps, (n.d.). 2023 County Health Rankings National Findings Report. Retrieved 9^th July 9, 2023, from https://www.countyhealthrankings.org/reports/2023-county-health-rankings-national-findings-report

dos Reis, M. E. D. M., de Abreu, M. F., Neto, O. D. O. B., Viera, L. E. V., Torres, L. F., & Calado, R. D. (2022). DMAIC in improving patient care processes: Challenges and facilitators in context of healthcare. IFAC-PapersOnLine, 55(10), 215-220. https://doi.org/10.1016/j.ifacol.2022.09.628

Khan, A., & Mir, M. S. (2021). E-health and m-health: Future of healthcare. J Anat Physiol, 2(3), 38.

Mateus-Coelho, N., Cruz-Cunha, M. M., & Ávila, P. (2021). Application of the Industry 4.0 technologies to mobile learning and health education apps. FME Transactions, 49, 876-885. https://doi.org/10.1007/s42413-019-00055-5

Petroutsatou, K. (2022). A proposal of project management practices in public institutions through a comparative analysis of critical path method and critical chain. International Journal of Construction Management, 22(2), 242-251. https://doi.org/10.1080/15623599.2019.1619225

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ARM1 — ARM1 TASK 1: POPULATION HEALTH DATA BRIEF

INFORMATICS FOR TRANSFORMING NURSING CARE — D029 PRFA — ARM1

TASK OVERVIEW SUBMISSIONS EVALUATION REPORT

COMPETENCIES
7067.1.1 : Analyze Underpinnings of Nursing Informatics
The learner analyzes the theoretical and conceptual underpinnings of the nursing informatics scope and standards to improve patient experience and health outcomes.
7067.1.2 : Determine Technologies to Improve Care
The learner determines how technology and informatics can be optimized to improve the patient experience and lower healthcare costs.
7067.1.3 : Analyze Administrative Systems
The learner analyzes core administrative systems to support the management of safe, cost-effective, and high-quality healthcare.
7067.1.4 : Analyze Population Data
The learner analyzes data from population-based systems to mitigate public.
7067.1.5 : Design Data Collection Tools
The learner designs data collection tools and processes to capture, analyze, and report health indicators and outcomes.
7067.1.6 : Refine Data Visualizations
The learner refines data to visually represent, forecast, monitor, and report progress in meeting healthcare outcomes.

INTRODUCTION
Population health, in its broadest sense, is defined as an integrated approach by which interdisciplinary collaboration between various groups in a community—such as businesses, academia, healthcare providers, philanthropic organizations, local governments, and civil and religious organizations—work together to achieve the common goal of improving overall human health within a defined geographical area (CDC, 2017).

When examining population health dynamics, it is important to recognize that important research areas include not only aggregated medical diagnoses but also the hazards in the living and working environments, socioeconomic statuses, ethnic backgrounds, educational levels, and health coverage-related aspects of a given population. In particular, underserved populations play an important role in the development of strategies, interventions, and policy for the delivery of improved population health. Improving population health focuses not only on bringing awareness to significant health issues and contributing factors within a given area, but also on identifying the resources necessary to influence and deliver positive changes.

For nurses and other members of the healthcare community, population health is just as much a professional responsibility as is the care of a single individual in an acute care setting. It is important for members of the healthcare community to cultivate an awareness of and sense of involvement in population health initiatives. In these initiatives, a nurse’s knowledge—including informatics competencies, clinical practice experience, and leadership skills—can be applied to positively affect health outcomes. It is equally important for nurses to first analyze and understand the geographical area an initiative focuses on. This helps identify modifiable and nonmodifiable health risk factors within a community, which serves as the foundation for setting priorities.
This first step is vital in generating the information necessary for the engagement and action of local stakeholders.

In this task, you will gather data about the local geographical distribution of health-related factors, study the significance of the data, and present the data in a manner illustrating the state of the selected county’s population health. You will explore the community’s health profile and trends as well as factors influencing the county’s current health status. The information you submit will consist of graphics such as maps, trending graphs, comparative charts, and statistical lists. You will summarize key findings and highlight at least one health factor or condition requiring focused attention.

REQUIREMENTS
Your submission must be your original work. No more than a combined total of 50% of the submission and no more than a 10% match to any one individual source can be directly quoted or closely paraphrased from sources, even if cited correctly. The originality report that is provided when you submit your task can be used as a guide.

You must use the rubric to direct the creation of your submission because it provides detailed criteria that will be used to evaluate your work. Each requirement below may be evaluated by more than one rubric aspect. The rubric aspect titles may contain hyperlinks to relevant portions of the course.

You will perform the following actions by completing the “Population Health Data Brief Template” attachment:

A. Complete the “Sociodemographic Profile” section in the “Population Health Data Brief Template” attachment by doing the following:

Note: If information is not available for any subsection, please provide an explanation.

1. Complete the “Key Findings” subsection, including a screenshot of the county you are investigating.
2. Complete the “Introductory Paragraph” subsection (suggested length of 1–2 paragraphs), identifying the source of the data and a summary of findings from the table in part A3.
3. Complete the 20 population characteristics in the “Sociodemographic Profile Table” subsection for the selected county and the United States.

B. Complete the “County Health Trends & Rankings” section in the “Population Health Data Brief Template” attachment by doing the following:
1. Complete the “Introductory Paragraph” subsection (suggested length of 1–2 paragraphs), including why the data for the health trends in part B2 were collected and identifying the source of the data and the methods used to gather the data.
2. Complete the “Discussion of Health Trends” subsection, including a discussion of the use of trend graphs for the seven major health trends selected in part B3.

3. Complete the “Health Trends (Visual Graphs)” subsection, including one trend graph for each of the selected health trends.

Note: Caption each visual graph in APA format.

4. Complete the “Health Trends Discussion” subsection (suggested length of 1–2 paragraphs), including how each of the trend graphs tell a story about the health of the county and how the health aspect is improving, worsening, or remaining stable.

C. Complete the “Health Factors” section in the “Population Health Data Brief Template” attachment by doing the following:
1. Complete the 14 items in the “Health Factors Table” subsection for the selected county, the top U.S. performer, and the state.
2. Complete the “Comparison of Data” subsection (suggested length of 1–2 paragraphs), including an analysis of background information on health rankings and the purpose of comparing county data to the top performers.

D. Complete the “Summary” section in the attached “Population Health Data Brief Template” by doing the following:
1. Complete the “Significant Finding(s)” subsection (suggested length of 1–2 paragraphs), including one main health trend from part B that has the potential to be redirected by an action plan to significantly improve community health outcomes in the county.
2. Complete the “Action Plan(s)” subsection (suggested length of 1–2 sentences), including the initial steps needed for implementing an action plan to address the main health trend in part D1.
a. Complete the “Services or Programs” subsection (suggested length of 1–2 sentences) with a discussion of the services or programs that may be introduced in the county to address the identified health trend(s) from part D2.
b. Complete the “Raise Public Awareness and Promote Public Engagement” subsection (suggested length of 1–2 paragraphs), including a description of three ways that the advanced professional nurse should use technology to integrate informatics into practice.
c. Complete the “Monitoring and Evaluating Action Plan” subsection (suggested length of 1–2 paragraphs), including a summary of how the elements of the proposed action plan from parts D2a and D2b will be monitored.

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E. Complete the “Data Sources & Methods” section in the attached “Population Health Data Brief Template,” including the sources you used to gather data for your data brief.

F. Incorporate the following components of APA style and formatting in your paper:
• bias-free language
• APA-specific rules regarding verb tense, voice, and perspective
• a title page and headers
• in-text citations and references
• APA-specific formatting rules for margins, spacing, numbering, and indentation for the title page and main body of your paper, including headers, bulleted and numbered lists, and tables and figures

G. Demonstrate professional communication in the content and presentation of your submission.

NOTE: The Performance Assessment should be uploaded as a separate attachment(s) and should not be included in the E-portfolio or submitted as a link.

File Restrictions

File name may contain only letters, numbers, spaces, and these symbols: ! – _ . * ‘ ( ) File size limit: 200 MB
File types allowed: doc, docx, rtf, xls, xlsx, ppt, pptx, odt, pdf, txt, qt, mov, mpg, avi, mp3, wav, mp4, wma, flv, asf, mpeg, wmv, m4v, svg, tif, tiff, jpeg, jpg, gif, png, zip, rar, tar, 7z

RUBRIC

A1. :KEY FINDINGS

A2. :SOCIODEMOGRAPHIC PROFILE INTRODUCTORY PARAGRAPH

A3. :SOCIODEMOGRAPHIC PROFILE TABLE

B1. :COUNTY HEALTH TRENDS & RANKINGS INTRODUCTORY PARAGRAPH

B2. :DISCUSSION OF HEALTH TRENDS

B3. :HEALTH TRENDS (VISUAL GRAPHS)

B4. :HEALTH TRENDS DISCUSSION

C1. :HEALTH FACTORS TABLE

C2. :COMPARISON OF DATA

D1. :SIGNIFICANT FINDINGS SUMMARY

D2.: ACTION PLAN(S)

D2A. :SERVICES OR PROGRAMS

D2B. :PUBLIC AWARENESS AND PUBLIC ENGAGEMENT

D2C. :MONITORING AND EVALUATING AN ACTION PLAN

E. :DATA SOURCES & METHODS

F. : APA SOURCES

G. : PROFESSIONAL COMMUNICATION

SUPPORTING DOCUMENTS
Population Health Data Brief Template (APA).docx