Fluent Essays

Scenario You have assessed your local population health needs and identified data sources and data sets that are needed to help providers make immediate gains in patient outcomes. Your health systems Board of Directors is requesting that you develop a high-level population health management program dashboard. For this assessment, you need to assess local population health needs and identify data sources and data sets that are needed to help providers make immediate gains in patient outcomes. It is a major undertaking to plan, design, and implement a robust PHM. Therefore, your health systems Board of Directors is requesting that you develop 1-2 page high-level population health management program dashboard. In this dashboard, list the health needs based on the community needs assessment and the critical data sources and data sets needed for the population health management program your health system is planning to launch. Instructions Using the information from the modules 01, 02, and 03 summative assessments, construct a dashboard that lists the health needs based on the community needs assessment that was performed and the critical data sources and data sets needed for the population health management program your health system is planning to launch. 1 7 Deliverable 3: Locating Data Sources and Sets for Population Health Management Hossin Mosaddad Rasmussen University Population Health Dr. Merle Point-Johnson Deliverable 3 Submitted August 8, 2021 Diabetes has become a common disease among many adults, both men and women, in Seminole County, Florida, which has significantly led to most individuals experiencing adverse effects on their health and well-being. Diabetes is a health condition that occurs when the blood glucose of an individual, commonly known as blood sugar, is too high. Blood glucose is usually the primary source of energy in human beings, and it is obtained from the food that we eat. A hormone that is made by the pancreas, insulin, assists glucose acquired from food to get into the cells of human beings in order to be used for energy. The main types of diabetes that the population in Seminole county is suffering from are type 1 and type 2 diabetes. Type 1 diabetes is described as an autoimmune illness and the immune system attacks and damages cells in the pancreas in which insulin is made. Both men and women who have type 1 diabetes, their body does not produce insulin, and in order to stay alive, they must take insulin each day. Type 2 diabetes normally emerges when an individuals body becomes resistant to insulin which leads to sugar building up in the blood. Individuals who have type 2 diabetes, their bodies do not generate or utilize insulin properly, and this is the most common type of diabetes among many people in Seminole county. The common symptoms of diabetes include sores that do not heal, extreme fatigue, blurry vision, frequent urination, loss of weight, increased thirst and increased hunger. Besides the overall symptoms of diabetes, men with this disease might have a diminished sex drive, erectile dysfunction and poor muscle strength, while ladies may also experience symptoms like dry and itchy skin, yeast infections and urinary tract infections. Big data is very important to every undertaking of a health care organization, and it is defined as the abundant health information which is obtained from several sources. Big data is distinguished from electronic medical and human health data used for decision making by certain features, including being obtained from numerous sources, it is extremely variable in structure and nature, it moves at a high velocity and spans the enormous digital universe, and it is available in extraordinarily high volume. Some of the major sources of big data include medical devices, wearable devices, pharmaceutical research, payer records, genomic sequencing, medical imaging and electronic health records. An electronic health record is a digital form of the paper chart of a patient. Electronic health records are usually are centered on the records of patients; they are real-time, can be acquired instantly and safely by authorized users. These records are computerized and contain certain information such as the patients billing information, hospital discharge instructions, lab test results, immunization status, allergies, medicines, health history, ethnicity, gender and age (Cowie et al., 2017). Health care providers can share these digital health records if they are in the same health care facility, clinic or health care system. For instance, in case a doctor orders a laboratory test, the other health care providers will also be able to see the results. Whenever a clinician puts a patient on a new medicine, the other clinicians will also be able to see the type of medicine that was prescribed to the patient; hence there will be less chance of a clinician prescribing medicine that could lead to problems in case it is used with another medicine. The use of electronic health records will significantly help in enhancing how well health care providers talk to each other and coordinate the treatment of patients well and improve the care of patients. Some of the benefits of electronic health records include security, education and fewer mistakes. There are always chances that papers records can get lost or be misfiled; hence electronic health plays a key role because there is less chance of those things happening, and the majority of the records are protected by passwords. Patients are also able to see their medical files, which lets them participate in their own health care. Patients are able to see their test results, keep track of things like glucose, check errors and review medical instructions given. Wearable devices are also a source of big data in health care which has been advanced by wearable technology. Wearable technology in health care comprises various electronic devices that customers can wear and are meant to gather the data of users’ individual health and exercise. The improvement of wearable technology has enabled many patients to take control of their own health, which has greatly impacted the medical industry, comprising technology companies, providers and insurers, to create more wearable devices. Some of the common wearable devices that can be used include wearable biosensors, blood pressure monitors, ECG monitors, smart health watches and wearable fitness trackers. Wearable biosensors hold the possibility to revolutionize remote healthcare ad telemedicine because these devices are portable and can be acquired in different forms like implants, bandages, clothing and gloves. These devices develop two-way feedback between the user and their health care providers, which enhances continuous and noninvasive diagnosis of disease and monitoring of health from physical motion and fluids of the body. Wearable blood pressure monitors usually measure blood pressure and the daily activities of the users, including the steps that they take to burn calories. The various sources and types of big data have several advantages, such as generating real-time alerting, enabling improved health care with fitness devices, delivering greater insights into the cohorts of patients and ensuring there is the reduction of general health care costs. Other benefits of big data include easing the diagnostics of patients with electronic health records, predicting patients at higher risk quickly and efficiently and improving the health care of patients (Dash et al., 2019). Clinical insights are obtained from the knowledge that is derived from big data analytics, which improves patient care in the health care system because health care providers are able to prescribe effective treatment and make clinical decisions that are more accurate. Data elements typically describe the logical unit of data, and these elements can greatly help the health care providers to make immediate gains in the well-being of patients as they develop the best practices for future initiatives. Some of the specific data elements that can be used by health care providers include the name of the patient, their age, ethnicity, gender, city, country and state (Bruland et al., 2016). Other data elements that can be required include billing information, hospital discharge instructions, laboratory test results, immunization status, allergies, medicines and health history. Every data element is usually defined by the type of information it represents. For instance, when distinguishing numeric data from text data, the data element will describe code values that should be observed with a certain type of data, minimum and maximum length and the data type of numeric, alphanumeric, time or date. Some of the common features that are included in the descriptions of data elements comprise the ID of the element, the name, the type of data, input and output formats and validation criteria to ensure that correct information is captured by the system. Learning to use more readily accessible information such as ADT alerts, ICD- 10 codes and demographics is very important because it will promote incorporating more complex and different big data into the population health management ecosystem. Demographics serve as crucial information, and in order for health care providers to make sure that there is equitable treatment of outcomes, they should look at a wide range of the patients personal information. This personal information can include the ethnicity, state, race, gender or age of the patient. Demographic information can significantly assist in informing treatment plans since physicians normally create standardized processes for collecting data and ensure that all patients have the potential to reach optimal treatment outcomes (Dinov, 2016). The ethnicity and race data can be used to improve the quality of care for all patients since it helps in developing more patient-centered devices, evaluating whether the practice is delivering culturally competent care, distinguishing which populations do not achieve optimum interventions and identifying and dealing with differences in care for certain populations. Learning to use ICD-10 codes is also important because these codes have various advantages in the health care system. Some of the benefits of using ICD-10 codes consist of tracking public concerns and evaluating risks of adverse public health events, inhibiting and detecting health care fraud and abuse, refining clinical, financial and administrative performance and monitoring utilization of resources (Khokhar, et al., 2016). Other advantages of using ICD-10 codes include setting health policy, enhances carrying out of research, designing payment systems, processing claims of reimbursement and measuring the quality, safety and efficacy of care. In conclusion, every individual should strive to ensure that they prevent and control diabetes disease by taking appropriate measures like avoiding foods with a lot of calories and taking part in exercises regularly. Every health care organization should also ensure that they implement appropriate big data sources like electronic health records, which offer various advantages like the security of information and eliminate errors that might be experienced in paper records. Health care providers should also learn to use more readily available data in order to promote the safety and efficacy of care to all patients. References Bruland, P., McGilchrist, M., Zapletal, E., Acosta, D., Proeve, J., Askin, S. & Dugas, M. (2016). Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting. BMC medical research methodology, 16(1), 1-10. https://doi.org/10.1186/s12874-016-0259-3 Cowie, M. R., Blomster, J. I., Curtis, L. H., Duclaux, S., Ford, I., Fritz, F., & Zalewski, A. (2017). Electronic health records to facilitate clinical research. Clinical Research in Cardiology, 106(1), 1-9. https://doi.org/10.1007/s00392-016-1025-6 Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 1-25. https://doi.org/10.1186/s40537-019-0217-0 Dinov, I. D. (2016). Volume and value of big healthcare data. Journal of medical statistics and informatics, 4. https://journalofbigdata.springeropen.com/articles/10.1186/s40537-019-0217-0 Khokhar, B., Jette, N., Metcalfe, A., Cunningham, C. T., Quan, H., Kaplan, G. G., ... & Rabi, D. (2016). A systematic review of validated case definitions for diabetes in ICD-9-coded and ICD-10-coded data in adult populations. BMJ Open, 6(8), e009952. http://dx.doi.org/10.1136/bmjopen-2015-009952 2 LITERATURE REVIEW 2 Deliverable 2: Executive Summary Hossin Mosaddad Rasmussen University Population Health Dr. Merle Point-Johnson Deliverable 2 Submitted July 24, 2021 Data sets are essential for accurate analysis (Dekker, 2021). Having data to measure against other data enhances one’s ability to understand the information. Data sets are an important component when conducting research (Dekker, 2021). Scientific research is based on the gathering and analysis of measurement data. Scientific datasets are intermediate results in scientific research projects (Dekker, 2021). Computers have brought substantial improvements to technology that led to the production of data (Zia & Khan, 2017). The healthcare industry contains very large and sensitive data and can benefit society (Zia & Khan, 2017). Improving the quality of care is a priority and main goal for healthcare organizations. Data comes from patients as well as patients’ health record. The information assists healthcare workers on developing prevention measures for healthcare concerns and enhance quality of care. The United States has an epidemic of type 2 diabetes (Stevens, 2020). Diabetes is a chronic disease that occurs either when the pancreas does not produce enough insulin or when the body cannot effectively use the insulin it produces (Chan, 2016). Diabetes is a health care concern (Chan, 2016). Diabetic Mellitus is a set of diseases in which the body is unable to control the quantity of sugar in the blood (Zia & Khan, 2017). It is a group of metabolic diseases which results in high blood sugar level, may be as the body does not produce sufficient insulin, or may because cells do not react to the produced insulin (Zia & Khan, 2017). The number of cases and the prevalence of diabetes have been increasing over the past few decades (Chan, 2016). An estimate of over 50\% of the adult population will have diabetes by 2022 (Stevens, 2020). More than 90\% of people with prediabetes are unaware and 25\% of people with diabetes are unaware (Stevens, 2020). Over the past decade, diabetes prevalence has risen faster in low- and middle-income countries (Chan, 2016). Diabetes caused 1.5 million deaths in 2012 (Chan, 2016). Increases the risks of cardiovascular disease (Chan, 2016). Many people with diabetes are affected by type 2 diabetes and occur in children now (Chan, 2016). Diabetes causes a substantial economic loss to people with diabetes and their families (Chan, 2016). It affects the health systems and national economies through direct medical costs and loss of work and wages (Chan, 2016). Hospitals and outpatient care is the major expense factor, however; the rise in cost of insulins is a concern (Chan, 2016). Even though type 1 diabetes can’t be prevented at this time, type 2 diabetes can with appropriate interventions. This is by implementing and adapting a healthy lifestyle at school, home and in the workplace (Chan, 2016). Exercising regularly, eating healthily, avoiding smoking, and controlling blood pressure and lipids (Chan, 2016). Education is key to success as in many areas. A whole-of-government and whole-of society approach, in which all sectors systematically consider the health impact of policies in trade, agriculture, finance, transport, education and urban planning (Chan, 2016). The prevalence of diabetes in the United States is increasing rapidly (Grundy, Howard, Smith, Eckel, Redberg, & Bonow, 2020). Individuals with diabetes are at high risk for cardiovascular disorders that affect the heart, brain, and peripheral vessels (Grundy, Howard, Smith, Eckel, Redberg, & Bonow, 2020). The increasing of obesity and sedentary lifestyles, major underlying risk factors for type 2 diabetes in both developed and developing countries, predicts that diabetes will continue to be a growing clinical and public health problem (Grundy, Howard, Smith, Eckel, Redberg, & Bonow, 2020). Collecting data from electronic health records, claims, and patient-reported outcomes is essential in diabetes (Centers for Disease Control and Prevention, 2018). The dataset contains patient vitals, family history, and laboratory values (Centers for Disease Control and Prevention, 2018). Obtaining information from physician office visits is another data set utilized for diabetes. It contains objective data on selected risk factors (e.g., age, sex, race, ethnicity), laboratory results, ambulatory health care services, pharmaceuticals, diagnoses, and a list of diseases drawn from the physician office electronic health record, including diabetes (Centers for Disease Control and Prevention, 2018). Risk factors to diabetes include family history, obesity, ethnicity, and abnormal lipids. Utilizing this information for data set may mitigate diabetes or enhance prevention measure. Data sets including socioeconomic determinants such as education level, occupation, income, ethnicity, sex, and age within a specific area is essential. References Centers for Disease Control and Prevention. (2018). Novel Approaches to State-level Diabetes and Prediabetes Surveillance. https://www.cdc.gov/diabetes/research/modeling/index.html Chan, M. (2016). Global Reports on Diabetes. World Health Organization. https://apps.who.int/iris/bitstream/handle/10665/204871/9789241565257_eng.pdf;Sequence=1 Grundy, S., Howard, B., Smith, S., Eckel, R., Redberg, R., & Bonow, R. (2020). Diabetes and Cardiovascular Disease Executive Summary Conference Proceeding for Healthcare Professionals.105:8 (2231-2239). https://doi.org/10.1161/01.CIR.0000013952.86046.DDCirculation Stevens, S. (2020). The United States of Diabetes: Challenges and opportunities in the decade ahead. UnitedHealth Group. https://www.unitedhealthgroup.com/content/dam/UHG/PDF/UNH-Working-Paper-5.pdf Zia, U. & Khan, N. (2017). Predicting Diabetes in Medical Datasets Using Machine Learning Techniques. International Journal of Scientific & Engineering Research. 8:5. https://www.ijser.org/researchpaper/Predicting-Diabetes-in-Medical-Datasets-Using-Machine-Learning-Techniques.pdf By: Hossin Mosaddad Seminole County Community needs Assesment By: Hossin Mosaddad Major findings from the Community Health Needs Assessment Current population - 473,408 Median household Income - $66,494 8.7\% of the population live below the federal poverty level 29.4\% of the households have incomes under $50,000 74.9\% of the population is Non-Hispanic and 21.7\% is Hispanic (U.S. Census Bureau, 2019) The population of Seminole County, Florida is 473,408 (U.S. Census Bureau, 2019). The average household income is $66,000 (U.S. Census Bureau, 2019). Over 8\% of the population live below poverty level (U.S. Census Bureau, 2019). 2 Unemployment 5\% Poverty Rate 11\% People without health insurance 10\% 109 Overdose death in 2020 (31\% Increase) 17,571 Students In poverty 538 Violent crime offenses (Seminole County, 2021) . Social determinants of health affecting Seminole County residents include 5\% of the population in Seminole County, Florida are unemployed (Seminole County, 2021). Poverty rate is 11\% (Seminole County, 2021). 10\% have no health insurance (Seminole County, 2021). 3 Lack of affordable and adequate housing and homelessness Lack of access to affordable food Lack of good paying jobs, jobs with advancement options, job training Lack of transportation Adverse childhood experiences (ACEs) Increased need of behavioral and mental health services. (Seminole County, 2021) . Social determinants of health affecting Seminole County residents include The social determinants of health affecting Seminole County residents are lack of affordable and adequate housing, lack of access to affordable food, lack of good paying jobs or job advancement, lack of transportation, and increased need of behavioral and mental health services (Seminole County, 2021). 4 IDENTIFIED PRIORITIES: Health Equity Behavioral Health (Including Mental Illness & Substance Abuse) Healthy Weight, Nutrition & Physical Activity (FloridaHealth, 2021) . Community Health Improvement Plan (CHIP) The community health improvement plan know as the CHIP has identified priorities. These priorities include health equity, behavioral health and healthy weight, nutrition and physical activity (FloridaHealth, 2021). 5 Health Equity: Access to Health Care (Mental Health & Dental Care) Affordable Care Poverty/Low Wages Lack of Insurance and Transportation B (FloridaHealth, 2021) . Health Equity Health equity has integrated focus on key elements which include health literacy, access to healthcare, affordable care, poverty and lack of insurance. Focus on these elements present the need to maintain a strong emphasis on care as well as commitment to improved health within the population (FloridaHealth, 2021). 6 Behavioral Health (Including Mental Illness & Substance Abuse) Access to Healthcare (Mental Health) Mental Health/Behavioral Health {Suicide, AGEs) (FloridaHealth, 2021) . IDENTIFIED PRIORITIES The priorities within the social context involve care and commitment to improved level of development. The major issues that are addressed in this case involve behavioural health, access to healthcare. These elements present the basis of a strong emphasis on care which address change development strategy in a given healthcare setting (FloridayHealth, 2021). 7 Health Literacy Affordable Care Access to Health (Mental & Dental Care) Lack of Insurance {Underinsure & Uninsured) Mental Health/Behavioral Health (Suicide, ACEs) (Seminole County, 2021) . Community Health needs Assessment Community health needs involve diverse processes which must be fully integrated within care environment to improve the level and quality of care. The needs within a given setting present a broad context where it is possible to build change and improve the quality of care. Health literacy, affordable care, mental health and access to health present a stronger context for improved care management context (Seminole County, 2021). 8 Hypertension/High Blood Pressure High Cholesterol Obesity and overweight Access to Healthy Affordable Food Dental hygiene/dental care Diabetes (Seminole County, 2021) . Community Health needs Assessment Health challenges within the community are diverse and thus it is imperative to address the common health needs which include high blood pressure, high cholesterol level, obesity, dental hygiene as well as diabetes (Seminole County, 2021). 9 13.5 \% of adults in Seminole county have diabetes 337 deaths per 100,000 in 2018 One of the leading causes of premature deaths in Seminole county. In 2017, roughly 87 men per 100,000 died from diabetes. For women, the rate was 55 deaths per 100,000 (Seminole County, 2021) . Diabetes African Americans and Native Americans have the highest rate of diabetes related mortality (U.S. Census Bureau, 2019). Asians/Pacific Islanders have the lowest (U.S. Census Bureau, 2019). Death related to diabetes is higher in the elderly (U.S. Census Bureau, 2019). 10 Type 1 diabetes is an autoimmune disease 5-10 percent of cases Must take insulin Type 2 diabetes is adult onset 90-95\% of cases Can be prevented Healthy lifestyle changes (Seminole County Diabetes, 2021) Diabetes Diabetes occurs in two ways which include Type 1 and Type 2. Type 1 diabetes occurs in 5-10 \% of the cases. These patients must duly take insulin. Type 2 diabetes is the most common and occurs in around 90 to 95\% of the cases. This can be prevented through a healthy lifestyle (Seminole County Diabetes, 2021). 11 Weight Inactivity Family history Race or ethnicity Age High blood pressure (Seminole County, 2021) Risk Factors There are different elements that are associated with development of diabetes. Older age is associated with increased risk of diabetes with type 2 more common in adults above 50 years. The fattier tissue you have, the more resistant your cells become to insulin. The less active you are, the greater your risk. High blood pressure, family history have also been found to significantly influence the development of diabetes (Seminole County, 2021). 12 (U.S. Census Bureau, 2019) Diabetes This data is based on CDCs multiple cause of death data (U.S. Census Bureau, 2019). Diabetes in noted in the death record but may not be the underlying cause of death (U.S. Census Bureau, 2019). 13 (U.S. Census Bureau, 2019) Diabetes Nationally men are more likely to have diabetes as a cause of death than women (U.S. Census Bureau, 2019). 87 men per 100,000 died from diabetes and 55 women per 100,000 (U.S. Census Bureau, 2019). Women death rate with diabetes continue to decrease (U.S. Census Bureau, 2019). The decrease could be related to differences in behavioral risk factors, access to medical care and biological differences (U.S. Census Bureau, 2019). 14 Teens – Lack of housing and affordable nutritional food Children – Adverse Childhood Experiences (ACEs) and parental stress on a child Intravenous drug users – Endocarditis (infection inside the heart as a result of IV drug use), hepatitis C (due to needle sharing) and sexually transmitted diseases African-Americans have the highest rates of infant mortality per 1,000 births, colorectal cancer and asthma incidences, compared to Whites and Hispanics Whites have the highest rates of breast and lung cancer compared to Blacks and Hispanics. (Seminole County, 2021) . Health inequities identified in Seminole County: Health inequities are inevitable in any given setting since they present a broader basis within which it is possible to improve the quality of care. Lack of housing and affordable nutritional food present a major challenge in delivery of quality care (Seminole County, 2021). 15 Intravenous drug users – Endocarditis (infection inside the heart as a result of IV drug use), hepatitis C (due to needle sharing) and sexually transmitted diseases African-Americans have the highest rates of infant mortality per 1,000 births, colorectal cancer and asthma incidences, compared to Whites and Hispanics Whites have the highest rates of breast and lung cancer compared to Blacks and Hispanics. (Seminole County, 2021) . Key Performance indicators Commitment to improved quality of care present a strong basis within which it is possible to maintain a higher focus on quality healthcare. It is imperative to help create a strong platform to improve the quality of care. Building change involves integration of different approaches which influence the quality of healthcare services (Seminole County, 2021). 16 Increase patient satisfaction by 15\% in a year Decrease obesity rate in the community by 5\% in a year Increase annual primary care visits by 10\% within a year Increase free exercise classes in the community Decrease emergency diabetes cases by 5\% (Gumber & Gumber, 2017). Key performance measures Performance assessment is essential factor that help understand the specific elements that need to be integrated within healthcare quality to improve efficiency and commitment to the need of individuals within the community. Patient satisfaction, internal process quality and financial performance index are crucial elements that present a strong basis to improve the quality of care. Diabetic patients require enhanced care which is crucial in attaining improved level of outcome (Gumber & Gumber, 2017). 17 Personnel Technology systems Expertise and knowledge Financial resources Teamwork (Seminole County, 2021) Current resources available Achieving the set goals requires higher commitment to existing strategies that can help aid improve service delivery. Utilizing available resources forms the basis of change and attaining higher level of engagement. The healthcare setting must effectively focus on using the available resources to attain needed resources. Personnel, technology, expertise and knowledge and financial resources are available resources that can be utilized to advance the set goals (Seminole County, 2021). 18 Multi-centered approach – Ensure cross sectional engagement within healthcare setting with priority to the target group Integrated community care approach – utilize the needs of the community in defining change strategy. Introduce mobile clinics in the community. (Abdoli et al., 2019) Strategies to improve diabetes in the community Improving the level of care engagement within the community require a stronger understanding on change processes which build significant changes that promote change and create a more enhanced basis for improved change and level of engagement. Therefore it would be imperative to ensure the approaches embraced are collaborative and specific in nature based on the underlying problem (Abdoli et al., 2019). 19 Abdoli, S., Jones, D. H., Vora, A., & Stuckey, H. (2019). Improving diabetes care: should we reconceptualize diabetes burnout? The Diabetes Educator, 45(2). 214-224 FloridaHealth.gov (2021). Programs and Services. https://floridahealth.gov Gumber, A., & Gumber, L., (2017). Improving prevention, monitoring and management of diabetes among ethnic minorities: contextualizing the six G’s approach. BMC research notes. 10(1), 1-5 Popeck, L. (2017). Diabetes Rate Rising in Central Florida: How to Reduce Your Risk. Orlando Health. https://www.orlandohealth.com/content-hub/diabetes-rate-rising-in-central-florida-how-to-reduce- your-risk Seminole County Diabetes Death Statistics. (2021). LiveStories. https://www.livestories.com/statistics/florida/seminole-county-diabetes-deaths- mortality Seminolecountyhealth.gov (2021). Community Health Improvement Plan. http://seminole.floridahealth.gov/programs-and-services/community- health-planning-and-statistics/accrediation-performance/_documents/seminole-chna-02-24-2020.pdf U.S. Census Bureau (2019). Quick Facts of Seminole County, Florida. https://www.census.gov/quickfacts/fact/table/seminolecountyflorida . References