Brief description of the disease/condition you selected and the data sources
The human immunodeficiency virus (HIV) is a virus that attacks the body’s immune system and can lead to AIDS (acquired immunodeficiency syndrome) It is an Infectious disease that has caused high mortality around the world since 1981 (CDC, 2020). It has no Cure, however, Antiretroviral therapy (ART) suppresses viral load by keeping CD4 cell counts (immune response) high which effectively increases life expectancy and reduces transmission of the virus. ART helps keep individuals with low viral count so that they can have good quality of life. (CDC, 2019) According to the CDC ‘1.2 million people in the U.S. are living with HIV today. About 14 percent of them (1 in 7) don’t know it and need testing’.(CDC, 2019)
Case protocol for the data sources
The surveillance system for HIV in the United States is a centralized system, managed and funded by the Center for Disease control. (CDC, 2020) The CDC’S National HIV Surveillance System monitors all HIV cases nationwide. By having a centralized surveillance system it will prevent reporting the same case twice if a person with HIV moves to different states several times in their lifetime.This is documented in the Case Report Form and the CDC’s Routine Interstate Duplicate Review (RIDR) process which is part of the ongoing surveillance process that occurs in every state. (Florida Health Department, 2020). The protocol consists of a uniform system that reports single cases from within the health system to the local Health departments in every state, which then report de-identified data to the CDC. This process helps the CDC to locate and oversee program funding to address this issue by mitigating prevalence and improving the lives of individuals at risk (CDC, 2020)
. How the accuracy of that data might influence disease surveillance.
The definition of surveillance of HIV has changed throughout the years in the US as scientists began to better understand the way this virus acts on the human body and its consequences for human health. As part of surveillance, The CDC now requests classification of cases depending on the stage of the virus (0,1,2,3 or unknown) where 0 is an early infection with a negative test result within 6 months and stage 3 is when an individual has AIDS. (CDC, 2014)
In Florida, the local surveillance program analyzes trends to develop projects and assess risks. This program is managed by HIV staff at the local level who review irregularities, such as duplication of cases, to obtain accurate data and be able to use it to plan the implementation of HIV programs at the local level (Florida health department, 2020). In general, there is an active way for health care practitioners and labs to report to Health departments and a passive way. When the health department requests lab results and records to ensure accuracy these two methods are regulated by the CDC as the final point of reporting the information (Ngugi et al, 2019)
Another surveillance system for HIV is The National HIV Behavioral Surveillance (NHBS) that monitors individuals who participate in high risk behaviors such as injection drug users and men who have sex with many men in metropolitan areas with high rates of HIV. This program works in three year cycles, examining risky behaviors, HIV testing, medical care, and prevention services. In South Florida The University of Miami collaborates with the CDC in an effort to provide services for this at-risk population and to obtain data for future implementations such as a new community program to address these high risk behaviors and prevent HIV transmission. (Florida health Department, 2020)
Center For Disease Control and Prevention. 2019. HIV. Art Adherence https://www.cdc.gov/hiv/clinicians/treatment/art-a…
Center For Disease Control and Prevention. Estimated HIV incidence and prevalence in the United States, 2014-2018. HIV Surveillance Supplemental Report 2020; 25(No. 1). https://www.cdc.gov/hiv/pdf/library/reports/survei…
Center For Disease Control and Prevention.. Revised Surveillance Case Definition for HIV Infection — United States, (2014). MMWR Recommendations & Reports, 63(3), 1–10. https://www.cdc.gov/mmwr/preview/mmwrhtml/rr6303a1.htm
Florida Health Department. 2020. HIV/AID Surveillance program. http://www.floridahealth.gov/diseases-and-conditions/aids/surveillance/index.html
Florida Health Department. 2020. National HIV Behavioral Surveillance Program http://www.floridahealth.gov/diseases-and-conditions/aids/surveillance/behavioral-survellance1.html
Ngugi, B. K., Harrington, B., Porcher, E. N., & Wamai, R. G. (2019). Data quality shortcomings with the US HIV/AIDS surveillance system. Health Informatics Journal, 25(2), 304–314. https://doi-org.ezp.waldenulibrary.org/10.1177/146…
RE: Discussion – Week 2
Post a brief description of the disease or conditioned you selected and the data sources you would use
I selected the Corona Virus disease. This is an infectious disease that started in December 2019 in Wuhan Province in China. By 31st January 2020 it had spread to 19 countries causing a total number of 11791infections and 213 deaths. It was then declared an International Public Health Disaster by the World Health Organization. This disease spreads fast and has since affected many people worldwide and caused a change in many activities that are done. The governments of many countries have been adopting strict measures to curb the control of this infectious disease. The outbreak of the disease has been linked to a seafood market in Wuhan. However, there has not been any treatment for the disease found this far any only symptomatic treatment and supportive care applies (Adhikari, 2020).
The data sources that I can use to get information on this infection include facility-based reports. This include the reports from hospitals that give information on the cases that have been reported in the various hospitals on COVID-19. This source of information is the so effective because the doctors in the hospitals are able to examine the patients with symptoms related to those of coronavirus and determine the number of people with the infection. This makes the hospital reports a very reliable source on the data on the infection therefore making it possible to come up with measures to control the disease (Ritchie, 2020).
Using surveillance-based methods is another great way to get data on the infection. Carrying out surveys will give me information about the disease by interacting with people from various places through media to get to know how they are exposed to the risk of the infection and come up with ways to keep them off from further contracting the disease. After giving this information to people via the media platforms like Facebook it is easy to give the instructions to the public on what is expected of them to avoid getting the disease. If the data gotten from the surveys is wrong there is likely to be a wrong analysis made about the disease (Ritchie, 2020).
Other sources of data on the Corona virus disease are social media platforms. These platforms are being used to pass information to the public on the prevalence of the disease, how it can be controlled and how effective or non-effective the strategies to control it are. These sources are able to reach so many people because people are recently using these platforms with the current advancements in technology (Maher, 2020). If people give the correct information on the disease through these platforms this increases the possibility of gathering the correct data to use in the implementation of the strategies for controlling the disease. The information can as well fail to reach people who don’t have access to the social media platform therefore making them be left behind.
Collecting laboratory data is another useful source of data for COVID-19. Data from the laboratory will be useful in doing investigations concerning the outbreak of the disease. When the cause of the disease is established, a report can be issued to the general population to avoid the things that further cause the infection to occur. Data is also gotten from the public announcements that are done concerning this disease. The information that is issued to the people keeps them on the toes and they find the need to take the necessary precaution against the infection (Maher, 2020).
The death reports can as well be a source of information concerning the pandemic. When the death occurs due the disease; when people get to hear about the rising number of deaths on COVI-19 they will take the necessary precaution measures to avoid dying. The government also takes an extra effort to ensure that all its people are protected as required (Maher, 2020).
Adhikari, S. P. (2020, March 17). Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: a scoping review. Retrieved from BMC: https://idpjournal.biomedcentral.com/articles/10.1…
Maher, K. H. (2020). Collecting Data. Retrieved from Epidemic Intelligence Service : https://www.cdc.gov/eis/field-epi-manual/chapters/…
Ritchie, H. (2020). Coronavirus Source Data. Retrieved from Our world in Data: https://ourworldindata.org/coronavirus-source-data
2 days ago
Dominique Morgan RE: Discussion – Week 2
Brief description of the disease/condition you selected and the data sources you would use
Diabetes is a chronic condition that impacts how the body turns food into energy (Centers for Disease Control and Prevention (CDC), 2020b). As the seventh leading cause of death in the United States, diabetes affects over 34 million people (CDC, 2019). Of those over 34 million people, about 90-95% cases are type 2 diabetes and about 5-10% are type 1 diabetes (CDC, 2020a). As Americans are aging, and the overweight and obesity rates have increased in the last 20 years, the rates of those diagnosed with diabetes have more than doubled (CDC, 2020a). Some of the data sources used to monitor diabetes are physician office visits, data from pharmacies, and laboratory requests.
Justify your selection of each of the data sources you identified
When a patient goes to the doctor, the physician will collect extensive information from the patient about their health history and any symptoms they may be experiencing. The physician collects information about the patients’ health history, family health history, symptoms, medications they take, and more (Lombardo & Buckeridge, 2007). According to Lombardo and Buckeridge (2007), a physician getting health history data is a beneficial tactic to get information about trends. This data is collected from insurance databases, and ICD-9 codes are used (Lombardo & Buckeridge, 2007). Most diabetics are under the care of a physician, so this would be a valuable data source when monitoring trends in diabetes, including detailed information on rates of diagnosis, treatment options, as well as co-morbidities, and mortalities.
Using data from pharmacies to monitor diabetes is also a valuable data source because it helps track trends in medication use. A pharmacy can provide the types of data in monitoring diabetes trends when a patient purchased the medication, the type of medication and amount prescribed, and where the store is that the drug was purchased (Lombardo & Buckeridge, 2007). Data like this helps to trace how people with diabetes comply with taking their medication as prescribed, looking for barriers to purchasing it, and if the medication is effective for managing the condition. Lastly, laboratory tests are an essential data source. While at the office visit, the physician may order lab tests to check the diabetic patients’ A1C or blood sugar level. These levels indicate how diabetes treatment is working and is an integral part of creating a plan to manage diabetes (American Diabetes Association, n.d.). Like physicians, laboratories report data on chronic conditions like diabetes to state health departments and national data collection databases to analyze if treatments effective.
Briefly address the case protocol (if appropriate) for the data sources and describe how the accuracy of that data might influence the disease surveillance
Procedures involved in collecting data for physician office visits include gathering information about the patients’ current symptoms, taking a detailed health history, and the actual exam of the patient. Using physician office data could validate other data sources, confirm disease outbreak suspicions, and provide more evidence to the type of outbreak versus other data sources (Lombardo & Buckeridge, 2007). In pharmacy chains, pharmacy sales information is collected by using the manufacturer codes on the product; Universal Product Codes (UPC) for over-the-counter drugs and National Drug Codes (NDC) for prescription drugs (Lombardo & Buckeridge, 2007). This type of data collection is useful in the surveillance of potential outbreaks as well. For example, if sales of cold/flu medications are higher than usual, researchers would further investigate if there has been an outbreak. Lastly, laboratory data is collected when a physician orders a test for a patient. It is assumed that a disease may be high on the suspicion index, so they want to either confirm or rule out the disease by using that test (Lombardo & Buckeridge, 2007). The accuracy of the data from these sources is vital in guiding the surveillance of the data.
American Diabetes Association. (n.d.). Understanding A1C. https://www.diabetes.org/a1c
Center for Disease Control and Prevention. (2019). Diabetes basics. https://www.cdc.gov/diabetes/basics/diabetes.html
Centers for Disease Control and Prevention. (2020a). Diabetes fast facts. https://www.cdc.gov/diabetes/basics/quick-facts.html
Centers for Disease Control and Prevention. (2020b). What is diabetes. https://www.cdc.gov/diabetes/basics/diabetes.html
Lombardo, J.S. & Buckeridge, D.L. (2007). Disease surveillance: A public health informatics approach. John Wiley & Sons, Inc Publications.
2 days ago
Carlin Nelson’s RE: Discussion – Week 2
Post a brief description of the disease/condition you selected and the data sources you would use.
The condition that I have selected is opioid abuse, leading to opioid addiction and deaths attributed to overdose. Opioid abuse has grown exponentially in the United States. An opioid is a group of drugs that are used to reduce pain and historically has been introduced to the United States in three trends or “waves”. Those three waves are the prescription opioids wave (introduced by physician’s over prescribing), the heroin wave (an illegal substance that permeated urban and rural areas), and the third wave, fentanyl (an artificial opioid that was made to act as an analgesic for extreme medical cases such as late-stage cancers) (Centers for Disease Control and Prevention, 2017). Opioid abuse is an urge of dependency to use opioids when it is no longer medically needed (U.S National Library of Medicine, 2020). The National Survey on Drug Use and Health in 2018 found that “the vast majority of past-year opioid users in 2018 misused prescription pain relievers. Specifically, 9.9 million people aged 12 or older in 2018 misused prescription pain relievers in the past year compared with 808,000 people who used heroin” (SAMHSA,2018).
The data sources I would use to monitor the prescription opioids wave, while it varies from state to state, an excellent example of a data source to observe over-prescribing on the physician’s behalf is California’s Controlled Substance Utilization Review and Evaluation System (CURES). For those patients that are “doctor shopping” and in my experience as a pharmacy technician, there are internal and externals databases where notes are associated with patient’s medical record number (MRN) that cautions the prescriber about distributing certain medications too quickly or if the patient may have already visited another clinic/prescriber seeking similar items. Concerning the heroin and fentanyl waves, the data source that I would use is “data from hospital visits and data from EMS and 911” (Lombardo and Buckeridge, 2007).
Justify your selection of each of the data sources you identified.
The data source that I chose to monitor the prescription opioids wave is the statewide electronic database like California’s Controlled Substance Utilization Review and Evaluation System (CURES). CURES, a statewide database that in real-time keeps a record of controlled substances, including the physician’s name, physician’s prescribing record and patterns/ trends, pharmacy where the drug was obtained, etc., to assist in reducing overprescribing (Jurkowitz et al., 2013). I chose this data source because it is the first of its kind, with parallels from pharmacy chains’ data. Data sources like this help hold both the prescriber and patient accountable. To properly monitor addiction in the heroin and fentanyl waves, I chose data from hospital visits, and data from EMS and 911 like Agency for Healthcare Research and Quality’s (AHRQ) Healthcare Cost and Utilization Project (HCUP) because I believe these data sources gives the holistic picture and can be applied for various scenarios regarding these waves including possible suicide, suicidal ideation, drug abuse, and overdose. All three of these data sources utilize notes, ICD-9, and ICD-10 codes to notify other public health professionals of the situation regarding a patient who may have opioid dependency (Lombardo and Buckeridge, 2007). All three of these data sources also prioritize biomarkers, testing, symptoms, and signs to create a profile concerning not only this patient’s diagnosis/condition but also a general profile to help identify similar/same cases to disseminate amongst health agencies (local, state and federal).
Briefly address the case protocol (if appropriate) for the data sources and describe how the accuracy of that data might influence the disease surveillance.
Opioid abuse is a crisis that affects all walks of life, including but not limited from the homeless population to the upper echelon in society. Different data sources have similar protocols with other variables, and indicators. The Agency for Healthcare Research and Quality’s (AHRQ) Healthcare Cost and Utilization Project (HCUP) collects data from physician visits as well as emergency department (ED) visits and defines a case of opioid abuse through medical history, chief complaint, ICD-9/ICD-10 codes, symptoms, and observation by signs of illicit use like needle marks on the arms or between the toes and biological testing. While all data sources have limitations, the AHRQ-HCUP, “the nation’s most comprehensive database for hospital care data” (AHRQ, 2019), must be accurate because they provide data to other agencies in aims of recognizing, reducing/eliminating trends and improving healthcare. Data sources like AHRQ-HCUP, CURE and others assist in creating a case profile to help all levels/types of surveillance recognize those who are abusing opioids, develop protocols on how to handle opioid abuse, and create awareness for signs and symptoms to prevent opioid abuse.
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