Big Data Risks and Rewards discussion Post essay example

Big Data in Healthcare

There are many ways that “big data” is currently being used to positively impact population health. For example, The Cancer Genome Atlas Program has molecularly characterized tens of thousands of cancer samples which has led to improvements in the diagnosis, treatment, and prevention of various types of cancers (National Cancer Institute, 2021). One way that I use “big data” in my current position, is by collecting data on certain metrics, such as CLABSI and CAUTI, for presentation at the Nurse Practice Council.

Data has the potential to increase patient safety by predicting and preventing hospital-acquired infections (HAI). The most obvious way is by using HAI rates as a benchmark to evaluate nursing interventions, such as the incorporation of CHG baths or a new Foley catheter protocol. Another way is by using predictive analytics and AI to actually predict which patients are at the highest risk for developing a HAI. According to HHS, this type of predictive technology has saved hospitals more than $12 billion between 2010 and 2013 (Bresnick, J., 2018).

Risks of Big Data

Unfortunately, there are some unintended risks with the collection of big data. The one that usually comes to mind is the unintended release of data or data hacking. Personal identifiable information is important to keep private to most people. This information could be used maliciously to steal money, take out loans, etc. Although more safeguards are being produced to protect our information, vulnerabilities still exist. Strang, K.D. & Sun, Z. (2019) state “the nature of wireless transmissions is that even encrypted data could be easily intercepted and decoded with currently available software”. One way of combating this issue is by ensuring you are only accessing or sharing data on a secure network.


Bresnick, J. (2018). Using big data analytics for patient safety, hospital acquired conditions. Health IT Analytics.

National Cancer Institute. (2021). The cancer genome atlas program.

Strang, K. D. & Sun, Z. (2019). Hidden big analytics issues in the healthcare industry. Health Informatics Journal, 26(2).

sample response post

I found your post to be informative, and I agree that security is the most significant risk associated with using and collecting big data. Unfortunately, data breaches happen more frequently than people realize. In 2020 alone, data breaches increased by 25% from 2019, and 176 data breaches of 500 healthcare records or more were reported every day (HIPPA Journal, 2021). Surprisingly, Mitchell (2021) states that “the average cost per healthcare record breached increased from $429 in 2019 to $499 in 2020, costing healthcare organizations around $13.2 billion in 2020”. Mitchell also points out that 37 out of the 50 states saw an increase in healthcare data breaches last year. The largest data breach in 2020 happened to Trinity Health, and it involved 3,320,726 people (Jercich, 2020). Using the data above, a breach of that size would cost the organization 1,424,591,454 to 1,657,320,726 dollars. A billion and a half dollars because of a data breach is unfathomable. Nevertheless, it shows that everyone needs to pay attention and ensure that everything is being done to prevent a breach.


Jercich, K. (2020, December 30). The biggest healthcare data breaches reported in 2020. Healthcare IT News.

Journal, H. (2021, March 3). 2020 Healthcare Data Breach Report: 25% Increase in Breaches in 2020. HIPAA Journal.

Mitchell, H. (2021, February 22). Healthcare data breaches up 55.1% in 2020, report finds. Becker’s Healthcare.

sample response 2

Enjoyed reading your post. As part of a clinical method, one of the main benefits of using big data is that it allows early detection of diseases at an early

stage. It is easy to treat and efficiently control diseases as they are identified only early. When diagnosed at an early stage, diseases such as cancer can

be fully treated and can be fatal in most cases if identified early. For example, ovarian cancer is a common condition for women and, with high

mortality rates, it ranks fourth among other cancers. The mortality rate from ovarian cancer is that most people were unaware of cancer before the

disease progressed to Stage III or Stage IV. The key to this problem is early detection to reduce the rate of death from ovarian cancer. The ethical issues

associated with big data are among the primary challenges facing the adoption and application of big data in the clinical system. The risk of a clash

between privacy and personal autonomy has emerged as a crucial problem that is a barrier to the adoption of big data. The use of large quantities of

data could, if accessed by unauthorized entities with malicious intent, reveal private information. The ethical problem of adopting big data can be

resolved by implementing appropriate policy initiatives and frameworks. The policy measure will direct data use and access and ensure that privacy

issues are addressed. The introduction of policy initiatives is a critical step to resolve Big Data-related privacy concerns in full.


Mehta N. and Pandit A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, 114, 57-65.

Yasodha P. and Anathanarayanan N. R. (2015). Analyzing big data to build a knowledge-based system for early detection of ovarian cancer. Indian journal of science and technology. 8(14), 1-7.

Murdoch, T. B., & Detsky, A. S. (2013). The inevitable application of big data to health care. Jama, 309(13), 1351-1352.

Discussion: Big Data Risks and Rewards
By Day 3 of Week 5
Post a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described. Be specific and provide examples.

Main Post:

One way that big data is used in health care is through patient portals to have the patients medical records available to both the patient and providers that are involved in their care.According to the 2019 Brief by Office of the National Coordinator for Health Information Technology [1], nearly 86% (9/10) of hospitals in the United States now have at least a basic EHR system (eg, patient demographics, problem lists, medication lists, and discharge summaries)( Han, Gleason, Sun, Miller, King, Chow, Anderson, Nagy, & Bauer, 2019)This is beneficial because when a patient cannot recall when they had a diagnostic test performed or the results of their lab work it is easily accessible to the health care team. This allows for continuity of care and when patients are presented with a lot of information they can go back into the patient portal and review information like laboratory results, medication history and discharge summaries and request refills and appointments. (Otokiti, Williams , & Warsame, 2020)information, labs and also send messages to their doctors or health care team members. These types of portals also increase safety measures can prevent medication errors from occurring or medications not being updated. However, one of the downfalls of these portals is that there is no universal EHR or portal system being used. This means that if i live in California for 5 years and move to Arizona later on some of my records could possibly get lost. How would a relatively healthy patient know to remember the name of the surgeon who took out his appendix that ruptured and the complications that may have arose when they were 20 and now at 35 that is relevant.Not many, even as a nurse I often forget the importance of keeping track of medical history that at the time seems irrelevant but may become pertinent later on down the road. They other side of the coin with big data is that when we have things like EHR and patients portals it is also an organizations responsibility to monitor the safety and security of their system continuously. These types fo systems are very appealing to cyber criminals because of the information thy contain and the amount of people that have access to the system is large and therefore more opportunities to penetrate the system. They are also remarkably vulnerable to penetration because of the fluid and always-evolving nature of a patient’s medical care and because of the number of clinicians, facilities and transactions required to connect patient care across multiple settings.( Koppell, & Kuziemsky, 2019) This is a huge downside to big data. The liability and possible fines for a data breach could be crippling for an organization.


Han, H.-R., Gleason, K. T., Sun, C.-A., Miller, H. N., Kang, S. J., Chow, S., Anderson, R., Nagy, P., & Bauer, T. (2019). Using Patient Portals to Improve Patient Outcomes: Systematic Review. JMIR Human Factors , 6 (4), e15038.

KOPPEL, R., & KUZIEMSKY, C. (2019). Healthcare Data Are Remarkably Vulnerable o Hacking: Connected Healthcare Delivery Increases he Risks. Studies in Health Technology & Informatics, 257, 218–222.

Otokiti, A., Williams, K. S., & Warsame, L. (2020). Impact of Digital Divide on the Adoption of Online Patient Portals for Self-Motivated Patients. Healthcare Informatics Research, 26(3), 220–228.

By Day 6 of Week 5
Respond to at least two of your colleagues* on two different days, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.

Electronic Health Records (EHRs) are a useful and dangerous tool at the same time. Many organizations have moved to using an EHR to collect and save patient data. These records can be used to save time, money, and lives (Pearl,2016). This data can be used to document allergies, medications, illness ect. There has been an increase in linking biometrics to health records in order to make these records more accurate, reduce the number of charts per patient, and reduce patient misidentifications that may occur with similar names (Muoio, 2020).

You are right, however, that medical records should be connected in some way. Locally we have 2 major hospitals, however, they don’t communicate with each other. If you have a procedure, admission, or ER visit at hospital A and then seek care at hospital B in the future, there is no way to access those records. With multiple EHRs being used it can be hard to ensure all data is correct and reliable. Many patients seek care with more than one provider and it puts patients at risk when records are not readily available (NHS, 2019)

Muoio, Dave. (2020). No-touch palm scanner helps ID patients while dodging COVID-19. Mobihealthnews. scanner-helps-id-patients-while-dodging-covid-19

NHS. (2019). Poor NHS medical record sharing is putting patient lives in danger. Health Europa.

Pearl, Robert. (2016). How an electronic health record can save time, money and lives. Forbes.

sample response 2

The use of electronic health records (EHR) has definitely shown the importance of using big data in a clinical system. With the high number of Americans living with chronic diseases, it can be difficult to remember multiple treatment plans for patients and their providers. Shen et al. (2020) states that “As one of the advantages, patients with certain chronic disease in regular contacts with the healthcare system will definitely have multiple records so that the variability of measurements can be tracked. However, the format of records may vary among different data sets and different systems”. As you mentioned, there is no universal EHR for all healthcare systems, and this could be detrimental to a patient’s health. “The traditional physician‑patient relationship must remain unaffected by such technological additions” (Kumar et al., 2020). If the patient-physician relationship is disrupted due to a patient not understanding how to use a particular EHR, this could unintentionally cause a delay in care by missing an important appointment, or forgetting medications they take when seeing a doctor in a different EHR system.


Kumar, A., Sundar, D., & Agarwal, D. (2020). Commentary: Electronic medical record system – should complement but not replace traditional health care. Indian Journal of Ophthalmology, 68(3), 432–433.

Shen, Y., Zhou, J., & Hu, G. (2020). Practical use of electronic health records among patients with diabetes in scientific research. Chinese medical journal, 133(10), 1224–1230.

response 3

You have made a great point. One of the points you made about the lack of universal EHR was something that played a big role during the Covid-19 pandemic. The lack of the ability to see the entire patient’s medical history became a bit of an issue when the covid vaccine administration began (Pelzman, 2021). There was no way to look up a person’s vaccination record and if they do not posse the vaccination card, there was no proof that they had received it at all. Even without the effect of covid- 19, the lack of a universal EHR makes it difficult to gain access to patients’ health history across the country and it might omit some part of the necessary information about the history along its way to the new healthcare facility. With this bridge in healthcare, comes a bridge in the communication and trust associated with the care of a patient’s life (Primary Care Development Corporation, 2021). Although to many individuals it might not play a big difference in the care, they are receiving but individuals who have chronic illness will be more concerned if all their information is not getting transferred and across to their new healthcare provider, it might create a rift from the beginning because of the lack of knowledge about the patient’s journey through the diagnosis. Creating a universal EHR will help create a universal communication line among all healthcare personnel and this will create a better patient care result.

Pelzman, F. (2021, May 17). COVID Exposes Another Gap in Care: Lack of Universal EHR Access. Retrieved from MedPage TODAY:

Primary Care Development Corporation. (2021, July 1). The Impact of Electronic Health Records and Interoperability. Retrieved from PCDC:

sample response 4

Electronic Medical Records (EMR) evolved from paper-based records to increase safety for patients, staff productivity, and reduction of errors. Patient Portals provides a way for the patient to see his own medical records. I just recently enrolled in a patient portal to access some diagnostic results. Interestingly, I was prompted that I can now link my other patient portals from other healthcare facilities with just a click of a button to integrate all portals together. Yes, I find it convenient for me to be able to see even the old health records even from a few years back. Then it occurred to me, that since all the records are now linked, what happens if one of these portals gets hijacked? Then the portal will become a goldmine for the intruder to get all information about the person if there was a security breach. In these present times, some older individual patients share their passwords to their caregivers may be because they are not computer savvy, or that these people are the ones helping the patients. Sharing login credentials has been associated with enormous security risks because people often reuse their passwords for different accounts, such as online banking or social media ( Das, et al., 2014). Strictly adhering to both the HIPAA Privacy and Security Rule must be done to avoid this complication.

It also presents a problem when caregivers call the hospitals and asks for the password of the patient, they care for to access the portal on the patient’s behalf. Sharing credentials can lead to multiple data security and privacy problems, including revealing more information than the patient intended, and to health care practitioner confusion and mistakes if they do not know with whom they are communicating (Semere, et al. 2014).

Indeed, patient portals are useful and time-saving when we have to look up our records and send communications with our health providers. Yet, we must always be mindful of the possibilities of information system hacking by criminals that a strong and hack proof password must be in place and access given strictly to your provider.


Das A, Bonneau J, Caesar M, Borisov N, Wang X. The tangled web of password reuse. NDSS Symposium. Published February 2014.

Semere W, Crossley S, Karter AJ, et al. Secure messaging with physicians by proxies for patients with diabetes: findings from the ECLIPPSE Study. J Gen Intern Med. 2019;34(11):2490-2496. doi:10.1007/s11606-019-05259-1

Big Data Risks and Rewards Discussion
While there are many potential benefits of using big data as part of a clinical systems, the one that stands out in my view is a test in validity. Most recent events related to Covid had to do with treatments. Initial reaction to the onset of the virus was nebulizer treatments. This course of action of was quickly change when the realization that the virus was airborne and the use of nebs was aerosolizing the contagious spread. While this method did not require too much big data over time, other topics like Walmart’s attempt to change healthcare qualifies as testing validity of big data.

In the following example, the challenge of using big data is to overcome a system (medical) that is ingrained with analogs and protocols which valid a surgeons decision to perform surgery. Offering prove that U.S. employs have reached their limit of tolerance with the countless problems of our medical system, an employee of Walmart who complained of back pain sought initial consultation from a local physician that resulted in recommendation of spinal surgery. Walmart sought second opinion for the employee and the patient was diagnosed with early onset of Parkinson’s Disease; thus avoiding a multi-thousand dollar surgery and recovery that was not needed (Farr, 2019). What chance does a single patient’s opinion have when it took a giant corporation to challenge the current healthcare model and alter this patient’s outcome?

One strategy that exits to mitigate the risk of big data is the proper use of EMRs. The EMR was brought into the spotlight during President Bush’s 2004 State of the Union address when he referenced a 10 year deadline for Americans to utilize EMRs. The purpose of this goal was to avoid dangerous mistakes, make spending more efficient, and improve the healthcare model. It comes as little surprise that the healthcare system was reluctant to embrace EMRs, despite a petition being made for the industry to up their game. Regardless of a slow start, EMRs were at 77% of target in a report published in 2013. Under the Obama administration, incentives or fines were offered for compliance to healthcare organizations. Continued studies are measuring the effects of this administration (McGonigle & Mastrian, 2017).

The use of EMR must be specific in nature, due to it’s boundaryless data. According to Wang et al., (2018), “The first step is to formulate the missions of data governance, with clearly focused goals, execution procedures, governance metrics, and performance measures. In other words, a strong data governance protocol should be defined to provide clear guidelines for data availability, criticality, authenticity, sharing, and retention that enable healthcare organizations to harness data effectively…” The initial physician for the Walmart worker needed to use big data for the best interests of the patient instead of validating the need for surgery. In this case, data governance would intervene for the patient’s best interest.


Farr, C. (2019). Walmart is so desperate to fix health care, it flies employees to top hospitals in other states for treatment. CNBC.

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning, 268-269.

Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3–13.


Good post xxx! The Electronic Health Record (EHR) is one of the best things that could have advanced when it comes to technology. The increasing population demands a system that holds multiple areas of clinical data. Electronic systems are needing to be revised and improved often to ensure patient data is available and documented correctly for any provider that might see the patient. The goal of big data with EHRs is to keep transforming and converting clinical data into knowledge. Another positive to big data and EHRs, is the accessibility of real-time patient information on mobile sites and healthcare apps (Ross et al, 2014).

According to Oregon Health & Science University, improving patient health, health care, public health and biomedical research is the purpose of biomedical informatics, which plays into why big data is so important pertaining to the EHR (McGonigle & Mastrian, 2017). EHRs can be beneficial if a patient is unresponsive, if one is traveling elsewhere, and aiding in providing continuity of care based off the patient’s medical history provided in his/her EMR. The thing that most facilities need to get on board with is having an updated electronic documentation system to fulfil the benefits that big data has to offer. Today’s world is advancing so quickly, using big data now and using it properly can help find cures for diseases, finding and participating in new evidence-based practice and nurses advocating for their patients using the most up-to-date research and health care information to provide the best quality care possible (McGonigle & Mastrian, 2017).


McGonigle, D., & Mastrian, K.G. (2017). Nursing Informatics and the foundation of knowledge

(4th ed.). Chapter 24, “Bioinformatics, Biomedical Informatics, and Computational

Biology ” (pp 537-551). Burlington, MA: Jones & Bartlett Learning.

M.K. Ross, L. Ohno-Machado, & W. Wei. (2014, August 15th). “Big Data” and the Electronic

Health Record.

response 2

You have many valid points on how big data can help and also hurt the health care consumer. Your analysis of big data breaching patient confidentiality is a concern. There has been work on implementing DNA encoding cryptography security on big data stored on the cloud by large healthcare organizations (Nayak, & Jayalakshmi, 2021). With solid security databases in place to protect our patient’s confidential information, big data could move health care in the right direction. The problem is that patient confidentiality makes the progress of healthcare in the information technology world far behind (Vij, & Bathla, 2020). Overall, informatics and big data could make a lot of progress for our field, but I agree with you, Timothy. Big data needs to be protected.


Nayak, L., & Jayalakshmi, V. (2021). A Study of Securing Healthcare Big Data using DNA Encoding based

ECC. 2021 6th International Conference on Inventive Computation Technologies (ICICT),

Inventive Computation Technologies (ICICT), 2021 6th International Conference On, 348–352.

Vij, A., Saini, S., & Bathla, R. (2020). Big Data in Healthcare: Technologies, Need, Advantages, and

Disadvantages. 2020 8th International Conference on Reliability, Infocom Technologies and

Optimization (Trends and Future Directions) (ICRITO), Reliability, Infocom Technologies and

Optimization (Trends and Future Directions) (ICRITO), 2020 8th International Conference On,


NURS 6051 Discussion: Big Data Risks and Rewards
Within our day we interact with multiple data-collecting devices. Every time we swipe our debit card data is sent to that company. They use this to track your spending habits, frequency, likes, and dislikes. They use this data to target your spending behavior and thereby send you information on credit card applications and incentives to entice you to continue to make their companies more money. Health care is similar, but we often think about the information we are collecting. Our electronic health records capture thousands of data points about our patients. In my field, we capture wound size, width, depth. We capture admission information and discharge outcomes that eventually lead to benchmarking standards. When I think of big data collection and health care I think of a company 23and me and other genetic big data collection companies. This company collects DNA samples for people across the world.

“23andMe offers a direct-to-consumer (DTC) genetic testing service based on the use of single-nucleotide polymorphisms (SNPs) to determine ancestry and to identify genetic markers associated with specific diseases and conditions and a few specific causal variants that the company claimed could provide information about their clients’ health and how to improve it(Stoeklé et al., 2016, p. 2).”

This collection of information has connected families and provided insight into your origins and ancestry. This valuable information collected by millions of willing participants is used in many great ways. “This collection of information has connected families and provided insight into your origins and ancestry(Khan & Mittelman, 2018, p. 2).” The use of this information could also one day be used to come up with cures for diseases or find trends in genetic patterns that unlock targeted gene therapy to cure specific disease types. However, with the ability to capture this amount of data comes a price. The data collected from these companies are often sold to other companies looking for this valuable information. Most of that information is used to aid in advancements in health care but some can manipulate it and could use the data in ways we are not aware of now. For example, what if your insurance company was able to retrieve your data and then preclude you from health care due to underlying conditions. This could severely limit coverage and your health care choices. There is also the unintended used some good and some bad we are not aware of. The data of these companies are now being used to solve cold cases and current crimes as the government. A genetic testing company was subpoenaed for access to their records which were used to solve the Golden State killer case. Many of us would have no problem with that but those who submitted their DNA did not sign away their rights to have their data used in that way. “The Fourth Amendment prohibits the government from conducting unreasonable searches of people or their property(Brown, 2019, p. 11).” Whether you agree or disagree about the outcomes of the data search leads to many ethical questions as to what our data is used for. In health care, we are protected and this data appropriation is mitigated by many layers of protection and consents that specifically state what, where, and how our data can be used but those who wish to exploit us, and our patients know the value in this big data and leave us vulnerable to Ransom were attacks and breaches in our information.



Khan, R., & Mittelman, D. (2018). Consumer genomics will change your life, whether you get tested or not. Genome Biology, 19(1).

Stoeklé, H.-C., Mamzer-Bruneel, M.-F., Vogt, G., & Hervé, C. (2016). 23andme: A new two-sided data-banking market model. BMC Medical Ethics, 17(1).

Discussion: Big Data Risks and Rewards
When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee.

From the moment you wake, you are in fact a data-generation machine. Each use of your phone, every transaction you make using a debit or credit card, even your entrance to your place of work, creates data. It begs the question: How much data do you generate each day? Many studies have been conducted on this, and the numbers are staggering: Estimates suggest that nearly 1 million bytes of data are generated every second for every person on earth.

As the volume of data increases, information professionals have looked for ways to use big data—large, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewards—and significant risks—to healthcare. In this Discussion, you will consider these risks and rewards.

To Prepare:

Review the Resources and reflect on the web article Big Data Means Big Potential, Challenges for Nurse Execs.
Reflect on your own experience with complex health information access and management and consider potential challenges and risks you may have experienced or observed.
By Day 3 of Week 5
Post a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described. Be specific and provide examples.

By Day 6 of Week 5
Respond to at least two of your colleagues* on two different days, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.

you bring an excellent example of big data’s pros and cons with the 23 and me and other like-minded companies. This information can bring families together and give people insight into risks for diseases they may not have known about (Kubick, 2013). There is great concern about how that data is used. Interestingly, an exciting thing is happening; however, the first genetic link to depression may have been found because of data from 23 and me (Abbasi, 2017). I believe that these genetic background companies can use their data to help people and help find cures for diseases, but I think there must be a way to protect this data not to get into the wrong hands.


Abbasi, J. (2017). 23 and me, big data, and the genetics of depression. JAMA, The Journal of the

American Medical Association, 317(1), 14.

Kubick, W. R. (2013). Personalized Medicine, Data, and Me. Applied Clinical Trials, 22(10), 24–25.

response 2

What an exciting topic you picked regarding direct-to-consumer genetic testing. I

personally have felt torn on getting my DNA tested for the exact reasons you mentioned, the

unintended consequences. I have always had a fascination with murder mysteries, which is part of the reason I would like to focus my PMHNP on forensic psychology, so using DNA through organizations such as 23andMe or ancestry to catch murderers like the Golden State Killer in California is fascinating.

DNA testing in this regard is vastly unknown, and police investigation has become a hot topic. Two companies and 23andMe, do not voluntarily cooperate with law enforcement (Chrisos, 2020), while GEDmatch now has clients opt if they want to participate in police searches or not (Payne, 2020).

Direct-to-consumer genetic testing can be significant for many reasons, finding long-lost family, tracing lineage, finding common illness within your family tree, but there also comes the risks. According to Raven (2018), there is a lack of appropriate counseling before and after patients get their results. Many factors analyze a patient’s risks regarding genetic diseases and conditions that these at-home kits do not address. Her sound advice is to consult your physician or genetic counselor to analyze your genetic history, risk factors, and concerns.

I feel people are quick to jump on these at-home kits without thinking about the consequences. Putting your information out there is never safe, and a breach of confidentially is always eminent. Becoming more educated on what you are doing, where that information is going, and how it is handled can help inform the person in making a decision they are most comfortable with.

Payne, K. (2020, August 28). Police used a genealogy website to crack an iowa cold case. The tool is raising concerns elsewhere. Iowa Public Radio.

Chrisos, J. (2020, November 17). Thinking about testing your ancestry? Here’s how police, researchers are using the results. WGME.

Raven, K. (2018, November 18). Is an at-home DNA test an ideal gift, really? Yale Medicine.

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