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Our people are passionate about clinical research and advancing the future of medicine. ICON manages an average of 150 studies per year around the world at our various clinical research sites.

We have an experienced team of physicians, clinic and support staff dedicated to making our participants' experience as positive and comfortable as possible. Participant safety is our top priority at all times.

ICON Salt Lake City is conveniently located just minutes from downtown, near St. Mark’s Hospital. With state of the art out-patient facilities and dorm style, semi-private and private rooms, as well as lounges for downtime, we make every effort to make our volunteers’ visit as pleasant as possible. Our 100+ bed research facility is fully equipped to handle the various types of studies we conduct and the physicians and friendly staff are experienced in studies involving healthy volunteers, Alzheimer’s patients, addiction, pain, dentistry, psychiatry, neurology, pediatric research and infectious disease. For more information or to schedule a tour, please call our staff at 1-801-269-8200 1-801-269-8200 , or click here to send us a note.

• Adult & Pediatric Tourette’s
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Dr. Matt Johnston, MD is Board Certified by the American Board of Family Medicine. His emphasis prior to entering clinical research was in clinical primary care and population care.

Dr. Johnston attended undergraduate school at Brigham Young University, majoring in Chemistry with a minor in English Literature. Proceeding to Baylor College of Medicine in Houston, TX for medical training receiving his Medical Doctor Degree. While in medical school he published research in the Hematology Department relating to Hemoglobin C Hemoglobinopathy.

Dr. Johnston continued to the University of Oklahoma, with residency study in Family Medicine. His final year he served as Chief Resident for the program and participated in education and training of students and residents. Dr. Johnston later served as an adjunct professor with the University of Oklahoma teaching medical students in Family Medicine. Completing a master’s degree in Medical Management from Tulane University, with an emphasis on Population Health and Medical Economics allowed Dr. Johnston to serve on multiple hospital administrative boards.

• The medical leadership board for the Cherokee Nation Health System • The Inaugural Board of Directors for the Tulsa County Health Improvement Organization • Pharmacy Therapeutic Board for an insurance company • The Medical Department Chairman at a Regional Hospital • Rural Health Liaison for the Oklahoma Healthy Heart Project

Dr. Johnston joined ICON as a full-time Clinical Research Physician in September of 2017. Serving as a Sub-Investigator and Principal Investigator on studies across multiple disciplines. Studies include: pain/therapeutics, Alzheimer’s disease, depression, immunology, oncology, liver disease, and lipid metabolism. These trials involve first-in-human testing, BA/BE studies, PK/PD trials, drug-drug Interaction, HAL, and multicenter phase II and phase III outpatient studies.

Dr. Ahad Sabet began his professional career at University of Illinois Urbana-Champaign. During his undergraduate training he earned a Bachelor of Science in Cell and Structural Biology as well as a minor in chemistry. This undergraduate curriculum had a strong emphasis on molecular biology and biomedical research.

He completed his first two years of medical school at the Universidad Autonoma de Guadalajara; where he acquired a solid foundation in clinical medicine and fluency in Spanish. He continued his education in Puerto Rico, and ultimately obtained his Medical Degree from Ponce School of Medicine.

After medical school, Dr. Sabet returned to the United States for continued training in Phoenix, Arizona. There he completed a dual residency in Internal Medicine and Pediatrics from Maricopa Medical Center in affiliation with Phoenix Children’s Hospital. He went on to become Chief Resident in Internal Medicine at Maricopa Medical Center and soon thereafter obtained his board certifications in both Internal Medicine and Pediatrics.

Following residency Dr. Sabet embarked on a series of travel medicine assignments. He spent a year working as a consultant physician in New Zealand; after which he returned to work as an Internal Medicine hospitalist in several areas across the western United States. Ultimately, he settled in Salt Lake City and after more than ten years of practicing and teaching clinical medicine, he found his way back to research.

Dr. Sabet joined ICON as a Sub-Investigator in September of 2015. His broad clinical experience has been well employed on trials across multiple disciplines including: pain/therapeutics, anesthesiology, immunology, lipid/metabolism, viral hepatitis, Alzheimer’s disease, and depression. His research experience includes First-In-Human, HAL, BA, BE, VRH, and PK/PD trials in addition to multicenter phase II and III studies. He has ascended through the research ranks and currently serves as Principal investigator on several early and late phase clinical trials.

Dr. Crockett graduated with highest distinction from Colorado State University in 1986 with a B.S. in Biology and minor in Spanish. She graduated at the top10% of her class when she received her Doctor of Medicine in 1990 from the University of Colorado. Dr. Crockett completed a year in clinical Dermatology and an additional year in Pathology at the University of Colorado after completing a transitional internship at the Presbyterian St. Luke’s Medical Center in Denver Colorado. She decided not to pursue a career in Dermatopathology. Dr. Crockett became a diplomat of the American Board of Family Practice in 1995. Dr. Crockett owned and operated Columbine Family Practice until 2017. While she operated Columbine, Dr. Crockett was a Principal Investigator for 18 years. She performed vaginal and C-section deliveries. She had a thriving women’s and pediatric patient population. Many of the trials she conducted were based on Pediatric and Women’s health care needs. Dr. Crockett is an active member of the American Academy of Family Physicians. She trained Family Practice residents from the Mercy Family Practice residency for 18 years. She has been recognized in Who’s Who and Top Doctor for two decades.

After selling Columbine Family Practice, Dr. Crockett worked for the University of Colorado in Sidney, NE. Her duties included being the Medical Director of the Family Outpatient Clinic, supervising the physician assistants in the Emergency Department, operating the OB deck, assisting the general surgeons with operations, and rotating one week a month as a hospitalist and ICU provider. While running the Family Outpatient Clinic in Sidney, NE., Dr. Crockett taught other providers about early reading programs, vaccinations, well child care, normal development and any issues concerning Pediatric patients. During the past two-and-a-half years, Dr. Crockett worked as Medical Director at Science 37. She was involved in decentralized clinical trials. The clinical studies ranged from Phase 1, FIH, through Phase IV clinical trials. The clinical trials focused on issues in Oncology, Dermatology, Internal Medicine, Urology, Rheumatology, Women’s Health, Immunology, Pediatrics, Orthopedics, Neurology and Psychiatry.

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While participation in a clinical study is voluntary, you may be paid for your time and travel. Compensation is based on the length of the study, the number of overnight stays in our clinic and the number of out-patient visits you attend. You may also be compensated for some procedures depending upon the study. All payments we make for study participation have been approved by an Independent Review Board (IRB). The method and frequency of payment will be described in detail in the Informed Consent Form (ICF).

Even if you don’t qualify for a particular study, you may be able to refer a friend or family member. If approved by an Independent Review Board (IRB), ICON may be able to provide you a referral bonus of up to $500 for each qualified study participant that you refer. To qualify for the payment, the person you refer must:

• Be a first-time volunteer

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• Fully participate in the study

All payments from ICON must be approved by an IRB before any payment may be made to you. Please contact us for more information.

The “PP-ICONS” approach will help you separate the clinical wheat from the chaff in mere minutes .

ROBERT J. FLAHERTY, MD

Fam Pract Manag. 2004;11(5):47-52

Keeping up with the latest advances in diagnosis and treatment is a challenge we all face as phycians. We need information that is both valid (that is, accurate and correct) and relevant to our patients and practices. While we have many sources of clinical information, such as CME lectures, textbooks, pharmaceutical advertising, pharmaceutical representatives and colleagues, we often turn to journal articles for the most current clinical information.

Unfortunately, a great deal of research reported in journal articles is poorly done, poorly analyzed or both, and thus is not valid. A great deal of research is also irrelevant to our patients and practices. Separating the clinical wheat from the chaff can take skills that many of us never were taught.

Reading the abstract is often sufficient when evaluating an article using the PP-ICONS approach.

The most relevant studies will involve outcomes that matter to patients (e.g., morbidity, mortality and cost) versus outcomes that matter to physiologists (e.g., blood pressure, blood sugar or cholesterol levels).

Ignore the relative risk reduction, as it overstates research findings and will mislead you.

The article “Making Evidence-Based Medicine Doable in Everyday Practice” in the February 2004 issue of FPM describes several organizations that can help us. These organizations, such as the Cochrane Library, Bandolier and Clinical Evidence, develop clinical questions and then review one or more journal articles to identify the best available evidence that answers the question, with a focus on the quality of the study, the validity of the results and the relevance of the findings to everyday practice. These organizations provide a very valuable service, and the number of important clinical questions that they have studied has grown steadily over the past five years. (See “Four steps to an evidence-based answer.” )

FOUR STEPS TO AN EVIDENCE-BASED ANSWER

When faced with a clinical question, follow these steps to find an evidence-based answer:

Search the Web site of one of the evidence review organizations, such as Cochrane (http://www.cochrane.org/cochrane/revabstr/mainindex.htm), Bandolier ( http://www.jr2.ox.ac.uk/bandolier ) or Clinical Evidence ( http://www.clinicalevidence.com ), described in “Making Evidence-Based Medicine Doable in Everyday Practice,” FPM, February 2004, page 51 . You can also search the TRIP+ Web site ( http://www.tripdatabase.com ), which simultaneously searches the databases of many of the review organizations. If you find a systematic review or meta-analysis by one of these organizations, you can be confident that you’ve found the best evidence available.

If you don’t find the information you need through step 1, search for meta-analyses and systematic reviews using the PubMed Web site (see the tutorial at http://www.nlm.nih.gov/bsd/pubmed_tutorial/m1001.html ). Most of the recent abstracts found on PubMed provide enough information for you to determine the validity and relevance of the findings. If needed, you can get a copy of the full article through your hospital library or the journal’s Web site.

If you cannot find a systematic review or meta-analysis on PubMed, look for a randomized controlled trial (RCT). The RCT is the “gold standard” in medical research. Case reports, cohort studies and other research methods simply are not good enough to use for making patient care decisions.

Once you find the article you need, use the PP-ICONS approach to evaluate its usefulness to your patient.

If you find a systematic review or meta-analysis done by one of these organizations, you can feel confident that you have found the current best evidence. However, these organizations have not asked all of the common clinical questions yet, and you will frequently be faced with finding the pertinent articles and determining for yourself whether they are valuable. This is where the PP-ICONS approach can help.

What is PP-ICONS?

When you find a systematic review, meta-analysis or randomized controlled trial while reading your clinical journals or searching PubMed ( http://www.ncbi.nlm.nih.gov/entrez/query.fcgi ), you need to determine whether it is valid and relevant. There are many different ways to analyze an abstract or journal article, some more rigorous than others. 1 , 2 I have found a simple but effective way to identify a valid or relevant article within a couple of minutes, ensuring that I can use or discard the conclusions with confidence. This approach works well on articles regarding treatment and prevention, and can also be used with articles on diagnosis and screening.

The most important information to look for when reviewing an article can be summarized by the acronym “PP-ICONS,” which stands for the following:

Patient or population,

Intervention,

Comparison,

Number of subjects,

Statistics.

For example, imagine that you just saw a nine-year-old patient in the office with common warts on her hands, an ideal candidate for your usual cryotherapy. Her mother had heard about treating warts with duct tape and wondered if you would recommend this treatment. You promised to call Mom back after you had a chance to investigate this rather odd treatment.

When you get a free moment, you write down your clinical question: “Is duct tape an effective treatment for warts in children?” Writing down your clinical question is useful, as it can help you clarify exactly what you are looking for. Use the PPICO parts of the acronym to help you write your clinical question; this is actually how many researchers develop their research questions.

You search Cochrane and Bandolier without success, so now you search PubMed, which returns an abstract for the following article: “Focht DR 3rd, Spicer C, Fairchok MP. The efficacy of duct tape vs cryotherapy in the treatment of verruca vulgaris (the common wart). Arch Pediatr Adolesc Med . 2002 Oct;156(10):971-974.”

You decide to apply PP-ICONS to this abstract (see "Abstract from PubMed" ) to determine if the information is both valid and relevant.

ABSTRACT FROM PUBMED

Using the PP-ICONS approach, physicians can evaluate the validity and relevance of clinical articles in minutes using only the abstract, such as this one, obtained free online from PubMed, http://www.ncbi. nlm.nih.gov/entrez/query.fcgi. The author uses this abstract to evaluate the use of duct tape to treat common warts.

Problem. The first P in PP-ICONS is for “problem,” which refers to the clinical condition that was studied. From the abstract, it is clear that the researchers studied the same problem you are interested in, which is important since flat warts or genital warts may have responded differently. Obviously, if the problem studied were not sufficiently similar to your clinical problem, the results would not be relevant.

Patient or population. Next, consider the patient or population. Is the study group similar to your patient or practice? Are they primary care patients, for example, or are they patients who have been referred to a tertiary care center? Are they of a similar age and gender? In this case, the researchers studied children and young adults in outpatient clinics, which is similar to your patient population. If the patients in the study are not similar to your patient, for example if they are sicker, older, a different gender or more clinically complicated, the results might not be relevant.

Intervention. The intervention could be a diagnostic test or a treatment. Make sure the intervention is the same as what you are looking for. The patient’s mother was asking about duct tape for warts, so this is a relevant study.

Comparison. The comparison is what the intervention is tested against. It could be a different diagnostic test or another therapy, such as cryotherapy in this wart study. It could even be placebo or no treatment. Make sure the comparison fits your question. You usually use cryotherapy for common warts, so this is a relevant comparison.

Outcome. The outcome is particularly important. Many outcomes are “disease-oriented outcomes,” which are based on “disease-oriented evidence” (DOEs). DOEs usually reflect changes in physiologic parameters, such as blood pressure, blood sugar, cholesterol, etc. We have long assumed that improving the physiologic parameters of a disease will result in a better disease outcome, but that is not necessarily true. For instance, finasteride can improve urinary flow rate in prostatic hypertrophy, but it does not significantly change symptom scores. 3

DOEs look at the kinds of outcomes that physiologists care about. More relevant are outcomes that patients care about, often called “patient-oriented outcomes.” These are based on “patient-oriented evidence that matters” (POEMs) and look at outcomes such as morbidity, mortality and cost. Thus, when looking at a journal article, DOEs are interesting but of questionable relevance, whereas POEMs are very interesting and very relevant. In the study on the previous page, the outcome is complete resolution of the wart, which is something your patient is interested in.

Number. The number of subjects is crucial to whether accurate statistics can be generated from the data. Too few patients in a research study may not be enough to show that a difference actually exists between the intervention and comparison groups (known as the “power” of a study). Many studies are published with less than 100 subjects, which is usually inadequate to provide reliable statistics. A good rule of thumb is 400 subjects. 4 Fifty-one patients completed the wart study, which is a pretty small number to generate good statistics.

Statistics. The statistics you are interested in are few in number and easy to understand. Since statistics are frequently misused in journal articles, it is worth a few minutes to learn which to believe and which to ignore.

Relative risk reduction. It is not unusual to find a summary statement in a journal article similar to this one from an article titled “Long-Term Effects of Mammography Screening: Updated Overview of the Swedish Randomised Trials”: 5

“There were 511 breast cancer deaths in 1,864,770 women-years in the invited groups and 584 breast cancer deaths in 1,688,440 women-years in the control groups, a significant 21 percent reduction in breast cancer mortality.”

This 21-percent statistic is the relative risk reduction (RRR), which is the percent reduction in the measured outcome between the experimental and control groups. (See “Some important statistics” for more information on calculating the RRR and other statistics.) The RRR is not a good way to compare outcomes. It amplifies small differences and makes insignificant findings appear significant, and it doesn’t reflect the baseline risk of the outcome event. Nevertheless, the RRR is very popular and will be reported in nearly every journal article, perhaps because it makes weak results look good. Think of the RRR as the “reputation reviving ratio” or the “reporter’s reason for ‘riting.” Ignore the RRR. It will mislead you. In our wart treatment example, the RRR would be (85 percent - 60 percent)/60 percent x 100 = 42 percent. The RRR could thus be interpreted as showing that duct tape is 42 percent more effective than cryotherapy in treating warts.

SOME IMPORTANT STATISTICS

Absolute risk reduction (ARR): The difference between the control group’s event rate (CER) and the experimental group’s event rate (EER).

Control event rate (CER): The proportion of patients responding to placebo or other control treatment. For example, if 25 patients are in a control group and the event being studied is observed in 15 of those patients, the control event rate would be 15/25 = 0.60.

Experimental event rate (EER): The proportion of patients responding to the experimental treatment or intervention. For example, if 26 patients are in an experimental group and the event being studied is observed in 22 of those patients, the experimental event rate would be 22/26 = 0.85.

Number needed to treat (NNT): The number of patients that must be treated to prevent one adverse outcome or for one patient to benefit. The NNT is the inverse of the ARR; NNT = 1/ARR.

Relative risk reduction (RRR): The percent reduction in events in the treated group compared to the control group event rate.

Absolute risk reduction. A better statistic is the absolute risk reduction (ARR), which is the difference in the outcome event rate between the control group and the experimental treated group. Thus, in our wart treatment example, the ARR is the outcome event rate (complete resolution of warts) for duct tape (85 percent) minus the outcome event rate for cryotherapy (60 percent) = 25 percent. Unlike the RRR, the ARR does not amplify small differences but shows the true difference between the experimental and control interventions. Using the ARR, it would be accurate to say that duct tape is 25-percent more effective than cryotherapy in treating warts.

Number needed to treat. The single most clinically useful statistic is the number needed to treat (NNT). The NNT is the number of patients who must be treated to prevent one adverse outcome. To think about it another way, the NNT is the number of patients who must be treated for one patient to benefit. (The rest who were treated obtained no benefit, although they still suffered the risks and costs of treatment.) In our wart therapy article, the NNT would tell us how many patients must be treated with the experimental treatment for one to benefit more than if he or she had been treated with the standard treatment.

Now this is a statistic that physicians and their patients can really appreciate! Furthermore, the NNT is easy to calculate, as it is simply the inverse of the ARR. For our wart treatment study, the NNT is 1/25 percent =1/0.25 = 4, meaning that 4 patients need to be treated with duct tape for one to benefit more than if treated by cryotherapy.

Wrapped up in this simple little statistic are some very important concepts. The NNT provides you with the likelihood that the test or treatment will benefit any individual patient, an impression of the baseline risk of the adverse event, and a sense of the cost to society. Thus, it gives perspective and hints at the “reasonableness” of a treatment. The value of this statistic has become appreciated in the last five years, and more journal articles are reporting it.

What is a reasonable NNT? In a perfect world, a treatment would have an NNT of 1, meaning that every patient would benefit from the treatment. Real life is not so kind (see “Examples of NNTs” ). Clearly, an NNT of 1 is great and an NNT of 1,000 is terrible. Although it is hard to come up with firm guidelines, for primary therapies I am satisfied with an NNT of 10 or less and very pleased with an NNT less than 5. Our duct tape NNT of 4 is good, particularly since the treatment is cheap, easy and painless.

EXAMPLES OF NNTS

The number needed to treat (NNT) is one of the most useful statistics for physicians and patients. It calculates the number of patients that must be treated to prevent one adverse event or for one patient to benefit. Note that NNTs for preventive interventions will usually be higher than NNTs for treatment interventions. The lower the NNT, the better.

The following examples of NNTs are borrowed from an excellent list available through the Bandolier Web site at http://www.jr2.ox.ac.uk/bandolier/band50/b50-8.html .

Note that NNTs for preventive interventions (e.g., the use of aspirin to prevent cardiac problems) will usually be higher than NNTs for treatment interventions (e.g., the use of duct tape to cure warts). Prevention groups contain both higher-risk and lower-risk individuals, so they produce bigger denominators, whereas treatment groups only contain diseased patients. Thus, an NNT for prevention of less than 20 might be particularly good.

When discussing a particular therapy, I explain the NNT to my patient. Since this statistical concept is easy to understand, it can help the patient be a more informed partner in therapeutic decisions.

You will soon start to see a similar statistic, the number needed to screen (NNS), which is the number of patients needed to screen for a particular disease for a given duration for one patient to benefit. 6 Although few NNSs have been calculated, they are likely to involve higher numbers, since the screening population consists of patients with and without the disease. For example, in the article on mammography screening mentioned above, the NNS was 961 for 16 years. In other words, you would need to screen 961 women for 16 years to prevent one breast cancer death.

The good news and the bad

Using PP-ICONS to assess the wart study, the problem, the patient/population, the intervention, the comparison and the outcome are all relevant to your patient. The number of subjects is on the small side, making you a little wary, but the intervention is cheap and low-risk. The statistics, particularly the NNT, are reasonable. On balance, this looks like a fair approach, so you call the patient’s mother and discuss it with her.

The PP-ICONS approach is an easy way to screen an article for validity and relevance, and the abstract often contains all of the information you need. Even the statistics can be done quickly in your head. You can apply PP-ICONS when searching for a particular article, when you come across an article in your reading, when data are presented at lectures, when a pharmaceutical representative hands you an article to support his or her pitch, and even when reading news stories describing medical breakthroughs.

Don’t be discouraged if you find that high-quality articles are rare, even in the most prestigious journals. This seems to be changing for the better, although many careers are still being built on questionable research. Nevertheless, screening articles will help you find the truth that is out there and will help you practice the best medicine. And as we become more discerning end-users of research, we might just stimulate improvements in clinical research in the process.

Miser WF. Critical appraisal of the literature. J Amer Board Fam Pract . 1999;12(4):315-333.

Guyatt GH, et al. Users’ guides to the medical literature. How to use an article about therapy or prevention. Are the results of the study valid?. JAMA . 1993;270(21):2598-2601.

Lepor H, et al. The efficacy of terazosin, finasteride or both in benign prostatic hyperplasia. Veterans Affairs Cooperative Studies Benign Prostatic Hyperplasia Study Group. N Engl J Med . 1996;335(8):533-539.

Krejcie RV, Morgan DW. Determining sample size for research activities. Educational and Psychological Measurement . 1970;30:607-610.

Nystrom L, et al. Long-term effects of mammography screening: updated overview of the Swedish randomised trials. Lancet . 2002;359(9310):909-919.

Rembold CM. Number needed to screen: development of a statistic for disease screening. BMJ . 1998;317:307-312.

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Copyright © 2024 American Academy of Family Physicians. All Rights Reserved.

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MedFuzz: Exploring the Robustness of Large Language Models in Medical Question Answering

• Robert Osazuwa Ness ,
• Hayden Helm ,
• Katie Matton ,
• Sheng Zhang ,
• Junaid Bajwa ,
• Carey E. Priebe ,
• Eric Horvitz

Large language models (LLM) have achieved impressive performance on medical question-answering benchmarks. However, high benchmark accuracy does not imply that the performance generalizes to real-world clinical settings. Medical question-answering benchmarks rely on assumptions consistent with quantifying LLM performance but that may not hold in the open world of the clinic. Yet LLMs learn broad knowledge that can help the LLM generalize to practical conditions regardless of unrealistic assumptions in celebrated benchmarks. We seek to quantify how well LLM medical question-answering benchmark performance generalizes when benchmark assumptions are violated. Specifically, we present an adversarial method that we call MedFuzz (for medical fuzzing). MedFuzz attempts to modify benchmark questions in ways aimed at confounding the LLM. We demonstrate the approach by targeting strong assumptions about patient characteristics presented in the MedQA benchmark. Successful “attacks” modify a benchmark item in ways that would be unlikely to fool a medical expert but nonetheless “trick” the LLM into changing from a correct to an incorrect answer. Further, we present a permutation test technique that can ensure a successful attack is statistically significant. We show how to use performance on a “MedFuzzed” benchmark, as well as individual successful attacks. The methods show promise at providing insights into the ability of an LLM to operate robustly in more realistic settings.

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• She had faced financial struggles and self-doubt, delaying her dream of becoming a doctor.
• At 50, she enrolled in medical school, inspired by the pandemic to help her community.

When my friend pitched me the idea of auditioning for a game show to make some money, I thought she was kidding. I never expected that two weeks later, I'd be flying home from a game show victory in Los Angeles with a trophy and a check for $10,000.

I used the prize money to pay for the first semester of graduate school, and later, I enrolled in medical school at 50 years old. It was the best decision I could've ever made.

My childhood dream was to be a doctor

I was always a gifted student . My peers labeled me as "the intelligent one," though I would say chronic overachiever was a more accurate description.

But when I went off to college in the late 1980s, I found myself surrounded by many other brilliant minds and realized that maybe I wasn't so special. Unsupportive professors only magnified my self-doubt; I remember one who said girls learned slower than boys and another who suggested the girls sit in the back of the room because none of us were going to use our degrees.

I lost faith in myself and let go of my dreams to be a doctor. I graduated with a degree in liberal arts and settled into a job at a coffee shop.

When I met my first husband at 24, I clung to our relationship as my source of identity. He reassured me it was okay I didn't know what I wanted to do with my life and that he would take care of me. We got married at 26 under the pretense that we'd try for kids right away and I would quit my job to care for them.

A challenging pregnancy had me in and out of the hospital and restricted to bed rest. My twin boys were born prematurely and required a year of isolation within the home. Shortly thereafter, one of my boys was diagnosed with autism and thus began the relentless hunt to find services for him. I loved having my babies at home, but the first two years of their lives were exhausting.

By the time they hit four, my boys were healthy, meeting all their milestones, and getting ready to enter kindergarten. I was finally able to take a breath, and my career ambitions crept back in.

I applied for a master's program without the money for it

When I told my ex-husband about my desire to go back to school , he shut me down, saying we didn't have money for it and making disparaging remarks about my intelligence.

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Our conflicts continued and ultimately led to a divorce when our boys were five. I became their primary caretaker and took on dual jobs as a barista and receptionist to make ends meet.

I was determined to continue my education so I applied for a master's program in special education. I figured I'd learn how to better accommodate my autistic son in a career that would allow me to work during school hours.

But I didn't have a way to pay for it. I applied for several scholarships and grants through Portland State University, but I was still about $10K short on tuition.

My friend convinced me to audition for a game show

I was hanging out at a friend's house and telling her about my financial woes when she joked about finding a part-time gig on Craigslist. We started sifting through sketchy job postings and laughing at the absurdity until my friend stumbled upon a local casting call for Singing Bee, a game show on Country Music Television.

She knew I had a knack for memorization and I loved country music, so she begged me to audition. I wasn't sold on the idea until she told me about the prize money . Then, I was all in.

That Thursday, she drove me to the local Marriott to join 700 other auditioners. We were ushered through rounds of auditions until the number of applicants was whittled down to 30, and then they sent us home.

A few nights later, I got a call from a Singing Bee representative offering to fly me to Los Angeles the next morning to compete on the show. He promised free hotel accommodations and a minimum prize of $1000. I frantically called people to watch my boys, then I packed my bags.

I never expected to win $10,000

The whole experience was a complete whirlwind. I flew to LA and a few hours later found myself standing on a television sound stage with six other country music fanatics anxiously awaiting directions from the host. I got completely in the zone as we played the game until it was between me and one other woman. She was nailing every lyric, and I thought I was toast — but then she missed a word on a song and they told me if I could get it right, I'd win the game .

I did. I was shocked as I was given a trophy and a check for $10,000 — exactly what I needed to fund the first semester of my master's degree.

I started doing research and dabbling in medicine

I pursued the master's degree while still working service jobs, but my heart wasn't in teaching. My advisor helped me change my focus to research, and I was hired as a full-time researcher at my university's Autism Research Institute the day after I graduated.

I began to work in local hospitals and lean into the biomedical aspect of autism studies while pursuing a master's in nutrition at Notre Dame of Maryland.

By 2013, I had met my now-husband. My boys and I moved into his house in a tiny town off the coast of Washington while I continued doing research and finding my space in medicine. I was so close to my childhood dream, but, I thought I was too old in my 40s to apply for medical school.

The pandemic made me realize it was time to help

In 2020, I saw the devastation that the pandemic caused to our rural community which was already a medically underserved area. The physician suicide rate was skyrocketing and healthcare workers were overworked and exhausted. I remember telling my husband that I could sit here and be angry about what was going on or I could be a part of the solution. I threw all my self-doubt aside and knew it was time to go back to school.

At 50 years old, I enrolled in Pacific Northwest University's medical school. I would be lying if I said I wasn't terrified, but I have my husband, beautiful boys, and parents to thank for being my biggest cheerleaders. I'm three years into my studies now, and there are so many benefits to starting medical school in my 50s.

Because my husband and I bought and sold properties and invested , I feel more financially stable than ever before.

I'm also more emotionally and mentally stable. After raising two twin boys, nothing fazes me. I can multitask and roll with the punches. Some of my younger peers freak out over a failed exam, but I'm able to let it roll off my back and keep moving.

Luckily, my different life experiences don't ostracize me from my peers; it just feels like I'm hanging out with my friends even if I'm their mom's age.

The most amazing part of going to medical school later in life is that I've already lived such a full life. I've raised my kids, fallen in love, and traveled to more places than I could ever imagine. Medical school isn't filling any holes in my life, it is just another experience to add to it.

My goal is to become a primary care physician which I'm expected to reach at age 57. It's taken over half a century, but I'm proud to say I'm finally pursuing my dream.

If winning a game show changed your life and you would like to tell your story, please email Tess Martinelli at [email protected] .

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• Personal Finance

This Biden Administration Proposal Just Might Salvage Your Credit Report

Published on Aug. 13, 2024

By: Dana George

• The Biden administration wants medical bills removed from credit reports to prevent lenders from making decisions based on medical information.
• Medical bills do not serve as a fair indicator of how likely someone is to pay their bills.
• Medical debt is the top reason for bankruptcies in the U.S.

Medical debt is no joke. Not only does the U.S. have the most expensive healthcare of any country, but medical debt is the No. 1 reason Americans file for bankruptcy, according to the American Medical Association (AMA).

Medical debt can also play havoc on a person's budget and personal finances, causing their credit score to plummet and making it harder for them to get credit when it's needed.

A step in the right direction

Two years ago, Experian, Equifax, and TransUnion -- the big three national credit reporting agencies -- announced that they were removing medical debts under $500 from credit reports. Removing relatively small medical debts certainly represented a step in the right direction for many U.S. consumers. Still, 15 million Americans were left with $49 billion worth of medical bills on their credit reports.

The Biden administration plan would force credit reporting agencies to go much further.

What this could mean for you

What matters is how erasing medical debt from credit reports will impact the everyday American. If your credit report currently lists medical expenses among your unpaid debts, here's how this change may benefit you.

Your credit score will get a boost

The Consumer Financial Protection Bureau (CFPB) estimates that Americans with medical debt on their credit reports will see their credit scores rise by an average of 20 points once medical debt is removed. A sudden 20-point boost may be just what some households need to qualify for a loan or open a credit card.

Your medical issues won't be public knowledge

While credit reports only show that you have outstanding medical debt and don't spell out the specifics, anyone who sees a copy of your report can tell that you (or someone in your household) have been ill.

That may not matter if you're applying for a car loan, but it could impact whether a potential employer checking your credit report decides to take a chance on you or a landlord believes you can pay your rent every month. In other words, it raises questions that should never be raised.

Your medical equipment cannot be repossessed

The proposed rule would prevent lenders from repossessing medical equipment like wheelchairs if you can't repay a loan.

Bill collectors can no longer use medical debt as a weapon

According to the CFPB, under the current system, medical debt collectors use the credit reporting system to force people to pay debts -- some of which they may not owe. CFPB reports that many debt collectors use a practice known as "debt parking."

Here's how it works: Debt collectors purchase medical debt at a discount. They then place the debt on your credit report, typically without your knowledge. It's only when you apply for credit that you discover that medical debt is holding you back from loan approval.

If you really need that loan, you may feel forced to pay the medical bill just to get it off your credit report and improve your credit score. Once medical debt no longer shows up on credit reports, bill collectors can no longer use this manipulative tactic.

This doesn't mean debt will be erased

There are undoubtedly benefits associated with having medical debts removed from your credit report, but you will still be responsible for repaying the debt . The point of removing the debt from your report is to make it easier for you to carry on with your financial responsibilities and get back on your financial feet.

The CFPB will continue to accept comments and feedback on the Biden administration proposal through Aug. 12, 2024. If all goes well, the rule will be finalized early next year.

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Dana is a full-time personal finance writer, with more than two decades of experience. Her focus is on helping readers feel less alone as they navigate their personal finances and offering actionable insights.

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• News for Globus Medical

Globus Medical (GMED) Receives a Hold from Oppenheimer

In a report released today, Steven Lichtman from Oppenheimer maintained a Hold rating on Globus Medical ( GMED – Research Report ), with a price target of $73.00 . The company’s shares closed yesterday at $67.32.

According to TipRanks , Lichtman is a 5-star analyst with an average return of 11.5% and a 52.65% success rate. Lichtman covers the Healthcare sector, focusing on stocks such as Dexcom, Zimmer Biomet Holdings, and Tandem Diabetes Care.

In addition to Oppenheimer, Globus Medical also received a Hold from Truist Financial’s Richard Newitter in a report issued today. However, on the same day, Barclays assigned a Buy rating to Globus Medical (NYSE: GMED).

Based on Globus Medical’s latest earnings release for the quarter ending June 30, the company reported a quarterly revenue of $629.69 million and a net profit of $31.76 million. In comparison, last year the company earned a revenue of $291.62 million and had a net profit of $57.71 million

TipRanks tracks over 100,000 company insiders, identifying the select few who excel in timing their transactions. By upgrading to TipRanks Premium, you will gain access to this exclusive data and discover crucial insights to guide your investment decisions. Begin your TipRanks Premium journey today.

Globus Medical (GMED) Company Description:

Globus Medical, Inc. operates as a medical device company that develops and commercializes healthcare solutions. The firm engages in developing products that promote healing in patients with musculoskeletal disorders. It classifies products into Innovative Fusion and Disruptive Technology. It operates through the United States and International geographical segments. The company was founded by David C. Paul, David D. Davidar and Andrew Iott in March 2003 and is headquartered in Audubon, PA.

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