The initiative seeks to drastically reduce asthma hospitalizations for low-income children and demonstrate the cost savings to healthcare of investment in housing improvements.
In New York City, households with cockroaches are 50 percent more likely to have someone diagnosed with asthma compared to the general population, and those with mice are twice as likely. 1 While local law requires many New York City property owners to carry out pest control in the homes of people with asthma, landlords ultimately have little incentive to do so comprehensively.
Meanwhile, medical insurers have a strong financial incentive to mitigate asthma hospitalizations, but they have rarely paid for housing-related interventions like pest management because of an understandable reluctance to invest in an unfamiliar sector.
To bridge this disconnect and to demonstrate that healthcare investment in housing improvements can sustainably generate financial benefits to insurers, Enterprise and the New York City Department of Health and Mental Hygiene (DOHMH) launched a groundbreaking new initiative: the Medicaid Together Improving Asthma Program, in partnership with five Medicaid health plans and multiple New York City hospitals.
The program challenges the healthcare sector to invest in asthma-focused housing improvements, specifically Integrated Pest Management with Allergy Reduction (IPM-AR), which is expected to decrease asthma hospitalizations among low-income children.
Landlords are responsible for the home improvements of tenants, and both the healthcare sector and residents benefit from healthier housing environments. The Medicaid Together Improving Asthma Program acknowledges the benefit of healthy housing by creating a platform for the health insurance sector to invest in the reduction of asthma triggers without removing full responsibility from landlords. Five Medicaid managed care organizations (MCOs) – Empire Blue Cross Blue Shield HealthPlus, EmblemHealth, Fidelis Care, Healthfirst and MetroPlusHealth – are participating in the program and together insure 87 percent of the children on Medicaid in New York City. 2
A system that benefits patients and managed care organizations
IPM-AR is a proven intervention that removes existing pest allergens from the home and improves the home’s structural and sanitary conditions to deny pests food, water, harborage and movement, decreasing asthma symptoms among children without the side effects of traditional pest control. By addressing the underlying causes of asthma exacerbation, IPM-AR has the potential to generate healthier New Yorkers with fewer asthma exacerbations and health care cost savings for insurers and healthcare providers, who are at full risk for asthma-related healthcare costs.
While there is public health consensus that IPM-AR is likely to yield a financial return, we are committing a $1.2 million guarantee fund to mitigate the perceived risk of using healthcare dollars to pay for a treatment that is not established as an insurance benefit, and to make this treatment available across health plans. This funding serves as a profitability guarantee for the five MCOs participating in the Medicaid Together program. If insurers don’t realize the reductions in hospital use projected to result from IPM-AR interventions, they will be eligible to recoup all or part of their costs through the guarantee fund.
The program was launched to demonstrate that by investing in IPM-AR services, insurers will financially benefit through reductions in asthma hospitalizations. If successful, we expect that this kind of upstream housing intervention will be a model for future healthcare investments.
Another innovative component of the program involves the pooling of funding among five different private Medicaid insurers. All five organizations are funding the effort based on their respective share of members and a single centralized non-profit point of contact is coordinating the IPM services to individual households.
With the Affordable Care Act’s push towards payments that incentivize patient health outcomes over healthcare procedures, the healthcare sector has begun to look at investing in social determinants of health through direct interventions that lead to improved healthcare outcomes while lowering cost of care. The Medicaid Together Improving Asthma program supports this movement and incentivizes private investment by MCOs in the public good.
We thank the New York City Health Department for their partnership in this critical endeavor and we look forward to reporting on progress made in the program.
1 New York City Housing and Vacancy Survey (2002)
2New York State Medicaid managed care enrollment as of December 2021


In the hustle and bustle of daily life, it’s easy to neglect things that are important to us like health and skincare. We are so busy with our jobs and house chores that we tend to put off healthcare for a later time. Even though it is important to take care of daily routine tasks, it’s equally crucial to take some time out from your routine to get a health care check-up at your local medical center. It helps in diagnosis of any potential illness or disease that may pose a threat to your life.
In this guide, we’ll delve into the importance of these routine visits.
Early Detection of Health Issues
Regular check-ups at an urgent care clinic serves as a proactive measure in identifying health concerns before they become serious. Through screenings, tests, and discussions with your healthcare provider, potential problems can be spotted early. Early detection often leads to more effective treatment and improved outcomes.
Monitoring Chronic Conditions
If you have a chronic condition like diabetes, hypertension, or asthma, regular check-ups are crucial. They allow your healthcare provider to monitor your condition, adjust treatment plans as needed, and offer guidance on managing your health. Consistent monitoring can help prevent complications and maintain your quality of life.
Building a Relationship with Your Healthcare Provider
Continuity of care is essential in healthcare. By attending regular check-ups, you build a lasting relationship with your healthcare provider or medical director. They become familiar with your medical history, preferences, and unique health needs, ensuring personalized care.
Vaccinations and Preventive Care
Staying up-to-date with vaccinations and preventive care is a vital aspect of regular check-ups. Vaccinations protect you from contagious diseases, while preventive care, such as cancer screenings and cholesterol checks, can catch potential health threats early.
If you’re taking medications, your healthcare provider can review and adjust your prescriptions during check-ups. This ensures that your medications are working as intended and that you’re not experiencing any adverse side effects or interactions.
Your healthcare provider can offer valuable advice on maintaining a healthy lifestyle. From nutrition and exercise recommendations to stress management tips, these check-ups are an opportunity to discuss your overall well-being and make positive changes.
Mental Health Check-Ins
Mental health is as important as physical health. Regular check-ups provide an opportunity to discuss any mental health concerns, such as stress, anxiety, or depression. Your healthcare provider can offer support, referrals, or treatment options to address these issues.
Establishing a Health Baseline
Regular check-ups help establish a baseline for your health. Your healthcare provider records your vital signs, blood pressure, cholesterol levels, and more. These baseline measurements enable them to track changes over time and spot deviations that may require attention.
Peace of Mind
Knowing that you’re taking proactive steps to care for your health provides a sense of peace and confidence. Regular check-ups offer reassurance that you’re prioritizing your well-being and staying on top of any potential health issues.


Welcome to Dr Kristen Lee OD where your vision and eye health are our primary concern. We look forward to meeting you and helping you with all of your optometric eyecare needs. We are located in Carson, CA, and have long been recognized as a leader in patient care. Since we started in 1985, our board-certified ophthalmologists and optometrists have offered the highest standards of quality and individualized attention in a relaxed, professional atmosphere.
We offer a full range of options to meet your eyecare needs. From advanced custom LASIK laser vision correction and cataract surgery to glasses to eye infections, contact lens fittings and routine eye tests, we can provide the treatment that is right for you. We stock a large selection of contact lenses as well as fashionable frames - including Prada, Rayban & Bebe - that are sure to suit your eyewear needs.
Please don't hesitate to contact us if you are concerned about your general eye health or are interested in LASIK screening, hard-to-fit contact lenses, or treatment for cataracts. Our optometry office is just a short drive from Torrance and Long Beach. We look forward to seeing you!


Welcome to Advanced Injury Treatment Center
At Advanced Injury Treatment Center (AITC) we specialize in physical therapy and chiropractic care. We have been serving Bedford NH and the surrounding area for over 15 years.
Our caring, professional staff is dedicated to restoring your body’s optimal function. Advanced Injury Treatment Center (AITC) provides individualized treatment programs to relieve pain, increase function and help our clients move better.
Our goal is to provide a proactive and unique approach to physical wellness that emphasizes treating and conditioning the entire body rather than a particular injury.
We use evidence-based, movement-focused evaluation techniques and treatment tools with a consistent standard of care.
Advanced Injury Treatment Center (AITC) is privately owned and operated and, as an independent practice, we have the freedom to refer to any specialist agreed upon by you and our professional staff based on our clients’ preferences and medical needs.
We continuously work together as a team to keep our skills sharp and our philosophy in tune to the needs of our clients and the advances in client care.
Also available at our location are massage therapy with the licensed massage therapists of Therapy Designed For You and counseling with Susan MacDermott, licensed clinical mental health counselor.


Dr. Oliver Sacks on the therapeutic power of art: “The therapeutic power of art is temporary; it can liberate the patient only while the performance or creative act is occurring. Turning to creativity can activate the patient, allowing him to fight and sometimes conquer PD for years on end. But knowing that they can be liberated in this way, and in doing so, they can reclaim for a while their healthy selves. This area of creativity and the extraordinary power of art is ripe for exploration by the next generation of neuroscientists.” — Parkinson’s Post, Fall/Winter 2006, pg. 14
Dr. Oliver Sacks was Honorary Chairman of this Creativity and Parkinson’s initiative at the World Parkinson Congress in Washington DC. Dr.Sacks is Professor of Neurology and Psychiatry at Colombia University, he is a bestselling author and a Fellow of the American Academy of Arts and Letters and the American Academy of Arts and Sciences.


I had my IUD removed last week. I was experiencing hives just about daily which would get worse when I was spotting or having my period. I needed to have it removed to find out if it was the cause or not. I’ve already had no issues with hives since it’s removal, but there have been other issues.
I’m still somewhat itchy, but I was informed that my hormones would need to normalize before that would go away. My body has to adjust without hormones and get back to some kind of baseline. A friend recommended chasteberry which I’ve taken previously. It helped get my body back to regularity after it was messed up from taking birth control pills.
Heavy menstrual bleeding is apparently normal after removal. I already have a blood disorder where my blood is thin and takes a long time to clot. Normal clotting time is between 5-7 minutes. I usually run 9-10 minutes. I have to take iron supplements and I get anemia and bruising quite easily. It has brought on a lot of fatigue and this feeling of being unwell (which is kind of weird because I feel so much better since having the IUD taken out). There isn’t much I can do except to continue taking my vitamins, eating better, and recognizing when my body needs to rest.
I made steak for dinner because I felt like I needed it. I’ve been trying to have salad and greens daily, but sometimes it isn’t enough. I can tell when my iron level is low because of the white spots on my nails. I can also tell when I cook my steak bloody instead of well done. I hate any red on my steak under normal circumstances, except when my iron is low. I paired it with homemade mac n cheese for my daughter and a big salad.
The next issue I’m not even sure what to do about. My joints hurt. A lot. I was diagnosed with a positive rheumatoid factor and fibromyalgia, but I learned to manage the muscular pain. This joint pain started the day after the IUD was removed. I have read a few posts of people complaining of joint pain after removal of their IUDs so I’m hoping that this is only temporary. I have done well with balancing out what my body can take and I have been proud of myself for it. I’m just really confused by the pain.
I’m not working out at this point. I’m just trying to work on my eating habits and will gradually increase what I need as I begin walking and working out again. Patience is the key. I will get there.


At NHS hospitals, a consultant will often only be seen if the case is particularly complex. Busy mother could take their children to private consultants in London for this and a number of other reasons.
Private consultants often have rapid access to complex diagnostic facilities, such as ultrasound, CT, MRI and X-rays. Drugs not offered by the NHS are available. Private consultants will frequently offer appointments outside of working hours. Consultations usually last for between 30 and 45 minutes, in contrast to the 6.2 minutes provided by GPs, on average.
One very good reason to prefer to see a private consultant is location. HCA's six hospitals in London are in central locations. The Portland Hospital for Women and Children is on Great Portland Street in the West End of London, linking Oxford Street with Albany Street. The Princess Grace Hospital is on Nottingham Place in the City of Westminster, where the nearest tube station is Baker Street. The London Bridge Hospital is on Tooley Street, overlooking the River Thames and Tower Bridge and close to the City of London.
The Lister Hospital is on Chelsea Bridge Road in Chelsea, on the north side of the Thames, near Sloane Square tube station and the Victoria mainline and tube station. The Wellington Hospital is on Wellington Place, slightly north of the West End. These are locations in which people often find themselves.
If a condition is diagnosed, the most common reason for people to seek private health coverage is that the infamous NHS waiting lists are bypassed. NHS waiting lists for the most oft-used procedures were recently reported to have risen by a third. If the pain or discomfort of a condition is preventing your child from leading a normal life, you'll want them to be treated immediately, rather than in as many as 18 weeks down the line, as would be the case of the NHS. With HCA hospitals, there is sometimes no waiting time at all.
With in-hospital stays, private healthcare provides a private en-suite room, television and a choice of food. Visiting hours aren't restricted, which is considerably more convenient for a child's parents.
In all, bringing her child to a private consultant will provide appreciable benefits to a mother who has other demands on her time and to the child.
This is a sponsored post


In the world of healthcare, trust and accuracy are paramount. However, like any industry, healthcare is not immune to fraudulent activities that seek to exploit loopholes for personal gain. These fraudulent activities not only drain precious resources but also jeopardize patient care and trust in the system.
As healthcare fraud becomes increasingly sophisticated, traditional methods of detection are falling short in their ability to keep up. Enter machine learning, a cutting-edge technology that has revolutionized various industries. By harnessing the power of advanced algorithms and data analysis, machine learning has emerged as a promising tool in the ongoing battle against healthcare fraud.
This article explores the impact of machine learning on healthcare fraud detection, delving into its applications, benefits, and challenges. From identifying patterns in vast amounts of data to flagging suspicious claims in real time, machine learning holds the potential to transform the way we combat fraud in healthcare. By shedding light on this emerging field, we aim to provide an in-depth understanding of the ways in which machine learning is driving change and amplifying the effectiveness of fraud detection methods in the healthcare industry.
1. Introduction: Unleashing the Power of Machine Learning for Healthcare Fraud Detection
In today’s modern world, healthcare fraud has become a pressing issue that poses significant challenges for both insurance companies and healthcare providers. The sheer scale of fraudulent activities in the healthcare industry has resulted in substantial financial losses and compromised patient care. Traditional methods of fraud detection have proven to be inadequate, prompting the need for innovative solutions that can effectively combat these fraudulent activities. This is where the power of machine learning comes into play.
Machine learning, a subfield of artificial intelligence, has gained significant prominence in recent years due to its ability to analyze large volumes of data and detect patterns that are not easily discernible to humans. By leveraging advanced algorithms and statistical models, machine learning systems can identify anomalies and flag potentially fraudulent activities in real-time, ensuring timely intervention and prevention. Applying machine learning techniques to healthcare fraud detection has the potential to revolutionize the healthcare industry, leading to significant improvements in cost savings, operational efficiency, and patient outcomes.
The purpose of this article is to delve deeper into the power of machine learning for healthcare fraud detection and explore the various ways in which it can be leveraged to tackle this pervasive issue. We will discuss the benefits of using machine learning, such as increased accuracy, reduced false positives, and improved scalability. Additionally, we will explore different machine learning algorithms commonly used in fraud detection, including anomaly detection, classification models, and clustering techniques. Furthermore, we will examine real-world examples and case studies highlighting the successful implementation of machine learning in healthcare fraud detection. Stay tuned as we uncover the potential of this cutting-edge technology and its invaluable contribution in combating healthcare fraud.
2. Evolution of Fraud Detection in Healthcare: From Traditional Methods to Machine Learning
With the rapid growth of healthcare data and an increasing number of fraudulent activities, the need for effective fraud detection methods has become paramount in the healthcare industry. Traditional methods of detecting fraud in healthcare, such as manual auditing and rule-based systems, have been in use for many years. However, these methods have their limitations and are often unable to keep up with the constantly evolving techniques used by fraudsters.
Machine learning, on the other hand, has emerged as a promising solution for fraud detection in healthcare. By using algorithms and advanced data analytics techniques, machine learning models are able to analyze large volumes of healthcare data and identify patterns and anomalies that may indicate fraudulent activities. These models are trained on historical data, allowing them to learn from past instances of fraud and continuously improve their accuracy over time.
One key advantage of machine learning-based fraud detection in healthcare is its ability to adapt to changing fraud patterns. Fraudsters are constantly evolving their techniques to evade detection, making it essential for fraud detection methods to be dynamic and flexible. Machine learning models can adapt to new patterns and anomalies by continuously updating their algorithms and incorporating new data. This ensures that healthcare organizations can stay one step ahead of fraudsters and detect fraudulent activities in real time.
Additionally, machine learning models can enhance the efficiency of fraud detection in healthcare by automating the process. Manual auditing and rule-based systems are time-consuming and often prone to errors. Machine learning models, on the other hand, can process large volumes of data in a fraction of the time, making it possible to detect fraud more quickly and accurately. This not only saves valuable resources for healthcare organizations but also allows them to focus on providing quality care to patients.
The evolution of fraud detection in healthcare from traditional methods to machine learning has revolutionized the way fraudulent activities are detected and prevented. Machine learning models offer a dynamic, flexible, and efficient solution to combat fraud in healthcare by analyzing large volumes of data and continuously adapting to changing fraud patterns. With their ability to detect fraudulent activities in real time and automate the detection process, machine learning models have become an invaluable tool for healthcare organizations in their fight against fraud.
3. Leveraging machine Learning Algorithms: Enhancing Accuracy and Efficiency in Healthcare Fraud Detection
In today’s fast-paced healthcare environment, the accurate detection and prevention of fraud are of utmost importance. Leveraging machine learning algorithms has emerged as a powerful tool that can significantly enhance accuracy and efficiency in healthcare fraud detection. These algorithms are capable of analyzing large volumes of data with speed and precision, enabling the identification of patterns and anomalies that might go unnoticed by traditional methods.
One key advantage of machine learning algorithms is their ability to adapt and learn from new data over time. By continuously feeding the algorithms with real-time information, they can improve their performance and detect emerging fraud patterns more effectively. This adaptive nature ensures that healthcare organizations stay one step ahead of fraudsters, who are constantly finding new ways to exploit vulnerabilities in the system.
Moreover, machine learning algorithms can perform a variety of complex tasks in fraud detection, such as anomaly detection, clustering, and classification. Anomaly detection allows the algorithms to identify irregularities in data that might signify fraudulent activities. By analyzing patterns in data, the algorithms can cluster entities into different groups based on their similarities, making it easier to identify suspicious behavior. Classification algorithms can then be used to predict whether a particular claim or transaction is likely to be fraudulent or not.
By leveraging machine learning algorithms, healthcare organizations can achieve higher accuracy rates in fraud detection, significantly reducing false positives and negatives. This not only saves time and resources but also helps protect the integrity of the healthcare system by ensuring that fraudsters are promptly identified and prosecuted.
The use of machine learning algorithms in healthcare fraud detection is revolutionizing the way organizations combat fraudulent activities. These algorithms offer unparalleled accuracy and efficiency, enabling automated analysis of vast amounts of data and the identification of complex patterns. By embracing this technology, healthcare organizations can stay at the forefront of fraud detection and ensure the integrity and sustainability of their operations.
4. Real-time Detection: How Machine Learning is Revolutionizing the Fight Against Healthcare Fraud
Machine learning has emerged as a powerful tool in the fight against healthcare fraud, providing real-time detection capabilities that are revolutionizing the industry. By leveraging sophisticated algorithms and vast amounts of data, machine learning is aiding in the identification and prevention of fraudulent activities, potentially saving billions of dollars each year and improving the overall integrity of the healthcare system.
One of the key ways in which machine learning is transforming the fight against healthcare fraud is through its ability to detect patterns and anomalies. Traditional methods of fraud detection often rely on manual analysis and rule-based systems, which can be time-consuming and limited in their effectiveness. Machine learning, on the other hand, can rapidly analyze vast amounts of data, identifying patterns that may be indicative of fraudulent activity. By continuously learning and adapting, these algorithms can stay one step ahead of fraudsters, helping to prevent fraudulent claims before they are paid out.
In addition to pattern detection, machine learning is also enhancing the speed and accuracy of fraud detection. Real-time monitoring allows for immediate identification of suspicious activity, enabling swift action to be taken to prevent further harm. Machine learning algorithms can also take into account a wide range of variables and factors when assessing the likelihood of fraud, improving the accuracy of prediction and reducing the incidence of false positives.
Moreover, machine learning is enabling the healthcare industry to better analyze and understand fraud patterns. Through the use of sophisticated analytics tools, healthcare organizations can gain insights into common fraud schemes, identifying trends and vulnerabilities that may have previously gone unnoticed. This information can be used to develop targeted strategies and interventions, making it more difficult for fraudsters to operate undetected.
Overall, machine learning is playing a pivotal role in the fight against healthcare fraud, revolutionizing the way fraud detection and prevention are approached. Through its ability to detect patterns and anomalies, provide real-time monitoring, and offer valuable insights, machine learning is helping to safeguard the integrity of the healthcare system and protect both patients and providers. As technology continues to advance, the potential for machine learning to further enhance fraud detection efforts is vast, making it an invaluable asset in the ongoing battle against healthcare fraud.
5. Overcoming Challenges: Ethical Considerations and Implementation Hurdles in Machine Learning for Healthcare Fraud Detection
As machine learning continues to revolutionize the healthcare industry, one area that holds immense potential is fraud detection. Machine learning algorithms have the ability to analyze large datasets and detect patterns that may indicate fraudulent activities. However, implementing machine learning for healthcare fraud detection comes with its own set of challenges, both ethical and technical.
When it comes to ethical considerations, one of the primary concerns is maintaining patient privacy and confidentiality. The use of machine learning algorithms requires access to a vast amount of patient data, including personal health information. To mitigate privacy risks, healthcare organizations must ensure that proper security measures, such as data encryption and access controls, are in place.
Additionally, clear and transparent consent processes should be implemented to obtain patient permission for the use of their data in fraud detection algorithms. By prioritizing patient privacy, healthcare organizations can maintain the trust of their patients while harnessing the power of machine learning for fraud detection.
Another ethical consideration is the potential for bias in machine learning algorithms. Bias can arise from the underlying data used to train the algorithms, leading to unfair treatment of certain individuals or populations. It is essential for healthcare organizations to regularly monitor and evaluate machine learning models to identify and rectify any biases. By using diverse and representative datasets during the training phase, healthcare organizations can minimize bias and ensure fair outcomes.
In addition to ethical considerations, the implementation of machine learning for healthcare fraud detection also faces technical hurdles. One of the primary challenges is the availability and quality of data. Machine learning algorithms require large amounts of high-quality data to be trained effectively. However, healthcare fraud data is often limited and highly imbalanced, with a small number of fraudulent cases compared to a vast number of legitimate cases.
Dealing with such imbalanced datasets can be challenging, as the algorithms may struggle to detect fraud accurately. Healthcare organizations must invest in data collection and curation processes to ensure they have sufficient and representative data for training their machine learning models. Another technical challenge is ensuring the interpretability and explainability of machine learning models in healthcare fraud detection.
With the complex nature of machine learning algorithms, it can be difficult to understand the reasoning behind their predictions. This lack of interpretability raises concerns, as healthcare professionals and regulatory bodies may struggle to trust decisions made by these black-box models. Healthcare organizations must focus on developing interpretable models that provide clear explanations for their fraud detection findings. This not only ensures transparency but also allows healthcare professionals to identify potential flaws or biases in the models.
The application of machine learning for healthcare fraud detection holds tremendous potential in improving the detection and Prevention of fraudulent activities. However, it is crucial to address the ethical considerations surrounding patient privacy and bias, while also overcoming the technical hurdles of data availability, quality, and interpretability. By navigating these challenges, healthcare organizations can leverage the power of machine learning to enhance fraud detection and ultimately protect the integrity of the healthcare system.
6. Future Outlook: Embracing the Potential of Machine Learning to Safeguard Healthcare Systems
The integration of machine learning in healthcare systems has the potential to revolutionize the way we safeguard patient health. With advancements in technology and the increasing availability of data, machine learning algorithms can help healthcare professionals make more accurate diagnoses, predict diseases before symptoms appear, and improve patient outcomes. Here, we explore the promising future outlook of machine learning in healthcare and its potential to transform the industry.
One of the key areas where machine learning can have a profound impact is in disease detection and diagnosis. By analyzing vast amounts of medical data, machine learning algorithms can identify patterns and correlations that may be overlooked by human physicians. This can lead to earlier and more accurate diagnoses, allowing for prompt and effective treatment. Additionally, machine learning models can continuously learn from new data, enhancing their diagnostic capabilities over time.
Q: How has machine learning technology transformed healthcare fraud detection?
A: Machine learning has had a profound impact on healthcare fraud detection by enabling faster and more accurate identification of fraudulent activities. Traditional methods of detecting healthcare fraud were often time-consuming and relied heavily on manual investigation, making it difficult to keep up with the rapidly evolving techniques used by fraudsters. However, with the use of machine learning algorithms, healthcare providers and insurers can now efficiently analyze large volumes of data, detect patterns, and identify potential cases of fraud in real time.
Q: What are the key advantages of using machine learning for healthcare fraud detection?
A: One of the main advantages of using machine learning in healthcare fraud detection is its ability to continuously learn and adapt to new fraud patterns. Machine learning models can be trained on vast amounts of historical data to recognize fraudulent activities based on various factors, such as abnormal billing patterns or suspicious claim behaviors. As these models continuously learn from new data, they become more accurate in detecting fraud and can flag potential cases for further investigation. Additionally, machine learning helps in reducing false positives and increasing overall detection rates, resulting in substantial cost savings and improved healthcare system integrity.
Q: Are there any challenges associated with implementing machine learning for healthcare fraud detection?
A: While machine learning offers significant benefits, there are several challenges associated with its implementation in healthcare fraud detection. One major challenge is the availability and quality of data. To develop accurate machine learning models, organizations need access to large amounts of labeled data representing both fraudulent and non-fraudulent activities. However, obtaining such data can be challenging due to privacy concerns and the reluctance of organizations to share sensitive information. Additionally, the interpretability of machine learning algorithms can be a concern, as their decision-making process is often considered a “black box.” This lack of transparency can lead to skepticism and resistance from stakeholders who may be hesitant to fully trust the automated detection systems.
As we delve deeper into the era of technology, the fascinating world of machine learning continues to offer innovative solutions across various sectors. We have explored its profound impact on healthcare fraud detection and the potential it holds for transforming the landscape of healthcare.
Machine learning has taken the fight against healthcare fraud to new heights, allowing professionals to identify fraudulent activities with increased precision and efficiency. Through the intelligent analysis of vast amounts of data, machine learning algorithms can detect patterns and anomalies that humans might miss, thereby preventing fraudulent practices from going unnoticed.
The implementation of machine learning in healthcare fraud detection has significantly reduced the burden on investigators and auditors, who traditionally spent countless hours sifting through data manually. With automated processes enabled by machine learning models, these professionals can redirect their efforts toward critical tasks and investigations that require human expertise and intervention.
Not only does machine learning expedite the detection process, but it also continually adapts and improves itself as it ingests more data. This adaptive feature allows models to stay ahead of evolving fraud schemes and adjust their detection strategies accordingly. As a result, healthcare organizations can safeguard their resources and protect patients from falling victim to fraudulent practices.
Furthermore, the integration of machine learning algorithms with existing systems and databases has streamlined the detection and prevention process. Real-time monitoring, predictive analysis, and early warning systems have bolstered the ability to identify potential fraudsters promptly, thus minimizing financial losses and safeguarding the integrity of the healthcare system.
While machine learning has showcased considerable potential, it is crucial to acknowledge that it is not a magical solution. Its success greatly relies on an ongoing commitment to data quality, model accuracy, and strict cybersecurity measures. Ethical considerations must remain at the forefront, ensuring that the rights and privacy of patients are respected throughout the process.
In conclusion, the impact of machine learning on healthcare fraud detection cannot be overstated. This technology has revolutionized the field, empowering healthcare organizations to mitigate fraud risks, save precious resources, and protect the well-being of patients. With ongoing advancements and a commitment to responsible implementation, the future of healthcare fraud detection holds tremendous potential for a more secure, efficient, and trustworthy healthcare system.
Healthcare fraud costs the US healthcare system billions of dollars every year. To counteract this, organizations have been using increasingly sophisticated technologies, such as machine learning, to detect and prevent it.
Machine learning is a subset of artificial intelligence that utilizes algorithms to analyze data and learn from patterns in the data. In terms of healthcare fraud detection, machine learning algorithms can find patterns in extensive troves of data about individuals and healthcare transactions, making it possible to identify potentially fraudulent activities.
The use of machine learning in healthcare fraud detection has several advantages. It can be used to validate claims more quickly, reducing the amount of time required for manual reviews. It also reduces the amount of bias in the system, which can be an issue in manual reviews. Additionally, since machine learning can help to uncover trends and unknown patterns, it can help to identify cases of fraud that might have otherwise been missed.
Given the potential benefits of machine learning, healthcare organizations have been investing in the technology and incorporating it into their fraud detection systems. Organizations can use it to develop predictive models that can identify suspicious claims and transactions. This in turn can help reduce the financial losses associated with fraud.
Organizations are also turning to machine learning to improve the accuracy of their results and reduce false positives. By using algorithms to analyze the data more efficiently, organizations can identify true cases of fraud and avoid wasting resources by chasing false leads.
In spite of its advantages, however, there are some challenges associated with the use of machine learning in healthcare fraud detection. One such challenge is that it can still be difficult for organizations to interpret the results generated by the algorithms. Additionally, since healthcare fraud is constantly evolving, machine learning algorithms must also be continually trained and updated in order to remain effective.
Overall, machine learning has the potential to revolutionize healthcare fraud detection. By using predictive models aided by machine learning algorithms, organizations can more quickly and accurately identify potentially fraudulent activities. This in turn can help reduce financial losses and improve the overall efficiency of healthcare organizations.


Allows our dentures to be engraved with the resident’s name during the denture fabrication process.
Low Radiation X-rays
Digital x-rays reduce radiation exposure by 75% or more. This means a higher and safer level of care.
Initial and Annual Exams
Every patient will receive initial exams and annual assessments with or without dental coverage
Full Facility Audits
Used in addition to our routine house visits to eliminate the possibility for deficiencies by the Department of Health
Comprehensive Examinations, Fillings & Restorations, Implants, Crowns & Bridges, Root Canals, Full & Partial Dentures, Deep Cleanings,
Very important to residents of Skilled Nursing Facilities who face challenges in self care due to sensory mobility and cognitive deficits.
Onsite Dental is an innovative and sophisticated mobile dental company that is designed to focus on improving our client’s oral health by eliminating and preventing
Potential problems such as tooth decay, gum disease, bad breath, and oral infections. We currently serve over 5000 residents who reside in Skilled Nursing Facilities, assisted livings, Alzheimer’s units and hospitals, in Southern California. Our team which consists of knowledgeable and compassionate Dentists, Dental Assistants, Dental Hygienists and X-Ray Technicians, visit the Facilities very often and eliminate the need to travel to an outside Dentist. We start with Initial exams, followed by X-Rays and comprehensive dental exam. We then develop individualized and customized treatment plans that meets the dental needs of each resident.
Our professional and highly trained Hygienists visit your residents several times a year as authorized by Medi-Cal. Our focus is mainly on preventive oral care such as x-Rays and cleanings which is crucial in maintaining a healthy life. Preventive oral care can reduce the risks for some life Threatening conditions such as Aspiration Pneumonia and Cardiovascular disease.
Our mission is to provide preventative On-site dentistry to all residents. We utilize state of the art equipment and highly trained professionals to deliver a full range of dental services, providing compassionate and convenient care for the elderly and disabled.
We Specialize in
24 Hour Emergency Services
Full Facility Audits
Routine Exams and Screenings
Full Mobile Hygiene Services
Fast Treatment Authorization Process
Low Radiation Digital X-rays
Fast Response Time
Patient and Staff Education
Annual Inservice Programs
Timely Treatment Plan Completion
3575 Cahuenga Blvd. Ste. #115
Los Angelea, CA 90068
Monday – Friday 8AM – 5PM
Hours of Operation
"Our experience with Onsite has been amazing. The patients as well as the staff really appreciate how they keep the families of each patient involved every step of the way."
“Onsite consistently goes the extra mile to make sure each patient is satisfied from start to finish. They truly have a personalized approach.”
“We switched to Onsite and we coldnt be more pleased. They are fast, efficient, and affordable. Most of all they work hard to meet our needs no matter the circumstance. We could not be more satisfied.”
Meghan Charles, Admin/Svcs
Years of Experience
Doctor Mitra Mashreghi specializes in all aspects of General Dentistry. She earned her Bachelor’s in Science of Nursing (BSN) at University of Kentucky in 1998. She worked as a Registered Nurse for four years and decided to pursue a career in Dentistry. She graduated from University of Kentucky College of Dentistry in 2006 and has since focused her practice on the nursing home, assisted living and hospital patients. She is very compassionate and takes pride in offering the finest patient care and services to each and every patient. Her nursing experience allows her to combine her medical background and knowledge with her dental skills in order to provide quality care to her patients. This is crucial for the residents of long term care facilities, since they are often present with numerous medical conditions. Her combined knowledge and experience allows her to analyze each and every patient closely and develop an ideal treatment plan without jeopardizing the patient’s well being.
Dr. Ayonna Taylor is a Los Angeles native.
She earned her high school diploma from St. Mary's Academy, and then earned a Bachelors degree in Biology from Hampton University in Hampton, VA.
Dr. Taylor earned her dental degree from Howard University College of Dentistry in Washington, D.C. in 1998, and completed a post-graduate General Practice Residency at King-Drew Medical Center.
She continuously refreshes and updates her dental knowledge by taking numerous dental continuing education courses on the latest trends and techniques.
She holds membership in the West Los Angeles Dental Society, California Dental Association, American Dental Association, and Angel City Dental Society.
Dr. Taylor has been practicing dentistry in the Los Angeles area for over 15 years and loves providing quality, professional, and caring service within the community in which she grew up.
Who We Are.....
Onsite Dental is a mobile dental service dedicated to providing high quality, comprehensive dental care. We value excellence, innovation, integrity and strive to make a positive differences in the lives of your residents. We operate a dental service that provides ONSITE care to nursing homes, assisted living facilites, Dementia and Alzheimer's units, and hospitals. Our goal is to provide appropriate, necessary, and cost effective dental care to residents who will otherwise have to travel to see the dentist. The advantage, especially when working with the elderly or disabled residents, is that the care center is a familiar place, so the dental appointment becomes easier and less stressful on the patient and their loved ones. While integrating the patient and their loved ones into the Consultation and Treatment process, everyone involved helps to reach a positive and satisfying outcome.
Meet Our Doctors
OUR CORE FEATURES
Continuity of Care- Our residents are treated by skilled, and compassionate staff. Through regular and consistent service we maintain a lasting relationship with patients and their families. All dentists are fully committed to maintaining the folllow-ups needed to ensure continuity of care.
Communication- Onsite Dental prides itself in maintaining open lines of communication by communicating directly with the families. Follow-up calls are regularly made and records are submitted to the facility staff.
Professionalism- a California based dental service with experience in SNF, Alzheimer’s, Home Care, Hospice, and Hospital dentistry. Comprehensive, and collaborative dental care, numerous years of experience in the art of mobile dentistry, FDA, OSHA, HIPPA, and California Dental Board Compliant.
Convenience- Brings the dental office to you. Competitive fee schedules. Collaborative approach with patients, families, and your staff. Paper work management including copies of progress notes and visit summary list. Ethical and honest treatment that balances your resident’s needs with their health, Behavior, and available resources. General discounts and payment plans available.


|Systematic (IUPAC) name|
|1-cyclopropyl- 6-fluoro- 4-oxo- 7-piperazin- 1-yl- quinoline- 3-carboxylic acid|
|ATC code||J01 S01 S02 S03|
|Metabolism||Hepatic, including CYP1A2|
|Pregnancy cat.||B3(AU) C(US)|
|Legal status||Prescription Only (S4) (AU) POM (UK)|
|Routes||Oral, intravenous, topical (ear drops, eye drops)|
|Y(what is this?)|
Ciprofloxacin is marketed worldwide with over three hundred different brand names. In the United States, Canada, and the UK, it is marketed as Baycip, Ciloxan, Ciflox, Cipro, Cipro XR, Cipro XL, Ciproxin, Prociflor, and most recently, Proquin. In addition, ciprofloxacin is available as a generic drug under a variety of different brand names and is also available for limited use in veterinary medicine.
Ciprofloxacin was first patented in 1983 by Bayer A.G. and subsequently approved by the United States Food and Drug Administration (FDA) in 1987. Ciprofloxacin has 12 FDA-approved human uses and other veterinary uses, but it is often used for unapproved uses (off-label). Ciprofloxacin interacts with other drugs, herbal and natural supplements, and thyroid medications.
History The United States patent was applied for in January 1987, but was not approved until 1996 according to the patent history.
In 2004, ciprofloxacin and levofloxacin together commanded 65% ($3.3 billion) of the global sales of the fluoroquinolone class. The first nine months of 2008 sales for ciprofloxacin were $242 million, as compared to $324 million for Bayer aspirin. Ciprofloxacin has proven to be a blockbuster drug for Bayer A. G., generating billions of dollars in additional revenue. "In 1999, Cipro was the eleventh most prescribed drug in the United States based on new prescriptions, and ranked twentieth in total United States sales. In 1999, Bayer's gross sales of Cipro in the United States were approximately $1.04 billion." The sale of ciprofloxacin increased dramatically following the anthrax scare of 2001. On 24 October 2002, the Bush Administration (2001–2009) announced a deal between the government and Bayer Pharmaceuticals to purchase 100 million tablets of ciprofloxacin at a reduced price of $0.95 per pill. A full course of ciprofloxacin for postexposure prophylaxis (60 days) resulting from this arrangement costs the government $204 per person treated, compared with $12 per person treated with doxycycline, the drug normally used to treat anthrax, a difference of $192.
Generic equivalentsOn 24 October 2001, The Prescription Access Litigation (PAL), filed suit to dissolve an agreement between Bayer and three of its competitors which produced generic versions of drugs (Barr Laboratories, Rugby Laboratories, and Hoechst-Marion-Roussel) that it claimed was blocking access to adequate supplies and cheaper, generic versions of ciprofloxacin. The plaintiffs charged that Bayer Corporation, a unit of Bayer AG, had unlawfully paid the three competing companies a total of $200 million to prevent cheaper, generic versions of ciprofloxacin from being brought to the market, as well as manipulating the price and supply of ciprofloxacin. Numerous other consumer advocacy groups joined the lawsuit. On 15 October 2008, five years after Bayer’s patent had expired, the United States District Court for the Eastern District of New York granted Bayer’s and the other defendants’ motion for summary judgment, holding that any anticompetitive effects caused by the settlement agreements between Bayer and its codefendants were within the exclusionary zone of the patent and thus could not be redressed by federal antitrust law, in effect upholding Bayer’s agreement with its competitors.
Licensed usesThe licensed uses for ciprofloxacin in the United States are as follows:
In the adult population, ciprofloxacin is limited to the treatment of proven bacterial infections such as:
- Urinary tract infections (not recommended as a first-line antibiotic)
- Acute uncomplicated cystitis in females
- Chronic bacterial prostatitis (not recommended as a first-line antibiotic choice)
- Lower respiratory tract infections (not recommended as a first-line antibiotic choice)
- Acute sinusitis (not recommended as a first-line antibiotic choice)
- Skin and skin structure infections
- Bone and joint infections
- Infectious diarrhea
- Typhoid fever (enteric fever) caused by Salmonella typhi
- Uncomplicated cervical and urethra gonorrhea (due to N. gonorrhoeae) – however, this indication is no longer effective in some areas (e.g., Asian countries, United States (including Hawaii), Canada , and Scotland) due to bacterial resistance. Fluoroquinolones are no longer recommended in the USA for this indication.
As well as in combination with other specific drugs:
- Complicated intra-abdominal infections (in combination with metronidazole);
- Empirical therapy for febrile neutropenic patients (in combination with piperacillin)
Current recommendations by the American Academy of Pediatrics note the systemic use of ciprofloxacin in children should be restricted to infections caused by multidrug resistant pathogens or when no safe or effective alternatives are available.
As such, the general opinion stated in 1994 that ciprofloxacin “is not to be considered a suitable agent for use in general practice for the blind initial treatment of chest infections....” does not appear to have changed within these current guidelines.
Antibiotics may not improve the long-term clinical outcome for sinusitis. When prescribed for chronic bronchitis and acute bacterial sinusitis, the use of the fluoroquinolone class offers no compelling advantages over established treatment. Nor does antibiotic treatment help sore throats. The use of antibiotics such as ciprofloxacin to treat bronchitis is to be considered unnecessary and as such exposes the patient to an unacceptable risk of suffering a severe adverse reaction. Additionally, antibiotics have no effect upon viral infections, such as the common head cold or viral respiratory infections.
Note: Ciprofloxacin may be licensed for other uses, or restricted, by the various regulatory agencies worldwide.
AvailabilityCiprofloxacin is available as:
- tablets (100 mg, 250 mg, 500 mg, 750 mg or 1000 mg)
- intravenous solutions (5% and 10%, 100 mL)
- eye and ear drops
See the latest package insert for ciprofloxacin (Cipro) for additional details.
Mode of actionCiprofloxacin is a broad-spectrum antibiotic active against both Gram-positive and Gram-negative bacteria. It functions by inhibiting DNA gyrase, a type II topoisomerase, and topoisomerase IV, enzymes necessary to separate bacterial DNA, thereby inhibiting cell division.
This mechanism can also affect mammalian cell replication. In particular, some congeners of this drug family (for example those that contain the C-8 fluorine) display high activity not only against bacterial topoisomerases but also against eukaryotic topoisomerases and are toxic to cultured mammalian cells and in vivo tumor models. Although quinolones are highly toxic to mammalian cells in culture, its mechanism of cytotoxic action is not known. Quinolone-induced DNA damage was first reported in 1986 (Hussy et al.).
Recent studies have demonstrated a correlation between mammalian cell cytotoxicity of the quinolones and the induction of micronuclei. As such, some fluoroquinolones may cause injury to the chromosome of eukaryotic cells.
There continues to be debate as to whether or not this DNA damage is to be considered one of the mechanisms of action concerning the severe adverse reactions experienced by some patients following fluoroquinolone therapy.
ContraindicationsAs noted above, under licensed use, ciprofloxacin is also now considered to be contraindicated for the treatment of certain sexually transmitted diseases by some experts due to bacterial resistance.
There are only four contraindications found within the 2009 package insert:
- “Coadministration of ciprofloxacin with other drugs primarily metabolized by CYP1A2 results in increased plasma concentrations of these drugs and could lead to clinically significant adverse events of the coadministered drug.”
- “Concomitant administration with tizanidine is contraindicated.”
- “Ciprofloxacin is contraindicated in persons with a history of hypersensitivity to ciprofloxacin, any member of the quinolone class of antimicrobial agents, or any of the product components.”
- “Local I.V. site reactions are more frequent if the infusion time is 30 minutes or less. These may appear as local skin reactions that resolve rapidly upon completion of the infusion. Subsequent intravenous administration is not contraindicated unless the reactions recur or worsen.”
Ciprofloxacin is also considered to be contraindicated within the pediatric population (except for the indications outlined under licensed use above), pregnancy, nursing mothers, and in patients with epilepsy or other seizure disorders.
- Pediatric population
Within the studies submitted in response to a Pediatric Written Request (ciprofloxacin, circa 2004), the rate of atrophy was reported to be 9.3%. Within the BPCA Pediatric Studies Summary for ciprofloxacin, it was stated that the overall incidence of adverse events at six weeks was 41%. This would be consistent with the safety profile found with the other fluoroquinolones studied in the pediatric population. As such, the current ban on the use of the fluoroquinolones in the pediatric population is both reasonable and supported by various clinical studies. The most recent long term study, BAY 0 9867 Cipro Pediatric Use Study (QUIP), which followed pediatric patients from 1999–2008, supports the current expert opinion that the risk of permanent injury continues to outweigh the potential benefits of ciprofloxacin therapy in the pediatric population.
Within the United States, the FDA has stated it is their intention to pursue the licensing of the fluoroquinolones for pediatric use in spite of the evidence presented at that 62 Meeting of the Anti-Infective Drugs Advisory Committee that the fluoroquinolones cause irreversible joint damage in the pediatric population.
Special precautionsThe status of the patient’s renal function and hepatic function must also be taken into consideration to avoid an accumulation that may lead to an overdose and the development of toxicity. Ciprofloxacin is eliminated primarily by renal excretion. However, the drug is also metabolized and partially cleared through the liver and the intestines. Modification of the dosage is recommended using the table found within the package insert for those with impaired liver or kidney function. However, since the drug is known to be substantially excreted by the kidneys, the risk of toxic reactions to this drug may be greater in patients with impaired renal function. The duration of treatment depends upon the severity of infection and is usually 7 to 14 days.
Adverse effectsSerious adverse events occur more commonly with fluoroquinolones than with any other antibiotic drug classes. In most, adverse reactions are mild to moderate; however, occasionally serious adverse effects occur. There have been a number of regulatory actions taken as a result of such adverse reactions, which included published warnings, additional warnings and safety information added to the package inserts together with the issuance of "Dear Doctor Letters" concerning the recent addition of Black Box Warnings. In 2004, the U.S. FDA requested new warning labels to be added to all of the fluoroquinolones, including ciprofloxacin, regarding peripheral neuropathy (irreversible nerve damage), tendon damage, heart problems (prolonged QT Interval / torsades de pointes), pseudomembranous colitis, rhabdomyolysis (muscle breakdown), Stevens-Johnson syndrome, as well as concurrent usage of NSAIDs contributing to the severity of these reactions.
Subsequent to this, on 25 June 2007, the U.S. FDA required the manufacturer to add an additional warning to the package inserts that stated “Other serious and sometimes fatal events, some due to hypersensitivity, and some due to uncertain etiology, have been reported in patients receiving therapy with quinolones, including ciprofloxacin.” It was not until 2008, (four years later) that the label revisions for ciprofloxacin included any warnings concerning heart problems (prolonged QT interval / torsade de pointes). Warnings concerning rhabdomyolysis and Stevens-Johnson syndrome are still conspicuously absent from the package inserts as of September 2009.
The serious adverse effects that may occur as a result of ciprofloxacin therapy include irreversible peripheral neuropathy, spontaneous tendon rupture and tendonitis, acute liver failure or serious liver injury (hepatitis), QTc prolongation/torsades de pointes, toxic epidermal necrolysis (TEN), and Stevens-Johnson syndrome, severe central nervous system disorders (CNS) and Clostridium difficile associated disease (CDAD: pseudomembranous colitis), as well as photosensitivity/phototoxicity reactions.
Psychotic reactions and confusional states, acute pancreatitis, bone marrow depression, interstitial nephritis and hemolytic anemia may also occur during ciprofloxacin therapy. Additional serious adverse reactions include temporary, as well as permanent, loss of vision, irreversible double vision, drug induced psychosis and chorea (involuntary muscle movements), impaired color vision, exanthema, abdominal pain, malaise, drug fever, dysaesthesia and eosinophilia. Pseudotumor cerebri, commonly known as idiopathic intracranial hypertension (IIH), (also referred to as increased intracranial pressure), has been reported to occur as a serious adverse reaction to ciprofloxacin.
Children and the elderly are at a much greater risk of experiencing such adverse reactions. Such reactions may manifest during fluoroquinolone therapy, and long after it had been discontinued.
Serious visual complications have also been reported to occur with ophthalmic fluoroquinolone therapy, which may also occur with ciprofloxacin eye drops, especially corneal perforation, but also evisceration and enucleation. This increased incidents of corneal perforation may be due to fluoroquinolones causing alterations in stromal collagen, leading to a reduction in tectonic strength. As noted previously permanent double vision (diplopia) has also been reported. An unusual case of seizures has also been reported with ciprofloxacin ear drops in an elderly patient.
Some groups refer to these adverse events as "fluoroquinolone toxicity". These groups of people claim to have suffered serious long term harm to their health from using fluoroquinolones. This has led to a class action lawsuit by people harmed by the use of fluoroquinolones, as well as legal action by the consumer advocate group Public Citizen. Partly as a result of the efforts of the State of Illinois and Public Citizen, the FDA ordered black box warnings on all fluoroquinolones advising consumers of the possible toxic effects of fluoroquinolones on tendons.
InteractionsThe toxicity of drugs that are metabolised by the cytochrome P450 system is enhanced by concomitant use of some quinolones. Coadministration may dangerously increase coumarin (warfarin) activity; INR should be monitored closely. They may also interact with the GABA A receptor and cause neurological symptoms; this effect is augmented by certain nonsteroidal anti-inflammatory drugs. Quercetin, a flavonol, occasionally used as a dietary supplement, may interact with fluoroquinolones, as quercetin competitively binds to bacterial DNA gyrase. Some foods, such as garlic and apples, contain high levels of quercetin; whether this inhibits or enhances the effect of fluoroquinolones is not entirely clear. Ciprofloxacin can reduce phenytoin plasma levels, which may, in some cases, result in seizures. Ciprofloxacin may interfere with the levels of thyroid medications resulting in hypothyroidism.
On 9 November 2005, the U.S. FDA required the manufacturers to provide additional warnings within the package inserts concerning ciprofloxacin being an inhibitor of human cytochrome P450 1A2 (CYP1A2) mediated metabolism. The new warning stated:
"Coadministration of ciprofloxacin with other drugs primarily metabolized by CYP1A2 results in increased plasma concentrations of these drugs and could lead to clinically significant adverse events of the coadministered drug."Concurrent administration of ciprofloxacin with magnesium or aluminum antacids, sucralfate or products containing calcium, iron, or zinc (including multivitamins or other dietary supplements) may substantially decrease the absorption of ciprofloxacin, resulting in serum and urine levels considerably lower than desired.
Significant drug interactionsCiprofloxacin can alter and be altered by the metabolism and effects of other drugs, resulting in some significant drug-drug interactions that may affect the musculoskeletal, central nervous, renal, and other systems.
Current or past treatment with oral corticosteroids is associated with an increased risk of achilles tendon rupture, especially in elderly patients who are also taking the fluoroquinolones. This is the subject of Black box warnings in FDA and BNF labeling for quinolones.
The Committee on the Safety of Medicines and the FDA warn that central nervous system adverse effects, including seizure risk, may be increased when NSAIDs are combined with quinolones. The interaction between quinolones and NSAIDs is important, because it has the potential for considerable CNS toxicity. The mechanism for this interaction is believed to be due to a synergistic increased antagonism of GABA neurotransmission.
Ciprofloxacin's renal clearance may affect other drugs subject to renal clearance or otherwise affecting the kidney. The use of ciprofloxacin concomitantly with cyclosporine has also been associated with transient elevations in serum creatinine. Renal tubular transport of methotrexate may be inhibited by concomitant administration of ciprofloxacin, potentially leading to increased plasma levels of methotrexate and risk of methotrexate toxicity. Probenecid interferes with renal tubular secretion of ciprofloxacin and produces an increase in the level of ciprofloxacin in serum.
Some quinolones, including ciprofloxacin, exert an inhibitory effect on the cytochrome P-450 enzyme CYP1A2, thereby reducing clearance, and thus increasing blood levels of tizanidine and methylxanthines (e.g., theophylline and caffeine). The quinolones have also been reported to enhance the effects of warfarin or its derivatives. Such interactions can augment the effects of the co-administered drug, including adverse effects. Ciprofloxacin can reduce effects of other drugs; for example, it has been shown to interact with thyroid medications (levothyroxine), resulting in unexplained hypothyroidism. Altered serum levels of phenytoin (increased and decreased) have been reported in patients receiving concomitant ciprofloxacin.
OverdoseOverdose of ciprofloxacin may result in reversible renal toxicity. Treatment of overdose includes emptying of the stomach via induced vomiting or by gastric lavage. Careful monitoring and supportive treatment, monitoring of renal function and maintaining adequate hydration is recommended by the manufacturer. Administration of magnesium, aluminum, or calcium containing antacids can reduce the absorption of ciprofloxacin. Hemodialysis or peritoneal dialysis removes only less than 10 percent of ciprofloxacin. Ciprofloxacin may be quantitated in plasma or serum to monitor for drug accumulation in patients with hepatic dysfunction or to confirm a diagnosis of poisoning in acute overdose victims.
ChemistryCiprofloxacin is 1-cyclopropyl-6-fluoro-1,4-dihydro-4-oxo-7-(1-piperazinyl)-3-quinolinecarboxylic acid. Its empirical formula is C17H18FN3O3 and its molecular weight is 331.4 g/mol. It is a faintly yellowish to light yellow crystalline substance.
Ciprofloxacin hydrochloride (USP) is the monohydrochloride monohydrate salt of ciprofloxacin. It is a faintly yellowish to light yellow crystalline substance with a molecular weight of 385.8 g/mol. Its empirical formula is C17H18FN3O3HCl•H2O.
PharmacokineticsThe effects of 200–400 mg of ciprofloxacin given intravenously are linear; drug accumulation does not occur when administered at 12 hour intervals. Bioavailability is approximately 70-80%, with no significant first pass effect. IV administration produces a similar serum levels as those achieved with administration of 500 mg administered orally. IV administration over 60 minutes given every 8 hours produces similar serum levels of the drug as 750 mg administered orally every 12 hours. Biotransformation is hepatic. The elimination half life is 4 hours.
History of the black box warningsMusculoskeletal disorders attributed to use of quinolone antibiotics were first reported in the medical literature in 1972, as an adverse reaction to nalidixic acid. Rheumatic disease after use of a fluoroquinolone (norfloxacin) was first reported eleven years later. In response to a 1995 letter published in the New England Journal of Medicine, representatives of the U.S. Food and Drug Administration (FDA) stated that the agency would "update the labeling [package insert] for all marketed fluoroquinolones to include a warning about the possibility of tendon rupture."
By August 1996, the FDA had not taken action, and the consumer advocacy group Public Citizen filed a petition with the FDA prompting the agency to act. Two months later, the FDA published an alert in the FDA Medical Bulletin and requested that fluoroquinolone package inserts be amended to include information on this risk.
Nine years later, in 2005, the Illinois Attorney General filed a second petition with the FDA again seeking Black Box Warnings and "Dear Doctor" letters emphasizing the risk of tendon rupture; the FDA responded that it had not yet been able to reach a decision on the matter. In 2006, Public Citizen, supported by the Illinois Attorney General, renewed its demand of ten years prior for Black Box Warnings by filing a third petition requesting such changes be made. When the FDA failed to respond to these two petitions as required by law Public Citizen, in January 2008, filed suit to compel the FDA to respond to their 2006 petition. On July 7, 2008 the FDA requested that the makers of systemic-use fluoroquinolones add a boxed warning regarding spontaneous tendon ruptures, and to develop a Medication Guide for patients. The package inserts for Ciprofloxacin, Avelox (moxifloxacin), Proquin XR, Factive (gemifloxacin), Floxin (ofloxacin), Noroxin (norfloxacin) and Levaquin (levofloxacin) were amended on September 8, 2008 to include these new warnings. Bayer, which manufactures Cipro, Avelox and Proquin XR, issued a Dear Healthcare Professional letter on October 22 concerning these changes. Ortho-McNeil, the manufacturers of Levaquin, issued a similar letter in November. through the Health Care Notification Network, a registration-only website that distributes drug alerts to licensed healthcare professionals.
Review of the FDA website indicates that the majority of the generic versions of the fluoroquinolones have not been updated to include this Black Box Warning as of September 2009. Additionally there are numerous reports that this information has not been dessiminated to the pharmacist, the name brand products continue to contain the previous labels that are absent of this warning, and the Medication Guide has not been made available to the pharmicist or physician for distribution.
FDA warning lettersAdditionally the manufacturers of ciprofloxacin (Bayer A.G.) received numerous warning letters from the United States Food and Drug Administration regarding false advertising and failure to provide adequate warnings within their promotional materials.
Overprescribing and bacterial resistanceCiprofloxacin is commonly used for urinary tract and intestinal infections (traveler's diarrhea) and was once considered a powerful antibiotic of last resort, used to treat especially tenacious infections. Not all physicians agreed with this assessment, as evidenced by its wide spread use to treat minor infections as well as non-approved uses. As a result in recent years many bacteria have developed resistance to this drug, leaving it significantly less effective than it would have been otherwise.
Resistance to ciprofloxacin and other fluoroquinolones may evolve rapidly, even during a course of treatment. Numerous pathogens, including Staphylococcus aureus, enterococci, and Streptococcus pyogenes now exhibit resistance worldwide. Widespread veterinary usage of the fluoroquinolones, particularly in Europe, has been implicated.
Fluoroquinolones had become the most commonly prescribed class of antibiotics to adults in 2002. Nearly half (42%) of these prescriptions were for conditions not approved by the FDA, such as acute bronchitis, otitis media, and acute upper respiratory tract infection, according to a study that was supported in part by the Agency for Healthcare Research and Quality. Additionally they are commonly prescribed for medical conditions that are not even bacterial to begin with, such as viral infections, or those to which no proven benefit exist.


A Quick Comparison Between Botox And Dysport
Botox and Dysport are both cosmetic surgery solutions that have been derived from the same toxin and serve essentially the same purpose: paralyzing the muscles in the area in order to eliminate the wrinkles and lines generate by motion (facials expressions like frowning, laughing or smiling for instance). At the same time, both products have received the FDA seal of approval, even though Botox has been available on the US market much longer compared to Dysport. However, it is necessary to point out that even though Dysport manufacturers have received the US green light more recently, it has been frequently used in Europe and Canada. By the end of this article, you will find out how Botox and Dysport score in terms of speed, duration, safety and costs.
Time Taken For First Visible Results
In regards to the timeframe between the injection and the first visible results, Dysport has proven slightly superior to Botox (at least for 30 percent of the people in this study). This means that while individuals who utilized Botox injections had to wait for 2-3 days before the effects of the substance became prominent, it is entirely possible that the initial results of Dysport become visible on the very first day. On the other hand, keep in mind that this only refers to the initial results and not the full effect of the injection, which on average is similar for both of them.
Duration of Effect
As far as the duration of the effect is concerned, several clinical trials have shown that Botox is just slightly better than Dysport. However, other studies revealed the opposite results and consensus among cosmetic surgeon boards is yet to be reached. The most probable reason for the diverse testing results resides in the lack of normalization for the quantity of substance injected among the subjects of the studies. In other words, there is a direct correlation between the quantity of substance utilized and the length of the period when the results are visible.
It is also necessary to point out that the quantity of Dysport necessary to obtain the same results as Botox is 2.5 times larger. This means that 1 unit of Botox converts into approximately 2.5 units from the Dysport solution. Now, the larger quantity of Dysport (and its consistence) means that it has the potential of spreading easier within the area, but that has positive and negative consequences. To put it simply, it makes Dysport more effective for eliminating the wrinkles in larger zones (such as the forehead) but less convenient for localized usage (eyebrows or eyes).
Let’s Talk Money
From the financial point of view, one unit of Dysport is cheaper than one unit of Botox by approximately 5 to 10 percent. However, don’t forget about the conversion rates discussed previously. Depending on the type of procedure, you may be able to utilize less Dysport and therefore it could constitute the more profitable alternative. In order to learn which product would prove more proficient in treating your particular type of wrinkles, it is advisable to schedule a consultation with your cosmetic surgeon and assess the state of your epidermis, facial structure, potential side effects and so on.
Filed under: General Health
Like this post? Subscribe to my RSS feed and get loads more!