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Artificial Intelligence Permeation in Testing

According to research conducted by the Institute of Medicine of the National Academies of Science, Engineering, and Medicine (NASEM), diagnostic errors cause around 10% of patient deaths and account for almost 17% of hospital problems. Although NASEM said that these challenges are not caused by professional ignorance, but rather by a combination of variables such as ineffective communication between patients and organizations, human mistakes, and others. 

 AI implementation and testing in the medical sector can aid in illness diagnosis and treatment by evaluating massive amounts of treatment and patient data (previous medical data, doctor reports, etc.) and offering relevant assistance and recommendations to clinicians. As a result, the total treatment procedure would be sped up and improved.  

Artificial Intelligence (AI) to Improve the Medical Sector

The use of AI in medical diagnostics can assist physicians to enhance medical therapies in a variety of ways. Physical burnout as a result of overwork is a severe problem that many medical professionals experience these days. It reduces medical practitioners’ overall performance, which leads to an increase in diagnostic inaccuracy. The most recent Medscape National Physician Burnout and Suicide Report 2020 data highlighted the risks of putting too much pressure on physicians, particularly those juggling families, retirement plans, and the intricacies of their employment.  

Furthermore, AI in medical diagnosis could help reduce the number of diagnostic errors made every year. Making use of the AI ability of deep learning professionals can increase the efficiency of disease detection. A recent study shows that an AI system has achieved the skill of tracking breast cancer similar to an average breast radiologist, demonstrating a 95 percent accuracy rate, published in the journal of the National Cancer Institute. In oncology, AI applications are being utilized to identify tumors. Pathologists use machine vision technologies to diagnose diseases in bodily fluids and tissues, and facial recognition helps match phenotypes with specific rare diseases. 

Other AI use in healthcare includes the development of new medications and more effective drug targeting to improve efficacy and prevent bad drug effects. Hundreds of startups are actively leveraging AI for drug discovery. For instance, Atomwise (a San Francisco-based startup) has recently joined a partnership knot of 1.5 billion USD with the giant Jiangsu Hansoh Pharmaceutical Group on working to design new cancer drugs. 

AI and Internet of Medical Things (IoMT) 

The application of artificial intelligence and the Internet of Medical Things (IoMT) in consumer health apps is another possible area where it can flourish its benefits. These solutions put medical IoT devices to gather healthcare records and AI-based medical apps to evaluate the data and provide modifications based on patients’ current lifestyles. The patient-centered approach of medical software developers has brought the in-house trend toward at-home health solutions.  

One of the potential implementations under consideration is a voice-based virtual nurse program. The main goal is to improve the hospital room experience and make the process of preparing patients to continue their rehabilitation at home easier. Virtual nurses also help to minimize patient anxiety, improve privacy, keep patients interested, and raise patient satisfaction with medical services. 

Challenges with AI in Medical Diagnosis

While implementation of Artificial Intelligence (AI) opens doors of many possibilities but at the same time it raises several challenges for the medical sector: 

Safety of Data

The desire for huge datasets encourages developers to acquire such information from a large number of patients. Some patients may be worried that this data collection would infringe on their privacy, and lawsuits have been brought as a result of data sharing between large health institutions and AI startups. AI may potentially compromise patient privacy in another way: deep learning AI can anticipate personal information about patients that were never even revealed to the algorithm. (In fact, this is often the goal of healthcare AI.) 

Data Availability 

Training AI systems need a massive quantity of data from many sources, including electronic health records (EHRs), medication records, symptom data, and consumer-generated information such as activity trackers or purchase histories. Health data, on the other hand, is usually problematic. Data is frequently spread across several platforms. Aside from the variances stated above, patients routinely change doctors and insurance carriers, resulting in data fragmentation across several systems and formats. This fragmentation increases the risk of inaccuracy, decreases dataset comprehensiveness, and boosts the cost of data acquisition, restricting the sorts of organizations that can construct successful healthcare AI. 

Error

A well-known primary concern is that AI systems will be, or can be, inaccurate on occasion, which might have a negative impact on the patient’s life or other healthcare difficulties. If an AI system prescribes the incorrect medication to a patient, fails to discover a tumor on a radiological test, or gives a hospital bed to one patient than another because it mistakenly predicted which patient would benefit more, the patient may experience damage. Despite this, countless injuries occur in the current healthcare system as a result of medical mistakes, even when AI is not involved.  

AI flaws can differ from one another due to at least two factors. For starters, patients and physicians may react differently to software-caused injuries than to human-caused ones. Second, suppose an AI system is extensively utilized; a single error can endanger thousands of lives. 

Conclusion

In the healthcare business, artificial intelligence has a bright future. Although AI medical diagnosis is not now commonly employed in most clinical settings, experts predict that widespread AI intervention is not far off. And, as we progress toward digitalization and integration of medical data, we will see a rise in the use of AI to assist us in making the best and most cost-effective answers for complicated topics.  

To discuss AI implementations in medical diagnosis, feel free to reach out to our expert team of testers. Contact us for a quick consultation!  

The post Artificial Intelligence (AI) and its Assistance in Medical Diagnosis appeared first on ImpactQA.

As per research by Reports and Data, the global IoT in Healthcare Market is forecasted to grow at a rate of 19.8% from USD 60.83 Billion in 2019 to USD 260.75 Billion in 2027. The scope and benefits of IoT in healthcare can be majorly associated with trends about innovations in medicine, medical devices, and overall healthcare service delivery for maximum customer satisfaction.

These devices give you the liberty to be connected remotely across an active network infrastructure that allows better integration of devices with your computer systems. This kind of integration helps with improved efficiency and accuracy adding to a ton of economic benefits for you and your clients.

Today IoT has a huge influence on the healthcare sector that involves easy monitoring of patients and using such data for better analytics. Talking about IoT for medical device integration, the focus has shifted towards the end consumer needs that include medical devices made to record data of the patients’ everyday vitals. A lot of this process is automated that includes auto-generated reports and treatment recommendations. The hiccup that arises here is the little importance companies give to the privacy of this data. Easy accessibility of such critical information to someone outside or even within the system gives them the power to severely injure or even kill someone without being detected. The rise of such hackable medical devices has pushed the food and drug administration (FDA) to issue formal guidance on how such cyber vulnerabilities must be handled. Today we have enough QA consulting companies that deliver step-by-step guidance on how to proceed with safely releasing a medical healthcare device into the market.

This write up will focus on the various security and privacy issues healthcare based applications face and what measures companies can take to secure their healthcare IoT devices.

Security and Privacy Issues with IoT in Healthcare:

DDoS with IoT Devices

Distributed Denial of Service or DDoS as it’s called is a non-intrusive internet attack carried out to dismantle the targeted website that eventually slows down the functionality of a server, application or network by flooding it with fake users traffic. This essentially means that a server is denying its service to the user resulting in the system crashing. There are various methods used to prevent your application from a DDoS trap that mostly uses malicious botnets. Off lately, the code of malware that builds botnets out of IoT products was publicly released that instantly increased the number of IoT devices infected by it to more than 450,000 approximately. The same value was close to 200,000 before. Imagine the amount of collateral damage this must have caused internally putting the security of thousands of application’s data at risk.

Wearable Technology and Associated Security Risks

The latest invention in the IoT for healthcare devices that rolled into the market has been wearable technology. Gadgets like smartwatches, wrist bands, smart monitors and other associated wearable devices work as extensions to your mobile devices and give access to news, notifications, texts, emails and much more. They come with an inbuilt sensor that measures your stress, SPO2, sleep and what not, but when it comes to security most of these devices fail to save you from malicious attackers.

Issues that range from personal data exposure to user interfaces that lacked two-factor authentication or the aptitude to freeze accounts after multiple failed password attempts all contributed to the extreme levels of vulnerability your integrated IoT devices can expose you to.

Top 4 Ways To Secure Your Healthcare IoT Devices

IoT Security Analytics

When it comes to healthcare, it is essential to track all major activities happening in your IoT enabled devices and applications. This can be accomplished by IoT security analytics. IoT security analytics give you notifications about potential cyber threats in your app well in advance, which gives you enough time to mitigate them before your app goes into a potential data risk. It helps you create a full proof protection strategy through in-depth data analysis where it uses data procured through different devices clubbed together.

Software Update

Major IoT devices need remote access and connection via sensors to collect data in the healthcare industry. Hackers majorly target remote devices integrated through a network because of their limited security provisions. When it comes to increasing security standards and significantly reducing the rapidly evolving cyber threats in networks, it’s essential to update your healthcare IoT device software from time to time.

These software updates help IoT devices incorporate new features by providing secure remote management firmware along with identifying and eliminating security breaches.

Public Key Infrastructure

Public Key Infrastructure or PKI is a security solution that authenticates devices and users in the online world. It provides encryption and authentication solutions for all IoT devices that can be used to gate private patient data and ensure its visible to only concerned departments. A PKI is a common and useful way of minimising the risks associated with transferring information from one device to another. It uses a cryptographic key to identify a user or device on an online network. This data can then be shared with internal departments to check the vulnerability of your application in the latter stages. The demand for PKIs has increased significantly and in order to enable safe authentication of your system, you need to install proper healthcare certificates.

Secure Cloud Platform

Today cloud platforms are the top preference of all major companies or businesses for data storage. Similarly, the healthcare sector also uses cloud platforms for storing and transferring essential data from IoT devices. Therefore, cloud data storage protection becomes a major concern to protect IoT healthcare devices from data breaches. The way to go ahead is proper authentication control. Some basic practices that can be adopted include changing passwords at regular intervals and ensuring the account is blocked for a defined time frame after repeated failed attempts.

Wrapping Up

There have been active researches across the industry that predict the interference of ransomware for a medical device or wearable technology. It’s obvious that IoT devices are here to stay and their involvement in healthcare cannot be limited. They help you cut costs and increase the efficiency of your systems to a great extent.

Hence, it’s is important to ensure that the networks we use run on automated workflows and give quick access to critical work information while ensuring the security of your applications. This can easily be accomplished by implementing proper security policies and implementing solutions that focus on vulnerabilities and configuration assessments, along with proper event monitoring.

Security of IoT healthcare devices isn’t just about figuring out security risks and securing data. It’s more about building strong and long-lasting relationships with your clients. You need a strong testing partner to create that kind of impact with your clients. ImpactQA’s dynamic application security testing services effectively expose your software vulnerabilities to minimize risks and ensure better security and scalability of your application.

Have a new project in mind? Schedule a call with our experts now!

The post Security and Privacy Issues with IoT Healthcare Devices appeared first on ImpactQA.

With such a pace, the latest study by Meticulous Research on the medical devices testing market states that it’s expected to reach $12.5 billion by 2027, at a CAGR of 4.7% during the forecast period of 2020 to 2027. This growth is predominantly driven by the increasing demand for quick validation and verification of these devices along with ensuring stringent government regulations across the MedTech industry. Moreover, the availability of integration features of these medical devices with mobile applications offers prominent opportunities for equivalent market growth.

In this article, we will try and have a closer insight on the need for Quality assurance and Quality control as an integral part of the medical devices testing services.

What is Medical Device Testing?

For those unaware, medical device testing is a basic process of demonstrating that the device will reliable and safe to use at the time of a medical emergency. This is one of the most crucial steps towards transforming an innovative design into a reliable and marketable product in future.

These devices or the entire MedTech industry is governed by multiple regulatory bodies and have to satisfy a set of compliances and standardizations before moving forward. This is where expert medical device testing service providers come into the picture. These giant software testing companies create effective device testing strategies and ensure that your devices are well integrated with your mobile applications, are thoroughly tested and fully functional before their release. Moreover, they need to deliver effective performance, accurate readings and should be safe while in use.

Medical device testing ensures that devices fulfil all quality-related aspects of the product for which you require stringent Quality Assurance and Quality control support that helps deliver optimum quality and reliability of these devices.

Let’s take a closer look at the key difference between Quality Assurance and Quality Control to have a better understanding of these terms and their special role in the medical devices testing industry.

Quality Assurance (QA)

The most essential part of quality assurance is ensuring the right process. Skipping through processes or not following a comprehensive testing strategy that leaves out loopholes can land you to releasing unfinished products that are full of bugs. It’s the job of a QA expert team to maintain these processes to ensure high-quality products are delivered.

Talking about medical devices, comprehensive quality assurance helps prevent flaws in the way a medical device is manufactured by closely observing the entire process.

Quality assurance isn’t a single step, a particular method, or a tactic that can be used at once. It involves a combination of methods and processes to prevent flaws in a device or a system

The Essential Role of Quality Assurance in Medical Device Testing

Your quality assurance services provider closely monitors the medical device development process to ensure that it meets the standards set by regulatory bodies (that include FDA, ISO, etc.), along with the internal quality standards by the company.

A general rule of thumb followed here is the Deming cycle or the PDCA cycle that comes from a four-step process: Plan, Do, Check, and Act:

• PLAN: plan ahead for a change. Analyze and predict the results
• DO: execute the plan, taking small steps in controlled circumstances
• CHECK: study the results
• ACT: take actions to ensure standardization and help improve the process

The quality assurance testing highlights why we refer to quality assurance as process-oriented.

QUALITY CONTROL (QC)

Unlike QA, the most essential part of quality control is the product. Therefore, quality control experts swoop in once the product is past the development and quality assurance stages. It helps ensure the ‘final product’ is bug-free and abiding by all the necessary quality checks.

Talking about Quality control in medical devices, your QC expert team is predominantly responsible for identifying flaws in a medical device after they have been manufactured but before its market distribution.

Note: looking at the current Covid 19 outbreak, the quality control department has taken a big leap. Device manufacturers need to move quickly enough to help confront those affected by the pandemic while ensuring they safely move past all the criteria mentioned in the quality control department.

The Essential Role of Quality Control in Medical Device Testing

As mentioned above, the role of a Quality control expert is to ensure a fully tested and functional product is launched into the market.

They have a variety of tools at their disposal that are used to test or inspect the manufactured product. They come in once the product is entirely ready for shipment and give a final check to the product before its release.

There are three primary QC tactics followed worldwide:

1. Acceptance criteria: the quality control staff is responsible to establish a clear acceptance criterion that details the essential quality checkpoints their team will be utilising to determine if the product conforms to the established specifications. They also document, from a batch of products they test, the products that match the set criterion and which did not
2. Product testing: as per FDA quality system regulations, Medical device manufacturers can enjoy the freedom to design their quality control test but need to ensure that all these tests are well documented and prove the efficacy of the verification process
3. Corrective and preventive action management: CAPA comes into the picture when a sample out of the product batch tested fails to pass the set quality control requirements. They perform a root-cause analysis to identify and discover a systemic flaw that majorly led to the nonconformance

To state a single line difference: Quality assurance is more proactive and process focussed. Quality control on the other hand is more reactive and product focussed.

It’s the right combination between these two that gives any medical devices testing company the edge to deliver quality products into the market

Enable Quality Outcomes With The Best QA Solutions

If you are a medical device manufacturer then making sure you abide by the quality assurance and quality check regulations diligently is the most vital decision. Noting the fact that you have a life at stake in case your developed product fails to deliver the quality it’s expected, it’s extremely important to either have a full-fledged in-house quality assurance and quality check team or to opt for QA outsourcing to avoid any major fatalities.

Listed below are a few befits that you may receive in case you opt for hiring a QA consultant for a medical device testing service.

• Reduced project budget
• Faster time-to-market
• Continuous support & maintenance
• Efficient domain expertise

We at ImpactQA emphasizes project and business requirements to provide outsourced software testing solutions that ultimately increases the cost-effectiveness of your QA processes. As a software testing and outsourcing company, we implement the most suitable testing strategy as per your medical device to eliminate various challenges linked to QA processes and out-of-sight costs.

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