Guide on how to Outsource Data Annotation for the Healthcare Industry

Guide on how to Outsource Data Annotation for the Healthcare Industry

 

The world is an unforgiving place. One has to keep running in order to stay in the same place; at least in relative terms. Everyone else in running, hence so should you.

It applies to healthcare as well. Patient expectations of treatment and care are rising, while expecting to pay less for the same, as treatments become mainstream and acquire volumes.

What is a business engaged in the healthcare cycle, either a pharmaceutical company producing drugs and medicines, or a hospital, providing treatment and care, or an insurer, creating financial solutions for people to pay for healthcare expenses?

 

What are healthcare solution providers doing?

They are harnessing data and employing smart technology solutions to move forward at a rapid pace, even as breakthroughs in science and medicine happen as and when they do.

Pharma companies are making progress in formulations, repurposing and targeting efforts based on analysis of patient records and clinical trials.

Biotechnology device makers are leveraging data on health outcomes to produce better devices that can peel more layers off a condition.

Insurers are mining information from health plans and correlating with claims to make health insurance cheaper by isolating instances of fraud and predicting claims with greater accuracy.

Hospitals are developing algorithms for efficient allocation of their scarce resources so that a greater population segment can be served with the same set of resources.

As are many others providers engaged in the healthcare industry in one way or another.

The technology solution that has been requisitioned by all of them is what is fairly well known now as Artificial Intelligence (AI) and the process of Machine learning (ML) on which it depends for the level of efficacy with which it can perform.

 

Data annotation for the healthcare industry – enabling AI

Data annotation is the bedrock on which the superstructure of AI engines is built. The stronger the bedrock, the more reliable the AI engine.

While we may have an understanding of the terms ‘data’ and ‘annotation’ separately, the meaning of the term ‘data annotation’ bears repetition, because of its position as an enabler for the AI which is enabling healthcare industry participants to do more.

AI is the technology that seeks to undertake many tasks done by humans today, using human intelligence.

Like identifying tumors. Or detecting kidney stones. Or teeth degeneration.

To be in a position to do that, AI engines need to be trained to learn how humans think and behave. This training, thankfully, can only be done with the help of humans, by creating training data sets.

The usage of human intelligence to make sense of what we may call raw data, is not a facility available to a machine, or a software program. What a software does have is the ability to ingest information, understand patterns, and apply them without human bias to the next set of data that it comes by, to arrive at conclusions it has been taught to arrive at.

What needs to happen for this is for that raw data to be converted to a format that is meaningful for a machine to ingest based on which rules can be taught.

If an MRI scan is the tool based on which the presence of a tumor can be confirmed or denied, then the software needs to be taught how to read an MRI scan which, otherwise, is a meaningless set of pixels for it.

This is done by creating data sets for ML.

A particular specialist doctor might review a hundred MRI scans every week and arrive at a conclusion based on what he sees in them. To enable a machine to be able to do the same, he needs to mark/ highlight/ point the aspects based on which he has reached his conclusion. This needs to be done in a manner that can be understood by the engine that is being trained. It could be through highlighting the size of a particular organ and attaching an outcome to it, which is then uploaded to the software through ‘computer vision’ that enables the software to ‘take in’ this information.

When done repeatedly, the software is built to create associations such that when the next MRI scan comes to it without any markings, it is able to reach the same conclusions as it has been taught to do by the ML data sets.

This is data annotation. To be more specific, data annotation for the healthcare industry, is the process of converting ‘raw’ data to ‘smart’ data for the purpose of training an AI algorithm. As the annotated data set provided to it keeps getting bigger, the AI engine keeps getting smarter, helping in establishing patterns. A kind of equation building process which will enable it to find an ‘x’ the next time it encounters a set of ‘y’s.

 

Why outsource data annotation for the healthcare industry?

If we are brutally honest with ourselves, data annotation is a critical but perhaps one of the most monotonous, dull, unappreciated jobs in the whole AI and ML process. And, whether we like it or not, if we have to achieve some sort of progress on AI, this process needs to be done by human data annotators.

In many other industries, data annotation may be a monotonous but straightforward task that can be done by anyone with a little training, like identifying objects on a street while building a training data set for autonomous vehicles. To annotate data for the healthcare industry is a different ball-game altogether that needs to marry a certain amount of knowledge of medicine and healthcare with all the other skills required for the task. Lives will depend on their work.

After all there are only so many ophthalmologists and endocrinologists whose priority is patients, not marking MRIs and CT scans for building AI models. This is where specialised medical data annotators complete the jigsaw.

With the development of AI, the task of data annotation has become a job category by itself, under which medical data annotation could be a further specialisation. They are available in larger numbers than doctors and for more reasonable prices too. Hence it stands to reason to permit this group to do data annotation for the healthcare industry.

The choice should be quite clear. To engage an outsourcing outfit that specialises in data annotation solutions. That lives and breathes Data Annotation.

Of course, at the start of any exercise, experts in the particular field, radiologists or cardiologists, may be required to ‘show the way’ and train the resources who are going to be doing the major part of the exercise.

 

Choosing a partner

The decision to outsource having been taken, selection of a provider would be the logical next step. What parameters would you use to separate suitable providers from the unsuitable ones?

Prior experience

It would be desirable to select a partner with prior experience in data annotation for the healthcare industry. Though experience of providing these services to competitors is ideal, as they are likely to be the most similar to your work, it could create an additional sensitivity of data security as one is always interested in knowing what a competitor is doing. Hence, this may need to be viewed in conjunction with the partner’s ability to provide comfort on data security.

oWorkers has successfully executed a wide variety of data annotation projects covering a wide range of data types and annotation services, over the eight years of their existence.

Accuracy and quality of delivery

The final goal is great quality, irrespective of the type of work, regardless of the type of data annotation. When we enter into a commercial contract, while we are looking for many things, the one thing we always want is great quality of work. Of course, at times we need to make compromises because of budgetary constraints and other reasons, but for a given set of constraints, we want the best quality.

The provider should be able to demonstrate the ability to consistently provide superior quality and accuracy. Testimonials from existing clients is generally accepted as a good way to establish the quality and accuracy delivered on existing contracts.

99% is the accuracy oWorkers delivers across contracts, across different measurement systems, and the same is on offer for your outsourcing project. Many of our clients can be referenced.

Speed and turnaround time

The faster you finish a task, the more you will be able to do, is the simple logic. Business always wants more. Why should healthcare be any different?

To annotate data for the healthcare industry could be a painstaking activity, to be done with care, where data keeps building up gradually. Speed in this context refers to not only the rate at which each transaction is processed, but also to the partner’s ability to find the capacity to process greater volumes so that the AI engine for which it is being done, can be up and running.

With three global centers and 24×7 operations, oWorkers can not only deliver to exacting turnaround time expectations, but also create capacity to work with specialists in order to deliver larger volumes.

Access to talent pool

Human input being a pre-requisite to annotate data for development of AI, the need for human resources in the right quantity with the right skills and training is a dependency. Attrition being a feature of the BPO industry, the need for hiring is continuous, even if the business is not growing, as there will be a requirement to fill the gaps created by people leaving the company. Hence, access to a talent pool for year-round hiring is a requirement.

With the deep commitment to the communities we work in, oWorkers is seen as a preferred employer and benefits from a regular flow of interested candidates approaching us for employment. This also keeps our hiring costs in control as we do not need to spend money on attracting talent. With our philosophy of working with employees, and not freelancers, gives oWorkers the flexibility of deployment based on requirements, and helps create long-term relationships.

Commercials

An essential part of any commercial engagement, a party delivering goods or services under a contract receives value for it, usually in money terms, based on agreed terms. Also called ‘pricing.’ In a B2B engagement, the basket of services and products provided is unique to the buyer, as is the price for it. While low is desirable, the outsourcer needs to ensure that the pricing terms offered will add value to their business instead of opting for the lowest number.

At oWorkers, with our nearshore and offshore centers, you have the potential to save up to 80 % on your cost prior to outsourcing. We also offer you a choice between rate per unit of output and rate per unit of resource in a transparent manner.

Multi lingual

The consistency of processing enables an organisation to expand the volume of processing and build connectors to processes in and out of it. When you seek a partner to annotate data for the healthcare industry it is important to have a partner who is able to offer multilingual processing support as that will be a key factor when the business grows and expands across the globe, as we are, today, more global and connected than we have been at any point of time in human history.

Across the three centers of oWorkers, support is provided in over 22 languages for a wide variety of data services.

Internal Quality

Whatever be the business process outsourced, Internal Quality has come to occupy an important role in ensuring that delivery teams stay true to the task committed to a client and there is a system of monitoring in place before gaps, if any, become visible to the client. Outsourcing of data annotation for the healthcare industry is no different.

With a mix of QA (Quality Assurance) and QC (Quality Control) processes supported by technological tools, oWorkers delivers best in class performance which also supports our delivery of over 99% accuracy. The Quality team, with independent reporting lines directly to senior management, also ensure that the leadership team is kept abreast of developments and are equipped to intervene as and when a need may arise.

Access to Technology

To annotate data for the healthcare industry might sound like ‘technology for the sake of technology’ as it needs to be done to create a functional AI engine, which is, again, technology. But on a deeper look we will find that AI is not the end game. The AI is being created for a purpose, which could be to analyse MRI scans faster, or evaluate many more CT scans as compared to a human and do it more accurately.

Advancements in technology are changing the world, even to the extent of accelerating the development of technologies like AI. Access to technologies for doing data annotation is a useful resource for this purpose.

Our partnership with leading data annotation tool owners for both NLP and Computer Vision projects gives oWorkers access to the best technology solutions, including upgrades to newer versions as and when they take place.

Data Security

Data security is linked to technology through an umbilical cord, since data is stored digitally and moved digitally for transaction processing. Data being a critical resource for a business, ensuring its security becomes a key determinant in vendor selection. When the same vendor works for competitors too, which gives them the benefit of prior experience and knowledge, it becomes even more important.

Firstly, GDPR compliance is a requirement for oWorkers, not a choice, as we operate out of the Eurozone. In addition, we offer super secure facilities and protocols for your data security with ISO certifications (27001:2013 & 9001:2015). Our staff also sign NDAs (non-disclosure agreements).

Scalability

Variation in volumes is a common feature of business. The business of data annotation for the healthcare industry is no different. Some businesses retain staff at the peak levels so that transaction flow can be handled. These extra resources, during lean periods, are an additional cost for the business. Some other businesses are able to handle short-term peaks by taking on short-term additional resources and staying lean the rest of the time. BPO providers, if they offer the facility of short-term resourcing, can be of great service to clients, as it enables them to stay lean.

For most projects, our local community associations enable oWorkers to ramp up and down fast. To be more specific, by a hundred headcount in 48 hours.

 

The oWorkers Advantage

As a pure player, specialising in Data and Content services with multilingual capability, oWorkers stands tall amongst its competitors. Our delivery centers are located in three global locations providing the benefit of business contingency in times of need.

All our workforce remains prepared to work from home when required. Our management team has over 20 years of hands-on industry experience. Locally registered in the global centers it operates from, oWorkers has been a consistently profitable enterprise.

As a result, we have been a trusted partner of several UNICORN marketplaces over the years.

Partnering with us creates positive social and economic change through employment in underserved communities. By working with us, you help bring motivated individuals into the global digital economy.

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