Category: Radiology

04 Feb 2019
PACS

Picture Archiving and Communication System (PACS) and Its Benefits

Technology and innovation play a major role in today’s healthcare system as it is crucial for sustaining health. It has enhanced the quality of medical care offered to patients, and PACS system in hospitals & health facilities is one such example of technology improving medical care.

PACS (Picture Archiving and Communication System) has changed the way radiology works and is now considered one of the most essential requirements in healthcare facilities. Sharing of instant medical images electronically and reporting them remotely is now very easy and quick, thanks to this invaluable software. With AI (Artificial Intelligence) enabled technologies now becoming available in PACS, their functionality is growing by the day

What is PACS?

PACS (Picture Archiving and Communication System) is a medical imaging technology that provides economical storage, presentation, retrieval, distribution, and management of medical images. Transmission of electronic images and reports takes place digitally via PACS. Thus, manual filing, retrieving and distribution of film jackets is no longer required. It allows storage and viewing of all types of medical imaging by healthcare organizations both internally and externally.

A radiology PACS is often deployed with RIS. An RIS is used to record patient history and schedule appointments, whereas PACS focuses on image storage and retrieval.

The four major components of PACS are:

  • The imaging modalities
  • Transmission of patient information through a secured network
  • Interpreting and reviewing of images through a workstation
  • Storage archives for retrieval of images and patient reports

Benefits of PACS

PACS improves efficiency in electronic data handling workflow. It offers a cost and space advantage due to decreasing price of digital storage. Benefits provided by PACS are many, but here we highlight few of the most important ones:

Improved Viewing and Analysis

An effective viewing and analysis is possible as PACS’ digital images enable you to zoom in and operate the images for a more elaborate analysis.

Where the conventional film can only exist in one place at one time, PACS enables simultaneous multi location viewing of images. It enables collaboration among radiologists as they can seek each other’s opinions by viewing the cases simultaneously and discussing them under peer review module. The interpretive skills of the professionals prove beneficial for the patients as well. The high-quality images make it possible to give a more accurate diagnosis.

Easy Accessibility to Images and Reports


PACS enables instant and easy access to images and reports. No matter where the tests are performed reporting can be done remotely and results can be shared anywhere, even if it is an isolated facility. PACS enables submitting reports, archiving images and transferring them through a portable media anywhere in the world. Practitioners at different physical locations can access the same information concurrently for teleradiology. In addition, quick access to prior images is also possible at the same institution. Radiology history of patients is available, which allows comparison with previous studies.

User-friendly Software


User-friendly since there are several customizations available for easy use of the software for staff and beneficial for patients. PACS is a great integration platform for other automation systems such as Radiology Information System (RIS), Electronic Medical Record (EMR), and Hospital Information System (HIS). The PACS database automatically groups all images chronologically, correctly labelled according to their examination. They can also be retrieved easily with the help of criteria’s such as name, hospital, referring clinician, etc.

Efficient Data Management

The system provides an efficient, seamless review of radiology cases within a physician’s daily workflow as it makes it easier to store and organize imaging data, with a centralized and accessible system. Data management becomes more efficient as the number of duplicate images can be reduced as previous data is available with the system.

Steps to Consider While Purchasing or Upgrading PACS

While purchasing or upgrading to a new PACS, one should look for features such as scalability and user-friendliness. The features should be easily configurable and should have uploading features for prior studies. Other than that, it should have a voice recording feature, integration with the Hospital Information System (HIS) and the Cloud feature. It is also beneficial switching to a new system when it has in-built AI algorithms.

An integrated RIS-PACS is a great advantage to radiology department as it can give evidence-based insights such as enhanced productivity of radiologist, turn-around time, modalities being used for improved workflow, and referring physicians sending maximum exams. RADSpa, one of the best integrated RIS-PACS available, provides a customizable work-flow suiting the requirements of radiologists.

A RIS-PACS’ rich intuitive AI integrated workflow, supporting all DICOM modalities, an orchestrated work-flow, multilingual software, advanced application supporting MIP/MPR and 2D/3D viewer, a scalable architecture and ability to integrate with any existing PACS and 3rd party AI algorithm, is sure to add value and increase productivity for any radiology department.

28 Dec 2018
Dr Anjali

Artificial Intelligence in Emergency Radiology

A Report, based on the Keynote Speech delivered
– By –
Dr. Anjali Agrawal, Head, Teleradiology Solutions, Delhi Operations
@ Artificial Intelligence in Radiology 2018 Symposium, November 10, 2018
Organized by Telerad Tech and Image Core Lab

Dr. Anjali Agrawal addressed the audience about how AI was going to be relevant in emergency care and emergency radiology.

Deep learning and the human brain

Speaking broadly on artificial intelligence (AI), Dr Anjali said that AI is a more gen­­­eral term and includes machine learning (ML) and deep learning (DL). Machine learning, a specific type of AI, gives computers the ability to learn without being explicitly programmed. Deep learning, a subset of machine learning, mimics the human brain configuration, where the multiple neuronal layers or neurons can crunch vast amounts of data and draw conclusions. In particular, DL has immense relevance for radiology and healthcare. The availability of large amounts of annotated image datasets and increased computational power had made AI a reality and it wasn’t an illusion anymore. It is moving from experimental to the implementation phase now.

Current state of Emergency and Trauma Care

Dr. Anjali drew attention to the current state of emergency and trauma care in India. From trauma registry, it was a documented fact that trauma related deaths in India occurred every 1.9 minutes. The mortality in serious injuries was 6 times worse in a developing country such as India, as compared to a developed country. A WHO survey revealed that there were more deaths due to lack of timely care than due to other diseases like AIDS, Malaria and TB, all put together.

Dr. Anjali said that, more than 80% of Indians didn’t get care within the golden hour and she highlighted the challenges in emergency care and radiology. There was tremendous pressure on the limited resources that were available at one’s disposal. The process from the scene of accident to the emergency room is disorganized. Dr. Anjali drew attention to the education system and training, which was quite heterogeneous.

AI will transform the ER services

As per Dr. Anjali, AI could be very useful for triage in the emergency room. Studies have shown that Emergency Severity Index assignment by doctors and nurses is correct only 60% of the time. They ended up under-triaging almost 27% of the patients. And a vast majority of those, nearly half, went into the mid-acuity group, level 3 – a typical human tendency to play safe.

AI and deep learning could help by analyzing the complex data from various sources – the age and sex of the patient, presenting history, complaints, vital signs, what was the mode of transport – did the patient walk-in or was s/he brought by an ambulance, past medical history etc. This could help in transforming the emergency department operations. By using these algorithms one could accurately triage patients, so that the critically ill patients got the attention of the emergency medicine physician and were managed appropriately. These algorithms could also help in allocating resources appropriately, minimizing mismatch between staff and patient case load, with improved patient outcomes. AI could help expedite interpretation of emergent imaging studies. These algorithms would be able to make predictions of adverse events and help make an individual-specific follow-up plan.

AI will revolutionize the radiology workflow and create smart enterprises

Dr. Anjali maintained that disruptive new generation healthcare technologies such as AI, robotics, machine learning and deep learning will revolutionize radiology workflow in many ways and that it was going to lead to massive improvements in quality, value and the depth of contribution of radiology towards patient care. She stated that one of the most well researched applications is emergency radiology.

Dr. Anjali cited that, AI could help make an informed decision regarding the need for imaging and the choice of modality based on analysis of the patient records. AI enabled algorithms could play a huge role in reducing radiation doses of CT examinations or reducing scan time for MRI, by using various enhancement and post-processing techniques. However, the overall decision making and communication with the referring physician or the patient would require the intervention of a human radiologist for quite some time, despite being aided by AI.

AI can help reduce scan timings and dosages

Dr. Anjali said that, the algorithms could enhance very noisy, grainy and undersampled data, such as from MRI, which were being produced in shortened timeframes and produce high-resolution MRI images– with huge implications in the emergency room, where one tends to shy away from doing an MRI because of time constraints. For e.g., if an MRI could be done in two- thirds or one-third the time required, one would be more comfortable in sending a sick patient for a suspected hip fracture for an MRI.

Similarly, these algorithms could also be applied to Computed Tomography (CT) scanners to help reduce the CT radiation dose – a huge advantage, as the reduction in radiation dose from CT would be comparable to a standard chest x-ray. One would be able to do ultra low-dose CTs, and get more information from diagnostic quality images, compared to a radiograph.

AI can ease the workflow of a radiologist in many ways

Showcasing a typical workflow of a radiologist, Dr. Anjali said that the radiologist logs into the system, reviews his/her work list and selects a study to review. The radiologist reviews other information such as patient history, prescriptions, etc., that are related to the case. Once the images are presented, the radiologist, in most cases, adjusts the hanging protocols to enable him/her to perform the interpretation and generate a report. The initial process of arranging studies is time consuming. Citing the recent developments in reading protocols, Dr. Anjali said that it could help hang the images in an interactive manner, learning each time, catering to individual preferences, and saving time.

AI can help in detection of findings, segmentation, quantification and reporting, in a manner that is easier to understand by both the referring physicians and the patients.

Dr. Anjali maintained that AI could help the radiologist by triaging cases, such that only the positive ones could be seen by the radiologists for further interpretation. She was of the thought that, as opposed to a few articles quoting that AI would replace a radiologist for particular targeted applications,  AI would assist a radiologist, where a radiologist would act as a second reader or vice versa.

She gave one particular example where an article looked into automated detection of critical findings on non-contrast CT examinations of the head –hemorrhage, mass effect, and hydrocephalus using an AI algorithm, which would be helpful in triage. If the algorithm found the non-contrast CT to be negative, it went through another stroke algorithm. In the case of it being positive, it was labeled as a critical imaging finding, and if they were both negative, it was labelled as “no critical imaging finding”. The algorithm had a good sensitivity of 62% and a specificity of 96%, comparable to a radiologist in the detection of acute ischemia. The sensitivity and specificity were higher for detection of hemorrhage, hydrocephalus and mass effect, matching the performance of the radiologists. Therefore, the study concluded that there was a huge potential for AI algorithm in terms of screening and detection of critical findings in the emergency setting.

Dr. Anjali said that she had seen similar data in her group and had detected intracranial hemorrhage with a very high sensitivity and specificity using a hybrid approach of convoluted neural networks and factorial image analysis.  The data and the results were comparable to the existing literature and that more data pertaining to quantification and localization of intracranial hemorrhage is underway.

Juxtaposing her earlier statement on triage being the low hanging fruit for AI applications in radiology, Dr. Anjali, mentioned that apart from acute neurologic conditions, these triage tools had been used in the detection of chest radiographic findings by classifying them into normal or abnormal with a high accuracy of almost 95%.

She quoted another example of AI application – wrist fractures. These algorithms were trained by senior orthopedic surgeons. When the emergency room physicians, not trained orthopedicians or radiologists, used them, their sensitivity improved from 81% to almost 92% and specificity from 88% to 94%; with a relative reduction in misinterpretation rate of almost 47%. Dr. Anjali simplified it further by saying that the algorithm was able to emulate the diagnostic acumen of the experts by providing the labels on where the fracture was and also put a heat map, assigning a confidence level to the detected fracture.

Adding on, Dr. Anjali said that AI applications would also be useful in detection of non-acute findings the emergency radiology setting. These may be overlooked because the focus is on the critical life-threatening illnesses. AI could help with measurements of bone density, detection of fatty liver, coronary calcifications, and the presence of emphysema, which may not be relevant in the acute setting, but would have implications in the future.

AI can make expertise widely available and scalable

Dr. Anjali then stated that according to her, AI would become a huge leveler in terms of the expertise and experience of radiologists. Good radiology consult would become easily accessible, affordable, as well as scalable. In the scenario of a mass casualty incident, the algorithms could be put to use to quickly distinguish between critical and non-critical cases. Handling massive imaging volumes would also become easier.

Dr. Anjali mentioned about one particular study on automated bone age estimation where the algorithms were extremely accurate as well as reproducible, with an interpretation time of fewer than 2 seconds. This is a huge achievement because every radiologist knows how tedious and time-consuming the task of bone age determination is.

Man with machine synergy

She went to add that many similarities had been drawn between the fields of medicine and aviation. The pilot, as well as the doctor, needs to be highly skilled, as they are responsible for human lives. Both the professions have benefitted tremendously from automation. There is no flight without a human pilot, and similarly, there would be no healthcare without human doctors, because the legal responsibility would always be with the doctors. Dr. Anjali urged the doctors to not forget that medicine was an art and that the physicians needed to practice it like an art to stay relevant. AI would not replace radiologists. According to Dr. Anjali, it would be the synergy between man and machine that will help the profession as well as benefit the patients.

26 Dec 2018
New Pacs

Replacing existing RIS-PACS? Or a first time RIS-PACS buyer?

Struggling with what to do about an outdated RIS-PACS? Or, planning for RIS-PACS for the first time? In either case, it is not an easy and simple decision to take. But prolonging the decision will not help either. There will always be a dilemma, for an existing RIS-PACS user, regarding whether to pay the upgradation cost and stick to the same old vendor who ask for big bucks for each single support or whether to replace existing PACS with a new system which also comes with value added features such as AI algorithms in-built into the RIS-PACS. Other factors which needs to be considered before switching to a new system include the data migration costs, training costs, opportunity costs, related hardware upgradations costs, regulatory environment., cost of upgradation versus going with a new system, all these questions have to be answered.  As per expert estimate, transition and migration to a new system may take from 30-90 days. The challenge is also therefore to identify a vendor which can fast track the transition to maximum 15 days while ensuring that the ongoing work is not affected.

Finding the appropriate RIS-PACS can be a big challenge. Few important questions that needs to be asked regarding a new RIS/PACS is that it must be affordable, faster, should have prior studies uploading feature, voice recording feature, ability to integrate with third part voice recognition system such as dragon application or PowerScribe, and ability to be integrated with the hospital information system amongst the few important pre-requisites. Growing number of RIS-PACS providers are placing emphasis on reporting on the cloud feature.

What is an Integrated Radiology Information System (RIS) PACS?

PACS, or picture archiving and communication system, is a medical imaging technology used for storing, retrieving, presenting and sharing images produced by various medical hardware modalities, such as X-ray, CT scan, MRI and ultrasound machines. While digital medical imaging has brought in enormous savings for the imaging centres in terms of archival, storing, retrieval and sharing. It is the Radiology Information System (RIS), which helps manage the radiology workflow and the business.

Older RIS/PACS consisted of disparate systems – one for archiving patient images and one for storing patient records. Often, it would be noticed that the patient data in the PACS database may not be same as the data entered in the RIS database. If there is a mismatch between patient’s name or other demographic details entered in the PACS and RIS databases, then the system will not be able to correctly access all relevant records.  Such discrepancies can cause unwanted inconvenience to patients and referring physicians while also expose the facilities to unwarranted risks and legal liabilities.

Functions of RIS

Some of the key functions of RIS includes order entry; patient scheduling, assigning studies; tracking number of exams; assistance in billing etc.  A combination of the two (PACS and RIS) is termed as an integrated RIS-PACS. An integrated RIS-PACS gives radiologists or the administrators access to evidence-based insights such as which modalities are being used the most, which referring physicians are sending maximum exams, radiologist productivity, turn-around time, busiest time, days or week of the month etc.

An imaging facility stands to make enormous gain in terms of patient and financial outcomes if they choose an integrated RIS-PACS. RADSpa is one of the best Integrated RIS-PACS available on the shelf and deployable in various situations and for different kinds of facilities.

Now, what is AI-enabled RIS-PACS?

AI -Enabled RIS PACS is a platform on which resides numerous AI algorithms developed by the RIS-PACS providers themselves or those provided by niche AI companies. For example, the RADSpa RIS-PACS platform is AI enabled. So, when you go with RADSpa, you also get access to a number of algorithms. What makes this system very interesting is the fact that there are no initial upfront investments on AI part. You pay for the algorithms, only when you use them. That, too, it is pay-per-use system.

To replace or retain?

There was a time when the average longevity of a RIS-PACS would be around 7-10 years. But now in the current fast developing diagnostic imaging space where not only the volume of imaging and its complexities are growing by leap and bound but also the regulatory and privacy requirements such as HIPAA and GDPR, which is forcing radiologists to be always hard pressed for time and for quality reporting.  Any delay or hesitation in decision making can be hazardous to imaging business.

But hesitation presents hazards

Imaging facilities need to appreciate that failing behind on modernization and working with an out-of-date RIS-PACS can have serious consequences for clinical efficiency and financial health of the centre.  In addition, sticking to system which has far outlived its lifespan can also make it tough for a facility to keep up with the expectations of referring physicians, affiliated organizations and patients.

Telerad Tech, the global health IT company and one of the leading providers of integrated RIS-PACS Workflow strongly recommends that while analyzing current RIS-PACS and its vendor, an imaging facility should do proper audit in the key areas of operations such as – administrative, clinical, information technology (IT), regulatory environment and the market.

Important points to consider

For instance, if your existing PACS or RIS-PACS chokes your competitiveness, is unable to give you important insights regarding productivity of manpower, modality machines, have a confusing user interface, or simply doesn’t give you the next generation workflow tools such as workflow orchestration that optimize your productivity, you should consider a new system. Also, you should take into account the regulatory environment such as HIPAA and GDPR and go with systems which is capable of anonymizing patient data and is able to give you patient security framework (PSF) gateway, if needed. Teleradiology companies who are either reporting or have an ambition to serve defense hospital establishments, should ideally look for RIS-PACS which comes with PSF Gateway feature. RADSpa, which comes with PSF feature, is deployed at multiple hospitals under the Navy establishment in Mexico.

Making the Switch

Finally, having decided to switchover to a new RIS-PACS, a facility should first clearly define its requirement. Talk to vendors who can help you assess your current and future growth requirements.

First Time RIS-PACS buyers

For a facility which is considering acquiring PACS for the first time, they should look for a solution which offers latest productivity tools, can integrate with the existing DICOM compliant modalities amongst other features which are explained below.

Listing the requirements

Begin your process for procuring RIS-PACS, like for any other product, by listing the requirements. If possible, involve the Radiologists, Technicians, IT Team, Operations Team, and Finance Team in the process. Your list of requirements can include:

  • RIS-PACS should easily and fast integrate with existing modality machines;
  • System should be able to integrate with existing Hospital Information System (HIS) through Health Level 7 (HL7) protocol;
  • Should be able to reduce the turn around time (TAT) and increase productivity;
  • Should be able to integrate with existing PACS, without requiring any major overhaul of the system;
  • For teleradiology companies which have complex workflow and QA requirements, the facility should look for systems which has multi-read workflow management features and whose QA and peer review module facilitates collaborations as per ACR guidelines;
  • The new system should have smart features like workflow orchestration, real-time work lists, CD burning feature, multi-monitor support;
  • The RIS-PACS should meet regulatory requirements of FDA and should be CE certified, HIPAA and GDPR compliant;
  • Should have advanced 3D DICOM Viewer Features such as Minimum Intensity Projection (MIP), Maximum Intensity Projection (MIP), Multi Planar Reconstruction (MPR), and sculpting tools;
  • Radiologists/facilities often want to customize layout in the viewport using custom feature which helps standardize the workflows as per their specific requirements. So, look for such features in the system proposed by your vendor;
  • Facilities should also look for RIS-PACS which offers hanging protocol features for each specific modality machine;
  • Vendor Neutral Archive (VNAs) technology is today a game changer. VNA is enabling imaging facilities to archive and retrieve millions of medical images generated by disparate modalities from many different vendors. So, look out for RIS-PACS which is VNA compliant;
  • If you are a new and starting small, look for solutions which will be able to grow with you, i.e., look for a solution which is scalable;
  • Depending upon your specific choice, you may go with a solution which is pure cloud so that you can jump start radiology without any major investments in IT infrastructure;
  • You may go with an on-premise solution, if your already have the IT infra and manpower in place or have the capital to invest in on-premise solutions;
  • Products like RADSpa also offers something called Hybrid solution that stores images on site in the local system, while RIS is available on cloud which gives the flexibility to report from anywhere. This type of systems can potentially reduce your investments and recurring bandwidth expenditure by up to 30%.

Timing

Regardless of the fact that whether you are switching to a new system or a first-time buyer of RIS-PACS, it is the timing which is most important. The transition should be such that the normal operations are not affected. You can also go for a trial run for about a month so that your team is well familiarized with the software. RADSpa offers free trial to most of its prospects after properly assessing the seriousness of the customer.  So, go on, and go for your new system to leapfrog your facility to an integrated and AI-Enabled RIS-PACS environment.

09 Oct 2018

Unlock productivity, quality and communication with radiology workflow orchestration

Radiology exams are typically categorized as Stroke Cases, STAT cases, Trauma cases, Emergency Radiology, Inpatient, Outpatient and ICU cases etc. A radiologist’s workflow dashboard therefore must be organized in a manner that s/he has access to all vital information with the click of a button. But, it is easier said than done!

With increased accessibility and affordability of imaging modality machines and also due to incessant endeavors of modality manufacturers and PACS companies to provide precise imaging solution, there has been a quantum jump in the number of exams to be read. Further, the advent and availability of newer modality machines has also created the need for subspecialists readings.  A radiologist dashboard is now no less than a cross-word puzzle. What is most affected are the radiologist’s productivity, quality of work, communication between different stakeholders and the overall viability of running an imaging facility.

To overcome these challenges, companies are creating workflow orchestrators. Workflow Orchestrator is a mechanism for automatically matching imaging scans with a radiologist profile in the radiologist service provider environment. So, instead of radiologists spending their precious time figuring out which scan to read, the scans look for a perfect radiologist to read them.  Workflow Orchestrator further mines for exams in terms of priority or SLA (service level agreement), right sub-specialty and the best relationships and accordingly populates them in the worklist of the relevant radiologists for their appropriate response.

RIS-PACS with Workflow Orchestration lends itself in enhancing productivity, quality and communication.  With the implementation of intelligent tools such as Workflow Orchestration, the exams are exposed to a broader audience as time goes by. To begin with, the exams are exposed to the most suited radiologists, ones that have the best expertise and the best relationship to read that exam.

The Workflow Orchestrator also ensures that all available subspecialists are taken into the fold if a particular exam is not read or taken up quickly enough. The orchestrator delivers incalculable augmentation where quality KPI is concerned. The software also organizes exams not just by clinical but also by business priorities. The most crucial exams can be seen on top followed by the emergency and STAT exams, right after that comes inpatient exams, and then outpatient exams. Each exam is tagged by the intelligent software by the SLA so the time remaining to read each exam can be seen easily.

The productivity of the radiologists can be seen clearly from the personal radiologist dashboard. Apart from other features, there is also a break glass mechanism so that if a radiologist chooses to read out of order, the system will ask for a reason to do so. With integrated communication tools such as chat or instant messaging and more, the orchestrator’s software allows radiologists and referring physicians to easily share context of exams with each other and even ask for a specific exam to be reviewed.  The workflow orchestrator lets radiologists have the right tools to manage inaccurate exams and enhance productivity.

The Workflow Orchestrator helps direct imaging exams first to suitable clinical subspecialists, and then it makes sure that the exams are made available to other radiologists as needed to satisfy desired turnaround times. Exams also can be allocated to specific radiologists according to a referring physician’s preference and existing affiliations with hospitals or healthcare facilities. The platform’s workload balancing function can optimize reporting times.

RADSpa’s Workflow Orchestrator is one such value-added capability in the ever-evolving healthcare delivery paradigm.

  • It takes care of enhanced productivity by aligning demand with supply.Dynamic assignment automatically accelerates and assigns studies to the most appropriate, available radiologists. There is better communication through associated tools and automated notifications.

 

  • With a universal worklist, the orchestrator incorporates quality and interpretations tasks in one place. Efficiency is improved by contributing to quicker turnaround times and reduced length of stay.

When a study was conducted to see the impact of RADSpa’s Workflow Orchestrator feature, the results were overwhelmingly positive.

  • Almost 85% of the radiologists agreed that RADSpa’s Workflow Orchestrator helped them to reduce the TATs and increase productivity.
  • Statistical analysis of 180 days of logs before and after automation indicated 35% improvement in overall TAT for emergency cases.
  • Radiologist productivity per case improved by 25% as every case is auto-validated for images prior it is assigned.
  • Exam Coordinators or the Assigners reported a massive 98% reduction in effort which used to go in manually eliminating errors, and thereby more time in hand for handling greater workloads.

Radiology Workflow Automation has positively impacted timely patient care specifically in Reporting Emergency cases and thereby saving lives.

  • Manual errors and allocation time is reduced by 98%, TAT is improved 35% and RAD’s productivity by 25%.
  • Zero error in case assignment to radiologists by the coordinators (assigners).
  • Radiologists receiving advance alert regarding their work list.
  • Notification to assigners regarding un-attended cases. This helped assigners to follow-up with the respective Radiologists or re-assign them to equivalent Radiologists.

This value-based care has helped radiologists achieve more and do much more. This increased cooperation between healthcare providers as well as professionals benefits all participants in the care continuum. Workflow Orchestrator is therefore a great productivity and quality boosting tool and promises to be an excellent tool for collaboration and communication.

  • It takes care of enhanced productivity by aligning demand with supplyDynamic assignment automatically accelerates and assigns studies to the most appropriate, available radiologists. There is better communication through associated tools and automated notifications.
  • With a universal worklist, the orchestrator incorporates quality and interpretations tasks in one place. Efficiency is improved by contributing to quicker turnaround times and reduced length of stay.

When a study was conducted to see the impact of RADSpa’s Concierge Automation feature, the results were overwhelmingly positive.

  • Almost 85% of the radiologists agreed that RADSpa’s Concierge Workflow automation helped them to reduce the TATs and increase productivity.
  • Statistical analysis of 180 days of logs before and after automation indicated 35% improvement in overall TAT for emergency cases.
  • Radiologist productivity per case improved by 25% as every case is auto-validated for images prior it is assigned.
  • Exam Coordinators or the Assigners reported a massive 98% reduction in effort which used to go in manually eliminating errors, and thereby more time in hand for handling greater workloads.

Radiology Workflow Automation has positively impacted timely patient care specifically in Reporting Emergency cases and thereby saving lives.

  • Manual errors and allocation time is reduced by 98%, TAT is improved 35% and RAD’s productivity by 25%.
  • Zero error in case assignment to radiologists by the coordinators (assigners).
  • Radiologists receiving advance alert regarding their work list.
  • Notification to assigners regarding un-attended cases. This helped assigners to follow-up with the respective Radiologists or re-assign them to equivalent Radiologists.

This value-based care has helped radiologists achieve more and do much more. This increased cooperation between healthcare providers as well as professionals benefits all participants in the care continuum. Workflow Orchestrator is therefore a great productivity and quality boosting tool and promises to be an excellent tool for collaboration and communication.