How is Blue Label Labs different from its competitors?

First, we live and breathe cutting-edge/bleeding-edge technology, so your app will similarly be cutting-edge/bleeding edge with a long “shelf-life”. Second, with a perfect mix of local, domestic and international talent you are guaranteed to get the optimal mix of a high-quality product and a fair price. Third, you will be assigned a dedicated Program Manager (PM) after we’ve established a contract who will be your single point-person for all of your needs and questions. This PM will stay with you for the duration of your relationship with Blue Label Labs and is your conduit to all of the resources we have to offer, thus streamlining your communication and preventing you from having to repeat your message to multiple resources or play air traffic control. Our PMs are the best in the business and we’d be happy to introduce you to a projected PM (and project team) once we’ve got an estimate on the table to discuss. Fourth, the size of Blue Label Labs team (now 64 people strong) means you don’t have to worry about the “single point of failure” issue that exists at smaller shops of just one or two developers, nor the burden paying for the high overhead cost associated with larger shops. Fifth, we have a stronger focus on design than most other shops. We split our design team into two specific functions—Product/User Experience and User Interface. It’s a rare unicorn designer that is good at both thinking through flow and product decisions, as well as branding, colors, logos and overall User Interface. To that end, each project team has both a UX Designer and UI Designer staffed to ensure top notch design. Sixth, with over 7 years of operation and over 250 apps completed, we have both the experience and extensive re-usable code base to ensure your app is built as efficiently and as inexpensively as possible. Seventh, our QA and Testing methodology is rigorous and as important to us as the actual development—meaning your app will be as bug free as is possible. We have a dedicated QA Engineer staffed on every project. This engineer is not the original author of the code ensuring the highest quality results from the QA process. Please see the below sections for more details.

How does Blue Label Labs work with clients?

Blue Label Labs Labs begins most projects with a Discovery, Planning & Design Phase (Phase One). First, we determine the proper technologies and development schedule. Second, the Design teams inherit the User Stories that were drafted during the sales process. User Stories are simple one-liners that outline the activities your users will need to be able to accomplish within the app. These User Stories then get grouped together into meaningful features and feature sets. The Design teams work with the client to finalize the User Stories. Third, our design team sets out creating greyscale wireframes to illustrate how a user will move through the app (i.e., the user experience, UX). Fourth, we transition to full color illustrations/designs that have the final look and feel of the app (i.e., the user interface, UI). Fifth, the app designs are then uploaded into a prototyping platform called Invision that allows our team to create tappable and swipeable “hotspots” so that you can show the app on your phone or via a mocked-up phone in a web browser. At the same time, we draft a Functional Specification document that details the technical hows and whys of the project for the development team. Once that work is complete, we them move on to the Development Phase (Phase Two). The Agile development/engineering team works hand-in-hand with the Program Manager and follows the wireframes and the Functional Specifications to build the app. Our first development goal is the First Deliverable milestone—we call this D1; this is a highly functional build of the app that contains a subset of features agreed upon by Blue Label Labs and the client. We then begin an iterative process of finalizing the remaining features. At the same time, a QA Team builds a full test plan for the app. The QA Team continually performs functional and regression testing on the app, reporting issues to the Project Manager. Learn more about our process here.

How long does it take to complete the average app?

Typically, for our average 4 to 5-month project, the Phase One: Discovery & Planning and Design lasts for approximately 4 to 6 weeks, with Phase Two: Development and Testing Phase occupying the remaining 3 to 4 months. At the end of the Phase Two, the final app is prepared for Deployment. Deployment involves moving any web services and server side components to a production environment and submitting the app to the relevant app store(s).

How much does the average app cost?

If we were in full-swing on a new project, a client can estimate a cost of between $10,000 and $30,000 per two-week sprint ($20,000 to $60,000 per month) for the effort—typically billed bi-weekly. If Blue Label Labs is handling everything from Discovery, Planning & Design through to Deployment in an app store, total app costs average about $120,000 for one “platform”–iOS, Android, Web, etc. That said, it very much depends on the complexity of the design and development required for each individual app, we’ve completed full apps at costs of between $50,000 (a bare-bones, simple MVP/prototype) and $2,000,000 (a full featured, enterprise apps). We provide free, no commitment estimates to clients. After the app is submitted to an app store(s) or pushed live on the web, the Blue Label Labs team monitors the app store and customer reviews and deals with any issues, questions, delays or approvals that arise. We have a great track record with app submissions and make sure that the app submitted is highly likely to be approved without issue. Post approval, a maintenance agreement can be put into place to cover and small issues, minor app edits (e.g., color, image or text changes) and any bugs that might linger. At the end of the project, we will transfer all source code and project files to you and you will remain the sole owner of all IP in the app. After that time, we provide our services at an hourly rate of $120/hour for ad-hoc updates or at an hourly rate of $100/hour for a mutually agreed upon set number of hours in a 6-month retainer. The monthly maintenance cost for the average app is $2,000/month: in other words, a retainer of 20 hours per month at $100 per hour equals $2,000/month and guarantees expedited service vs. ad-hoc requests.

What is the difference between a Native App, a Hybrid App and an HTML5 App?

Native App: A Native App is an app written for a specific platform like iOS or Android—in other words, the app is written in the coding language used for development on that specific platform (Objective-C or Swift for iOS and Java for Android). When you build a Native App, you get access to all the hardware features exposed by the native code APIs and SDKs. For example, Apple iOS Push Notifications are one example of a feature that cannot be supported by an HTML5 App. The graphics and user interface of a Native App are far superior to any Hybrid or HTML5 app. You would choose this option, if you want to use the user interface components from Apple’s proprietary user interface libraries (i.e., the usability is better); you want full device hardware access—cameras, microphone, and geo-location; you want peak performance with no lag; you want users to be able to access the app off-line (i.e., without Internet access); you want access to push notifications and in-app purchase; and you want your app to de discoverable in the app store. On the downside, your code is less portable across operating systems and it is often the most expensive development option. It is our recommendation that if you plan to start a true, revenue generating, app-based business, this is the only viable option. Hybrid App: A Hybrid App is a form of web app that is deployed to a native platform like an iPhone or Android phone inside a native shell. This shell is usually little more than a web browser view (to display the HTML5 content) and some other hooks to allow your web app to potentially access some more hardware features that are not available inside a typical mobile web browser—e.g., push notification and in-app purchases. It improves code portability because if you want to port your app to another platform, you only need a native shell on that other platform to run it, the HTML5 content of the app is directly portable. These shells can be hand written, but can also be generated automatically by tools in the marketplace like React Native, PhoneGap, Cordova or Xamarin. These tools allow a developer to push the app out to multiple platforms (e.g., iOS, Android, Windows Mobile) quickly by generating the shell and packages required to do so automatically. This sounds powerful, and it is, but clearly creators of these third-party platforms have a lot of configurations and hardware to support, and thus, the solutions do not always work the same across all devices, and in practice, testing and hacking of special cases will be required by the developer to get proper functionality. You would choose this option if you want a balance between cost and usability; you want access to some (but not all) of the phone’s native APIs/SDKs and hardware; you want to be able to quickly deploy across multiple device types; and you’re not worried about high-end graphics. On the downside, because these third-party hybrid platforms (e.g., React Native, PhoneGap and Xamarin) need to support so many device types there are always implementation and usability issues to workout. In addition, you will only have access to the features of a new operating system 6+ months AFTER it is released by Apple, Google or Microsoft. In this way, your app will never be able to cutting-edge technology. While we are fully capable of building Hybrid Apps, it is our recommendation that this option is only viable for simple, lo-fi apps that are heavy on text and images, but don’t need much in the way of functionality or user interface. An HTML5 Web App: An HTML5 app is essentially a website with JavaScript code written to allow the app to perform dynamically, as opposed to a static website that you need to refresh to see the changes. It works interactively to make it feel like an app, but it is actually running in a web browser. It is essentially a website, which will support multiple viewports or screen sizes so that it works well on mobile. Because it is running in a browser, it is confined to what is possible within a mobile web browser. You would choose this option if you want to support multiple platforms with the same app/codebase; you want to deploy it on the web; you want the widest possible support across multiple device operating systems and manufacturers; and you want to be able to update your source files on your server and have them immediately deployed to all devices (i.e., removing the need for the app approval process). On the downside, your app is not discoverable in the app stores; it will never look and feel like a true mobile app; and you will have limited access to some of the software and hardware functionality of the phone (e.g., push notifications and cameras). It is our recommendation, that this option is only viable for view-only content where users are not expected to interact in any meaningful way.

Has Blue Label Labs ever transitioned an app the firm has built to a client’s internal development team? What is the typical process and how long does it usually take? Is there a fee for this?

Quite often Blue Label Labs transitions an app to a client’s in-house development team. As part of our regular transition for any client, we transfer all functional specs, wireframes, UI design resources, screen flow maps, passwords/certificates/credentials and source code to the client. We also have extensive experience working in tandem with a client’s existing engineering team. For example, Blue Label Labs will build the front-end experience of an app on top of a client’s existing backend web service and databases. These transitions are the quickest, averaging only a few days, since the Blue Label Labs team and the client team have already been working hand-in-hand for months. If we are handing over a complete project with no prior engagement with the client’s development team, then the transition can take a little longer depending on the support needed. This can range from a few days to a couple weeks. The transition is typically free of charge unless engineering resources are needed to facilitate the transition or the Program Manager is required to spend more than a week on the transition and training. We’ve even helped companies to interview potential new technical team members—e.g., developers and CTOs.

How does Blue Label Labs provide training to a client’s development team so that they could make app enhancements and how much would that training cost?

Along with all the project documentation and support outlined in the answer to the question above, we are happy to provide hands-on training to in-house developers/team members as part of the transition. There is typically no extra charge for this if only a few hours are required. If ongoing training is necessary, for example an in-house developer is not familiar with app development and requires a crash course, then we can offer our services at our hourly rate of $120/hour for training. We’ve even aided our partners in their hiring of their own technical/development team if/when the time is right.

How many designers and developers does Blue Label Labs have on staff? How many work on each client project? Where is the team located? Can the client talk directly to whomever will work on the app?

The Blue Label Labs team is comprised of 64 individuals across its UX Design/Product, UI Design, Development, Program Management, Quality Assurance, Sales, Marketing and Leadership teams. We have 6 Designers, 10 Program Managers, 35 Developers, 3 App Marketers—the remainder of the team is comprised of the Sales, Marketing, Operations & Leadership Teams. Depending on the size of the project, a team of at least 7 Blue Label Labs staffers will work on your project: 1 Program Manager, 1 UX Designer, 1 UI Designer, 1 Technical Architect, 1 Front-End Developer, 1 Back-End Developer, and 1 Quality Assurance Engineer—in addition to the technical and strategic oversight provided by Blue Label Labs leadership. The majority of our Design and Program Manager teams is based in New York City, Seattle and San Francisco areas. The Developers and Quality Assurance Testers are also based in the aforementioned cities, in addition to India-based team members. The Development, Design and QA Teams are managed directly by the Program Manager. The Program Manager is your primary point of contact and the liaison across all other Blue Label Labs team members associated with your project. That said, clients are welcome to speak directly with any individual team member as is needed.

Are projects priced based on “time-and-material” (i.e., hourly) estimate or a “fixed-price” quote?

Projects are priced on a “time-and-material” basis. With 7 years and 250+ apps of experience to our credit, we are able to produce very accurate estimates. We do our best to stay within budget or provide you ample warning if we think we may exceed our initial estimate so we can coordinate how to move forward together with you. Prior client references can vouch for the accuracy of our estimates and can be provided to you upon request.

Is Blue Label Labs able to guarantee that our app will be published in an app store?

Unfortunately, no application can be guaranteed for app store approval. However, Blue Label Labs has successfully built and deployed over 250 apps for the Google Play and Apple iTunes stores. We have a solid understanding and insight into what these stores will typically approve or disapprove of. We will warn you well in advance if any particular aspect of you project poses an approval risk. We have had a handful of instances where an app store has rejected an app for publication; not due to technical issues, but due to legal/business/terms of use issues; however, we successfully appealed ALL of these rejections and these very same apps are now in the app store for download today. We led these appeals on behalf of our clients at no extra charge. If your app is rejected due to technical reasons, we will make all necessary corrections needed to get approval at no extra charge. We are happy to connect you with some of our clients who did face some app store pushback to tell you about the rejection and our successful appeal.

What is Blue Label Labs’ policy regarding correcting defects and publishing an update in the app store?

We provide our services at a blended hourly rate of $120/hour for ad-hoc updates or at blended hourly rate of $100/hour at a mutually agreed upon set number of hours over a 6-month retainer. For example, a retainer of 20 hours a month for $2,000/month guarantees expedited service vs. ad-hoc requests. Ad-hoc requests are handled on a first come, first serve basis across all of our clients and development is based on our team’s earliest availability. The monthly retainer of hours functions much like an extension of the warranty period; issues are addressed within 24-48 hours and development will start as soon as the scope of the issue is defined. For those clients wanting a guaranteed 24 to 48-hour turnaround time on maintenance issues, a 6-month retainer is suggested.

What level of Quality Assurance is included and provided by you in your proposal?

A Quality Assurance (QA) Engineer is assigned to every project and builds a custom test plan for every project during the Discovery, Planning & Design Phase. During the Development & Testing Phase the QA Engineer continually tests the app using functional and regression testing. We test on a wide array of physical devices as needed for a given project. If we are building a backend web service and databases as part of the project, we will also have a set of automated unit tests that are run regularly to verify functionality.

What is Blue Label Labs’ quality assurance (QA) and testing methodology?

We believe that Blue Label Labs’ QA and testing methodology is part of our competitive differentiation. The fact that we dedicate resources to solely this function is something that sets us apart from other development shops for whom testing is simply an afterthought. At Blue Label Labs, QA is handled at all levels of development. There are generally 3 layers of QA/testing that happens for every project: 1.) Internal Development Team Testing Each Development Team has an internal QA Tester along with the Developer Lead who perform basic validation on bug fixes prior to builds being released to the broader Project Manager and QA team. Their validation is to ensure that items within JIRA, which we use alongside Trello, to coordinate team efforts and communicate with clients—are properly remedied according to their descriptions prior to “checking-in” or committing code. When items are resolved by the Development Team they are pulled into the “Testing Done by Dev Team” stack of Trello cards and/or within JIRA. When developing new projects, the Blue Label Labs Development Team will also be responsible for creating “unit tests” for our code so that we can quickly run a basic set of verifications. The dev team does the majority of their testing using iOS and Android app simulators. 2.) Dedicated QA Engineer Each project has a dedicated QA Engineer who sits independently from the Development Team who is responsible for: a.) Drafting a milestone based test plan which outlines a list of black box scenarios to verify and the expected results; b.) Performing smoke and full test pass runs against weekly and milestone builds; c.) Verifying and closing bugs that the Development Team has marked as complete; d.) Working with the Development Team to report issues and regressions; and d.) The QA Engineer takes items from the “Testing Done by Dev Team” Trello stack and verifies whether it is actually fixed. If it is, the Trello card is moved to the “Done (Verified)” pile, or sent back to the “Weekly Priorities” or “Product Backlog” stacks, as appropriate. The QA Engineer will generally perform their tests on 2-3 devices, depending on project requirements. 3.) Project Manager (PM) Testing The final QA gate is the PM who is responsible for quality of the entire product. They will also work with the QA Engineer to verify items have been fixed properly in addition to triaging new issues coming in from the client and the QA Engineer. The PM will appropriately schedule issues to be resolved based on their severity and importance. The PM’s testing is done on actual devices.

Can Blue Label Labs help me with Marketing and PR?

Absolutely. We aim to be your full-service app partner. Our Marketing & PR Offering is designed to help you launch your app and gain marketing exposure. Learn more about our Marketing & PR Offering here.

Generative AI

Revolutionizing Healthcare: The Opportunity for Generative AI in Clinical Care

The healthcare industry, in particular hospitals, clinics and physician groups, are continuously seeking innovative ways to improve patient care and streamline operations. Generative AI, a rapidly advancing field within Artificial Intelligence (AI), holds tremendous potential to revolutionize clinical healthcare by enhancing patient satisfaction and increasing efficiency in various aspects of clinical operations.

The application of AI to clinical medicine is nothing new; for years, significant effort has been made to use machine and deep learning AI to help with diagnoses and treatment of patients. While the utopian vision of an all-seeing AI that can spot cancers in a CT scan that a physician might miss is alluring, in practice, using AI to diagnose and treat patients is still fraught with the risk of misdiagnosis and its potential consequences.

Rather than attempt to use AI to play the role of a physician, instead a much more practical application of AI in a clinic, is to leverage Large Language Models (LLM) it to put more information and power into the hands of a patient and to ease the tremendous administrative burden carried by physicians, nurses and clinical staff at hospitals and physician groups across the country. This blog post will explore practical ways to apply generative AI in a clinical setting today without having AI attempt to play the role of a physician.

Improving Patient Satisfaction through Generative AI-Assisted Self-Service Chatbots

One of the most significant challenges in healthcare is addressing patient dissatisfaction due to perceived neglect. Patients often feel that healthcare providers do not hear them or provide sufficient information about their treatments and medications. The rapid adoption of patient portals since 2020, in particular patient messaging has ironically contributed to increased dissatisfaction as the increased volume of patient messages results in additional workload on physicians and support staff, which leads to delays in responses and increased patient dissatisfaction.

A study by the American Journal of Family Medicine indicated that non-urgent messages, such as those related to administrative tasks or simple clinical questions, often make up the majority of patient portal interactions. Today the burden to answer these falls onto already overstretched clinical staff.

Generative AI chatbots integrated into patient portals offer a powerful solution to this problem. These chatbots can provide patients with instant answers to common questions about their treatments and medications without requiring a physician’s intervention. For example, Google’s recently introduced research AI system, AMI (Articulare Medical Intelligence Explorer), has demonstrated diagnostic accuracy, empathy, and helpful explanations on par with or even surpassing real primary care clinicians in simulated text consultations with a generative AI powered chatbot.

GenAI Chatbots Can Help Patients Interpret Lab Results

Generative AI can also provide context and explanations for lab results published on patient portals. For instance, a fertility clinic might publish an Anti-Mullerian Hormone (AMH) measurement for a patient to view, with no more than a simple table to help the patient interpret the result. However, almost immediately a patient will likely want to know “is that high?”, “is that low?”, “what does that mean?!” Off-the-shelf open source LLMs can easily answer these questions without requiring any sensitive patient data or integrations into an Electronic Health Records (EHR) system, as this is general-purpose knowledge.

Provide After Hours Patient Assistance In Lieu of the On-Call Doctor

Moreover, generative AI can offer after-hours support for patients seeking advice on symptoms and general questions about medications. Today, a patient would likely need to call the on-call number for their clinic, only to then have to wait by the phone for the on-call nurse or physician to call them back. By empowering patients through a self-service chat interface, clinics can improve patient satisfaction by providing the information they need promptly and drastically reduce the inquires fielded by their on-call nurses and physicians. Finally, reducing on-call volume significantly boosts clinical employee satisfaction because fewer physicians and nurses need to be on-call at any given time.

Translate Patient Instructions to their Native Language

Another benefit of generative AI in healthcare is its ability to translate lab work, progress notes, and patient instructions into the patient’s native language. A study has shown that patients who require an interpreter or do not receive care in their preferred language report lower satisfaction levels. Generative AI’s exceptional language translation capabilities can eliminate the need for translators and reduce confusion for patients who are not fluent in the language of their clinical team. The use of generative AI for translation is another low-risk application of the technology in the clinical setting.

Generative AI Can Increase the Efficiency of Clinical Operations

Generative AI can significantly increase the efficiency of clinical operations by automating various tasks. One such application is generating consultation notes, referral letters, and progress notes from transcripts. A study conducted in 2016 found that Physicians spend roughly 50% of their time on EHR tasks and desk work, with only 27% of their time dedicated to patient care. Further, a study of 4,938 progress notes showed that the average length of 886 words and a significant portion of these notes were highly similar from one to the other due to practices like copy-pasting, which can introduce risks and reduce the usefulness of the notes.

Automate the Creation of Progress Notes and Referral Letters

The rise of telemedicine after the 2020 pandemic has led to a greater number of physicians conducting consultations over Zoom or other remote solutions. These services today produce AI generated transcripts and summaries of these calls. Clinics can largely automate the production of referral letters, progress notes, and other routine documentation by using the transcripts of these meetings coupled with a generative AI agent. Generative AI can eliminate a substantial time burden on physicians and reduce errors by automating the process of creating these documents, which currently rely on shortcuts to ease the burden.

Streamline Insurance Reimbursements and Prior Authorization Workflows

Another area where generative AI can streamline operations is insurance reimbursements and prior authorizations. The process of obtaining prior authorizations is costly and time-consuming for healthcare providers. A 17-hospital system reported spending $11 million annually to comply with prior authorization requirements, while a 355-bed psychiatric facility needed 24 full-time staff members solely to manage authorizations. Generative AI tools can ease this burden by automatically mapping and suggesting treatment codes and error-checking to ensure proper codes are applied. Additionally, hybrid human-AI workflows can semi-automate the process of submitting and obtaining prior authorization from insurance companies by using Robotic Process Automation (RPA) tools in combination with large language models and minimal human review.

Self-Service Appointment Setting and Patient Onboarding

Generative AI can also streamline the patient appointment booking and onboarding experience. An AI-powered booking tool can assist patients in navigating the calendars of their clinics and physicians to book follow-up appointments and consultations. This can significantly reduce the costs associated with medical answering services, which can range from $0.96 to $1.84 per call.

Risks & Challenges to the Adoption of Generative AI In Clinics and Hospitals

While generative AI offers numerous benefits to clinical healthcare, there are challenges to its adoption. Regulatory and privacy concerns are paramount in the healthcare industry. Clinical IT systems must protect patient care data, eliminating the use of third-party, cloud-hosted generative AI platforms like ChatGPT. To deploy generative AI solutions in clinical operations, healthcare providers will likely need to self-host open-source models like Llama or Mistral within their clinical IT systems.

The sensitivity of patient data requires careful consideration of any integration between an AI system and an EHR system. For all of the example use cases of generative AI solutions discussed above, none of them require access to any specific patient medical records or integration into an EHR data feed. While this type of integration would make the tools richer and more impactful, deploying them without any integration into an EHR system can still provide substantial patient value and clinical efficiency.

Another challenge is the risk of an AI disseminating misinformation. Safeguards must be implemented through fine-tuning or other means to ensure that deployed AIs do not provide incorrect advice or misinform patients when answering their questions. While these measures are effective, the risk of the AI potentially saying something incorrect cannot be fully eliminated. Therefore, any deployment of a generative AI solution within a clinical environment needs to include appropriate terms of use and protections to guard against inaccuracies disseminated by an AI tool.

Conclusion

Generative AI has the potential to revolutionize clinical healthcare by improving patient satisfaction and increasing operational efficiency. From AI-assisted self-service for patient assistance and consultation to streamlining clinical operations, generative AI can significantly benefit both patients and healthcare providers. However, healthcare providers must approach the adoption of generative AI cautiously, considering regulatory and privacy concerns and the risk of misinformation. As healthcare providers navigate these challenges and explore the implementation of generative AI solutions, they can unlock a new era of patient-centric care and optimized clinical operations.

Bobby Gill

Co-Founder & Chief Architect at BlueLabel | + posts

Bobby Gill is the co-founder and Chief Architect of BlueLabel, an award winning digital product agency headquartered in New York. With over two decades of experience in software development, he is a seasoned full-stack engineer, software architect, and AI practitioner. Bobby currently leads the BlueLabel AI/ML practice, where he is leading a team of engineers operationalizing the transformational capabilities of generative AI within BlueLabel and for a number of enterprise clients.

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