Top healthcare IT outsourcing companies in the USA

The first question that you should ask yourself before contacting the IT outsourcing company is “what billing model is the best fit for my project?”. If you are confused about choosing an outsourcing model from the Dedicated team vs. Fixed price vs. Time and Materials for your business idea, then welcome aboard!

In this article, we will compare these business models for your project. Let’s analyze each in detail and describe the advantages and disadvantages of 3 main IT outsourcing models.

Fixed price

The fixed-price agreement is a single-sum contract where the software development team must deliver the project within a predefined sum which is agreed by both parties. A client should be able to share his clear vision of the product with developers to ensure appropriate final results. This model requires the client to provide a detailed list of requirements for the project and all required developer documentation.

Pros of fixed price model:

• Clarity. Project requirements are agreed upon before signing the software development contract, as well as all the required developer documentation is specified beforehand.
• Accuracy. The project scope and time frames are known and discussed in advance, so the team can set the deadlines, and it is convenient to monitor the project progress.
• Autonomy. The development process is coordinated by a project manager, so the client’s participation isn’t necessary.

Cons of fixed price model:

• Preparation. The period is needed as all requirements for implementation and deadlines must be documented.
• Inflexibility. Any change in the scope of work would cause a change in the total cost of the project and this change would be compensated by the service provider’s end.
• Risks. If you don’t provide your requirements correctly, then the delivered product won’t be the same as expected.

When is recommended to use a fixed price model:

• Clear requirements and determined deadlines.
• Limited or fixed budget.
• MVP.
• Small and medium projects with limited project scope of work.

Time and Materials

Time and materials contract is absolutely different. This model is great suited for long-term projects with changing requirements, where the final requirements are not known in advance and can be changed on the go. This is a flexible approach to IT outsourcing, as the customer pays in smaller chunks for work accomplished during the billable hours. To say more, this pay-as-you-go model allows you to pay only for the work actually done. For example, for features delivered, milestones, etc.

Pros of Time and Materials model:

• A flexible approach. The customer can change the scope of work, requirements or add/drop features on the go to meet his business aims without thinking about the budget. This model perfectly combines with modern agile methodologies, for example with Scrum.
• Transparency. This model allows the customer to control the cost and concentrate on important elements of the project. The client pays only for the results actually delivered.
• Involvement. The client can monitor the process of the development of a certain work schedule in accordance with the expected results.

Cons of Time and Materials model:

• Budget and time. It is not always possible to estimate the budget in advance. It’s hard to predict when the product will be delivered or how much it will cost. This depends on the accuracy of the specifications or its changes in the process of work;
• Communications. To achieve a high-quality product, continuous communication with the team is necessary. It requires full-fledged involvement from your side, which includes spending much time in communication with the development team.

When is recommended to use Time and Materials model:

• Long and middle term projects with dynamic requirements;
• Project scope is not fully known;
• The customer wants the flexibility to modify the project scope.

Dedicated team

The Dedicated Team model is used to compensate for the lack of in-house IT expertise on mid-to-long-term projects. The billing is based on hourly rates of the developers, and they become a part of a team that is only concerned with the project and not engaged in any other tasks. The developers report directly to the client. However, the client is responsible for team management and control.

As an example, let’s say the client wants to develop software that is not in his team’s expertise, he can hire a developer or team who can do this. In this case, the client can outsource to an experienced team that can help him fulfill his customer’s needs by creating rich quality projects. This will enable the client to maintain stability between your team and the dedicated team.

Pros of Dedicated Team model:

• Control. The customer is provided full control and management of the team. Cooperation between the client and the team is very important because it allows for effective planning and evaluating the strengths and weaknesses of the work process.
• Development. When a team is focused on one project, it ensures the best results. The team has a full understanding of all project features and is dedicated to running the project smoothly.
• Progress. The ability to optimize the product is important for product growth. With the dedicated team, it is much easier.
• Reduced costs. The remote team solves many problems with the recruitment and hiring of staff. Plus, you always know the next month’s payments and taxes.

Cons of Dedicated Team model:

• Thoroughness. The client must consider process planning and task distribution for every member of the team.
• Engagement. You might have to invest more time in communication, discussion and software development.
• Graduality. Looking for the perfect candidate takes a lot of time and the client has to be involved in hiring team members.

When is recommended to use Dedicated Team model:

• For long-term IT projects with rapidly changing scopes.
• Adding more workforce to set up a strong development team.
• When you want to access cross-border expertise and knowledge sharing.

Conclusion

To sum up, every project provides the best results when it is managed according to the most suitable IT outsourcing model. Each software product development pricing model has its pros and cons. Choosing the best possible approach fully depends on the specifics of your project and expected results.

According to this, the first step is understanding your business model’s requirements. After determining your project’s needs, you can select the right outsourcing model and start with it.

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Hey, are you here to find a solution for a consolidated and easy-to-access “home” for your business information, which is usually transferred from different places, often unrelated to each other? Then, you probably need to think about creating a digital space where it will be integrated, cleaned, structured, and stored accordingly, for further use in your regular business operations. But what is this space? Let’s find it out right now.

What Is Data Warehousing?

In a nutshell, it is a repository where your business data comes from disparate sources, where it is brought to the proper quality, and where it is stored, providing individuals with the appropriate rights with easy and fast access to it. Typically, such repositories serve as one of the central components in automated analytical solutions, but, as practice shows, the range of their application can be much wider.

Key Components of a Data Warehouse

In general, its main components are considered to be the following:

• Sources, from which structured and unstructured information comes – these can be third-party databases, tables, systems, applications, etc.;
• Data Extraction, Transformation, and Loading (ETL) tools, which define scenarios for extracting, transforming, and loading the information;
• Data warehouse database, which is the main repository (usually in the form of a database management system, DBMS) with already prepared, i.e., cleaned and structured data, that can be used for analytics, reporting, and other business tasks without additional manipulation;
• Metadata repository, which includes the permissible data types and the rules according to which this data will be used;
• Query and reporting tools, which define algorithms for fast and unified access to data, as well as its analysis;
• Data mart, a subset of the data warehouse that is used for individual business tasks (this can imply, for example, marketing data warehouse design) which formation occurs either directly through the collection from disparate sources or pre-preparing within a consolidated space.

Core Principles of Data Warehouse Design

Now, let's talk about the main data warehouse design principles:

• A clear definition of business requirements and goals, as well as metrics that allow you to objectively assess the degree of their achievement;
• Understanding how information is integrated from multiple sources and what should be the unified format after its transformation;
• Choosing the right type of data modeling – these can be star schemas, snowflake schemas, fact tables, and so on;
• Choosing the right methods and data warehouse software to ensure the quality and consistency of information, in particular, the methods of cleansing, validation, and supplementing of data;
• Planning, scaling, and managing the performance through various methods of indexing, partitioning, compression, etc.;
• Choosing the right tools for metadata management to simplify and improve access to the information;
• Ensuring security and access based on policies and rules (usually, this is achieved through the implementation of advanced encryption algorithms, the introduction of access policies for different user groups, as well as providing reliable authentication and authorization methods);
• Implementing end-to-end monitoring for ensuring data quality and security, performance of processes occurring within the data warehouse, and so on.

Steps in Data Warehouse Design

In this section, we invite you to consider the key steps leading to a successful and agile data warehouse design.

Requirement Gathering

According to the principles to design a data warehouse we defined above, the key to effective data warehouse design is to gather business requirements and clear business goals that it should fulfill. It is also important to identify the requirements for security, scalability, and performance of the repository.

Data Modeling

This is not yet a practical stage, but it still requires the participation of specialists – in particular, it implies the identification of entities, their attributes, as well as possible relationships between them. After this, the most suitable type of DBMS implementation needs to be selected – for example, in the form of tables, columns, indexing, etc. After this, you have to make sure that the selected type performs all the tasks assigned to it according to the predetermined requirements.

ETL Process Design

We have already explained above what the ETL process means, and this stage actually involves choosing the right tools and scenarios for their use.

In particular, you will need to define methods for extracting information from disparate sources (these can be database queries, API calls, file transfers, etc.), methods for bringing data to a single format and ensuring its proper quality (since you will most likely have to deal with big data, there may be many inconsistencies), methods for aggregating data to create complex information structures, automation methods for bulk loading of data (this can be full or incremental loading, and so on) with the usage of temporary storage areas, methods for detecting and eliminating data errors, as well as methods for checking data for completeness and accuracy.

Database Schema Design

There are several well-known data warehouse design patterns, such as:

• Star, which has a fact table at its center and dimension tables associated with it around it;
• Snowflake, which is a more complex Star and also implies additional dimension tables that surround each base dimension table;
• Galaxy, which contains two fact tables and the dimension tables between them.

Data Integration

Now, you can start integrating the data using the previously defined ETL tools and technologies. At this step, you need to make sure that everything works as intended, and the data is transformed into the required unified format.

Data Storage Solutions

At this stage, you need to choose specific data storage solutions according to your requirements for the expected data volume, performance, scalability, and cost. Usually, the choice is made between relational databases, columnar databases, data lakes, and cloud data warehouse solutions.

Data Presentation Layer

Finally, to design data warehouse, you will need to understand what your data presentation layer will be – the layer at which end users will be able to seamlessly access the data and use it to solve specific business problems. This includes developing interfaces, dashboards, reports, and various data visualization tools.

Conclusion

Now that you have a clear guide to data warehouse design, you can begin implementing it with a full understanding of the principles and stages on which it is based. If you would like to delegate this comprehensive task to seasoned data warehouse development specialists, just contact us.

No matter how ambitious your goals are when you first think of creating a custom software solution, strict budget and deadline constraints can easily dash them. So, what should you do in this case?

Specifically, before your tech team starts implementing a healthtech solution, you can choose two different paths for them: native and cross-platform mobile app development. In the vast majority of cases, in this area, the second option can cover all the needs and requirements for the project without harming its critical aspects, such as usability, performance, reliability, etc. At the same time, you will be able to launch your product on the market faster and save your financial resources. 

However, such a development process is somewhat different from the one that precedes the launch of several native applications. Below, we'll cover how these differences can impact critical aspects of your project and share insights that help you fix them.

Best Practices for Cross-Platform Development in Healthcare

Since cross-platform app development involves adapting a healthcare solution to multiple platforms at once, it is important for the team to adhere to the following best practices to ensure the proper quality of the resulting solution.

Compliance and Security

The first thing you should probably start the development process for the healthcare industry is to ensure compliance with generally accepted standards and policies. The most common among them are HIPAA (Health Insurance Portability and Accountability Act) and GDPR (EU regulation aimed at giving citizens control over their personal data). Along with that, software engineers must use standard security mechanisms such as encryption, integration of secure connection certificates, etc. Ultimately, it is better to check the requirements for medical software development according to the legislation in force in a particular region – this way, you will not face any fines and bans.

User Experience (UX) Design

Now, let's talk about user experience in health apps – it should be smooth regardless of the platform they are running on. Since many healthcare mobile applications are positioned as an alternative to offline services from legally operating medical institutions, they must comply with accessibility rules that are described in detail in WCAG 2.0. These guidelines allow developers to implement seamless interaction with medtech solutions for people with all kinds of disabilities. Depending on the type of medical tasks assigned, you will need to ensure that your healthcare app UI/UX design meets WCAG 2.0 requirements to the appropriate level.

Performance Optimization

Nowadays, high performance is considered one of the key aspects ensuring the app’s survival in the market; however, in the healthcare sector, this parameter is much more critical since someone's life may depend on it. Indeed, if your digital solution involves an urgent call to a doctor, lags in its functioning may end tragically for some of the users. At the same time, it is believed that native applications work faster than those created in the process of cross-platform or hybrid app development. This is not true – such modern development tools as React Native, Flutter, Ionic, and many others allow teams to build software with complex business logic without reducing its speed. Of course, these frameworks will not handle resource-intensive gaming applications, but, most likely, this is not the original task. Whatever approach and technology stack you choose, your team involved in software development for healthcare will need to spend some time testing the application before launching and ensuring that it works equally effectively on all platforms.

Testing and Quality Assurance

Yes, we have already outlined the importance of this process above, but we will repeat it once again: no application can be launched for public access before it has passed a series of tests, both with the participation of the team itself and involving focus groups assembled from representatives of the target audience of your software. The most common types of testing are modular, integration, functional, acceptance, system, smoke, and so on. Each of these types takes place at a certain stage of development (and has to be performed on each platform separately), but the amount of code covered by test cases and the number of iterations will directly depend on the established deadlines. 

Integration

Finally, it is worth saying a few words about integrating your app with existing third-party products and services that your organization already uses. This is usually necessary to expand the functionality of the former and, in particular, to ensure seamless data transfer between applications. However, while the vast majority of modern custom healthcare solutions integrate via API, it is quite predictable that your team will face some issues if you use legacy software. For this, an additional middleware will have to be developed – it will take responsibility for converting data to the required format and back.

Conclusion

In general, as you may know, cross-platform development is cheaper than native development, because most of the code is reused between platforms, and you do not need to hire two separate teams to create native software for each of them (in particular iOS and Android). Moreover, with the right approach, frameworks such as Ionic allow you to build both mobile cross-platform and web applications, reusing most of the code, which, in turn, speeds up and reduces the cost of development for mobile and web platforms, respectively.

So, now, knowing the specifics of developing solutions using cross-platform app development tools, you will be better informed about how to ensure their proper quality and control each stage of their creation. However, if you would like to outsource this complex task without unnecessary doubts so as not to spend too much time on supervising, feel free to contact us.