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  1. A Bad Time to Be Average
  2. What is a deployment diagram?
  3. How to incorporate enterprise legacy systems into your digital strategy
  4. Our Team - Digital Deployment

Heather is our Customer Success Manager. She grew up in a family of entrepreneurs, which led to a passion for building strong business relationships and for educating customers in a way that makes learning smooth and easy. Her goal is to empower communication, stay connected with her community, and be a welcoming, supportive resource for all Digital Deployment customers. Taking feature requests and ideas from our support and management teams and turning them into reality is the name of his game.

With the amazing Streamline team, he loves taking business problems and producing elegant, easy to use solutions with state of the art technology.

A Bad Time to Be Average

She leads client services through the demonstration, discovery, and development phases, while providing direct support along the way. By working first-hand with clients, Maria hopes to increase their success by understanding the challenges faced and how Streamline can fix them.

Rocky Martin is an accomplished relationship builder with a strong commitment to helping clients succeed. With over 10 years of relationship sales, he has a passion for customer service and offers the kind of leadership and consultative expertise that Digital Deployment clients demand. Jason is our lead frontend developer, making our client websites look spectacular and always keeping up with the cool new things in our industry. His passion lies in the details of a design, always working his hardest to make it a reality in the digital space. With his focus on details, he enjoys building computers from scratch and organizing all the cables and cords in the office.

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After work and on the weekends you can find Jason hanging with his two awesome kids, watching a movie, playing a round of golf, or zipping around in his speedy car. Ginger works hard to ensure all financial and legal matters of Digital Deployment are in order. For more than 20 years Frank has worked at the intersection of marketing, innovation and technology.

What is a deployment diagram?

Frank and his team began working with Streamline in early and he provides marketing strategy and marketing project management for the Streamline team at Digital Deployment. Stephen Potenza is our full-stack engineer who brings almost 20 years of experience developing web-based applications.

In addition to his technical expertise, he has an eye for design and brings an empathetic approach to user interface architecture. By developing an understanding of our customers, Stephen hopes to continually refine Streamline and tailor the product to their explicit and implicit needs.

The approach was felt to be most appropriate considering the cross-collaborative nature of the research which required the input of various types of expertise in the health technology field, from both research and industry, throughout the design process of the evaluation framework. Two industry collaborators were involved at different points throughout the process.

In both cases, selection of human performance measurement technologies was a critical issue for their business, one company being involved in telehealth service provision, and the other being a clinical research organisation. Figure 2 illustrates the main project stages including the point at which each stakeholder group was involved. The initial phase of the project aimed to define the Device Search process step 2 in Results. Early iterations of this process were trialled by the researchers B. These searches were unstructured but did entail the formulation of keyword searches.

When all keyword sequences were saturated, the researchers reconvened to critically evaluate the process used. The core aspect to emerge from this early work was that although the process made sense in terms of formulating keyword sequences to identify potential devices, without the requirements of a specific use case, the web search findings were too expansive. For instance, a plethora of smart blood pressure monitors were identified, but without contextual information such as a set budget per device, there was no early mechanism to filter down the large number of devices garnered from the web search.

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Through further consensus, the researchers decided that hypothetical applications with specific requirements should be developed first, one academic in nature and one from a health technology industry perspective. Doing so would allow the researchers to assess the flexibility of the tool in relation to the diverse needs of potential end-users. Crucially, the specific application requirements would help focus the identification process while providing the device evaluation with a more purposeful direction.

A hypothetical academic application, concerning a diabetes self-monitoring study requiring the use of a smart glucometer, was then developed, forming the basis for the Requirements Definition process step 1 in Results. Ethical approval was obtained from the Ethics research committee at University College Dublin, Ireland.

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Verbal consent was obtained from participants prior to the commencement of workshops and expert consultations. During the workshop, the collaborators were presented with the hypothetical academic application use case.

Based on this example, they were then given the task of developing an industry-led application use case that reflected the requirements of a provider style study. The primary outcome of the workshop was the development of industry-led hypothetical use case namely a medication adherence programme, requiring the use of a smart pill adherence tracking device. The aim of this phase was to develop the specifications for the device evaluation template.

Each expert was invited to participate in a min brainstorming session with researchers B. The experts came from a variety of digital health backgrounds including biomedical, software and systems engineering, human factors, regulatory, clinical and digital health expertise. Each expert was provided with a copy of the alpha version at the beginning of the session. They were asked for their feedback regarding the domain content in the context of using it to evaluate a digital health and wellbeing device. Notes were taken by the researchers regarding the relevant points made by each expert.

Upon completing the feedback sessions, the notes gathered were collated and examined for patterns. As patterns were identified, they were cross-checked for consistency and compiled into iteration additions.

How to incorporate enterprise legacy systems into your digital strategy

The researchers then refined the domains and the alpha template was subjected to its first iteration. The aim of this phase was to develop the questions within each domain. The experts received a copy of the iterated template at the beginning of the session and asked for their feedback regarding the domains and questions there within.

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As the expert critiqued the iterated template, notes were taken, and afterwards collated and examined for patterns. If patterns were identified, they were cross-checked for consistency and compiled into iteration additions.

Our Team - Digital Deployment

The insights gathered informed the final iteration. The researchers now had a beta version of the template ready for testing. In this phase, the researchers B. To explain how the devices were chosen for the testing phase, it will be instructive to provide an example using the smart pill-box hypothetical use case.

The researchers followed the first two steps of the process: Requirements Definition and Device Search. Using the Google search engine, a search was conducted to identify potentially suitable devices. The researchers went 4 pages deep into the Google search engine 10 results displayed per page for each keyword permutation.

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In each case, the first 40 results were examined to search for relevant devices. Once new search combinations were not yielding any new device search information within the 40 results, the researchers concluded that saturation had been reached and ceased the search. A number of keyword permutation combinations were tested.

One researcher B. A record was not kept of the number of unique devices that were found using each search combination.


From this search, 21 devices were initially identified. All smartphone apps, connected blister packs and smart ingestible pills, totalling 5, were excluded since they were outside the scope of this medication adherence programme. A further two devices were excluded because they were not focussed on pill or tablet adherence monitoring. Another two devices were excluded because they were bound to a service that did not allow integration with external services.

The remaining 12 devices were subjected to the requirements comparison matrix. Based on this comparison, 9 devices were excluded because they did not meet one or more criteria or not enough information was available despite contacting manufacturing company and 3 devices were shortlisted as suitable to allocate to the evaluation template testing phase as seen in Table 7. The same process was followed by the researchers to determine the devices to be allocated to those testing the evaluation template based on the smart glucometer hypothetical use case. In total, 10 devices were identified of which 2 were found to be suitable for the testing phase.

For this phase, the aim was to finalise the device evaluation template in terms of its usability and general experience.