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Spring Framework has already made serious inroads as an integrated technology stack for building user-facing applications. Specifically, Spring Framework provides various tasks are geared around preparing data for further analysis and visualization. Angular Training. That is very interesting; you are a very skilled blogger. I have shared your website in my social networks! A very nice guide. I will definitely follow these tips. Thank you for sharing such detailed article. Project Management Apps.
Excellent post! One of my friends recently started developing an agile product development proposal. You are sharing a piece of nice information. It helped me. Through this article I get more knowledge about agile proposal development. Thanks for sharing very valuable information. The goal of this article isn't to portray a start to finish measure for rethinking; after all there are a lot of articles about that.
It is hoping to investigate, from a customer point of view, those parts of the "rethinking formula" that we know for a fact are frequently ignored or underestimated but then we accept are basic regarding conveying the necessary incentive all through the term of the agreement.
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Outsourcing development. Thank you for sharing such a useful article. I had a great time. This article was fantastic to read. Post a Comment. February 04, Two weeks ago, I posted an article that discussed how proposal management is in actuality project management.
I pointed out how our long-standing proposal best practices are Agile , and have been Agile long before Agile was the latest industry craze. I have been so pleased with the discussion that this article has sparked. I plan to build on some of these discussion points in a series of articles focused on how we can expand the application of Agile in our opportunity pursuit processes.
Last week I discussed the role of stakeholders and explored how we can better integrate stakeholders into the business development lifecycle. A Scrum is comprised of short iterations, called sprints, within which work is completed iteratively. In my calculations, a proposal response effort in actuality is a Scrum.
Sprints are a period—typically 1 — 4 weeks long—when the Agile development team produces the next increment of the product in our case, the proposal.
And following this logic, sprints are just the writing and development process that occurs between each color team review. As we mentioned last week, the Scrum comprises three key roles, which together make up the Scrum Team Proposal Team :. Scrum Master Proposal Manager : This is the leader responsible for daily stand-up meetings and tracking the overall progress of the product development. Development Team Proposal Development Team : The Proposal Development Team is a collection of individuals working together to deliver the requested and committed product proposal increments.
We believe this approach will offer guidance to individuals considering different strategies for regulating digital products and to individual and system-level decision-makers regarding widespread product adoption.
This approach could improve the quality and safety of digital health solutions by facilitating ongoing evaluation, an element of particular relevance for academic developers seeking to simultaneously create and evaluate digital products. Such an approach may also promote industry-academic partnerships to combine development with more rigorous product evaluation. Given the widespread use of digital health products, several approaches have been proposed for how best to combine research with development in the digital space.
One notable example is the IDEAS framework, which combines strategies from behavioral theory, design thinking, user-centered design, evaluation, and dissemination to develop a step, 4-stage process that can be utilized in the development of digital health interventions. In addition, in light of the particular challenges associated with implementing and reporting on online health interventions, including issues with blinding and capturing sufficient study details for replicability, in the CONSORT-EHEALTH checklist was developed.
This checklist acts as an extension of the CONSORT statement, which was developed to improve the reporting of randomized control trials. The E-HEALTH checklist adapts this approach to eHealth and mHealth interventions, recommending best practices for reporting and knowledge translation that accommodate the unique nature of digital health research. Recently, an assessment conducted by a working group organized by the Mobile World Capital Barcelona Foundation sought to explore existing mHealth assessment initiatives and their potential effectiveness.
The authors also recommend that all relevant stakeholders be engaged in a continuous, iterative evaluation process built on a common foundation of guidelines and recommendations. Coinciding with the development of these academic approaches to improved mHealth regulation and evaluation, governmental agencies have also been developing strategies to more effectively regulate digital health products. In the United States, the Food and Drug Administration FDA has conducted extensive work to balance the importance of rapid innovation with the need to regulate mHealth products that may be classified as medical devices.
In , non-binding recommendations were issued by the FDA to provide guidance to developers and manufacturers of mobile applications that would be considered medical devices and could present a risk to safety if they did not function as intended. More recently, it has been suggested that rather than regulating individual devices, eligible developers could qualify for pre-certification by demonstrating a track-record of high-quality products, allowing their digital solutions to undergo a faster and more streamlined evaluation process.
In Canada, efforts are also underway to develop new approaches for regulating digital health technologies. This addition is part of ongoing efforts on the part of Health Canada to improve the regulatory system currently in place for mHealth products. The primary challenge to the application of any evaluation framework is the potential perception from developers that resources should not be invested in research because such efforts will slow down innovation a perception that has also been acknowledged by the FDA At the same time, it will help developers to improve and continuously iterate their solutions based on research evidence.
The approaches described above recognize the uniqueness of the total product life cycle and the ongoing evolution of medical devices. This path to market is linear and typically not modifiable; if a product fails in early phase studies, there is usually no opportunity to make changes that would permit moving forward to later phase studies.
By contrast, the development of digital health products is non-linear. Dynamic and iterative approaches are required for a number of reasons. First, the speed at which consumer digital technology evolves necessitates a considerably faster development process than standard clinical interventions.
Second, linear evaluation processes to establish drug safety can take upwards of 10 years, while digital products can be iteratively enhanced and modified almost immediately following identification of system bugs and upon receipt of user feedback. Both of these elements can allow for a development and evaluation process that is much faster than the clinical trial approach used in pharmaceutical research.
The traditional four-phase pharmaceutical evaluation framework. Adapted from K. Sagitova, Watching clinical trials liability. Risk Futures. One common approach to digital product development is Agile Development Fig. Ideally, agile development emphasizes face-to-face collaboration 18 and interactions between developers and customers as the best mechanism to create effective solutions for the end-user.
However, in the development of mHealth products that present more than a minimal risk to users, as in the development of pharmaceuticals, safety and efficacy evaluations are required by regulatory agencies, necessitating a development process that supports such evaluations.
This methodology serves as a gating process, only allowing through products with sufficient evidence to support their use. Likewise, mHealth apps could benefit from a similar gating process. However, unlike pharmaceuticals, the gating process for mHealth apps can facilitate additional iteration of the product at each impasse, until the product either succeeds and progresses to the next phase or is deemed unviable and is retired.
Mobile products are also different from pharmaceuticals in that apps often have many features or components that can exist at different phases of development simultaneously, while individual components of a drug cannot usually be significantly altered during the pharmaceutical clinical trial process. This is especially true for complex mHealth products which may incorporate a broad set of features and interventions into a single platform. Finally, neither agile nor traditional pharmaceutical development fully incorporate methods that ensure a developed product is well-designed for the people who will use it.
Methods that do so are found in related approaches and traditions often grouped under labels such as user-centred design, human-centred design, user experience design, co-design, or design thinking. The aforementioned digital product regulation strategies proposed by academics and regulatory officials will be important components of the eventual success of the digital health space. As strategies for mHealth app regulation move toward legislation, we recommend a development approach that combines the agile development process with current methods used to evaluate pharmaceuticals.
We believe that this approach can help developers build better products while also preparing them to meet regulatory requirements. We propose a framework that applies a four-phase approach to mHealth product development and evaluation in order to produce high-quality apps that solve real problems while also being safe, effective, and commercializable.
Figure 3 presents our proposed lifecycle. This proposed framework incorporates a similar set of steps to those currently in use by the FDA in the approval of medical devices, 20 but modifies this approach in order to allow for continuous, iterative development.
Using a risk-based approach similar to that used by the FDA, many products will require only Phase 1 or Phase 2 evaluation, and for many products, individual elements of the product can be evaluated while an earlier version is already on the market.
For each phase, we have identified a set of sample gating questions that can facilitate the decision regarding whether a product should advance to the next stage in the development cycle.
These questions are not exhaustive, as certain questions will not be relevant in some cases while additional factors may need to be considered in other cases. Importantly, our approach promotes the development of high-quality, thoroughly-tested applications and is aligned with the workflows that have been built into app publishing platforms e. Sample Gating Questions: Does this problem actually require a digital platform or could it be solved with a simpler solution?
Do we have the expertise and resources we will need to be able to support the project through the process? In this stage, a challenge is identified, a product is envisioned, and a project is initiated.
Team members are identified, funding is secured, and initial requirements are established. The idea for the product is evaluated against other approaches to solving the identified problem.
The vision for the product is also evaluated based on its ability to attract funding and talent with which to undertake the project.
It is important that a long-term view is taken when evaluating whether the project will have sufficient resources to make it through the mHealth development and evaluation lifecycle. There would ideally also be an identified target market for the product so that financial sustainability for the project is conceivable.
Sample Gating Questions: Is it easy to use? Do people want to use it? Does it perform its intended purpose? Is it safe to use? Is it accessible to people at various levels of ability?
Do people enjoy using it? Once the project has reached the development phase, the first step is to develop and evaluate the user experience. While the design is being refined, development can begin, resulting in an initial functional prototype. This prototype then enters alpha testing, in which test engineers and project team members evaluate the functionality of the product to determine whether it performs its intended purpose.
This process helps to eliminate bugs and other critical issues. Early feedback from alpha testers may also inform the design of the product or new features, resulting in further design phase iteration cycles. It is also during this phase that key assessments are performed to determine whether the product is technically secure and aligned with privacy and accessibility standards.
For the former, it is typical to perform threat risk assessments, privacy impact assessments, and technical vulnerability assessments. Sample Gating Questions: Will people actually use it? Does it meet the needs of the user? Is this approach feasible and acceptable?
Can it be implemented in its intended context? Is there sufficient face validity for this product to solve the challenge at hand? Once a functional prototype is developed, mHealth products can be tested in cohorts of external users, such as patients or members of the public.
This beta testing seeks to further determine in conjunction with data from alpha testing whether the developed prototype meets the needs of users in ways that will lead to sustained adoption. Here, the acceptability and accessibility of the product can be ascertained and evaluated against patient demographics age, sex, gender, education, literacy, sociodemographic status, health status, technology readiness 24 , 25 in order to identify any equity issues or barriers to access.
This creates an opportunity for evaluation using feedback from users or more formal evaluations based on surveys, interviews, focus groups, and analytics data. A successfully-tested beta version of the product may be considered for clinical trial study designs in order to generate evidence that the product solves the clinical problem for which it was originally designed.
A product that meets this characterization is often classified as a medical device, and, in many countries, is thus subject to regulatory requirements that govern its path to market. Novel study designs may also be better suited to evaluating mHealth products than standard randomized trials. For example, adaptive research designs may be particularly useful in evaluating multi-faceted interventions such as mHealth products where the functionality can be initially disaggregated and then combined based on the proven effectiveness of each individual component.
As in the other phases, user feedback and the results of formal evaluations can be fed back into the iteration process to improve the product. Can it be further improved? Post-market surveillance is standard practice for monitoring the safety of a pharmaceutical drug or medical device after it has been released to the market. This holds true for mHealth products as well. Once a product is available, users will continue to generate feedback on an ongoing basis and will expect this feedback to be incorporated into the product.
Services such as Google Analytics, app download and use statistics, or within-app tracking can provide an in-depth understanding of how and how much a product is being used in a way that is not available for traditional pharmaceutical products. While products are in the post-market surveillance phase, the health landscape, technology, and market will all continue to change, requiring continual evaluation of whether the product is still 1 relevant, useful, and being used; 2 safe to use; and 3 effective both clinically and technologically.
Changes in technology will inevitably require frequent iteration of the application so that it can continue to function. The standard approach to the evaluation of pharmaceutical products has important limitations when applied to the flexible approach characteristic to the development of many digital products.
As such, this approach may potentially deter the efforts to properly evaluate mHealth products as developers, scientists, and health care providers believe that the timelines and approach are not practical. An iterative approach to research that permits more flexibility, rapid evaluation, and changing protocols as technology changes may encourage more evaluations of digital products. Our proposed framework builds on previous strategies to promote improved regulation and evaluation of these products by offering a common set of gating questions and best practices for continuous iteration and ongoing improvement of mHealth solutions.
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