AI project management and healthcare: preparing your resources for the coming revolution

AI project management and healthcare: preparing your resources for the coming revolution

Imagine the time savings your healthcare organization could achieve if pathology scans could be automatically assessed by a machine. Picture the cost savings if software could alert you to a health claim fraud. Or, think of the improved wellbeing of your patients if you could use risk scoring to highlight hazards to their health – and inform them of better lifestyle choices.

These are just some of the potential benefits that healthcare organizations can hope to experience by deploying artificial intelligence (AI) technology.

AI promises to revolutionize the healthcare industry, helping physicians, nurses, engineers and hospital managers make better decisions, faster and more efficiently. The potential is huge, but many healthcare organizations are struggling to tap into the opportunity due to a lack of know-how and experience. To turn the possibilities of AI into reality, healthcare organizations will require people with the skills to deploy the tech and intelligent strategies that make best use of experts time and knowledge.

Let’s look at how you can prepare your resources for AI project management.

AI creates more jobs

Despite fears that artificial intelligence and robotics will make humans redundant, right now it’s creating more jobs than there are people with the skills available. Introducing an AI project in your organization will mean sourcing talented staff with AI knowledge, software development skills (typically developers who know Python and R), data analysts, and project managers.

To develop an AI project for your organization, you will therefore require resources with the skills, time, and experience to achieve your goals. With this in mind, here are some essential tips, drawn on our experience of working with healthcare project management, which can help you prepare for the resource requirements of the coming healthcare AI revolution.

AI project management guidance

1. Define a goal 

More important than anything is the requirement to define a goal for your healthcare AI project. It’s best to choose a ‘narrow but deep’ purpose, because AI works best when given very specific tasks. This might be something like:

  • Analysis of dosage errors to limit abuse
  • Using predictive analytics to discover hotspots for different illness types
  • Matching patients to clinical trials
  • Chatbots – either on your website for diagnosis, or for patients within the hospital
  • Workflow and working hours analysis to limit employee burnout

Once you have a goal, you can then begin defining the project scope and the kinds of resources that will be required to complete it.

2. Define the project roles you will need

Depending on the kind of AI project you choose to implement, you will need employees with different kinds of relevant skill sets.

For instance, if you are mainly implementing third-party software, you will need to assemble your IT team plus external consultants who can install the technology on your systems. On the other hand, if you are building your own AI tool for a specific purpose, you will need to source AI experts, developers, and project managers with skills related to that project.

At the most basic, AI project management will require the following kinds of resources:

  • Computing power – normally using a cloud-based environment
  • Data analysts – to clean and crunch numbers
  • Data modelers – who understand machine learning and who can pull out results and insights from the data
  • Engineers/developers – who can piece your AI tool together. They will either know how to use an existing third-party AI platform, or have the experience to build a new machine for you

3. Start with a limited trial

IT projects are famous for going over budget and over time. It is therefore sensible to start your healthcare organization’s AI project with a small and targeted trial. Keep the project within one department and focused on a very specific activity. This will help you understand how long a larger project would take and provide important experience for the resources you’ve assembled.

4. Training

Like any tool, AI is only useful if people know how to use it. Once your AI project is complete, you will need to set aside time and resources to train physicians, nurses, administrators and other hospital staff to use the tool effectively.

Your AI project needs to be dependably managed

According to McKinsey, the consultancy, around 66% of all software projects run over budget. Artificial intelligence deployments face the same cost and time overrun risks as any traditional tech deployments. And in the healthcare sector, where budgets are tight and expectations high, these kinds of overruns could prove damaging.

So, to ensure that your AI project achieves its targets, it’s essential that your project – and your resources – are deployed in the most cost and time efficient manner. Resource management tools like Tempus Resource are specifically designed to help you run your projects in the most effective way possible – learn more here.

 

The AI revolution is coming to the healthcare sector. Now’s the time to start preparing your resources.  

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