In recent years, organizations of all kinds have adopted analytics solutions for the promise of efficiency and to gain new, data-backed insight into their customers and business. Yet, according to MIT Sloan Management Review's latest report, many still struggle to extract value from the data collected and deliver on these promises.
This trend is especially true within the healthcare industry, where the number of data sources continues to proliferate; the market for IoT technology alone is expected to more than double between 2014 and 2021. As more hospitals continue to purchase and deploy analytics solutions under pressure to reduce spending and improve patient care, it is more vital than ever that healthcare leaders share lessons and best practices from their deployments to create the best possible outcomes.
To help healthcare facilities realize these goals, here are five lessons inspired from real-world analytics deployments:
1. Encourage Technology Adoption by Avoiding Top-Down Leadership
One of the biggest challenges in deploying any kind of technology in a hospital environment is getting buy-in from highly skilled healthcare professionals. These are people with advanced degrees and a critical thinking process, and their job function is both urgent and frequently evolving. Many of them have learned a particular way to get the work done, and new technologies will almost certainly impact their workflow. If leadership introduces a great technology but it doesn't resonate with staff, it won't contribute value to the organization.
Hospitals are most successful when at the outset of introducing new analytics solutions, they first aim to create consensus among employees about the problems they're aiming to solve as a team. This involves interviewing employees about what is and isn't working, and direct input on potential goals for the analytics solutions.
A common example of a pain point is managing workload. By focusing on the ways in which analytics can be applied to create efficiencies that make people's workloads lighter and help them see more patients, leadership can avoid the perception that they're adding to an already full plate.
2. Focus on Solving a Few Problems or Improving a Single Environment
Hospitals deal with a continual flow of new patients, staff, equipment and inventory. Everything is moving quickly and the environment is ever-changing, which means that tackling even one process or workflow can produce a lot of data. It can be easy to get overwhelmed amidst all the opportunities for improvement, so to avoid information overload, hospitals should focus on a few core areas to address with analytics. Alternatively, consider focusing on just one unit of a hospital at the beginning of a deployment, and gradually rolling out solutions across the facility as results manifest. Starting small allows teams to validate the use case and make improvements for potential facility-wide deployment, thus maximizing the return on the initial deployment while minimizing stress on staffers.
3. Identify Key Performance Indicators and Set Achievable Goals
What works for one hospital won't necessarily work for another. Each hospital must identify the metrics that will enable them to measure the impact of the analytics project on the workflow in question. These Key Performance Indicators (KPIs) should be recognizable and meaningful to those involved in the workflow. In fact, the greatest success comes when clinicians and other staff members are involved in defining this right from the outset. A critical piece of this approach is to ensure that stakeholders have visibility to the KPIs most relevant to them — not days or weeks afterwards, but immediately so that they can react on the spot and begin to connect their own actions to overall events.
Often, there is a "lynchpin" KPI that strongly influences performance in other areas. For example, first-case start time has a major impact on patient flows throughout the day. If the first appointment of the day doesn't start on time or goes too long, it can cascade into other appointments and leave staff struggling to make up for lost time. Most hospitals can benefit from focusing on these key KPIs, and then developing supporting KPIs on key factors for each group in the workflow. In this case, steps that will help the workflow recover from a delay: room turnover time, equipment availability and bed availability downstream in the next phase of care.
4. Plan for Lessons Learned in Deployment Timelines
When planning an analytics deployment in a hospital setting, be sure to leave room for lessons learned. Sometimes, the data surprises you. Leaving a buffer in the deployment timeline will ensure that results are delivered on time and analytics programs have a fair chance to show impact once they're actually in play. It also gives you time to adjust both initial data infrastructure, and data visualization, to ensure that the data is accurate and presented in a manner that's useful for its intended audience.
For example, when one of STANLEY Healthcare's customers set out to deploy RTLS/RFID technologies to track the flow of patients and staff, they had to first set the infrastructure and identify which areas of the hospital they wanted to track motion in. But how do you decide where to track patients without analytics? The RTLS/RFID technology would show this, but it had to be deployed first – a true chicken and egg moment. Staff made an informed decision about the priority areas to track in the hospital, but they had to revisit this when they saw gaps in the data about where patients and staff were traveling often. In the end, the hospital had to expand the original scope of tracking to include a broader area. Had they not left room for the unexpected in their initial deployment, this extra step would have impacted the overall timeline, leaving less time for results to manifest before evaluation phase, and causing their visualizations to represent incomplete data sets.
5. Review Performance in Real-time
Half the battle in obtaining value from an analytics programs is make sure that staff can quickly respond to the information it delivers. Once you've identified KPIs, consider establishing a dashboard and displaying it for critical stakeholders on-the-ground and in management. When employees can see progress against goals in real-time, they can evaluate whether what they're doing is working, make changes in real-time and then measure the effectiveness of those decisions. A simple dashboard displayed throughout the facility may encourage employees to take ownership over the team's progress against goals, especially if those goals map to the problems they shared at the outset.
As the level and complexity of healthcare data and analytics continues to grow, hospitals and other healthcare facilities must take a proactive first step in preparing for these deployments by sharing their insights and experience with other leaders in the industry.
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