• Written by Muhammed Abdulla NC, CEO

Healthcare providers often struggle to measure the return on investment of new interventions, as the counterfactual - what would have happened without the intervention - is invisible, making it difficult to determine the actual impact. This challenge is exacerbated by the constraints of clinical operations, which have strict privacy obligations, making it hard to access the necessary data to measure the effectiveness of an intervention.

Challenges in measuring ROI in healthcare providers

Healthcare providers face unique challenges when it comes to measuring the ROI of new interventions. Scheduling and utilisation of resources, such as operating rooms and equipment, can be difficult to optimise, leading to variability in supply consumption and documentation burden. For example, a shift supervisor checks the maintenance log to ensure that equipment is properly maintained, but this process can be time-consuming and may not always be up-to-date. This can lead to inefficiencies and waste, making it harder to measure the impact of an intervention.

The documentation burden is another significant challenge. Healthcare providers are required to maintain detailed records of patient care, which can be time-consuming and may not always be accurate. This can make it difficult to access the necessary data to measure the effectiveness of an intervention, and may lead to incomplete or inaccurate data.

Leading measures that can be observed

Despite the challenges, there are leading measures that can be observed to determine the effectiveness of an intervention. For example, a category manager compares two suppliers to determine which one provides the best value for money. This process can be used to measure the impact of an intervention on supply chain management. Additionally, metrics such as patient satisfaction and staff engagement can be used to measure the impact of an intervention on clinical operations.

These leading measures can provide valuable insights into the effectiveness of an intervention, and can be used to make data-driven decisions. By using AsscherAi to analyse data from various sources, healthcare providers can gain a better understanding of the impact of an intervention and make informed decisions about future investments.

Why aggregate outcome metrics are unreliable

Aggregate outcome metrics, such as patient outcomes and readmission rates, are often used to measure the effectiveness of an intervention. However, these metrics can be influenced by a variety of factors, including changes in patient population and external factors such as weather or economic conditions. This means that aggregate outcome metrics may move for unrelated reasons, making it difficult to determine the actual impact of an intervention.

For example, a hospital may see a decrease in readmission rates, but this may be due to changes in patient population rather than the effectiveness of an intervention. Therefore, it is essential to use more nuanced metrics that take into account the complexities of clinical operations and the various factors that can influence patient outcomes.

Baselining before rollout

Baselining before rollout is essential to determine the effectiveness of an intervention. By establishing a baseline before the intervention is implemented, healthcare providers can determine the actual impact of the intervention and make data-driven decisions. This involves collecting data on key metrics, such as patient satisfaction and staff engagement, before the intervention is implemented, and then comparing this data to post-intervention data.

Reconstructing the baseline after the intervention has been implemented can be challenging, as it may be difficult to determine what would have happened without the intervention. By baselining before rollout, healthcare providers can avoid this challenge and gain a more accurate understanding of the impact of an intervention. For more information on how to baseline before rollout, please contact us.

Limitations of this approach

This approach to measuring ROI in healthcare providers is not without its limitations. It requires significant resources and expertise to collect and analyse data, and may not be suitable for all types of interventions. Additionally, it may not be possible to measure the impact of an intervention on certain outcomes, such as patient satisfaction, using quantitative metrics.

In some cases, alternative approaches, such as qualitative research or observational studies, may be more suitable for measuring the impact of an intervention. Healthcare providers should carefully consider the limitations of this approach and determine the best method for measuring the ROI of an intervention based on their specific needs and circumstances. By doing so, they can make informed decisions about future investments and improve the quality and efficiency of patient care.