Mara Paré, vice president of client solutions at PartsSource in Aurora, Ohio, talks to 24×7 Magazine about how HTM teams can make better use of data to control their costs while increasing their quality and efficiency. 

24×7 Magazine: What industry trends are pushing HTM to become more data-driven?

Mara Paré: Supply chain expenses are predicted to eclipse labor as the new No.1 cost in healthcare in 2020. And the shift to value-based care has put more accountability on patient satisfaction while increasing quality and lowering costs. Traditional cost-cutting initiatives alone won’t compensate for the decreasing revenue, so hospital leaders are seeking other ways to reduce costs. As a result of these pressures, now more than ever, clinical engineering can and should use data to guide their strategies and demonstrate their impact on cost reductions, quality performance, and increased productivity.

Another factor driving the need for data is the expanding and changing role of clinical engineering while the talent pool is shrinking from retirements. HTM teams can use data to help inform their decisions and use technology to help alleviate clerical duties so they have time to tackle big challenges such as cybersecurity, capital planning, resource planning, and cost of service ratios, all while cutting costs and improving uptime.

24×7: How can HTM leverage data to become more evidence-based and quality driven?

Paré: Using evidence-based data to guide HTM purchases can help reduce subjective decision-making that may or may not net in cost savings or quality. For instance, using quality return rates can provide insight to truly understand quality failure rates and total cost of ownership by modality, by supplier. 

This is the data that the HTM community can and should have access to in order to make the best decisions for their organization, and it’s where PartsSource can add real value to clinical engineering. Most people know of us for the efficiency of our online procurement platform, but we also work with thousands of hospitals to provide data-driven decision support that improves parts and service quality, realizes greater cost savings, and provides significant resource efficiencies. And then we provide cost and quality reporting that can be shared with hospital leadership to show the HTM team’s value.

24×7: What elements can help determine quality that HTM should be looking at to support operational excellence?

Paré: Operational excellence is an ongoing process of continual improvement and problem solving—having data helps identify these opportunities for improvement. Three critical data points to look at to support operational excellence are quality, efficiency, and cost containment. 

Quality: Monitoring what equipment and parts fail is an obvious way to track quality, but other quality indicators such as accessibility of parts, service, and equipment can be monitored too. Back orders and dead-on-arrival parts contribute to equipment downtime and affect patient care. 

Efficiency: Finding the most impactful use of resources and processes can support operational excellence. For example, we’ve conducted before and after time-motion studies on the procure-to-pay process in hospitals to identify inefficiencies. From these time studies, teams see up to a 95% reduction in sourcing and procuring parts and services by automating and integrating to existing workflows.

Boyd Hutchins and his team at Arkansas Children’s conducted their own time-motion study before having a managed service program in place. They found that their engineers were spending 20% of their time on clerical duties involved with ordering parts. Automating the procurement process into the CMMS allowed their team to spend that time on other priority projects.

Cost containment: Monitoring pricing and what is spent throughout an organization at different locations by different people at different times is important to ensure standardization of off-contract spend and to identify opportunities to cut costs. Having the processes and systems in place to track each of these can identify opportunities for improvement.

24×7: How can hospitals and IDNs use data and insights to improve uptime and reduce mean time between failures? 

Paré: First, it starts with quality. Use data to establish a quality management system (QMS), which plans, measures, tracks, and responds to the quality of medical equipment replacement parts and service. This helps ensure quality is built in from the start and reduces mean time between failures.

Second, use data to measure performance and quality outcomes to create a path for continuous improvement. For example, solutions that use years of longitudinal outcomes data to measure part and equipment failure can help ensure purchases are optimized for quality and increased uptime. Finally, using technology to help implement standardization policies across hospitals and health systems can ensure insights are actionable in an efficient and scalable way. 

24×7: What analytics are on the horizon and will become commonplace for HTM leaders?

Paré: We see three trends quickly becoming the norm for HTM: 1) having industry data available to benchmark your own performance, 2) deeper analytics tied to lifetime performance of specific models and pieces of equipment to gather and improve total cost of ownership metrics, and 3) predictive analytics, which would gather and combine data points to predict when equipment will fail, when to proactively replace it, or when to repair it.

These analytics are on the horizon and can help address rising supply costs and improve overall healthcare performance. For now, using processes and technology to create a data infrastructure allows HTM teams to be data-driven, ultimately leading to better patient care.