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Rich Miller

How gaps in data flow hit your bottom line

By Rich Miller

Rich Miller is co-founder and CEO of OpenTempo, which provides workforce optimization and staff scheduling solutions for health care organizations.

The benefits of interoperability for Electronic Health Records are well known – better outcomes, increased efficiency, and informed decision-making. Yet very few healthcare organizations make the leap to seeing the benefits of interoperability for their staffing data. Staffing data, such as staff schedules, time tracking, and payroll, are typically housed in completely distinct systems. This creates a knowledge gap that hits healthcare organizations directly in their bottom line, affecting costs for overtime and locums, and creating delays or cancellations for patient procedures.

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Data flow and overtime

Most practices are not aware of overtime and under-time risk until the end of a pay period. It is rare that a practice knows in the middle of a payroll period which provider is going into overtime. Even rarer are the practices that know how many of their providers are not being utilized for their full 40-hour commitment. A lack of visibility into the data creates an imbalance in staff utilization, one that frequently leads to excessive overtime costs and underutilized staff.

To correct this situation, practices need to close the gap between data in the staff schedules and data in the payroll system. By integrating scheduling data with time tracking data (what is scheduled to be worked with what has already been worked), practices are able to see who is at risk for overtime and who is being under-utilized before the pay period ends. Seeing this information before the end of the pay period is critical, as that is the crucial moment when practices can adjust staffing levels and prevent excessive overtime from occurring. This gives practices much better control over their labor budget, which is 50-60 percent of an average practice’s operating budget.

Using data to better match staff with patient need

Further benefits can be realized by linking the data among staff schedules, EHRs, and provider credentialing information. This seemingly unlikely trio of information allows staff to be assigned in accordance with patient need, while simultaneously keeping track of provider credentials.

By integrating these areas, practices are able to ensure they have the right credentialed providers for each day’s patient load. A seemingly obvious step, it requires data sharing among systems that are typically unable to communicate with each other. As a result, many practices find themselves short-staffed, or inappropriately staffed, indicating a situation where they have sufficient providers available, but the credential mix is incorrect, or being short staffed based on the volume of patient cases.
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