Skilled Nursing Analytics: Beyond Reports

This month, 40 individuals were admitted to two skilled nursing facilities. Although their reports may look similar, the teams’ workloads differ significantly. For example, one team manages information with minimal interruptions, while the other frequently corrects records, requests clarifications, and revisits incomplete tasks. Admission counts are tracked, but they do not reflect the full scope of each team’s efforts.

Skilled nursing analytics enables leaders to identify this unseen work. Analyzing operational patterns can uncover issues not visible within summary totals. An effective admissions strategy begins with targeted questions: Which ongoing projects require attention? What are each department’s starting points? How can admission coordination be improved? Leaders can use these data to identify repeated problems and execute targeted improvements. This approach strengthens coordination among admissions, nursing, MDS, and the business office.

What Is Skilled Nursing Analytics?

With skilled nursing analytics, teams can leverage facility data to identify trends, investigate issues, and make informed decisions. Analytics can be used to gain insights into clinical outcomes, staffing, finances, census, and daily operations. But every region has its own particular information and interpretation. For instance, clinical leaders may consider the outcomes for residents. In the meantime, administrators can analyze building workloads. In addition, business offices may review consistent billing issues. Moreover, CMS releases nursing home data based on resident assessments, staffing data, and Medicare claims. Information for different measures is available from each source. Internal operational analytics also provides a different viewpoint by analyzing how the employees perform their work within the building. Taking this view into account, this article concentrates on admissions analytics. In particular, it examines the impact of corrections, exceptions and department transfers on the work of completed admissions.

Reports Show Activity. Analytics Helps Explain It.

There are 40 admissions completed in the report. But an analytical review can provide leaders with insight into why some had to be coordinated more than others. A task list likewise lists completed tasks. Teams can use the reopened assignments to see what caused the extra work. The two methods are valid approaches. Finally, teams should use the information they can draw from their findings to inform specific decision-making. So, if you want to request another dashboard, first determine the question you are trying to answer. Next, identify relevant information and explore patterns within this information.

Examine the Work Behind Each Admission

Understanding admission volume is useful, but it does not fully reflect the team’s workload. Residents have varying needs, referral packets may be incomplete, and each department faces unique review considerations. Teams should examine each case in the skilled nursing facility to identify actions that advance cases. This helps leaders understand workload differences and identify common barriers.

First-Pass Completion

First-pass completion measures how well teams complete tasks they are eligible for without correcting or reopening them within a set time frame. For example, monitor teams to ensure they correct admission forms within 7 days of initial completion. To begin, establish clear completion requirements. Otherwise, the employees might use different criteria for the same job. Then, identify unnecessary corrections from valid updates. For instance, employees have completed the initial task correctly, but the information received is new and needs further work. Finally, before comparing, let the entire observation period be completed. After all, teams must follow up for six more days on a form they completed yesterday.

Repeated Work

Teams duplicate work when they enter duplicate information, conduct unnecessary repeat reviews, or repeatedly request clarification. There are some necessary repeat actions, though. For instance, a second review might identify errors or confirm key information. Thus, note down the cause of each repeated action. Organize the reasons into categories: missing information, conflicting information, unclear information, and newly received information. Then, determine recurring causes using those categories. This means that leaders can address workflow issues without assuming that employees are responsible for reopening all tasks.

Department Handoffs

A handoff is when someone or another department hands off responsibility or information to another person or department. For instance, admissions provides information to the business office. But can this crew start their evaluation right away? If a person is not clear, write down what is stopping them. Then, look at those reasons to see if there are any common barriers. Over time, these patterns can lead to better coordination within the department for leaders. Also, differentiate between available reviews and completed reviews. The fact that a person has entered information into a field doesn’t mean the information was accurate.

Choose SNF Analytics Metrics That Answer Questions

A useful metric enables your team to connect data to operational questions and guide decision-making. Start by identifying a recurring problem. Then, choose a few key measures to help determine its cause. This approach focuses your team on actionable insights. As a starting point, use the following operational measures with this goal in mind.

Define Each Measure Before Calculating It

First, define what you will count, the observation period, and any exclusions. Then, document the numerator and denominator. To calculate the clarification rate, divide the number of eligible handoffs requiring clarification by the total number of eligible handoffs during that period. Next, multiply by 100. For example, if teams request clarification on 12 of 60 handoffs, the rate equals 20%. Count each handoff once. However, count individual clarification requests separately to examine repeated activity. Additionally, distinguish case counts from event counts. One admission with five reopened tasks differs from five admissions, each with one reopening. Affected admissions show the problem’s reach, while reopening show how often teams repeat work. For first-pass completion, include only eligible completed tasks whose observation periods have ended. Then, divide tasks requiring no correction or reopening by that total and multiply by 100. Finally, apply exclusions consistently. Document how you handle canceled tasks and updates triggered by newly received information during follow-up.

Separate Waiting Time From Staff Effort

If a task remains open for two days, the employee may spend much less time on it. For instance, staff might have to wait for records, signatures, or an external response. Meanwhile, they could complete the actual review in a matter of minutes. Thus, measure elapsed time in terms of timestamps. Your system also needs to track the time that employees are actively engaged in their work to measure their effort. Then, use task counts and elapsed time to determine places to investigate. If, however, you make specific estimates of labor, substantiate them with evidence of work actually performed by your staff.

Check Data Quality Before Comparing Teams

Unreliable data can make analytics ineffective and direct teams towards wrong decisions. That is why, before comparing buildings, ensure that the teams consistently register the same events. Namely, one team may log each clarification, while another team might solve the problem by making phone calls, but not register anything. Consequently, proper logging can lead the team to face more issues. Hence, the teams have to be compared based on reliable data.

Compare Similar Admissions

First, one needs to consider packet completeness, required reviews, residents’ needs, and arrival time. For instance, teams working on complex cases require additional coordination. At the same time, in another building, simpler cases can be solved by fewer administrative employees. Still, admission numbers alone cannot answer how these differences influence each team’s workload. Consequently, one should group cases by several criteria. For instance, comparing admissions with incomplete packets with those that lack necessary documentation is one such approach. Also, one should review the responsibilities of department employees. Employees with identical job titles might have different assignments.

Show Counts and Missing Information

Start by presenting numbers in conjunction with percentages. Two incidents with 50% frequency offer less proof than 200 incidents with the same percentage frequency. Moreover, ensure that the missing data is presented to the reader so they know where information is lacking. The absence of an event in the employees’ reports does not mean that it never occurred. This means that in case 20 reports do not contain information on handoff, make sure that you indicate this limitation before interpreting the rate. Lastly, use anomalies to initiate a discussion with your team. You can then analyze individual cases.

Turn Operational Patterns Into Workflow Improvements

Skilled nursing analytics deliver value when evidence changes an operational decision. A chart can highlight a concern. However, employees still need to explain what happened and test an appropriate response.

Examine the Cases for the Number

First, identify the group of affected cases. Also, review cases managed successfully by other teams. Next, ask employees what they needed, what they received, and why they could not continue with the process. Then, compare their explanations with recorded events. This helps managers distinguish between reasonable assumptions and data-driven conclusions. For example, confusing instructions may lead to repeated requests for clarification, or employees may receive a handover lacking essential data. Because each reason requires a different approach, discovering the root cause is essential.

Test One Targeted Change

First, select an area for improvement based on the problem your results highlight. This may involve defining a transfer policy, determining a reviewer, or changing when you give information to a department. Then assign an owner and schedule a review. You must also record the change so your team can make future comparisons. Where possible, conduct the test on one workflow. Once you have results, expand the test to other buildings. It is critical to maintain consistency of measurement definitions throughout the test process. Mixing up workflows and measurement definitions complicates results.

Watch for Unintended Effects

To begin with, match your primary indicator with another indicator to determine whether the change affects another valuable outcome. For instance, monitor requests for clarification and the number of new problems that arise after the handover process. The reduction in questions has no value if the problems are handed down to the next department. Also, make sure the reduction in reopening is due to proper completion rather than to the avoidance of certain tasks. Furthermore, ensure that employees still perform the required checks and that the department receiving the work can use the data. Lastly, consider other factors that may affect the results before concluding that your change is responsible for them.

Example: Equal Admissions, Unequal Workloads

Consider this fictional example, which illustrates an analytical approach rather than a Flowtrics customer result. Buildings A and B each admit 40 residents monthly. Although Building A handles more complex cases, its departments receive enough information to begin reviews. Meanwhile, Building B’s business office frequently requests clarification. Initially, leadership assumes Building B needs more administrative support. However, a review of records reveals that 15 of 40 handoffs required clarification—a 37.5% rate—and ten involved uncertainty about representative information. Staff entered the details, but receiving employees could not confirm whether anyone had reviewed them. Therefore, the team adds a clear review indicator and assigns an owner. During a defined trial, employees track clarification requests, problems they discover after transfer, and changes in case complexity. Finally, if requests are declined, leadership reviews the quality of the review before proceeding with the change. By investigating the work, leaders can address the underlying coordination problem rather than relying on admission totals.

Start With One Question This Month

You can begin with one focused question without launching a large analytics initiative. First, choose a problem that repeatedly interrupts admissions. Then, define what you will count and which cases you will review.

Follow this practical sequence: Select one recurring operational question.

1. Next, define eligible events and the observation period.
2. Then, check whether employees consistently record those events.
3. Compare affected cases with examples your team completed smoothly.
4. Use your findings to choose one targeted change, assign an owner, and set a review date.
5. Finally, compare results while checking quality and downstream effects.

Additionally, keep a brief record of findings, decisions, and results. Over time, this history helps your team evaluate changes and direct future improvements. Ultimately, use skilled nursing analytics to understand daily work, detect recurring obstacles, and improve how employees coordinate admissions.

Book a Flowtrics demo to explore connected admissions workflows and discuss your facility’s most pressing operational questions.

Skilled Nursing Analytics FAQs

What Can Analytics Reveal Beyond Admission Counts?

It can reveal repeated work, difficult handoffs, unresolved exceptions, and differences in workload. Consistent records make these patterns easier to investigate. Reviewing individual cases helps explain the causes behind the numbers.

Which Admissions Metric Should an SNF Track First?

Start with a metric connected to a recurring problem. For example, track handoffs requiring clarification when departments struggle to begin. Define eligible cases and review the reasons behind each request.

How Can Facilities Compare Workloads Fairly?

Consider case complexity, available staff, role responsibilities, and packet completeness. Show sample sizes alongside rates. Also, check whether teams record events consistently. Task counts alone cannot establish employee effort.

Can Analytics Replace Staff Judgment?

Analytics identifies patterns and questions. Employees still need to validate information, interpret context, and make decisions. Combining recorded evidence with staff experience provides a stronger basis for improvement.