MHA 507 Week 5 Performance, Productivity, Morale and Safety Example

Overtime, Burnout and Falls on the Same Units: Linking Workforce Productivity, Staff Morale and Patient Safety Data in a Four-Hospital System

[Student Name]

University of Phoenix

MHA/507: Using Informatics in the Health Sector

Week 5 Assignment

[Instructor Name]

[Date]

The health system, its units, measures and results are composites written for a model paper; research findings come from the sources listed.

At a monthly operations review of a composite four-hospital system, the chief financial officer praised the medical-surgical units that had cut worked hours per patient day below target. The chief nursing officer answered that two of those units also had the most falls with injury in the system. Both were reading from different reports. The chief executive asked the performance improvement manager to put the numbers in one place. This paper describes the measures, the data, the evidence and the decision that followed.

Four Concepts, Four Measures

Each concept needed a definition that could be measured. Performance was defined as achieving the unit's quality and financial goals together. Productivity was measured as worked nursing hours per patient day compared with the unit's target. Morale was measured by an annual engagement survey and a quarterly burnout pulse survey using validated items. Safety was measured by falls with injury, hospital-acquired pressure injuries and medication errors reaching the patient, per 1,000 patient days.

Where the Data Live

The data lived in four systems. Payroll recorded worked hours, overtime and agency hours by unit and pay period. The census system recorded patient days. The survey vendor held engagement and burnout results by unit, reported only when at least five staff responded. The incident reporting system and the electronic record held safety events. None of these systems shared a common unit code, so the first task was a crosswalk matching each system's unit names to one list of 48 nursing units.

Joining the Data

The manager built a quarterly table with one row per unit and columns for hours per patient day, overtime share, turnover, engagement, burnout, falls, pressure injuries and medication errors. Two years of quarters gave 384 unit-quarters. Units with too few survey responses were flagged rather than dropped, so leaders could see where morale data were missing.

What the Research Suggests

Research gave reasons to expect these measures to move together. A systematic review of 46 studies found that 21 of 30 studies measuring burnout reported a significant association between burnout and patient safety, and that most studies of wellbeing found poor wellbeing linked to worse safety, although the lack of prospective designs limited conclusions about cause (Hall et al., 2016).

Evidence From Physicians

A national survey of physicians found that 54.3% reported at least one symptom of burnout and 10.5% reported a major medical error in the previous three months; after adjustment, burnout was associated with more than double the odds of reporting an error, and poor safety grades in the physician's work unit were independently associated with errors as well (Tawfik et al., 2018). Burnout and unsafe units each raised the odds of error, which means both the person and the place matter.

Evidence on Shift Length

Productivity choices shape schedules, and schedules shape morale. Surveying 31,627 hospital nurses on medical and surgical wards in a dozen European countries, researchers compared long and short shifts: those on shifts lasting 12 hours or longer, against colleagues on 8-hour or shorter shifts, had greater adjusted odds of emotional exhaustion, job dissatisfaction and intention to leave because of dissatisfaction (Dall'Ora et al., 2015).

Finding One: Overtime and Burnout

In the system's data, the 12 units in the highest quarter for overtime share had a burnout rate of 48% on the pulse survey, compared with 31% on the 12 units with the least overtime. Hours per patient day were lowest on the high-overtime units, meaning the units looked productive on paper while relying on fewer staff working longer.

Finding Two: Burnout and Falls

Falls with injury averaged 0.62 per 1,000 patient days on the high-burnout units and 0.38 on the low-burnout units. Pressure injuries showed a similar but smaller gap. Medication errors reaching the patient showed no clear pattern.

Finding Three: Turnover

Turnover followed burnout. The high-burnout units lost 24% of registered nurses in a year, compared with 13% on the low-burnout units, and each departure brought more overtime for those who stayed.

Association, Not Proof

The manager was careful about what the data showed. The relationships were associations in observational data, and several explanations were possible: busy units with sicker patients could have more falls and more overtime at once. She therefore compared units with similar patient acuity, and the pattern held, though it weakened. She presented the findings as a strong signal worth acting on, not proof of cause.

A Reporting Trap

Incident reports depend on staff choosing to report. Units with poor morale may report fewer events, which would hide problems. Falls with injury are hard to miss and are also captured in the record, so the manager relied on them more than on self-reported near misses.

Productivity Reconsidered

The findings changed how leaders read productivity. A unit below its hours target is only efficient if safety and staff hold steady. The chief financial officer agreed that hours per patient day would no longer be praised in isolation; it would appear beside overtime, burnout and falls on the same line.

The Decision

Leaders approved three changes for the 12 high-overtime units: a cap on overtime of 12 hours per nurse per pay period except in emergencies; a system float pool of 30 registered nurses to fill gaps instead of overtime; and a choice between 8-hour and 12-hour shifts for nurses on those units, reflecting the European evidence. The cost of the float pool was estimated at $3.1 million a year, partly offset by lower overtime and agency spending and by reduced turnover.

Measuring Whether It Works

The dashboard tracks overtime, burnout, turnover and falls quarterly on the 12 units and compares them with the rest of the system. First-year targets are to cut overtime by half, bring burnout below 40% and reduce falls with injury by a quarter.

Involving Staff

Nurses on the affected units helped design the float pool rules and the shift choice, and their unit councils review the dashboard each quarter. Involving staff made the changes something done with them rather than to them, which the manager expected to help morale in its own right.

Physicians and Other Staff

The physician evidence mattered as well. The system added a burnout pulse question to its annual physician survey and will report results by department, linking them to safety measures in the same way.

Protecting Privacy in Morale Data

Survey results are shown only for groups of five or more, so no individual can be identified, and managers see unit results, never individual responses.

Limits

The analysis covers two years of observational data from one system, relies on a short burnout measure and cannot exclude other explanations. Results will be revisited after a year of the new policies.

Conclusion

Separate reports had allowed the same units to be praised for productivity and criticized for safety at once. Joining payroll, survey and incident data by unit showed overtime, burnout, turnover and falls moving together, consistent with research on burnout, safety and long shifts. Leaders changed how productivity is judged and invested in staffing, with measures in place to show whether performance, morale and safety improve together.

References

Dall'Ora, C., Griffiths, P., Ball, J., Simon, M., & Aiken, L. H. (2015). Association of 12 h shifts and nurses' job satisfaction, burnout and intention to leave: Findings from a cross-sectional study of 12 European countries. BMJ Open, 5(9), e008331. https://doi.org/10.1136/bmjopen-2015-008331

Hall, L. H., Johnson, J., Watt, I., Tsipa, A., & O'Connor, D. B. (2016). Healthcare staff wellbeing, burnout, and patient safety: A systematic review. PLOS ONE, 11(7), e0159015. https://doi.org/10.1371/journal.pone.0159015

Tawfik, D. S., Profit, J., Morgenthaler, T. I., Satele, D. V., Sinsky, C. A., Dyrbye, L. N., Tutty, M. A., West, C. P., & Shanafelt, T. D. (2018). Physician burnout, well-being, and work unit safety grades in relationship to reported medical errors. Mayo Clinic Proceedings, 93(11), 1571-1580. https://doi.org/10.1016/j.mayocp.2018.05.014