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Introduction
In healthcare facilities, many factors can affect deviations from the original budget. To establish and track budget variances, it is essential to keep a record of finances through variance analysis. Each new budget is built based on the previous variance data and the standard method of calculating the required items. However, healthcare institutions cannot, in any case, accurately calculate the probable overrun of funds. This work aims to consider the deviations present in the submitted report for the last month and highlight additional data to describe them. In addition, a strategy has been developed to correct deviations to create a more accurate budget plan.
Month Variances
As seen from the table, several deviations have recently been noted in the institution. Discrepancies in the originally budgeted budget and the final amount can be traced in many points of the report. The most considerable difference is noted in such items as ambulatory surgery, supplies, and net assets released. Areas that go far beyond the planned budget require closer attention, as they can significantly impact the organization’s financial position (Drury, 2018). In addition, this indicates that the calculations need to be corrected, and these areas require significant investments.
Furthermore, some items slightly exceeded the given budget. If the organization considers this in the context of one month, then the discrepancy seems insignificant. However, this happens all the time, and looking at finances over a long period can play a significant role. Nevertheless, not only negative discrepancies are observed from the provided report, which increases the financial gap. Some items show the use of less funding than initially offered. For example, Inpatient Revenue and Other Patient Revenue show a decline of $960 and $326. In this case, it is essential to reconsider the budget distribution and strengthen those areas lacking funding (Kouvelis et al., 2018). This can lead to a more sustainable system with a well-defined budget.
Additional Data
However, additional data must be considered to explain the details thoroughly. First, it is essential to understand that the influx of patients calculated in the budget is nominal and may not reflect the actual reality. Accordingly, one of the main points in the additional data is the exact number of clients compared with the prediction made (Jones et al., 2018). Thus, the healthcare organization can hire other employees in case of a large flow of clients. This will require supplementary costs that were not originally foreseen. Further, with a large flow of customers, staff can stay at the workplace for more hours. Since the overtime rate is increased, the nurse manager must account for this factor in the budget. Nevertheless, as the report shows, salaries and wages were $345 less than previously estimated monthly. This may be because many patients did not visit the health facility, and some staff needed to be more involved.
In addition, more than the flow of patients can explain the lower number of salaries. There could be an outbreak of a viral disease among the staff, spreading to many workers. As a result, many of them could not attend the workplace, resulting in a shortage of staff and lower pay (Hansen et al., 2021). Furthermore, any catastrophes or natural disasters can become an additional factor. This may explain the high budget overruns in ambulatory surgery. These are quick one-day interventions that do not require the patient to stay in the hospital. This includes the treatment of wounds and burns, suturing, and other manipulations that do not keep the patient in the department. Supplies are an essential item in the process of protecting the health of patients. The report shows additional budget spending in this area, possibly due to a need for more materials. Thus, the nurse manager is forced to order more necessary items than were initially included in the finances. To a greater extent, this is due to the difference in the estimated and actual volume of procedures associated with these resources, including X-ray examinations and laboratory tests.
Strategy
In case of discrepancies between the planned and actual budget, a strategy for correcting the variances should be developed. First, it is crucial to determine where the most remarkable difference in the budget can be traced and detail the reason. The next step is to analyze the discrepancies and highlight the most critical areas. It is necessary to establish whether the deviations are single or increase over time (Dai et al., 2021). This will help to understand how vulnerable this or that side of the system is. An equally significant step is the definition of the nature of the dispersion, that is, positive or negative. Those areas that consistently use less than the gold budget can be used for those with a constant shortage. Thus, such a strategy will help to correct the difference between the forecast and the actual budget.
Conclusion
In conclusion, variance analysis is a critical tool for the health care system. It highlights the organization’s effectiveness and allows one to trace the distribution of financial flows. In addition, it helps to predict the possible costs of payments, procedures, etc. If it is necessary to fix deviations, it is essential to highlight the main points and outline whether they are positive or negative. In this way, a successful budget adjustment can be made.
References
Dai, M., Jin, H., Kou, S., & Xu, Y. (2021). A dynamic mean-variance analysis for log returns. Management Science, 67(2), 1093-1108. Web.
Drury, C. (2018). Cost and management accounting. Cengage Learning.
Hansen, D. R., Mowen, M. M., & Heitger, D. L. (2021). Cost management. Cengage Learning.
Jones, C., Finkler, S. A., Kovner, C. T., & Mose, J. (2018). Financial Management for Nurse Managers and Executives-E-Book. Elsevier Health Sciences.
Kouvelis, P., Pang, Z., & Ding, Q. (2018). Integrated commodity inventory management and financial hedging: A dynamic mean‐variance analysis. Production and Operations Management, 27(6), 1052-1073. Web.
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