AMANDA SMITH

Running head: Productivity Metrics 1

Productivity Metrics 5

Productivity Metrics

Tables 3.2 and 3.3 from Case 3: Physician Care Services, Inc, containing the record of service for the community-based hospital, indicates a busy healthcare center but, at the same time presenting insights that necessitate some improvements on servicers and service delivery moving forward (Seidel & Lewis, 2013). This observation is based on two main metrics of performance measurement. First, I have assessed the readmission rates of the patients who attend the hospital. Readmission rates refer to the rate at which treated patients report back to seek improved care. In many cases, readmitted cases indicated a failed or unsuccessful medical intervention. High readmission rates indicate impoverished treatment schemes, while lower rates suggest effective interventions (Caverzagie et al., 2018). In both Beta and Alpha centers of the hospital there is a 30% readmission rates- the percentage is drawn from the column of patients getting to the hospital for the second time but are not invited by the medics.

This performance indicator, the rate at which treated patients seek continued attention from medics, can be improved by both the doctors at an individual capacity or collectively through the heads of the various departments. Such changes would involve prolonged admissions, the improvement of diagnostic machines for an accurate determination of causes of disease, and an accurate determination of the level of healing achieved before discharging patients. Alternatively, or by complementing other interventions, the hospital administration can increase the number of nurses giving individualized care to patients even after discharge from the hospital. Previous evidence-based practice has also suggested that this problem of readmission can be solved through patient education on practices of medication and healthy lives after treatment (Caverzagie et al., 2018). However, the Middleboro hospital should have an accurate determination of the illnesses that have high levels of readmission rates to have specific solutions to specific cases.

The second performance metric I would engage in while determining the hospital's productivity is patient service reputation. This metric implies how treated patients and the public view the hospital as well as how employees perceive the healthcare institution's internal systems. In the case of the hospital, the metric can be based on the rates of new admissions to the hospital in both Alpha and Beta centers. The metric is also sourced from the rate of employee retention. The case study presents low employee retention as a significant problem ailing the institution (Seidel & Lewis, 2013). Secondly, there is still a high hospital capacity, 272 bed capacity, which has not been fully utilized by the local community and the other towns, both domestic and far away. The failure to have a fully exploited capacity is based on a reputation deficit that causes people not to highly regard the institution and employees seeking to shift to other employers after serving in the organization.

The hospital's leadership and management can utilize data from the two tables and from the data captured in the case study to correct this slight productivity deficiency. As for employee retention, the hospital should check on its compensation scheme and weave one that is fair to employees. Secondly, the problem can be cured through the development of motivation-based reward systems that have been credited by causing employees to have positive feelings about themselves and their employer. To solve the reputational deficit on the side of the public, the public relations department should strengthen its means of collecting feedback and making sure that the customer comments are factored in the other strategic decision making. This intervention will create an excellent customer satisfaction scenario and hence market the institution. Additionally, the organization can boost its reputation by having the best skills and diagnostic machines.

References

Caverzagie, K. J., Lane, S. W., Sharma, N., Donnelly, J., Jaeger, J. R., Laird-Fick, H., & Steinmann, A. F. (2018). Proposed performance-based metrics for the future funding of graduate medical education: Starting the conversation. Academic Medicine, 93(7), 1002-1013.

Seidel, L. F., & Lewis, J. B. (2014). The Middleboro casebook: Healthcare strategy and operations. Chicago, IL: Health Administration Press.