Post-Operative Readmission Rates: Literature Review

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Post-Operative Readmission Rates: Literature Review

Table of Contents

Introduction
Methods
Results
Discussion
Conclusion
References

Introduction

Cancer has become one of the major burdens in the healthcare system, leading to high mortality rates and significantly decreasing the quality of life of the surviving patients. In many cases, healthcare professionals manage to save their patients lives through surgical operations. However, there exists a considerable risk of hospital readmissions after such operations for cancer patients. According to Stitzenberg, Chang, Smith, and Nielsen (2015), such readmissions lead to higher costs and lower patient outcomes. Scholars emphasize the importance of coming up with effective interventions that could minimize the burden of readmissions among cancer patients that have undergone surgery.

The focus of the present review of literature is on identifying the level of the problem and investigating the extent to which the issue has been researched. The articles under investigation come from scholarly peer-reviewed journals and contain the latest research results. The significance of the identified problem is manifested in the statistical data on post-operative cancer patients readmission rates and on the negative effects resulting from such readmissions.

Cancer patients are defined as the individuals ill with the oncology disease that have undergone surgery. Readmission is designated as the process of repeated admission to the hospital after having been discharged. Intervention is defined as a viable solution to solve the stated problem. The purpose of this review is to investigate the PICOT question, which has been formulated in the following way:

In patients who have undergone cancer surgery (P),
does the use of the early screen for discharge planning (ESDP) intervention (I),
compared to no use of such a tool (C),
resulting in reduced readmission rates (O)
within a 30- and 90-day period (T)?

Methods

The search of the literature was performed with the help of such databases as Cochrane Library, EBSCOhost, MedlinePlus, and PubMed. These search engines are designed specifically for medical research and offer their users access to a vast variety of materials on healthcare subjects. The keywords that were used to limit search results included readmission, cancer surgery, oncology surgery, and cancer patients.

The inclusion criteria were concerned with the type of the source (peer-reviewed scholarly articles) and the time of publication (within the past five years). With the help of these criteria, nearly fifty matches were found. Then, the articles that were the most relevant to the present paper were selected. The credibility of the sources is manifested through the authors experience, as well as through the sample size and research performed.

Results

Out of the articles located as a result of the search, several foci on post-surgery oncology patients and a few discuss the problems of readmissions. The source that covers the aspects of the PICOT question most comprehensively is the study by Socwell et al. (2018). In their research, the authors investigate the feasibility of using the ESDP in predicting the readmission risk of oncology patients.

The data were collected with the help of a cohort taken from the Peter MacCallum Cancer Centre. Socwell et al. (2018) note that although the ESDP is not a significant predictor of the patients length of stay, this factor can be useful in forecasting discharge destination and readmission. In particular, the negative ESDP score is associated with the 14-day readmission. As a result, Socwell et al. (2018) remark that the ESDP score has the potential to predict readmissions. The major strength of this study is the analysis of the possible ways of reducing readmissions. The limitation is that the authors focus on a 14-day readmission rate whereas the PICOT question aims at analyzing the 30- and 90-day rates.

In several of the located articles, the issue of hospital readmissions upon surgery in cancer patients is analyzed. The purpose of the study performed by Mays, Worley, Ackall, DAgostino, and Waltonen (2015) is to investigate the effect of gastronomy tube (G-tube) placement timing on post-surgery outcomes for cancer patients. 793 cases were identified with the help of the retrospective review of patient records from the Wake Forest Baptist Health Otolaryngology-Head and Neck Oncology clinic (Mays et al., 2015)

The major findings of the study are concerned with the connection between the information available to physicians before the operation and the surgerys success. Mays et al. (2015) conclude that to reduce readmissions of oncology patients, it is crucial to make sure that there are no complications during the operation. The main strength of this research is the large sample size, whereas the biggest limitation is that data was mainly dependent on clinic notes.

The study by Stitzenberg et al. (2015) also focuses on postoperative readmissions. The data were collected with the help of the Medicare-linked database, the Surveillance, Epidemiology, and End Results. The major findings are concerned with the readmission predictors, which are the length of stay, the discharge destination, comorbidities, long travel distance, and a higher stage at diagnosis. The strengths of the study include the investigation of readmission predictors and the 90-day readmission rate, which coincides with the PICOT question. The major limitation is that only the older population was included whereas younger patients characteristics may be quite different.

Two other of the located sources deal with the causes of readmission following surgery and preparatory education for cancer patients undergoing such operations. The purpose of Merkow et al.s (2015) study is to investigate the factors related to unplanned post-surgical readmissions. The data collection was performed with the help of the American College of Surgeons National Surgical Quality Improvement Program, which collects clinical readmission evidence. The major findings indicate that the most common reasons for readmissions are surgical site infection and obstruction (Merkow et al., 2015).

The strength of the article is the identification of possible readmission triggers. The limitations include the impossibility to be completely sure of the reasons for readmissions. The objective of Waller et al.s (2015) research is to analyze the effect of pre-operative education of cancer patients on readmission rates. The data for the analysis were collected from EMBASE, Medline, and PsychINFO databases. The findings indicate that educational interventions lead to improved patient satisfaction and knowledge. The strength of the study is the investigation of interventions aimed at improving the quality of health. The limitation is concerned with the inclusion criteria preferred by the authors.

Discussion

The reviewed articles signify that there is much interest of researchers in the issue of hospital readmissions in oncology patients. However, some studies are limited by patients age (Stitzenberg et al., 2015), and some focus on a shorter readmission period than included in the PICOT question (Socwell et al., 2018). Still, the authors of all articles agree that readmission rates should be reduced both for the sake of patients quality of life and hospitals expenditures.

Conclusion

The review of literature offered an insight into the investigated problem. The major findings allow concluding that the question of readmission rate reduction has gained substantial interest from scholars, but a viable solution for post-operative cancer patients has not been found yet. Overall, the combination of all articles findings provides some crucial data on the PICOT question. Further investigation should be focused on various age groups of patients and different readmission periods.

References

Mays, A. C., Worley, M., Ackall, F., DAgostino, R., & Waltonen, J. D. (2015). The association between gastrostomy tube placement, poor post-operative outcomes, and hospital re-admissions in head and neck cancer patients. Surgical Oncology, 24(3), 248-257.

Merkow, R. P., Ju, M. H., Chung, J. W., Hall, B. L., Cohen, M. E., Williams, M. V.,& Bilimoria, K. Y. (2015). Underlying reasons associated with hospital readmission following surgery in the United States. JAMA, 313(5), 483-495.

Socwell, C. P., Bucci, L., Patchell, S., Kotowicz, E., Edbrooke, L., & Pope, R. (2018). Utility of Mayo Clinics early screen for discharge planning tool for predicting patient length of stay, discharge destination, and readmission risk in an inpatient oncology cohort. Supportive Care in Cancer, 26(11), 3843-3849.

Stitzenberg, K. B., Chang, Y., Smith, A. B., & Nielsen, M. E. (2015). Exploring the burden of inpatient readmissions after major cancer surgery. Journal of Clinical Oncology, 33(5), 455-464.

Waller, A., Forshaw, K., Bryant, J., Carey, M., Boyes, A., & Sanson-Fisher, R. (2015). Preparatory education for cancer patients undergoing surgery: A systematic review of volume and quality of research output over time. Patient Education and Counseling, 98(12), 1540-1549.

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