Value Proposition/Contribution to My Professional Interests/Goals The project will help develop my data analysis skills for quality improvement in various care settings. Background: Review of the Literature
Place Your Order NowValue Proposition/Contribution to My Professional Interests/Goals The project will help develop my data analysis skills for quality improvement in various care settings. Background: Review of the Literature
Value Proposition/Contribution to My Professional Interests/Goals
The project will help develop my data analysis skills for quality improvement in various care settings.
Background: Review of the Literature
| Authoritative Source (APA Format) | How the Source Directly Relates to the Problem (One-Sentence Summary) |
| Lassemo, E., Myklebust, L. H., Salazzari, D., & Kalseth, J. (2021). Psychiatric readmission rates in a multi-level mental health care system–a descriptive population cohort study. BMC Health Services Research, 21(1), 1-15. https://doi.org/10.1186/s12913-021-06391-7 | This source shows that the problem of hospital readmission exists globally and at different rates. |
| Phillips, M. S., Steelesmith, D. L., Campo, J. V., Pradhan, T., & Fontanella, C. A. (2020). Factors associated with multiple psychiatric readmissions for youth with mood disorders. Journal of the American Academy of Child & Adolescent Psychiatry, 59(5), 619-631. https://doi.org/10.1016/j.jaac.2019.05.024. | Explores factors connected with psychiatric readmissions and units of measurements. |
| Kim, B., Weatherly, C., Wolk, C. B., & Proctor, E. K. (2019). Measurement of unnecessary psychiatric readmissions: a scoping review protocol. BMJ Open, 9(7), e030696. http://dx.doi.org/10.1136/bmjopen-2019-030696 | This source analyzes the ethical consideration around psychiatric readmissions, such as unnecessary readmissions. |
| Benjenk, I., & Chen, J. (2018). Effective mental health interventions to reduce hospital readmission rates: a systematic review. Journal of Hospital Management and Health Policy, 2. https://doi.org/10.1016/j.jaac.2019.05.024 | This source highlights the existence of the problem and some strategies to reduce it. |
| Morel, D., Kalvin, C. Y., Liu-Ferrara, A., Caceres-Suriel, A. J., Kurtz, S. G., & Tabak, Y. P. (2020). Predicting hospital readmission in patients with mental or substance use disorders: a machine learning approach. International Journal of Medical Informatics, 139, 104136. https://doi.org/10.1016/j.ijmedinf.2020.104136 | The source also indicates that the problem is common and discusses ways of predicting hospital readmissions. |
| Edgcomb, J. B., Sorter, M., Lorberg, B., & Zima, B. T. (2020). Psychiatric readmission of children and adolescents: a systematic review and meta-analysis. Psychiatric Services, 71(3), 269-279. https://doi.org/10.1176/appi.ps.201900234 | A systematic review that explored the readmission rates of children and adolescents with mental health challenges. |
Conclusion
Hospital readmission among patients with mental illness is a common problem that needs solutions. Analyzing data existing in the institutions can be key in addressing this problem. In addition, it is important to identify key performance indicators associated with the problem to help address the problem.
References
Benjenk, I., & Chen, J. (2018). Effective mental health interventions to reduce hospital readmission rates: a systematic review. Journal of Hospital Management and Health Policy, 2. https://doi.org/10.1016/j.jaac.2019.05.024
Edgcomb, J. B., Sorter, M., Lorberg, B., & Zima, B. T. (2020). Psychiatric readmission of children and adolescents: a systematic review and meta-analysis. Psychiatric Services, 71(3), 269-279. https://doi.org/10.1176/appi.ps.201900234
Kim, B., Weatherly, C., Wolk, C. B.,
Order Now
