Centers for Medicaid & Medicare Services: Evidence-Based Project

The Identified Healthcare Issue

One of the major goals of the Centers for Medicaid and Medicare Services (CMS) is the elimination of the level of hospital readmissions. With this aim, the CMS has introduced the disciplinary punishment for those healthcare establishments the readmission rates in which are greater than expected. The prospect of such a penalty poses a threat to many clinics that cannot cope with the readmission problem.

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The Importance of the Established Problem

It has been determined that the cost of avoidable readmissions in the class of individuals suffering from heart failure and diabetes in the US exceeds $14 billion every year. Singling out the causes of preventable readmission could promote a better organization and maintenance of clinical practice, regulations, systems, and programs.

The Present System

From the moment that penalties were introduced, the national average for readmission rates has decreased. However, approximately every fifth patient under Medicare that has been hospitalized tends to go back to the hospital within a thirty-day period.

The Effect of Background Circumstances

Not all of the determinants of readmission rates can be under the control of hospitals. For instance, such issues as the disease’s reappearance, the patient’s lack of comprehension of doctors’ recommendations, and the insufficient follow-up support cannot be controlled by healthcare institutions. The existent data testify that the most crucial place in the rates of readmissions belongs to social factors. In addition, the social vulnerability has been identified as the major underlying aspect. Variables determining avoidable readmissions are the patient’s age, beliefs, and cultural issues.

The PICO Question

The PICO question is composed of such elements as P (patient/problem), I (intervention/indicator), C (comparison), O (outcome) and is formulated as follows: “In Medicare patients with one-month hospital readmission (P), does one-week post-discharge observation of high-risk individuals by healthcare employees (I) compared to no categorization or post-discharge surveillance (C) lead to the decline in avoidable readmissions and, as a result, in the number of fines imposed on healthcare facilities (O)?”

The Evidence-Based Practice Question

Is the probability of undergoing the hospital readmission within a month after discharge in high-risk Medicare patients obtaining the follow-up intervention lower than in patients not receiving any follow-up observation?

Keywords and Search Parameters

The data on the research theme were collected with the help of the PubMed search engine. The inquiry was made employing such keywords as “readmission,” “Medicare,” “one month,” “a month,” and “30 days.” Further, the search was limited by such measures as the publication date (no older than five years), the full-text option, and free access.

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Types of Scholarly Sources and Their Number

With the help of search criteria, forty sources were located. Not all articles were research studies, some of them being reviews of literature, evidence-based research studies, opinions of experts, and qualitative studies.

Research Evidence

Out of all the located sources, two research articles were exploited for the project: one quantitative and one qualitative. The first article under consideration, titled “A patient navigator intervention to reduce hospital readmissions among high-risk safety-net patients: A randomized controlled trial,” is authored by Balaban et al. (2015). In their research, scholars analyze the population groups represented insufficiently in other studies, such as the homeless, non-elderly people, individuals suffering from dementia, patients who leave hospitals against medical service, and those who do not speak English. The population entity is composed of commonly underserved individuals and those coming from various ethnicities. Balaban et al. (2015) note that it is impossible to come up with a single productive approach to eliminating readmission rates for different population groups. Scholars remark that not only can investigations be culturally perceptive but they can also vary significantly depending on the participants’ age. Other factors to be considered when analyzing readmissions are mental illnesses and substance abuse since these conditions require more time to produce the necessary outcomes. Thus, scholars emphasize the need to establish specific methods of addressing various population groups in respect of hospital readmissions.

The second article under consideration is a qualitative exploration by Sentell et al. (2016) titled “Pathways to potentially preventable hospitalizations for diabetes and heart failure patients: A qualitative analysis of patient perspectives.” In this research, preventable hospitalizations for patients with diabetes are analyzed. The authors emphasize the significance of taking into account patient perspectives when studying the problem of readmissions. In particular, Sentell et al. (2016) conclude that there is not enough administrative data on patient outlook regarding avoidable readmissions. It is recommended to introduce innovative policies and partnerships to build connections between behavioral health and social services, which will lead to better management of the readmission problem.

Non-Research Evidence

Apart from research-based articles, non-research evidence was used to provide additional insight into the key problem of the project. The first of such non-research studies is the article “Understanding value-based incentive models and using performance as a strategic advantage” by Bosko, Dubow, and Koenig (2016). The authors remark that the system of fines and quality incentive campaigns put into action by the CMS are the crucial components of making the system of payment more value-based. According to Bosko et al. (2016), the programs implemented as a constituent of the Affordable Care Act will impact not only the bottom line of healthcare facilities but also their position on the market due to the clarity of outcomes. Therefore, scholars emphasize the significance of coming up with a practical approach to making the implementation of these solutions successful.

Bosko et al.’s (2016) article focuses on the advantages and disadvantages of the penalty system suggested by the CMS. In particular, three programs currently existing and governed by the CMS are the Hospital Readmissions Reduction Program (HRRP), the Value-Based Purchasing Program (VBP), and the Hospital-Acquired Conditions (HAC) (Bosko et al., 2016). Each of these policies manifests crucial changes in the compensation process of Medicare hospitals regarding services. Also, HRRP, VBP, and HAC reflect the way in which healthcare institutions manage and control the quality of their work. Out of the three programs in question, only the VBP initiative can boast having upside advantages in offering bonuses. What concerns the HRRP and HAC, they are roughly the programs based on the system of punishment for healthcare establishments that fail to comply with the requirements inaugurated by the CMS (Bosko et al., 2016).

The authors note that from the time fines were introduced, the level of readmission has dropped. Still, nearly one in five individuals are readmitted within the period of a month. Thus, according to Bosko et al. (2016), the penalty and incentive initiatives offered by the CMS have the potential to arrange the value-based care and increase the quality of citizens’ health. Under these programs, healthcare institutions’ financial performance is likely to increase, and their reputation and communication with various stakeholders, such as patients, employers, insurers, and the community, can enhance. Scholars conclude that it is crucial for hospital boards and managers to evaluate their institutions’ performance critically and analyze it in comparison with their rivals’ achievements (Bosko et al., 2016). Hospital authorities should make the necessary changes to enhance productivity and establish the culture of value with the aim of reducing readmission rates.

The second non-research piece of evidence is the memo “HCA implements potentially preventable readmission (PPR) adjustments” prepared by Wagner, Busz, Sanders, and Evert (2016). The authors of the bulletin aim to increase the employees’ awareness of the Health Care Authority’s (HCA) policy regarding readmission penalties. Ni particular, it is noted that the HCA would like its workers to be better informed about the aspects that can cause readmissions (Wagner et al., 2016). The reason behind such a proposal is that all American healthcare facilities started to have their Medicare compensation rates decreased in case they have a sufficient number of preventable readmissions. The reductions will be estimated based on the comparison between hospital readmission levels to the national rates (Wagner et al., 2016). Thus, it is noted that the HCA initiated the avoidable readmission campaign to make sure that all of its patients obtain the highest quality of care during the hospitalization. Moreover, the program aims at ensuring patients’ well-being upon leaving the healthcare facility.

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Wagner et al. (2016) remark that a supplementary element of care is needed, and it should involve such aspects as the revised mediation plan, the analysis of ambiguous issues, the forecast of potential complications, and the ways of avoiding them. To make the implementation of the new program easier, the HCA offers a combination of post-discharge services and doctor appointments (Wagner et al., 2016). In order to reach its goals, the HCA suggests sending copies of patient records to healthcare providers and designing individual care plans for all customers. It is noted that the team approach plays a crucial role in the process of reaching reduced readmission rates.

The Suggested Practice Modification

To decrease the rate of 30-day readmission, it is necessary to enforce a comprehensive analytical method. The initial step in this approach is the identification of the patient’s diagnosis. Further, the individual should be assisted during the whole process of treatment through the continuum of care. This continuum involves the quality of treatment the person receives at the healthcare institution, the discharge plan upon being admitted to the hospital, and the analysis and categorization of the patient as having a low or high risk for readmission. The application of these methods can lead to the creation of personalized care plans issues before discharge to impact the substantial change after discharge.

In the article “The influence of a postdischarge intervention on reducing hospital readmissions in a Medicare population” by Costantino, Frey, Hall, and Painter (2013), it is noted that post-discharge interventions can eliminate the possibility of hospital readmissions. The authors remark that at the beginning of the continuum of care, physicians need to be cautious when evaluating risk factors. On the basis of evidence, Costantino et al. (2013) conclude that diagnosis alone is not a sufficient reason for selecting the level of risk. Scholars argue that other aspects should be taken into consideration when analyzing the patient’s condition. This opinion is supported by Sentell et al. (2016) who note that avoidable hospitalization is affected by issues outside the common understanding of clinical factors, such as social aspects. Social factors include mental health problems, financial stability, patient support system, homelessness, substance abuse, and others (Sentell et al., 2016). Thus, it is vital to consider all of these aspects when establishing the risk level of the patient.

When identifying risk factors, such a tool as the LACE index may be useful. The specifications of this approach are analyzed in the article “Unplanned readmissions after hospital discharge among patients identified as being at high risk for readmission using a validated predictive algorithm” by Gruneir et al. (2011). The LACE index incorporates the following elements: the length of stay, the acuity of the patient’s admission, the comorbidity, and the number of emergency department visits over the past half year (Gruiner et al., 2011). With the help of this index, physicians can predict the risk of readmission or death of the patient within the nearest month (Gruiner et al., 2011). The major advantage of using the LACE index is that it allows analyzing the information and determining trends (Gruiner et al., 2011). Such data can be helpful when performing longitudinal research and implementing policies grounded on study results.

The identified approaches can serve as beneficial tools for those healthcare employees who perform the follow-up assessment of patients within seven days after discharge. With the help of the obtained data, physicians and nurses will be able to make their methods more effective and patient-centered. According to Constantino et al. (2013), a large portion of readmissions is the result of the low quality of care and insufficient transitional care. Thus, the establishment of the proposed approaches is likely to eliminate the readmission rates among patients eligible for Medicare.

The Major Stakeholders

The three most important stakeholders are the nurse manager, the quality insurance specialist, and the chief financial officer. The primary step in the implementation of the project will involve arranging a meeting of the key collaborators. During this meeting, the suggested alterations will be delineated in a concise and clear-cut way. The emphasis will be put on the fines that can be imposed on facilities exceeding the national average rate of readmissions. The report will be complemented by the evidence-based research indicating the potential of the proposed solutions to decrease the rates of readmissions.

Limitations

Obstacles to the implementation include financial expenses and the adaptation of employees to new duties. Costs will involve the salary for follow-up personnel and additional payments to other workers such as nursing case managers, floor nurses, and social workers. Also, there will be a need in costs related to designing or buying computer programs helping to evaluate the level of patients’ readmission risk as high or low.

Ways of Eliminating the Obstacles

In order to assess the potential means of reducing expenses, a cost-benefit analysis will be employed. Another cost-effective approach that might be helpful is searching the existing computer programs rather than paying for the new ones. Any alterations are challenging for a healthcare organization, so it is crucial to prepare employees and make sure that the process of changing will not be harmful to the hospital. A system of bonuses may be suggested to mark the achievements of the most productive staff members.

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Measuring Results

The measurement of the intervention’s success will be the decreased level of readmissions within a one-month period after discharge among Medicare patients that have been identified as having a high risk of readmission.

References

Balaban, R. B., Galbraith, A. A., Burns, M. E., Vialle-Valentin, C. E., Larochelle, M. R., & Ross-Degnan, D. (2015). A patient navigator intervention to reduce hospital readmissions among high-risk safety-net patients: A randomized controlled trial. Journal of General Internal Medicine, 30(7), 907-915.

Bosko, T., Dubow, M., & Koenig, T. (2016). Understanding value-based incentive models and using performance as a strategic advantage. Journal of Healthcare Management, 61(1), 11-14.

Costantino, M. E., Frey, B., Hall, B., & Painter, P. (2013). The influence of a postcharge intervention on reducing hospital readmissions in a Medicare population. Population Health Management, 16(5), 310-316.

Gruneir, A., Dhalla, I. A., van Walraven, C., Fischer, H. D., Camacho, X., Rochon, P. A., & Anderson, G. M. (2011). Unplanned readmissions after hospital discharge among patients identified as being at high risk for readmission using a validated predictive algorithm. Open Medicine, 5(2), e104.

Sentell, T. L., Seto, T. B., Young, M. M., Vawer, M., Quensell, M. L., Braun, K. L., & Taira, D. A. (2016). Pathways to potentially preventable hospitalizations for diabetes and heart failure: A qualitative analysis of patient perspectives. BMC Health Services Research, 16(1), 300.

Wagner, C., Busz, A., Sanders, C., & Evert, T. (2016). HCA implements potentially preventable readmission (PPR) adjustments. Web.

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StudyCorgi. (2021, July 10). Centers for Medicaid & Medicare Services: Evidence-Based Project. Retrieved from https://studycorgi.com/centers-for-medicaid-and-amp-medicare-services-evidence-based-project/

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"Centers for Medicaid & Medicare Services: Evidence-Based Project." StudyCorgi, 10 July 2021, studycorgi.com/centers-for-medicaid-and-amp-medicare-services-evidence-based-project/.

1. StudyCorgi. "Centers for Medicaid & Medicare Services: Evidence-Based Project." July 10, 2021. https://studycorgi.com/centers-for-medicaid-and-amp-medicare-services-evidence-based-project/.


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StudyCorgi. "Centers for Medicaid & Medicare Services: Evidence-Based Project." July 10, 2021. https://studycorgi.com/centers-for-medicaid-and-amp-medicare-services-evidence-based-project/.

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StudyCorgi. 2021. "Centers for Medicaid & Medicare Services: Evidence-Based Project." July 10, 2021. https://studycorgi.com/centers-for-medicaid-and-amp-medicare-services-evidence-based-project/.

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StudyCorgi. (2021) 'Centers for Medicaid & Medicare Services: Evidence-Based Project'. 10 July.

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