Answer

    Using Hospital Data to Reduce Readmissions

Patient readmission has significant financial implications for a hospital. It is imperative for a medical facility to keep data on the influential factors to patient readmissions which inform improvement strategies. This paper entails a literature review on how the hospital can use financial data to determine the areas of improvement to avert patient readmissions, thus saving millions for the medical facility.

Several factors affect the reputation of a medical facility and its financial stability. According to Ahmad et al. (2018), hospital readmissions have a negative financial implication on the quality of patient outcome and organizational reputation. Further, readmissions significantly drain the hospital of its resources. To a patient, readmissions have been proved to expose the individual to nosocomial infections and contribute to high-stress levels. Secemsky et al. (2018) concur with Ahmad et al. (2018) about the impacts of readmissions on a patient and the hospital and adds that most observations advocate reducing hospitals admissions as an effective strategy to not only enhance the quality of care but also lower the medical costs incurred. The Centers for Medicare & Medicaid Services (CMS) in March 2010 commissioned the Hospital Readmissions Reduction Program (HRRP) which penalizes hospitals for 30-day readmission rates that are higher than the predicted levels for particular clinical conditions (Hoffman & Cronin, 2015). It is, therefore, critical to explore how readmission financial implications data can be employed by a hospital to develop mitigation strategies that can enhance the quality of patient outcome which further translates to reduced organizational costs.

Use of Data to Improve Quality and Reduce the Readmission Rates

            Accurate, timely, and reliable data can be used to point out areas of improvement which then reduces the healthcare costs. This was established in a study by Wheeler (2017) on Allina Health which serves Western Wisconsin and Minnesota. In the organizational data-driven improvement approach, it was established that a profound data infrastructure is critical such as the enterprise data warehouse (EDW) coupled with analytics applications to provide data in the consumable form for quality decision making. Wheeler (2017) proposed a 10-step quality enhancement framework which entails phases such as determining the needs, identification of stakeholders, examining the current process, and setting objectives for the process improvement. Other steps include identifying the root causes and improvement barriers, developing and testing the improvement plan, and redesigning tests and monitoring results. In hospital readmissions, obtaining data on different variables including the costs of readmission, penalties made by the HRRP, and top healthcare conditions or procedures that cause readmissions aid in developing mitigation strategies.

            The analysis of comprehensive data on readmissions informs the prevention measures based on the profits by the organization. This was established by Postel et al. (2014) who conducted a retrospective review of patients’ database in 2012 to determine whether the patients readmitted within 30 days would have received a different treatment without readmission. This study while using the 2012 database revealed that there are different approaches which can be used to reduce the rate of readmissions. These include focusing on transitioning in care and post-discharge phases. The rates of readmissions can be examined based on 7, 15, or 30 days after discharge. According to Fingar, Barrett, and Jiang (2017), 30-day readmissions are higher as compared to 7-day. Important to note is that these readmissions differ based on the patient’s conditions. Drawing data from Bailey, Weiss, Barrett, and Jiang (2019), it can be shown that the average readmission costs for any diagnosis are $ 14000. This is as demonstrated in figure 1 below. Notably, this bar graph is developed based on 2016 data for the 30-day readmissions for different diagnosis.

Figure 1: Average costs for readmissions of various conditions (Bailey et al., 2017).

            The financial implications for the readmissions can be described by the expected payer. According to Fingar et al. (2017), Medicare is the most affected while the private insurers are the least affected. As demonstrated by the Agency for Healthcare Research and Quality (AHRQ) and the Healthcare Cost and Utilization Project (HCUP), the readmission rates per 100 inpatients stay for both the 7-day and 30-day readmissions can be summarized in table 1 below and the subsequent bar-graph (figure 2).

Table 1. 7 and 30-Day Readmission per Expected Payer (Fingar et al., 2017)

Figure 2: Readmission Rate per 100 Index Inpatient Stays

            The above data analysis demonstrates that the rates of rehospitalization have persisted despite the penalties placed on organizations. According to Boccuti and Casillas (2017), the majority of these readmissions are avoidable, and there is a difference in the readmission rates per hospital which implies that there are medical organizations where the patient has a high chance of being readmitted. These authors agree with Ahmad et al. (2018) that the readmissions are preventable through clarifying the discharge instructions for the patient, coordination between the care providers and physicians, and profoundly addressing the medical complications during the patient’s stay at the hospital. Presently, there are various incentives by Medicate to lower the readmission rates. Among the profound approaches is the HRRP which penalizes hospitals with high readmission rates. Based on the 2017 estimates, the HRRP have significant impacts on the hospitals and patients. Among the key findings from the 2017 findings include an increase in the readmission penalties by $ 528 million and 78% of the readmissions being in hospitals without readmission penalties or fines that are less than 1%. The effectiveness of the HRRP is challenged by the increased readmission rates from 2013 to 2017. As reflected in table 2 below, the CMS estimated costs of readmissions regardless of the minimum rate of penalty has been increasing. These costs if saved would have been used for other purposes including equipping the hospitals.

Table 2: CMS Estimated Penalties per Financial Year (Boccuti and Casillas, 2017)

Figure 3: CMS Estimate of Total Penalties per Financial Year

            Based on the above findings, it is evident that hospitals can save numerous finances by effectively implementing the readmission reduction approaches and observing the financial data such as penalties to establish the improvement points. In 2017 for instance, the hospitals would have saved a total of 528 million dollars through the implementation of effective readmission mitigation strategies. However, there is a need to determine how the identified readmission mitigation approaches in literature compare in reducing the healthcare costs. The importance of such a study is centered on the increased number of readmissions regardless of the HRRP implementation. This demonstrates that HRRP enough is not sufficient in addressing the readmission pandemic in hospitals (Hoffman & Cronin, 2015). Other approaches should, therefore, be explored including the effective collaboration among the healthcare providers, reduction of medical errors, and effective follow-up of the patient after discharge.

Leading Diagnosis and Procedure Readmissions

The rates of readmission differ based on the condition and procedure. According to the Healthcare cost and utilization project (HCUP) Statistical Brief (2010), the leading 30-day readmission rates by diagnosis are congestive heart failure, schizophrenia, and acute and unspecified renal failure while for the procedures, these conditions include lower extremity amputation, heart valve procedures, and wound debridement. Fingar et al. (2017) confirm these findings, and as reflected in table 3 below, congestive heart failure, schizophrenia, and respiratory failure are among the leading conditions with high readmission rates within 30 days. Based on these authors, also, both the 30-day and 7-day readmissions are highest among individuals covered by Medicare followed by Medicaid, uninsured, and lastly the private insurance. The importance of understanding the leading procedures and diagnosis for readmission is to develop intervention approaches that are specific to these conditions and procedures. A question or concern that arises from these readmissions is the reasons for the readmission costs being high among patients covered by Medicare. Also, it is essential to examine the reasons for the three leading conditions in readmissions and mitigation approaches.

Table 3: Leading Conditions for 30-day readmission (Fingar et al., 2017).

Figure 4: Pie-Chart Showing the 30-Day Readmission for the Top 3 Diagnosis

            In summary, hospital readmissions have a significant financial burden to an organization. In 2010, Medicare introduced the HRRP which penalizes hospitals with a high number of 30-day readmissions. Drawing from the above analysis, although there are effective measures to reduce the readmissions, they remain high as reflected in the 2013-2017 financial years. Based on the analysis also, it is evident that the rate of readmissions differs with the conditions. The principal diagnosis as established in the literature are congestive heart failure, respiratory diseases, and schizophrenia and other psychotic conditions. A research gap from the above analysis is conducting a study on the why readmissions remain high despite the HRRP penalizations and the specific factors that influence the high number of 30-day readmissions for the top three diagnosis and procedures.