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Community & Public Health Reducing Hospital Readmissions Among High-Risk Patient Populations

Community & Public Health Reducing Hospital Readmissions Among High-Risk Patient Populations

Historical Background
Readmissions to the hospital are associated with poor patient outcomes and high financial costs.
Readmissions are caused by a variety of factors, and rates vary greatly by institution.
3, 4 Historically, nearly 20% of all Medicare discharges resulted in a 30-day readmission.
1 According to the Medicare Payment Advisory Commission (MedPAC), 12% of readmissions are potentially avoidable. Even preventing 10% of these readmissions could result in a $1 billion savings for Medicare. As a result, reducing hospital readmissions has been designated as a national priority. MedPAC recommended to Congress in 2008 that the Centers for Medicare and Medicaid Services (CMS) begin reporting readmission rates and resource usage to hospitals and physicians in a confidential manner. 6 CMS started publicly reporting hospital-level readmission rates in 2009, which were then added to the Hospital Compare website. 7

Prior to 2012, there was little direct financial incentive for hospitals to reduce readmissions. Hospitals receive payment for inpatient stays for Medicare beneficiaries through the inpatient prospective payment system (IPPS). This payment, which is based on a diagnosis-related group (DRG), covers the inpatient stay as well as any outpatient diagnostic and admission-related outpatient non-diagnostic services provided by the institution on the date of the patient’s admission or within three days of the date of admission. 8 Notably, this payment excludes post-discharge care or interventions that may reduce the likelihood of readmission.
The ACA added section 1886(q) to the Social Security Act, establishing the HRRP, to provide direct financial incentives to hospitals participating in the IPPS to reduce readmission rates. The HRRP has required CMS to reduce payments to IPPS-participating hospitals with excessive readmissions since October 1, 2012. 9 Excess readmissions are defined by comparing a hospital’s readmission rates, adjusted for age, gender, and co-existing conditions, to national averages. 10 The penalty is calculated as a percentage of total Medicare payments to the hospital; the maximum penalty for 2013 is 1%, 2% for 2014, and 3% for 2015. CMS saves money by imposing penalties on hospitals. The savings are added to the Medicare Hospital Insurance Trust Fund, with the goal of protecting guaranteed benefits and providing new benefits and services to all Medicare beneficiaries, as well as lowering the cost of Part B premiums, according to the ACA. 11

The HRRP initially included acute myocardial infarction, heart failure, and pneumonia, but in 2015 it expanded to include patients with acute exacerbation of chronic obstructive pulmonary disease and patients admitted for elective total hip and total knee arthroplasty.

9 The primary discharge diagnosis, not the DRG assigned to the hospitalization, is used to identify conditions. Furthermore, for a diagnosis to be measured, hospitals must have at least 25 initial hospitalizations. Following that, public, and possibly financial, accountability is being extended to hospital-wide readmission rates. 10, 12 The HRRP’s policies are constantly being refined, including previous changes in the methodology used to calculate the hospital readmission adjustment factor and accounting for planned readmissions.

Visit: Methodology
Hospital performance is measured using risk-adjusted 30-day readmission measures. The risk adjustment measures, which have been approved by the National Quality Forum, are based on hierarchical logistic regression models. The models were developed with the help of Medicare claims data and validated with the help of claims and medical record data. The hospital risk-standardized 30-day all-cause readmission rates are calculated using these claims-based models. 13-15 The reported rates are comparable to the Hospital Compare rates, with the exception of readmissions to VA or critical access hospitals.
Community & Public Health Reducing Hospital Readmissions Among High-Risk Patient Populations
The excess readmission ratio, which is used to penalize hospitals, accounts for variations in hospital volume and case mix. In the numerator, hierarchical logistic regression models are used to calculate an adjusted actual number of readmissions and an expected number of readmissions. 16 The numerator is computed by estimating the likelihood of readmission for each patient at each hospital. This considers the hospital-specific effect, the likelihood of readmission for each patient, and the likelihood of readmission based on patient risk factors (age, gender, and selected clinical comorbidities). These probabilities are then averaged across all patients with the diagnosis in a hospital. The denominator is computed by adding the readmission probabilities for each patient at an average hospital using the same regression coefficients and the average hospital effect. As a result, the ratio compares the total predicted readmissions at a hospital to the total predicted readmissions if the patients were treated at a typical hospital with similar patients. The threshold established to define “excess” is greater than the average (i.e. ratio >1.0), and any ratio above that will result in a penalty; the actual dollar amount of the penalty is then calculated by dividing 1 minus the aggregate payments for excess readmissions by the aggregate payments for all discharges, and multiplying this “readmissions adjustment factor” by a hospital’s base DRG payment. 9

Hospital volume can be an important factor in determining hospital performance. Quality is determined by the amount of information available, which means that the fewer patients treated, the less data available; additionally, estimates for small hospitals may be more unstable due to their smaller sample size. Due to the volume criteria, many hospitals were excluded because only three conditions were included in the first two years. With the addition of more conditions in 2015, a greater number of hospitals are at risk of receiving a penalty, as have the dollars at stake.

Navigate to: Structure: Hospital Penalties
To fully comprehend the impact of HRRP, it is necessary to identify which hospitals are subject to penalties. In the first year of the HRRP (based on data from 2008 to 2011), 2,213 hospitals were fined $280 million for having excessive readmission rates; approximately 30% of eligible hospitals received no penalty, 60% received a penalty of less than 1%, and 10% received the maximum penalty. 17 This was approximately $10 million less than the initial estimate and represented 0.3% of total Medicare base payments to hospitals. In year two, 2,225 hospitals were fined $227 million, which amounted to 0.2% of total Medicare base payments to hospitals. 17 The average penalty decreased from 0.42% to 0.38% in the second year, with 1,371 hospitals receiving lower penalties and 1,074 hospitals receiving higher penalties. 17 The majority of hospitals that were penalized were large, teaching, and safety-net hospitals. 18 The majority of hospitals receiving penalties served low-income patients in both years. The most recent data for year three was released in August 2014, with penalties assessed to 2,610 hospitals. The average penalty rose from 0.38% to 0.63%, with 39 hospitals receiving the maximum penalty of 3%. 19 The addition of two conditions is one reason for the increased and extensive penalties.

Go to: Transitions of Care Processes
The HRRP has sparked a great deal of interest in determining the predictors and causes of readmission. However, the retrospective nature of diagnosis ascertainment, the relatively poor performance of readmission risk models20, and the wide range of causes of readmission have limited hospitals’ ability to target high-risk patients with tailored interventions. Regardless, many hospitals have spent significant time and money implementing a wide range of general transitional care interventions, such as arranging early discharge follow-up, reconciling medications, collaborating with other local hospitals or care facilities, and making follow-up phone calls.21

The HRRP does not provide hospitals with resources to fund readmission reduction interventions or care redesign. However, through complementary programs, CMS has provided additional funding for transitional care efforts. Section 3026 of the ACA established the Community-based Care Transitions Program (CCTP), which aims to test models for improving care transitions and lowering readmissions. 22 Notably, the CCTP directs $500 million only to hospitals that applied and were approved; there are currently 102 organizations in the program. Transitional Care Management Services introduced two new current procedural terminology (CPT) codes in January 2013. 23, 24 These CPT codes apply to services provided to patients whose medical or psychosocial issues necessitate moderate or high-complexity medical decision making during care transitions. This includes discharge from an inpatient hospital setting (acute hospital, rehabilitation hospital, long-term acute care hospital), partial hospitalization, hospital observation status, or skilled nursing facility to the patient’s community setting (home, domicile, rest home, or assisted living). While these codes provide a higher billing for post-discharge visits within 7 or 14 days of discharge (depending on the code), they go to the outpatient provider and thus do not help offset HRRP penalties unless inpatient and outpatient care are financially integrated. Similarly, CMS will start paying physicians for chronic care management services, incentivizing the coordination of inpatient and outpatient care. 25, 26

Go to: Readmissions Reduction Outcomes
Early data indicate that HRRP implementation is associated with a decrease in readmissions. According to recently released Health and Human Services data, the all-cause 30-day readmission rate among Medicare beneficiaries remained relatively stable from 2007 to 2011 at 19.0-19.5%; however, in 2012 and 2013, this rate fell to 18.5% and 17.5%, respectively (Figure). 27, 28 Between January 2012 and December 2013, these lower rates resulted in an estimated 150,000 fewer hospital readmissions. Although these positive trends could be due to any number of other changes that occurred during this time period, the temporal relationship suggests that the HRRP may be accomplishing its goal of reducing hospital readmissions and CMS spending.

An external file containing a picture, illustration, or other data.
Figure Medicare fee-for-service, all-cause, 30-day readmission rates (nihms682650f1.jpg).

Visit: Commentary
The HRRP has received both positive and negative feedback. Proponents of the program emphasize the overall engagement of hospitals and health care providers throughout the illness experience. During the program’s duration, readmission rates fell by about 1%, with no discernible increase in length of stay or mortality. However, there is still debate about the potential unintended consequences of readmission strategies, as well as the potential to penalize hospitals that serve vulnerable populations disproportionately.

Visit: Pros
Concentrate on Care Coordination Across Care Silos
The reliance on episode-based payments entrenched care silos, with acute care hospitals largely incentivized to get patients well enough to leave. Transitional care, communication of care plans with outside providers, and proper disposition were all downplayed. Today, these issues are front and center, with hospitals paying more attention to what happens after patients leave the hospital. The HRRP has aided in the formation of collaborative relationships—within hospitals, between medical institutions, and in surrounding communities—with the goal of improving the overall patient experience during and after hospitalization.

The HRRP has also raised national awareness and collaboration. One national quality initiative, Hospital to Home (H2H), began in 2009 with the goal of improving care transitions and reducing unnecessary readmissions. 29 The American College of Cardiology and the Institute for Healthcare Improvement continue to collaborate to provide a national clearinghouse of information and tools based on successful interventions at institutions. Similarly, the American Heart Association’s TARGET-HF program aims to improve the quality, care transitions, and outcomes of heart failure patients by providing resources and materials to healthcare professionals focused on heart failure awareness, prevention, and treatment. 30 The State Action on Avoidable Rehospitalizations is a multi-state initiative that brings together patients, families, payers, and policymakers to reduce rehospitalizations. 31 Other initiatives, such as Interventions to Reduce Acute Care Transfers, have focused on the post-discharge environment, with the goal of lowering readmissions from skilled nursing facilities. 32 The interest in successful transitional care strategies continues to grow, and national collaboration will help hospitals find the most practical and effective solutions. 33

The emphasis is on patient outcomes. Instead of a Few Care Procedures
Historically, many quality measures used for public reporting and pay-for-performance have focused on individual care processes. Properly constructed process measures have several important advantages: they have high face validity and do not require risk-adjustment, which adds credibility and interpretability. 34 However, process measures have several inherent limitations, including: 1) they apply only to those patients who qualify for the measure; 2) they assess only a small fraction of the routinely delivered processes of care; and 3) performance on many process measures can reach very high levels for all hospitals, such that they no longer discriminate among institutions. 35 Most importantly, there has been debate about the relationship between quality of care as determined by process performance measures and important patient outcomes. An analysis that compared patients who received heart failure processes of care to those who did not discovered that only beta blocker therapy—which is not currently used by CMS as part of the hospital quality measurement program—was associated with lower mortality, and even this one association was minor. 36 Another study discovered that, with the exception of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers prescribed at discharge, current heart failure performance measures have little relationship to patient mortality or rehospitalization in the first 60 to 90 days after discharge. 37

The shift to an outcome measure focusing on risk-standardized hospital readmission rates has several appealing features. A patient-centered outcome measure, such as readmission, focuses on what is important to patients, caregivers, payers, and society. Rather than selecting a few care processes from the thousands that occur during a hospitalization, outcomes measures, when carefully constructed and fairly adjusted for case mix, can better reflect a health system’s overall performance. This incentivizes providers and hospitals to prioritize care design that is felt to be most important (rather than just what can be easily measured), avoiding a one-size-fits-all approach.

Readmission for Any Reason vs. Disease-Specific Readmission
The emphasis on all-cause readmission versus disease-specific readmission has been a source of contention. According to reports, the reasons for readmission vary and are less frequently related to the condition that led to the index hospitalization. In one study of Medicare fee-for-service data from 2007 to 2009, only 35%, 10%, and 22% of heart failure, acute myocardial infarction, and pneumonia patients were readmitted within 30 days for the same condition as the index hospitalization, respectively. 38 The emphasis on all-cause readmission rates incentivizes hospitals to focus on a patient’s comorbid, psychological, social, and environmental conditions in addition to the primary medical problem. Hospitals have focused on transitional care measures as part of the HRRP in order to improve total care delivery. Patients benefit from better communication between inpatient and outpatient providers, a smoother transition from hospital to home, and the possibility of avoiding an unnecessary hospitalization.

Index for balancing length of stay with readmission risk
Variation in the length of stay for the index hospitalization has been one of the more noticeable inter-hospital differences. This could be related to readmission. Countries with longer hospital stays for heart failure appear to have lower rates of readmission within 30 days. The average length of stay in a large contemporary acute heart failure trial conducted across 27 countries ranged from 4.9 to 14.6 days (6.1 days in the U.S.). There was an inverse relationship (r=-0.52) between country-level mean length of stay and readmission. 39 Across all study sites in the United States, similar trends were observed. Longer index hospitalizations consume more resources and keep patients away from home; however, there appears to be a trade-off in terms of readmission rates. The HRRP supplements IPPS-DRG-based reimbursement incentives in the current system, balancing the desire to limit unnecessarily long hospital stays while discouraging unnecessary readmissions due to premature discharge.

Moving Away from the Fee-For-Service Model
Medicare has established specific goals for alternative payment models and value-based payments for the first time. Medicare intends to tie 85% of all Medicare fee-for-service payments to quality or value by 2016, and 90% by 2018. 40 Because of the ACA’s increased emphasis on improving outcomes, expanding access to care, and lowering costs, many payment providers are shifting away from the fee-for-service model and toward an outcome-based payment model. Accountable care organizations (ACOs) are one example of this model, in which providers and health care organizations share accountability. The Medicare Shared Savings Program and the Pioneer Model provide incentives for ACOs to manage care coordination and other factors influencing readmission rates. There are already examples of ACOs reducing readmissions. Kaiser Permanente, for example, has demonstrated a reduction in 30-day all-cause readmission rates through transitional care programs and bundling elements. 41 Similarly, Colorado’s Accountable Care Collaborative, which tests health-care payment and delivery reforms through Medicaid, demonstrated 8.6% fewer hospital readmissions than non-participating Medicaid enrollees in its first year. 42

ACOs are far from ideal. One source of concern is the conflicting incentives between ACOs and the HRRP, which reduces the impact of both. ACOs must decide which quality measures are most important given limited resources. Choosing how to prioritize these will necessitate ACOs balancing those in greatest need versus those most likely to benefit. However, it is expected that the incentives provided by ACOs and HRRP will be complementary, promoting the development of readmission-reducing interventions. CMS issued a proposed rule on July 3, 2014, that would add new quality reporting measures to the Medicare Shared Savings Program, such as all-cause unplanned admissions for patients with heart failure and all-cause unplanned admissions for patients with multiple chronic conditions. These changes to the quality reporting standard for the 2015 reporting period will bring the Medicare Shared Savings Program even closer to the HRRP. 43

Visit: Cons Potential to Disproportionately Penalize Hospitals Serving Poor People
Despite the aforementioned successes, there has been much debate about the methodology for calculating excess readmissions. The initial risk-adjustment models did not take socioeconomic status into account. Several studies have found that caring for patients with lower socioeconomic status puts a hospital at a higher risk of fines. 18, 44, 45 This means that the HRRP may be unintentionally removing resources from hospitals that serve disadvantaged populations, such as safety-net hospitals. The National Quality Forum convened an expert panel that concluded that not accounting for socioeconomic factors could exacerbate disparities by penalizing these hospitals. 46 MedPAC proposed comparing hospitals to other hospitals with patients of similar socioeconomic status in their June 2013 Report to Congress to account for the differences seen in current computation strategies, but the implementation of these suggested changes and approaches to risk adjustment have yet to take shape. 10, 47

Potential to Reduce Required Readmissions and Increase Mortality
The reported relationship between readmission and mortality measures has received a lot of attention. According to a brief report based on Hospital Compare heart failure data, there is a statistically significant inverse correlation between higher risk-standardized hospital 30-day readmission rates and lower risk-standardized hospital 30-day mortality rates. 48 A more detailed analysis of hospital-level risk-standardized readmission and mortality rates revealed a modest inverse relationship between mortality and readmission rates in heart failure (correlation coefficient -0.14), but not across the entire range of performance; there was no relationship in the acute myocardial infarction and pneumonia rates. 49

There are several possible explanations for why readmission and morality data in heart failure are inversely related. One theory is that some hospitals have a lower admission and readmission threshold; these hospitals may hospitalize lower-acuity patients (which is not entirely accounted for by the risk-standardization process), resulting in higher readmission rates and lower mortality rates. Regional differences in all-cause readmission rates have been found to be significantly associated with all-cause admission rates. 50 Another explanation is that hospitals with higher mortality rates have fewer patients who need to be readmitted. A high-risk patient who dies in the hospital is ineligible for the readmission measure, and a patient who dies at home shortly after being discharged from the index episode of care is never readmitted. As a result, a lower readmission rate could be the result of increased mortality.

However, it is the lack of association, rather than the inverse association, that is perhaps most noteworthy. There are nearly as many hospitals with concordant (low-low and high-high) risk-standardized readmission-mortality rates as there are with discordant (high-low and low-high) rates. This implies that the domains of readmission and mortality are largely unrelated, and that mortality and readmission are caused by somewhat different causes, and thus respond to different interventions. There are plausible explanations for the distinction between the quality domains of mortality and readmission. Transitions of care interventions, for example, and the use of hospice are more likely to reduce readmissions; in contrast, code teams and the implantation of defibrillators are more likely to improve survival. The Hospital Compare website includes both mortality and readmission rates;7 however, these measures do not occur at comparable rates and are not equally important to patients, so the current side-by-side reporting is flawed.

Root Cause Attribution Issues
Many readmissions, according to institutions and providers, are the result of disease progression and patient behaviors. “Why should my institution be punished if a patient with heart failure leaves the hospital, falls, and breaks her hip?” is a common example. If this is truly a random event, it should have no effect on the variability of risk-adjusted institutional rates on average. Many events, including hip fractures, may, however, be avoidable. Why did the patient collapse? Did she have a physical therapy evaluation prior to discharge, and did she have adequate home support? Was she overly diuretic or overly sedated? Care systems, if appropriately incentivized, can theoretically identify and address many of these contributing factors, avoiding some unnecessary readmissions. While specific attribution for individual cases may be difficult to assess, risk-standardized summary measures should ideally reflect comprehensive differences in care at the institutional level.

The key question for the outcome measure is not whether a single readmission is appropriate, but whether hospital-level variations in readmission rates are caused by preventable events. While truly avoidable readmissions are common (as few as 12% of hospital admissions may be truly avoidable51), they are also, by definition, relatively invariable, and thus should contribute little to differences in risk-standardized readmission rates. The HRRP’s goal is to incentivize care processes that reduce preventable events and, as a result, overall readmission rates. It is debatable whether the variation in risk-standardized readmission measures reflects significant differences in quality or other inappropriate avoidance of readmission. The more than two-fold variation in risk-standardized readmission rates across institutions appears to be a strong argument that many readmissions are avoidable. A number of existing interventions to improve the hospital transition process (e.g., medication reconciliation, transition coaches, and early follow up) have been shown to reduce overall readmission rates. However, studies have consistently found that a significant minority of readmissions are due to modifiable causes such as medication errors, noncompliance with recommended therapies, and failure to obtain timely ambulatory follow up. 52

Window of Arbitrary Time
Decisions about how long after discharge a new admission should be counted as a readmission have also been criticized.
53 Readmissions closer to the index hospital discharge are more likely to be related to inpatient care quality and transition measures provided. As a result, 30-days was chosen as the time frame for defining a readmission, recognizing that there is little difference between a hospitalization occurring 29 days after the last hospital discharge and one occurring 31 days after the last hospital discharge. Some have proposed weighting the HRRP penalties based on readmission timing, with a greater emphasis on earlier readmissions. Readmissions within the first few days after discharge may reflect poor care coordination or an insufficient recognition of post-discharge needs, whereas readmissions four weeks later are more likely to be due to the underlying severity of a patient’s disease or events beyond the hospital’s control. Hospitals that care for sicker or more socioeconomically vulnerable populations would be more heavily rewarded for improvements in discharge planning and care coordination to prevent short-term readmissions, with lower penalties for the fact that their patients may require additional hospital services in the long run. 54

Contentious Inclusions and Exclusions
All unplanned readmissions within 30 days of hospital discharge are included in the HRRP. Only two procedures were considered planned readmissions in fiscal year 2013 and had no impact on the readmission measure: Patients with acute myocardial infarction who later underwent coronary artery bypass graft surgery, and patients with acute myocardial infarction who later underwent percutaneous coronary intervention. This initial algorithm penalized hospitals for any other planned admission, including procedures such as implantable cardioverter-defibrillators (ICD) in patients with heart failure. Many planned readmissions, such as ICD placement, represent high-quality care and should not be used to penalize hospitals. In response, CMS implemented an algorithm in fiscal year 2014 to account for a broader range of planned readmissions. 9

Furthermore, a number of patient groups are excluded from the readmissions measure. Patients admitted under observation status, for example, are not eligible. As a result, many hospitals have created clinical decision units, which are typically short-stay observation areas linked to emergency departments and designed to care for patients for less than 24 hours. While the option of streamlining care for patients who are unlikely to require admission is appealing, there is little evidence that using clinical decision units has reduced acute care utilization, let alone readmission rates. There has only been a minor increase in observation stays following hospitalization for acute myocardial infarction, heart failure, and pneumonia. 55 However, there has been a significant increase in emergency department visits following heart failure hospitalizations. 55 Furthermore, there are concerns about inappropriate patient selection, prolonged observation time, and increased out-of-pocket expenses if patients are eventually admitted to a skilled nursing facility when clinical decision units are used. 56 With efficient use of a clinical decision unit, a hospital also risks removing low-risk patients from the excess readmission denominator.

The Risk of Ignoring the Impact of Hospitalization
With most efforts aimed at reducing readmissions, it is possible to overlook the stress and vulnerability that patients face. An acquired “post-hospital syndrome” has been defined as a period of transient vulnerability and a generalized risk of adverse health outcomes among recently hospitalized patients. 57 Patients undergo significant stress as well as disruption of their normal physiologic systems while in the hospital. While transitional care measures focus on the time between inpatient and outpatient care, there is less emphasis on the hospitalization itself. One article suggests interventions to reduce the trauma experienced by hospital patients, such as ensuring adequate rest and nutrition, encouraging activity, eliminating unnecessary testing and procedures, and reducing random medication changes. 58 A focus not only on transitional care, but also on the hospitalization itself, may aid in reducing post-discharge syndrome and its potential to increase readmissions. 58

Visit: Recommendations
The HRRP is just the beginning. Fairness is essential in any quality measurement, as it is in any other. As a result, validation of the risk-standardization process is required and ongoing. This must include additional research into the nuanced relationship between readmission rates and socioeconomic factors, which are currently not considered in risk adjustment methodology. This was done on purpose, as additional socioeconomic adjustment could mask existing disparities in care experienced by disadvantaged populations. In contrast, failing to account for the socioeconomic environment unfairly penalizes hospitals that serve disadvantaged populations, widening care disparities. Thus, reporting rates that include and exclude socioeconomic status at the same time may be more informative than picking one measure or the other.

Due to limitations in existing administrative data and concerns about coding manipulation, the current approach is forced to combine necessary and unnecessary readmissions and rely on aggregate rates to reflect potentially preventable events. Improvements in health information technology should make it easier to incorporate more clinical detail, allowing for more targeted assessment of preventable readmissions and a better ability to risk adjust. Iterative improvements to outcome measures are essential for their success.

Furthermore, while outcomes measures have the advantage of reflecting the entire domain of care preceding an event, CMS does not recommend specific actions to improve them. Then, providers, hospitals, researchers, and policymakers must identify flaws in care processes and implement targeted solutions. Programs such as the H2H Initiative,29 TARGET:HF,30 and the Aligning Forces for Quality Network,59 which aim to share best practices among institutions and improve care transitions, are an important approach. A thorough examination of outliers—hospitals with high-high, high-low, low-high, and low-low risk-standardized mortality and readmission rates—promises to uncover some of the causes of variation in outcomes. 60 Finally, more research is needed to develop more targeted, efficient, patient-centered interventions to improve care transitions and patient outcomes. The HRRP has focused attention and energy on such endeavors.

For the time being, measuring, reporting, and penalizing risk-standardized readmission rates are critical components of efforts to improve the overall quality and efficiency of hospitalized patients’ care. If the variability in hospital-level risk-standardized readmission measures is fairly adjusted for case mix, it should primarily reflect the continuum of care delivery following hospital admission—inpatient, transitional, and early outpatient follow-up. Furthermore, the HRRP focuses its efforts on the critical and complicated process of care transitions. Finally, it helps realign financial incentives to better reward the entire process of care; until 30-day bundled payments or ACOs replace the current fee-for-service structure, readmission metrics are a necessary complement to the IPPS-DRG-based system. The HRRP and similar policies provide a foundation for a more integrated, patient-centered, and value-based system.
After reviewing Module 2: Lecture Materials & Resources, you will select a diagnosis among high-risk patient populations that are commonly readmitted to the hospital. Prepare a work that examines the rationale for readmissions among this population and provide evidence-based interventions for reducing hospital readmissions in this population.

Submission Instructions:

The submission is to be clear and concise and students will lose points for improper grammar, punctuation and misspelling.
The submission is to be 5 pages in length:
Title (Page 1)
Abstract (Page 2)
Body (Pages 3-4, 1000 words total)
Reference Page (Page 5)
Incorporate a minimum of 3 current (published within the last five years) scholarly journal articles or primary legal sources (statutes, court opinions) within your work. Journal articles and books should be referenced according to APA style (the library has a copy of the APA Manual).
Your work should be formatted per APA and references should be current (published within last five years) scholarly journal articles or primary legal sources (statutes, court opinions)

Rector, C. & Stanley, M.J. (2022).
Chapter 6 – Structure and Economics of Community Health Services
Chapter 7 – Epidemiology in Community Health Care
Chapter 8 – Communicable Disease Control
Chapter 9 – Environmental Health and Safety
The Healthcare System of the United States (00:07:35)
Healthcare Triage (2014, February 17) Healthcare System of the United States [Video] YouTube.

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