A graduate project submitted in partial fulfillment of the requirements
For the degree of Master of Public Administration,
Health Administration
___________________________________________ _______________
California State University, Northridge
by
Master of Public Administration, Health Administration
The Hospital Readmission Reduction Program was introduced in 2012 as part of the
Affordable Care Act. The program's primary purpose is to reduce the number of patients
readmitted into the hospital within 30 days of their discharge date. HRRP was implemented to
help lower readmission rates, but that was not always the case. Many non-safety net and private
hospitals, which served patients with better insurance and income, had better readmission rates.
The hospitals that struggled with being penalized were safety-net hospitals and hospitals that
helped patients with different social determinants. These social determinants included patients
with housing troubles, income issues, disability issues, transportation issues, language barriers,
and so on. This study is a qualitative analysis of different peer-reviewed articles that focus on
safety-net hospitals and social determinants in healthcare. Based on the findings, safety-net
hospitals are being penalized more often than non-safety net hospitals because they serve many
patients. In addition, patients from different social determinants are more likely to be readmitted
to hospitals from the same condition. Barriers such as homelessness, transportation, lack of
internet should also be considered because they can impact what type of health care a patient has
access to and receives. Overall, taking a look at studies regarding safety net hospitals and
different social determinants can help decrease the readmission rates for hospitals.
1
Introduction
The United States healthcare system is considered to be very complex. It is also
expensive and can cost the U.S trillions of dollars. U.S. healthcare spending grew by 4.6% in
2019, reaching $3.8 trillion or $11,582 per person (CMS.gov, 2020). Health insurance is also a
massive factor in the U.S. healthcare system. Many different private and public institutions pay
for the healthcare of U.S. citizens (Burg, 2019). Private health insurance is usually obtained by
patients who can afford it. A few examples of private health insurance include Blue Shield,
Health Net, Cigna, and so on. The public sector in the United States is under the Affordable Care
Act (ACA), enacted on March 23, 2010, by President Barack Obama (Rapfogel et al., 2020).
Medicare is a federal health insurance program for patients 65 and older or with specific
disabilities (Burg, 2019). Medicaid is a state-based insurance program for people with low
income (Burg, 2019). Unfortunately, according to the U.S. Census, about 46 million people did
not have health insurance in 2007 (Burg, 2019). The ACA aimed to expand health coverage to
uninsured individuals (Rapfogel et al., 2020) and improve healthcare quality.
Healthcare programs can measure the quality of care a patient receives in a hospital. One of
those programs is the Hospital Readmissions Reduction Program (HRRP), which aims to reduce
the number of times a patient is readmitted to a hospital within 30 days after discharge for the
same health issue initially admitted (Mcllvennan et al., 2016). The HRRP was introduced in
2012 as part of the ACA (Mcllvennan et al., 2016). The conditions and procedures that are
covered under HRRP include Acute Myocardial Infarction (AMI), Chronic Obstructive
Pulmonary Disease (COPD), Heart failure (HR), Pneumonia, Coronary Artery Bypass Graft
(CABG) surgery, Elective Primary Total Hip Arthroplasty and/ or Total Knee
2
Arthroplasty(Cagliostro, 2021). Its primary purpose is to improve the quality of care the patients
receive in the hospital. High-quality care eliminates the need for a patient to be readmitted to a
hospital. HRRP was embedded in the ACA to reduce costly hospitalizations because many
patients were being readmitted to the hospital for the same diagnosis that they were admitted for
the first time. Readmission costs the hospital a net loss of their profits due to the unwillingness
of insurance companies to reimburse their beneficiaries (Mcllvennan et al., 2016). HRRP
introduces financial penalties to institutions when they fail to reduce the number of patients
readmitted within 30 days of their discharge (Mcllvennan et al., 2016).
Throughout the year, different issues have been pointed out with HRRP. One of those
issues is that HRRP is not entirely compliant with safety-net hospitals and patients from various
social determinants. HRRP needs to look at individual safety-net hospitals and consider adjusting
the program for those hospitals. Safety net hospitals usually serve minority groups, Medicaid
patients who are dually enrolled, disabled patients entitled to Medicare, and housing instability
patients (Hsuan & Ponce, 2020). Ultimately, the Hospital Readmissions Reduction program
needs to be adjusted for different social determinants and safety-net hospitals, as various social
determinants affect the results of HRRP. This study aims to see how HRRP can be changed for
in safety-net hospitals and help serve marginalized individuals. The report focuses on HRRP and
how different hospitals have conducted studies associated with HRRP and its effects.
3
Methodology
This research study is a qualitative analysis of data from peer-reviewed journal articles.
The academic databases used to search for peer-reviewed articles were One Search, CSUN
Library, ProQuest, BioMed Central, PubMed, Google Scholar, JAMA Network. The non-peer-
reviewed database that was used was the CDC website. The search keywords were Hospital
Readmission Reduction Program (HRRP): “Hospital Readmission Reduction Program,”
“HRRP,” “safety-net hospitals,” “social determinants,” and other various combinations of these
keywords. Search filters were used to narrow down the results. These filters included the English
language, peer-reviewed articles, articles dated from the last ten years, and the newest articles on
top. The specific themes included articles regarding various social determinants, safety-net, and
non-safety-net hospitals. Reports had to be published within the past ten years to be included.
After some time, I started to focus on specific wording, making it easier to find reports. The
particular vocabulary included “Hospital Readmission Reduction Program,” “HRRP,” “social
risk factors,” “social determinants,” “safety-net hospitals,” “non-safety hospitals,” “health
conditions.” A total of thirty-five articles were considered after reading the title and the abstract.
After a full-text review, a total of twenty-seven articles were finalized for use for this qualitative
study.
4
Literature Review
Many studies have been conducted to help determine what HRRP needs to consider to
improve the program for different social determinants and safety-net hospitals. Social risk factors
are also another component that impacts the program, and changes need to be considered. Non-
safety net and safety-net hospitals serve different patients, and these factors affect HRRP.
Overall, the Hospital Readmissions Reduction Program will need to be adjusted to better serve
patients in safety-net hospitals. High-quality care eliminates the need for a patient to be
readmitted to an institution.
Safety-Net Hospitals
Throughout the years, different issues have been pointed out with HRRP. One of those
issues is that HRRP is not entirely compliant with safety-net hospitals. Safety net hospitals
usually serve minority groups, Medicaid patients who are dually enrolled, disabled patients
entitled to Medicare, and housing instability patients (Hsuan & Ponce, 2020). Hospitals that
serve more financially disadvantaged patients have higher readmission rates. Ultimately, the
Hospital Readmissions Reduction program needs to be adjusted for different social determinants
and safety-net hospitals. According to Sezgin Ayabakan & Indranil Bardhan (2021), HRRP
needs to focus on three crucial components: improving hospital quality, reducing cost, and
improving the patient experience. Studies have been conducted and written about determining
what HRRP needs to implement to improve the program for different safety-net hospitals. Non-
safety net and safety-net hospitals serve different types of patients, and these factors affect the
HRRP. Overall, the Hospital Readmissions Reduction Program will need to be adjusted to
better fit patients in safety-net hospitals and other social determinants.
5
Popescu (2019) focuses on comparing three Safety-Net Hospital (SNH) Definitions and
Association with Hospital Characteristics. SNH’s can be defined as public hospitals, academic
medical centers, or private hospitals that usually serve vulnerable populations and are under
more significant financial stress than non-SNHs (Popescu, 2019). The study's objective was to
examine characteristics of SNHs as classified under three standard definitions (Popescu, 2019).
The study used a cross-sectional analysis that included noncritical access hospitals in the
Healthcare Cost and Utilization Project State Inpatient Databases from 47 US states for 2015,
linked to the Centers for Medicare & Medicaid Services Hospital Cost Reports and the American
Hospital Association Annual Survey (Popescu, 2019). The data were analyzed from March 1
through September 30, 2018 (Popescu, 2019). It was found that different safety-net hospital
definitions were used to identify hospitals with other characteristics and financial conditions. In
addition, they used a new Disproportionate Share Hospital payment formula, which accounts for
uncompensated care, leading to redistributed payments across hospitals (Popescu, 2019).
Social Determinants
Patients from different social determinants can impact how successful a hospital is in
regard to readmission rates. Joynt Maddox (2019) focuses on how Medicare's HRRP does not
account for social risk factors in risk adjustment, leading to penalizing safety-net hospitals. The
study's objective was to determine the impact of adjusting for social risk factors on HRRP
penalties. The findings concluded that poverty, disability, housing instability, residents in
disadvantaged neighborhoods, and hospitals had higher readmission rates. The article stated a
retrospective cohort study that included data from Medicare beneficiaries with AMI, congestive
6
heart failure, and pneumonia (Maddox, 2019). When social risk factors were added to risk
adjustments, penalties were cut in half (Maddox, 2019). By looking at the study's specific social
risk factors, it is determined that HRRP does not cover all health conditions.
Kathleen Carey (2016) states that even though HRRP has made a difference in safety-net
hospitals, some modifications need to be made to the penalty. The study focused on seeing if
HRRP has been a valuable tool for reducing the 30-day readmission in safety-net hospitals. In
the first three years of the program, the readmission rate had decreased by 2.86 points for heart
attack patients, heart failure was 2.78 percentage, and pneumonia by 1.77
percentage. The penalty policy should be adjusted because all hospitals are different, and they
want an approach that is a tad bit more flexible (Carey, 2016). Hospitals will keep being
penalized if HRRP does not focus on different socioeconomic statuses.
According to Joanna Jiang (2016), assessing the mortality performance of SNHs using all-
payer databases and measures for a broad range of conditions and procedures is another
important factor. The study consisted of 1891 urban, nonfederal, general acute hospitals in 31
states (Jiang, 2016). It appeared that safety-net hospitals performed equally well as other
hospitals in medical and surgical mortality measures (Jiang, 2016). Therefore, policymakers
should continue to monitor the quality of care in safety-net hospitals so that it does not decline
over the years.
Mouch (2013) focuses on the quality of surgical care in safety-net hospitals. Not much data
has been collected to determine if surgical care quality is higher in non-safety net hospitals than
in safety-net hospitals. A systematic review of published literature was performed to help
resolve this study. The search included 1,556 citations from different databases, and 86 were
7
eligible for the survey (Mouch, 2013). In conclusion, it seemed like safety net hospitals did not
rate as high as non-safety net hospitals for timeliness and patient-centeredness. Even though the
data was limited for this study, it still seems like the quality of care needs to be improved for
safety-net hospitals regarding surgical care (Mouch, 2013). Another article mentions that
readmission after hospitalization is costly and potentially preventable (Lucas &Pawlik, 2014).
Safety net hospitals tend to serve patients with different social risk factors and, for that reason,
may have higher readmission rates compared to non-safety-net hospitals. Some of these social
risk factors include income, housing situation, access to preventative health care.
It was essential to examine the trends in disparities of quality of care between hospitals
with high and low percentages of Medicaid patients (Werner, 2008). About 3665 hospitals were
included in the final analysis, and it seemed like hospitals with high ratios of Medicaid patients
had a worse performance rate in 2004. Thus, just like the other articles, it looks like those safety-
net hospitals did score lower than non-safety-net hospitals. It was also concluded that safety-net
hospitals might not get the economic benefits from public reports and pay for others hospitals'
performance (Werner, 2008).
Racial disparities also make a difference in readmission rates between black and white
patients with safety-net and non-safety net hospitals after HRRP. In the study by Krisda H.
Chaiyachati (2018), a cohort study was conducted of Medicare data which consisted of 58.2
million hospital patients discharged from 2007 to 2015. It is evident from the study by
Chaiyachati (2018), that black patients had more readmission rates in safety-net hospitals.
Similarly, there was a big difference in the non-safety net hospitals between black and white
patients (Chaiyachati, 2018). Overall, it looks like after HRRP was put into place, the racial
8
disparities have grown between the safety net and non-safety hospitals (Chaiyachati, 2018).
Ye et al. (2019), focused on a study that would determine two main objectives regarding HRRP.
The first objective was to examine the combined effects of multiple 90-day readmission
predictors, and the second objective was to determine if there was a difference in geospatial,
social demographic, and clinical characteristics (Ye et al., 019). They compared patients
readmitted within 90 days after discharge and those who were not (Ye et al., 2019). Social
determinants included in the study were age, sex, length of stay (LOS), the distance of patients
home to the hospital based on zip codes, diagnosis, insurance, discharge unit, and discharge
disposition (Ye et al., 2019). The results from the study showed that older male patients had a
longer LOS and severe illness, patients from labor and delivery were less likely to be readmitted
(Ye et al., 2019). Overall, it seems like patients with severe diseases have a higher chance of
readmission, making it essential to look at specific social determinants (Ye et al., 2019).
Health Conditions
Yunwei Gai and Dessislava Pachamanova (2019) wanted to analyze the impact of the
HRRP on readmissions for three targeted conditions. The three states were acute myocardial
infarction, heart failure, and pneumonia. They were among four types of different populations,
including low-income patients, patients served by hospitals that serve a high percentage of
low-income or Medicaid patients, and high-risk patients at the highest quartile of the Elixhauser
comorbidity index score (Gai & Pachamanova, 2019). The method they used for this study was
to gather the Nationwide Readmission Database (NRD) data, which contained all
discharges from community hospitals in 27 states during 2010-2014 (Gai & Pachamanova,
2019). They used different methods such as the difference-in-difference models and linear
9
probability regression (Gai & Pachamanova, 2019). According to the results, there has been a
significant reduction in readmission rates overall and vulnerable patients. At the same time,
HRRP can adjust the policy according to hospital patients' socioeconomic status and
neighborhood (Gai & Pachamanova, 2019). This study allows us to see the importance of
different health conditions and the improvements that are needed.
Gu’s (2014) main focus was to see if HRRP had unintended consequences for hospitals
serving vulnerable individuals. The data that was used for this study included medicare inpatient
claims to calculate condition-specific readmission rates. Medicare cost reports were also used to
determine a hospital's share of duals, profit margin, and characteristics (Gu,2014). They found
out that both a patient's dual-eligible status and a hospital's dual-eligible share of Medicare
discharges positively impact risk-adjusted hospital readmission rates (Gu, 2014). Therefore,
policymakers need to put in place policies that ensure vulnerable patients receive quality care, in
an effort to reduce hospital readmission levels (Gu, 2014). Zingmond (2018) stated the study
examines 30-day readmission rates for indicator conditions before and after the adoption of
HRRP. The California hospital discharge data from 2005 to 2014 was used in the study, which
estimated the difference between pre-HRRP and post-HRRP rates of hospital readmission. The
conditions that HRRP targeted were heart attack, heart failure, and pneumonia (Zingmond,
2018). The study concluded that post-HRRP had significant reductions in hospitalization for
patients with Medicare (Zingmond, 2018).
Patients with Chronic Obstructive Pulmonary Disease (COPD) were also studied because
they also fall under different social determinants. COPD is a group of lung diseases that cause
difficulty breathing (Croft, 2018). According to the CDC, COPD is the leading cause of death
10
and has been diagnosed in 15.5 million adults in the United States (Croft, 2018). Shah and Press
(2016) stated that 1 in 5 patients with COPD requires rehospitalization within 30 days. Even
though COPD is covered under HRRP, not much is known about reducing readmission rates
(Shah & Press, 2016). The study states that it has become a target condition and that changes
should be made.
Conceptual Framework
Problem Stream
The Hospital Readmissions Reduction Program (HRRP) is best explained using John
Kingdon’s multiple streams models. Kingdon’s model focuses on the three streams: the problem,
policy, and politics (Beland, 2015). Kingdon’s model also focuses on the agency and timing of a
policy (Beland, 2015). HRRP was introduced in 2012 as part of the Affordable Care Act, with
the aim to reduce the number of times a patient is readmitted to a hospital thirty days after
discharge (Mcllvennan et al., 2016). The problem stream focuses on high hospital costs. The
policy stream focuses on the quality of the program. Finally, the political stream focuses on the
stakeholders that are involved with HRRP.
Before HRRP was introduced in 2012, it was estimated that about $25-45 billion was spent
on unnecessary spending due to complications that could have been avoided and the readmission
of patients (Cagliostro, 2021). HRRP is one of the programs that lower payments to Inpatient
Prospective Payment System (IPPS) hospitals with excess admissions (Cagliostro, 2021). IPPS
categorizes each of the cases in diagnosis groups, and then the resources are measured to treat
those Medicare groups (Cagliostro, 2021).
Hospital readmission has been associated with unfavorable patient outcomes and high
financial costs (Mcllvennan, 2015). In the past, nearly 20% of all Medicare discharges had a
readmission within 30 days of release (Mcllvennan, 2015). In 2008, the Medicare Payment
Advisory Commission recommended to Congress that the CMS should begin to report readmission
rates and resources used to hospitals and physicians. Also, it has been said that
12
hospitals receive $1 out of every $3 spent on health care, and the United States is projected to
spend about $1.3 trillion for hospital care in 2019 (Gee, 2019). Commercial insurers also end up
paying twice as much as what Medicare does for hospital care (Gee, 2019). Gee (2019), also
suggest that hospitals have very high prices that do not match the kind of care they provide. He
asserts that despite these high medical costs, most medical mistakes end up being ignored.
Jordan Rau (2019) discussed that Medicare decided to cut payments for 2,583 hospitals to
reduce HRRP over time. If hospitals continued this way, then HRRP would cost hospitals over
$563 million over a year (Rau, 2019). This program started in 2012, but many hospitals decided
not to follow the policy rules, which significantly impacted them. About 83% of the hospitals
were penalized, deducted from each patient with Medicare (Rau, 2019). Hospitals also made sure
to look at how HRRP had been improving over the years; it was revealed that from 2010 to 2017,
the percentage had dropped from 16.7% to 15.7% (Rau, 2019). It is essential to look at the
penalty numbers regarding safety-net hospitals since HRRP can also penalize them. Safety net
and training hospitals seem more likely to be punished for poor readmission performance, and
when they are disciplined, it could be an even more significant penalty (Hoffman & Tilson,
2018). Even though they are constantly penalized, it has been known that they are improving
their quality of care (Hoffman & Tilson, 2018).
13
these stakeholders include hospital government agencies, payers (health insurances), patients,
taxpayers, healthcare professionals, interest groups. When the Obama Administration launched
HRRP, many other stakeholders believed this program would help improve patients’ overall
healthcare quality. These groups included over 500 hospitals, physicians, nursing groups,
employers, consumer advocacy organizations (Voelker, 2011). They also wanted to reduce
medical errors, which would bring down health care costs (Voelker, 2011). All these
stakeholders had the same goal when it came to HRRP. It would allow them to provide a better
quality of care for patients.
Another stakeholder would be the media, such as magazines, the internet, news channels.
They focused on the topic of HRRP for a while because it was part of the Affordable Care Act.
By using these tools, the media could speak about HRRP and discuss the pros and cons of the
program.
The Department of Health and Human Services can expand the program to include other
conditions (James, 2013). The CMS is very much involved in HRRP because it tracks all the
hospital numbers and makes sure hospitals follow the guidelines. The CMS has also completed
additional programs such as the Community-Based Care Transitions and the Partnership for
Patients (James, 2013). According to James (2013), hospitals will continue to focus on
experimenting with HRRP for a few years, as CMS continues to come up with different
strategies to curb patient readmission issues. Other methods need to be tested to see which one
14
will be the most effective. For significant changes to be made, it needs to be passed by the
legislature. Some changes can include the number of penalties. Some other improvements that
have been discussed are to spread HRRP to other health care facilities such as nursing homes and
clinics.
15
Policy Stream
Many policymakers wanted to figure out a way to help improve the quality of healthcare,
patient care, and the cost of Medicare (James, 2013). Through the Affordable Care Act (ACA),
HRRP provided a financial incentive to hospitals to lower the readmission rates (James, 2013).
However, different factors can also affect HRRP, such as a patient’s diagnosis, the severity of an
illness, patient behavior, and post-discharge care availability and quality (James, 2013). In 2009,
CMS started to report public hospital readmission rates, and hospitals began to compare
numbers(James, 2013). However, even after HRRP was introduced, it seems like reducing
readmission has not been straightforward.
According to Nehemiah and Reinke (2020), one method of improving the quality of care
for patients is by introducing health literacy. Health literacy is the degree to which an individual
can obtain, communicate, process, and understand basic health information and services to make
appropriate health decisions (Nehemiah & Reinke, 2020). Some of the variety of skills
associated with health literacy include understanding prescription labels, reading and filling out
medical forms, and understanding the consent process (Nehemiah & Reinke, 2020). The tool that
was used to measure health literacy is called 3-question Brief Health Literacy Screen. It would
ask patients about their confidence in filling out medical forms, their frequency of needing
assistance with reading hospital materials, and their frequency of having problems reading or
understanding their medical information (Nehemiah & Reinke, 2020). This tool can help
improve the quality of care for patients because they would appreciate all the information they
are being given. It is essential for patients to be fully aware of each step they need to go through
16
in a healthcare setting. Confusion leads to anxiety and feeling stressed, which might decline their
health over time.
Findings and Analysis
The studies included in the paper have been conducted to see if HRRP has benefited
hospitals, specifically safety and non-safety-net hospitals. This would also include hospitals with
patients who come from different social determinants. One specific study's objective was to
determine the impact of adjusting for social risk factors on HRRP penalties (Maddox, 2019). The
study was a retrospective cohort study with 2,952 605 fee-for-service Medicare beneficiaries
with myocardial infarction, congestive heart failure, and pneumonia from December 2012 to
November 2015 (Maddox, 2019). After this study was completed, it was concluded that many of
these patients did have different types of social determinants. Some of those determinants
included poverty, disability, and disadvantaged neighborhoods. In addition, these patients were
associated with higher readmission rates. The study also concluded that safety-net hospitals also
had higher readmission rates (Maddox, 2019).
Dr. Karen Joynt conducted a study that contrasted the wealthiest hospitals with safety-net
hospitals to see how correcting for socioeconomic risk affected HRRP penalties for three specific
conditions: AMI, HF, and Pneumonia. From the data gathered, it was discovered that safety-net
hospitals were located in extremely poor areas and provided treatment to patients. The patient
population of safety-net hospitals was "Females are more likely to have dual-enrolled in
Medicaid and to have been eligible for Medicare owing to disability. They were also less likely
to be white and had a greater rate of home insecurity (4 ZIP codes or more)". Table 1 shows the
results (Joynt et al., 2019).
18
Age 85+ (%) 26.3% 30.5% 40.1% 36.8% 42.3%
34.4
57.4
55.6
20.7
61.9
45.5
0.50
Table 1: Hospital Performance by Safety-Net Status
The sort of patients that the hospitals see is influenced by their location. The social risk
adjustment, which determines a change in readmission ratios, was added by Joynt and her
colleagues. In risk adjustment, social factors that can influence health, health-related processes,
and healthcare outcomes are taken into account. It also protects hospitals and clinicians from
being punished because of the social risk profiles of their patients (Tran 2020). As a result, the
mean readmission rations for safety-net hospitals fell by nearly 50%, while the rations for most-
affluent hospitals soared (Table 2). The hospitals' penalized status was also influenced by this
reduction.
20
With Medical and
Proportion of
Table 2: Patient and Hospital Characteristics
In another study that surveyed leadership at 1600 acute care hospitals (Figueroa, 2017),
about 980 hospitals ended up participating between June 2013 and January 2014. The surveys
included twenty-eight questions focused on readmission-related barriers, and strategies were
compared between safety-net and non-safety-net hospitals (Figueroa, 2017). The study had a
62% response rate, and safety-net hospitals reported patient-related barriers such as
transportation, homelessness, and language barriers compared with non-safety net hospitals
(Figueroa, 2017). The findings also concluded that high-performing safety-net hospitals were
more likely to use strategies that resulted in readmission rates (Figueroa, 2017).
22
The graph above shows the difference between the safety net and non-safety net hospitals
regarding different social determinants and barriers. Each one of those barriers impacts the
hospital and HRRP.
Figure 1: Difference Between the Safety Net and Non-Safety Net Hospitals
23
The Hospital Readmission Reduction Program has been beneficial for non-safety net
hospitals but not as much for safety-net hospitals that serve patients with barriers, such as a lack
of transportation, housing issues, homelessness, language barriers, and so on. HRRP needs to be
improved to help service these patients and lower readmission rates of safety-net hospitals.
Barriers can exist within any policy, and they need to be considered for the policy to be
successful. When HRRP was being discussed, these barriers might not have been discussed as
much as they should have. Many non-safety net and private hospitals have had high success
rates, but safety-net hospitals have been placed in difficult situations. These barriers that are
included for HRRP would be considering the different social determinants. Social determinants
include homelessness, housing issues, money issues, lack of transportation, language barriers,
accessibility to the internet or telephone. These barriers will impact HRRP because they are less
likely to visit their primary care doctors. After all, issues start to arise. Many patients may also
have difficulty getting the correct type of insurance because they are not aware of their options.
Therefore, it is essential to look at these social determinants and barriers and consider how much
of an impact they will have on the policy itself.
24
Recommendation
From this study, the following recommendations have been made in an effort to help in
the improvement of readmission rates from safety-net hospitals under the HRRP. Evidently,
many safety-net hospitals have continued to incur great costs due to the HRRP penalties. As
much as these penalties have seen to it that these hospitals improve over time, most of them are
still being penalized over readmission of patients with special cases. Thus, this study
recommends that the penalty policy be revised to consider certain health disparities such as
Chronic Obstructive Pulmonary Disease (COPD). Also, there need to be further studies on other
health conditions not currently under HRRP. Even though HRRP focuses on a few health
conditions, furthering that list can help find more statistics regarding the success rate. Focusing
on these new health conditions will allow hospitals to see the improvements that still need to be
made.
Another recommendation is the monitoring of the quality of care that each patient
received, irrespective of their social status. Policymakers need to ensure that departments such as
surgical care departments provide quality, timely, patient-centered care in all safety-net hospitals,
to avoid patient readmission and medical errors. This study recommends that quality care be
provided to people with disadvantaged social determinants such as race, age, gender, and
financial capabilities. Similarly, HRRP needs to consider illnesses that are related to certain
special social determinants such as age, to ensure that hospitals are fairly scrutinized when
assessing readmission rates. This will help reduce penalties to hospitals as well as encourage
these hospitals to provide better care to patients.
25
Additionally, this study recommends that the HRRP be passed as a law. With the HRRP
as a law, hospital administrations will be able to take the program seriously and provide quality,
patient-centered care to their patients to avoid being on the wrong side of the law. This will also
instill keenness in medical practitioners to avoid making medical mistakes. Another
recommendation is that the HRRP regulations need to be spread to other healthcare facilities
such as clinics and nursing homes. Lastly, the study recommends that hospitals improve on
health literacy in patients. This will ensure that patients are aware of how to fill medical forms
and of their medical rights and medical procedures for their specific conditions, reducing the
risks of miscommunication within medical facilities.
26
Conclusion
The Hospital Readmission Reduction Program was implemented to reduce the number of
times a patient is readmitted to a hospital within 30 days after discharge. In addition, hospitals
will be penalized for returning patients for an amount depending on the hospital. HRRP was
created in 2012, around the time that the Affordable Care Act passed. HRRP has been successful
in lowering readmission rates, which leads to a better quality of healthcare. However, certain
aspects of the policy need to be improved. For example, HRRP needs to strengthen the safety-net
hospitals and hospitals that serve patients with different social determinants. Studies show that
these two factors impact the readmission rates for these hospitals. If they are addressed, the
HRRP can be even more successful over time.
27
References
Atupem, George. (2017). Applying John Kingdon’s Three Stream Model to the Policy Idea of
Universal Preschool. In BSU Honors Program Theses and Projects. Item 245. Available at:
https://vc.bridgew.edu/honors_proj/245
Carey, K., & Lin, M. (2016). Hospital readmissions reduction program: Safety-net hospitals
show improvement, modifications to penalty formula still needed. Health Affairs, 35(10),
1918-1923. doi:http://dx.doi.org.libproxy.csun.edu/10.1377/hlthaff.2016.0537
Chaiyachati KH, Qi M, Werner RM. Changes to Racial Disparities in Readmission Rates After
Medicare’s Hospital Readmissions Reduction Program Within Safety-Net and
Non–Safety-Net Hospitals. JAMA Netw Open. 2018;1(7):e184154.
doi:10.1001/jamanetworkopen.2018.4154
Croft JB, Wheaton AG, Liu Y, et al. Urban-Rural County and State Differences in Chronic
Obstructive Pulmonary Disease — United States, 2015. MMWR Morb Mortal Wkly Rep
2018;67:205–211. DOI: http://dx.doi.org/10.15585/mmwr.mm6707a1external icon
Daniel Béland (2015): Kingdon Reconsidered: Ideas, Interests and Institutions in Comparative
Policy Analysis, Journal of Comparative Policy Analysis: Research and Practice, DOI:
10.1080/13876988.2015.1029770
2018;153(3):251. doi:10.1001/jamasurg.2017.4586
Figueroa, J. F. , Joynt, K. E. , Zhou, X. , Orav, E. J. & Jha, A. K. (2017). Safety-net Hospitals
Face More Barriers Yet Use Fewer Strategies to Reduce Readmissions. Medical Care, 55
(3), 229-235. doi: 10.1097/MLR.0000000000000687.
vulnerable populations. BMC Health Serv Res 19, 837 (2019).
https://doi.org/10.1186/s12913-019-4645-5
Gu, Q., Koenig, L., Faerberg, J., Steinberg, C. R., Vaz, C., & Wheatley, M. P. (2014). The
Medicare Hospital Readmissions Reduction Program: potential unintended consequences
for hospitals serving vulnerable populations. Health services research, 49(3), 818–837.
https://doi.org/10.1111/1475-6773.12150
Hsuan, Charleen, Braun, Thomas M, Ponce, Ninez A, & Hoffman, Geoffrey J. (2020). Are
Improvements Still Needed to the Modified Hospital Readmissions Reduction Program:
Health and Retirement Study (2000-2014)? Journal of General Internal Medicine :
JGIM, 35(12), 3564–3571. h ttps://doi.org/10.1007/s11606-020-06222-1
Jha AK. To Fix the Hospital Readmissions Program, Prioritize What Matters. JAMA.
2018;319(5):431–433. doi:10.1001/jama.2017.21623
Jiang, H. J. , Reiter, K. L. & Wang, J. (2016). Measuring Mortality Performance. Medical Care,
54(7), 648–656. doi: 10.1097/MLR.0000000000000540.
Joynt KE, Jha AK. Characteristics of Hospitals Receiving Penalties Under the Hospital
Readmissions Reduction Program. JAMA. 2013;309(4):342–343.
doi:10.1001/jama.2012.94856
Joynt Maddox, K. E., Reidhead, M., Hu, J., Kind, A., Zaslavsky, A. M., Nagasako, E. M., &
Nerenz, D. R. (2019). Adjusting for social risk factors impacts performance and penalties
in the hospital readmissions reduction program. Health services research, 54(2), 327–336.
https://doi.org/10.1111/1475-6773.13133
29
Lucas, Donald J., MD, MPH, & Pawlik, Timothy M., MD, MPH, PhD. (2014). Readmission
After Surgery. Advances in Surgery (Chicago), 48(1), 185–199.
https://doi.org/10.1016/j.yasu.2014.05.009
McIlvennan, C. K., Eapen, Z. J., & Allen, L. A. (2015). Hospital readmissions reduction
program. Circulation, 131(20), 1796–1803.
https://doi.org/10.1161/CIRCULATIONAHA.114.010270
Mouch, C. A., Regenbogen, S. E., Revels, S. L., Wong, S. L., Lemak, C. H., & Morris, A. M.
(2014). The quality of surgical care in safety-net hospitals: a systematic review. Surgery,
155(5), 826–838. h ttps://doi.org/10.1016/j.surg.2013.12.006
Popescu, I., Fingar, K. R., Cutler, E., Guo, J., & Jiang, H. J. (2019). Comparison of 3 Safety-Net
Hospital Definitions and Association With Hospital Characteristics. JAMA network open,
2(8), e198577. https://doi.org/10.1001/jamanetworkopen.2019.8577
Shah, T., Press, V. G., Huisingh-Scheetz, M., & White, S. R. (2016). COPD Readmissions:
Addressing COPD in the Era of Value-based Health Care. Chest, 150(4), 916–926.
https://doi.org/10.1016/j.chest.2016.05.002
Thompson, M. P., Kaplan, C. M., Cao, Y., Bazzoli, G. J., & Waters, T. M. (2016). Reliability of
30-Day Readmission Measures Used in the Hospital Readmission Reduction Program.
Health services research, 51(6), 2095–2114. h ttps://doi.org/10.1111/1475-6773.12587
Tran LD (2020, June 10). Social Risk Adjustment in Health Care Performance Measures. JAMA
Netw Open. 3(6):e208020. doi:10.1001/jamanetworkopen.2020.8020
Voelker R. Stakeholders Join Forces in Attempt to Improve Safety, Reduce Health Care Costs.
JAMA. 2011;305(18):1849. doi:10.1001/jama.2011.599
Wadhera, R. K., Yeh, R. W., & Joynt Maddox, K. E. (2019). The Hospital Readmissions
2289–2291. https://doi.org/10.1056/NEJMp1901225
Wasfy, J. H. , Bhambhani, V. , Healy, E. W. , Choirat, C. , Dominici, F. , Wadhera, R. K. , Shen,
C. , Wang, Y. & Yeh, R. W. (2019). Relative Effects of the Hospital Readmissions
Reduction Program on Hospitals That Serve Poorer Patients. Medical Care, 57(12), 968–
976. doi: 10.1097/MLR.0000000000001207.
Werner RM, Goldman LE, Dudley RA. Comparison of Change in Quality of Care Between
Safety-Net and Non–Safety-Net Hospitals. JAMA. 2008;299(18):2180–2187.
doi:10.1001/jama.299.18.2180
Ye Y, Beachy MW, Luo J, et al. Geospatial, Clinical, and Social Determinants of Hospital
Readmissions. American Journal of Medical Quality. 2019;34(6):607-614.
doi:10.1177/1062860619833306
Zingmond, D. S., Liang, L. J., Parikh, P., & Escarce, J. J. (2018). The Impact of the Hospital
Readmissions Reduction Program across Insurance Types in California. Health services
research, 53(6), 4403–4415. https://doi.org/10.1111/1475-6773.12869