Transcript of CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Improving the ...
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