I need help with my RUA.

NR449 Evidence Based Practice

Required Uniform Assignment: Analyzing Published Research
Purpose

The purpose of this paper is to interpret the two articles identified as most important to the group topic.

COURSE OUTCOMES

This assignment enables the student to meet the following course outcomes:
CO 2: Apply research principles to the interpretation of the content of published research studies. (POs #4
and #8)

CO 4: Evaluate published nursing research for credibility and clinical significance related to evidence- based
practice. (POs #4 and #8)

DUE DATE

Refer to the course calendar for due date information. The college’s Late Assignment policy applies to this
activity.

TOTAL POINTS POSSIBLE: 200 POINTS REQUIREMENTS

The paper will include the following.

1. Clinical question
a. Description of problem
b. Significance of problem
c. Purpose of paper

2. Description of findings
a. Summarize basics in the Matrix Table as found in Assignment Documents in e-College.
b. Describe

i. Concepts
ii. Methods used
iii. Participants
iv. Instruments including reliability and validity
v. Answer to “Purpose” question vi. Identify next step for group

3. Conclusion of paper
4. Format

a. Correct grammar and spelling
b. Use of headings for each section

NR449 Evidence Based Practice
c. Use of APA format (sixth edition)
d. Page length: three pages

PREPARING THE PAPER

1. Please make sure you do not duplicate articles within your group.
2. Paper should include a title page and a reference page.

DIRECTIONS AND ASSIGNMENT CRITERIA

Assignment
Criteria

Points % Description

Clinical Question

30

15%

1. Problem is described: What is the focus of your group’s work?
2. Significance of the problem is described: What health outcomes result

from your problem? Or what statistics document this is a problem? You
may find support on websites for government or professional
organizations.

3. Purpose of your paper: What will your paper do or describe? “The purpose
of this paper is to . . .”

**Please note that although most of these questions are the same as
you addressed in paper 1, the purpose of this paper is different. You
can use your work from paper 1 for items 1 and 2 above, including
any suggestions for improvement provided as feedback. Item 3 above
should be specific to this paper.

Description of
Findings: Summary

60

30%

Summarize the basics of each article in a matrix table that appears in the
appendix.

Description of
Findings:

Description
60 30%

Describe in the body of the paper the following.
• What concepts have been studied?
• What methods have been

used?

• Who are the participants or members of the samples?
• What instruments have been used? Did the authors describe the

reliability and validity?
• How do you answer your original “purpose of this paper” question?

Do the findings of the articles provide evidence for your answers? If
so, how? If not, what is still needed to be able to answer your
question?

• What is needed for the next step? Identify two questions that can
help guide the group’s work.

Description of
Findings: Conclusion 20 10%

Conclusion: Review major findings in your paper in a summary paragraph.

Format 30

15%

1. Correct grammar and spelling
2. Use headings for each section: Problem, Synthesis of the Literature

(Concepts, Methods, Participants, Instruments, Implications for Future
Work), Conclusion.

3. APA format (sixth ed.): Appendices follow references.
4. Paper length: Three pages

Total 200 100%

NR449 RUA Analyzing Published Research x Revised 07 / 25 /2016 2

NR449 Evidence Based Practice

NR449 RUA A nalyzing Published Research x Revised 07/25 /2016 4

GRADING RUBRIC

Assignment
Criteria

Outstanding or Highest
Level of Performance

A (92–100%)

Very Good or High Level of
Performance

B (84–91%)

Competent or Satisfactory
Level of Performance

C (76–83%)

Poor, Failing or
Unsatisfactory Level of

Performance F
(0–75%)

Clinical Question
(30 points)

Includes all elements in a
manner that is clearly
understood.

• Problem description
provides focus of the
group’s work.

• Significance of the problem
is clearly stated and
supported by current
evidence.

• Purpose of paper is clearly
stated.

28-30

points

Missing only one element

OR
One element is not presented
clearly

• Problem description provides
focus of the group’s work.

• Significance of the problem is
clearly stated and supported
by current evidence.

• Purpose of paper is clearly
stated.

26-27 points

Missing two elements

OR
One element is not presented
clearly
• Problem description provides
focus of the group’s work.
• Significance of the problem is
clearly stated and supported
by current evidence.
• Purpose of paper is clearly
stated.

23-25 points

Missing two or more elements

AND/OR
One or more elements are not
presented clearly

• Problem description provides
focus of the group’s work.
• Significance of the problem is
clearly stated and supported
by current evidence.
• Purpose of paper is clearly
stated.

0-22 points

Description of
Findings:
Summary
(60 points)

Summary omits no
more than one required
item from the Evidence
Matrix Table.

55-60 points

Summary omits two or three
required items from the
Evidence Matrix Table.

51-55 points

Summary omits four required
items from the Evidence
Matrix Table.

46-50
points

Summary omits five or more
required items from the
Evidence Matrix Table.

0–45

points

NR449 Evidence Based Practice

NR449 RUA A nalyzing Published Research x Revised 07/25 /2016 5

Description of
Findings:
Description
(60 points)

Description includes ALL
elements.

• What concepts have
been studied?

• What methods have
been used?

Description missing no more than
one element.

• What concepts have been

studied?
• What methods have been

used?

Description missing no more than
two elements.

• What concepts have been
studied?
• What methods have been
used?

Description missing three or
more elements.

• What concepts have been
studied?
• What methods have been
used?

NR449 Evidence Based Practice

NR449 RUA A nalyzing Published Research x Revised 07/25 /2016 6

• Who are the
participants or
members of the
samples?

• What instruments
have been used?
Did the authors
describe the
reliability and
validity?

• How do you answer
your original “the
purpose of this
paper” question?
Do the findings of
the articles provide
evidence for your
answers? If so,
how? If not, what is
still needed to be
able to answer your
question?

• What is needed for
the next step?
Identify two
questions that can
help guide the
group’s work.

56–60 points

• Who are the participants or
members of the samples?

• What instruments have
been used? Did the authors
describe the reliability and
validity?

• How do you answer your
original “the purpose of
this paper” question? Do
the findings of the articles
provide evidence for your
answers? If so, how? If not,
what is still needed to be
able to answer your
question?

• What is needed for the
next step? Identify two
questions that can help
guide the group’s work.

51–55 points

• Who are the participants or
members of the samples?
• What instruments have
been used? Did the authors
describe the reliability and
validity?
• How do you answer your
original “the purpose of
this paper” question? Do
the findings of the articles
provide evidence for your
answers? If so, how? If not,
what is still needed to be
able to answer your
question?
• What is needed for the
next step? Identify two
questions that can help
guide the group’s work.

46–50 points

• Who are the participants or
members of the samples?
• What instruments have
been used? Did the authors
describe the reliability and
validity?
• How do you answer your
original “the purpose of
this paper” question? Do
the findings of the articles
provide evidence for your
answers? If so, how? If not,
what is still needed to be
able to answer your
question?
• What is needed for the
next step? Identify two
questions that can help
guide the group’s work.

0–45 points

NR449 Evidence Based Practice

NR449 RUA A nalyzing Published Research x Revised 07/25 /2016 7

Description of
Findings:
Conclusion
(20 points)

Summary paragraph includes
ALL major findings from
article.

• Independently extracts

complex data from a
variety of quantitative
sources, presents those
data in summary form,
makes appropriate

Summary paragraph omits ONE
major finding from article.

• Independently extracts complex

data from a variety of
quantitative sources, presents
those data in summary form,
makes appropriate
connections and inferences
consistent with the data, and

Summary paragraph omits TWO
major findings from article.

• Independently extracts complex
data from a variety of
quantitative sources, presents
those data in summary form,
makes appropriate
connections and inferences
consistent with the data, and

Summary paragraph omits THREE
or MORE major findings from
article.

• Independently extracts complex

data from a variety of
quantitative sources, presents
those data in summary form,
makes appropriate
connections and inferences

connections and inferences

consistent with the data, and
relates them to a larger
context.

• Recognizes points of view
and value assumptions in
formulating
interpretation of data
collected and articulates
the point of view in a
given situation.

• Identifies
misrepresentations in the
presentation points of
quantitative data and the
logical and empirical
fallacies in inferences
drawn from data.
19-20 points

relates them to a larger context.
• Recognizes points of view and

value assumptions in
formulating interpretation of
data collected and articulates
the point of view in a given
situation.

• Identifies misrepresentations in
the presentation of
quantitative data and the
logical and empirical fallacies in
inferences drawn from data.

17-18 points

relates them to a larger context.
• Recognizes points of view and
value assumptions in
formulating interpretation of
data collected and articulates
the point of view in a given
situation.
• Identifies misrepresentations in
the presentation of
quantitative data and the
logical and empirical fallacies in
inferences drawn from data.

16 points

consistent with the data, and
relates them to a larger
context.

• Recognizes points of view and
value assumptions in
formulating interpretation of
data collected and articulates
the point of view in a given
situation.

• Identifies misrepresentations in
the presentation of quantitative
data and the logical and
empirical fallacies in inferences
drawn from data.

0-15 points

NR449 Evidence Based Practice

NR449 RUA A nalyzing Published Research x Revised 07/25 /2016 8

Grammar, Spelling,
Mechanics, and
APA Format
(30 points)

• Length is three full
pages.

• Used appropriate APA

format and is free of
errors.

• Includes ALL headings

and subheadings as
instructed.

• Grammar, spelling, and
mechanics are free of
errors.

28–30 points

• Length is no more than
one quarter page under or
over.

• Used appropriate APA
format, with one type of
error.

• Includes ALL headings and

subheadings as instructed.
• Grammar, spelling, and

mechanics have one type
of error.

26–27 points

• Length is no more than one
half page under or over.

• Used appropriate APA
format, with two types of
errors.

• Includes ALL headings and
subheadings as instructed.
• Grammar, spelling, and

mechanics have two types
of errors.

23–25 points

• Length is three quarters of a
page or more under or over.

• Attempts made to use APA
format; three or more types
of errors are present.

• Includes ALL headings and
subheadings as instructed.

• Grammar, spelling, and
mechanics have three or
more types of errors.

0–22 points

Total Points Possible = 200 points

COURSE OUTCOMES
DUE DATE
TOTAL POINTS POSSIBLE: 200 POINTS REQUIREMENTS
PREPARING THE PAPER
DIRECTIONS AND ASSIGNMENT CRITERIA
GRADING RUBRIC

Chamberlain College of Nursing NR449 Evidence-Based Practice

Evidence Matrix Table

Article

Reference

Purpose

Hypothesis

Study Question

Variables

Independent(I)

Dependent(D)

Study Design

Sample

Size and Selection

Data Collection

Methods

Major Findings

1
(sample not a real article)

Smith, Lewis (2013),
What should I eat? A focus for those living with diabetes. Journal of Nursing Education, 1 (4) 111-112.

How do educational support groups effect dietary modifications in patients with diabetes?

D-Dietary modifications
I-Education

Qualitative

N- 18
Convenience sample-selected from local support group in Pittsburgh, PA

Focus Groups

Support and education improved compliance with dietary modifications.

1

2

3

4

5

NR449 Evidence Matric Table x Revised10/20/14 ns/cs

1

References

Kneepkens, E.-L., Brouwers, C., Singotani, R. G., de Bruijne, M. C., & Karapinar-Çarkit, F. (2019). How do studies assess the preventability of readmissions? A systematic review with narrative synthesis. BMC Medical Research Methodology, 19(1), 128.

https://doi-org.chamberlainuniversity.idm.oclc.org/10.1186/s12874-019-0766-0

Mennella, H. D. A.-B., & Key, M. A.-C. A. A. C. (2018). Case management: readmissions. CINAHL Nursing Guide. Retrieved from https://chamberlainuniversity.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=nup&AN=T708339&site=eds-live&scope=site be directly applied to the practice

RESEARCH ARTICLE Open Access

How do studies assess the preventability of
readmissions? A systematic review with
narrative synthesis
Eva-Linda Kneepkens1†, Corline Brouwers2†, Richelle Glory Singotani2, Martine C. de Bruijne2 and
Fatma Karapinar-Çarkit1*

Abstract

Background

: A large number of articles examined the preventability rate of readmissions, but comparison and
interpretability of these preventability rates is complicated due to the large heterogeneity of methods that
were used

.

To compare (the implications of) the different methods used to assess the preventability of readmissions by
means of medical record review.

Methods

: A literature search was conducted in PUBMED and EMBASE using “readmission” and “avoidability”
or “preventability” as key terms. A consensus-based narrative data synthesis was performed to compare and
discuss the different methods.

Results

: Abstracts of 2504 unique citations were screened resulting in 48 full text articles which were included in the
final analysis. Synthesis led to the identification of a set of important variables on which the studies differed considerably
(type of readmissions, sources of information, definition of preventability, cause classification and reviewer process). In
69% of the studies the cause classification and preventability assessment were integrated; meaning specific causes were
predefined as preventable or not preventable. The reviewers were most often medical specialist (67%), and 27% of the
studies added interview as a source of information.

Conclusion: A consensus-based standardised approach to assess preventability of readmission is warranted to reduce
the unwanted bias in preventability rates. Patient-related and integrated care related factors are potentially underreported
in readmission studies.

Keywords: Hospital readmission, Avoidability, Preventability, Assessment, Review, Patient interview

Background
The general goal of hospital care is to restore the
patient’s health condition to the pre-admission state or
to discharge the patient in the best possible health con-
dition. Nevertheless, approximately 20% of the hospital
admissions in the US result in an unplanned readmission
within 30 days after discharge, of which a subset is
preventable [1]. These readmissions result in an increase
in cost, workload for caregivers and a potential health risk

for patients [2]. Hence, hospital readmission rates are
increasingly being used to monitor quality improvement
and cost control [3]. Currently, hospitals are being bench-
marked in several countries based on their readmissions
rate. In some of these countries, high rates can result in
financial penalties and they are used as a policy to stimu-
late hospitals to implement improvement plans [4].
These improvement plans are generally complex and

costly, therefore, prediction models to identify patients
who are at risk for readmissions are being developed [5].
However, these models are often not validated pros-
pectively or in other datasets [6]. Furthermore, electronic
prediction algorithms tend to overestimate potentially pre-
ventable readmissions [7]. It is important to understand

© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

* Correspondence: f.karapinar@olvg.nl
E.L. Kneepkens and C. Brouwers are shared first authors
†E.L. Kneepkens and C. Brouwers contributed equally to the manuscript
1Department of Clinical Pharmacy, OLVG Hospital, Jan Tooropstraat 164, 1061
AE Amsterdam, The Netherlands
Full list of author information is available at the end of the article

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128
https://doi.org/10.1186/s12874-019-0766-0

http://crossmark.crossref.org/dialog/?doi=10.1186/s12874-019-0766-0&domain=pdf

http://creativecommons.org/licenses/by/4.0/

http://creativecommons.org/publicdomain/zero/1.0/

mailto:f.karapinar@olvg.nl

the complex mechanism behind readmissions and to
achieve an accurate prediction of preventable read-
missions. This can be achieved through medical record
review, preferably combined with narratives obtained from
patient interviews [7], and other sources, such as a general
practitioner (GP).
Many studies have examined the preventability rate of

readmissions, but comparison and interpretability of
these preventability rates are complicated by the large
heterogeneity of methods used to assess the preventa-
bility [8]. In addition, (systematic) reviews that studied
the preventability of readmissions did not focus on the
method of assessment, and whether specific metho-
dological options affect the likelihood of finding a high
or low preventability rate [7, 9–11]. Understanding the
implications of different methodological options could
aid in solving a piece of the readmission puzzle. There-
fore, the objective of this study is to compare methods
and discuss all studies in which preventability of hospital
readmissions was assessed by use of medical record
review. By these means, we hope to provide the reader
guidance in how to conduct and report their study data
on readmissions.

Methods
Data source and searches
A systematic literature search was applied in Pubmed
and Embase in December 2016. In the first step of the
search strategy(MeSH and tiab)-terms for “readmission”
and “rehospitalization” were combined with terms such
as “avoidability” or “preventability” (see Additional file 1).
In the next step this search was combined with terms such
as “quality of health care”, “quality indicators”, and “chart
review”. In the last step conference abstracts were ex-
cluded from the search. For this search a medical informa-
tion specialist was consulted. All citations were imported
into Endnote X 7.3.1TM.

Study selection
A stepwise study selection (described below) was con-
ducted using a consensus-based approach. In case of dis-
agreement, an independent senior researcher was consulted
(FKC and MdB).

� Step 1: Two researchers (CB, EK) independently
screened all abstracts using the major inclusion and
exclusion criteria, i.e. English language, manual
assessment using, at least, the medical record and a
clear method description regarding preventability
assessment in the aim, method or result section, see
Additional file 2. Cohen’s kappa for interrater
agreement (CB and EK) was good (k = 0.70).

� Step 2:

References

of included articles were assessed
and a cited reference search in Web of Science and

Scopus (CB and EK) was performed additionally for
all full text articles included in step 1 (n = 77).

� Step 3: Detailed inclusion and exclusion criteria
(Additional file 2) were applied to all 77 articles by
two researchers independently (equally divided over
CB, EK, RS). This additional step was conducted to
ensure that the finally selected articles were able to
help us reach our study objective; 1. Full text article
in English; 2. The article should be based on original
patient data; in case of ≥2 or more papers used the
same, or partly the same, patient sample only the
paper with the most thoroughly described
methodology of preventability assessment was
included; 3. Studying hospital readmissions should
be clearly stated in the aim/ primary objective; 4.
Duration between index and readmission should be
≤6 months; 5. Assessment of preventability should
be performed via manual medical record review or
at least, it should be clear that the preventability
assessment was performed on an individual patient
level by a care provider and/or trained researcher
which cannot be performed without a review; 6.
The methodology of the preventability assessment of
readmissions should be described clearly in order to
perform data-synthesis; this includes a description of
criteria of preventability and/or a cause classification
(≥3 cause categories) of preventable readmissions
and the reviewer process (at least 2 independent
reviewers and disagreement should have been solved
by reaching consensus and/ or a third independent
reviewer OR, in case not performed/ nor reported
(NR) > 50 medical files of readmitted patients should
have been reviewed).

Critical appraisal of individual sources of evidence
A validated critical appraisal was performed to evaluate
the reliability, value and relevance of each article. Com-
monly used quality appraisal tools were not suitable
because of the large heterogeneity in study designs. Hence,
a critical appraisal tool was used which is developed by
the Cochrane recommendations for narrative data syn-
thesis and analysis [12]. This critical appraisal was im-
plemented in the data synthesis. The goal of using the
narrative synthesis is, similar to other appraisal tools, to
avoid bias. The process of narrative data synthesis is rigo-
rous and transparent, in which the process is specified in
advance. These process steps were followed systematically.

Data synthesis
A (textual) narrative synthesis was performed to compare
the methods of the included studies and this led to the
identification of a set of important variables. The following
variables were systematically collected and described in
the Result section: study design characteristics, sources of

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 2 of 12

information to assess preventability, definition of prevent-
ability, cause classification (classifying the cause of a re-
admission) and reproducibility (i.e. the reviewer process
and training) (see Additional file 3).
There are several important considerations to take into

account prior to reading the results; (1) the cause classifi-
cation and preventability assessment are often integrated;
meaning specific causes were predefined as always pre-
ventable or not preventable. These studies were called a
priori preventability cause classifications; (2) some articles
reported the number and percentage of readmissions
while others reported the number of readmitted patients,
or both. For the purpose of this article, we reported
the percentage of preventable readmissions/readmitted
patients based on the actual number of reviewed files
within one month (if this could be extracted from the
provided data); (3) cause classification refers to description
of at least three causes; (4) lastly, the index admission is
the admission prior to readmission.

Data extraction and analysis
Data was collected (CB, EK, RS) using a predefined form
which included study characteristics and relevant data
with regard to the method of preventability assessmen

t.

During the preliminary data synthesis, all data extracted
by one researcher was checked by at least one other
researcher (CB, EK, RS). During the systematic approach
a double check or consensus-discussion was only per-
formed in case of doubt because all definitions were
thoroughly discussed after the preliminary phase. Lastly,
potential associations between preventability rates and
study characteristics were explored using the indepen-
dent sample t test, Mann-Whitney u test or χ2 test
depending on the variable distribution. A value of < 0.05 was considered to be statistically significant. The data were analysed with SPSS version 21.0 software (IBM, New York, USA).

Results
Abstracts of 2504 unique citations were screened
resulting in 77 full text articles that reported on the
assessment of preventability. Step 3 of the stepwise
study selection resulted in the final inclusion of 48
(64%) articles. The other studies (n = 29) were ex-
cluded because the primary objective of the paper
was not focussed on readmissions, the duration (dis-
charge index admission to readmission) was longer
than 6 months, or because the readmission method of
preventability assessment was not explicitly described
in the method section. A minimal dataset for the
excluded articles, and the reason for exclusion, is
shown in Additional file 4. An overview of the selection
process is shown in Fig. 1.

Study design and characteristics
As shown in Table 1, the studies were published between
1988 and 2017, often as single center studies (n = 37;
77.1%) and often performed in the USA (n = 32; 66.6%).
Twelve studies focused on a specific diagnosis (n = 12)
or a group (e.g. elderly or children) within a single
department (e.g. internal medicine). Furthermore, nine
studies examined all-cause readmissions, meaning that
patients readmitted at all departments were eligible for
inclusion [13–21]. Additional file 5 provides more
detailed information on the descriptive characteristics of
the studies.

Sources of information
Thirteen articles (n = 13) used additional sources of infor-
mation, such as interviews, questionnaires or surveys, in
addition to the manual medical record review, see Table 1
[14, 21–32]. Additional file 6 provides more information
on the interviews with care providers and/or patients. In 7
studies the patient was approached [21–23, 25, 30–32]
and in 5 studies the patient or caregiver was approached
[14, 26–29]. In 4 studies it was mentioned that the results
of the interview were available for the reviewers during
their assessment of preventability, however, it was not
specified if and how these results influenced the prevent-
ability assessment [14, 22, 26, 29]. In the paper of Toomey
et al. [27] the preventability was first assessed without the
interview results. Subsequently, the interview results were
shared with the reviewer and it was documented how this
additional information changed the review outcome. This
resulted in new information in 31.2% of the cases and a
change in the final preventability score in 11.8%. However,
no further details were published regarding which in-
formation of the interview was crucial for the reviewer to
change his or her opinion. The other 5 studies did not
specify whether or not the additional patient/caregiver
information was used to assess the preventability [25,
28, 30–32]. In the study of Burke et al. [23], only 6
patients were interviewed during a pilot phase. After the
pilot, they concluded that the interviews did not provide
additional data to the patient’s medical record.
Six studies interviewed at least one care provider, of

which mostly the GP, see Additional file 6. Four studies
reported that the results of the care provider interview
were available for the reviewers [14, 22], or were in-
cluded in the preventability judgement [26] and one re-
ported that the opinion of the interviewee was included
in the final preventability judgement via equal weighing
of their opinion with the opinion of the audit team [24].

Preventability
A subset of articles used a very broad definition of
preventability, such as the study of Ryan et al.;

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 3 of 12

‘Providers were given no specific guidelines for deciding
whether a readmission was preventable. This allowed
use of their different backgrounds in choosing which
elements of the clinical record to focus on.’ [33]

In addition, the majority of the articles did not explicitly
provide the definition of preventability, instead they often
directly referred to the cause classification (see Additional
file 7), such as Williams et al.; ‘It was noted that readmis-
sion could have been avoided if more effective action had
been taken in one or more of five areas: preparation for
and timing of discharge, attention to the needs of the carer,
timely and adequate information to the general practi-
tioner and subsequent action by the general practitioner,
sufficient and prompt nursing and social services support,
and management of medication.’ [28]

Cause classification
The cause classification (the description of at least three
causes) that was used by the studies varied largely. Several
studies used an existing tool, like the STate Action on
Avoidable Rehospitalizations (STAAR) initiative [14, 21,
27, 30, 34] or root cause approach [5, 18, 24, 35–37] but
all others adapted an existing tool or developed their own

tool based on previous publications. For the purpose of
this article we focused only on the distinction between
studies using an a priori preventability cause classification
[13–16, 19, 21–26, 31, 35, 37–55], or not [5, 17, 18, 20,
27–30, 32, 33, 36, 56–59], see Table 2. As an example of
an a priori cause classification, Clarke et al. reported,
Unavoidable causes: chronic or relapsing disorder; un-
avoidable complication, readmission for social or psy-
chological reason, reasons probably beyond control of
hospital services, completely different diagnosis from
previous admission. Avoidable causes: recurrence or
continuation of disorder leading to first admission,
recognised avoidable complication, readmission for
social or psychological reason, reasons probably within
control of hospital services. [39]
The majority of the studies did not report whether

they assessed the causal relationship (i.e. whether the
readmission is related to the care provided during index
admission) explicitly, but ‘causative or causal’ could be
extracted from the cause and/or preventability criteria [15,
16, 23, 32, 43, 44, 52, 53]. In addition, a few articles
included information on ‘related readmissions’. These
readmissions were defined as related based on the
same diagnosis (or complication), the same department, or

Fig. 1 PRISMA 2009 Flow Diagram

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 4 of 12

medical/clinically related [13, 20, 35, 37, 38, 40, 42, 48–51,
56, 57]. Another term used was ‘causation’ [18, 27, 32].

Reproducibility/reviewer process
As shown in Table 2, the number of reviewers varied
between 1 and 35. Four studies had ≥10 reviewers [17, 32,
36, 43]. The reviewers were most often physicians (spe-
cialists) or a combination hereof [5, 13, 15–18, 20–23, 25,
27, 28, 30–32, 35–39, 41, 42, 45, 47, 50, 51, 53–55, 57, 58].
A subset of studies included a multidisciplinary study
team consisting of physicians, general practitioners, a
medical officer, case managers, (specialized) nurses, me-
dical record specialists, social workers and/or administra-
tive staff [14, 24, 29, 33, 44, 46, 48]. In three studies senior
residents performed the review supervised by a senior
physicians [19, 26, 59]. In five studies no information on
expertise was reported [40, 49, 52, 56, 60].
As shown in Table 2 roughly three options for review

were possible: a single reviewer without a double check
[13, 17, 28, 38, 51, 59], a single reviewer double checked
by a second reviewer [15, 18, 32, 36, 45] or a team [24,
40, 43] or a team of 3 to 4 persons which reviewed the
readmissions directly [20, 25, 27, 33, 41, 49, 54]. Agree-
ment and consensus regarding the preventability was
handled differently: a double review of each readmission
was performed meaning that both reviewers assessed the
preventability of the readmissions and came to a mutual
agreement [14, 16, 18, 19, 22, 23, 29–31, 35, 42, 44, 46,
47, 50, 52, 53, 57]. In some cases a team or panel was
consulted when mutual agreement on the preventability
was not achieved [5, 48, 55, 60]. Two studies could not
be allocated to one of these review categories because
the review process was not clearly described or because
they used a mix of different methods [39, 56].
A subset of the included articles offered some kind of

support to the reviewers to clarify and solidify classifi-
cation criteria, to increase the uniformity between the
assessments or to refine the study logistics and/or
survey instrument or implemented as an educational
program [59]. The support was mainly provided by
means of a training, instruction session, pilot [17, 22,
27, 32, 36, 42, 52] and/or discussion of preventable
causes and readmissions [14, 16, 18, 27, 36, 37, 42, 52,
53, 55]; other options were: a study protocol or review

Table 1 Descriptives of included studies

Study characteristics (n = 48) No. or percentage
of studies

Year of publication, range 1988–2016

Country, n (%)

USA 32 (67%)

Other 16 (33%)

Study design, n (%)

Retrospective 30 (63%)

Cross-sectional 10 (21%)

Prospective 8 (16%)

Setting, n (%)

Single center 37 (77%)

Multicenter 11 (23%)

Number of readmissions reviewed, n ± SD 226 ± 208

Planned readmission excluded, n (%)

Yes 30 (63%)

No 11 (23%)

Not reported 7 (14%)

All-cause readmission, n (%)

Yes 9 (19%)

No 39 (81%)

Percentage preventable readmissions, mean, ± SD 27,8 ± 16,7%

Scoring of preventability, n (%)

Binary 22 (46%)

Scale 4 (8%)

Categorical 17 (35%)

Not applicable (a priori studies) 5 (11%)

A priori preventable causes determined, n (%)

Yes 32 (67%)

No 16 (33%)

Training of reviewers, n (%)

Yes 16 (33%)

No 2 (4%)

Not reported 30 (63%)

Number of reviewers, n (%)

Individual 8 (16%)

Duo 23 (48%)

Duo + team 2 (4%)

Individual + team 2 (4%)

Team 5 (11%)

Individual or duo + panel 3 (6%)

Other 5 (11%)

Double check, n (%)

All cases 28 (58%)

Partially 7 (15%)

Table 1 Descriptives of included studies (Continued)

Study characteristics (n = 48) No. or percentage
of studies

No 3 (6%)

Not reported 10 (21%)

Additional sources, n (%)

Interview or survey 13 (27%)

None 35 (73%)

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 5 of 12

T
a
b
le

2
Pr
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ta
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se
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en

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o
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(N

=
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s
–

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 6 of 12

T
a
b
le
2
Pr
ev
en
ta
b
ili
ty

as
se
ss
m
en

t
o
f

th
e
in
cl
u
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st
u
d
ie
s
(N

=
48
)
(C
on

tin
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)

A
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Pl
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ed
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ad
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N
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%
p
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p
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ai
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Re
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D
o
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Ry
an

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40
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26
,7

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2

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18
,1

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in
ar
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te
am
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se
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–

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ah

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o

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7

14
9

36
,6

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A
ye
s
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l
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se
s
–

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al
ch
i

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R

63
45

71
,4

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in
ar
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o
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te
am
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l
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se
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–

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im

iz
u

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o

15
3

50
32
,7

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in
ar
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ye
s
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p
an
el
al
l
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se
s
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te
rv
ie
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e

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ei
n

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s

21
3

64
29
,5

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in
ar
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n
o
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in
d
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id
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al
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A
In
te
rv
ie
w
f

Su
th
er
la
n
d

ye
s

47
11

23
,4

N
A
n
o
N
R
in
d
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id
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al
N
R
In
te
rv
ie
w
e

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je
d
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r-
So
jo

n
o

14
7

62
42
,2

ca
te
g
o
ric
al
ye
s
ye
s
te
am
N
R
–

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o
m
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ye
s

30
5

90
29
,5

sc
al
e
n
o
ye
s
te
am
al
l
ca
se
s
In
te
rv
ie
w
f

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ch
o
n

ye
s

98
14

14
,3

b
in
ar
y
ye
s
N
R
in
d
iv
id
u
al
N
R
–

Va
n
W
al
ra
ve
n

ye
s

31
7

70
22
,1

sc
al
e
n
o
ye
s
d
u
o
p
ar
ti
al
ly
In
te
rv
ie
w
e

Vi
n
so
n

N
R

66
10

15
,2

ca
te
g
o
ric
al
n
o
N
R
d
u
o
N
R
In
te
rv
ie
w
e

W
al
la
ce

ye
s

20
4

41
20
,1

b
in
ar
y
ye
s
ye
s
d
u
o
al
l
ca
se
s
–

W
as
fy

N
R

89
3

38
0

42
,6

ca
te
g
o
ric
al
ye
s
ye
s
d
u
o
al
l
ca
se
s
–

W
ei
n
b
er
g

ye
s

50
3

6,
0
b
in
ar
y
ye
s
N
R
p
an
el
al
l
ca
se
s
–

W
ill
ia
m
s

ye
s

13
3

78
58
,6

b
in
ar
y
n
o
N
R
in
d
iv
id
u
al
n
o
In
te
rv
ie
w
f

Ya
m

ye
s

60
3

24
6

40
,8

b
in
ar
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n
o
n
o

D
u
o
+
p
an
el

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l
ca
se
s

–
a
P
la
n
n
ed

re
ad

m
is
si
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n
s
w
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co
n
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d
er
ed

ex
cl
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w
h
en

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e
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la
n
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ed

re
ad

m
is
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s
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ex
cl
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as

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ed

.
b
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a

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is
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as

as
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ed

,
b
as
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m
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,
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.

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im

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o
th
er

st
u
d
ie
s.
*B
as
ed

o
n
p
h
as
e
2
o
f
th
e
st
u
d
y

d
in
d
iv
id
u
al
=
a
si
n
g
le

re
vi
ew

er
in
d
ep

en
d
en

tl
y
as
se
ss
ed

th
e
p
re
ve
n
ta
b
ili
ty

o
f
th
e
re
ad

m
is
si
o
n
w
it
h
o
u
t
a
d
o
u
b
le

ch
ec
k
b
y
o
th
er

re
vi
ew

er
s
o
r
a
co
n
se
n
su
s
m
ee
ti
n
g
;i
n
d
iv
id
u
al
+
te
am

/p
an

el
=
a
si
n
g
le

re
vi
ew
er
in
d
ep
en
d
en
tl
y
as
se
ss
ed
th
e
p
re
ve
n
ta
b
ili
ty
o
f
th
e
re
ad

m
is
si
o
n
,
b
u
t
a
d
o
u
b
le

ch
ec
k
is
p
er
fo
rm

ed

o
n
a

se
le
ct
io
n
o
f
ca
se
s;
d
u
o
=
b
o
th

re
vi
ew

er
s
as
se
ss
ed

th
e
p
re
ve
n
ta
b
ili
ty
o
f
th
e
re
ad

m
is
si
o
n
s
an

d
ca
m
e
to

a
m
u
tu
al

ag
re
em

en
t;
d
u
o
+
te
am

/p
an

el
=
b
o
th

re
vi
ew

er
s
as
se
d
th
e
p
re
ve
n
ta
b
ili
ty

ad
d
ed

b
y

a
te
am

o
r
p
an

el
w
h
ic
h
co
u
ld

ad
vi
se

th
e
tw

o
re
vi
ew

er
s
in

ca
se
a
m
u
tu
al
ag
re
em

en
t

o
n
th
e
p
re
ve
n
ta
b
ili
ty

w
as

n
o
t
ac
h
ie
ve
d
;
te
am

o
r
p
an

el
:c
as
es

ar
e
d
ir
ec
tl
y
re
vi
ew

ed
b
y
a
te
am

o
f
3
to

4
p
er
so
n
s.

e
In
te
rv
ie
w

(o
r
q
u
es
ti
o

n
n
ai
re

o
r
su
rv
ey

)
w
as

co
n
d
u
ct
ed

w
it
h
th
e
p
at
ie
n
t
o
n
ly
;

f In
te
rv
ie
w

(o
r
q
u
es
ti
o
n
n
ai
re
o
r
su
rv
ey
)
w
as
co
n
d
u
ct
ed

w
it
h
th
e
p
at
ie
n
t
an

d
th
e

ca
re

p
ro
vi
d
er

(g
en

er
al

p
ra
ct
it
io
n
er

o
f
p
h
ys
ic
ia
n
).

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 7 of 12

guide [22, 37, 40], a bimonthly meeting and/or an
educational program [59].
Agreement was calculated in different ways: the inter-

rater agreement (i.e. kappa coefficient) [15, 16, 23, 30,
40, 42, 50, 52, 53, 60], intrarater reliability [49] or both
[36]; other options were the interclass correlation and a
concordance coefficient [39, 41] or the percentage of
agreement on preventability [25, 33, 37, 43, 48, 55]. A
low level of agreement was associated with the presence
of multiple conditions; the more difficult it was to di-
sentangle the reason for readmissions, the higher the
chance of disagreement between the reviewers [39].

Discussion

The aim of this study was to compare the currently avail-
able methods to assess the preventability of readmissions,
and the implications of these methods in terms of the
preventability rates that were found. The focus on the
methodology of preventability assessment is unique to this
review and the results can be used to contribute to the
development of a consensus-based approach to assess the
preventability of readmissions. Furthermore, we aimed to
provide the reader guidance in how to design, conduct
and report their study in a well-considered manner.
A large heterogeneity in study designs was identified

which limits the comparability of the preventability rates.
In addition, it is currently not possible to distinguish
which part of the variation in preventability rate really
represents variation in quality of care. Only a consensus-
based standardised approach to assess preventability can
reduce the unwanted bias caused by methodological dif-
ferences and contextual factors.
The interpretation of the results was further compli-

cated by inconsistent use of important study definitions
(i.e. definition of preventability). Studies were also contra-
dictory, for example some studies regarded patient factors
such as noncompliance as a potential preventable cause
for readmissions as others regarded this non-preventable.
Most studies used an a priori preventability cause classi-

fication approach which is less time-consuming to apply.
An a priori approach is comparable with an electronic
algorithm to predict potentially preventable readmissions.
In these cases a prediction is based on a specific connec-
tions between variables (i.e. matching or correlated admis-
sion diagnosis codes). Such predictive algorithms, based
on administrative data, are increasingly used. However,
the performance (in terms of the discriminative ability) of
risk predictive models has varied significantly [61].
Although, manually applying these algorithm rules may
improve the likelihood of identifying true potentially pre-
ventable readmissions, it still does not invite the reviewer
to look beyond the predefined potential causes of prevent-
ability. On the other hand, performing chart review is
time-intensive and has a limited reproducibility. Our

results show that researchers try to optimize the
reproducibility in different ways, e.g. the training of
reviewers, a double check with the use of a second re-
viewer and/or a (multidisciplinary) team. Nevertheless,
these different variables were not significantly associated
with preventability percentages.
In the majority of studies the preventability assessment

was performed by a physician or several physicians (often
from the same department or specialty). This might
increase the risk of reluctancy to consider alternatives to
one’s preferred line of thought (i.e. potential causes related
to other specialties). In addition, many patients are treated
by multiple care providers and this might complicate
optimal assessment of the readmissions when a single
(medical specialty) perspective is used [62]. It is currently
unknown which readmissions should be reviewed by a
multidisciplinary team and how that would affect the
preventability outcome and the causes found.
Most studies only assessed preventability based on chart

review. However, charts usually do not contain all the
potential information that can influence the preventability
assessment, for example information on the collaboration
between care providers or lack of social support. Future
research should therefore focus more on examining which
information (i.e. on communication, follow-up care or
information needs) from which care providers is valuable
to optimize the preventability assessment [22]. The studies
that did obtain additional information from the patient-
and primary care provider perspective often did not
describe the added value of this information. This is a
missed opportunity because collecting this information is
often complex and time consuming.
The use of readmission rates to benchmark hospital

performance is controversial [11]. Readmissions often
seem to be caused by a multitude of causes, some of
which are not modifiable by the hospital (i.e. home
environment or social support), meaning hospitals are
penalized for causes that are beyond their control. In
addition, the use of readmission as a quality indicator
may provide a wrong incentive, for example by lengthen-
ing hospital stays to decrease the chance of readmissions
or hesitation to readmit a patient who might benefit
from it. This is contradictory to what the indicator was
designed for, namely to provide the incentive to provide
higher quality care. Hence, readmissions do not seem to
be a useful indicator of quality of care [3].
This was the first review which compared the different

methods used to assess preventability of unplanned
hospital readmissions via medical record review, however,
some limitations need to be discussed. Unfortunately, the
heterogeneity of the studies was large, therefore, the
options for a quality appraisal tool were limited and a
meta-analysis was not possible. To compensate for this,
we performed a (textual) narrative synthesis based on the

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 8 of 12

T
a
b
le

3
A
d
va
n
ta
g
es
,l
im

it

at
io
n

s
an
d
co
n
si
d
er
at
io
n
s
o
f
se
ve
ra
l
st
u
d
y
d
es
ig
n
o
p
ti
o
n
s

A
d
va
n
ta
g
e

Li
m
it
at
io
n

Re
co
m
m
en

d
at
io
n
s

Si
n
g
le
ce
n

te
r

ve
rs
u
s

m
u
lt
ic
en

te
r

Si
n
g
le
ce
n
te
r
st
u
d
ie
s
p
ro
vi
d
e

in
fo
rm

at
io
n

o
n
o
n
e’
s
o
w
n
p
er
fo
rm

an
ce

w
h
ic
h
is

n
ee
d
ed

to
in
d
u
ce

a
q
u
al

it
y

im

p
ro
ve
m
en

t
cy
cl
e

Fo
r
sc
ie
n
ti
fic

p
u
rp
o
se
s
it

is
ea
si
er

to

id
en

ti
fy

w
h
ic
h
re
su
lt
s
ca
n
b
e
ex
tr
ap
o
la
te
d
to

o
th
er

in
st
it
u
te
s
w
h
en

th
e
re
su
lt
s
ar
e
o
b
ta
in
ed

vi
a
a

m
u
lt
ic
en

te
r
st
u
d
y.
Fu
rt
h
er

m
o
re

,i
n
a

m
u
lt
ic
en

te
r
st
u
d
y
b
en

ch
m
ar
ki
n
g
b
et
w
ee
n

th
e
ce
n
te
rs
is
p
o
ss
ib
le
.

C
o
m
p
ar
e
th
e
re
su
lt
s
w
it
h
th
e
cu
rr
en

t
lit
er
at
u
re

o
n
th
e
p
re
ve
n
ta
b
ili
ty
o
f

re
ad
m
is
si
o
n
s,
an
d
b
e
aw

ar
e
o
f

(in
te
r)
n
at
io
n
al
an
d
re
g
io
n
al
d
iff
er
en

ce
s

in
o
rg
an
iz
at
io
n
o
f
ca
re
.

Po
p
u
la
ti
o
n

(F
o
cu
s
o
n
a
sp
ec
ifi
c
p
o
p
u
la
ti
o
n
ve
rs
u
s
a

b
ro
ad

p
o
p
u
la
ti
o
n
)

M
an
u
al
re
vi
ew

is
ea
si
er

to
p
er
fo
rm

o
n
a

sp
ec
ifi
c
g
ro
u
p
(e
.g
.d

ia
g
n
o
si
s
h
ea
rt
fa
ilu
re

o
r
d
ep

ar
tm

en
t)
.

Fo
cu
s
o
n
si
n
g
le
g
ro
u
p
ca
n
ca
u
se

u
n
d
er
es
ti
m
at
io
n
o
f
th
e
p
re
ve
n
ta
b
ili
ty

re
ad
m
is
si
o
n
ra
te

an
d
/o
r
u
n
d
er
re
p
o
rt
in
g
o
f

ce
rt
ai
n
ca
u
se
s.

C
o
n
si
d
er

a
m
u
lt
id
is
ci
p
lin
ar
y
p
an
el
o
r

te
am

to
re
vi
ew

th
e
re
ad
m
is
si
o
n
s
to

re
d
u
ce

b
lin
d
sp
o
ts
.

Re
la
te
d
n
es
s
(f
o
cu
s
o
n
re
ad
m
is
si
o
n
s

th
at

ar
e

re
la
te
d
to

th
e
in
d
ex

re
ad
m
is
si
o
n
ve
rs
u
s

al
l-c
au
se

re
ad
m
is
si
o
n
s)

Re
ad
m
is
si
o
n
s
re
la
te
d
to

th
e
in
d
ex

h
o
sp
it
al
iz
at
io
n
w
ill
g
en

er
al
ly
id
en

ti
fy

ca
u
se
s
th
at

ar
e
re
la
te
d
to

h
o
sp
it
al
ca
re

.

A
ll-
ca
u
se

re
ad
m
is
si
o
n
s
ar
e
ea
si
er

to
id
en
ti
fy
b
as
ed

o
n
ad
m
in
is
tr
at
iv
e
d
at
a,
p
ro
vi
d
e
a
b
ro
ad

sc
o
p
e
an
d
w
ill
id
en

ti
fy
o
th
er

ca
u
se
s;
fo
r

ex
am

p
le
ca
u
se
s
re
la
te
d
to

ca
re

in
th
e
p
rim

ar
y
ca
re

se
tt
in
g
.

D
et
er
m
in
e
th
e
sc
o
p
e
o
f
th
e
q
u
al
it
y

im
p
ro
ve
m
en

t
cy
cl
e;
to

id
en

ti
fy
ca
u
se
s

re
la
te
d
to
h
o
sp
it
al
ca
re

o

r
to

ca
re
o
f

a
re
g
io
n

Ty
p
e
o
f
re
ad
m
is
si
o
n
s

(u
n
p
la
n
n
ed

ve
rs
u
s
p
la
n
n
ed

re
ad
m
is
si
o
n
s)

Se
le
ct
in
g
o
n
ly
u
n
p
la
n
n
ed

re
ad
m
is
si
o
n
s

re
se
m
b
le
s
th
e
re
ad
m
is
si
o
n
s
th
at

ar
e
u
se
d

to
ca
lc
u
la
te

th
e
re
ad
m
is
si
o
n
q
u
al
it
y
in
d
ic
at
o
r

Pl
an
n
ed

re
ad
m
is
si
o
n
m
ig
h
t
al
so

h
av
e

p
re
ve
n
ta
b
le
ca
u
se
s
w
h
ic
h
w
ill
b
e
m
is
se
d
if

p
la
n
n
ed

re
ad
m
is
si
o
n
s
ar
e
ex
cl
u
d
ed

D
et
er
m
in
e
w
h
et
h
er

yo
u
co
n
si
d
er

u
n
p
la
n
n
ed

re
ad
m
is
si
o
n
s
p
re
ve
n
ta
b
le

p
rio
r
to

st
ar
ti
n
g
a
re
ad
m
is
si
o
n
st
u
d
y

Se
tt
in
g
an
d
so
u
rc
es

(f
o
cu
s
o
n
h
o
sp
it
al
ve
rs
u
s
an

in
te
g
ra
te
d

ca
re

n
et
w
o
rk
)

A
ss
es
sm

en
t
b
as
ed

o
n
a
h
o
sp
it
al
’s

p
er
sp
ec
ti
ve

o
n
ly
re
q
u
ire
s

th
e
m
ed

ic
al
re
co
rd

as
si
n
g
le

so
u
rc
e.

Fr
ag
m
en

te
d
an
d
in
co
m
p
le
te

d
es
cr
ip
ti
o
n
o
f

th
e
p
at
ie
n
t’s

jo
u
rn
ey

ca
n
re
su
lt
in

u
n
d
er
re
p
o
rt
in
g
ca
u
se
s
re
la
te
d
to

in
te
g
ra
te
d

ca
re
,p

at
ie
n
t
an
d
so
ci
al
fa
ct
o
rs
.

In
te
rv
ie
w
,q

u
es
tio

n
n
ai
re
o
r
su
rv
ey

a
(s
u
b
se
t)
o
f
p
at
ie
n
ts
an
d
o
r
p
rim

ar
y
ca
re

p
ro
vi
d

er
s.

In
fo
rm

at
io
n
an
d
so
u
rc
es

(w
h
ic
h
so
u
rc
es

an
d
in
fo
rm

at
io
n
to

in
cl
u
d
e;
an
d
in

w
h
ic
h
o
rd
er
)

In
cl
u
d
in
g
th
e
fu
ll
m
ed

ic
al
re
co
rd
,o
u
tp
at
ie
n
t

d
at
a
an
d
ev
en

ad
d
it
io
n
al
so
u
rc
es

(e
.g
.

in
te
rv
ie
w

s)
ca
n
ch
an
g
e
th
e
p
er
sp
ec
ti
ve

o
n
p
re
ve
n
ta
b
ili
ty

an
d

it
s

ca
u
se
s.

Re
vi
ew

er
s
m
ig
h
t
u
se

a
d
iff
er
en

t
ap
p
ro
ac
h
o
f

o
b
ta
in
in
g
/u
si
n
g
th
e
(a
d
d
it
io
n
al
)
in
fo
rm

at
io
n

w
h
ic
h
ca
n
cr
ea
te

u
n
w
an
te
d
d
iff
er
en

ce
s
in

th
e
p
er
sp
ec
ti
ve

o
n
p
re
ve
n
ta
b
ili
ty
.

N
o
te

th
at

fo
r
an

in
te
rv
ie
w

o
f
st
ak
eh

o
ld
er
s
a

cr
o
ss
-s
ec
ti
o
n
al
o
r
p
ro
sp
ec
ti
ve

st
u
d
y
d
es
ig
n
is

n
ee
d
ed

to
re
d
u
ce

re
ca
ll
b
ia
s.

A

st
ric
t
p
ro
to
co
l
an
d
lo
g
b
o
o
k
as

w
el
l

as

tr
ai
n
in
g
p
rio

r
to

st
ar
t
o
f
th
e
st
u
d
y.

C
o
n
si
d
er

to
p
ro
vi
d
e
ad
d
it
io
n
al

in
fo
rm

at
io
n
st
ep

w
is
e
to

as
se
ss
it
s
ad
d
ed

va
lu
e
o
n
th
e
p
re
ve
n
ta
b
ili
ty

as
se
ss
m
en
t.
A
p
rio

ri
(p
re
ve
n
ta
b
ili
ty
)
ca
u
se

cl
as
si
fic
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Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 9 of 12

T
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p
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e.

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 10 of 12

Cochrane recommendations [12]. In addition, since there
was no uniformity amongst studies on the use of (key)
words in their title and abstract, it could be that some
studies on readmissions were missed during our search
because these terms were not included in our search stra-
tegy. All phases were either consensus based –driven and/
or performed by at least two independent data extractors.
However, this procedure could not prevent that some
amount of interpretation bias was present during data
collection, synthesis and the interpretation.
In conclusion, many articles on preventability of read-

missions are currently available, however, a meaningful
comparison is limited due to the large study hetero-
geneity (i.e. the included population, definition inconsis-
tencies and variation in methods to assess preventability)
. Moreover, the majority of assessments was based on a
hospital and physician perspective only, resulting in a
potentially underestimation of factors related to coordin-
ation of care (e.g. integrated care), patient or social sup-
port system. Readmissions are most likely multifactorial
and readmission rate reduction is a shared responsibility
within the network of care providers and the patient or
carer himself. Therefore, the scope should switch from
the hospital to the organization of care within the region
and patient participation. Overall, we recommend that
researchers carefully consider the different methodo-
logical options (i.e. study population, setting and its
modifiable factors, and type of resources) prior to initiat-
ing a study to assess the preventability of readmissions.
In Table 3 we outlined a few important methodological
aspects of readmission studies and provided the ad-
vantages, disadvantages and recommendations for each
of these aspects. Furthermore, we recommend for future
research that the methodological considerations of each
readmission study are explicitly reported to increase
reproducibility and comparability (e.g. the number of
reviewers, review process).

Additional files

Additional file 1: Search strategy. (DOCX 14 kb)

Additional file 2: Inclusion criteria. (DOCX 85 kb)

Additional file 3: Definition of variables. (DOCX 18 kb)

Additional file 4: Characteristics of studies which were excluded based
on the inclusion criteria of the flow chart (N=29). (DOCX 24 kb)

Additional file 5: Detailed descriptives of included studies (N=48).
(DOCX 33 kb)

Additional file 6: Details regarding patient (and/or caregiver) interview
and care provider interview. (DOCX 40 kb)

Additional file 7: Definition of preventability. (DOCX 24 kb)

Abbreviations

GP: General practitioner; NR: Not reported; STAAR: The STate Action on
Avoidable Rehospitalizations

Acknowledgements

The authors are very grateful for assistance by the medical information
specialist that assisted with the search.

Authors’ contributions

Study conception and design was performed by: FKC, MdB, EK and CB. Two
researchers (CB, EK) independently screened all abstracts. Detailed inclusion
and exclusion criteria were applied blindly to all eligible articles by CB, EK
and RS. Data of the included citations was collected by CB, EK, RS, disagreement
was resolved by two independent senior researcher FKC and MdB. Analysis and
interpretation of data was performed by all authors. CB, EK en RS drafted the
manuscript. FKC and MdB critically revised the manuscript. All authors read and
approved the final manuscript.

Funding

Not applicable.

Availability of data and materials

The datasets supporting the conclusions of this article are included within
the article.

Ethics approval and consent to participate

Ethics approval is not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that none of them have received honoraria, reimbursement
or fees from any pharmaceutical companies, related to this study.

Author details

1Department of Clinical Pharmacy, OLVG Hospital, Jan Tooropstraat 164, 1061
AE Amsterdam, The Netherlands. 2Department of Public and Occupational
Health, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public
Health Research Institute, Van der Boechorststraat 7, NL-1081, BT,
Amsterdam, The Netherlands.

Received: 10 August 2018 Accepted: 4 June 2019

References
1. Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in

the Medicare fee-for-service program. N Engl J Med. 2009;360(14):1418–28.
2. Felix HC, Seaberg B, Bursac Z, et al. Why do patients keep coming back?

Results of a readmitted patient survey. Soc Work Health Care. 2015;54(1):1–15.
3. Fischer C, Lingsma HF, Marang-van de Mheen PJ, et al. Is the readmission

rate a valid quality indicator? A review of the evidence. PLoS One. 2014;
9(11):e112282.

4. Rau J. Medicare to penalize 2,217 hospitals for excess readmissions 2012.
Available from: http://www.kaiserhealthnews.org/stories/2012/august/13/
medicare-hospitals-readmissions-penalties.aspx.

5. Yam CH, Wong EL, Chan FW, et al. Avoidable readmission in Hong Kong–
system, clinician, patient or social factor? BMC Health Serv Res. 2010;10:311.

6. Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for
hospital readmission: a systematic review. JAMA. 2011;306(15):1688–98.

7. van Walraven C, Bennett C, Jennings A, et al. Proportion of hospital
readmissions deemed avoidable: a systematic review. CMAJ. 2011;
183(7):E391–402.

8. van Walraven C. The utility of unplanned early hospital readmissions as a
health care quality Indicator. JAMA Intern Med. 2015;175(11):1812–4.

9. van Walraven C, Jennings A, Forster AJ. A meta-analysis of hospital 30-day
avoidable readmission rates. J Eval Clin Pract. 2012;18(6):1211–8.

10. Yam CH, Wong EL, Chan FW, et al. Measuring and preventing potentially
avoidable hospital readmissions: a review of the literature. Hong Kong Med
J. 2010;16(5):383–9.

11. Benbassat J, Taragin M. Hospital readmissions as a measure of quality of
health care: advantages and limitations. Arch Intern Med. 2000;160(8):1074–81.

12. Ryan R. Cochrane consumers and communication review group: data
synthesis and analysis; 2013.

Kneepkens et al. BMC Medical Research Methodology (2019) 19:128 Page 11 of 12

https://doi.org/10.1186/s12874-019-0766-0

https://doi.org/10.1186/s12874-019-0766-0

https://doi.org/10.1186/s12874-019-0766-0

https://doi.org/10.1186/s12874-019-0766-0

https://doi.org/10.1186/s12874-019-0766-0

https://doi.org/10.1186/s12874-019-0766-0

https://doi.org/10.1186/s12874-019-0766-0

http://www.kaiserhealthnews.org/stories/2012/august/13/medicare-hospitals-readmissions-penalties.aspx

http://www.kaiserhealthnews.org/stories/2012/august/13/medicare-hospitals-readmissions-penalties.aspx

13. Cakir B, Gammon G. Evaluating readmission rates: how can we improve?
South Med J. 2010;103(11):1079–83.

14. Feigenbaum P, Neuwirth E, Trowbridge L, et al. Factors contributing to all-
cause 30-day readmissions: a structured case series across 18 hospitals. Med
Care. 2012;50(7):599–605.

15. Halfon P, Eggli Y, van Melle G, et al. Measuring potentially avoidable
hospital readmissions. J Clin Epidemiol. 2002;55(6):573–87.

16. Jimenez-Puente A, Garcia-Alegria J, Gomez-Aracena J, et al. Readmission
rate as an indicator of hospital performance: the case of Spain. Int J Technol
Assess. 2004;20(3):385–91.

17. Koekkoek D, Bayley KB, Brown A, et al. Hospitalists assess the causes of early
hospital readmissions. J Hosp Med. 2011;6(7):383–8.

18. Miles TA, Lowe J. Are unplanned readmissions to hospital really
preventable? J Qual Clin Pract. 1999;19(4):211–4.

19. Pace R, Spevack R, Menendez C, et al. Ability of nurse clinicians to predict
unplanned returns to hospital within thirty days of discharge. Hosp Pract
(1995). 2014;42(5):62–8.

20. Shalchi Z, Saso S, Li HK, et al. Factors influencing hospital readmission rates
after acute medical treatment. Clin Med (Lond). 2009;9(5):426–30.

21. Stein J, Ossman P, Viera A, et al. Was this readmission preventable?
Qualitative study of patient and provider perceptions of readmissions. South
Med J. 2016;109(6):383–9.

22. Auerbach AD, Kripalani S, Vasilevskis EE, et al. Preventability and causes of
readmissions in a National Cohort of general medicine patients. JAMA
Intern Med. 2016;176(4):484–93.

23. Burke D, Link N, Bails D, et al. A taxonomy of seven-day readmissions to an
urban teaching hospital. J Hosp Med. 2016;11(1):33–8.

24. Gautam P, Macduff C, Brown I, et al. Unplanned readmissions of elderly
patients. Health Bull (Edinb). 1996;54(6):449–57.

25. Shimizu E, Glaspy K, Witt MD, et al. Readmissions at a public safety net
hospital. PLoS One. 2014;9:3.

26. Sutherland T, David-Kasdan JA, Beloff J, et al. Patient and provider-identified
factors contributing to surgical readmission after colorectal surgery. J
Investig Surg. 2016;29(4):195–201.

27. Toomey SL, Peltz A, Loren S, et al. Potentially preventable 30-day hospital
readmissions at a Children’s hospital. Pediatrics. 2016;138:2.

28. Williams EI, Fitton F. Factors affecting early unplanned readmission of
elderly patients to hospital. BMJ. 1988;297(6651):784–7.

29. Vinson JM, Rich MW, Sperry JC, et al. Early readmission of elderly patients
with congestive-heart-failure. J Am Geriatr Soc. 1990;38(12):1290–5.

30. Balla U, Malnick S, Schattner A. Early readmissions to the department of
medicine as a screening tool for monitoring quality of care problems.
Medicine (Baltimore). 2008;87(5):294–300.

31. Bianco A, Mole A, Nobile CG, et al. Hospital readmission prevalence and
analysis of those potentially avoidable in southern Italy. PLoS One.
2012;7(11):e48263.

32. van Walraven C, Jennings A, Taljaard M, et al. Incidence of potentially
avoidable urgent readmissions and their relation to all-cause urgent
readmissions. Can Med Assoc J. 2011;183(14):E1067–E72.

33. Ryan J, Andrews R, Barry MB, et al. Preventability of 30-day readmissions for
heart failure patients before and after a quality improvement initiative. Am J
Med Qual. 2014;29(3):220–6.

34. Institute for Healtcare Improvement. Available from: http://www.ihi.org/
Engage/Initiatives/Completed/STAAR/Pages/default.aspx.

35. Fluitman KS, van Galen LS, Merten H, et al. Exploring the preventable causes
of unplanned readmissions using root cause analysis: coordination of care is
the weakest link. Eur J Intern Med. 2016;30:18–24.

36. Oddone EZ, Weinberger M, Horner M, et al. Classifying general medicine
readmissions. Are they preventable? Veterans affairs cooperative studies in
health services group on primary care and hospital readmissions. J Gen
Intern Med. 1996;11(10):597–607.

37. Tejedor-Sojo J, Singleton LM, McCormick K, et al. Preventability of
pediatric 30-day readmissions following ventricular shunt surgery. J
Pediatr-Us. 2015;167(6):1327.

38. Agrawal K, Kumar P, Markert R, et al. Risk factors for 30-day readmissions of
individuals with decompensated cirrhosis. South Med J. 2015;108(11):682–7.

39. Clarke A. Are readmissions avoidable? BMJ. 1990;301(6761):1136–8.
40. Frankl SE, Breeling JL, Goldman L. Preventability of emergent hospital

readmission. Am J Med. 1991;90(6):667–74.
41. Hain PD, Gay JC, Berutti TW, et al. Preventability of early readmissions at a

children’s hospital. Pediatrics. 2013;131(1):e171–81.

42. Harhay M, Lin E, Pai A, et al. Early rehospitalization after kidney
transplantation: assessing preventability and prognosis. Am J Transplant.
2013;13(12):3164–72.

43. Jonas JA, Devon EP, Ronan JC, et al. Determining preventability of pediatric
readmissions using fault tree analysis. J Hosp Med. 2016;11(5):329–35.

44. Kelly CL, Thomson K, Wagner AP, et al. Investigating the widely held belief
that men and women with learning disabilities receive poor quality
healthcare when admitted to hospital: a single-site study of 30-day
readmission rates. J Intellect Disabil Res. 2015;59(9):835–44.

45. Maurer PP, Ballmer PE. Hospital readmissions–are they predictable and
avoidable? Swiss Med Wkly. 2004;134(41–42):606–11.

46. Meisenberg BR, Hahn E, Binner M, et al. Insights into the potential
preventability of oncology readmissions. J Oncol Pract. 2016;12(2):153 -+.

47. Nahab F, Takesaka J, Mailyan E, et al. Avoidable 30-day readmissions among
patients with stroke and other cerebrovascular disease. Neurohospitalist.
2012;2(1):7–11.

48. Nijhawan AE, Kitchell E, Etherton SS, et al. Half of 30-day hospital
readmissions among HIV-infected patients are potentially preventable. AIDS
Patient Care STDs. 2015;29(9):465–73.

49. Saunders ND, Nichols SD, Antiporda MA, et al. Examination of unplanned
30-day readmissions to a comprehensive cancer hospital. J Oncol Pract.
2015;11(2):e177–81.

50. Shah MN, Stoev IT, Sanford DE, et al. Are readmission rates on a
neurosurgical service indicators of quality of care? J Neurosurg. 2013;
119(4):1043–9.

51. Vachon CM, Aaland M, Zhu TH. Readmission of trauma patients in a
nonacademic level II trauma center. J Trauma Acute Care. 2012;72(2):531–6.

52. Wallace SS, Keller SL, Falco CN, et al. An examination of physician-,
caregiver-, and disease-related factors associated with readmission from a
pediatric hospital medicine service. Hosp Pediatr. 2015;5(11):566–73.

53. Wasfy JH, Strom JB, Waldo SW, et al. Clinical preventability of 30-day
readmission after percutaneous coronary intervention. J Am Heart Assoc.
2014;3(5):e001290.

54. Weinberg DS, Kraay MJ, Fitzgerald SJ, et al. Are readmissions after THA
preventable? Clin Orthop Relat Res. 2017;475(5):1414–23.

55. Dawes AJ, Sacks GD, Russell MM, et al. Preventable readmissions to surgical
services: lessons learned and targets for improvement. J Am Coll Surgeons.
2014;219(3):382–9.

56. Glass CC, Gondek SP, Vollmer CM Jr, et al. Readmission following
pancreatectomy: what can be improved? HPB (Oxford). 2013;15(9):703–8.

57. Greenberg JK, Washington CW, Guniganti R, et al. Causes of 30-day
readmission after aneurysmal subarachnoid hemorrhage. J Neurosurg.
2016;124(3):743–9.

58. Mittal MK, Rabinstein AA, Mandrekar J, et al. A population-based study for
30-d hospital readmissions after acute ischemic stroke. Int J Neurosci. 2017;
127(4):305–13.

59. Njeim M, Chiha M, Whitehouse S, et al. System-based approach to
educating internal medicine residents on preventable hospital readmissions.
J Grad Med Educ. 2012;4(4):505–9.

60. Epstein AS, Crosbie C, Martin SC, et al. 30-day-or-sooner readmissions of
gastrointestinal medical oncology patients following cancer center
inpatient service discharge: characteristics and preventability. Hosp Pract
(1995). 2014;42(5):34–44.

61. Zhou H, Della PR, Roberts P, Goh L, et al. Utility of models to predict 28-day
or 30-day unplanned hospital readmissions: an updated systematic review.
BMJ Open. 2016;6(6):e011060.

62. Donze J, Aujesky D, Williams D, et al. Potentially avoidable 30-day hospital
readmissions in medical patients: derivation and validation of a prediction
model. JAMA Intern Med. 2013;173(8):632–8.

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Abstract
Background
Methods
Results
Conclusion
Background
Methods
Data source and searches
Study selection
Critical appraisal of individual sources of evidence
Data synthesis
Data extraction and analysis
Results
Study design and characteristics
Sources of information
Preventability
Cause classification
Reproducibility/reviewer process
Discussion
Additional files
Abbreviations
Acknowledgements
Authors’ contributions
Funding
Availability of data and materials
Ethics approval and consent to participate
Consent for publication
Competing interests
Author details
References
Publisher’s Note

EVIDENCE-
BASED CARE
SHEET

Authors
Hillary Mennella, DNP, ANCC-BC

Cinahl Information Systems,

Glendale, CA

Monica Key, ANP-C, APRN, AOCNP,
CCRN

Cinahl Information Systems, Glendale, CA

Reviewers
Debra Balderrama, RN, MSCIS

Clinical Informatics Services, Tujunga, CA

Alysia Gilreath-Osoff, RN, BSN, CEN,
SANE

Cinahl Information Systems, Glendale, CA

Nursing Executive Practice Council
Glendale Adventist Medical Center,

Glendale, CA

Editor
Diane Pravikoff, RN, PhD, FAAN

Cinahl Information Systems, Glendale, CA

June 8, 2018

Published by Cinahl Information Systems, a division of EBSCO Information Services. Copyright©2018, Cinahl Information Systems. All rights
reserved. No part of this may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by
any information storage and retrieval system, without permission in writing from the publisher. Cinahl Information Systems accepts no liability for advice
or information given herein or errors/omissions in the text. It is merely intended as a general informational overview of the subject for the healthcare
professional. Cinahl Information Systems, 1509 Wilson Terrace, Glendale, CA 91206

Case Management: Readmissions

What We Know
› Readmission is defined as patient admission to the same or a different hospital within a

period of 30 days of discharge(1,3,4)

• The estimated national 30-day, all-cause, hospital readmission rate for Medicare
beneficiaries in the United States was 18.4% in 2012, down from an average of 19%
during the period 2007–2011; this translates to ~ 70,000 fewer readmissions in 2012
than would have occurred if the readmission rate had remained at 19%(7)

–An estimated two-thirds of readmissions are preventable(1)

• Reasons for readmission include premature discharge, inappropriate treatment, and
inadequate patient education and discharge planning(1)

–Hospitals serving a higher population of patients from a lower socioeconomic status
often have higher rates than the national average for readmission,resulting in lower
Medicare reimbursements. Patients from a lower socioeconomic status can have
difficulty procuring follow-up appointments, food, and medications after discharge(10)

› Even though readmission rates have decreased, one in five Medicare patients are still
being readmitted within a month(6)

› In 2010 the Affordable Care Act (ACA) established the Hospital Readmissions Reduction
Program, which provides financial incentives to hospitals to reduce readmissions(3,4)

• The program requires a reduction in Medicare and Medicaid reimbursement to
applicable hospitals for excess readmissions for acute myocardial infarction (AMI),
heart failure (HF), pneumonia, chronic obstructive pulmonary disease (COPD), and
elective hip and/or total knee replacement. A readmission measure for coronary artery
bypass graft (CABG) surgery was added in 2016(3,4)

–Readmission reimbursement calculations for individual hospitals are based on national
readmission rates for these specific diagnoses and are intended to improve health care
for beneficiaries and control unnecessary spending of healthcare dollars(6)

–As of October 1, 2016, penalties went into effect and are applied to all Medicare
discharges, with an average penalty that is less than 1% of the Medicare payment(6)

–By the end of 2016 hospitals lost a total of $420 million in penalties for excess
readmissions(6)

–Hospitals can lose up to 3% of their Medicare reimbursement if they have higher than
average 30-day readmissions for patients with heart failure, heart attack, elective hip or
knee replacement, pneumonia, and an acute exacerbation of COPD(6)

–Current penalties are not large enough to have a big impact on the bottom line and for
some hospitals the penalties are not high enough to justify the cost of adding staff or
taking other steps to reduce readmissions(6)

–Beginning in 2017 the hospital’s base operating pay could be reduced by 6% from
Medicare if a hospital receives the maximum penalties(6)

› Authors of a large study in New York, which utilized data from de-identifiedMedicaid
claims discovered that high-value post-discharge utilization resulted in fewer inpatient

re-hospitalizations. This required population-based transitional care strategies to improve
continuity between settings and considers the illness complexity of the patient(8)

› Case managers can be utilized to make the difference on the bottom line for hospitals by putting in place processes to reduce
readmissions(6)

› A multi-layered approach is necessary to make a positive impact and reduce hospital readmissions. Some hospitals have a
group of nurses acting as health coaches for hundreds of at-risk patients. In some cases these nurses will visit the patients in
their home and routinely follow up with them(6)

• This multi-layered approach along the entire continuum has been shown to positively impact readmission rates(6)

› A readmission task force can help to analyze hospital data and determine the key diagnoses for the focus of the clinical team
to prevent readmissions(6)

› Case managers play an important role in the patient discharge process and in the prevention of unnecessary readmissions.
Discharge is a shared responsibility between staff members, the patient, caregivers, and the case manager; the case manager
is responsible for the safe and smooth transition of care. Collaboration between the case manager, social worker, and treating
clinician must lead to change at the practice level to decrease readmission rates
• Case managers will require extensive education for the advanced practice role and to perform the readmission screening

surveys that are anticipated to emerge during healthcare reform
• In Tampa, Florida the Veterans Administration Health Center used telehealth and phone care initiatives to reduce

congestive heart failure hospital readmission rates by 5%, while also providing a decrease in costs, and improved veteran
satisfaction with overall care experience(12)

–Similarly, in 2013, case management leadership in Flagstaff, Arizona used the Better Outcomes for Older Adults through
Safe Transitions (BOOST; a tool used for evidence-basedquality improvement in the hospital setting) program to
implement telehealth and follow-up phone calls,effectively reducing all-cause 30-day readmissions; the readmission rate
decreased from 23% to 12%. In 2014. The program was implemented in another Flagstaff system hospital to include
pneumonia, COPD, total joint replacements, and AMI, demonstrating an all-cause Medicare 30-day readmission rate of
10.8% compared to the national average of over 18%. and scheduled post-acute follow-up services within one day of
patient discharge(2)

• Researchers in a randomized controlled study of 281 older adults with at least two medical diagnoses demonstrated
that a nurse-led CM program involving basic care, treatment compliance, and arrangements for outpatient follow-up
appointments significantly reduced hospital readmission rates

• New York State has one of the highest readmission rates in the U.S. A New York hospital decreased 30-day readmissions
by 70% for their highest-risk patients by implementing a care coordination team of case managers, social workers, and
patient service coordinators. The team was trained by the BOOST program and also visited readmitted patients to find out
why readmission was necessary

• Pima Council on Aging and Carondelet Health Network have partnered to provide follow-up care coordination for at-risk
patients being discharged from the hospital. The U.S. Centers for Medicare & Medicaid Services (CMS) has referred to the
program as a National Best Practice in reducing hospital readmission rates(11)

What We Can Do
› Case managers and hospitals need to look beyond the hospital walls and determine what happens to patients throughout the

continuum to better avoid readmissions(9)

› Become knowledgeable about CM as an approach to reduce patient readmissions so you can accurately assess your patients’
personal characteristics and health education needs; share this information with your colleagues

› Improving communication with post-acute providers is a critical part of reducing readmissions. Sending a written report as
well as talking to a clinician at a skilled nursing facility, home health agency, or long-termacute care hospital is one way to
improve communication(9)

› Case managers should spend time with the patients and family members for an understanding of patient characteristics, such
as culture, language barriers, socioeconomic status, healthcare literacy, and access to social support, and take these dynamics
into consideration when developing a discharge plan(9)

› If a patient does not have immediate family or other support, then looking for other resources, such as community agencies,
churches, and neighbors becomes vital. Being creative is important for case managers to connect patients with resources
before discharge(9)

› Refer appropriate patients to palliative care is a critical part of reducing readmissions; this involves educating patients and
family members on palliative care and end-of-life issues(5)

› Work closely with case managers who are embedded in physician offices and other venues of care. They are a great source
of information for developing a successful discharge plan because they know what services can safely be provided in which
venue of care. One example is residents of supportive living centers might be able to receive home care services and avoid a
skilled nursing facility admission(5)

› Facilitate discharges early in the day, considering elderly patients have trouble driving at night and many pharmacies are
closed at night(5)

› Follow up with assisted living residents to ensure communication with a clinician to provide the details of the hospitalization
and the treatment plan(5)

› Collaborate with others in your healthcare facility to initiate a CM program to meet the needs of every patient and to
maintain compliance with healthcare reform quality outcome readmission measures

› Track and trend readmission rates and analyze core reasons for rehospitalization
› Involve patients and their caregivers in the discharge planning process, provide education, and implement the teach-back

method regarding performing patient care after discharge to home
› Collaborate with others in your healthcare facility to identify and implement validated and reliable screening tools for

increased risk for readmission among your patient population
› Participate in continuing education for implementation of readmission screening surveys

Coding Matrix
References are rated using the following codes, listed in order of strength:

M Published meta-analysis

SR Published systematic or integrative literature review

RCT Published research (randomized controlled trial)

R Published research (not randomized controlled trial)

C Case histories, case studies

G Published guidelines

RV Published review of the literature

RU Published research utilization report

QI Published quality improvement report

L Legislation

PGR Published government report

PFR Published funded report

PP Policies, procedures, protocols

X Practice exemplars, stories, opinions

GI General or background information/texts/reports

U Unpublished research, reviews, poster presentations or
other such materials

CP Conference proceedings, abstracts, presentation

References
1. Adeoye, S., & Pineo, T. (2014). Reducing excess readmission 101: Evidence-driven strategies and facility-specific initiatives. Journal of Medical Practice Management, 30(1),

42-48. (RV)

2. Care management revamp helps keep readmission rates low. (2017). Hospital Case Management, 25(3), 39-41. (GI)

3. Centers for Medicare & Medicaid Services. (n.d.). The Hospital Readmissions Reduction Program (HRRP). Retrieved May 29, 2018, from
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/HRRP/Hospital-Readmission-Reduction-Program.html (GI)

4. Department of Health and Human Services. (2012). 42 CRF Parts 412, 413, 424, et al. Medicare Program; Hospital inpatient prospective payment systems
for acute care hospitals and the long-term are hospital prospective payment system and fiscal year 2013 rates; hospitals’ resident caps for graduate medical
education payment purposes; quality reporting requirements for specific providers and for ambulatory surgical centers, 77(170), 53258-53750. Retrieved from
http://www.gpo.gov/fdsys/pkg/FR-2012-08-31/pdf/2012-19079 (L)

5. Five more ways to improve readmissions, according to the experts. (2015). Hospital Case Management, 23(1), 4-5. (QI)

6. Five years later, hospitals still struggle with readmissions. (2015). Hospital Case Management: The Monthly Update on Hospital-Based Care Planning and Critical Paths,
23(11), 141-144. (PP)

7. Gerhardt, G., Yemane, A., Hickman, P., Oelschlaeger, A., Rollins, E., & Brennan, N. (2013). Medicare readmission rates showed meaningful decline in 2012. Medicare &
Medicaid Research Review, 3(2), E1-E12. doi:10.5600/mmrr.003.02.b01 (PGR)

8. Hewner, S., Casucci, S., & Castner, J. (2016). The roles of chronic disease complexity, health system integration, and care management in post-discharge healthcare utilization
in a low-income population. Research in Nursing & Health, 39(4), 215-228. doi:10.1002/nur.21731 (GI)

9. Hospitals are still struggling with reducing readmissions. (2015). Hospital Case Management, 23(1), 1-4. (PP)

10. Hospitals can now factor socioeconomic status into readmissions. (2017). Hospital Case Management, 25(3), 41-42. (GI)

11. Hospitals, Council on Aging Partner to reduce readmissions. (2015). Hospital Case Management, 23(1), 9-10. (PP)

12. Messina, W. (2016). Decreasing congestive heart failure readmission rates within 30 days at the Tampa VA. Nursing Administration Quarterly, 40(2), 146-152. doi:10.1097/
NAQ.0000000000000154 (QI)