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Towards a patient journey perspective on causes of unplanned readmissions using a classification framework: results of a systematic review with narrative synthesis

  • The Correction to this article has been published in BMC Medical Research Methodology 2019 19:214



Several literature reviews have been published focusing on the prevalence and/or preventability of hospital readmissions. To our knowledge, none focused on the different causes which have been used to evaluate the preventability of readmissions. Insight into the range of causes is crucial to understand the complex nature of readmissions.

With this review we aim to: 1) evaluate the range of causes of unplanned readmissions in a patient journey, and 2) present a cause classification framework that can support future readmission studies.


A literature search was conducted in PUBMED and EMBASE using “readmission” and “avoidability” or “preventability” as key terms. Studies that specified causes of unplanned readmissions were included. The causes were classified into eight preliminary root causes: Technical, Organization (integrated care), Organization (hospital department level), Human (care provider), Human (informal caregiver), Patient (self-management), Patient (disease), and Other. The root causes were based on expert opinions and the root cause analysis tool of PRISMA (Prevention and Recovery Information System for Monitoring and Analysis). The range of different causes were analyzed using Microsoft Excel.


Forty-five studies that reported 381 causes of readmissions were included. All studies reported causes related to organization of care at the hospital department level. These causes were often reported as preventable. Twenty-two studies included causes related to patient’s self-management and 19 studies reported causes related to patient’s disease. Studies differed in which causes were seen as preventable or unpreventable. None reported causes related to technical failures and causes due to integrated care issues were reported in 18 studies.


This review showed that causes for readmissions were mainly evaluated from a hospital perspective. However, causes beyond the scope of the hospital can also play a major role in unplanned readmissions. Opinions regarding preventability seem to depend on contextual factors of the readmission. This study presents a cause classification framework that could help future readmission studies to gain insight into a broad range of causes for readmissions in a patient journey.

In conclusion, we aimed to: 1) evaluate the range of causes for unplanned readmissions, and 2) present a cause classification framework for causes related to readmissions.

Peer Review reports


The definition of unplanned readmissions varies among countries, but it is most often defined as an urgent readmission within 30 days from a previous admission [1,2,3]. In many cases, unplanned readmissions result in potential health risks for patients, an increased workload for caregivers and excessive healthcare expenditure [4]. Reducing readmission rates is therefore considered to be of great importance. Many countries use readmission rates as a quality indicator of hospital care. However, previous research shows that unplanned readmissions are not only caused by suboptimal care provided by the hospital [5, 6]. In fact, unplanned readmissions that are considered to be potentially preventable due to suboptimal hospital care (~ 20–25% of the unplanned readmissions) often also have other underlying causes which are not related to hospital care [6, 7]. This suggests that hospitals are being held accountable for unplanned readmissions, while they may not always be able to prevent them [8].

In the previous decades, studies have been performed on the prevalence and preventability of readmissions. Existing assessment tools with predefined causes (such as State Action on Avoidable Rehospitalizations (STAAR), Root-Cause Analysis Tool (PRISMA: Prevention and Recovery Information System for Monitoring and Analysis) [9] and Research Electronic Database Capture (REDcap tool) are often applied or adapted in readmission studies. The variation in different sets of causes used makes comparison between studies difficult. Comparison between studies is crucial to fully understand the complex nature of readmissions.

To date, it is unclear which causes are considered in unplanned readmission studies. In particular, the causes which are not related to hospital care have not been given much emphasis so far. Hence, this systematic review focuses on evaluating the different causes that have been taken into consideration in studies on unplanned readmissions using patient record review. With this review we aim to: [1] evaluate the range of causes of unplanned readmissions in a patient journey, and [2] present a cause classification framework that can support future readmission studies.


In 2017, we conducted a systematic review on (the implications of) the different methods used to assess the preventability of unplanned readmissions by use of patient record review [10]. Previous studies demonstrated that health administrative databases often lack extensive information (e.g. functional status and social support) [11]. Therefore, we focused on studies which used patient record review to assess preventability of unplanned readmissions. The current systematic review provides an in-depth insight on the causes that have been used by the studies in the previous review.

Literature search

The literature search was applied in Web of Science, Scopus, Pubmed and Embase in December 2016, using “readmission and avoidability or preventability” as key terms (Additional file 1). A medical information specialist was consulted for the search. All citations were imported into Endnote × 7.3.1TM.

Study selection

The 77 studies which were included in the previous review [10] were checked for eligibility for this review by two researchers (CB and RS) (see Additional file 2). Studies were included if they fulfilled to the following criteria: original data, primary focus on preventable readmissions, clear description of preventable readmissions and potential causes of preventable readmissions (the cause classification) (see Additional file 3). We defined a cause classification as the description of at least three causes or synonyms for causes (e.g. (contributing) factors and reasons). Studies that described the causes of preventable readmissions (≥3) were further reviewed. Studies that made no distinction in readmissions and (primary) admissions, or preventable readmissions and non-preventable readmissions, were excluded from further analysis. In case of disagreement, a senior researcher was consulted to reach a final selection of studies.

Critical appraisal of individual studies

We applied a validated approach to evaluate and compare the studies. This approach was developed by the Cochrane Consumers and Communication Review Group with the aim to perform a structured and transparent analysis for systematic reviews that rely primarily on the use of words and text to summarize and explain the findings of the synthesis. The approach can be described as ‘narrative’ analysis or synthesis [12]. We used this approach because of the large heterogeneity in study designs, and because other quality appraisal approaches and tools were less appropriate to apply. Prior to the narrative analysis a data-charting form was jointly developed by the authors to determine which variables to extract (including defining these variables). Subsequently, the authors independently charted the data, discussed the results and continuously updated the data-charting form in an iterative process. The data-charting form included variables such as: study design characteristics, sources of information to assess preventability, definition of preventability and percentage of preventable readmissions. After extracting the data the authors critically evaluated the applicability of the data and tabulated the results in order to identify patterns across the included studies.

Data collection and classification


Two researchers (RS and CB) collected all the causes described by the studies. Each cause was classified as preventable or unpreventable. In our previous review, we found that the definition of preventability varied widely among studies. Many studies did not provide a clear definition, but referred to a cause classification with causes that were pre-defined as preventable [10]. For instance, Williams et al. defined potential areas to avoid readmissions; ‘It was noted that readmission 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 practitioner and subsequent action by the general practitioner, sufficient and prompt nursing and social services support, and management of medication’ [13]. Other studies such as Ryan et al. provided a broad definition of preventability; ‘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’ [14].

In this study, the researchers coded whether a cause was preventable as stated by the study authors. When the study was unclear regarding the preventability of a cause, the researchers classified the cause as neutral. Causes that studies considered both preventable and unpreventable, were coded as both.

Root cause

The root causes were based on the PRISMA classification scheme of Schaaf & Habraken [9]. PRISMA is an abbreviation of Prevention and Recovery Information System for Monitoring and Analysis, and is often applied for root cause analyses in healthcare. Schaaf & Habraken defined four root causes: technical, organizational, human behavior and patient. We adapted these categories prior to the start of the data collection based on our experience with patient record reviewing in several Dutch hospitals [91]. We sub-divided the root causes “organization, human and patient” in organization (integrated care), organization (hospital department level), human (care provider), human (informal caregiver), patient (self-management) and patient (disease). In addition, we provided examples of causes for the settings: hospital care, ambulatory care and home (care). Hospital care was defined as the complete care process from admission until discharge, including outpatient visits after discharge. Ambulatory care was defined as medical care provided in an outpatient setting. Care at home was defined as informal care provided at home after discharge.

Two researchers (RS, MdB, CB, FK independently) allocated each cause to the root causes mentioned above. A third senior researcher performed a double check on the final cause classification. Disagreements between researchers were resolved during meetings (RS, CB, FK, MdB) until consensus was reached.

A few studies combined multiple types of causes within one single cause. We separated these different causes in order to allocate each of them to the most appropriate root cause. This resulted in a higher number of causes than there were originally present in the study. Furthermore, we were not able to allocate all causes to one root cause because some causes lacked a clear description of the context. We classified these causes as Unclassifiable. Specific categories of causes such as planned readmissions or unrelated readmissions were not considered for further analysis as these were not root causes for a readmission. After allocating all the causes, a final cause classification framework was constructed. Data collection and analyses were documented in Microsoft Excel 2016.


After applying the detailed inclusion and exclusion criteria 32 studies were excluded for this review, leaving 45 studies for further analysis (see Additional file 2b). The 32 studies were excluded because of at least one of the following reasons: no original data [16,17,18], no primary focus on preventable readmissions [15, 19,20,21,22], no clear description of methods and results (e.g. no distinction in preventability or type of admission [23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44] and no description of causes [45]. An overview of the excluded studies is shown in Additional file 4.

Study design and characteristics

A summary of the study characteristics is shown in Table 1. The majority of the studies (64.4%) was conducted in the US and all studies were performed in a hospital setting (75.6% monocenter studies). Eight studies (17.8%) examined all-cause readmissions, meaning that these studies included readmissions from all departments, irrespective of whether this department was similar to that of the previous admission [46,47,48,49,50,51,52,53]. The majority of the studies included readmissions of a specific specialty (31.1%) [54,55,56,57,58,59,60,61,62,63,64,65,66,67] such as readmissions to a pediatric department. Twenty-seven percent of the studies examined readmissions of a specific group to a specific specialty (26.6%) [14, 68,69,70,71,72,73,74,75,76,77,78] such as patients with diabetes readmitted to internal medicine. Twenty-four percent of the studies included readmissions of a specific group (24.4%), such as elderly [2, 3, 13, 79,80,81,82,83,84,85,86]. Other studies included readmissions occurring to any department for a specific group (e.g. elderly to internal medicine).

Table 1 Descriptive characteristics of included studies that reported causes* (n = 45)

Eight studies referred to an existing root-cause assessment tool with predefined causes such as STAAR, PRISMA or REDcap tool [2, 53, 65, 69, 76, 81, 84, 85]. Multiple studies referred to causes used in previous publications [3, 50, 55, 57, 59,60,61, 64, 66, 67, 71, 74, 75, 79]. In particular, the studies of Clarke [59], Goldfield [87], Jiminez-Puente [49] and Oddone [74] were frequently referred to.

Cause classification

The frequencies of each root cause are listed in Additional file 5. A total of 381 causes were found of which 275 were reported as preventable and 44 as unpreventable (see Additional file 5). Twenty-six causes were reported as both preventable and unpreventable in a single study, and these causes were coded as both. Examples of causes that were considered differently among studies are listed in Table 2. Other causes that were not explicitly defined as preventable or unpreventable (n = 36) were coded as neutral. The final cause classification framework is listed in Table 3.

Table 2 Causes that were reported as both preventable and unpreventable
Table 3 Final cause classification framework


None of the studies reported technical failures as a cause for preventable readmissions.

Organization – integrated care

Eighteen studies reported causes related to the organization of integrated care [13, 48, 51, 53, 55, 57,58,59,60,61, 64, 65, 67, 72, 74, 79, 80, 82]. Fifteen studies considered these causes as preventable [48, 51, 57,58,59,60,61, 64, 65, 67, 72, 74, 79, 80, 82]. Social readmissions, unavailability of outpatient care and system failures were frequently considered as preventable. One study reported that hospitals were partly accountable for social readmissions [48], while other studies reported that social readmissions were related to inadequate care by the caretaker/spouse [84, 86]. Two studies stated that causes related to the organization of integrated care were seen as unpreventable [64, 72]. For example, Jonas described the lack of alternative resources as an unpreventable cause [72].

Organization – hospital department level

The majority of the studies (n = 44; 97.8%) described causes related to the organization of care at hospital department level [3, 13, 14, 46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86]. Many causes were related to the coordination and planning of care. Feigenbaum et al. (2012) reported factors contributing to potentially preventable readmissions such as “suboptimal coordination of care during index stay” and “inadequate arrangement of supplies during discharge process” [47]. In addition, Greenberg et al. (2016) reported that a readmission could be prevented if the disposition of planning and the coordination of care would have been adequate. Forty-two studies described these causes as preventable [3, 14, 46,47,48,49,50,51,52, 54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86]. Readmissions related to complications caused by the care provided during the previous admission were often reported as a preventable cause [2, 3, 11, 47,48,49, 52, 54, 59, 61,62,63,64, 66, 72, 76, 78, 79, 81, 84, 85].

Nine studies also described unpreventable causes related to the organization of patient care [50, 61, 63, 64, 69, 70, 72, 75, 80]. Some studies reported complications related to a specific patient population [70, 72, 76]. For example, the study of Vachon et al. (2012) focused on trauma patients and included the following complications: wounds, abdominal, pulmonary, thromboembolic, central nervous system, hematoma and other [76].

Human – care provider

Seven studies reported causes related to the care provider [2, 67, 68, 72, 74, 84, 86], such as inadequate decision making, inadequate (clinical) skills and knowledge, or lack of experience. In all cases, these causes were considered to be preventable. Examples of these causes include: ‘Failure resulting from faulty task planning or performance’ and ‘Failure of an individual to apply their knowledge to a new clinical situation’ [2].

Human – informal caregiver

Six studies described causes related to the informal caregiver [13, 71, 77, 84,85,86]. All these causes were seen as preventable. For example, Harhay and Vinson described inadequate support at home as a cause for preventable readmissions.

Patient – self-management

Twenty-one studies included causes related to self-management of the patient [13, 14, 47, 48, 51, 53,54,55, 58, 59, 61, 64, 67, 68, 71, 74, 75, 77, 79, 81, 82]. Ten studies described causes related to self-management as preventable [14, 47, 48, 51, 54, 55, 58, 64, 67, 68, 71, 74, 75, 77, 82]. Non-adherence was also frequently reported as a preventable cause [14, 51, 54, 59, 61, 67, 71, 74, 77, 82]. For example, Yam described adherence problems and patient coping as causes for preventable readmissions. In six studies, causes related to self-management were seen as unpreventable [58, 59, 61, 64, 79, 81]. For example, Burke considered causes such as adherence to discharge plan, refusal of discharge plan and substance use as unpreventable.

Patient – disease

Many studies reported causes related to the patient’s disease [3, 13, 48,49,50, 53, 58, 59, 61, 64, 66, 67, 70, 72, 79,80,81,82, 86]. Ten studies considered disease related causes as potentially preventable causes. Clarke reported ‘recurrence or continuation of disorder leading to first admissions’ as a preventable disease-related cause [59]. Disease progression (n = 16) was frequently reported as unpreventable. Examples of the disease-related causes were; chronic or relapsing disorder [59, 61, 79], unforeseen worsening of disease progress and closely related conditions [49, 58, 72], acute myocardial ischemia and poorly controlled arrhythmias [82].


Twelve studies reported some causes that could not be classified into root causes [13, 14, 47, 59, 65, 69, 71, 74, 75, 78, 82, 85]. Causes such as problems with services can apply to institutions, departments or individuals. For example, patient assessment was mentioned as a cause for readmission, but it was not specified who performed the patient assessment or what was exactly meant with it.


Purpose of study and significant conclusions

The main objective of this systematic review was to summarize the range of causes described for unplanned readmissions and to present a cause classification framework for causes of readmissions. The findings of this review show that many studies primarily focus on causes related to organization of care at the department level. The causes were mainly evaluated from a hospital perspective. None reported technical failures as one of the causes of (preventable) readmissions. We succeeded in classifying the majority of the causes according to the adapted PRISMA scheme and to distinguish between levels of care. We were not able to allocate causes that were ambiguous.

Key results compared to other studies

The results of this review indicate that the causes of readmissions depend on the context of the study, e.g. the inclusion of department/healthcare organization, case-mix, assessor of preventability, and definition of preventability. All studies were conducted in the hospital and several studies included causes beyond the setting of the hospital. The latter studies often identified other causes for readmissions in addition to hospital care (e.g. social support [13, 71, 77, 84,85,86]). This finding is in line with the existing literature [6, 11, 88,89,90]. Zhou et al. (2017) reviewed studies which used prediction models for (preventable) unplanned readmissions. They identified that health insurance and overall prognosis should be considered as contributors in addition to the clinical factors which are normally included in the statistical models. We also found that factors such as self-management, social support, and type of healthcare organization can play a role. Other factors beyond the scope of the hospital should be assessed in more detail to gain a better insight into the complexity behind unplanned readmission and to understand where interventions can have the most impact. In addition, gaining more understanding on these factors is necessary in order to optimize the applicability of unplanned readmissions as a quality indicator of integrated care [11, 88]. Decreasing unplanned readmissions needs a holistic approach, because health care is a complex dynamic system in which patients, professionals, health care organization are acting within the regulations of their national health care system.

Furthermore, this review highlights that studies differ in which causes are considered to be preventable. In particular, complications, adherence and disease progression were seen as both preventable and unpreventable. For example, ‘foreseen complications’ were seen as preventable [61, 79]. Complications of surgical procedures were also reported as preventable in many studies [48, 49, 81]. Greenberg et al. reported complications related to neurological impairment and immobility as an unpreventable cause [70]. Shah et al. considered complications as preventable and unpreventable. They defined the following complications: complications occurring in spite of best practices being followed, complications due to progression of natural history of certain chronic neurosurgical disease, post-procedure complications and complications related to medication use. The first two were reported as unpreventable, and the latter two as preventable [63]. These findings highlight that preventability can differ depending on many contextual factors and what the authors of studies regard as adequate care.

The proposed classification allows researchers and policymakers to further consider the complex nature of readmissions. Differences in cause classifications can be problematic for fair comparison of studies. Therefore, it is essential that studies describe the context of the research setting/research population and elaborate on what they regard as preventable.

In addition, this review indicates that the assessment of readmissions is mainly based on data that is inputted in the hospital information system. Some studies included interviews and were thereby able to capture the patients’ experience. However, the transcripts were not available and therefore not included in this review. Furthermore, studies indicated that interviews with patients and/or caregivers can provide additional information on factors beyond the hospital setting which cannot be found in medical records [85]. For instance, Sutherland et al. (2016) found that the combination of patient interviews and chart review revealed additional gaps in care [75]. In addition, Toomey et al. (2014) found in 31.2% of cases that interviews with patients and primary care providers provided new information. These findings support other studies stating that increased involvement of patients and other stakeholders are crucial for assessing the cause of the readmission and may contribute to the prevention of readmissions and to better quality of care [89].

Strengths and limitations

This review provides insight into the range of causes reported in unplanned readmission studies. The insights gained from this review may help others in conducting readmission studies. However, this review has some limitations. Firstly, the studies included were based on a set of articles which were collected for a previous review [10]. As a consequence, we may have missed studies which also examined the causes of unplanned readmissions, but did not provide information on the rate of preventable readmissions. This might have limited the number of causes reported in this study and consequently the number of root causes/categories in our cause classification framework. However, we performed a cross reference checking in Scopus and Web-of-Science and did not find additional studies. Secondly, we allocated a single cause to only one root cause. Thus, causes which consisted of multiple sub-causes were disentangled into separate causes. This might have influenced the frequency of the themes and subthemes that were found. Thirdly, studies which did not explicitly specify the context of a specific cause (ambiguous causes) were considered “Unclassifiable”. As a result, the number of causes related to other root causes may be underestimated. Lastly, all phases were either consensus based-driven and/or performed by at least two independent data extractors. However, using this procedure can not preclude that some amount of interpretation bias occurs during data collection, synthesis and interpretation.

Recommendations for policy

Since 2016, unplanned readmissions have been used as a quality indicator for hospital care in the Netherlands. To increase the comparability of causes between readmission studies, we advise that the use of a standardized cause classification framework should be stimulated. The framework proposed in this review provides a broad range of causes which are most frequently observed. Regarding hospital care at the department and institutional level this overview is rather complete, although technical causes are lacking and are becoming more relevant due to development of eHealth, mHealth and ICT supported long distance care. Causes at the patient and health care system level are still of limited detail. For example, more information on the patient experience can be collected using interviews. Insight into these causes is crucial for developing improvement opportunities.

In addition, the proposed framework may contribute to a transparent development of prediction models. Information on how data sources are used to calculate the readmission indicator are often lacking [11]. Current prediction models depend on a limited range of data documented in the hospital information system. Information on what happens after discharge is (often) not documented. Hence, policy makers should be careful in holding hospitals accountable for unplanned readmissions as long as it is unclear which percentage of these readmissions is truly preventable by preventive actions of the hospital itself. Unplanned readmission should be viewed as adverse events occurring in a complex dynamic system, in which patients, professionals and organizations all play a crucial role, regulated by the healthcare system.

Recommendations for research

This review indicates that the causes of unplanned readmissions which are examined by the studies differ between studies and are often limited to causes focused on hospital care. As a result, the multifactorial nature of readmissions is not well understood and certain contributing causes might be overlooked. This limits the potential impact of (patient-centered) interventions to prevent readmissions [88]. To improve our understanding of readmissions, all actors involved in the patient journey should be considered. The suggested framework may provide direction on which causes to include in a readmission study and prediction models. In the future, we hope that with the use of prediction models, high-risk patients can be more easily identified and targeted for alternative management [90]. In addition, future research should take into account the interdependency of causes. For instance, when a patient gets readmitted due to an incorrect assessment by a physician at discharge, this readmission might be the result of how readmissions are handled at a department/organization. Physicians might not be effectively trained to ask the patient if they are ready to be discharged. Lack of skills can thus also be considered a result of suboptimal organization of care (organization department level care). Failure on organization level (e.g. missed opportunity to train physicians) or care-provider level (lack of skills) are important to consider. In addition, it is also possible that failure on one level might be mitigated by other levels. Each level must be considered in the study of readmissions. Multiple causes of readmissions - in and beyond the hospital - play a role. All these causes should be assessed to capture the complex nature of readmissions and should be considered interdependently.


In conclusion, we aimed to: [1] evaluate the range of causes for unplanned readmissions, and [2] present a cause classification framework for causes related to readmissions. The results show that the causes of readmissions used differ considerably among the studies. The current use of different causes limits the opportunity to compare studies and to learn from unplanned readmissions. A shared vision on unplanned readmissions is necessary to improve the uniformity and transparency on the causes of readmissions. This can be achieved by ordering all causes in the new cause classification framework based on the PRISMA cause classification. The new cause classification framework may contribute to the standardization of designing and conducting readmission studies, and the comparability of readmission studies. The findings of this review may help us to understand the complex nature of readmissions and emphasize the importance of using a broad range of causes that may occur on the patient’s journey when examining unplanned readmissions. As described by the studies, unplanned readmissions can be caused by many factors at all levels of the health care system throughout all the phases of the patient journey.

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article or provided in the additional files.

Change history

  • 27 November 2019

    Due to an error introduced during copyediting of this article [1], following corrections need to be made.


PRISMA (flowcharts):

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PRISMA (root cause analysis tool):

Prevention and Recovery Information System for Monitoring and Analysis

REDcap tool:

Research Electronic Database Capture


State Action on Avoidable Rehospitalizations


  1. 1.

    Blunt I, Bardsley M, Grove A, Clarke A. Classifying emergency 30-day readmissions in England using routine hospital data 2004–2010: what is the scope for reduction? Emerg Med J. 2015;32(1):44–50.

    PubMed  Google Scholar 

  2. 2.

    Cooksley T, Merten H, Kellett J, Brabrand M, Kidney R, Nickel C, et al. PRISMA analysis of 30 day readmissions to a tertiary cancer hospital. Acute Med. 2015;14(2):53–6.

    PubMed  Google Scholar 

  3. 3.

    Kelly CL, Thomson K, Wagner AP, Waters JP, Thompson A, Jones S, 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.

    CAS  PubMed  Google Scholar 

  4. 4.

    Felix HC, Seaberg B, Bursac Z, Thostenson J, Stewart MK. Why do patients keep coming back? Results of a readmitted patient survey. Soc Work Health Care. 2015;54(1):1–15.

    PubMed  PubMed Central  Google Scholar 

  5. 5.

    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.

    CAS  PubMed  Google Scholar 

  6. 6.

    Fischer C, Lingsma HF, Marang-van de Mheen PJ, Kringos DS, Klazinga NS, Steyerberg EW. Is the Readmission Rate a Valid Quality Indicator? A Review of the Evidence. PLoS ONE. 2014;9(11):e112282.

    PubMed  PubMed Central  Google Scholar 

  7. 7.

    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.

    CAS  PubMed  Google Scholar 

  8. 8.

    Axon R, Williams MV. Hospital readmission as an accountability measure. JAMA. 2011;305(5):504–5.

    CAS  PubMed  Google Scholar 

  9. 9.

    Van der Schaaf T, Habraken M. PRISMA-Medical: a brief description. Eindhoven, The Netherlands: Eindhoven University of Technology; 2005.

    Google Scholar 

  10. 10.

    Kneepkens E-L, Brouwers C, Singotani RG, de Bruijne MC, Karapinar-Çarkit F. How do studies assess the preventability of readmissions? A systematic review with narrative synthesis. BMC Med Res Methodol. 2019;19(1):128.

    PubMed  PubMed Central  Google Scholar 

  11. 11.

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

    PubMed  Google Scholar 

  12. 12.

    Ryan R, Consumers C. Communication review group. Cochrane Consumers and Communication Review Group: data synthesis and analysis 2013.

  13. 13.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Ryan J, Andrews R, Barry MB, Kang S, Iskandar A, Mehla P, 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.

    PubMed  Google Scholar 

  15. 15.

    El-Jawahri A, Keenan T, Abel GA, Steensma DP, LeBlanc TW, Chen Y-B, et al. Potentially avoidable hospital admissions in older patients with acute myeloid leukaemia in the USA: a retrospective analysis. The Lancet Haematology. 2016;3(6):e276–e83

    PubMed  Google Scholar 

  16. 16.

    Halfon P, Eggli Y, Pretre-Rohrbach I, Meylan D, Marazzi A, Burnand B. Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care. Med Care. 2006;44(11):972–81.

    PubMed  Google Scholar 

  17. 17.

    Herzig SJ, Schnipper JL, Doctoroff L, Kim CS, Flanders SA, Robinson EJ, et al. Physician perspectives on factors contributing to readmissions and potential prevention strategies: a multicenter survey. J Gen Intern Med. 2016;31(11):1287–93.

    PubMed  PubMed Central  Google Scholar 

  18. 18.

    Jackson AH, Fireman E, Feigenbaum P, Neuwirth E, Kipnis P, Bellows J. Manual and automated methods for identifying potentially preventable readmissions: a comparison in a large healthcare system. Bmc Med Inform Decis. 2014;14.

  19. 19.

    Borzecki AM, Chen Q, Restuccia J, Mull HJ, Shwartz M, Gupta K, et al. Do pneumonia readmissions flagged as potentially preventable by the 3M PPR software have more process of care problems? A cross-sectional observational study. Bmj Quality & Safety. 2015;24(12):753–63.

    Google Scholar 

  20. 20.

    Brooks GA, Abrams TA, Meyerhardt JA, Enzinger PC, Sommer K, Dalby CK, et al. Identification of Potentially Avoidable Hospitalizations in Patients With GI Cancer. J Clin Oncol. 2014;32(6):496−+.

    PubMed  PubMed Central  Google Scholar 

  21. 21.

    Ruiz B, Garcia M, Aguirre U, Aguirre C. Factors predicting hospital readmissions related to adverse drug reactions. Eur J Clin Pharmacol. 2008;64(7):715–22.

    PubMed  Google Scholar 

  22. 22.

    Witherington EM, Pirzada OM, Avery AJ. Communication gaps and readmissions to hospital for patients aged 75 years and older: observational study. Qual Saf Health Care. 2008;17(1):71–5.

    CAS  PubMed  Google Scholar 

  23. 23.

    Allen Liles E Jr, Moore CR, Stein J. Feedback on bounce backs: real-time notification of readmissions and the impact on readmission rates and physician perceptions. South Med J. 2015;108(6):354–8.

    PubMed  Google Scholar 

  24. 24.

    Amin D, Ford R, Ghazarian SR, Love B, Cheng TL. Parent and physician perceptions regarding preventability of pediatric readmissions. Hosp Pediatr. 2016;6(2):80–7.

    PubMed  PubMed Central  Google Scholar 

  25. 25.

    Bell H, Povilus, J. & Yarbrough, P.M. The use of an automated notification system to identify and address early readmissions by a university hospitalist service. Hospital Practice 2015.

  26. 26.

    Experton B, Ozminkowski RJ, Pearlman DN, Li ZL, Thompson S. How does managed care manage the frail elderly? The case of hospital readmissions in fee-for-service versus HMO systems. Am J Prev Med. 1999;16(3):163–72.

    CAS  PubMed  Google Scholar 

  27. 27.

    Gilotra NA, Shpigel A, Okwuosa IS, Tamrat R, Flowers D, Russell SD. Patients commonly believe their heart failure hospitalizations are preventable and identify worsening heart failure, nonadherence, and a knowledge gap as reasons for admission. J Card Fail. 2017;23(3):252–6.

    PubMed  Google Scholar 

  28. 28.

    Graham H, Livesley B. Can readmissions to a geriatric medical unit be prevented. Lancet. 1983;1(8321):404–6.

    CAS  PubMed  Google Scholar 

  29. 29.

    Hauviller L, Eyvrard F, Garnault V, Rousseau V, Molinier L, Montastruc J, et al. Hospital re-admission associated with adverse drug reactions in patients over the age of 65 years. Eur J Clin Pharmacol. 2016;72(5):631–9.

    CAS  PubMed  Google Scholar 

  30. 30.

    Hechenbleikner EM, Makary MA, Samarov DV, Bennett JL, Gearhart SL, Efron JE, et al. Hospital readmission by method of data collection. J Am Coll Surgeons. 2013;216(6):1150–8.

    Google Scholar 

  31. 31.

    Kirk E, Prasad MK, Abdelhafiz AH. Hospital readmissions: patient, carer and clinician views. Acute Med. 2006;5(3):104–7.

    PubMed  Google Scholar 

  32. 32.

    Lee MJ, Daniels SL, Wild JRL, Wilson TR, Grp SR. Readmissions after general surgery: a prospective multicenter audit. J Surg Res. 2017;209:53–9.

    PubMed  Google Scholar 

  33. 33.

    Levy A, Alsop K, Hehir M, Lock V, Greenwood R, Tobin G. Hospital readmissions. We'll meet again. Health Serv J. 2000;110(5725):30–1.

    CAS  PubMed  Google Scholar 

  34. 34.

    Ludke RL, Macdowell NM, Booth BM, Hunter SA. Appropriateness of admissions and discharges among readmitted patients. Health Serv Res. 1990;25(3):501–25.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    McIntyre LK, Arbabi S, Robinson EF, Maier RV. Analysis of risk factors for patient readmission 30 days following discharge from general surgery. JAMA Surg. 2016;151(9):855–61.

    PubMed  Google Scholar 

  36. 36.

    Patel KK, Vakharia N, Pile J, Howell EH, Rothberg MB. Preventable admissions on a general medicine service: prevalence, causes and comparison with AHRQ prevention quality indicators-a cross-sectional analysis. J Gen Intern Med. 2016;31(6):597–601.

    PubMed  PubMed Central  Google Scholar 

  37. 37.

    Trickey AW, Wright JM, Donovan J, Reines HD, Dort JM, Prentice HA, et al. Interrater reliability of hospital readmission evaluations for surgical patients. Am J Med Qual. 2017;32(2):201–7.

    PubMed  Google Scholar 

  38. 38.

    Volk ML, Tocco, R.S., Bazick, J, Rakoski, M.O. & Lok, A.S. Hospital Re-Admissions among Patients with Decompensated Cirrhosis. Am J Gastroenterol. 2012.

  39. 39.

    Yap V, Mutneja R, Metersky M. Thirty-day readmissions after pneumonia: how many are preventable? Conn Med. 2016;80(3):147–51.

    PubMed  Google Scholar 

  40. 40.

    Epstein AS, Crosbie C, Martin SC, Egan B, Goring TN, Koo DJ, 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.

    Google Scholar 

  41. 41.

    Fluitman KS, van Galen LS, Merten H, Rombach SM, Brabrand M, Cooksley T, 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.

    CAS  PubMed  Google Scholar 

  42. 42.

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

    CAS  Google Scholar 

  43. 43.

    Hain PD, Gay JC, Berutti TW, Whitney GM, Wang W, Saville BR. Preventability of early readmissions at a children's hospital. Pediatrics. 2013;131(1):e171–81.

    PubMed  Google Scholar 

  44. 44.

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

    PubMed  PubMed Central  Google Scholar 

  45. 45.

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

    PubMed  Google Scholar 

  46. 46.

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

    PubMed  Google Scholar 

  47. 47.

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

    PubMed  Google Scholar 

  48. 48.

    Halfon P, Eggli Y, van Melle G, Chevalier J, Wasserfallen JB, Burnand B. Measuring potentially avoidable hospital readmissions. J Clin Epidemiol. 2002;55(6):573–87.

    PubMed  Google Scholar 

  49. 49.

    Jimenez-Puente A, Garcia-Alegria J, Gomez-Aracena J, Hidalgo-Rojas L, Lorenzo-Nogueiras L, Perea-Milla-Lopez E, et al. Readmission rate as an indicator of hospital performance: the case of Spain. Int J Technol Assess. 2004;20(3):385–91.

    Google Scholar 

  50. 50.

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

    CAS  PubMed  Google Scholar 

  51. 51.

    Pace R, Spevack R, Menendez C, Kouriambalis M, Green L, Jayaraman D. Ability of nurse clinicians to predict unplanned returns to hospital within thirty days of discharge. Hosp Pract (1995). 2014;42(5):62–8.

    Google Scholar 

  52. 52.

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

    CAS  Google Scholar 

  53. 53.

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

    PubMed  Google Scholar 

  54. 54.

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

    PubMed  Google Scholar 

  55. 55.

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

    PubMed  PubMed Central  Google Scholar 

  56. 56.

    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.

    Google Scholar 

  57. 57.

    Bianco A, Mole A, Nobile CG, Di Giuseppe G, Pileggi C, Angelillo IF. Hospital readmission prevalence and analysis of those potentially avoidable in southern Italy. PLoS One. 2012;7(11):e48263.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

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

    PubMed  Google Scholar 

  59. 59.

    Clarke A. Are readmissions avoidable? BMJ. 1990;301(6761):1136–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Dawes AJ, Sacks GD, Russell MM, Lin AY, Maggard-Gibbons M, Winograd D, et al. Preventable readmissions to surgical services: lessons learned and targets for improvement. J Am Coll Surgeons. 2014;219(3):382–9.

    Google Scholar 

  61. 61.

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

    PubMed  Google Scholar 

  62. 62.

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

    PubMed  Google Scholar 

  63. 63.

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

    PubMed  PubMed Central  Google Scholar 

  64. 64.

    Shimizu E, Glaspy K, Witt MD, Poon K, Black S, Schwartz S, et al. Readmissions at a Public Safety Net Hospital. Plos One. 2014;9:3.

    Google Scholar 

  65. 65.

    van Walraven C, Jennings A, Taljaard M, Dhalla I, English S, Mulpuru S, 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.

    Google Scholar 

  66. 66.

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

    PubMed  Google Scholar 

  67. 67.

    Yam CH, Wong EL, Chan FW, Leung MC, Wong FY, Cheung AW, et al. Avoidable readmission in Hong Kong--system, clinician, patient or social factor? BMC Health Serv Res. 2010;10:311.

    PubMed  PubMed Central  Google Scholar 

  68. 68.

    Frankl SE, Breeling JL, Goldman L. Preventability of emergent hospital readmission. Am J Med. 1991;90(6):667–74.

    CAS  PubMed  Google Scholar 

  69. 69.

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

    Google Scholar 

  70. 70.

    Greenberg JK, Washington CW, Guniganti R, Dacey RG Jr, Derdeyn CP, Zipfel GJ. Causes of 30-day readmission after aneurysmal subarachnoid hemorrhage. J Neurosurg. 2016;124(3):743–9.

    PubMed  Google Scholar 

  71. 71.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  72. 72.

    Jonas JA, Devon EP, Ronan JC, Ng SC, Owusu-McKenzie JY, Strausbaugh JT, et al. Determining preventability of pediatric readmissions using fault tree analysis. J Hosp Med. 2016;11(5):329–35.

    PubMed  Google Scholar 

  73. 73.

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

    PubMed  PubMed Central  Google Scholar 

  74. 74.

    Oddone EZ, Weinberger M, Horner M, Mengel C, Goldstein F, Ginier P, 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):597–6057.

    CAS  PubMed  Google Scholar 

  75. 75.

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

    Google Scholar 

  76. 76.

    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.

    Google Scholar 

  77. 77.

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

    CAS  PubMed  Google Scholar 

  78. 78.

    Wasfy JH, Strom JB, Waldo SW, O'Brien C, Wimmer NJ, Zai AH, et al. Clinical preventability of 30-day readmission after percutaneous coronary intervention. J Am Heart Assoc. 2014;3(5):e001290.

    PubMed  PubMed Central  Google Scholar 

  79. 79.

    HainesWood J, Gilmore DH, Beringer TRO. Re-admission of elderly patients after in-patient rehabilitation. Ulster Med J. 1996;65(2):142–4.

    CAS  Google Scholar 

  80. 80.

    Meisenberg BR, Hahn E, Binner M, Weng D. Insights Into the Potential Preventability of Oncology Readmissions. J Oncol Pract. 2016;12(2):153.

    PubMed  Google Scholar 

  81. 81.

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

    PubMed  PubMed Central  Google Scholar 

  82. 82.

    Phelan D, Smyth L, Ryder M, Murphy N, O'Loughlin C, Conlon C, et al. Can we reduce preventable heart failure readmissions in patients enrolled in a disease management Programme? Irish J Med Sci. 2009;178(2):167–71.

    CAS  PubMed  Google Scholar 

  83. 83.

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

    PubMed  Google Scholar 

  84. 84.

    Tejedor-Sojo J, Singleton LM, McCormick K, Wrubel D, Chern JJ. Preventability of Pediatric 30-Day Readmissions following Ventricular Shunt Surgery. J Pediatr-Us. 2015;167(6):1327.

    Google Scholar 

  85. 85.

    Toomey SL, Peltz A, Loren S, Tracy M, Williams K, Pengeroth L, et al. Potentially Preventable 30-Day Hospital Readmissions at a Children’s Hospital. Pediatrics. 2016;138:2.

    Google Scholar 

  86. 86.

    Wallace SS, Keller SL, Falco CN, Nead JA, Minard CG, Nag PK, 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.

    PubMed  Google Scholar 

  87. 87.

    Goldfield N. Strategies to decrease the rate of preventable readmission to hospital. CMAJ. 2010;182(6):538–9.

    PubMed  PubMed Central  Google Scholar 

  88. 88.

    Shams I, Ajorlou S, Yang K. A predictive analytics approach to reducing 30-day avoidable readmissions among patients with heart failure, acute myocardial infarction, pneumonia, or COPD. Health care management science. 2015;18(1):19–34.

    PubMed  Google Scholar 

  89. 89.

    van Galen LS, Brabrand M, Cooksley T, van de Ven PM, Merten H, So RK, et al. Patients’ and providers’ perceptions of the preventability of hospital readmission: a prospective, observational study in four European countries. BMJ Qual Saf. 2017;26(12):958–69.

    PubMed  Google Scholar 

  90. 90.

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

    Google Scholar 

  91. 91.

    Zegers M, de Bruijne MC, Wagner C, Hoonhout LHF, Waaijman R, Smits M, Groenewegen PP. Adverse events and potentially preventable deaths in Dutch hospitals: results of a retrospective patient record review study. BMJ Quality & Safety. 2009;18(4):297–302.

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We would like to thank Eva-Linda Kneepkens for her contribution to the primary selection of the studies on which this review is based.


This study is funded by the Dutch Ministry of Health, Welfare and Sports. This study is part of the Dutch Adverse Event Study which is carried out by VU medical center and NIVEL (Netherlands institute for Health Services research). For this review we collaborated with one researcher (FK) of Onze Lieve Vrouwe Gasthuis (OLVG). The funding body had no role in the design of the study, or the collection, analysis, interpretation of data and in writing the manuscript.

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Two researchers (RS and CB) independently screened the set of articles included in the primary selection for eligibility for this review (according to the inclusion and exclusion criteria (see: Additional file 2A and 2B)). RS and CB contributed to the collection of the data. RS, MdB, CB, FK contributed to the analysis. RS, MdB, CB, FK and CW contributed to the interpretation of the data. RS, MdB, CB, FK and CW drafted the manuscript and approved the final version for publication.

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Correspondence to M. C. de Bruijne.

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The original version of this article was revised: “Several corrections are made in the article”.

Additional files

Additional file 1:

Pubmed search strategy. (DOCX 14 kb)

Additional file 2:

PRISMA flowchart reviews. (DOCX 66 kb)

Additional file 3:

Flowchart Inclusion and exclusion criteria. (DOCX 25 kb)

Additional file 4:

Excluded studies and reason for exclusion for review. (XLSX 23 kb)

Additional file 5:

Root cause and causes as reported in articles. (XLSX 29 kb)

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Singotani, R.G., Karapinar, F., Brouwers, C. et al. Towards a patient journey perspective on causes of unplanned readmissions using a classification framework: results of a systematic review with narrative synthesis. BMC Med Res Methodol 19, 189 (2019).

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  • Hospital readmission
  • Avoidability
  • Preventability