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Implementation of Pediatric Early Warning Score; Adherence to Guidelines and Influence of Context
Journal of Pediatric Nursing 38 (2018) 33–39
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Journal of Pediatric Nursing
Implementation of Pediatric Early Warning Score; Adherence to Guidelines and Influence of Context Ann-Charlotte Almblad ⁎, Petra Siltberg, Gunn Engvall, Mats Målqvist Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
a r t i c l e
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Article history: Received 30 January 2017 Revised 8 September 2017 Accepted 8 September 2017 Available online xxxx Keywords: Deterioration Implementation PARIHS Pediatric Pews
a b s t r a c t Purpose: To describe data of Pediatric Early Warning Score (PEWS) registrations and to evaluate the implementation of PEWS by examining adherence to clinical guidelines based on measured PEWS, and to relate findings to work context. Design and Methods: PEWS, as a part of a concept called Early Detection and Treatment-Children (EDT-C) was implemented at three wards at a Children's Hospital in Sweden. Data were collected from the Electronic Patient Record (EPR) retrospectively to assess adherence to guidelines. The Alberta Context Tool (ACT) was used to assess work context among healthcare professionals (n = 110) before implementation of EDT-C. Results: The majority of PEWS registrations in EPR were low whereas 10% were moderate to high. Adherences to ward-specific guidelines at admission and for saturation in respiratory distress were high whereas adherence to pain assessment was low. There were significant differences in documented recommended actions between wards. Some differences in leadership and evaluation between wards were identified. Conclusions: Evaluation of PEWS implementation indicated frequent use of the tool despite most scores being low. High scores (5–9) occurred 28 times, which may indicate that patients with a high risk of clinical deterioration were identified. Documentation of the consequent recommended actions was however incomplete and there was a large variation in adherence to guidelines. Contextual factors may have an impact on adherence. Practice Implications: EDT-C can lead to increased knowledge about early detection of deterioration, strengthen nurses as professionals, optimize treatment and teamwork and thereby increase patient safety for children treated in hospitals. © 2017 Elsevier Inc. All rights reserved.
Background Children are vulnerable regarding medical errors and the detection of clinical deterioration (Pruitt & Liebelt, 2010; Shaw et al., 2009; Shaw et al., 2013). A report showed that 4.4% of children from birth to 15 years, who are cared for in hospital settings in Sweden suffer from health-related injuries, i.e. avoidable injuries caused by treatment rather than an underlying disease (The National Board of Health and Wellfare, 2008). Shortcomings in clinical judgment and communication are common causes of unsafe conditions in pediatric care (Ruddy et al., 2015). Early recognition of severely ill children and the subsequent appropriate intervention are therefore necessary to prevent deterioration and cardiac arrest. Education and practical teamwork exercises, a structured approach and the use of assessment tools are described as ways to facilitate the care of acutely, severely ill children (Almblad, Malqvist, & Engvall, 2016).
⁎ Corresponding author at: Department of Women's and Children's Health, Uppsala University, Akademiska Sjukhuset, SE-751 85 Uppsala, Sweden. E-mail address: [email protected] (A.-C. Almblad).
https://doi.org/10.1016/j.pedn.2017.09.002 0882-5963/© 2017 Elsevier Inc. All rights reserved.
The Pediatric Early Warning Score (PEWS) is a scoring system developed for children and focuses on three components: behavior, color/cardiovascular status and respiratory status (Akre et al., 2010; Monaghan, 2005; Parshuram et al., 2011). A retrospective evaluation of estimated PEWS showed that for 85.5% of the patients, the earliest indicator on a critical PEWS was approximately 11.5 h before deterioration (Akre et al., 2010). A study at a pediatric hospital in Norway showed that a PEWS N3 was associated with severe illnesses and that these children were transferred to a higher level of care more often than children with PEWS 0–2 (Solevag, Eggen, Schroder, & Nakstad, 2013). Sefton, McGrath, Tume, Lane, Lisboa, and Carrol (2014) report that after implementation of PEWS the patients required less Pediatric Intensive Care Unit (PICU) interventions and had a shorter length of stay at the PICU. In addition, PICU service delivery improved. The Promoting Action on Research Implementation in Health Services (PARiHS) is a framework for the implementation of evidence to practice. It is built around three components: Evidence, Context and Facilitation. Evidence encompasses research evidence, clinical experience and local information. Implementation of such evidence is a dialectical process and a team effort. Successful implementation requires contexts that have transformational leaders, evaluative and feedback
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mechanisms and appropriate facilitators who work with individuals and teams to enhance the process (Kitson et al., 2008). PARiHS can identify barriers to research utilization in practice and by processing these barriers increase the susceptibility of an intervention (Obrecht, Van Hulle Vincent, & Ryan, 2014). The Early Detection and Treatment Program for Children (EDT-C) was developed at Uppsala University Hospital and consists of the Pediatric Early Warning Score (PEWS), Airway, Breathing, Circulation, Disability, Exposure (ABCDE), Crew Resource Management (CRM), Situation, Background, Assessment, Recommendation (SBAR), and recommended action according to EDT-Ladder for Children. ABCDE is a structured tool to examine, treat and evaluate the patient's vital functions on the basis of a pre-determined order (Jafarpour, Nassiri, Bidari, Chardoli, & Rahimi-Movaghar, 2015). CRM is a model for teamwork focusing on communication, situation awareness, leadership and resource management (Flin & Maran, 2004; Jafarpour et al., 2015). SBAR is a standardized tool for clear and concise communication (Sweeney, Warren, Gardner, Rojek, & Lindquist, 2014). It has been shown that structured communication can improve teamwork, increase patient safety and reduce unexpected deaths (Barata, Benjamin, Mace, Herman, & Goldman, 2007; Woodhall, Vertacnik, & McLaughlin, 2008) (Panel 1). The Implementation Process In March 2013, EDT-C was implemented, at The University Children's Hospital, Uppsala in accordance with the PARiHS framework. Three inpatient wards participated: the Emergency Care ward with general pediatrics and emergency care with 9 beds, the Elective Care ward with mainly planned care for neurology and surgery with 22 beds, and finally the Oncology ward with 12 beds mainly for planned care for children with blood and tumor diseases. Emergency conditions occur in all units, such as bleeding and infection after surgery, seizures, meningitis and serious brain conditions, life-threatening sepsis and serious
respiratory problems. The implementation process with the preparation phase, implementation phase and evaluation phase is briefly described in Flow Chart 1. Preparation Phase The Brighton Pediatric Early Warning Score scoring system was chosen, on the basis that it is a validated instrument (Akre et al., 2010; Monaghan, 2005). Two translators, one with Swedish and one with English as their mother tongue, translated the PEWS instrument, first from English into Swedish and then back to English. A minor adjustment of the instrument was made regarding oxygen treatment and persistent postoperative vomiting, which was regulated in a separate document. A cross-sectional pilot study was conducted to investigate the interrater reliability for the Swedish version of the PEWS. The PEWS scores were assessed 56 times by two independent observers at an oncologic ward at a University Hospital. Inter-rater reliability for the total PEWS was good to excellent: Cohen's kappa was 0.80 and ICC was 0.96 (Nilsson & Zittra, 2014). The PEWS is a structured instrument to assess patients' health (range from 0 to 9): behavior (0–3) color/cardiovascular status (0–3) and respiratory status (0–3) (Akre et al., 2010). Cross-professional reference groups, consisting of physicians, assistant nurses and nurses, were established on each ward to determine the adapted guidelines These guidelines (Panel 2) determine which patients should be assessed according to PEWS based on the ward's specific needs. The recommendations for actions to be performed on the basis of measured PEWS and/ or concern for the patient's health are described in the EDT-Ladder for Children (Panel 1). Training materials for EDT-C were developed in collaboration with nurses and physicians from the hospital's Clinical Training Center and from various pediatric care wards. The working group underwent EDT-C head instructor training.
Flow Chart 1. The implementation process.
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An eight-hour training program for EDT-C-instructors was conducted, in which a total of 12 instructors (9 nurses and 3 physicians) were trained. The instructors then trained staff on the ward to which they belonged. Cross-professional, mandatory three-hour training sessions was conducted for all employees at the three wards where EDT-C was to be introduced. Context was measured by using the Alberta Context Tool (Estabrooks, Squires, Cummings, Birdsell, & Norton, 2009).
documented for some of the stages it was coded as “partly performed” (Partial adherence to EDT-Ladder for Children). If no measures were documented it was coded as “lack of information” (No adherence to EDT-Ladder for Children). When the PEWS was one (1) for “sleeping” under the category of behavioral/alertness, and it was the only parameter that scored points, it was considered that no action was needed and interpreted as a normal sleeping condition. Statistical comparisons were performed between the wards regarding the presence of documentation of actions performed according to EDT-Ladder for Children.
Evaluation Phase
Data Collection and Sample From the Work Context
Recurring meetings for instructors were provided approximately three times during the first year. These meetings included discussion and feedback about the teaching and implementation of EDT-C on each ward. The instructors' function was, in addition to training staff, to facilitate during the implementation phase on their respective wards to inform, support and to capture the staff's views. The present study is part of a larger project focusing on increased patient safety by the implementation of the concept called Early Detection and Treatment-Children (EDT-C). The aim of the present study was to describe data of PEWS registrations and to evaluate the implementation of PEWS by examining adherence to clinical guidelines based on measured PEWS, and to relate findings to work context.
The Alberta Context Tool (ACT) was developed to describe the conditions in the work environment in health care. It assesses several core domains to provide a comprehensive account of organizational context in health care, and has been validated in settings similar to the current study setting (Squires et al., 2013; Squires et al., 2015). The ACT reflects the following contextual dimensions: leadership, culture, evaluation, social capital, formal and informal interactions, structural and electronic resources and organizational resources of staffing, time and space. The items describing each dimension are presented as statements and measured on a scale from 1 to 5, where five indicates most consistent with the statement. It also adds information about the respondent's working hours, experience, education and age. All who participated in the EDT-C training received an ACT questionnaire. Data were obtained from nurses and nurse assistants. The ACT questionnaires were distributed at training sessions for EDT-C or sent to the respondent's personal postbox, with return envelopes to the first author, after the training session. The questionnaires were marked with a section number but not linked to any person.
Implementation Phase
Method Two study methods were used: a retrospective review of the Electronic Patient Records to assess adherence to guidelines and a context assessment of the work environment on the different wards, using the Alberta Context Tool (ACT). Data Collection and Sample From Electronic Patient Records Data were gathered through the Electronic Patient Record (EPR). Variables collected were: time for PEWS measurement, PEWS, social security number of inpatients, age, gender and healthcare contact number. The concept of healthcare contact number is a specific contact identification for each contact admission to a ward, where each individual may have one or several contact numbers. In addition, the total number of admissions was retrieved. All inpatients were included from the 4th of March 2013 for the Elective Care ward and the 18th of March 2013 for the Oncology ward and the Emergency Care ward up until the 31st of December 2013 where EDT-C had been implemented. Data were retrieved from the EPR by staff at the EPR department. To be able to achieve a structured review of the data from the EPR, a random sample was drawn with the help of the Internet-based tool, Research Randomizer, which is based on the social security number. Patients 19 years and older were excluded. Based on this randomization process 20% of admitted patients at the Oncology and Elective Care and 10% from the Emergency Care wards were included to obtain a suitable sample. Data were collected from the EPR and in addition from the scanned part of the EPR. Day monitoring lists with the PEWS written on paper were scanned and kept in the scanned part of the EPR. Each registered PEWS was studied to ascertain whether blood pressure, saturation and pain assessment had been conducted according to specified guidelines (Panel 2) and documented in the EPR or scanned part of the EPR at the specified time and this was determined as performed when documentation was found. In cases of no documentation of any actions it was determined as “not performed”. Furthermore, the documentation in the EPR or scanned part of the EPR for each PEWS was studied to evaluate if any actions according to the EDT-Ladder for Children (Panel 1) had been performed. When all the measures were documented, it was coded as “performed” (Full adherence to EDT-Ladder for Children). When measures were only
Analysis Data obtained from Electronic Patient Records were processed in Microsoft Excel and the statistics management software IBM SPSS Statistics 22, IBM, New York, US. Data from the questionnaire ACT were processed in IBM SPSS Statistics 20 (IBM, New York, US) according to the Alberta Context Tool User Manual (Squires et al., 2014). Student's t-test was used to analyze dimensions from ACT. Chi-square was used to analyze differences between groups. A p-value b 0.05 was considered significant. Ethical Considerations The EPR system is governed by the Personal Data Acts: SFS 1998:204 and 2008:355 (Ministry of Justice, 1998; Ministry of Social Affairs, 2008). All who received the ACT questionnaire signed a written informed consent form, on which it was stated that participation was voluntary and that the results could not be linked to any person. The study was approved by the Regional Ethical Review Board, Uppsala, Sweden. Result Results consist of: 1) descriptive data from the total PEWS registrations, 2) descriptive data about adherence to each ward's specific guidelines for PEWS and 3) descriptive and comparative data about contextual influences between the three wards based on staff responses to the Alberta Context Tool (ACT). PEWS Measurement, Distribution of Scores In total, 4865 PEWS were recorded, divided into 875 unique social security numbers (individuals) during the study period for children from birth to 19 years old. There was at least one PEWS score recorded for 1160 of these admissions.
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PEWS 0, the patient being unaffected and in a normal state, was measured on 2265 (46.7%) occasions and there were 8 PEWS 7–9 registered (b 0.01%). The majority of PEWS were however, between 0 and 2, PEWS 3–9 were registered on 505 (10.4%) occasions.
Table 2 Adherence to ward-specific guidelines according to the documentation.
When to perform PEWS All admissions to the ward Back to ward after intensive care Acute admissions to the ward Postoperative for certain diagnosis Postoperative Ongoing infection Measuring pain After anesthesia Saturation in respiratory distress At deterioration According to medical prescription Action after PEWS Blood pressure at PEWS N3
PEWS Measurement and Distribution in Age Groups in the Randomized Sample The randomized sample consisted of 20% of all admissions for Oncology and Elective Care, and 10% of all admissions for Emergency Care of the patients aged from birth to 19 years with at least one registered PEWS score. This corresponds to 166 patients (Oncology: 40, Elective Care: 55 and Emergency Care: 71) with a total of 981 PEWS (Oncology: 279, Elective Care: 227 and Emergency Care: 475). PEWS 0 and PEWS 1–2 were measured on 444 (45.3%) and 401(40.9%) occasions respectively. PEWS 3–4 were measured on 108 (11%) occasions and 28 (2.9%) scored PEWS 5–9, of which 12 were for children less than one year old. In the age group 16–17 years, 63 PEWS were measured and 3 of them were PEWS 5–9. In the age group 7–15 years, no PEWS 5–9 were measured (Table 1). Adherence to Ward-specific Guidelines for PEWS Adherence to the specific guidelines (Panel 2) for PEWS is presented in Table 2. Adherence was 65% and 88% for performing PEWS at all admissions at Oncology and Emergency Care respectively, and 67% at acute admissions at Elective Care. Adherence was between 83 and 92% for measurement of oxygen saturation when respiratory distress was noted. Measuring PEWS according to medical prescription was 79% for Oncology, 56% for Elective Care, and 87% for Emergency Care. Adherence to blood pressure measurement at scores ≥ 3 was 51% for Oncology, whereas it was 8% for Elective Care and 13% for Emergency Care. Instructions to measure pain revealed adherence of 7–13% on the three wards.
Oncology
Elective
Emergency
n
%
n
%
n
%
41 1
65 25 –
–
–
51
88
67 60 81 – 7
–
–
4 36
33 – 13
68
– 62 10 50 84 – 79
6 3 29 – 16 19 5 44
83 45 56
69 0 202
92 0 87
19
51
2
8
6
13
– 89 27 13 57
Work Context The ACT survey was distributed to nurses and assistant nurses currently working in the three wards. In Oncology, 23 completed surveys of 31 distributed (74%), with Elective Care, 46 of 59 distributed (78%), and with Emergency Care, 40 of 48 distributed (83%) were collected. There were no differences in culture, internal processes, relationships, staffing and time between the three wards. For leadership there was a difference between Elective Care and Emergency Care revealing higher levels of satisfaction in Elective Care. There was also a difference in the evaluation dimension between Elective Care and Emergency Care, where the staff reported that evaluation and feedback occurred to a greater extent in Elective Care compared to Emergency Care. No differences between men and women or between nurses and assistant nurses could be found (Table 4).
Adherence to Early Detection and Treatment Ladder for Children
Discussion
There were 536 registered measurements of PEWS 1 or higher (Oncology: 137; Elective Care: 113 and Emergency Care: 286) which were compared to the recommended actions according to the EDT-Ladder for Children (Panel 1). According to the documentation in the EPR, there was full adherence to the EDT-Ladder for Children in 23.4%, partial in 32.1% and no adherence in 44.5% of cases in Oncology; full adherence in 39.8%, partial in 30% and no adherence in 30% of cases in Elective Care; full adherence in 36.7%, partial in 6.9% and no adherence in 56.2% of cases in Emergency Care (Table 3). When comparing groups (Chi-square test) there was greater adherence to full adherence in Elective Care compared to partial/no adherence to recommended actions in Oncology (p b 0.01) and greater adherence in Emergency Care compared to Oncology (p b 0.01). However, there was no difference between Elective Care and Emergency Care (p = 0.6). When comparing full/partial adherence to no adherence there was a greater adherence to EDT-Ladder for Children in Elective Care vs Oncology (p = 0.035), and in Elective Care vs. Emergency Care (p ≤0.01) and also in Oncology vs Emergency Care (p = 0.01).
In the randomized sample most of the measured PEWS were 0–2 and only a few scored PEWS 5–9. This reveals that the majority of hospitalized patients in the present study were stable in behavior, cardiovascular status and respiratory status according to PEWS. Solevag et al. (2013) showed that PEWS N 3 occurred in 16% of patients and were most common in younger children (b 2 years). The purpose of PEWS is to detect patients at risk of deterioration and thereby optimize treatment to avoid further deterioration and death (Monaghan, 2005). A measured PEWS N2 may indicate temporary or severe persistent deterioration. Consequently, the recommended monitoring and treatment remains important at this level. PEWS 5–9 occurred 28 times in this study, which may indicate that patients with a very high risk of clinical deterioration were identified on the ward. In modern health care medical monitoring equipment plays a significant role, despite the fact that it cannot fully replace the professional judgment of healthcare professionals. According to Lambert, Matthews, MacDonell, and Fitzsimons (2017), real-life cases and using a cross-professional approach to PEWS education can stimulate a heightened sense of situation
Table 1 Distribution of total PEWS according to age groups in the randomized sample (n = 981). PEWS
0 1–2 3–4 5–6 7–9
0 yr
1–2 yrs
3–6 yrs
7–9 yrs
10–12 yrs
13–15 yrs
16–17 yrs
18 yrs
n
%
n
%
n
%
n
%
n
%
n
%
n
%
n
%
113 113 27 9 3
11.5 11.5 2.8 0.9 0.3
76 98 31 5 3
7,7 9.9 3.2 0.5 0.3
81 85 29 5 0
8.2 8.6 3.0 0.5 0
67 45 12 0 0
6.8 4.5 1.2 0 0
20 9 0 0 0
2.0 0.9 0 0 0
54 20 2 0 0
5.5 2.0 0.2 0 0
27 26 7 2 1
2.7 2.6 0.7 0.2 0.1
6 5 0 0 0
0.6 0.5 0 0 0
A.-C. Almblad et al. / Journal of Pediatric Nursing 38 (2018) 33–39 Table 3 Documentation of adherence to measures (n = 536) according to EDT-Ladder for Children per ward: Oncology ward (n = 137), Elective Care ward (n = 113) and Emergency Care ward (n = 286). Oncology
Full adherence Partial adherence No adherence
Elective
Emergency
n
%
n
%
n
%
32 44 61
23.4 32.1 44.5
45 34 34
39.8 30 30
105 20 161
36.7 6.9 56.2
awareness and open communication among clinicians about children at risk of clinical deterioration. Adherence to ward-specific guidelines according to the data from EPR varied in the three wards. Measuring oxygen saturation during respiratory distress had high adherence in all three wards as well as medical prescription and admissions to the wards, while adherence to pain measurement was low in all wards. Adherence to blood pressure at PEWS N3 was high at Oncology but low at Elective Care and Emergency Care. This may indicate that blood pressure was an important parameter in the type of care that was conducted at Oncology (Jeddi et al., 2010) while it did not have the same importance in the care in Elective Care and Emergency Care. The adapted guidelines were established before the introduction of EDT-C and an evaluation may be necessary to assess their relevance for the care provided on the wards. For those that are considered relevant there should be a discussion on how compliance can increase. Tsao & Browne (2015) describe the importance of developing a culture focused on safety as such a priority is needed for the sustainable reduction of harm, and improvement in the reliability of care. In a Swedish study it was shown that certain factors, such as feedback processes, structural resources and information sharing in the
Table 4 Mean scores of Alberta Context Tool dimensions, per ward. Dimensions of ACT Leadership
Culture
Evaluation
Formal interactions
Informal interactions
Social capital
Structural and electronic resources Organizational slack - staff
Organizational slack - space
Organizational slack - time
Student's t-test. ⁎ p b 0.05. ⁎⁎ p b 0.01.
Oncology Elective Emergency p n = 23 n = 46 n = 40 Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev
4.12 0.55
4.34 0.53
3.80 0.68
4.09 0.43
4.19 1.31
4.06 0.43
3.29 0.46
3.46 0.49
3.24 0.52
0.75 0.46
0.93 0.54
0.71 0.60
3.47 1.59
3.77 1.70
3.37 1.83
4.17 0.41
4.13 0.50
4.24 0.47
3.85 1.41
3.43 1.64
4.11 1.59
2.98 0.92
2.84 0.96
2.78 0.85
3.59 0.66
2.07 0.88
2.26 0.98
2.79 0.51
2.63 0.59
2.69 0.51
⁎⁎
⁎
⁎⁎
37
work context affected adherence to clinical practice guidelines among registered nurses in pediatric care (Forberg et al., 2014). The analysis of ACT in this study showed that the highest score for the dimension leadership and evaluation occurred in Elective Care. Adherence to the EDT-Ladder for Children was, according to documented percentage, also highest in Elective Care. These two results may indicate that work context may influence adherence to guidelines. Furthermore, the structure on a ward with elective care, where the diagnosis is known and the care planned, may also influence guidelines and documentation. Implementation can be seen as a process to increase knowledge with the aim of achieving change. Complex interventions like EDT-C involve individual, group and organizational levels. It is necessary to find out what is implemented and how a process evaluation can be investigated by: fidelity, if the intervention was delivered as intended; dose, the quantity of intervention implemented; and reach, how and if the intended audience comes in contact with the intervention (Kitson et al., 2008). Even if the implementation process does not vary, the intervention may have different effects in different contexts (Moore et al., 2015; Shiell, Hawe, & Gold, 2008). For example, the documentation and monitoring of the patient may be affected in a ward where there is high patient turnover, such as in an Emergency Care. Patients may also to a greater extent have electronic monitoring equipment and caregivers may therefore perceive that they have control over the condition of the patient. There are also several other factors that may have an impact on adherence to guidelines, such as how engaged and dedicated the facilitators are and how they perceive their role (Waterman et al., 2015). The importance of proper documentation could also have been better clarified and emphasized in the training prior to the implementation process. Scott, Grimshaw, Klassen, Nettel-Aguirre, and Johnson (2011) have designed a protocol which can be used in future studies in order to study the causal mechanism and factors that shape the implementation process of guidelines and how to reduce clinical practice variations. Implementation aims, as have been previously highlighted, to raise awareness and create change. PEWS should be embraced as a part of a larger multifaceted safety framework which can lead to increased knowledge about early detection of deterioration, optimize treatment and teamwork. This can develop over time with strong leadership, targeted training, ongoing support and continuous improvement (Lambert et al., 2017). An expanded toolbox, like PEWS, can enhance the ability to make an objective assessment of the patient's condition and strengthen the nursing profession. Methodological Considerations Implementation of evidence-based care is complicated, and good conditions for applying evidence in clinical work must be created even if, as in this process, the healthcare organization is large and complex. To study the outcome of the implementation process and to be able to handle a large amount of data, a retrospective medical review was chosen. Individual cases could also be interesting to study, but they would only be able to show data from a small group of patients. Akenroye and Stack (2015) found that the keys to success were strong leadership, support and local presence of guidelines, selection of motivated facilitators, development of practical processes for guidelines and implementation, and frequent feedback to stakeholders. This implementation of EDT-C included several of these factors on three different wards and included all categories of health professionals. An implementation process based on multidisciplinary involvement can increase the understanding of each other's levels of knowledge. According to Murray, Williams, Pignataro, and Volpe (2015) education in the clinical setting regarding early warning system scores should emphasize that these tools aid all levels of expertise and should be introduced in an inter-professional forum to engage all users. Also Kitson et al. (2008) state that implementation requires effective dialogue and teamwork with great understanding of the different professions' skills. PEWS
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can help healthcare professionals with varying degrees of education and experience to assess the patient's condition so that the patient receives optimal care. With the implementation of an early warning score system it is important to select a tool for children that is validated, reliable and best meets the needs of the patient (Chapman, Grocott, & Franck, 2010).
Strengths The present study has contributed to increase knowledge about implementation processes in complex healthcare environments. EDT-C is a new concept which comprises conventional components for healthcare professionals using a structured process to assess, treat and communicate. This can lead to increased knowledge about early detection of deterioration, strengthen nurses as professionals, optimize work treatment and teamwork and thereby increase patient safety for children at Swedish hospitals. The PARiHS framework was used as a model for the implementation, and a validated instrument, PEWS, was chosen (Kitson et al., 2008). Furthermore, an investigation of inter-rater reliability of the Swedish version of the PEWS instrument was performed (Akre et al., 2010; Nilsson & Zittra, 2014). To adapt the use of PEWS optimally in the different wards, ward-specific guidelines based on the specific health needs were formulated, and interdisciplinary teams together with EDT-C instructors were assigned to facilitate the implementation. ACT was used to examine the work context which is a validated instrument used both international and nationally in different healthcare settings (Eldh, Ehrenberg, Squires, Estabrooks, & Wallin, 2013; Squires et al., 2015). The ACT manual was used for distribution and analysis (Squires et al., 2014).
Limitations Some weaknesses in the study need to be mentioned. This study is based on material from output data and the documentation that has been available in the EPR. This does not give any indication of measurements and assessments that may have been carried out without being documented. It is even more difficult to estimate how well the documentation of actions according to the EDT-Ladder for Children was carried out. An observation study may provide answers to what is conducted and thereafter documented. In emergency situations documentation is very important but can sometimes have a lower priority due to stress with the focus of the team being to assess and treat the patient optimally (Ali, Thomson, Graham, Rickard, & Stang, 2017). Lack of time and staff resources can also be a contributing factor to inadequate documentation. The organization and management of data may have caused errors since documentation has been carried out in different systems in the EPR. However, additional examination of the records in the EPR and the scanned part of EPR reduced the risk of missing data in the randomized sample. The study is based on material from approximately the ten first months after the implementation of the EDT-C. Since this was a relatively short time for such a comprehensive implementation process, it would be interesting to repeat the study at a later stage to see how adherence to guidelines and estimated PEWS has developed. McLellan, Gauvreau and Connor (2017) showed in a study of the Children's Hospital Early Warning Score (CHEWS), that CHEWS had a higher sensitivity but a longer early warning time than PEWS, so ongoing development work is necessary to refine the instrument. To enhance the understanding of the complex process of implementation, further studies are needed in which healthcare professionals' experiences of implementation are captured.
Conclusion Evaluation of the implementation of PEWS at a pediatric hospital in Sweden indicated frequent use of the tool despite the fact that most scores were low, signifying that the majority of hospitalized patients are stable in behavior, cardiovascular status and respiratory status according to PEWS. Estimated PEWS 5–9 occurred 28 times in this study, which may indicate that patients with a very high risk of deterioration are identified at the ward. Documentation of assessments of the patient and the subsequent recommended actions was however incomplete and there was significant variation in adherence to guidelines. Contextual factors such as leadership and evaluation may have impact on adherence to guidelines. Targeted training and ongoing support by facilitators in a continuous improvement effort supported by strong leadership is warranted. EDT-C can lead to increased knowledge about early detection of deterioration, strengthen nurses as professionals, optimize treatment and teamwork and thereby increase patient safety for children treated in hospitals. Acknowledgments This research was supported by Her Royal Highness Crown Princess Lovisa's Society for Children's Health Care, Sweden. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.pedn.2017.09.002. References Akenroye, A. T., & Stack, A. M. (2015). The development and evaluation of an evidencebased guideline programme to improve care in a paediatric emergency department. Emergency Medicine Journal. https://doi.org/10.1136/emermed-2014-204363. Akre, M., Finkelstein, M., Erickson, M., Liu, M., Vanderbilt, L., & Billman, G. (2010). Sensitivity of the pediatric early warning score to identify patient deterioration. Pediatrics, 125(4), e763–769. https://doi.org/10.1542/peds.2009-0338. Ali, S., Thomson, D., Graham, T. A., Rickard, S. E., & Stang, A. S. (2017). High stakes and high emotions: Providing safe care in Canadian emergency departments. Open Access Emergency Medicine, 9, 23–26. https://doi.org/10.2147/oaem.s122646. Almblad, A. C., Malqvist, M., & Engvall, G. (2016). Caring for the acutely, severely ill childA multifaceted situation with paradoxical elements: Swedish healthcare professionals' experiences. Journal of Pediatric Nursing, 31(5), e293–e300. https://doi.org/ 10.1016/j.pedn.2016.05.001. Barata, I. A., Benjamin, L. S., Mace, S. E., Herman, M. I., & Goldman, R. D. (2007). Pediatric patient safety in the prehospital/emergency department setting. Pediatric Emergency Care, 23(6), 412–418. https://doi.org/10.1097/01.pec.0000278393. 32752.9f. Chapman, S. M., Grocott, M. P., & Franck, L. S. (2010). Systematic review of paediatric alert criteria for identifying hospitalised children at risk of critical deterioration. Intensive Care Medicine, 36(4), 600–611. https://doi.org/10.1007/s00134-009-1715-x. Eldh, A. C., Ehrenberg, A., Squires, J. E., Estabrooks, C. A., & Wallin, L. (2013). Translating and testing the Alberta context tool for use among nurses in Swedish elder care. BMC Health Services Research, 13, 68. https://doi.org/10.1186/1472-6963-13-68. Estabrooks, C. A., Squires, J. E., Cummings, G. G., Birdsell, J. M., & Norton, P. G. (2009). Development and assessment of the Alberta Context Tool. BMC Health Services Research, 9, 234. https://doi.org/10.1186/1472-6963-9-234. Flin, R., & Maran, N. (2004). Identifying and training non-technical skills for teams in acute medicine. Quality & Safety in Health Care, 13(Suppl. 1), i80–84. https://doi. org/10.1136/qhc.13.suppl_1.i80. Forberg, U., Wallin, L., Johansson, E., Ygge, B. M., Backheden, M., & Ehrenberg, A. (2014). Relationship between work context and adherence to a clinical practice guideline for peripheral venous catheters among registered nurses in pediatric care. Worldviews on Evidence-Based Nursing, 11(4), 227–239. https://doi.org/10.1111/ wvn.12046. Jafarpour, S., Nassiri, S. J., Bidari, A., Chardoli, M., & Rahimi-Movaghar, V. (2015). Principles of primary survey and resuscitation in cases of pediatric trauma. Acta Medica Iranica, 53(4), 242–245. Jeddi, R., Achour, M., Amor, R. B., Aissaoui, L., Bouteraa, W., Kacem, K., ... Meddeb, B. (2010). Factors associated with severe sepsis: Prospective study of 94 neutropenic febrile episodes. Hematology, 15(1), 28–32. https://doi.org/10.1179/ 102453310x12583347009577. Kitson, A. L., Rycroft-Malone, J., Harvey, G., McCormack, B., Seers, K., & Titchen, A. (2008). Evaluating the successful implementation of evidence into practice using the PARiHS framework: Theoretical and practical challenges. Implementation Science, 3, 1–12. https://doi.org/10.1186/1748-5908-3-1.
A.-C. Almblad et al. / Journal of Pediatric Nursing 38 (2018) 33–39 Lambert, V., Matthews, A., MacDonell, R., & Fitzsimons, J. (2017). Paediatric early warning systems for detecting and responding to clinical deterioration in children: A systematic review. BMJ Open, 7(3), e014497. https://doi.org/10.1136/bmjopen-2016-014497. McLellan, M. C., Gauvreau, K., & Connor, J. A. (2017). Validation of the Children's Hospital Early Warning System for Critical Deterioration Recognition. Journal of Pediatric Nursing, 32, 52–58. https://doi.org/10.1016/j.pedn.2016.10.005. Ministry of Justice (1998). Svensk författningssamling SFS personuppgiftslagen: 1998:204. (In Swedish). Ministry of Social Affairs (2008). Svensk författningssamling SFS 2008:355 Patientdatalagen. Monaghan, A. (2005). Detecting and managing deterioration in children. Paediatric Nursing, 17(1), 32–35. https://doi.org/10.7748/paed2005.02.17.1.32.c964. Moore, G. F., Audrey, S., Barker, M., Bond, L., Bonell, C., Hardeman, W., ... Baird, J. (2015). Process evaluation of complex interventions: Medical Research Council guidance. BMJ, 350, h1258. https://doi.org/10.1136/bmj.h1258. Murray, J. S., Williams, L. A., Pignataro, S., & Volpe, D. (2015). An Integrative Review of Pediatric Early Warning System Scores. Pediatric Nursing, 41(4), 165–174. Nilsson, E., & Zittra, T. (2014). Bedömning av vitalparametrar hos barn med cancer. Tillförlitlighet av bedömningsinstrumentet Pediatric Early Warning Score (in Swedish). Master Theses Umeå University. Obrecht, J. A., Van Hulle Vincent, C., & Ryan, C. S. (2014). Implementation of evidencebased practice for a pediatric pain assessment instrument. Clinical Nurse Specialist, 28(2), 97–104. https://doi.org/10.1097/nur.0000000000000032. Parshuram, C. S., Duncan, H. P., Joffe, A. R., Farrell, C. A., Lacroix, J. R., Middaugh, K. L., ... Parkin, P. C. (2011). Multicentre validation of the bedside paediatric early warning system score: A severity of illness score to detect evolving critical illness in hospitalised children. Critical Care, 15(4), R184. https://doi.org/10.1186/cc10337. Pruitt, C. M., & Liebelt, E. L. (2010). Enhancing patient safety in the pediatric emergency department: Teams, communication, and lessons from crew resource management. Pediatric Emergency Care, 26(12), 942–948 quiz 949–951 https://doi.org/10.1097/ PEC.0b013e3181fec9cf. Ruddy, R. M., Chamberlain, J. M., Mahajan, P. V., Funai, T., O'Connell, K. J., Blumberg, S., ... Shaw, K. N. (2015). Near misses and unsafe conditions reported in a Pediatric Emergency Research Network. BMJ Open, 5(9), e007541. https://doi.org/10.1136/ bmjopen-2014-007541. Scott, S. D., Grimshaw, J., Klassen, T. P., Nettel-Aguirre, A., & Johnson, D. W. (2011). Understanding implementation processes of clinical pathways and clinical practice guidelines in pediatric contexts: a study protocol. Implementation Science, 6, 133. https:// doi.org/10.1186/1748-5908-6-133. Sefton, G., McGrath, C., Tume, L., Lane, S., Lisboa, P. J., & Carrol, E. D. (2014). What impact did a Paediatric Early Warning system have on emergency admissions to the paediatric intensive care unit? An observational cohort study. Intensive & Critical Care Nursing. https://doi.org/10.1016/j.iccn.2014.01.001.
39
Shaw, K. N., Lillis, K. A., Ruddy, R. M., Mahajan, P. V., Lichenstein, R., Olsen, C. S., & Chamberlain, J. M. (2013). Reported medication events in a paediatric emergency research network: Sharing to improve patient safety. Emergency Medicine Journal, 30(10), 815–819. https://doi.org/10.1136/emermed-2012-201642. Shaw, K. N., Ruddy, R. M., Olsen, C. S., Lillis, K. A., Mahajan, P. V., Dean, J. M., & Chamberlain, J. M. (2009). Pediatric patient safety in emergency departments: Unit characteristics and staff perceptions. Pediatrics, 124(2), 485–493. https://doi.org/10. 1542/peds.2008-2858. Shiell, A., Hawe, P., & Gold, L. (2008). Complex interventions or complex systems? Implications for health economic evaluation. BMJ, 336(7656), 1281–1283. https://doi.org/ 10.1136/bmj.39569.510521.AD. Solevag, A. L., Eggen, E. H., Schroder, J., & Nakstad, B. (2013). Use of a modified pediatric early warning score in a department of pediatric and adolescent medicine. PloS One, 8(8), e72534. https://doi.org/10.1371/journal.pone.0072534. Squires, J. E., Estabrooks, C. A., Scott, S. D., Cummings, G. G., Hayduk, L., Kang, S. H., & Stevens, B. (2013). The influence of organizational context on the use of research by nurses in Canadian pediatric hospitals. BMC Health Services Research, 13, 351. https://doi.org/10.1186/1472-6963-13-351. Squires, J. E., Hayduk, L., Hutchinson, A. M., Mallick, R., Norton, P. G., Cummings, G. G., & Estabrooks, C. A. (2015). Reliability and validity of the Alberta Context Tool (ACT) with professional nurses: Findings from a multi-study analysis. PloS One, 10(6), e0127405. https://doi.org/10.1371/journal.pone.0127405. Squires, J. E., Hutchinson, A., Hayduk, L., Cranley, L., Cummings, G., Norton, P., & Estabrooks, C. (2014). Alberta context tool, user manual. Retrieved from http:// www.kusp.ualberta.ca/en/ACT/~/media/Knowledge%20Utilization%20Studies% 20Program/Documents/ACT/ACTManual2014.pdf. Sweeney, L. A., Warren, O., Gardner, L., Rojek, A., & Lindquist, D. G. (2014). A simulationbased training program improves emergency department staff communication. American Journal of Medical Quality, 29(2), 115–123. https://doi.org/10.1177/ 1062860613491308. The National Board of Health and Wellfare (2008). Vårdskador inom somatisk slutenvård. (Medical injuries in somatic inpatient) [in Swedish]. Retrieved from http://www. socialstyrelsen.se/publikationer2008/2008-109-16. Tsao, K., & Browne, M. (2015). Culture of safety: A foundation for patient care. Seminars in Pediatric Surgery, 24(6), 283–287. https://doi.org/10.1053/j.sempedsurg.2015.08.005. Waterman, H., Boaden, R., Burey, L., Howells, B., Harvey, G., Humphreys, J., ... Spence, M. (2015). Facilitating large-scale implementation of evidence based health care: Insider accounts from a co-operative inquiry. BMC Health Services Research, 15, 60. https:// doi.org/10.1186/s12913-015-0722-6. Woodhall, L. J., Vertacnik, L., & McLaughlin, M. (2008). Implementation of the SBAR communication technique in a tertiary center. Journal of Emergency Nursing, 34(4), 314–317. https://doi.org/10.1016/j.jen.2007.07.007.
Contents lists available at ScienceDirect
Journal of Pediatric Nursing
Implementation of Pediatric Early Warning Score; Adherence to Guidelines and Influence of Context Ann-Charlotte Almblad ⁎, Petra Siltberg, Gunn Engvall, Mats Målqvist Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
a r t i c l e
i n f o
Article history: Received 30 January 2017 Revised 8 September 2017 Accepted 8 September 2017 Available online xxxx Keywords: Deterioration Implementation PARIHS Pediatric Pews
a b s t r a c t Purpose: To describe data of Pediatric Early Warning Score (PEWS) registrations and to evaluate the implementation of PEWS by examining adherence to clinical guidelines based on measured PEWS, and to relate findings to work context. Design and Methods: PEWS, as a part of a concept called Early Detection and Treatment-Children (EDT-C) was implemented at three wards at a Children's Hospital in Sweden. Data were collected from the Electronic Patient Record (EPR) retrospectively to assess adherence to guidelines. The Alberta Context Tool (ACT) was used to assess work context among healthcare professionals (n = 110) before implementation of EDT-C. Results: The majority of PEWS registrations in EPR were low whereas 10% were moderate to high. Adherences to ward-specific guidelines at admission and for saturation in respiratory distress were high whereas adherence to pain assessment was low. There were significant differences in documented recommended actions between wards. Some differences in leadership and evaluation between wards were identified. Conclusions: Evaluation of PEWS implementation indicated frequent use of the tool despite most scores being low. High scores (5–9) occurred 28 times, which may indicate that patients with a high risk of clinical deterioration were identified. Documentation of the consequent recommended actions was however incomplete and there was a large variation in adherence to guidelines. Contextual factors may have an impact on adherence. Practice Implications: EDT-C can lead to increased knowledge about early detection of deterioration, strengthen nurses as professionals, optimize treatment and teamwork and thereby increase patient safety for children treated in hospitals. © 2017 Elsevier Inc. All rights reserved.
Background Children are vulnerable regarding medical errors and the detection of clinical deterioration (Pruitt & Liebelt, 2010; Shaw et al., 2009; Shaw et al., 2013). A report showed that 4.4% of children from birth to 15 years, who are cared for in hospital settings in Sweden suffer from health-related injuries, i.e. avoidable injuries caused by treatment rather than an underlying disease (The National Board of Health and Wellfare, 2008). Shortcomings in clinical judgment and communication are common causes of unsafe conditions in pediatric care (Ruddy et al., 2015). Early recognition of severely ill children and the subsequent appropriate intervention are therefore necessary to prevent deterioration and cardiac arrest. Education and practical teamwork exercises, a structured approach and the use of assessment tools are described as ways to facilitate the care of acutely, severely ill children (Almblad, Malqvist, & Engvall, 2016).
⁎ Corresponding author at: Department of Women's and Children's Health, Uppsala University, Akademiska Sjukhuset, SE-751 85 Uppsala, Sweden. E-mail address: [email protected] (A.-C. Almblad).
https://doi.org/10.1016/j.pedn.2017.09.002 0882-5963/© 2017 Elsevier Inc. All rights reserved.
The Pediatric Early Warning Score (PEWS) is a scoring system developed for children and focuses on three components: behavior, color/cardiovascular status and respiratory status (Akre et al., 2010; Monaghan, 2005; Parshuram et al., 2011). A retrospective evaluation of estimated PEWS showed that for 85.5% of the patients, the earliest indicator on a critical PEWS was approximately 11.5 h before deterioration (Akre et al., 2010). A study at a pediatric hospital in Norway showed that a PEWS N3 was associated with severe illnesses and that these children were transferred to a higher level of care more often than children with PEWS 0–2 (Solevag, Eggen, Schroder, & Nakstad, 2013). Sefton, McGrath, Tume, Lane, Lisboa, and Carrol (2014) report that after implementation of PEWS the patients required less Pediatric Intensive Care Unit (PICU) interventions and had a shorter length of stay at the PICU. In addition, PICU service delivery improved. The Promoting Action on Research Implementation in Health Services (PARiHS) is a framework for the implementation of evidence to practice. It is built around three components: Evidence, Context and Facilitation. Evidence encompasses research evidence, clinical experience and local information. Implementation of such evidence is a dialectical process and a team effort. Successful implementation requires contexts that have transformational leaders, evaluative and feedback
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mechanisms and appropriate facilitators who work with individuals and teams to enhance the process (Kitson et al., 2008). PARiHS can identify barriers to research utilization in practice and by processing these barriers increase the susceptibility of an intervention (Obrecht, Van Hulle Vincent, & Ryan, 2014). The Early Detection and Treatment Program for Children (EDT-C) was developed at Uppsala University Hospital and consists of the Pediatric Early Warning Score (PEWS), Airway, Breathing, Circulation, Disability, Exposure (ABCDE), Crew Resource Management (CRM), Situation, Background, Assessment, Recommendation (SBAR), and recommended action according to EDT-Ladder for Children. ABCDE is a structured tool to examine, treat and evaluate the patient's vital functions on the basis of a pre-determined order (Jafarpour, Nassiri, Bidari, Chardoli, & Rahimi-Movaghar, 2015). CRM is a model for teamwork focusing on communication, situation awareness, leadership and resource management (Flin & Maran, 2004; Jafarpour et al., 2015). SBAR is a standardized tool for clear and concise communication (Sweeney, Warren, Gardner, Rojek, & Lindquist, 2014). It has been shown that structured communication can improve teamwork, increase patient safety and reduce unexpected deaths (Barata, Benjamin, Mace, Herman, & Goldman, 2007; Woodhall, Vertacnik, & McLaughlin, 2008) (Panel 1). The Implementation Process In March 2013, EDT-C was implemented, at The University Children's Hospital, Uppsala in accordance with the PARiHS framework. Three inpatient wards participated: the Emergency Care ward with general pediatrics and emergency care with 9 beds, the Elective Care ward with mainly planned care for neurology and surgery with 22 beds, and finally the Oncology ward with 12 beds mainly for planned care for children with blood and tumor diseases. Emergency conditions occur in all units, such as bleeding and infection after surgery, seizures, meningitis and serious brain conditions, life-threatening sepsis and serious
respiratory problems. The implementation process with the preparation phase, implementation phase and evaluation phase is briefly described in Flow Chart 1. Preparation Phase The Brighton Pediatric Early Warning Score scoring system was chosen, on the basis that it is a validated instrument (Akre et al., 2010; Monaghan, 2005). Two translators, one with Swedish and one with English as their mother tongue, translated the PEWS instrument, first from English into Swedish and then back to English. A minor adjustment of the instrument was made regarding oxygen treatment and persistent postoperative vomiting, which was regulated in a separate document. A cross-sectional pilot study was conducted to investigate the interrater reliability for the Swedish version of the PEWS. The PEWS scores were assessed 56 times by two independent observers at an oncologic ward at a University Hospital. Inter-rater reliability for the total PEWS was good to excellent: Cohen's kappa was 0.80 and ICC was 0.96 (Nilsson & Zittra, 2014). The PEWS is a structured instrument to assess patients' health (range from 0 to 9): behavior (0–3) color/cardiovascular status (0–3) and respiratory status (0–3) (Akre et al., 2010). Cross-professional reference groups, consisting of physicians, assistant nurses and nurses, were established on each ward to determine the adapted guidelines These guidelines (Panel 2) determine which patients should be assessed according to PEWS based on the ward's specific needs. The recommendations for actions to be performed on the basis of measured PEWS and/ or concern for the patient's health are described in the EDT-Ladder for Children (Panel 1). Training materials for EDT-C were developed in collaboration with nurses and physicians from the hospital's Clinical Training Center and from various pediatric care wards. The working group underwent EDT-C head instructor training.
Flow Chart 1. The implementation process.
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An eight-hour training program for EDT-C-instructors was conducted, in which a total of 12 instructors (9 nurses and 3 physicians) were trained. The instructors then trained staff on the ward to which they belonged. Cross-professional, mandatory three-hour training sessions was conducted for all employees at the three wards where EDT-C was to be introduced. Context was measured by using the Alberta Context Tool (Estabrooks, Squires, Cummings, Birdsell, & Norton, 2009).
documented for some of the stages it was coded as “partly performed” (Partial adherence to EDT-Ladder for Children). If no measures were documented it was coded as “lack of information” (No adherence to EDT-Ladder for Children). When the PEWS was one (1) for “sleeping” under the category of behavioral/alertness, and it was the only parameter that scored points, it was considered that no action was needed and interpreted as a normal sleeping condition. Statistical comparisons were performed between the wards regarding the presence of documentation of actions performed according to EDT-Ladder for Children.
Evaluation Phase
Data Collection and Sample From the Work Context
Recurring meetings for instructors were provided approximately three times during the first year. These meetings included discussion and feedback about the teaching and implementation of EDT-C on each ward. The instructors' function was, in addition to training staff, to facilitate during the implementation phase on their respective wards to inform, support and to capture the staff's views. The present study is part of a larger project focusing on increased patient safety by the implementation of the concept called Early Detection and Treatment-Children (EDT-C). The aim of the present study was to describe data of PEWS registrations and to evaluate the implementation of PEWS by examining adherence to clinical guidelines based on measured PEWS, and to relate findings to work context.
The Alberta Context Tool (ACT) was developed to describe the conditions in the work environment in health care. It assesses several core domains to provide a comprehensive account of organizational context in health care, and has been validated in settings similar to the current study setting (Squires et al., 2013; Squires et al., 2015). The ACT reflects the following contextual dimensions: leadership, culture, evaluation, social capital, formal and informal interactions, structural and electronic resources and organizational resources of staffing, time and space. The items describing each dimension are presented as statements and measured on a scale from 1 to 5, where five indicates most consistent with the statement. It also adds information about the respondent's working hours, experience, education and age. All who participated in the EDT-C training received an ACT questionnaire. Data were obtained from nurses and nurse assistants. The ACT questionnaires were distributed at training sessions for EDT-C or sent to the respondent's personal postbox, with return envelopes to the first author, after the training session. The questionnaires were marked with a section number but not linked to any person.
Implementation Phase
Method Two study methods were used: a retrospective review of the Electronic Patient Records to assess adherence to guidelines and a context assessment of the work environment on the different wards, using the Alberta Context Tool (ACT). Data Collection and Sample From Electronic Patient Records Data were gathered through the Electronic Patient Record (EPR). Variables collected were: time for PEWS measurement, PEWS, social security number of inpatients, age, gender and healthcare contact number. The concept of healthcare contact number is a specific contact identification for each contact admission to a ward, where each individual may have one or several contact numbers. In addition, the total number of admissions was retrieved. All inpatients were included from the 4th of March 2013 for the Elective Care ward and the 18th of March 2013 for the Oncology ward and the Emergency Care ward up until the 31st of December 2013 where EDT-C had been implemented. Data were retrieved from the EPR by staff at the EPR department. To be able to achieve a structured review of the data from the EPR, a random sample was drawn with the help of the Internet-based tool, Research Randomizer, which is based on the social security number. Patients 19 years and older were excluded. Based on this randomization process 20% of admitted patients at the Oncology and Elective Care and 10% from the Emergency Care wards were included to obtain a suitable sample. Data were collected from the EPR and in addition from the scanned part of the EPR. Day monitoring lists with the PEWS written on paper were scanned and kept in the scanned part of the EPR. Each registered PEWS was studied to ascertain whether blood pressure, saturation and pain assessment had been conducted according to specified guidelines (Panel 2) and documented in the EPR or scanned part of the EPR at the specified time and this was determined as performed when documentation was found. In cases of no documentation of any actions it was determined as “not performed”. Furthermore, the documentation in the EPR or scanned part of the EPR for each PEWS was studied to evaluate if any actions according to the EDT-Ladder for Children (Panel 1) had been performed. When all the measures were documented, it was coded as “performed” (Full adherence to EDT-Ladder for Children). When measures were only
Analysis Data obtained from Electronic Patient Records were processed in Microsoft Excel and the statistics management software IBM SPSS Statistics 22, IBM, New York, US. Data from the questionnaire ACT were processed in IBM SPSS Statistics 20 (IBM, New York, US) according to the Alberta Context Tool User Manual (Squires et al., 2014). Student's t-test was used to analyze dimensions from ACT. Chi-square was used to analyze differences between groups. A p-value b 0.05 was considered significant. Ethical Considerations The EPR system is governed by the Personal Data Acts: SFS 1998:204 and 2008:355 (Ministry of Justice, 1998; Ministry of Social Affairs, 2008). All who received the ACT questionnaire signed a written informed consent form, on which it was stated that participation was voluntary and that the results could not be linked to any person. The study was approved by the Regional Ethical Review Board, Uppsala, Sweden. Result Results consist of: 1) descriptive data from the total PEWS registrations, 2) descriptive data about adherence to each ward's specific guidelines for PEWS and 3) descriptive and comparative data about contextual influences between the three wards based on staff responses to the Alberta Context Tool (ACT). PEWS Measurement, Distribution of Scores In total, 4865 PEWS were recorded, divided into 875 unique social security numbers (individuals) during the study period for children from birth to 19 years old. There was at least one PEWS score recorded for 1160 of these admissions.
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PEWS 0, the patient being unaffected and in a normal state, was measured on 2265 (46.7%) occasions and there were 8 PEWS 7–9 registered (b 0.01%). The majority of PEWS were however, between 0 and 2, PEWS 3–9 were registered on 505 (10.4%) occasions.
Table 2 Adherence to ward-specific guidelines according to the documentation.
When to perform PEWS All admissions to the ward Back to ward after intensive care Acute admissions to the ward Postoperative for certain diagnosis Postoperative Ongoing infection Measuring pain After anesthesia Saturation in respiratory distress At deterioration According to medical prescription Action after PEWS Blood pressure at PEWS N3
PEWS Measurement and Distribution in Age Groups in the Randomized Sample The randomized sample consisted of 20% of all admissions for Oncology and Elective Care, and 10% of all admissions for Emergency Care of the patients aged from birth to 19 years with at least one registered PEWS score. This corresponds to 166 patients (Oncology: 40, Elective Care: 55 and Emergency Care: 71) with a total of 981 PEWS (Oncology: 279, Elective Care: 227 and Emergency Care: 475). PEWS 0 and PEWS 1–2 were measured on 444 (45.3%) and 401(40.9%) occasions respectively. PEWS 3–4 were measured on 108 (11%) occasions and 28 (2.9%) scored PEWS 5–9, of which 12 were for children less than one year old. In the age group 16–17 years, 63 PEWS were measured and 3 of them were PEWS 5–9. In the age group 7–15 years, no PEWS 5–9 were measured (Table 1). Adherence to Ward-specific Guidelines for PEWS Adherence to the specific guidelines (Panel 2) for PEWS is presented in Table 2. Adherence was 65% and 88% for performing PEWS at all admissions at Oncology and Emergency Care respectively, and 67% at acute admissions at Elective Care. Adherence was between 83 and 92% for measurement of oxygen saturation when respiratory distress was noted. Measuring PEWS according to medical prescription was 79% for Oncology, 56% for Elective Care, and 87% for Emergency Care. Adherence to blood pressure measurement at scores ≥ 3 was 51% for Oncology, whereas it was 8% for Elective Care and 13% for Emergency Care. Instructions to measure pain revealed adherence of 7–13% on the three wards.
Oncology
Elective
Emergency
n
%
n
%
n
%
41 1
65 25 –
–
–
51
88
67 60 81 – 7
–
–
4 36
33 – 13
68
– 62 10 50 84 – 79
6 3 29 – 16 19 5 44
83 45 56
69 0 202
92 0 87
19
51
2
8
6
13
– 89 27 13 57
Work Context The ACT survey was distributed to nurses and assistant nurses currently working in the three wards. In Oncology, 23 completed surveys of 31 distributed (74%), with Elective Care, 46 of 59 distributed (78%), and with Emergency Care, 40 of 48 distributed (83%) were collected. There were no differences in culture, internal processes, relationships, staffing and time between the three wards. For leadership there was a difference between Elective Care and Emergency Care revealing higher levels of satisfaction in Elective Care. There was also a difference in the evaluation dimension between Elective Care and Emergency Care, where the staff reported that evaluation and feedback occurred to a greater extent in Elective Care compared to Emergency Care. No differences between men and women or between nurses and assistant nurses could be found (Table 4).
Adherence to Early Detection and Treatment Ladder for Children
Discussion
There were 536 registered measurements of PEWS 1 or higher (Oncology: 137; Elective Care: 113 and Emergency Care: 286) which were compared to the recommended actions according to the EDT-Ladder for Children (Panel 1). According to the documentation in the EPR, there was full adherence to the EDT-Ladder for Children in 23.4%, partial in 32.1% and no adherence in 44.5% of cases in Oncology; full adherence in 39.8%, partial in 30% and no adherence in 30% of cases in Elective Care; full adherence in 36.7%, partial in 6.9% and no adherence in 56.2% of cases in Emergency Care (Table 3). When comparing groups (Chi-square test) there was greater adherence to full adherence in Elective Care compared to partial/no adherence to recommended actions in Oncology (p b 0.01) and greater adherence in Emergency Care compared to Oncology (p b 0.01). However, there was no difference between Elective Care and Emergency Care (p = 0.6). When comparing full/partial adherence to no adherence there was a greater adherence to EDT-Ladder for Children in Elective Care vs Oncology (p = 0.035), and in Elective Care vs. Emergency Care (p ≤0.01) and also in Oncology vs Emergency Care (p = 0.01).
In the randomized sample most of the measured PEWS were 0–2 and only a few scored PEWS 5–9. This reveals that the majority of hospitalized patients in the present study were stable in behavior, cardiovascular status and respiratory status according to PEWS. Solevag et al. (2013) showed that PEWS N 3 occurred in 16% of patients and were most common in younger children (b 2 years). The purpose of PEWS is to detect patients at risk of deterioration and thereby optimize treatment to avoid further deterioration and death (Monaghan, 2005). A measured PEWS N2 may indicate temporary or severe persistent deterioration. Consequently, the recommended monitoring and treatment remains important at this level. PEWS 5–9 occurred 28 times in this study, which may indicate that patients with a very high risk of clinical deterioration were identified on the ward. In modern health care medical monitoring equipment plays a significant role, despite the fact that it cannot fully replace the professional judgment of healthcare professionals. According to Lambert, Matthews, MacDonell, and Fitzsimons (2017), real-life cases and using a cross-professional approach to PEWS education can stimulate a heightened sense of situation
Table 1 Distribution of total PEWS according to age groups in the randomized sample (n = 981). PEWS
0 1–2 3–4 5–6 7–9
0 yr
1–2 yrs
3–6 yrs
7–9 yrs
10–12 yrs
13–15 yrs
16–17 yrs
18 yrs
n
%
n
%
n
%
n
%
n
%
n
%
n
%
n
%
113 113 27 9 3
11.5 11.5 2.8 0.9 0.3
76 98 31 5 3
7,7 9.9 3.2 0.5 0.3
81 85 29 5 0
8.2 8.6 3.0 0.5 0
67 45 12 0 0
6.8 4.5 1.2 0 0
20 9 0 0 0
2.0 0.9 0 0 0
54 20 2 0 0
5.5 2.0 0.2 0 0
27 26 7 2 1
2.7 2.6 0.7 0.2 0.1
6 5 0 0 0
0.6 0.5 0 0 0
A.-C. Almblad et al. / Journal of Pediatric Nursing 38 (2018) 33–39 Table 3 Documentation of adherence to measures (n = 536) according to EDT-Ladder for Children per ward: Oncology ward (n = 137), Elective Care ward (n = 113) and Emergency Care ward (n = 286). Oncology
Full adherence Partial adherence No adherence
Elective
Emergency
n
%
n
%
n
%
32 44 61
23.4 32.1 44.5
45 34 34
39.8 30 30
105 20 161
36.7 6.9 56.2
awareness and open communication among clinicians about children at risk of clinical deterioration. Adherence to ward-specific guidelines according to the data from EPR varied in the three wards. Measuring oxygen saturation during respiratory distress had high adherence in all three wards as well as medical prescription and admissions to the wards, while adherence to pain measurement was low in all wards. Adherence to blood pressure at PEWS N3 was high at Oncology but low at Elective Care and Emergency Care. This may indicate that blood pressure was an important parameter in the type of care that was conducted at Oncology (Jeddi et al., 2010) while it did not have the same importance in the care in Elective Care and Emergency Care. The adapted guidelines were established before the introduction of EDT-C and an evaluation may be necessary to assess their relevance for the care provided on the wards. For those that are considered relevant there should be a discussion on how compliance can increase. Tsao & Browne (2015) describe the importance of developing a culture focused on safety as such a priority is needed for the sustainable reduction of harm, and improvement in the reliability of care. In a Swedish study it was shown that certain factors, such as feedback processes, structural resources and information sharing in the
Table 4 Mean scores of Alberta Context Tool dimensions, per ward. Dimensions of ACT Leadership
Culture
Evaluation
Formal interactions
Informal interactions
Social capital
Structural and electronic resources Organizational slack - staff
Organizational slack - space
Organizational slack - time
Student's t-test. ⁎ p b 0.05. ⁎⁎ p b 0.01.
Oncology Elective Emergency p n = 23 n = 46 n = 40 Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev Mean Std. dev
4.12 0.55
4.34 0.53
3.80 0.68
4.09 0.43
4.19 1.31
4.06 0.43
3.29 0.46
3.46 0.49
3.24 0.52
0.75 0.46
0.93 0.54
0.71 0.60
3.47 1.59
3.77 1.70
3.37 1.83
4.17 0.41
4.13 0.50
4.24 0.47
3.85 1.41
3.43 1.64
4.11 1.59
2.98 0.92
2.84 0.96
2.78 0.85
3.59 0.66
2.07 0.88
2.26 0.98
2.79 0.51
2.63 0.59
2.69 0.51
⁎⁎
⁎
⁎⁎
37
work context affected adherence to clinical practice guidelines among registered nurses in pediatric care (Forberg et al., 2014). The analysis of ACT in this study showed that the highest score for the dimension leadership and evaluation occurred in Elective Care. Adherence to the EDT-Ladder for Children was, according to documented percentage, also highest in Elective Care. These two results may indicate that work context may influence adherence to guidelines. Furthermore, the structure on a ward with elective care, where the diagnosis is known and the care planned, may also influence guidelines and documentation. Implementation can be seen as a process to increase knowledge with the aim of achieving change. Complex interventions like EDT-C involve individual, group and organizational levels. It is necessary to find out what is implemented and how a process evaluation can be investigated by: fidelity, if the intervention was delivered as intended; dose, the quantity of intervention implemented; and reach, how and if the intended audience comes in contact with the intervention (Kitson et al., 2008). Even if the implementation process does not vary, the intervention may have different effects in different contexts (Moore et al., 2015; Shiell, Hawe, & Gold, 2008). For example, the documentation and monitoring of the patient may be affected in a ward where there is high patient turnover, such as in an Emergency Care. Patients may also to a greater extent have electronic monitoring equipment and caregivers may therefore perceive that they have control over the condition of the patient. There are also several other factors that may have an impact on adherence to guidelines, such as how engaged and dedicated the facilitators are and how they perceive their role (Waterman et al., 2015). The importance of proper documentation could also have been better clarified and emphasized in the training prior to the implementation process. Scott, Grimshaw, Klassen, Nettel-Aguirre, and Johnson (2011) have designed a protocol which can be used in future studies in order to study the causal mechanism and factors that shape the implementation process of guidelines and how to reduce clinical practice variations. Implementation aims, as have been previously highlighted, to raise awareness and create change. PEWS should be embraced as a part of a larger multifaceted safety framework which can lead to increased knowledge about early detection of deterioration, optimize treatment and teamwork. This can develop over time with strong leadership, targeted training, ongoing support and continuous improvement (Lambert et al., 2017). An expanded toolbox, like PEWS, can enhance the ability to make an objective assessment of the patient's condition and strengthen the nursing profession. Methodological Considerations Implementation of evidence-based care is complicated, and good conditions for applying evidence in clinical work must be created even if, as in this process, the healthcare organization is large and complex. To study the outcome of the implementation process and to be able to handle a large amount of data, a retrospective medical review was chosen. Individual cases could also be interesting to study, but they would only be able to show data from a small group of patients. Akenroye and Stack (2015) found that the keys to success were strong leadership, support and local presence of guidelines, selection of motivated facilitators, development of practical processes for guidelines and implementation, and frequent feedback to stakeholders. This implementation of EDT-C included several of these factors on three different wards and included all categories of health professionals. An implementation process based on multidisciplinary involvement can increase the understanding of each other's levels of knowledge. According to Murray, Williams, Pignataro, and Volpe (2015) education in the clinical setting regarding early warning system scores should emphasize that these tools aid all levels of expertise and should be introduced in an inter-professional forum to engage all users. Also Kitson et al. (2008) state that implementation requires effective dialogue and teamwork with great understanding of the different professions' skills. PEWS
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can help healthcare professionals with varying degrees of education and experience to assess the patient's condition so that the patient receives optimal care. With the implementation of an early warning score system it is important to select a tool for children that is validated, reliable and best meets the needs of the patient (Chapman, Grocott, & Franck, 2010).
Strengths The present study has contributed to increase knowledge about implementation processes in complex healthcare environments. EDT-C is a new concept which comprises conventional components for healthcare professionals using a structured process to assess, treat and communicate. This can lead to increased knowledge about early detection of deterioration, strengthen nurses as professionals, optimize work treatment and teamwork and thereby increase patient safety for children at Swedish hospitals. The PARiHS framework was used as a model for the implementation, and a validated instrument, PEWS, was chosen (Kitson et al., 2008). Furthermore, an investigation of inter-rater reliability of the Swedish version of the PEWS instrument was performed (Akre et al., 2010; Nilsson & Zittra, 2014). To adapt the use of PEWS optimally in the different wards, ward-specific guidelines based on the specific health needs were formulated, and interdisciplinary teams together with EDT-C instructors were assigned to facilitate the implementation. ACT was used to examine the work context which is a validated instrument used both international and nationally in different healthcare settings (Eldh, Ehrenberg, Squires, Estabrooks, & Wallin, 2013; Squires et al., 2015). The ACT manual was used for distribution and analysis (Squires et al., 2014).
Limitations Some weaknesses in the study need to be mentioned. This study is based on material from output data and the documentation that has been available in the EPR. This does not give any indication of measurements and assessments that may have been carried out without being documented. It is even more difficult to estimate how well the documentation of actions according to the EDT-Ladder for Children was carried out. An observation study may provide answers to what is conducted and thereafter documented. In emergency situations documentation is very important but can sometimes have a lower priority due to stress with the focus of the team being to assess and treat the patient optimally (Ali, Thomson, Graham, Rickard, & Stang, 2017). Lack of time and staff resources can also be a contributing factor to inadequate documentation. The organization and management of data may have caused errors since documentation has been carried out in different systems in the EPR. However, additional examination of the records in the EPR and the scanned part of EPR reduced the risk of missing data in the randomized sample. The study is based on material from approximately the ten first months after the implementation of the EDT-C. Since this was a relatively short time for such a comprehensive implementation process, it would be interesting to repeat the study at a later stage to see how adherence to guidelines and estimated PEWS has developed. McLellan, Gauvreau and Connor (2017) showed in a study of the Children's Hospital Early Warning Score (CHEWS), that CHEWS had a higher sensitivity but a longer early warning time than PEWS, so ongoing development work is necessary to refine the instrument. To enhance the understanding of the complex process of implementation, further studies are needed in which healthcare professionals' experiences of implementation are captured.
Conclusion Evaluation of the implementation of PEWS at a pediatric hospital in Sweden indicated frequent use of the tool despite the fact that most scores were low, signifying that the majority of hospitalized patients are stable in behavior, cardiovascular status and respiratory status according to PEWS. Estimated PEWS 5–9 occurred 28 times in this study, which may indicate that patients with a very high risk of deterioration are identified at the ward. Documentation of assessments of the patient and the subsequent recommended actions was however incomplete and there was significant variation in adherence to guidelines. Contextual factors such as leadership and evaluation may have impact on adherence to guidelines. Targeted training and ongoing support by facilitators in a continuous improvement effort supported by strong leadership is warranted. EDT-C can lead to increased knowledge about early detection of deterioration, strengthen nurses as professionals, optimize treatment and teamwork and thereby increase patient safety for children treated in hospitals. Acknowledgments This research was supported by Her Royal Highness Crown Princess Lovisa's Society for Children's Health Care, Sweden. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.pedn.2017.09.002. References Akenroye, A. T., & Stack, A. M. (2015). The development and evaluation of an evidencebased guideline programme to improve care in a paediatric emergency department. Emergency Medicine Journal. https://doi.org/10.1136/emermed-2014-204363. Akre, M., Finkelstein, M., Erickson, M., Liu, M., Vanderbilt, L., & Billman, G. (2010). Sensitivity of the pediatric early warning score to identify patient deterioration. Pediatrics, 125(4), e763–769. https://doi.org/10.1542/peds.2009-0338. Ali, S., Thomson, D., Graham, T. A., Rickard, S. E., & Stang, A. S. (2017). High stakes and high emotions: Providing safe care in Canadian emergency departments. Open Access Emergency Medicine, 9, 23–26. https://doi.org/10.2147/oaem.s122646. Almblad, A. C., Malqvist, M., & Engvall, G. (2016). Caring for the acutely, severely ill childA multifaceted situation with paradoxical elements: Swedish healthcare professionals' experiences. Journal of Pediatric Nursing, 31(5), e293–e300. https://doi.org/ 10.1016/j.pedn.2016.05.001. Barata, I. A., Benjamin, L. S., Mace, S. E., Herman, M. I., & Goldman, R. D. (2007). Pediatric patient safety in the prehospital/emergency department setting. Pediatric Emergency Care, 23(6), 412–418. https://doi.org/10.1097/01.pec.0000278393. 32752.9f. Chapman, S. M., Grocott, M. P., & Franck, L. S. (2010). Systematic review of paediatric alert criteria for identifying hospitalised children at risk of critical deterioration. Intensive Care Medicine, 36(4), 600–611. https://doi.org/10.1007/s00134-009-1715-x. Eldh, A. C., Ehrenberg, A., Squires, J. E., Estabrooks, C. A., & Wallin, L. (2013). Translating and testing the Alberta context tool for use among nurses in Swedish elder care. BMC Health Services Research, 13, 68. https://doi.org/10.1186/1472-6963-13-68. Estabrooks, C. A., Squires, J. E., Cummings, G. G., Birdsell, J. M., & Norton, P. G. (2009). Development and assessment of the Alberta Context Tool. BMC Health Services Research, 9, 234. https://doi.org/10.1186/1472-6963-9-234. Flin, R., & Maran, N. (2004). Identifying and training non-technical skills for teams in acute medicine. Quality & Safety in Health Care, 13(Suppl. 1), i80–84. https://doi. org/10.1136/qhc.13.suppl_1.i80. Forberg, U., Wallin, L., Johansson, E., Ygge, B. M., Backheden, M., & Ehrenberg, A. (2014). Relationship between work context and adherence to a clinical practice guideline for peripheral venous catheters among registered nurses in pediatric care. Worldviews on Evidence-Based Nursing, 11(4), 227–239. https://doi.org/10.1111/ wvn.12046. Jafarpour, S., Nassiri, S. J., Bidari, A., Chardoli, M., & Rahimi-Movaghar, V. (2015). Principles of primary survey and resuscitation in cases of pediatric trauma. Acta Medica Iranica, 53(4), 242–245. Jeddi, R., Achour, M., Amor, R. B., Aissaoui, L., Bouteraa, W., Kacem, K., ... Meddeb, B. (2010). Factors associated with severe sepsis: Prospective study of 94 neutropenic febrile episodes. Hematology, 15(1), 28–32. https://doi.org/10.1179/ 102453310x12583347009577. Kitson, A. L., Rycroft-Malone, J., Harvey, G., McCormack, B., Seers, K., & Titchen, A. (2008). Evaluating the successful implementation of evidence into practice using the PARiHS framework: Theoretical and practical challenges. Implementation Science, 3, 1–12. https://doi.org/10.1186/1748-5908-3-1.
A.-C. Almblad et al. / Journal of Pediatric Nursing 38 (2018) 33–39 Lambert, V., Matthews, A., MacDonell, R., & Fitzsimons, J. (2017). Paediatric early warning systems for detecting and responding to clinical deterioration in children: A systematic review. BMJ Open, 7(3), e014497. https://doi.org/10.1136/bmjopen-2016-014497. McLellan, M. C., Gauvreau, K., & Connor, J. A. (2017). Validation of the Children's Hospital Early Warning System for Critical Deterioration Recognition. Journal of Pediatric Nursing, 32, 52–58. https://doi.org/10.1016/j.pedn.2016.10.005. Ministry of Justice (1998). Svensk författningssamling SFS personuppgiftslagen: 1998:204. (In Swedish). Ministry of Social Affairs (2008). Svensk författningssamling SFS 2008:355 Patientdatalagen. Monaghan, A. (2005). Detecting and managing deterioration in children. Paediatric Nursing, 17(1), 32–35. https://doi.org/10.7748/paed2005.02.17.1.32.c964. Moore, G. F., Audrey, S., Barker, M., Bond, L., Bonell, C., Hardeman, W., ... Baird, J. (2015). Process evaluation of complex interventions: Medical Research Council guidance. BMJ, 350, h1258. https://doi.org/10.1136/bmj.h1258. Murray, J. S., Williams, L. A., Pignataro, S., & Volpe, D. (2015). An Integrative Review of Pediatric Early Warning System Scores. Pediatric Nursing, 41(4), 165–174. Nilsson, E., & Zittra, T. (2014). Bedömning av vitalparametrar hos barn med cancer. Tillförlitlighet av bedömningsinstrumentet Pediatric Early Warning Score (in Swedish). Master Theses Umeå University. Obrecht, J. A., Van Hulle Vincent, C., & Ryan, C. S. (2014). Implementation of evidencebased practice for a pediatric pain assessment instrument. Clinical Nurse Specialist, 28(2), 97–104. https://doi.org/10.1097/nur.0000000000000032. Parshuram, C. S., Duncan, H. P., Joffe, A. R., Farrell, C. A., Lacroix, J. R., Middaugh, K. L., ... Parkin, P. C. (2011). Multicentre validation of the bedside paediatric early warning system score: A severity of illness score to detect evolving critical illness in hospitalised children. Critical Care, 15(4), R184. https://doi.org/10.1186/cc10337. Pruitt, C. M., & Liebelt, E. L. (2010). Enhancing patient safety in the pediatric emergency department: Teams, communication, and lessons from crew resource management. Pediatric Emergency Care, 26(12), 942–948 quiz 949–951 https://doi.org/10.1097/ PEC.0b013e3181fec9cf. Ruddy, R. M., Chamberlain, J. M., Mahajan, P. V., Funai, T., O'Connell, K. J., Blumberg, S., ... Shaw, K. N. (2015). Near misses and unsafe conditions reported in a Pediatric Emergency Research Network. BMJ Open, 5(9), e007541. https://doi.org/10.1136/ bmjopen-2014-007541. Scott, S. D., Grimshaw, J., Klassen, T. P., Nettel-Aguirre, A., & Johnson, D. W. (2011). Understanding implementation processes of clinical pathways and clinical practice guidelines in pediatric contexts: a study protocol. Implementation Science, 6, 133. https:// doi.org/10.1186/1748-5908-6-133. Sefton, G., McGrath, C., Tume, L., Lane, S., Lisboa, P. J., & Carrol, E. D. (2014). What impact did a Paediatric Early Warning system have on emergency admissions to the paediatric intensive care unit? An observational cohort study. Intensive & Critical Care Nursing. https://doi.org/10.1016/j.iccn.2014.01.001.
39
Shaw, K. N., Lillis, K. A., Ruddy, R. M., Mahajan, P. V., Lichenstein, R., Olsen, C. S., & Chamberlain, J. M. (2013). Reported medication events in a paediatric emergency research network: Sharing to improve patient safety. Emergency Medicine Journal, 30(10), 815–819. https://doi.org/10.1136/emermed-2012-201642. Shaw, K. N., Ruddy, R. M., Olsen, C. S., Lillis, K. A., Mahajan, P. V., Dean, J. M., & Chamberlain, J. M. (2009). Pediatric patient safety in emergency departments: Unit characteristics and staff perceptions. Pediatrics, 124(2), 485–493. https://doi.org/10. 1542/peds.2008-2858. Shiell, A., Hawe, P., & Gold, L. (2008). Complex interventions or complex systems? Implications for health economic evaluation. BMJ, 336(7656), 1281–1283. https://doi.org/ 10.1136/bmj.39569.510521.AD. Solevag, A. L., Eggen, E. H., Schroder, J., & Nakstad, B. (2013). Use of a modified pediatric early warning score in a department of pediatric and adolescent medicine. PloS One, 8(8), e72534. https://doi.org/10.1371/journal.pone.0072534. Squires, J. E., Estabrooks, C. A., Scott, S. D., Cummings, G. G., Hayduk, L., Kang, S. H., & Stevens, B. (2013). The influence of organizational context on the use of research by nurses in Canadian pediatric hospitals. BMC Health Services Research, 13, 351. https://doi.org/10.1186/1472-6963-13-351. Squires, J. E., Hayduk, L., Hutchinson, A. M., Mallick, R., Norton, P. G., Cummings, G. G., & Estabrooks, C. A. (2015). Reliability and validity of the Alberta Context Tool (ACT) with professional nurses: Findings from a multi-study analysis. PloS One, 10(6), e0127405. https://doi.org/10.1371/journal.pone.0127405. Squires, J. E., Hutchinson, A., Hayduk, L., Cranley, L., Cummings, G., Norton, P., & Estabrooks, C. (2014). Alberta context tool, user manual. Retrieved from http:// www.kusp.ualberta.ca/en/ACT/~/media/Knowledge%20Utilization%20Studies% 20Program/Documents/ACT/ACTManual2014.pdf. Sweeney, L. A., Warren, O., Gardner, L., Rojek, A., & Lindquist, D. G. (2014). A simulationbased training program improves emergency department staff communication. American Journal of Medical Quality, 29(2), 115–123. https://doi.org/10.1177/ 1062860613491308. The National Board of Health and Wellfare (2008). Vårdskador inom somatisk slutenvård. (Medical injuries in somatic inpatient) [in Swedish]. Retrieved from http://www. socialstyrelsen.se/publikationer2008/2008-109-16. Tsao, K., & Browne, M. (2015). Culture of safety: A foundation for patient care. Seminars in Pediatric Surgery, 24(6), 283–287. https://doi.org/10.1053/j.sempedsurg.2015.08.005. Waterman, H., Boaden, R., Burey, L., Howells, B., Harvey, G., Humphreys, J., ... Spence, M. (2015). Facilitating large-scale implementation of evidence based health care: Insider accounts from a co-operative inquiry. BMC Health Services Research, 15, 60. https:// doi.org/10.1186/s12913-015-0722-6. Woodhall, L. J., Vertacnik, L., & McLaughlin, M. (2008). Implementation of the SBAR communication technique in a tertiary center. Journal of Emergency Nursing, 34(4), 314–317. https://doi.org/10.1016/j.jen.2007.07.007.