BACKGROUND: Clinical errors in intensive care units (ICUs) are consistently attributed to communication errors. Despite its importance for patient safety and quality in critical care settings, few studies consider interprofessional communication as more than the basic exchange of information. METHODS: We conducted a scoping review of interprofessional communication in ICUs to (1) characterize how communication is defined and measured and (2) identify contributions the field of health communication can make to team communication in ICUs. Through a series of queries in PubMed and Communication and Mass Media Complete databases, we identified and compared persistent gaps in how communication is framed and theorized in 28 publications from health services and 6 from social science outlets. We identified research priorities and suggested strategies for discussing communication more holistically in future health services research. RESULTS: 34 articles published from 1999 to 2021 were included. Six explicitly defined communication. Six were published in social science journals, but none were authored by a communication studies scholar. Half of the articles addressed communication as a transaction focused on information transfer, and the other half addressed communication as a process. CONCLUSIONS: Methodological implications are identified with the intent to encourage future interdisciplinary collaboration for studying communication in ICUs. We discuss the importance of (1) using language to describe communication that facilitates interdisciplinary engagement, (2) prioritizing communication as a process and using qualitative methods to provide insight, and (3) engaging health communication theories and experts to assist in developing more fruitful research questions and designs.

AIM: To analyse how family members participate in hospital inpatient palliative care, and how their participation could be supported. METHODS: This review followed a methodology outlined in the literature for integrative reviews. A literature search supplemented by a manual search was conducted on four electronic databases during 2020 to 2021: PubMed, CINAHL, PsycINFO, and Cochrane Library. A critical appraisal of the included studies was performed, and data were analysed using inductive content analysis. RESULTS: The literature search resulted in 4990 articles, of which 14 articles were included in this review. Four main categories were identified concerning the participation of family members in hospital inpatient palliative care: participation in the physical care, provision of emotional support, promoting good patient care, and support provided by healthcare professionals for family members' participation. Family members' participation can be supported in different ways, including active communication and adequate information. CONCLUSION: Family members' participation in hospital inpatient palliative care has been an important part of palliative care in hospital settings. Family members should be offered the opportunity to participate in patient care, and their presence in the hospital should be accommodated. Research on the topic is still scarce, and future research is needed from different perspectives, including intervention research.

BACKGROUND: Successful implementation and utilization of Computerized Clinical Decision Support Systems (CDSS) in hospitals is complex and challenging. Implementation science, and in particular the Nonadoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework, may offer a systematic approach for identifying and addressing these challenges. This review aimed to identify, categorize, and describe barriers and facilitators to CDSS implementation in hospital settings and map them to the NASSS framework. Exploring the applicability of the NASSS framework to CDSS implementation was a secondary aim. METHODS: Electronic database searches were conducted (21 July 2020; updated 5 April 2022) in Ovid MEDLINE, Embase, Scopus, PyscInfo, and CINAHL. Original research studies reporting on measured or perceived barriers and/or facilitators to implementation and adoption of CDSS in hospital settings, or attitudes of healthcare professionals towards CDSS were included. Articles with a primary focus on CDSS development were excluded. No language or date restrictions were applied. We used qualitative content analysis to identify determinants and organize them into higher-order themes, which were then reflexively mapped to the NASSS framework. RESULTS: Forty-four publications were included. These comprised a range of study designs, geographic locations, participants, technology types, CDSS functions, and clinical contexts of implementation. A total of 227 individual barriers and 130 individual facilitators were identified across the included studies. The most commonly reported influences on implementation were fit of CDSS with workflows (19 studies), the usefulness of the CDSS output in practice (17 studies), CDSS technical dependencies and design (16 studies), trust of users in the CDSS input data and evidence base (15 studies), and the contextual fit of the CDSS with the user's role or clinical setting (14 studies). Most determinants could be appropriately categorized into domains of the NASSS framework with barriers and facilitators in the "Technology," "Organization," and "Adopters" domains most frequently reported. No determinants were assigned to the "Embedding and Adaptation Over Time" domain. CONCLUSIONS: This review identified the most common determinants which could be targeted for modification to either remove barriers or facilitate the adoption and use of CDSS within hospitals. Greater adoption of implementation theory should be encouraged to support CDSS implementation.

BACKGROUND: Hospital-acquired pressure injuries (HAPIs) constitute a significant challenge harming thousands of people worldwide yearly. While various tools and methods are used to identify pressure injuries, artificial intelligence (AI) and decision support systems (DSS) can help to reduce HAPIs risks by proactively identifying patients at risk and preventing them before harming patients. OBJECTIVE: This paper comprehensively reviews AI and DSS applications for HAPIs prediction using Electronic Health Records (EHR), including a systematic literature review and bibliometric analysis. METHODS: A systematic literature review was conducted through PRISMA and bibliometric analysis. In February 2023, the search was performed using four electronic databases: SCOPIS, PubMed, EBSCO, and PMCID. Articles on using AI and DSS in the management of PIs were included. RESULTS: The search approach yielded 319 articles, 39 of which have been included and classified into 27 AI-related and 12 DSS-related categories. The years of publication varied from 2006 to 2023, with 40% of the studies taking place in the US. Most studies focused on using AI algorithms or DSS for HAPIs prediction in inpatient units using various types of data such as electronic health records, PI assessment scales, and expert knowledge-based and environmental data to identify the risk factors associated with HAPIs development. CONCLUSIONS: There is insufficient evidence in the existing literature concerning the real impact of AI or DSS on making decisions for HAPIs treatment or prevention. Most studies reviewed are solely hypothetical and retrospective prediction models, with no actual application in healthcare settings. The accuracy rates, prediction results, and intervention procedures suggested based on the prediction, on the other hand, should inspire researchers to combine both approaches with larger-scale data to bring a new venue for HAPIs prevention and to investigate and adopt the suggested solutions to the existing gaps in AI and DSS prediction methods.

BACKGROUND: Over 50% of annual deaths in low-income and middle-income countries (LMICs) could be averted through access to high-quality emergency care. OBJECTIVES: We performed a scoping review of the literature that described at least one measure of emergency care access in LMICs in order to understand relevant barriers to emergency care systems. ELIGIBILITY CRITERIA: English language studies published between 1 January 1990 and 30 December 2020, with one or more discrete measure(s) of access to emergency health services in LMICs described. SOURCE OF EVIDENCE: PubMed, Embase, Web of Science, CINAHL and the grey literature. CHARTING METHODS: A structured data extraction tool was used to identify and classify the number of 'unique' measures, and the number of times each unique measure was studied in the literature ('total' measures). Measures of access were categorised by access type, defined by Thomas and Penchansky, with further categorisation according to the 'Three Delay' model of seeking, reaching and receiving care, and the WHO's Emergency Care Systems Framework (ECSF). RESULTS: A total of 3103 articles were screened. 75 met full study inclusion. Articles were uniformly descriptive (n=75, 100%). 137 discrete measures of access were reported. Unique measures of accommodation (n=42, 30.7%) and availability (n=40, 29.2%) were most common. Measures of seeking, reaching and receiving care were 22 (16.0%), 46 (33.6%) and 69 (50.4%), respectively. According to the ECSF slightly more measures focused on prehospital care-inclusive of care at the scene and through transport to a facility (n=76, 55.4%) as compared with facility-based care (n=57, 41.6%). CONCLUSIONS: Numerous measures of emergency care access are described in the literature, but many measures are overaddressed. Development of a core set of access measures with associated minimum standards are necessary to aid in ensuring universal access to high-quality emergency care in all settings.

INTRODUCTION: Clinical practice guidelines recommend periodic colonoscopy surveillance following colorectal adenoma excision. Inappropriate use of post polypectomy surveillance is common and lead to improper resource utilisation.The aim of this review is to identify structured interventions which can affect post polypectomy surveillance practices and to evaluate the effectiveness of these various interventions in improving clinician adherence to post polypectomy surveillance guidelines. METHODS: A computerised search was performed to identify relevant studies between 1997 to November 2020. Two investigators identified eligible studies and extracted data independently. The quality of the included studies was assessed by the Newcastle-Ottawa risk of assessment scoring system. RESULTS: The search identified 5602 citations. Forty-one articles were retrieved for full text analysis and seven studies met the inclusion criteria. Compliance to PPS guidelines were higher following interventions which included medical education, specialist nurse coordinators facilitation, continuous quality improvement and clinical decision support systems. CONCLUSION: This study demonstrates that medical education, specialist nurse coordinators, continuous quality improvement and clinical decision support systems are effective in improving clinicians' compliance to post polypectomy surveillance guidelines and is associated with reduction in over- and underutilisation of colonoscopy surveillance resources.

BACKGROUND: In an effort to improve both quality of care and cost-effectiveness, various care-management programmes have been developed for high-need high-cost (HNHC) patients. Early identification of patients at risk of becoming HNHC (i.e. case finding) is crucial to a programme's success. We aim to systematically identify prediction models predicting future HNHC healthcare use in adults, to describe their predictive performance and to assess their applicability. METHODS: Ovid MEDLINE® All, EMBASE, CINAHL, Web of Science and Google Scholar were systematically searched from inception through January 31, 2021. Risk of bias and methodological quality assessment was performed through the Prediction model Risk Of Bias Assessment Tool (PROBAST). RESULTS: Of 5890 studies, 60 studies met inclusion criteria. Within these studies, 313 unique models were presented using a median development cohort size of 20,248 patients (IQR 5601-174,242). Predictors were derived from a combination of data sources, most often claims data (n = 37; 62%) and patient survey data (n = 29; 48%). Most studies (n = 36; 60%) estimated patients' risk to become part of some top percentage of the cost distribution (top-1-20%) within a mean time horizon of 16 months (range 12-60). Five studies (8%) predicted HNHC persistence over multiple years. Model validation was performed in 45 studies (76%). Model performance in terms of both calibration and discrimination was reported in 14 studies (23%). Overall risk of bias was rated as 'high' in 40 studies (67%), mostly due to a 'high' risk of bias in the subdomain 'Analysis' (n = 37; 62%). DISCUSSION: This is the first systematic review (PROSPERO CRD42020164734) of non-proprietary prognostic models predicting HNHC healthcare use. Meta-analysis was not possible due to heterogeneity. Most identified models estimated a patient's risk to incur high healthcare expenditure during the subsequent year. However, case-finding strategies for HNHC care-management programmes are best informed by a model predicting HNHC persistence. Therefore, future studies should not only focus on validating and extending existing models, but also concentrate on clinical usefulness.

OBJECTIVES: Machine learning (ML) has been increasingly used in clinical medicine including studies focused on Clostridioides difficile infection (CDI) to inform to clinical decision making. We aimed to summarize ML choices in studies that used ML to predict CDI or CDI outcomes. METHODS: We searched Ovid MEDLINE, Ovid EMBASE, Web of Science, medRxiv, bioRxiv and arXiv from inception to March 18, 2021. We included fully published studies that used ML where CDI constituted the study population, exposure or outcome. Two reviewers independently identified studies and abstracted outcomes. We summarized study characteristics and approaches to CDI definition and ML-specific modelling. RESULTS: Forty-three studies of prediction (n = 21), classification (n = 17) or inference (n = 5) were included. Approaches to defining CDI were labelling during a clinical study or chart review (n = 21), electronic phenotyping (n = 13) or not specified (n = 9). None of the studies using an electronic phenotype described phenotype validation. Almost all studies (n = 41, 95%) conducted supervised ML and the most common ML algorithms were penalized logistic regression (n = 20, 47%) and classification tree (n = 17, 40%). Approaches to feature selection and dimension reduction were heterogeneous. Metrics were evaluated in a held-out test set in 16 (37%) studies; only seven used a time-based split. In terms of reporting quality assessment, the most poorly reported items were data leakage prevention (n = 0, 0%), code availability (n = 8, 19%) and class imbalance management (n = 12, 43%). CONCLUSIONS: While many studies have used ML to investigate CDI or CDI outcomes, electronic phenotyping of CDI was uncommon and phenotype validation was not reported in any study. Methodological approaches were heterogeneous. Validating CDI electronic phenotypes, evaluating performances of CDI models during a silent trial and deploying a CDI classifier to guide clinical practice are important future goals.

Delirium is one of the common manifestations of acute brain dysfunction in critically ill patients. We aimed to evaluate the effect of family intervention on reducing the delirium incidence in patients hospitalized in the intensive care unit (ICU). We searched electronic databases for randomized clinical trials, cohort, and before-and-after studies up to September 2021 using the MeSH terms ("family" OR "family caregiver") AND ("delirium"). A total of 6 studies including 4199 patients were analyzed. Compared to the control group, the risk of delirium was 24% lower in the family intervention group (OR 0·76 [0·67-0·86], P = 0.20, I2 = 31%). Pooled data from two trials showed that family intervention was associated with fewer delirium days (SMD: -1.13, 95% CI: -1.91 to -0.34; P = 0.08; I2 = 67%;). However, there were no significant differences between the two groups in the length of ICU stay, mechanical ventilation duration, and mortality (ICU stay days: MD: -0.62 days; 95% CI: -1.49 to 0.24; P = 0.14; I2 = 72%; mechanical ventilation days: MD: -0.48 days; 95% CI: -2.10 to 1.13; P = 0.56; I2 = 0%; mortality: OR: 0.68, 95% CI: 0.22 to 2.09; P = 0.08; I2 = 67%). Current evidence supports the use of family intervention in reducing the delirium risk and delirium days in hospitalized ICU patients. However, its effects on reducing ICU stay length, ventilation duration, and mortality require further study. Future research should consider identifying the specific family intervention strategies and their duration.

Parental presence at the bedside (PPB) of critically ill children in the pediatric intensive care unit (PICU) is necessary for operationalizing family-centred care. Previous evidence syntheses emphasize parent-healthcare provider interactions at rounds and resuscitation; our focus is the parent–child dyad. Prior to embarking on further study, we performed a scoping review to determine the breadth and scope of the literature addressing PPB of critically ill children in the PICU. We searched five online databases (MEDLINE, EMBASE, CINAHL, Cochrane Library, and PSYCHINFO) and the grey literature to identify English and French reports from January 1960 to June 2020 addressing physical parental presence with children (birth to 18 years) in intensive care units, without limitation by methodology. Screening, reference selection, and data extraction were performed by two independent reviewers. Data were extracted into a researcher-designed tool. We identified 204 publications (81 quantitative, 68 qualitative, 22 mixed methods, and 9 descriptive case or practice change studies, and a further 24 non-study reports). PPB was directly assessed in 78 (38%) reports, and was the primary objective in 64 (31%). Amount or quality of presence was addressed by 114 reports, barriers and enablers by 152 sources, and impacts and outcomes by 134 sources. While only 6 reports were published in the first two decades of our search (1960–1980), 17 reports were published in 2019 alone. CONCLUSIONS: A relatively large body of literature exists addressing PPB of critically ill children. Separate systematic evidence syntheses to assess each element of PPB are warranted.

OBJECTIVE: To determine the effects of using unstructured clinical text in machine learning (ML) for prediction, early detection, and identification of sepsis. MATERIALS AND METHODS: PubMed, Scopus, ACM DL, dblp, and IEEE Xplore databases were searched. Articles utilizing clinical text for ML or natural language processing (NLP) to detect, identify, recognize, diagnose, or predict the onset, development, progress, or prognosis of systemic inflammatory response syndrome, sepsis, severe sepsis, or septic shock were included. Sepsis definition, dataset, types of data, ML models, NLP techniques, and evaluation metrics were extracted. RESULTS: The clinical text used in models include narrative notes written by nurses, physicians, and specialists in varying situations. This is often combined with common structured data such as demographics, vital signs, laboratory data, and medications. Area under the receiver operating characteristic curve (AUC) comparison of ML methods showed that utilizing both text and structured data predicts sepsis earlier and more accurately than structured data alone. No meta-analysis was performed because of incomparable measurements among the 9 included studies. DISCUSSION: Studies focused on sepsis identification or early detection before onset; no studies used patient histories beyond the current episode of care to predict sepsis. Sepsis definition affects reporting methods, outcomes, and results. Many methods rely on continuous vital sign measurements in intensive care, making them not easily transferable to general ward units. CONCLUSIONS: Approaches were heterogeneous, but studies showed that utilizing both unstructured text and structured data in ML can improve identification and early detection of sepsis.

OBJECTIVE: To evaluate the effectiveness of exercise interventions delivered via telerehabilitation (via videoconference) for recently hospitalized adult medical patients. DATA SOURCES: A search was undertaken across six databases for English language publications from inception to May 2020. METHODS: Studies were selected if they included an exercise intervention for recently hospitalized adults, delivered by a physiotherapist via videoconference. Two reviewers independently screened 1,122 articles (21 full text screening) and assessed methodological quality using the Downs and Black Checklist. A narrative synthesis of the included studies was undertaken. RESULTS: Three studies met eligibility criteria involving 201 participants with chronic heart failure or chronic obstructive pulmonary disease. Findings demonstrated limited evidence supporting the effectiveness of exercise delivered via telerehabilitation in improving physical function and patient reported quality of life outcomes in recently hospitalized medical patients. Telerehabilitation in this setting was also associated with high attendance rates and patient satisfaction. CONCLUSIONS: Findings provide preliminary support for the benefits of exercise interventions delivered via telerehabilitation for recently hospitalized medical patients. Results do need to be interpreted with caution as further high-quality studies specific to this method of exercise intervention delivery are needed.

BACKGROUND: Emergency telehealth has been used to improve access of patients residing in rural and remote areas to specialist care in the hope of mitigating the significant health disparities that they experience. Patient disposition decisions in rural and remote emergency departments (EDs) can be complex and largely dependent on the expertise and experience available at local (receiving-end) hospitals. Although there has been some synthesis of evidence of the effectiveness of emergency telehealth in clinical practice in rural and remote EDs for nonacute presentations, there has been limited evaluation of the influence of contextual factors such as clinical area and acuity of presentation on these findings. OBJECTIVE: The aims of this systematic review are to examine the outcome measures used in studying the effectiveness of telehealth in rural and remote EDs and to analyze the clinical context in which these outcome measures were used and interpreted. METHODS: The search strategy used Medical Subject Headings and equivalent lists of subject descriptors to find articles covering 4 key domains: telehealth or telemedicine, EDs, effectiveness, and rural and remote. Studies were selected using the Population, Intervention, Comparator, Outcomes of Interest, and Study Design framework. This search strategy was applied to MEDLINE (Ovid), Cochrane Library, Scopus, CINAHL, ProQuest, and EconLit, as well as the Centre for Reviews and Dissemination databases (eg, National Health Service Economic Evaluation Database) for the search period from January 1, 1990, to May 23, 2020. Qualitative synthesis was performed on the outcome measures used in the included studies, in particular the clinical contexts within which they were interpreted. RESULTS: A total of 21 full-text articles were included for qualitative analysis. Telehealth use in rural and remote EDs demonstrated effectiveness in achieving improved or equivalent clinical effectiveness, appropriate care processes, and-depending on the context-improvement in speed of care, as well as favorable service use patterns. The definition of effectiveness varied across the clinical areas and contexts of the studies, and different measures have been used to affirm the safety and clinical effectiveness of telehealth in rural and remote EDs. The acuity of patient presentation emerged as a dominant consideration in the interpretation of interlinking time-sensitive clinical effectiveness and patient disposition measures such as transfer and discharge rates, local hospital admission, length of stay, and ED length of stay. These, together with clinical area and acuity of presentation, are the outcome determination criteria that emerged from this review. CONCLUSIONS: Emergency telehealth studies typically use multiple outcome measures to determine the effectiveness of the services. The outcome determination criteria that emerged from this analysis are useful when defining the favorable direction for each outcome measure of interest. The findings of this review have implications for emergency telehealth service design and policies.

Nutrition is a key component of care for critically ill patients; yet nutrition delivery is below international recommendations. In order to improve nutrition delivery to critically ill patients, an understanding of the barriers that prevent guideline adherence is required. It is known that clinicians' knowledge, attitudes, and beliefs of the role of nutrition may act as a potential barrier to nutrition delivery, but whether this remains true in critical care is unknown. The aim of this systematic scoping review was to summarize the literature exploring the knowledge, attitudes, and beliefs of clinicians around nutrition support in critically ill patients. A search of four online databases (MEDLINE via Ovid, Emcare via Ovid, PsycINFO, and CINAHL via EBSCOhost) was conducted on August 14, 2020, to identify literature that reported on clinicians' knowledge, attitudes, and beliefs of nutrition in adult intensive care patients. Data were extracted on study and participant characteristics, methodology, and key study outcomes related to nutrition. Eighteen articles met eligibility criteria and were included in the review. Key findings included the following: nutrition was seen as a priority that ranked below life-saving interventions; differences in perceived clinician responsibilities exist; common barriers to nutrition delivery included inadequate resourcing, lack of nutrition protocols, and gastrointestinal intolerance; and identified facilitators included nutrition education and the presence of a supportive multidisciplinary team. The implementation of nutrition protocols, enhanced clinical nutrition education, and further clarification of roles and responsibilities pertaining to nutrition may assist in improving nutrition delivery in critical care.

BACKGROUND: Methods to visualise patient safety data can support effective monitoring of safety events and discovery of trends. While quality dashboards are common, use and impact of dashboards to visualise patient safety event data remains poorly understood. OBJECTIVES: To understand development, use and direct or indirect impacts of patient safety dashboards. METHODS: We conducted a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched PubMed, EMBASE and CINAHL for publications between 1 January 1950 and 30 August 2018 involving use of dashboards to display data related to safety targets defined by the Agency for Healthcare Research and Quality's Patient Safety Net. Two reviewers independently reviewed search results for inclusion in analysis and resolved disagreements by consensus. We collected data on development, use and impact via standardised data collection forms and analysed data using descriptive statistics. RESULTS: Literature search identified 4624 results which were narrowed to 33 publications after applying inclusion and exclusion criteria and consensus across reviewers. Publications included only time series and case study designs and were inpatient focused and emergency department focused. Information on direct impact of dashboards was limited, and only four studies included informatics or human factors principles in development or postimplementation evaluation. DISCUSSION: Use of patient-safety dashboards has grown over the past 15 years, but impact remains poorly understood. Dashboard design processes rarely use informatics or human factors principles to ensure that the available content and navigation assists task completion, communication or decision making. CONCLUSION: Design and usability evaluation of patient safety dashboards should incorporate informatics and human factors principles. Future assessments should also rigorously explore their potential to support patient safety monitoring including direct or indirect impact on patient safety.

Intensive care units are hostile places, which must be conditioned to the needs of patients and families, and therefore the factors that influence their satisfaction must be known. OBJECTIVE: To update the knowledge on the satisfaction of the patients admitted to an adult intensive care unit and that of their family caregivers as described in the scientific literature. METHODOLOGYy: A systematized literature review was carried out in PubMed, Scopus, Cinahl and WOS databases. SEARCH STRATEGY: "Personal Satisfaction" and (patients or caregivers) and "Intensive Care Units". INCLUSION CRITERIA: studies published between 2013-2018, population aged between 19-64 years, english and spanish language. RESULTS: 760 studies were located and 15 were selected. The factors that increased satisfaction are: good communication with professionals (n=5), the quality of care (n=4), and the cleanliness and environment of the units (n=2). The factors that produced dissatisfaction are: the infrastructure of the waiting room (n=5), inadequate communication (n=4), and the involvement of families and patients in decision-making (n=4). Training of professionals (n=5), inclusion of the family during the process of hospitalization (n=2) and redesigning the waiting room (n=2) are some of the suggestions for improvement. CONCLUSIONS: Factors related to professionals, environment and cleanliness of the units are satisfaction-generating factors. Factors generating dissatisfaction related to poor infrastructure, a lack of involvement in decision-making and poor professional communication. Strategies to improve patient and family satisfaction relate to the organization, professionals, family members, and infrastructure and environment.

Introduction: Effective information management in the emergency department (ED) can improve the control and management of ED processes. Dashboards, known as data management tools, efficiently provide information and contribute greatly to control and management of ED. This study aimed to identify performance indicators quality dashboard functionalities, and analyze the challenges associated with dashboard implementation in the ED. Methods: This systematic review began with a search in four databases (Web of Science, PubMed, Embase, and Scopus) from 2000 to May 30, 2020, when the final search for papers was conducted. The data were collected using a data extraction form and the contents of the extracted papers were analyzed through ED performance indicators, dashboard functionalities, and implementation challenges. Results: Performance indicators reported in the reviewed papers were classified as the quality of care, patient flow, timeliness, costs, and resources. The main dashboard functionalities noted in the papers included reporting, customization, alert creation, resource management, and real-time information display. The dashboard implementation challenges included data sources, data quality, integration with other systems, adaptability of dashboard functionalities to user needs, and selection of appropriate performance indicators. Conclusions: Quality dashboards facilitate processes, communication, and situation awareness in the ED; hence, they can improve care provision in this department. To enhance the effectiveness and efficiency of ED dashboards, officials should set performance indicators and consider the conformity of dashboard functionalities with user needs. They should also integrate dashboards with other relevant systems at the departmental and hospital levels.

CONTEXT: Alternative pain management interventions involving caregivers may be valuable adjuncts to conventional pain management interventions. OBJECTIVES: Use systematic review methodology to examine caregiver-facilitated pain management interventions in a hospital setting and whether they improve patient, caregiver, provider, or health system outcomes. METHODS: We searched MEDLINE, EMBASE, PsycINFO, CINAHL, and Scopus databases from inception to April 2020. Original research on caregiver-facilitated pain management interventions in hospitalized settings (i.e., any age) were included and categorized into three caregiver engagement strategies: inform (e.g., pain education), activate (e.g., prompt caregiver action), and collaborate (encourage caregiver's interaction with providers). RESULTS: Of 61 included studies, most investigated premature (n = 27 of 61; 44.3%) and full-term neonates (n = 19 of 61; 31.1%). Interventions were classified as activate (n = 46 of 61; 75.4%), inform-activate-collaborate (n = 6 of 61; 9.8%), inform-activate (n = 5 of 61; 8.2%), activate-collaborate (n = 3 of 61; 4.9%), or inform (n = 1 of 61; 1.6%) caregiver engagement strategies. Interventions that included an activate engagement strategy improved pain outcomes in adults (18-64 years) (e.g., self-reported pain, n = 4 of 5; 80%) and neonates (e.g., crying, n = 32 of 41; 73.0%) but not children or older adults (65 years and older). Caregiver outcomes (e.g., pain knowledge) were improved by inform-activate engagement strategies (n = 3 of 3). Interventions did not improve provider (e.g., satisfaction) or health system (e.g., hospital length of stay) outcomes. Most studies were of low (n = 36 of 61; 59.0%) risk of bias. CONCLUSION: Caregiver-facilitated pain management interventions using an activate engagement strategy may be effective in reducing pain of hospitalized neonates. Caregiver-facilitated pain management interventions improved pain outcomes in most adult studies; however, the number of studies of adults is small warranting caution pending further studies.

Environmental health services (EHS) in healthcare facilities (HCFs) are critical for safe care provision, yet their availability in low- and middle-income countries is low. A poor understanding of costs hinders progress towards adequate provision. Methods are inconsistent and poorly documented in costing literature, suggesting opportunities to improve evidence. The goal of this research was to develop a model to guide budgeting for EHS in HCFs. Based on 47 studies selected through a systematic review, we identified discrete budgeting steps, developed codes to define each step, and ordered steps into a model. We identified good practices based on a review of additional selected guidelines for costing EHS and HCFs. Our model comprises ten steps in three phases: planning, data collection, and synthesis. Costing-stakeholders define the costing purpose, relevant EHS, and cost scope; assess the EHS delivery context; develop a costing plan; and identify data sources (planning). Stakeholders then execute their costing plan and evaluate the data quality (data collection). Finally, stakeholders calculate costs and disseminate findings (synthesis). We present three hypothetical costing examples and discuss good practices, including using costing frameworks, selecting appropriate indicators to measure the quantity and quality of EHS, and iterating planning and data collection to select appropriate costing approaches and identify data gaps.

BACKGROUND: There has been a growing interest in using diagnosis-related groups (DRGs) payment to reimburse inpatient care worldwide. But its effects on healthcare and health outcomes are controversial, and the evidence from low- and middle- income countries (LMICs) is especially scarce. The objective of this study is to evaluate the effects of DRGs payment on healthcare and health outcomes in China. METHOD: A systematic review was conducted. We searched literature databases of PubMed, Cochrane Library, EMBASE, Web of Science, Chinese National Knowledge Infrastructure and SinoMed for empirical studies examining the effects of DRGs payment on healthcare in mainland China. We performed a narrative synthesis of outcomes regarding expenditure, efficiency, quality and equity of healthcare, and assessed the quality of evidence. RESULTS: Twenty-three publications representing thirteen DRGs payment studies were included, including six controlled before after studies, two interrupted time series studies and five uncontrolled before-after studies. All studies compared DRGs payment to fee-for-service, with or without an overall budget, in settings of tertiary (7), secondary (7) and primary care (1). The involved participants varied from specific groups to all inpatients. DRGs payment mildly reduced the length of stay. Impairment of equity of healthcare was consistently reported, especially for patients exempted from DRGs payment, including: patient selection, cost-shifting and inferior quality of healthcare. However, findings on total expenditure, out of pocket payment (OOP) and quality of healthcare were inconsistent. The quality of the evidence was generally low or very low due to the study design and potential risk of bias of included studies. CONCLUSION: DRGs payment may mildly improve the efficiency but impair the equity and quality of healthcare, especially for patients exempted from this payment scheme, and may cause up-coding of medical records. However, DRGs payment may or may not contain the total expenditure or OOP, depending on the components design of the payment. Policymakers should very carefully consider each component of DRGs payment design against policy goals. Well-designed randomised trials or comparative studies are warranted to consolidate the evidence of the effects of DRGs payment on healthcare and health outcomes in LMICs to inform policymaking.