Measuring quality in maternal-newborn care: developing a clinical dashboard

Developing public health surveillance dashboards: a scoping review on the design principles

BACKGROUND

Public Health Dashboards (PHDs) facilitate the monitoring and prediction of disease outbreaks by continuously monitoring the health status of the community. This study aimed to identify design principles and determinants for developing public health surveillance dashboards.

METHODOLOGY

This scoping review is based on Arksey and O'Malley's framework as included in JBI guidance. Four databases were used to review and present the proposed principles of designing PHDs: IEEE, PubMed, Web of Science, and Scopus. We considered articles published between January 1, 2010 and November 30, 2022. The final search of articles was done on November 30, 2022. Only articles in the English language were included. Qualitative synthesis and trend analysis were conducted.

RESULTS

Findings from sixty-seven articles out of 543 retrieved articles, which were eligible for analysis, indicate that most of the dashboards designed from 2020 onwards were at the national level for managing and monitoring COVID-19. Design principles for the public health dashboard were presented in five groups, i.e., considering aim and target users, appropriate content, interface, data analysis and presentation types, and infrastructure.

CONCLUSION

Effective and efficient use of dashboards in public health surveillance requires implementing design principles to improve the functionality of these systems in monitoring and decision-making. Considering user requirements, developing a robust infrastructure for improving data accessibility, developing, and applying Key Performance Indicators (KPIs) for data processing and reporting purposes, and designing interactive and intuitive interfaces are key for successful design and development.

Planning and implementing practice changes in Ontario maternal-newborn hospital units: a secondary qualitative analysis

BACKGROUND

Moving evidence into practice is complex, and pregnant and birthing people and their infants do not always receive care that aligns with the best available evidence. Implementation science can inform how to effectively move evidence into practice. While there are a growing number of examples of implementation science being studied in maternal-newborn care settings, it remains unknown how real-world teams of healthcare providers and leaders approach the overall implementation process when making practice changes. The purpose of this study was to describe maternal-newborn hospital teams' approaches to implementing practice changes. We aimed to identify what implementation steps teams take (or not) and identify strengths and potential areas for improvement based on best practices in implementation science.

METHODS

We conducted a supplementary qualitative secondary analysis of 22 interviews completed in 2014-2015 with maternal-newborn nursing leaders in Ontario, Canada. We used directed content analysis to code the data to seven steps in an implementation framework (Implementation Roadmap): identify the problem and potential best practice; assemble local evidence; select and customize best practice; discover barriers and drivers; tailor implementation strategies; field-test, plan evaluation, prepare to launch; launch, evaluate, and sustain. Frequency counts are presented for each step.

RESULTS

Participants reported completing a median of 4.5 of 7 Implementation Roadmap steps (range = 3-7), with the most common being identifying a practice problem. Other steps were described less frequently (e.g., selecting and adapting evidence, field-testing, outcome evaluation) or discussed frequently but not optimally (e.g., barriers assessment). Participants provided examples of how they engaged point-of-care staff throughout the implementation process, but provided fewer examples of engaging pregnant and birthing people and their families. Some participants stated they used a formal framework or process to guide their implementation process, with the most common being quality improvement approaches and tools.

CONCLUSIONS

We identified variability across the 22 hospitals in the implementation steps taken. While we observed many strengths, we also identified areas where further support may be needed. Future work is needed to create opportunities and resources to support maternal-newborn healthcare providers and leaders to apply principles and tools from implementation science to their practice change initiatives.

Clinical index to quantify the 1-year risk for common postpartum mental disorders at the time of delivery (PMH CAREPLAN): development and internal validation

BACKGROUND

Common postpartum mental health (PMH) disorders such as depression and anxiety are preventable, but determining individual-level risk is difficult.

AIMS

To create and internally validate a clinical risk index for common PMH disorders.

METHOD

Using population-based health administrative data in Ontario, Canada, comprising sociodemographic, clinical and health service variables easily collectible from hospital birth records, we developed and internally validated a predictive model for common PMH disorders and converted the final model into a risk index. We developed the model in 75% of the cohort (n = 152 362), validating it in the remaining 25% (n = 75 772).

RESULTS

The 1-year prevalence of common PMH disorders was 6.0%. Independently associated variables (forming the mnemonic PMH CAREPLAN) that made up the risk index were: (P) prenatal care provider; (M) mental health diagnosis history and medications during pregnancy; (H) psychiatric hospital admissions or emergency department visits; (C) conception type and complications; (A) apprehension of newborn by child services (newborn taken into care); (R) region of maternal origin; (E) extremes of gestational age at birth; (P) primary maternal language; (L) lactation intention; (A) maternal age; (N) number of prenatal visits. In the index (scored 0-39), 1-year common PMH disorder risk ranged from 1.5 to 40.5%. Discrimination (C-statistic) was 0.69 in development and validation samples; the 95% confidence interval of expected risk encompassed observed risk for all scores in development and validation samples, indicating adequate risk index calibration.

CONCLUSIONS

Individual-level risk of developing a common postpartum mental health disorder can be estimated with data feasibly collectable from birth records. Next steps are external validation and evaluation of various cut-off scores for their utility in guiding postpartum individuals to interventions that reduce their risk of illness.

Development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard

Objective

To describe the development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard.

Materials and methods

Comparative study analyzing a manually extracted and an automatically extracted dataset with 262 patients treated for HNC cancer in a tertiary oncology center in the Netherlands in 2020. The primary outcome measures were the percentage of agreement on data elements required for calculating quality indicators and the difference between indicators results calculated using manually collected and indicators that used automatically extracted data.

Results

The results of this study demonstrate high agreement between manual and automatically collected variables, reaching up to 99.0% agreement. However, some variables demonstrate lower levels of agreement, with one variable showing only a 20.0% agreement rate. The indicator results obtained through manual collection and automatic extraction show high agreement in most cases, with discrepancy rates ranging from 0.3% to 3.5%. One indicator is identified as a negative outlier, with a discrepancy rate of nearly 25%.

Conclusions

This study shows that it is possible to use routinely collected structured data to reliably measure the quality of care in real-time, which could render manual data collection for quality measurement obsolete. To achieve reliable data reuse, it is important that relevant data is recorded as structured data during the care process. Furthermore, the results also imply that data validation is conditional to development of a reliable dashboard.

Requirements and challenges of hospital dashboards: a systematic literature review

Background

Today, the use of data in administrative and clinical processes is quite challenging due to the large volume of data, data collection from various sources, and lack of data structure. As a data management tool, dashboards play an important role in timely visual display of critical information on key performances.

Objectives

This systematic review aimed to identify functional and non-functional requirements, as well as challenges of using dashboards in hospitals.

Methods

In this systematic review, four databases, including the Web of Science, PubMed, EMBASE, and Scopus, were searched to find relevant articles from 2000 until May 30, 2020. The final search was conducted on May 30, 2020. Data collection was performed using a data extraction form and reviewing the content of relevant studies on the potentials and challenges of dashboard implementation.

Results

Fifty-four out of 1254 retrieved articles were selected for this study based on the inclusion and exclusion criteria. The functional requirements for dashboards included reporting, reminders, customization, tracking, alert creation, and assessment of performance indicators. On the other hand, the non-functional requirements included the dashboard speed, security, ease of use, installation on different devices (e.g., PCs and laptops), integration with other systems, web-based design, inclusion of a data warehouse, being up-to-data, and use of data visualization elements based on the user’s needs. Moreover, the identified challenges were categorized into four groups: data sources, dashboard content, dashboard design, implementation, and integration in other systems at the hospital level.

Conclusion

Dashboards, by providing information in an appropriate manner, can lead to the proper use of information by users. In order for a dashboard to be effective in clinical and managerial processes, particular attention must be paid to its capabilities, and the challenges of its implementation need to be addressed.

Applicability of care quality indicators for women with low-risk pregnancies planning hospital birth: a retrospective study of medical records

Practices for planned birth among women with low-risk pregnancies vary by birth setting, medical professional, and organizational system. Appropriate monitoring is essential for quality improvement. Although sets of quality indicators have been developed, their applicability has not been tested. To improve the quality of childbirth care for low-risk mothers and infants in Japanese hospitals, we developed 35 quality indicators using existing clinical guidelines and quality indicators. We retrospectively analysed data for 347 women in Japan diagnosed with low-risk pregnancy in the second trimester, admitted between April 2015 and March 2016. We obtained scores for 35 quality indicators and evaluated their applicability, i.e., feasibility, improvement potential, and reliability (intra- and inter-rater reliability: kappa score, positive and negative agreement). The range of adherence to each indicator was 0-95.7%. We identified feasibility concerns for six indicators with over 25% missing data. Two indicators with over 90% adherence showed limited potential for improvement. Three indicators had poor kappa scores for intra-rater reliability, with positive/negative agreement scores 0.94/0.33, 0.33/0.95, and 0.00/0.97, respectively. Two indicators had poor kappa scores for inter-rater reliability, with positive/negative agreement scores 0.25/0.92 and 0.68/0.61, respectively. The findings indicated that these 35 care quality indicators for low-risk pregnant women may be applicable to real-world practice, with some caveats.

General methods for measuring and comparing medical interventions in childbirth: a framework

Background

The continue increase of interventions during labour in low risk population is a controversial issue of the current obstetric literature, given the lack of evidence demonstrating the benefits of unnecessary interventions for women or infants’ health. This makes it important to have approaches to assess the burden of all medical interventions performed.

Methods

Exploiting the nature of childbirth intervention as a staged process, we proposed graphic representations allowing to generate alternative formulas for the simplest measures of the intervention intensity namely, the overall and type-specific treatment ratios. We applied the approach to quantify the change in interventions following a protocol termed Comprehensive Management (CM), using data from Robson classification, collected in a prospective longitudinal cohort study carried out at the Obstetric Unit of the Cà Granda Niguarda Hospital in Milan, Italy.

Results

Following CM a substantial reduction was observed in the Overall Treatment Ratio, as well as in the ratios for augmentation (amniotomy and synthetic oxytocin use) and for caesarean section ratio, without any increase in neonatal and maternal adverse outcomes. The key component of this reduction was the dramatic decline in the proportion of women progressing to augmentation, which resulted not only the most practiced intervention, but also the main door towards further treatments.

Conclusions

The proposed framework, once combined with Robson Classification, provides useful tools to make medical interventions performed during childbirth quantitatively measurable and comparable. The framework allowed to identifying the key components of interventions reduction following CM. In its turn, CM proved useful to reduce the number of medical interventions carried out during childbirth, without worsening neonatal and maternal outcomes.

Obstetrical safety indicators for preventing hospital harms in low risk births: a scoping review protocol

INTRODUCTION

Optimising the safety of obstetric patient care is a primary concern for many hospitals. Performance indicators measuring aspects of patient care processes can lead to improvements in health systems and the prevention of harm to the patient. We present our protocol for a scoping review to identify indicators for obstetric safety in low risk births. We aim to identify indicators addressing preventable hospital harms, to summarise the data and synthesise results.

METHODS AND ANALYSIS

We will use methods described by Arksey and O'Malley and further expanded by Levac et al. We will search electronic databases such as Medline, Embase, CINAHL and the Cochrane Library, and websites from professional bodies and other organisations, using an iterative search strategy.Two reviewers will independently screen titles and abstracts of search results to determine eligibility for inclusion. If eligibility is not clear, the reviewers will screen the full text version. If reviewers' decisions regarding eligibility differ, a third reviewer will review the record. Two reviewers will independently extract data from records that meet our inclusion criteria using a standardised data collection form. We will narratively describe quantitative data, such as the frequency with which indicators are identified, and conduct a thematic analysis of the qualitative data. We will compile a comprehensive list of patient safety indicators and organise them according to concepts that best suit the data such as the Donabedian model or the Hospital Harm Framework. We will discuss the implications for future research, clinical practice and policy-making. We will report the conduct of the review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews checklist.

ETHICS AND DISSEMINATION

The sources of information included in this scoping review will be available to the public. Therefore, ethics approval is not warranted. We will disseminate results in a peer-reviewed publication, conference/event presentation(s) and stakeholder communications.

Data accuracy in the Ontario birth Registry: a chart re-abstraction study

Background

Ontario’s birth Registry (BORN) was established in 2009 to collect, interpret, and share critical data about pregnancy, birth and the early childhood period to facilitate and improve the provision of healthcare. Since the use of routinely-collected health data has been prioritized internationally by governments and funding agencies to improve patient care, support health system planning, and facilitate epidemiological surveillance and research, high quality data is essential. The purpose of this study was to verify the accuracy of a selection of data elements that are entered in the Registry.

Methods

Data quality was assessed by comparing data re-abstracted from patient records to data entered into the Ontario birth Registry. A purposive sample of 10 hospitals representative of hospitals in Ontario based on level of care, birth volume and geography was selected and a random sample of 100 linked mother and newborn charts were audited for each site. Data for 29 data elements were compared to the corresponding data entered in the Ontario birth Registry using percent agreement, kappa statistics for categorical data elements and intra-class correlation coefficients (ICCs) for continuous data elements.

Results

Agreement ranged from 56.9 to 99.8%, but 76% of the data elements (22 of 29) had greater than 90% agreement. There was almost perfect (kappa 0.81–0.99) or substantial (kappa 0.61–0.80) agreement for 12 of the categorical elements. Six elements showed fair-to-moderate agreement (kappa <0.60). We found moderate-to-excellent agreement for four continuous data elements (ICC >0.50).

Conclusion

Overall, the data elements we evaluated in the birth Registry were found to have good agreement with data from the patients’ charts. Data elements that showed moderate kappa or low ICC require further investigation.

A dashboard-based system for supporting diabetes care

Objective

To describe the development, as part of the European Union MOSAIC (Models and Simulation Techniques for Discovering Diabetes Influence Factors) project, of a dashboard-based system for the management of type 2 diabetes and assess its impact on clinical practice.

Methods

The MOSAIC dashboard system is based on predictive modeling, longitudinal data analytics, and the reuse and integration of data from hospitals and public health repositories. Data are merged into an i2b2 data warehouse, which feeds a set of advanced temporal analytic models, including temporal abstractions, care-flow mining, drug exposure pattern detection, and risk-prediction models for type 2 diabetes complications. The dashboard has 2 components, designed for (1) clinical decision support during follow-up consultations and (2) outcome assessment on populations of interest. To assess the impact of the clinical decision support component, a pre-post study was conducted considering visit duration, number of screening examinations, and lifestyle interventions. A pilot sample of 700 Italian patients was investigated. Judgments on the outcome assessment component were obtained via focus groups with clinicians and health care managers.

Results

The use of the decision support component in clinical activities produced a reduction in visit duration (P ≪ .01) and an increase in the number of screening exams for complications (P < .01). We also observed a relevant, although nonstatistically significant, increase in the proportion of patients receiving lifestyle interventions (from 69% to 77%). Regarding the outcome assessment component, focus groups highlighted the system's capability of identifying and understanding the characteristics of patient subgroups treated at the center.

Conclusion

Our study demonstrates that decision support tools based on the integration of multiple-source data and visual and predictive analytics do improve the management of a chronic disease such as type 2 diabetes by enacting a successful implementation of the learning health care system cycle.

Admission hypothermia, neonatal morbidity, and mortality: evaluation of a multicenter cohort of very low birth weight preterm infants according to relative performance of the center

This prospective cohort study aimed to assess the association of admission hypothermia (AH) with death and/or major neonatal morbidities among very low birth weight (VLBW) preterm infants based on the relative performance of 20 centers of the Brazilian Network of Neonatal Research. This is a retrospective analysis of prospectively collected data using the database registry of the Brazilian Network on Neonatal Research. Center performance was defined by the relative mortality rate using conditional inference trees. A total of 4356 inborn singleton VLBW preterm infants born between January 2013 and December 2016 without malformations were included in this study. The centers were divided into two groups: G1 (with lower mortality rate) and G2 (with higher mortality rate). Crude and adjusted relative risks (RR) and 95% confidence intervals (95%CI) were estimated by simple and multiple log-binomial regression models. An AH rate of 53.7% (19.8-93.3%) was significantly associated with early neonatal death in G1 (adjusted RR 1.41, 95% CI 1.09-1.84) and G2 (adjusted RR 1.29, 95%CI 1.01-1.65) and with in-hospital death in G1 (adjusted RR 1.29, 95%CI 1.07-1.58). AH was significantly associated with a lower frequency of necrotizing enterocolitis (adjusted RR 0.58, 95%CI 38-0.88) in G2.Conclusion: AH significantly associated with early neonatal death regardless of the hospital performance. In G2, an unexpected protective association between AH and necrotizing enterocolitis was found, whereas the other morbidities assessed were not significantly associated with AH. What is Known: • Admission hypothermia is associated with early neonatal death. • The association of admission hypothermia with major neonatal morbidities has not been fully established. What is New: • Admission hypothermia was significantly associated with early neonatal and in-hospital death in centers with the lowest relative mortality rates. • Admission hypothermia was not associated with major neonatal morbidities and with in-hospital death but was found to be a protective factor against necrotizing colitis in centers with the highest relative mortality rates.

Development and Implementation of Maternity Dashboard in Regional Hospital for Quality Improvement at Ground Level: A Pilot Study

Objectives

We sought to develop and implement a Maternity Dashboard to improve the quality of health care at the ground level.

Methods

We conducted a prospective, descriptive cross-sectional study, involving patients with high-risk pregnancies who had been referred to Nizwa Hospital, Oman. The selection of quality indicators was based on the prototype of clinical outcomes from the Royal College of Obstetricians and Gynecologists. The Maternity Dashboard team adapted local parameters and used preselected general parameters, based on clinical observations, to develop the dashboard.

Results

The issues posing a threat to Nizwa Hospital in becoming a world-class healthcare facility were: overbooked outpatient department, insufficient staff, and more junior doctors compared to senior doctors and consultants. Additionally, being pioneers, naturally, the dashboard development team faced difficulties while handling adverse situations. More time, guidance, and standardization of quality indicators are desirable.

Conclusions

Following the approval for a Maternity Dashboard in Nizwa Hospital, the data compiled in an Excel sheet are transmitted manually every month for display on the dashboard in the delivery suite. It is intended to make data collected and dissemination completely automated in the future with the help of the Al-Shifa Healthcare Information System. Expansion of the idea of a Maternity Dashboard to other hospitals and specialties at the regional and tertiary level of the health care system in Oman and a comparison of the standard of health care provided between hospitals based on similar quality indicators would be the next milestone.

Use of a maternal newborn audit and feedback system in Ontario: a collective case study

Background

As part of a larger study examining the effectiveness of the Maternal Newborn Dashboard, an electronic audit and feedback system to improve maternal-newborn care practices and outcomes, the purpose of this study was to increase our understanding of factors explaining variability in performance after implementation of the Dashboard in Ontario, Canada.

Methods

A collective case study. A maximum variation sampling approach was used to invite hospitals reflecting different criteria to participate in a 1-day to 2-day site visit by the research team. The visits included: (1) semistructured interviews and focus groups with healthcare providers, leaders and personnel involved in clinical change processes; (2) observations and document review. Interviews and focus groups were audio-recorded and transcribed verbatim. Qualitative content analysis was used to code and categorise the data.

Results

Between June and November 2016, we visited 14 maternal-newborn hospitals. Hospitals were grouped into four quadrants based on their key indicator performance and level of engagement with the Dashboard. Findings revealed four overarching themes that contribute to the varying success of sites in achieving practice change on the Dashboard key performance indicators, namely, interdisciplinary collaboration and accountability, application of formal change strategies, team trust and use of evidence and data, as well as alignment with organisational priorities and support.

Conclusion

The diversity of facilitators and barriers across the 14 hospitals highlights the need to go beyond a ‘one size fits all’ approach when implementing audit and feedback systems. Future work to identify tools to assess barriers to practice change and to evaluate the effects of cointerventions to optimise audit and feedback systems for clinical practice change is needed.

Effect of a population-level performance dashboard intervention on maternal-newborn outcomes: an interrupted time series study

OBJECTIVES

To assess the effect of the Maternal Newborn Dashboard on six key clinical performance indicators in the province of Ontario, Canada.

DESIGN

Interrupted time series using population-based data from the provincial birth registry covering a 3-year period before implementation of the Dashboard and 2.5 years after implementation (November 2009 through March 2015).

SETTING

All hospitals in the province of Ontario providing maternal-newborn care (n=94).

INTERVENTION

A hospital-based online audit and feedback programme.

MAIN OUTCOME MEASURES

Rates of the six performance indicators included in the Dashboard.

RESULTS

2.5 years after implementation, the audit and feedback programme was associated with statistically significant absolute decreases in the rates of episiotomy (decrease of 1.5 per 100 women, 95% CI 0.64 to 2.39), induction for postdates in women who were less than 41 weeks at delivery (decrease of 11.7 per 100 women, 95% CI 7.4 to 16.0), repeat caesarean delivery in low-risk women performed before 39 weeks (decrease of 10.4 per 100 women, 95% CI 9.3 to 11.5) and an absolute increase in the rate of appropriately timed group B streptococcus screening (increase of 2.8 per 100, 95% CI 2.2 to 3.5). The audit and feedback programme did not significantly affect the rates of unsatisfactory newborn screening blood samples or formula supplementation at discharge. No statistically significant effects were observed for the two internal control outcomes or the four external control indicators-in fact, two external control indicators (episiotomy and postdates induction) worsened relative to before implementation.

CONCLUSION

An electronic audit and feedback programme implemented in maternal-newborn hospitals was associated with clinically relevant practice improvements at the provincial level in the majority of targeted indicators.

A method to assess obstetric outcomes using the 10-Group Classification System: a quantitative descriptive study

OBJECTIVES

Internationally, the 10-Group Classification System (TGCS) has been used to report caesarean section rates, but analysis of other outcomes is also recommended. We now aim to present the TGCS as a method to assess outcomes of labour and delivery using routine collection of perinatal information.

DESIGN

This research is a methodological study to describe the use of the TGCS.

SETTING

Stavanger University Hospital (SUH), Norway, National Maternity Hospital Dublin, Ireland and Slovenian National Perinatal Database (SLO), Slovenia.

PARTICIPANTS

9848 women from SUH, Norway, 9250 women from National Maternity Hospital Dublin, Ireland and 106 167 women, from SLO, Slovenia.

MAIN OUTCOME MEASURES

All women were classified according to the TGCS within which caesarean section, oxytocin augmentation, epidural analgesia, operative vaginal deliveries, episiotomy, sphincter rupture, postpartum haemorrhage, blood transfusion, maternal age >35 years, body mass index >30, Apgar score, umbilical cord pH, hypoxic-ischaemic encephalopathy, antepartum and perinatal deaths were incorporated.

RESULTS

There were significant differences in the sizes of the groups of women and the incidences of events and outcomes within the TGCS between the three perinatal databases.

CONCLUSIONS

The TGCS is a standardised objective classification system where events and outcomes of labour and delivery can be incorporated. Obstetric core events and outcomes should be agreed and defined to set standards of care. This method provides continuous and available observations from delivery wards, possibly used for further interpretation, questions and international comparisons. The definition of quality may vary in different units and can only be ascertained when all the necessary information is available and considered together.

An environmental scan of quality indicators in critical care

BACKGROUND

We performed a directed environmental scan to identify and categorize quality indicators unique to critical care that are reported by key stakeholder organizations.

METHODS

We convened a panel of experts (n = 9) to identify key organizations that are focused on quality improvement or critical care, and reviewed their online publications and website content for quality indicators. We identified quality indicators specific to the care of critically ill adult patients and then categorized them according to the Donabedian and the Institute of Medicine frameworks. We also noted the organizations' rationale for selecting these indicators and their reported evidence base.

RESULTS

From 28 targeted organizations, we identified 222 quality indicators, 127 of which were unique. Of the 127 indicators, 63 (32.5%) were safety indicators and 61 (31.4%) were effectiveness indicators. The rationale for selecting quality indicators was supported by consensus for 58 (26.1%) of the 222 indicators and by published research evidence for 45 (20.3%); for 119 indicators (53.6%), the rationale was not reported or the reader was referred to other organizations' reports. Of the 127 unique quality indicators, 27 (21.2%) were accompanied by a formal grading of evidence, whereas for 52 (40.9%), no reference to evidence was provided.

INTERPRETATION

There are many quality indicators related to critical care that are available in the public domain. However, owing to a paucity of rationale for selection, supporting evidence and results of implementation, it is not clear which indicators should be adopted for use.

Hospital performance dashboards: a literature review

Purpose

The purpose of this paper is to give a comprehensive and updated analysis of the available literature on hospital dashboards.

Design/methodology/approach

A search of the current literature was performed by searching electronic databases, including Google Scholar, EBSCO and Medline, as well as books.

Findings

In all, 48 manuscripts consisting of peer reviewed articles, conference proceedings, case reports and text books were included in this review.

Practical implications

Despite the numerous advantages of performance dashboards, several authors have mentioned a number of challenges. It was evident from the literature that any setting requires significant effort, especially to ensure the quality of data being collected. In fact, significant investment, both in terms of financial and human resources, is required to achieve an effective dashboard. Furthermore, most of the studies available in the literature were individual case reports or anecdotal accounts rather than empirical studies. Thus, further research is required to ascertain the effectiveness of performance dashboards. In view of these findings, each organisation should make its own decisions whether or not to adopt performance dashboards.

Originality/value

Most of the literature is fragmented as it reports the use of different types of dashboards, namely strategic, tactical and operational, as separate tools. This literature review contributes to knowledge as it brings together the different types of dashboards and the cascading effect of one dashboard onto another in order to achieve and retain organisational alignment with the overall strategic goals.

Cochrane Rapid Reviews Methods Group to play a leading role in guiding the production of informed high-quality, timely research evidence syntheses

BACKGROUND

Policymakers and healthcare stakeholders are increasingly seeking evidence to inform the policymaking process, and often use existing or commissioned systematic reviews to inform decisions. However, the methodologies that make systematic reviews authoritative take time, typically 1 to 2 years to complete. Outside the traditional SR timeline, "rapid reviews" have emerged as an efficient tool to get evidence to decision-makers more quickly. However, the use of rapid reviews does present challenges. To date, there has been limited published empirical information about this approach to compiling evidence. Thus, it remains a poorly understood and ill-defined set of diverse methodologies with various labels. In recent years, the need to further explore rapid review methods, characteristics, and their use has been recognized by a growing network of healthcare researchers, policymakers, and organizations, several with ties to Cochrane, which is recognized as representing an international gold standard for high-quality, systematic reviews.

PURPOSE

In this commentary, we introduce the newly established Cochrane Rapid Reviews Methods Group developed to play a leading role in guiding the production of rapid reviews given they are increasingly employed as a research synthesis tool to support timely evidence-informed decision-making. We discuss how the group was formed and outline the group's structure and remit. We also discuss the need to establish a more robust evidence base for rapid reviews in the published literature, and the importance of promoting registration of rapid review protocols in an effort to promote efficiency and transparency in research.

CONCLUSION

As with standard systematic reviews, the core principles of evidence-based synthesis should apply to rapid reviews in order to minimize bias to the extent possible. The Cochrane Rapid Reviews Methods Group will serve to establish a network of rapid review stakeholders and provide a forum for discussion and training. By facilitating exchange, the group will strive to conduct research to advance the methods of rapid reviews.

A mixed methods evaluation of the maternal-newborn dashboard in Ontario: dashboard attributes, contextual factors, and facilitators and barriers to use: a study protocol

Background

There are wide variations in maternal-newborn care practices and outcomes across Ontario. To help institutions and care providers learn about their own performance, the Better Outcomes Registry & Network (BORN) Ontario has implemented an audit and feedback system, the Maternal-Newborn Dashboard (MND), for all hospitals providing maternal-newborn care. The dashboard provides (1) near real-time feedback, with site-specific and peer comparison data about six key performance indicators; (2) a visual display of evidence-practice gaps related to the indicators; and (3) benchmarks to provide direction for practice change. This study aims to evaluate the effects of the dashboard, dashboard attributes, contextual factors, and facilitation/support needs that influence the use of this audit and feedback system to improve performance. The objectives of this study are to (1) evaluate the effect of implementing the dashboard across Ontario; (2) explore factors that potentially explain differences in the use of the MND among hospitals; (3) measure factors potentially associated with differential effectiveness of the MND; and (4) identify factors that predict differences in hospital performance.

Methods/design

A mixed methods design includes (1) an interrupted time series analysis to evaluate the effect of the intervention on six indicators, (2) key informant interviews with a purposeful sample of directors/managers from up to 20 maternal-newborn care hospitals to explore factors that influence the use of the dashboard, (3) a provincial survey of obstetrical directors/managers from all maternal-newborn hospitals in the province to measure factors that influence the use of the dashboard, and (4) a multivariable generalized linear mixed effects regression analysis of the indicators at each hospital to quantitatively evaluate the change in practice following implementation of the dashboard and to identify factors most predictive of use.

Discussion

Study results will provide essential data to develop knowledge translation strategies for facilitating practice change, which can be further evaluated through a future cluster randomized trial.

A review of dashboards for data analytics in nursing

Dashboards are data-driven clinical decision support tools used to analyze data from multiple databases using easy-to-read, color-coded graphical displays, much like the dashboards of automobiles. Dashboards can be used to promote data-driven decision making and improve adherence to evidence-based practice guidelines. The purpose of this article was to provide a review of dashboards used to query electronic health records for the purpose of guiding clinical practice and research. An inductive content analysis approach was used to identify emerging themes directly from the literature. Five basic dashboard properties identified include the type of database integration, visual properties, purpose, time focus (ie, retrospective, real time, or predictive), and type of process monitored. These dashboard properties are determined by the characteristics of the specific organization, user, and purpose of data analysis. Using dashboards to perform automated analytical reviews of clinical data will prove more efficient when data elements stored in electronic health records become standardized. Other limitations of dashboard use include user anxiety, information overload, and technology overload. The increased use of electronic documentation in healthcare settings will provide a wealth of data, and dashboards will play a pivotal role in converting these data into actionable knowledge.

Design and evaluation of electronic briefs of neonatal intensive care unit in Taleghani hospital, Tabriz, Iran

More than 9 million neonatal deaths are reported through out the world each year happening in the early weeks of life most of which relate to developing countries. Thus it is very important to present a better way to keep the infants healthy which could be possible by accessing accurate information at any time required during hospitalization of infants. Therefore the required data should be collected, stored and analyzed before which is best possible by using computer. The main objective of this research is enabling researchers and clinicians quick access to the data of the babies admitted in NICU. This study involves the stage of developing a system design and its implementation following the evaluation of the electronic records which is done in a query form. By defining the neccessary terminology and designing a data model, the database and user interface are developed by using a programing language and data base tools. Finally, the system has been evaluated by user satisfaction showing to be about 85% As a result we suggest the hospitals take serious in buying the suitable technology for the NICU ward along with teaching the staffs how to work with it.

The use of a quality indicator to reduce elective repeat Caesarean section for low-risk women before 39 weeks' gestation: the Eastern Ontario experience

OBJECTIVE

Elective repeat Caesarean section (ERCS) for low-risk women at < 39 weeks' gestation has consistently been associated with increased risks to the neonate, including respiratory morbidity, NICU admission, and lengthier hospital stays than ERCS at 39 to 40 weeks' gestation. The objective of this quality improvement project was to reduce high rates of ERCS < 39 weeks across the Eastern Ontario region.

METHODS

All hospitals within the region providing care during labour and birth (n = 10) were asked to participate. Representatives from each hospital received information about their site-specific rates and knowledge-translation resources to assist them with the project. A benchmark rate for ERCS < 39 weeks was set at 30%. The rates of ERCS < 39 weeks were calculated for two different times (the 2009-2010 and 2010-2011 fiscal years) and the relative difference and 95% confidence intervals were calculated to quantify the magnitude and statistical significance of any change. Qualitative interviews were completed with key informants from each hospital.

RESULTS

The proportion of ERCS at < 39 weeks' gestation across the region in the fiscal year 2010-2011 (n = 197/497; 39.6%) was significantly decreased (relative difference: -21%; 95% CI -31% to -8%, P = 0.002) from the previous fiscal year 2009-2010 (n = 229/459; 49.9%). A number of barriers to, and facilitators of, practice change were identified.

CONCLUSION

A reduction in the rate of ERCS < 39 weeks among low-risk women was achieved across the region. Awareness of the issue, possession of site-specific data, and agreement about the evidence and the need for change are critical first steps to improving practice.