***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Background Multiorganisational quality improvement ( QI ) collaborative networks are promoted for improving quality within healthcare . Recently , several large-scale QI initiatives have been conducted in the intensive care unit ( ICU ) environment with successful quantitative results . However , the mechanisms through which such networks lead to QI success remain uncertain . We aim to underst and ICU staff perspectives on collaborative QI based on involvement in a multiorganisational improvement network and hypothesise about theoretical constructs that might explain the effect of collaboration in such networks . Methods Qualitative study using a modified grounded theory approach . Key informant interviews were conducted with staff from 12 community hospital ICUs that participated in a cluster r and omized control trial ( RCT ) of a QI intervention using a collaborative approach between 2006 and 2008 . Data analysis followed the st and ard procedure for grounded theory using constant comparative methodology . Results The collaborative network was perceived to promote increased intrateam cooperation over interorganisational cooperation , but friendly competition with other ICUs appeared to be a prominent driver of behaviour change . Bedsides , clinicians reported that belonging to a collaborative network provided recognition for the high- quality patient care that they already provided . However , the existing communication structure was perceived to be ineffective for staff engagement since it was based on a hierarchical approach to knowledge transfer and project awareness . Conclusions QI collaborative networks may promote behaviour change by improving intrateam communication , fostering competition with other institutions , and increasing recognition for providing high- quality care . Other commonly held assumptions about their potential impact , for instance , increasing interorganisational legitimisation , communication and collaboration , may be less important BACKGROUND The adherence to evidence -based treatment guidelines for acute myocardial infa rct ion ( AMI ) is still suboptimal . Therefore , we design ed a study to evaluate the effects of a collaborative quality improvement ( QI ) intervention on the adherence to AMI guidelines . The intervention used a national web-based quality registry to generate local and regular real-time performance feedback . METHODS A 12-month baseline measurement of the adherence rates was retrospectively collected , comprising the period July 1 , 2001 , through June 30 , 2002 . During the intervention period of November 1 , 2002 , through April 30 , 2003 , multidisciplinary teams from 19 nonr and omized intervention hospitals were subjected to a multifaceted QI-oriented intervention .  Another 19 hospitals , unaware of their status as controls , were matched to the intervention hospitals . During the postintervention measurement period of May 1 , 2003 , through April 30 , 2004 , a total of 6726 consecutive patients were included at the intervention ( n = 3786 ) and control ( n = 2940 ) hospitals . The outcome measures comprised 5 Swedish national guideline -derived quality indicators , compared between baseline and postintervention levels in the control and QUICC intervention hospitals . RESULTS In the control and QI intervention hospitals , the mean absolute increase of patients receiving angiotensin-converting enzyme inhibitors was 1.4 % vs 12.6 % ( P = .002 ) , lipid-lowering therapy 2.3 % vs 7.2 % ( P = .065 ) , clopidogrel 26.3 % vs 41.2 % ( P = .010 ) , heparin/low-molecular weight heparin 5.3 % vs 16.3 % ( P = .010 ) , and coronary angiography 6.2 % vs 16.8 % ( P = .027 ) , respectively . The number of QI intervention hospitals reaching a treatment level of at least 70 % in 4 or 5 of the 5 indicators was 15 and 5 , respectively . In the control group , no hospital reached 70 % or more in just 4 of the 5 indicators . CONCLUSIONS By combining a systematic and multidisciplinary QI collaborative with a web-based national quality registry with functionality allowing real-time performance feedback , major improvements in the adherence to national AMI guidelines can be achieved Background Quality improvement collaboratives ( QIC ) have proliferated internationally , but there is little empirical evidence for their effectiveness . Method We search ed Medline , Embase , CINAHL , PsycINFO and the Cochrane Library data bases from January 1995 to December 2014 . Studies were included if they met the criteria for a QIC intervention and the Cochrane Effective Practice and Organisation of Care ( EPOC ) minimum study design characteristics for inclusion in a review . We assessed study bias using the EPOC checklist and the quality of the reported intervention using a subset of SQUIRE 1.0 st and ards . Results Of the 220 studies meeting QIC criteria , 64 met EPOC study design st and ards for inclusion . There were 10 cluster r and omised controlled trials , 24 controlled before-after studies and 30 interrupted time series studies . QICs encompassed a broad range of clinical setting s , topics and population s ranging from neonates to the elderly . Few reports fully described  QIC implementation and methods , intensity of activities , degree of site engagement and important context ual factors . By care setting , an improvement was reported for one or more of the study ’s primary effect measures in 83 % of the studies ( 32/39 ( 82 % ) hospital based , 17/20 ( 85 % ) ambulatory care , 3/4 nursing home and a sole ambulance QIC ) . Eight studies described persistence of the intervention effect 6 months to 2 years after the end of the collaborative . Collaboratives reporting success generally addressed relatively straightforward aspects of care , had a strong evidence base and noted a clear evidence - practice gap in an accepted clinical pathway or guideline . Conclusions QICs have been adopted widely as an approach to shared learning and improvement in healthcare . Overall , the QICs included in this review reported significant improvements in targeted clinical processes and patient outcomes . These reports are encouraging , but most be interpreted cautiously since fewer than a third met established quality and reporting criteria , and publication bias is likely Background : Continuous Quality Improvement ( CQI ) is a process where health teams systematic ally collect and regularly reflect on local data to inform decisions and modify local practice s and so improve delivery of services . We implemented a cluster r and omized trial to examine the effects of CQI interventions on Prevention of Mother-to-Child Transmission ( PMTCT ) services . Here , we report our experiences and challenges establishing CQI in 2 high HIV prevalence states in northern Nigeria . Methods : Facility-based teams were trained to implement CQI activities , including structured assessment s , developing change packages , and participation in periodic collaborative learning sessions . Locally evolved solutions ( change ideas ) were tested and measured using process data and intermediate process indicators were agreed including overall time spent accessing services , client satisfaction , and quality of data . Results : Health workers actively participated in clinic activities and in the collaborative learning sessions . During the study , the mean difference in time spent accessing services during clinic visits increased by 40 minutes ( SD = 93.4 ) in the control arm and decreased by 44 minutes ( SD = 73.7 ) in the intervention arm . No significant difference was recorded in the mean client satisfaction assessment score by study arm . The quality of data was assessed using a st and ardized tool scored out of 100 ; compared with baseline data , quality at the end of study had improved at intervention sites by 6 points ( 95 % CI : 2.0 to 10.1 ) . Conclusions : Health workers were receptive to CQI process . A compendium of “ change ideas ” compiled into a single change package can be used to improve health care delivery Background Maternal , perinatal and neonatal mortality remains high in low-income countries . We evaluated community and facility-based interventions to reduce deaths in three districts of Malawi . Methods We evaluated a rural participatory women ’s group community intervention ( CI ) and a quality improvement intervention at health centres ( FI ) via a two-by-two factorial cluster r and omized controlled trial . Consenting pregnant women were followed-up to 2 months after birth using key informants . Primary outcomes were maternal , perinatal and neonatal mortality . Clusters were health centre catchment areas assigned using stratified computer-generated r and omization . Following exclusions , including non-birthing facilities , 61 clusters were analysed : control ( 17 clusters , 4912 births ) , FI ( 15 , 5335 ) , CI ( 15 , 5080 ) and FI + CI ( 14 , 5249 ) . This trial was registered as International St and ard R and omised Controlled Trial [ IS RCT N18073903 ] . Outcomes for 14 576 and 20 576 births were recorded during baseline ( June 2007–September 2008 ) and intervention ( October 2008–December 2010 ) periods . Results For control , FI , CI and FI + CI clusters neonatal mortality rates were 34.0 , 28.3 , 29.9 and 27.0 neonatal deaths per 1000 live births and perinatal mortality rates were 56.2 , 55.1 , 48.0 and 48.4 per 1000 births , during the intervention period . Adjusting for clustering and stratification , the neonatal mortality rate was 22 % lower in FI + CI than control clusters ( OR = 0.78 , 95 % CI 0.60–1.01 ) , and the perinatal mortality rate was 16 % lower in CI clusters ( OR = 0.84 , 95 % CI 0.72–0.97 ) . We did not observe any intervention effects on maternal mortality . Conclusions Despite implementation problems , a combined community and facility approach using participatory women ’s groups and quality improvement at health centres reduced newborn mortality in rural Malawi Background The Medical Research Councils ’ framework for complex interventions has been criticized for not including theory-driven approaches to evaluation . Although the framework does include broad guidance on the use of theory , it contains little practical guidance for implementers and there have been calls to develop a more comprehensive approach . A prospect i ve , theory-driven process of intervention design and evaluation is required to develop complex healthcare interventions which are more likely to be effective , sustainable and scalable . Methods We propose a theory-driven approach to the design and evaluation of complex interventions by adapting and integrating a programmatic design and evaluation tool , Theory of Change ( ToC ) , into the MRC framework for complex interventions . We provide a guide to what ToC is , how to construct one , and how to integrate its use into research projects seeking to design , implement and evaluate complex interventions using the MRC framework . We test this approach by using ToC within two r and omized controlled trials and one non-r and omized evaluation of complex interventions . Results Our application of ToC in three research projects has shown that ToC can strengthen key stages of the MRC framework . It can aid the development of interventions by providing a framework for enhanced stakeholder engagement and by explicitly design ing an intervention that is embedded in the local context . For the feasibility and piloting stage , ToC enables the systematic identification of knowledge gaps to generate research questions that strengthen intervention design . ToC may improve the evaluation of interventions by providing a comprehensive set of indicators to evaluate all stages of the causal pathway through which an intervention achieves impact , combining evaluations of intervention effectiveness with detailed process evaluations into one theoretical framework . Conclusions Incorporating a ToC approach into the MRC framework holds promise for improving the design and evaluation of complex interventions , thereby increasing the likelihood that the intervention will be ultimately effective , sustainable and scalable . We urge research ers developing and evaluating complex interventions to consider using this approach , to evaluate its usefulness and to build an evidence base to further refine the methodology .Trial registration Clinical trials.gov : Deficiencies in the quality and safety of health care remain a significant concern in the United States and abroad as evidence documenting gaps between actual and recommended clinical practice s continues to accumulate ( 1 , 2 ) . The significance of the well-recognized health care quality chasm has been acknowledged by a broad array of stakeholders , who have responded with efforts to identify , underst and , and correct specific shortcomings in health care delivery . The quality improvement collaborative ( QIC ) examined by L and on and colleagues in this issue ( 3 ) is arguably the health care delivery industry 's most important response to quality and safety gaps ; it represents substantial investments of time , effort , and funding . Largely developed and popularized by the Boston-based Institute for Healthcare Improvement ( IHI ) and best exemplified by IHI 's Breakthrough Series collaborative program , the QIC method has been adopted on a large scale by the U.S. Health Re sources and Services Administration ( HRSA ) ( 4 ) and the United Kingdom 's National Health Service ( NHS ) ( 5 ) . The Veterans Health Administration ( 6 ) and numerous smaller health care systems and individual hospitals and clinics worldwide have adopted the method on a smaller scale ( 7 ) . The QIC method brings together a group of participating ( collaborating ) health care delivery organizations ( typically between 20 and 40 ) and guides them in study ing a specific health care quality problem , design ing and implementing specific solutions , evaluating and refining these solutions , and disseminating findings to other organizations . Each participating organization is represented by a 3- or 4-person team ; all teams meet together with a small faculty of experts in a series of 2 or 3 multiday collaborative learning session meetings , which take place over several months . During the meetings , the team members learn improvement techniques , exchange insights and advice , and generate enthusiasm and a shared sense of commitment to achieving common improvement goals and outcomes . Teams return to their organizations between learning sessions to apply their new knowledge and ideas in a Pl anD o Study Act framework ( 8) . They conduct repeated cycles of quality problem diagnosis , development and implementation of small-scale improvement efforts , assessment of effects , and refinement and expansion of effective actions until desired outcomes are achieved . The QIC method is described in detail elsewhere ( 7 
    Output:
    
Adequacy and appropriateness of external support , functionality of quality improvement teams , leadership characteristics and alignment with national systems and priorities may influence outcomes of quality improvement collaboratives , but the strength and quality of the evidence is weak .
Participation in quality improvement collaborative activities may improve health professionals ’ knowledge , problem-solving skills and attitude ; teamwork ; shared leadership and habits for improvement .
Interaction across quality improvement teams may generate normative pressure and opportunities for capacity building and peer recognition .