Quantification and visualisation methods of data-driven chronic care delivery pathways: protocol for a systematic review and content analysis

IntroductionChronic conditions require long periods of care and often involve repeated interactions with multiple healthcare providers. Faced with increasing illness burden and costs, healthcare systems are currently working towards integrated care to streamline these interactions and improve efficiency. To support this, one promising resource is the information on routine care delivery stored in various electronic healthcare databases (EHD). In chronic conditions, care delivery pathways (CDPs) can be constructed by linking multiple data sources and extracting time-stamped healthcare utilisation events and other medical data related to individual or groups of patients over specific time periods; CDPs may provide insights into current practice and ways of improving it. Several methods have been proposed in recent years to quantify and visualise CDPs. We present the protocol for a systematic review aiming to describe the content and development of CDP methods, to derive common recommendations for CDP construction.Methods and analysisThis protocol followed the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols. A literature search will be performed in PubMed (MEDLINE), Scopus, IEEE, CINAHL and EMBASE, without date restrictions, to review published papers reporting data-driven chronic CDPs quantification and visualisation methods. We will describe them using several characteristics relevant for EHD use in long-term care, grouped into three domains: (1) clinical (what clinical information does the method use and how was it considered relevant?), (2) data science (what are the method’s development and implementation characteristics?) and (3) behavioural (which behaviours and interactions does the method aim to promote among users and how?). Data extraction will be performed via deductive content analysis using previously defined characteristics and accompanied by an inductive analysis to identify and code additional relevant features. Results will be presented in descriptive format and used to compare current CDPs and generate recommendations for future CDP development initiatives.Ethics and disseminationDatabase searches will be initiated in May 2019. The review is expected to be completed by February 2020. Ethical approval is not required for this review. Results will be disseminated in peer-reviewed journals and conference presentations.PROSPERO registration numberCRD42019140494.

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Data-driven chronic care delivery pathways visualization Methods: protocol for a systematic review

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.029 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

L Siqueira do Prado ◽

S Allemann ◽

M Viprey ◽

A-M Schott ◽

D Dediu ◽

...

Keyword(s):

Integrated Care ◽

Visual Feedback ◽

Chronic Conditions ◽

Chronic Care ◽

Data Science ◽

Literature Search ◽

Care Delivery ◽

Healthcare Systems ◽

Term Care ◽

Electronic Healthcare Databases

Abstract Background Faced with increasing illness burden and costs, healthcare systems are working towards integrated care to streamline services and improve efficiency, especially for chronic conditions. Routine care delivery data stored in various electronic healthcare databases (EHD) has the potential to support chronic care coordination if information is integrated and accessible at the point of care. Care delivery pathways (CDPs) can be constructed by linking multiple data sources and extracting time-stamped healthcare utilization events and other medical data related to individual or groups of patients over specific time periods; CDPs may facilitate communication on current practice and ways of improving it. We aim to identify and describe the methods proposed to quantify and visualize CDPs. Methods A literature search was performed in PubMed (MEDLINE), Scopus, IEEE, CINAHL and EMBASE, without date restrictions. We will describe CPDs methods from 3 perspectives relevant for EHD use in long-term care: (1) clinical (what clinical information is used and how was it considered relevant?), (2) data science (how was the method developed and implemented?), and (3) behavioral (which behaviors and interactions are promoted among users and how?). Data extraction will be performed via deductive content analysis using selected frameworks, and inductive analysis to identify additional relevant features. We will compare these characteristics to identify common, infrequent, or missing features, and extract recommendations for future initiatives. Results The literature search identified 2349 entries, currently under title and abstract selection by 4 coders. This study will produce a comparison and synthesis of clinical, data, and behavioral features of CDPs methods and derive recommendations for CDP construction. Conclusions This review works towards a common basis for visualizing and quantifying CDPs across healthcare systems, an essential prerequisite for interoperable digital health. Key messages Visual feedback on health care trajectories, especially for chronic conditions, may support informed decisions and planning future care episodes to advance towards person-centered integrated care. We describe and compare technical and clinical characteristics of visual feedback methods available for care pathways, and behaviors they may promote in care planning, to inform future initiatives.

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Assessment of changes in efficacy of antimalarials: a systematic review and network meta-regression

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.828 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

S W Youdom ◽

R S Tchouenkou ◽

E-P Ndong-Nguema ◽

L K Basco

Keyword(s):

Systematic Review ◽

Uncomplicated Malaria ◽

Data Science ◽

Meta Analysis ◽

Decision Makers ◽

Inclusion Criteria ◽

Antimalarial Drug Resistance ◽

Consistency Model ◽

Meta Regression ◽

Methodological Studies

Abstract Background The fight against diseases such as malaria requires the synthesis of evidence from existing studies to inform decision makers. Indeed, at a cross road of antimalarial drug resistance, several artemisinin-based combination therapies (ACT) with multiple doses are available to fight uncomplicated malaria. However, little is known on how these combinations are combined as well as how different formulations are tested. Methods A systematic review was performed to identify randomized trials. Articles were sought by hand-searching and scanning references. Additional covariates effect on treatment outcome was assessed, and a modeling approach to reduce heterogeneity among trials was evaluated. We explored one single interaction effect for all treatment with age as the main covariate in a meta-regression. A Bayesian analysis was used to implement the consistency and inconsistency models under the WinBUGS software. Ranking measure was used to obtain a hierarchy of the competing interventions. Results In total, 77 articles meet the inclusion criteria with 15 combinations tested in 36,000 patients. Results were compared to that of frequentist approach and presented according to the Prisma NMA checklist. The consistency model showed a good performance than the inconsistency model under the hypothesis of homogeneity. It was found that compared to artemether-lumefantrine, the dihydro-artemisinin-piperaquine was more effective before (B, OR = 1.83; 95% CI = 1.31-2.56) and after (A, OR = 1.70; 95% CI = 1.20-2.43) covariate adjustment, and occupied the top rank. Conclusions The application of the methods described here may be helpful to gain better understanding of treatment efficacy and improve future decisions in malaria programs. Based on the available evidence, this study demonstrated the superiority of DHAP among currently recommended ACT in preventing as well as treating uncomplicated malaria. Key messages Choosing the best therapy requires data triangulation and data science. Network meta-analysis could be a solution but need more methodological studies.

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The effect of physical rehabilitation on activities of daily living in older residents of long-term care facilities: systematic review with meta-analysis

Age and Ageing ◽

10.1093/ageing/aft133 ◽

2013 ◽

Vol 42 (6) ◽

pp. 682-688 ◽

Cited By ~ 34

Author(s):

Tom Crocker ◽

John Young ◽

Anne Forster ◽

Lesley Brown ◽

Seline Ozer ◽

...

Keyword(s):

Systematic Review ◽

Activities Of Daily Living ◽

Daily Living ◽

Long Term Care ◽

Meta Analysis ◽

Physical Rehabilitation ◽

Term Care ◽

Care Facilities

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Prevalence and predictors of medication non-adherence among patients with multimorbidity: A systematic review protocol

HRB Open Research ◽

10.12688/hrbopenres.12961.1 ◽

2019 ◽

Vol 2 ◽

pp. 29

Author(s):

Louise Foley ◽

James Larkin ◽

Richard Lombard-Vance ◽

Andrew W. Murphy ◽

Gerard J. Molloy

Keyword(s):

Systematic Review ◽

Full Text ◽

Chronic Conditions ◽

Data Extraction ◽

Meta Analysis ◽

Intervention Development ◽

Evidence Base ◽

Multiple Chronic Conditions ◽

Review Protocol ◽

Form Quality

Introduction: Patients with multimorbidity are expected to adhere to complex medication regimens in order to manage their multiple chronic conditions. It has been reported the likelihood of adherence decreases as patients are prescribed more medications. Much medication adherence research to date is dominated by a single-disease focus, which is at odds with the rising prevalence of multimorbidity and may artificially underestimate the complexity of managing chronic illness. This review aims to describe the prevalence of medication non-adherence among patients with multimorbidity, and to identify potential predictors of non-adherence in this population. Methods: A systematic review will be conducted and reported according to PRISMA guidelines. PubMed, EMBASE, CINAHL and PsycINFO will be searched using a predefined search strategy from 2009–2019. Quantitative studies will be considered eligible for review if prevalence of medication non-adherence among adults with two or more chronic conditions is reported. Studies will be included in the review if available in English full text. Titles and abstracts will be screened by single review, with 20% of screening cross-checked by a second reviewer. Full-text articles will be screened by two independent reviewers, noting reasons for exclusions. Data extraction will be performed using a predefined extraction form. Quality and risk of bias assessment will be conducted using criteria for observational studies outlined by Sanderson et al. (2007). A narrative synthesis and, if feasible, meta-analysis will be conducted. Discussion: By exploring medication non-adherence from a multimorbidity perspective, the review aims to inform an evidence base for intervention development which accounts for the rising prevalence of patients with multiple chronic conditions. Study registration: The systematic review is prospectively registered in PROSPERO (CRD42019133849); registered on 12 June 2019.

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Measuring context-dependent memory in rodents: a systematic review and meta-analysis of important variables in the object-in-context task.

10.1101/2021.03.12.435070 ◽

2021 ◽

Author(s):

Milou Sep ◽

Marijn Vellinga ◽

R. Angela Sarabdjitsingh ◽

Marian Joëls

Keyword(s):

Systematic Review ◽

Meta Analysis ◽

Animal Experiments ◽

Data Driven ◽

Evidence Based ◽

Critical Factors ◽

Context Dependent ◽

Set Up ◽

Rats And Mice ◽

Learning Trials

Environmental information plays an important role in remembering events. Information about stable aspects of the environment (here referred to as ‘context’) and the event are combined by the hippocampal system and stored as context-dependent memory. In rodents (such as rats and mice), context-dependent memory is often investigated with the object-in-context task. However, the implementation and interpretation of this task varies considerably across studies. This variation hampers the comparison between studies and - for those who design a new experiment or carry out pilot experiments – the estimation of whether observed behavior is within the expected range. Also, it is currently unclear which of the variables critically influence the outcome of the task. To address these issues, we carried out a preregistered systematic review (PROSPERO CRD42020191340) and provide an up-to-date overview of the animal-, task-, and protocol-related variations in the object-in-context task for rodents. Using a data-driven explorative meta-analysis we next identified critical factors influencing the outcome of this task, such as sex, testbox size and the delay between the learning trials. Based on these observations we provide recommendations to create more consensus in the set-up, procedure and interpretation of the object-in-context task for rodents. This could contribute to a more robust and evidence-based design in future animal experiments.

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Effects of caregiver-involved interventions on the quality of life of children and adolescents with chronic conditions and their caregivers: a systematic review and meta-analysis

Quality of Life Research ◽

10.1007/s11136-018-1976-3 ◽

2018 ◽

Vol 28 (1) ◽

pp. 13-33 ◽

Cited By ~ 3

Author(s):

Nan Sheng ◽

Jiali Ma ◽

Wenwen Ding ◽

Ying Zhang

Keyword(s):

Quality Of Life ◽

Systematic Review ◽

Children And Adolescents ◽

Chronic Conditions ◽

Meta Analysis

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The preventable proportion of healthcare-associated infections 2005–2016: Systematic review and meta-analysis

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2018.183 ◽

2018 ◽

Vol 39 (11) ◽

pp. 1277-1295 ◽

Cited By ~ 32

Author(s):

Peter W. Schreiber ◽

Hugo Sax ◽

Aline Wolfensberger ◽

Lauren Clack ◽

Stefan P. Kuster ◽

...

Keyword(s):

Systematic Review ◽

Risk Ratio ◽

Meta Analysis ◽

Cochrane Library ◽

Healthcare Associated Infections ◽

Term Care ◽

Multifaceted Interventions ◽

Rate Ratios ◽

Tract Infections ◽

Healthcare Associated

AbstractObjectiveThe preventable proportion of healthcare-associated infections (HAIs) may decrease over time as standards of care improve. We aimed to assess the proportion of HAIs prevented by multifaceted infection control interventions in different economic settings.MethodsIn this systematic review and meta-analysis, we searched OVID Medline, EMBASE, CINAHL, PubMed, and The Cochrane Library for studies published between 2005 and 2016 assessing multifaceted interventions to reduce catheter-associated urinary tract infections (CAUTIs), central-line–associated bloodstream infections (CLABSIs), surgical site infections (SSIs), ventilator-associated pneumonia (VAP), and hospital-acquired pneumonia not associated with mechanical ventilation (HAP) in acute-care or long-term care settings. For studies reporting raw rates, we extracted data and calculated the natural log of the risk ratio and variance to obtain pooled risk ratio estimates.ResultsOf the 5,226 articles identified by our search, 144 studies were included in the final analysis. Pooled incidence rate ratios associated with multifaceted interventions were 0.543 (95% confidence interval [CI], 0.445–0.662) for CAUTI, 0.459 (95% CI, 0.381–0.554) for CLABSI, and 0.553 (95% CI, 0.465–0.657) for VAP. The pooled rate ratio was 0.461 (95% CI, 0.389–0.546) for interventions aiming at SSI reduction, and for VAP reduction initiatives, the pooled rate ratios were 0.611 (95% CI, 0.414–0.900) for before-and-after studies and 0.509 (95% CI, 0.277–0.937) for randomized controlled trials. Reductions in infection rates were independent of the economic status of the study country. The risk of bias was high in 143 of 144 studies (99.3%).ConclusionsPublished evidence suggests a sustained potential for the significant reduction of HAI rates in the range of 35%–55% associated with multifaceted interventions irrespective of a country’s income level.

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