Contextual Barriers to Implementing Open-Source Electronic Health Record Systems for Low- and Lower-Middle-Income Countries: Scoping Review.

BACKGROUND: Low- and lower-middle-income countries account for a higher percentage of global epidemics and chronic diseases. In most low- and lower-middle-income countries, there is limited access to health care. The implementation of open-source electronic health records (EHRs) can be understood as a powerful enabler for low- and lower-middle-income countries because it can transform the way health care technology is delivered. Open-source EHRs can enhance health care delivery in low- and lower-middle-income countries by improving the collection, management, and analysis of health data needed to inform health care delivery, policy, and planning. While open-source EHR systems are cost-effective and adaptable, they have not proliferated rapidly in low- and lower-middle-income countries. Implementation barriers slow adoption, with existing research focusing predominantly on technical issues preventing successful implementation. OBJECTIVE: This interdisciplinary scoping review aims to provide an overview of contextual barriers affecting the adaptation and implementation of open-source EHR systems in low- and lower-middle-income countries and to identify areas for future research. METHODS: We conducted a scoping literature review following a systematic methodological framework. A total of 7 databases were selected from 3 disciplines: medicine and health sciences, computing, and social sciences. The findings were reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. The Mixed Methods Appraisal Tool and the Critical Appraisal Skills Programme checklists were used to assess the quality of relevant studies. Data were collated and summarized, and results were reported qualitatively, adopting a narrative synthesis approach. RESULTS: This review included 13 studies that examined open-source EHRs' adaptation and implementation in low- and lower-middle-income countries from 3 interrelated perspectives: socioenvironmental, technological, and organizational barriers. The studies identified key issues such as limited funding, sustainability, organizational and management challenges, infrastructure, data privacy and protection, and ownership. Data protection, confidentiality, ownership, and ethics emerged as important issues, often overshadowed by technical processes. CONCLUSIONS: While open-source EHRs have the potential to enhance health care delivery in low- and lower-middle-income-country settings, implementation is fraught with difficulty. This scoping review shows that depending on the adopted perspective to implementation, different implementation barriers come into view. A dominant focus on technology distracts from socioenvironmental and organizational barriers impacting the proliferation of open-source EHRs. The role of local implementing organizations in addressing implementation barriers in low- and lower-middle-income countries remains unclear. A holistic understanding of implementers' experiences of implementation processes is needed. This could help characterize and solve implementation problems, including those related to ethics and the management of data protection. Nevertheless, this scoping review provides a meaningful contribution to the global health informatics discipline.

Systems for Identification and Location of Items at Scale: Study of Scan4Safety in Leeds Hospitals.

Hospitals improve safety and workflow efficiency by implementing systems for identification of items and patients. Little is known about the implementation of these systems across entire hospitals. The aim of this study is to identify challenges and enablers of adoption of such systems at scale, within a hospital organisation and across the English NHS. The focus is on the experience of the Scan4Safety project at Leeds Teaching Hospital NHS Trust (UK). Study methods are qualitative and include interviews with staff and review of documents. This poster paper presents preliminary findings of research in progress.

Effect of Camera Parallax Angle on the Accuracy of Static Contact Angle Measurements.

Measuring the contact angle at the solid/liquid/vapor triple point in sessile drop experiments is one of the most popular and simple ways to quantify the wettability of surfaces and determine the surface free energy. Despite decades of technical advancements in contact angle measurements, which allowed for improving the precision of sessile drop measurements below ±1°, an often overlooked source of experimental error in these measurements originates from the camera's parallax angle (PA) - the angle between the camera optical axis and the sample stage surface. Here, we quantified the systematic errors in the measurement of contact angles due to the acquisition of drop images at finite PA values by simulating sessile drop experiments in which synthetic drops were created using the Young-Laplace equation. The absolute contact angle error induced by imaging drops at nonzero PAs was found to increase as the true contact angle (TCA) deviates from 90° and resulted in an overestimation (underestimation) of the contact angle for drops having TCAs lower (higher) than 90°. The computed absolute contact angle error reaches values as high as -20° (+12.2°) for drops having a TCA of 175° (5°) when imaged with a PA of 10°, thus indicating the importance of considering the PA when accurately quantifying contact angles in sessile drop experiments. The shape and, by extension, volume of the sessile drop was also found to affect the magnitude of the absolute contact angle error as sessile drops with higher apex curvatures exhibited lower absolute error than those with lower curvatures at any given PA. The outcomes of this work provide guidelines for minimizing systematic errors in sessile drop measurements due to the collection of drop images at nonzero PAs.

The impact of hospital command centre on patient flow and data quality: findings from the UK National Health Service.

In the last 6 years, hospitals in developed countries have been trialling the use of command centres for improving organizational efficiency and patient care. However, the impact of these command centres has not been systematically studied in the past. It is a retrospective population-based study. Participants were patients who visited the Bradford Royal Infirmary hospital, Accident and Emergency (A&E) Department, between 1 January 2018 and 31 August 2021. Outcomes were patient flow (measured as A&E waiting time, length of stay, and clinician seen time) and data quality (measured by the proportion of missing treatment and assessment dates and valid transition between A&E care stages). Interrupted time-series segmented regression and process mining were used for analysis. A&E transition time from patient arrival to assessment by a clinician marginally improved during the intervention period; there was a decrease of 0.9 min [95% confidence interval (CI): 0.35-1.4], 3 min (95% CI: 2.4-3.5), 9.7 min (95% CI: 8.4-11.0), and 3.1 min (95% CI: 2.7-3.5) during 'patient flow program', 'command centre display roll-in', 'command centre activation', and 'hospital wide training program', respectively. However, the transition time from patient treatment until the conclusion of consultation showed an increase of 11.5 min (95% CI: 9.2-13.9), 12.3 min (95% CI: 8.7-15.9), 53.4 min (95% CI: 48.1-58.7), and 50.2 min (95% CI: 47.5-52.9) for the respective four post-intervention periods. Furthermore, the length of stay was not significantly impacted; the change was -8.8 h (95% CI: -17.6 to 0.08), -8.9 h (95% CI: -18.6 to 0.65), -1.67 h (95% CI: -10.3 to 6.9), and -0.54 h (95% CI: -13.9 to 12.8) during the four respective post-intervention periods. It was a similar pattern for the waiting and clinician seen times. Data quality as measured by the proportion of missing dates of records was generally poor (treatment date = 42.7% and clinician seen date = 23.4%) and did not significantly improve during the intervention periods. The findings of the study suggest that a command centre package that includes process change and software technology does not appear to have a consistent positive impact on patient safety and data quality based on the indicators and data we used. Therefore, hospitals considering introducing a command centre should not assume there will be benefits in patient flow and data quality.

Disease trajectories following myocardial infarction: insights from process mining of 145 million hospitalisation episodes.

BACKGROUND: Knowledge of post-myocardial infarction (MI) disease risk to date is limited-yet the number of survivors of MI has increased dramatically in recent decades. We investigated temporally ordered sequences of all conditions following MI in nationwide electronic health record data through the application of process mining. METHODS: We conducted a national retrospective cohort study of all hospitalisations (145,670,448 episodes; 34,083,204 individuals) admitted to NHS hospitals in England (1st January 2008-31st January 2017, final follow-up 27th March 2017). Through process mining, we identified trajectories of all major disease diagnoses following MI and compared their relative risk (RR) and all-cause mortality hazard ratios (HR) to a risk-set matched non-MI control cohort using Cox proportional hazards and flexible parametric survival models. FINDINGS: Among a total of 375,669 MI patients (130,758 females; 34.8%) and 1,878,345 matched non-MI patients (653,790 females; 34.8%), we identified 28,799 unique disease trajectories. The accrual of multiple circulatory diagnoses was more common amongst MI patients (RR 4.32, 95% CI 3.96-4.72) and conferred an increased risk of death (HR 1.32, 1.13-1.53) compared with matched controls. Trajectories featuring neuro-psychiatric diagnoses (including anxiety and depression) following circulatory disorders were markedly more common and had increased mortality post MI (HR ranging from 1.11 to 1.73) compared with non-MI individuals. INTERPRETATION: These results provide an opportunity for early intervention targets for survivors of MI-such as increased focus on the psychological and behavioural pathways-to mitigate ongoing adverse disease trajectories, multimorbidity, and premature mortality. FUNDING: British Heart Foundation; Alan Turing Institute.

Effect of a hospital command centre on patient safety: an interrupted time series study.

BACKGROUND: Command centres have been piloted in some hospitals across the developed world in the last few years. Their impact on patient safety, however, has not been systematically studied. Hence, we aimed to investigate this. METHODS: This is a retrospective population-based cohort study. Participants were patients who visited Bradford Royal Infirmary Hospital and Calderdale & Huddersfield hospitals between 1 January 2018 and 31 August 2021. A five-phase, interrupted time series, linear regression analysis was used. RESULTS: After introduction of a Command Centre, while mortality and readmissions marginally improved, there was no statistically significant impact on postoperative sepsis. In the intervention hospital, when compared with the preintervention period, mortality decreased by 1.4% (95% CI 0.8% to 1.9%), 1.5% (95% CI 0.9% to 2.1%), 1.3% (95% CI 0.7% to 1.8%) and 2.5% (95% CI 1.7% to 3.4%) during successive phases of the command centre programme, including roll-in and activation of the technology and preparatory quality improvement work. However, in the control site, compared with the baseline, the weekly mortality also decreased by 2.0% (95% CI 0.9 to 3.1), 2.3% (95% CI 1.1 to 3.5), 1.3% (95% CI 0.2 to 2.4), 3.1% (95% CI 1.4 to 4.8) for the respective intervention phases. No impact on any of the indicators was observed when only the software technology part of the Command Centre was considered. CONCLUSION: Implementation of a hospital Command Centre may have a marginal positive impact on patient safety when implemented as part of a broader hospital-wide improvement programme including colocation of operations and clinical leads in a central location. However, improvement in patient safety indicators was also observed for a comparable period in the control site. Further evaluative research into the impact of hospital command centres on a broader range of patient safety and other outcomes is warranted.

Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment Tools.

Oesophago-gastric cancer is difficult to diagnose in the early stages given its typical non-specific initial manifestation. We hypothesise that machine learning can improve upon the diagnostic performance of current primary care risk-assessment tools by using advanced analytical techniques to exploit the wealth of evidence available in the electronic health record. We used a primary care electronic health record dataset derived from the UK General Practice Research Database (7471 cases; 32,877 controls) and developed five probabilistic machine learning classifiers: Support Vector Machine, Random Forest, Logistic Regression, Naïve Bayes, and Extreme Gradient Boosted Decision Trees. Features included basic demographics, symptoms, and lab test results. The Logistic Regression, Support Vector Machine, and Extreme Gradient Boosted Decision Tree models achieved the highest performance in terms of accuracy and AUROC (0.89 accuracy, 0.87 AUROC), outperforming a current UK oesophago-gastric cancer risk-assessment tool (ogRAT). Machine learning also identified more cancer patients than the ogRAT: 11.0% more with little to no effect on false positives, or up to 25.0% more with a slight increase in false positives (for Logistic Regression, results threshold-dependent). Feature contribution estimates and individual prediction explanations indicated clinical relevance. We conclude that machine learning could improve primary care cancer risk-assessment tools, potentially helping clinicians to identify additional cancer cases earlier. This could, in turn, improve survival outcomes.

Building Process-Oriented Data Science Solutions for Real-World Healthcare.

The COVID-19 pandemic has highlighted some of the opportunities, problems and barriers facing the application of Artificial Intelligence to the medical domain. It is becoming increasingly important to determine how Artificial Intelligence will help healthcare providers understand and improve the daily practice of medicine. As a part of the Artificial Intelligence research field, the Process-Oriented Data Science community has been active in the analysis of this situation and in identifying current challenges and available solutions. We have identified a need to integrate the best efforts made by the community to ensure that promised improvements to care processes can be achieved in real healthcare. In this paper, we argue that it is necessary to provide appropriate tools to support medical experts and that frequent, interactive communication between medical experts and data miners is needed to co-create solutions. Process-Oriented Data Science, and specifically concrete techniques such as Process Mining, can offer an easy to manage set of tools for developing understandable and explainable Artificial Intelligence solutions. Process Mining offers tools, methods and a data driven approach that can involve medical experts in the process of co-discovering real-world evidence in an interactive way. It is time for Process-Oriented Data scientists to collaborate more closely with healthcare professionals to provide and build useful, understandable solutions that answer practical questions in daily practice. With a shared vision, we should be better prepared to meet the complex challenges that will shape the future of healthcare.

Transcription of the Alginate Operon in Pseudomonas aeruginosa Is Regulated by c-di-GMP.

Overproduction of the exopolysaccharide alginate contributes to the pathogenicity and antibiotic tolerance of Pseudomonas aeruginosa in chronic infections. The second messenger, c-di-GMP, is a positive regulator of the production of various biofilm matrix components and is known to regulate alginate synthesis at the posttranslational level in P. aeruginosa. We provide evidence that c-di-GMP also regulates transcription of the alginate operon in P. aeruginosa. Previous work has shown that transcription of the alginate operon is regulated by nine different proteins, AmrZ, AlgP, IHFα, IHFß, CysB, Vfr, AlgR, AlgB, and AlgQ, and we investigated if some of these proteins function as a c-di-GMP effector. We found that deletion of algP, algQ, IHFα, and IHFß had only a marginal effect on the transcription of the alginate operon. Deletion of vfr and cysB led to decreased transcription of the alginate operon, and the dependence of the c-di-GMP level was less pronounced, indicating that Vfr and CysB could be partially required for c-di-GMP-mediated regulation of alginate operon transcription. Our experiments indicated that the AmrZ, AlgR, and AlgB proteins are absolutely required for transcription of the alginate operon. However, differential radial capillary action of ligand assay (DRaCALA) and site-directed mutagenesis indicated that c-di-GMP does not bind to any of the AmrZ, AlgR, and AlgB proteins. IMPORTANCE The proliferation of alginate-overproducing P. aeruginosa variants in the lungs of cystic fibrosis patients often leads to chronic infection. The alginate functions as a biofilm matrix that protects the bacteria against host immune defenses and antibiotic treatment. Knowledge about the regulation of alginate synthesis is important in order to identify drug targets for the development of medicine against chronic P. aeruginosa infections. We provide evidence that c-di-GMP positively regulates transcription of the alginate operon in P. aeruginosa. Moreover, we revisited the role of the known alginate regulators, AmrZ, AlgP, IHFα, IHFß, CysB, Vfr, AlgR, AlgB, and AlgQ, and found that their effect on transcription of the alginate operon is highly varied. Deletion of algP, algQ, IHFα, or IHFß only had a marginal effect on transcription of the alginate operon, whereas deletion of vfr or cysB led to decreased transcription and deletion of amrZ, algR, or algB abrogated transcription.

Patient Safety Informatics: Meeting the Challenges of Emerging Digital Health.

The fourth industrial revolution is based on cyber-physical systems and the connectivity of devices. It is currently unclear what the consequences are for patient safety as existing digital health technologies become ubiquitous with increasing pace and interact in unforeseen ways. In this paper, we describe the output from a workshop focused on identifying the patient safety challenges associated with emerging digital health technologies. We discuss six challenges identified in the workshop and present recommendations to address the patient safety concerns posed by them. A key implication of considering the challenges and opportunities for Patient Safety Informatics is the interdisciplinary contribution required to study digital health technologies within their embedded context. The principles underlying our recommendations are those of proactive and systems approaches that relate the social, technical and regulatory facets underpinning patient safety informatics theory and practice.

The clinical course of pneumomediastinum in patients with SARS-CoV-2 before invasive mechanical ventilation.

Pneumomediastinum and pneumothorax are recognised complications encountered in COVID-19 before or during invasive mechanical ventilation (IMV). The clinical course of patients developing pneumomediastinum before IMV is yet to be evaluated.Four-thousand, one-hundred and thirty-one patients hospitalised with COVID-19 over a 12-month period were retrospectively reviewed to evaluate for incidence, clinical characteristics and outcomes. A subgroup analysis was done to identify any clinical traits between survivors and non-survivors. The overall incidence of pneumomediastinum prior to IMV was 0.92% (n=38) and was seen at admission or during non-invasive respiratory support. Thirty-seven per cent had associated pneumothorax most commonly unilateral (right side). The median (interquartile range (IQR)) duration from admission to developing pneumomediastinum was 7 days (3-11) and complete resolution was seen in 53% of patients; median (IQR) duration to resolution was 8 days (4-17). The in-hospital mortality associated with pneumomediastinum in patients with SARS-CoV-2 (PneumoCoV) was 55%. Increasing age (68 ± 12 years vs 56 ± 14 years; p=0.01), higher body mass index (31 ± 5 kg/m2 vs 28 ± 5 kg/m2; p=0.04), lack of resolution of pneumomediastinum (67% vs 24%; p=0.01; odds ratio (OR) 6.5; 95% confidence interval (CI) 1.5-27.5), presence of concurrent pneumothorax (65% vs 14%; p=0.002; OR 11; 95% CI 2.2-53.1) and elevated procalcitonin levels (>0.5 ng/mL; 81% vs 41%; p=0.01; OR 6; 95% CI 1.4-26) were significant features in those who did not survive.The incidence of PneumoCoV, despite being low, is associated with increased mortality. It is a hallmark of moderate to severe disease with multifaceted contributory factors. Both demographic and clinical factors predict survival.

To the emergency room and back again: Circular healthcare pathways for acute functional neurological disorders.

BACKGROUND AND OBJECTIVES: Studies of Functional Neurological Disorders (FND) are usually outpatient-based. To inform service development, we aimed to describe patient pathways through healthcare events, and factors affecting risk of emergency department (ED) reattendance, for people presenting acutely with FND. METHODS: Acute neurology/stroke teams at a UK city hospital were contacted regularly over 8 months to log FND referrals. Electronic documentation was then reviewed for hospital healthcare events over the preceding 8 years. Patient pathways through healthcare events over time were mapped, and mixed effects logistic regression was performed for risk of ED reattendance within 1 year. RESULTS: In 8 months, 212 patients presented acutely with an initial referral suggesting FND. 20% had subsequent alternative diagnoses, but 162 patients were classified from documentation review as possible (17%), probable (28%) or definite (55%) FND. In the preceding 8 years, these 162 patients had 563 ED attendances and 1693 inpatient nights with functional symptoms, but only 26% were referred for psychological therapy, only 66% had a documented diagnosis, and care pathways looped around ED. Three better practice pathway steps were each associated with lower risk of subsequent ED reattendance: documented FND diagnosis (OR = 0.32, p = 0.004), referral to clinical psychology (OR = 0.35, p = 0.04) and outpatient neurology follow-up (OR = 0.25, p < 0.001). CONCLUSION: People that present acutely to a UK city hospital with FND tend to follow looping pathways through hospital healthcare events, centred around ED, with low rates of documented diagnosis and referral for psychological therapy. When better practice occurs, it is associated with lower risk of ED reattendance.

Evaluating the safety and patient impacts of an artificial intelligence command centre in acute hospital care: a mixed-methods protocol.

INTRODUCTION: This paper presents a mixed-methods study protocol that will be used to evaluate a recent implementation of a real-time, centralised hospital command centre in the UK. The command centre represents a complex intervention within a complex adaptive system. It could support better operational decision-making and facilitate identification and mitigation of threats to patient safety. There is, however, limited research on the impact of such complex health information technology on patient safety, reliability and operational efficiency of healthcare delivery and this study aims to help address that gap. METHODS AND ANALYSIS: We will conduct a longitudinal mixed-method evaluation that will be informed by public-and-patient involvement and engagement. Interviews and ethnographic observations will inform iterations with quantitative analysis that will sensitise further qualitative work. Quantitative work will take an iterative approach to identify relevant outcome measures from both the literature and pragmatically from datasets of routinely collected electronic health records. ETHICS AND DISSEMINATION: This protocol has been approved by the University of Leeds Engineering and Physical Sciences Research Ethics Committee (#MEEC 20-016) and the National Health Service Health Research Authority (IRAS No.: 285933). Our results will be communicated through peer-reviewed publications in international journals and conferences. We will provide ongoing feedback as part of our engagement work with local trust stakeholders.

Process mining for healthcare: Characteristics and challenges.

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

The use of closed incision negative pressure therapy for incision and surrounding soft tissue management: Expert panel consensus recommendations.

As the use of closed incision negative pressure therapy (ciNPT) becomes more widespread, dressing designs have evolved to address implementation challenges and meet surgeon demand. While traditional application of ciNPT was limited to the immediate suture line, a novel dressing that covers the incision and additional surrounding tissues has become available. To expand upon previous ciNPT recommendations and provide guidance on this new dressing, an expert panel of plastic surgeons convened to review the current literature, identify challenges to the implementation and sustainability of ciNPT, and use a modified Delphi technique to form a consensus on the appropriate use of ciNPT with full-coverage dressings. After three rounds of collecting expert opinion via the Delphi method, consensus was reached if 80% of the panel agreed upon a statement. This manuscript establishes 10 consensus statements regarding when ciNPT with full-coverage foam dressings should be considered or recommended in the presence of patient or incision risk factors, effective therapeutic settings and duration, precautions for use, and tools and techniques to support application. The panel also discussed areas of interest for future study of ciNPT with full-coverage dressings. High-quality, controlled studies are needed to expand the understanding of the benefits of ciNPT over the incision and surrounding tissues.

Associations Between Anticholinergic Medication Exposure and Adverse Health Outcomes in Older People with Frailty: A Systematic Review and Meta-analysis.

INTRODUCTION: There are robust associations between use of anticholinergic medicines and adverse effects in older people. However, the nature of these associations for older people living with frailty is yet to be established. OBJECTIVES: The aims were to identify and investigate associations between anticholinergics and adverse outcomes in older people living with frailty and to investigate whether exposure is associated with greater risks according to frailty status. METHODS: MEDLINE, CINAHL, EMBASE, Cochrane Database of Systematic Reviews, Web of Science and PsycINFO were searched to 1 August 2019. Observational studies reporting associations between anticholinergics and outcomes in older adults (average age ≥ 65 years) that reported frailty using validated measures were included. Primary outcomes were physical impairment, cognitive dysfunction, and change in frailty status. Risk of bias was evaluated using the Cochrane Risk of Bias In Non-randomised Studies of Interventions (ROBINS-I) tool. Meta-analysis was undertaken where appropriate. RESULTS: Thirteen studies (21,516 participants) were included (ten community, one residential aged-care facility and two hospital studies). Observed associations included reduced ability for chair standing, slower gait speeds, poorer physical performance, increased risk of falls and mortality. Conflicting results were reported for grip strength, timed up and go test, cognition and activities of daily living. No associations were observed for transitions between frailty states, psychological wellbeing or benzodiazepine-related adverse reactions. There was no clear evidence of differences in risks according to frailty status. CONCLUSIONS: Anticholinergics are associated with adverse outcomes in older people living with frailty; however, the literature has significant methodological limitations. There is insufficient evidence to suggest greater risks based on frailty, and there is an urgent need to evaluate this further in well-designed studies stratifying by frailty.

Closed Incisional Negative Pressure Therapy Significantly Reduces Early Wound Dehiscence after Reduction Mammaplasty.

BACKGROUND: Closed incisional negative pressure therapy (ciNPT) has been shown to improve surgical outcomes. Functional reduction mammaplasty has a wound dehiscence rate of 25% and higher in most series, requiring extra care and delayed secondary healing. We aimed to determine if shifting from standard care dressings to ciNPT reduced early dehiscence after breast reduction. METHODS: This multisurgeon retrospective study compared consecutive patients undergoing primary breast reduction dressed with ciNPT to similar patients with standard dressing materials. Perioperative management was otherwise unchanged. Early dehiscence was defined as incisional disruption requiring wound care within the first 30 postoperative days. Statistical analyses were performed using t-test and Fisher exact test. RESULTS: We analyzed 79 patients with 158 breasts (114 standard and 44 ciNPT). Both groups were similar. Mean ages were 35 and 34 years; body mass index, 28.5 and 27.4 kg/m2; and reduction volumes, 565 and 610 g, respectively. None were active smokers, and 9.5% were former smokers. Wise pattern skin incisions were used in all, and parenchymal resections mostly utilized superomedial pedicles. Median ciNPT treatment was 6 days. Early dehiscence was significantly lower with ciNPT, occurring in only 1 of 44 (2%) breasts, compared to 16 of 114 in the standard group (14%), P = 0.003, a relative risk reduction of 84%. Two control patients required debridement, whereas none of the ciNPT patients did. CONCLUSION: Application of ciNPT markedly decreased early dehiscence requiring wound care, compared to using standard dressings, in otherwise similarly risk-stratified breast reduction patients.

Process Mining to Explore Variations in Endometrial Cancer Pathways from GP Referral to First Treatment.

The main challenge in the pathway analysis of cancer treatments is the complexity of the process. Process mining is one of the approaches that can be used to visualize and analyze these complex pathways. In this study, our purpose was to use process mining to explore variations in the treatment pathways of endometrial cancer. We extracted patient data from a hospital information system, created the process model, and analyzed the variations of the 62-day pathway from a General Practitioner referral to the first treatment in the hospital. We also analyzed the variations based on three different criteria: the type of the first treatment, the age at diagnosis, and the year of diagnosis. This approach should be of interest to others dealing with complex medical and healthcare processes.

Process Mining of Disease Trajectories: A Literature Review.

Disease trajectories model patterns of disease over time and can be mined by extracting diagnosis codes from electronic health records (EHR). Process mining provides a mature set of methods and tools that has been used to mine care pathways using event data from EHRs and could be applied to disease trajectories. This paper presents a literature review on process mining related to mining disease trajectories using EHRs. Our review identified 156 papers of potential interest but only four papers which directly applied process mining to disease trajectory modelling. These four papers are presented in detail covering data source, size, selection criteria, selections of the process mining algorithms, trajectory definition strategies, model visualisations, and the methods of evaluation. The literature review lays the foundations for further research leveraging the established benefits of process mining for the emerging data mining of disease trajectories.