Diabetes misconceptions, seriousness, motivation, self-efficacy and stigma: A cross-sectional comparison of eight Australian diabetes communication campaign videos.

AIM: This study examines potential intended (attitudes, motivation and self-efficacy) and unintended (stigmatisation of diabetes) consequences of past Australian National Diabetes Week campaign videos. Further, outcomes are compared by the extent to which participants perceived their allocated video as stigmatising diabetes. METHODS: In this cross-sectional, ten-arm study, participants (adults with or without diabetes; 1:2 ratio) were randomly allocated to view one of eight archival diabetes campaign videos (intervention), or either an active or passive control group. Post-exposure, study-specific scales measured diabetes Misconceptions and Seriousness, General and Diabetes Risk-Reduction Motivation and Self-efficacy, and perceptions of video Stigmatisation of diabetes. Scores were compared by condition (intervention vs. control) and by campaign Stigma (highest vs. lowest tertile score), separately by cohort (with or without diabetes). RESULTS: The sample included n = 1023 without diabetes; and n = 510 with diabetes (79% type 2 diabetes). No significant differences in outcomes were observed between conditions (intervention vs. control), with one exception: a modest effect on General Self-efficacy among those without diabetes only. Those perceiving high campaign Stigma (15%), relative to low Stigma (60%), reported significantly greater diabetes Misconceptions, lower perceived Seriousness and (among those without diabetes only) lower General Motivation but higher Diabetes Risk Reduction Motivation. CONCLUSION: Though limited to a single-exposure, we found little meaningful positive influence of past diabetes campaign videos on diabetes attitudes, behavioural intentions or self-efficacy. Further, campaign videos were perceived as stigmatising by a minority-a potential harmful impact. This novel study has implications for the design, implementation and evaluation of future diabetes campaigns.

Meta-research: How many diagnostic or prognostic models published in radiological journals are evaluated externally?

OBJECTIVES: Prognostic and diagnostic models must work in their intended clinical setting, proven via "external evaluation", preferably by authors uninvolved with model development. By systematic review, we determined the proportion of models published in high-impact radiological journals that are evaluated subsequently. METHODS: We hand-searched three radiological journals for multivariable diagnostic/prognostic models 2013-2015 inclusive, developed using regression. We assessed completeness of data presentation to allow subsequent external evaluation. We then searched literature to August 2022 to identify external evaluations of these index models. RESULTS: We identified 98 index studies (73 prognostic; 25 diagnostic) describing 145 models. Only 15 (15%) index studies presented an evaluation (two external). No model was updated. Only 20 (20%) studies presented a model equation. Just 7 (15%) studies developing Cox models presented a risk table, and just 4 (9%) presented the baseline hazard. Two (4%) studies developing non-Cox models presented the intercept. Just 20 (20%) articles presented a Kaplan-Meier curve of the final model. The 98 index studies attracted 4224 citations (including 559 self-citations), median 28 per study. We identified just six (6%) subsequent external evaluations of an index model, five of which were external evaluations by researchers uninvolved with model development, and from a different institution. CONCLUSIONS: Very few prognostic or diagnostic models published in radiological literature are evaluated externally, suggesting wasted research effort and resources. Authors' published models should present data sufficient to allow external evaluation by others. To achieve clinical utility, researchers should concentrate on model evaluation and updating rather than continual redevelopment. CLINICAL RELEVANCE STATEMENT: The large majority of prognostic and diagnostic models published in high-impact radiological journals are never evaluated. It would be more efficient for researchers to evaluate existing models rather than practice continual redevelopment. KEY POINTS: • Systematic review of highly cited radiological literature identified few diagnostic or prognostic models that were evaluated subsequently by researchers uninvolved with the original model. • Published radiological models frequently omit important information necessary for others to perform an external evaluation: Only 20% of studies presented a model equation or nomogram. • A large proportion of research citing published models focuses on redevelopment and ignores evaluation and updating, which would be a more efficient use of research resources.

Psychometric Evaluation of a Tablet-Based Tool to Detect Mild Cognitive Impairment in Older Adults: Mixed Methods Study.

BACKGROUND: With the rapid aging of the global population, the prevalence of mild cognitive impairment (MCI) and dementia is anticipated to surge worldwide. MCI serves as an intermediary stage between normal aging and dementia, necessitating more sensitive and effective screening tools for early identification and intervention. The BrainFx SCREEN is a novel digital tool designed to assess cognitive impairment. This study evaluated its efficacy as a screening tool for MCI in primary care settings, particularly in the context of an aging population and the growing integration of digital health solutions. OBJECTIVE: The primary objective was to assess the validity, reliability, and applicability of the BrainFx SCREEN (hereafter, the SCREEN) for MCI screening in a primary care context. We conducted an exploratory study comparing the SCREEN with an established screening tool, the Quick Mild Cognitive Impairment (Qmci) screen. METHODS: A concurrent mixed methods, prospective study using a quasi-experimental design was conducted with 147 participants from 5 primary care Family Health Teams (FHTs; characterized by multidisciplinary practice and capitated funding) across southwestern Ontario, Canada. Participants included health care practitioners, patients, and FHT administrative executives. Individuals aged ≥55 years with no history of MCI or diagnosis of dementia rostered in a participating FHT were eligible to participate. Participants were screened using both the SCREEN and Qmci. The study also incorporated the Geriatric Anxiety Scale-10 to assess general anxiety levels at each cognitive screening. The SCREEN's scoring was compared against that of the Qmci and the clinical judgment of health care professionals. Statistical analyses included sensitivity, specificity, internal consistency, and test-retest reliability assessments. RESULTS: The study found that the SCREEN's longer administration time and complex scoring algorithm, which is proprietary and unavailable for independent analysis, presented challenges. Its internal consistency, indicated by a Cronbach α of 0.63, was below the acceptable threshold. The test-retest reliability also showed limitations, with moderate intraclass correlation coefficient (0.54) and inadequate κ (0.15) values. Sensitivity and specificity were consistent (63.25% and 74.07%, respectively) between cross-tabulation and discrepant analysis. In addition, the study faced limitations due to its demographic skew (96/147, 65.3% female, well-educated participants), the absence of a comprehensive gold standard for MCI diagnosis, and financial constraints limiting the inclusion of confirmatory neuropsychological testing. CONCLUSIONS: The SCREEN, in its current form, does not meet the necessary criteria for an optimal MCI screening tool in primary care settings, primarily due to its longer administration time and lower reliability. As the number of digital health technologies increases and evolves, further testing and refinement of tools such as the SCREEN are essential to ensure their efficacy and reliability in real-world clinical settings. This study advocates for continued research in this rapidly advancing field to better serve the aging population. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/25520.

Association between social support and ambulance use among older people in Japan: an empirical cross-sectional study.

BACKGROUND: Ambulance service demand and utilization are increasing worldwide. To address this issue, the factors that affect ambulance use must be identified. Few studies have examined factors that can intervene and thus reduce the frequency of ambulance use. This study aimed to examine the association between social support and ambulance use among older adults in Japan. We hypothesize that social support is associated with reduced ambulance use. METHODS: This cross-sectional study was conducted as part of the Japan Gerontological Evaluation Study. In December 2019 and January 2020, we collaborated with individuals aged 65 years or above with no long-term care needs. A total of 24,581 participants were included in the analysis. The objective and explanatory variables were ambulance use and social support, respectively. Binomial regression analysis was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: Social support was associated with ambulance use. People who had no one to listen to their complaints or worries were significantly more likely to use ambulance services than those who did (OR [95% CI] = 1.26 [1.03-1.53]). People with no one to take care of them when they were ill were also significantly more likely to use ambulance services than those who had someone to provide care (1.15 [1.01-1.31]). Moreover, the results of binomial logistic regression analysis indicated that individuals who called an ambulance but were not hospitalized had significantly lower social support compared to those who did not call an ambulance. CONCLUSIONS: The results suggest that the presence and quality of social support play a significant role in ambulance use among older adults in Japan. Our findings can help policymakers to plan and implement strategies for reducing the burden on emergency medical care.

Assessment of a virtual prosthetic case planning environment for dental education - A multicentric analysis.

OBJECTIVES: The aim of the present study was the multicentric assessment of the virtual prosthetic case planning environment (VCPE), which relocates patient planning into the virtual space in dental education. MATERIALS AND METHODS: The VCPE is separated into two rooms: a virtual entry area where the user can choose between 10 different prosthetic case plans of ascending complexity, and a virtual patient case planning room. In spring term 2022, the use of virtual case planning was voluntarily assessed in four different German dental schools (DSs) from the perspective of both lecturers and students. The assessment was performed afterwards using a questionnaire. Data were analysed using Kolmogorov-Smirnov test, exploratory data analysis, Fisher-Freeman-Halton test, and exact Fisher test. Reliability was assessed with Cronbach Alpha test (α < 0.05). RESULTS: A total of 59 lecturers and 63 students were included. There were 38.5% male, 60.7% female, and 0.8% diverse participants. The mean age of the lecturers was 36.2 ± 9.0 years and of the students 24.3 ± 3.0 years. The VCPE was assessed as good, yet the evaluations between either the DSs or between the lecturers and students were significantly different. CONCLUSIONS: Even though for some assessment criteria significantly different results between the four DS were observed, the majority of participants evaluated the VCPE positively and recommended them for teaching. The virtual reality as a teaching method for teaching prosthetic case planning for the further preparation of the students for the later professional life can be considered as helpful.

[Bedside-teaching on dementia and delirium: Development, implementation, and evaluation in an acute care hospital]. / Bedside-Teaching zum Thema Demenz und Delir.

Bedside-teaching on dementia and delirium: Development, implementation, and evaluation in an acute care hospital Abstract: Background: Demographic change and the accompanying increase in people with dementia and delirium in acute care hospitals pose growing challenges for nurses in acute care wards. Objective: Pilot implementation and evaluation of knowledge gain and implementation of previously defined critical behaviors. Method: Implementation of the training by APNs. Parallel evaluation of the training along the New World Kirkpatrick model using questionnaires and non-participant observation. Analysis of the data using descriptive statistics. Results: The training itself was well evaluated by the participants. It showed an increase in knowledge of the participants in the main topic categories. The targeted critical behaviors were implemented for the most part. There are deficiencies in the mapping of interventions in the nursing care process. Conclusion: The training concept is suitable to give nurses confidence in dealing with people with dementia and delirium. Continuous support in practice is needed to maintain the interventions in the long term and sustainably in everyday life.

[Dementia Care Nurses in the networked care of people with dementia: a qualitative evaluation study]. / Dementia Care Nurses in der vernetzten Versorgung von Menschen mit Demenz.

Dementia Care Nurses in the networked care of people with dementia: A qualitative evaluation study Abstract: Background: To coordinate networked dementia care counselling concepts with case management (CM) structures are recommended. This approach has been explored and evaluated within the Dementia Care Nurse project in Saxony-Anhalt. Studies on the implementation of CM are mostly limited to cooperation between case managers and medical and nursing professional groups. Networking processes with all stakeholders involved in dementia care have hardly been described so far. Objective: The aim was to describe the experienced collaboration with Dementia Care Nurses (DCNs) from the perspective of the participating cooperation partners and to derive approaches for the continuation of the DCNs in routine care. Method: Eight semi-structured interviews were conducted with cooperation partners from the health and social care sector who participated in the DCN project. The interviews were analysed for content. Results: The interviews were evaluated by content analysis. Results: Overall, the interviewed cooperation partners rated the collaboration with the DCNs in the project as positive, especially the proactive approach and the continuous support of people with dementia. The continuation in routine care depends on the institutional location and the qualification of the DCNs. Conclusion: The commitment of DCNs enables a more demand-oriented involvement of relevant stakeholders in the individual planning of dementia care.

Performance of the National Institute of Infectious Diseases disability scale in HTLV-1-associated myelopathy/tropical spastic paraparesis.

HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a chronic disabling disease. However, there is a lack of an adequate and specific health measurement instrument validated and with good performance to assess their degree of physical disability. This led us to carry out this study and to evaluate the performance of Fiocruz's National Institute of Infectious Diseases (IDS) disability scale, a specific instrument for HAM/TSP. Ninety-two HAM/TSP patients participated in the study. One researcher applied the IDS, IPEC scale, Disability Status Scale (DSS), Expanded DSS (EDSS), Osame scale, Beck Depression Inventory, and the WHOQOL-BREF questionnaire. In parallel, blindly, and separately, other researchers applied the IDS. An inter-rater reliability analysis of the IDS, correlation analysis with the other scales, and depression and quality of life questionnaires were performed. The applicability of the IDS was also evaluated. The IDS showed high reliability in all scores. The inter-rater reliability test for the total IDS score was 0.94 (0.82-0.98) on its four dimensions. The scale adequately indicated the different degrees of disability, presenting a distribution similar to normal. There was a high correlation with the other scales (Spearman coefficients > 0.80, p < 0.001). The scale had good acceptance among users and a short application time. IDS for HAM/TSP was reliable, consistent, easy, and fast to use. It can be used for both prospective evaluations and clinical trials. The present study supports the IDS as a valid instrument to measure disability in patients with HAM/TSP compared to previously used scales.

Use of a web-based portal to return normal individual research results in Early Check: Exploring user behaviors and attitudes.

Early Check is a voluntary, large-scale expanded newborn screening study in North Carolina that uses a self-directed web-based portal for return of normal individual research results (IRR). Little is known about participant perspectives in using web-based portals to receive IRR. This study explored user attitudes and behaviors within the Early Check portal using three methods: (1) a feedback survey available to the consenting parent of participating infants (typically mothers), (2) semi-structured interviews conducted with a subset of parents, and (3) Google Analytics. During an approximate 3-year period, 17 936 newborns received normal IRR and there were 27 812 visits to the portal. Most surveyed parents reported viewing their baby's results (86%, 1410/1639). Parents largely found the portal easy to use to get results, and helpful in understanding the results. However, 10% of parents said it was difficult to find enough information to understand their baby's results. In Early Check, providing normal IRR via the portal made a large-scale study practical, and was highly rated by most users. Return of normal IRR may be particularly amenable to web-based portals, as the consequences to participants from not viewing results are modest, and the interpretation of a normal result is relatively straightforward.

Radiologists with and without deep learning-based computer-aided diagnosis: comparison of performance and interobserver agreement for characterizing and diagnosing pulmonary nodules/masses.

OBJECTIVES: To compare the performance of radiologists in characterizing and diagnosing pulmonary nodules/masses with and without deep learning (DL)-based computer-aided diagnosis (CAD). METHODS: We studied a total of 101 nodules/masses detected on CT performed between January and March 2018 at Osaka University Hospital (malignancy: 55 cases). SYNAPSE SAI Viewer V1.4 was used to analyze the nodules/masses. In total, 15 independent radiologists were grouped (n = 5 each) according to their experience: L (< 3 years), M (3-5 years), and H (> 5 years). The likelihoods of 15 characteristics, such as cavitation and calcification, and the diagnosis (malignancy) were evaluated by each radiologist with and without CAD, and the assessment time was recorded. The AUCs compared with the reference standard set by two board-certified chest radiologists were analyzed following the multi-reader multi-case method. Furthermore, interobserver agreement was compared using intraclass correlation coefficients (ICCs). RESULTS: The AUCs for ill-defined boundary, irregular margin, irregular shape, calcification, pleural contact, and malignancy in all 15 radiologists, irregular margin and irregular shape in L and ill-defined boundary and irregular margin in M improved significantly (p < 0.05); no significant improvements were found in H. L showed the greatest increase in the AUC for malignancy (not significant). The ICCs improved in all groups and for nearly all items. The median assessment time was not prolonged by CAD. CONCLUSIONS: DL-based CAD helps radiologists, particularly those with < 5 years of experience, to accurately characterize and diagnose pulmonary nodules/masses, and improves the reproducibility of findings among radiologists. KEY POINTS: • Deep learning-based computer-aided diagnosis improves the accuracy of characterizing nodules/masses and diagnosing malignancy, particularly by radiologists with < 5 years of experience. • Computer-aided diagnosis increases not only the accuracy but also the reproducibility of the findings across radiologists.

Collaborative evaluation study on 18 candidate diseases for newborn screening in 1.77 million samples.

Analytical and therapeutic innovations led to a continuous but variable extension of newborn screening (NBS) programmes worldwide. Every extension requires a careful evaluation of feasibility, diagnostic (process) quality and possible health benefits to balance benefits and limitations. The aim of this study was to evaluate the suitability of 18 candidate diseases for inclusion in NBS programmes. Utilising tandem mass spectrometry as well as establishing specific diagnostic pathways with second-tier analyses, three German NBS centres designed and conducted an evaluation study for 18 candidate diseases, all of them inherited metabolic diseases. In total, 1 777 264 NBS samples were analysed. Overall, 441 positive NBS results were reported resulting in 68 confirmed diagnoses, 373 false-positive cases and an estimated cumulative prevalence of approximately 1 in 26 000 newborns. The positive predictive value ranged from 0.07 (carnitine transporter defect) to 0.67 (HMG-CoA lyase deficiency). Three individuals were missed and 14 individuals (21%) developed symptoms before the positive NBS results were reported. The majority of tested candidate diseases were found to be suitable for inclusion in NBS programmes, while multiple acyl-CoA dehydrogenase deficiency, isolated methylmalonic acidurias, propionic acidemia and malonyl-CoA decarboxylase deficiency showed some and carnitine transporter defect significant limitations. Evaluation studies are an important tool to assess the potential benefits and limitations of expanding NBS programmes to new diseases.

A community-of-practice-based evaluation methodology for knowledge intensive computational methods and its application to multimorbidity decision support.

OBJECTIVE: The study has dual objectives. Our first objective (1) is to develop a community-of-practice-based evaluation methodology for knowledge-intensive computational methods. We target a whitebox analysis of the computational methods to gain insight on their functional features and inner workings. In more detail, we aim to answer evaluation questions on (i) support offered by computational methods for functional features within the application domain; and (ii) in-depth characterizations of the underlying computational processes, models, data and knowledge of the computational methods. Our second objective (2) involves applying the evaluation methodology to answer questions (i) and (ii) for knowledge-intensive clinical decision support (CDS) methods, which operationalize clinical knowledge as computer interpretable guidelines (CIG); we focus on multimorbidity CIG-based clinical decision support (MGCDS) methods that target multimorbidity treatment plans. MATERIALS AND METHODS: Our methodology directly involves the research community of practice in (a) identifying functional features within the application domain; (b) defining exemplar case studies covering these features; and (c) solving the case studies using their developed computational methods-research groups detail their solutions and functional feature support in solution reports. Next, the study authors (d) perform a qualitative analysis of the solution reports, identifying and characterizing common themes (or dimensions) among the computational methods. This methodology is well suited to perform whitebox analysis, as it directly involves the respective developers in studying inner workings and feature support of computational methods. Moreover, the established evaluation parameters (e.g., features, case studies, themes) constitute a re-usable benchmark framework, which can be used to evaluate new computational methods as they are developed. We applied our community-of-practice-based evaluation methodology on MGCDS methods. RESULTS: Six research groups submitted comprehensive solution reports for the exemplar case studies. Solutions for two of these case studies were reported by all groups. We identified four evaluation dimensions: detection of adverse interactions, management strategy representation, implementation paradigms, and human-in-the-loop support. Based on our whitebox analysis, we present answers to the evaluation questions (i) and (ii) for MGCDS methods. DISCUSSION: The proposed evaluation methodology includes features of illuminative and comparison-based approaches; focusing on understanding rather than judging/scoring or identifying gaps in current methods. It involves answering evaluation questions with direct involvement of the research community of practice, who participate in setting up evaluation parameters and solving exemplar case studies. Our methodology was successfully applied to evaluate six MGCDS knowledge-intensive computational methods. We established that, while the evaluated methods provide a multifaceted set of solutions with different benefits and drawbacks, no single MGCDS method currently provides a comprehensive solution for MGCDS. CONCLUSION: We posit that our evaluation methodology, applied here to gain new insights into MGCDS, can be used to assess other types of knowledge-intensive computational methods and answer other types of evaluation questions. Our case studies can be accessed at our GitHub repository (https://github.com/william-vw/MGCDS).

Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis.

OBJECTIVE: Ovarian cancer is a significant health issue with lasting impacts on the community. Despite recent advances in surgical, chemotherapeutic and radiotherapeutic interventions, they have had only marginal impacts due to an inability to identify biomarkers at an early stage. Biomarker discovery is challenging, yet essential for improving drug discovery and clinical care. Machine learning (ML) techniques are invaluable for recognising complex patterns in biomarkers compared to conventional methods, yet they can lack physical insights into diagnosis. eXplainable Artificial Intelligence (XAI) is capable of providing deeper insights into the decision-making of complex ML algorithms increasing their applicability. We aim to introduce best practice for combining ML and XAI techniques for biomarker validation tasks. METHODS: We focused on classification tasks and a game theoretic approach based on Shapley values to build and evaluate models and visualise results. We described the workflow and apply the pipeline in a case study using the CDAS PLCO Ovarian Biomarkers dataset to demonstrate the potential for accuracy and utility. RESULTS: The case study results demonstrate the efficacy of the ML pipeline, its consistency, and advantages compared to conventional statistical approaches. CONCLUSION: The resulting guidelines provide a general framework for practical application of XAI in medical research that can inform clinicians and validate and explain cancer biomarkers.

In vivo evaluation of a hyperspectral imaging system for minimally invasive surgery (HSI-MIS).

BACKGROUND: Hyperspectral Imaging (HSI) is a reliable and safe imaging method for taking intraoperative perfusion measurements. This is the first study translating intraoperative HSI to an in vivo laparoscopic setting using a CE-certified HSI-system for minimally invasive surgery (HSI-MIS). We aim to compare it to an established HSI-system for open surgery (HSI-Open). METHODS: Intraoperative HSI was done using the HSI-MIS and HSI-Open at the Region of Interest (ROI). 19 patients undergoing gastrointestinal resections were analyzed in this study. The HSI-MIS-acquired images were aligned with those from the HSI-Open, and spectra and parameter images were compared pixel-wise. We calculated the Mean Absolute Error (MAE) for Tissue Oxygen Saturation (StO2), Near-Infrared Perfusion Index (NIR-PI), Tissue Water Index (TWI), and Organ Hemoglobin Index (OHI), as well as the Root Mean Squared Error (RMSE) over the whole spectrum. Our analysis of parameters was optimized using partial least squares (PLS) regression. Two experienced surgeons carried out an additional color-change analysis, comparing the ROI images and deciding whether they provided the same (acceptable) or different visual information (rejected). RESULTS: HSI and subsequent image registration was possible in 19 patients. MAE results for the original calculation were StO2 orig. 17.2% (± 7.7%), NIR-PIorig. 16.0 (± 9.5), TWIorig. 18.1 (± 7.9), OHIorig. 14.4 (± 4.5). For the PLS calculation, they were StO2 PLS 12.6% (± 5.2%), NIR-PIPLS 10.3 (± 6.0), TWIPLS 10.6 (± 5.1), and OHIPLS 11.6 (± 3.0). The RMSE between both systems was 0.14 (± 0.06). In the color-change analysis; both surgeons accepted more images generated using the PLS method. CONCLUSION: Intraoperative HSI-MIS is a new technology and holds great potential for future applications in surgery. Parameter deviations are attributable to technical differences and can be reduced by applying improved calculation methods. This study is an important step toward the clinical implementation of HSI for minimally invasive surgery.

Intra-abdominal laparoscopic assessment of organs perfusion using imaging photoplethysmography.

BACKGROUND: An objective evaluation of the functional state and viability of biological tissues during minimally invasive surgery remains unsolved task. Various non-contact methods for evaluating perfusion during laparoscopic surgery are discussed in the literature, but so far there have been no reports of their use in clinical settings. METHODS AND PATIENTS: Imaging photoplethysmography (iPPG) is a new method for quantitative assessment of perfusion distribution along the tissue. This is the first study in which we demonstrate successful use of iPPG to assess perfusion of organs during laparoscopic surgery in an operation theater. We used a standard rigid laparoscope connected to a standard digital monochrome camera, and abdominal organs were illuminated by green light. A distinctive feature is the synchronous recording of video frames and electrocardiogram with subsequent correlation data processing. During the laparoscopically assisted surgeries in nine cancer patients, the gradient of perfusion of the affected organs was evaluated. In particular, measurements were carried out before preparing a part of the intestine or stomach for resection, after anastomosis, or during physiological tests. RESULTS: The spatial distribution of perfusion and its changes over time were successfully measured in all surgical cases. In particular, perfusion gradient of an intestine before resection was visualized and quantified by our iPPG laparoscope in all respective cases. It was also demonstrated that systemic administration of norepinephrine leads to a sharper gradient between well and poorly perfused areas of the colon. In four surgical cases, we have shown capability of the laparoscopic iPPG system for intra-abdominal assessment of perfusion in the anastomosed organs. Moreover, good repeatability of continuous long-term measurements of tissue perfusion inside the abdominal cavity was experimentally demonstrated. CONCLUSION: Our study carried out in real clinical settings has shown that iPPG laparoscope is feasible for intra-abdominal visualization and quantitative assessment of perfusion distribution.

Impact of an intrapartum care quality improvement intervention in Brazilian private hospitals on care safety measures and adverse outcomes.

BACKGROUND: In 2015, a quality improvement (QI) intervention to reduce cesarean sections (CS)-the Adequate Childbirth Project (PPA)-was implemented in the private sector in Brazil. This analysis aims to compare safety care measures and adverse outcomes between women exposed to the PPA intervention to those receiving standard care. METHODS: The analysis included a convenience sample of 12 private hospitals that participated in the PPA (2017-2018). Data collection was performed through chart review and interviews. Differences in 15 outcomes were examined using Pearson's chi-square test and multiple logistic regressions. RESULTS: The final weighted sample was comprised of 4789 births, 2570 in the PPA group (53.5%) and 2227 in the standard care group (46.5%). CS rate was significantly lower in the PPA group (67.3% vs 88.8%). After adjusting for potential confounders, PPA model was associated with decreased overall CS rate (OR = 0.30, 95% CI 0.24 to 0.36), as well as prelabor (OR = 0.41, 0.34 to 0.48) and repeated CS (OR = 0.45, 0.29 to 0.70). In terms of other safety care measures, women in the PPA model had an increased chance of absence of antibiotic prophylaxis in Group B Streptococcus (GBS) + women (OR = 4.63, 1.33 to 16.14) and for CSs (OR = 1.75, 1.38 to 2.22), while those with severe hypertension were less likely to not receiving magnesium sulphate (OR = 0.27, 0.09 to 0.77). Regarding obstetric and neonatal outcomes, PPA model was associated with a decreased chance of having an obstetric anal sphincter injury (OASI) following an episiotomy (OR = 0.34, 0.13 to 0.89), requiring antibiotics other than routine prophylaxis (OR = 0.84, 0.70 to 0.99), having a late preterm (OR = 0.36, 0.27 to 0.48) or early term baby (OR = 0.81, 0.70 to 0.94). There were no statistically significant differences for other outcomes. CONCLUSIONS: The PPA intervention was able to reduce CS rates, late preterm and early term deliveries without increasing the chance of adverse outcomes. The bidirectional effect on safety care measures reinforces that QI initiatives includes closer observation of routine care when implementing interventions to reduce C-section rates.

Cesarean section rates in Brazil are among the highest in the world, particularly in private hospitals. In 2015, a quality improvement project was implemented in private hospitals aiming to reduce the cesarean section (CS) rates (the Adequate Childbirth Project­PPA). In the 2017­2018 period, the Healthy Birth Study (HBS) was proposed to assess the effect of the PPA project in CS rates, as well as use of obstetric interventions, adoption of good practices during labor and birth care and outcomes for both women and their babies. This article presents the comparison of 4873 births analyzed in the HBS, 2589 who were exposed to the PPA project and 2284 who received standard care. The analysis aim was to compare CS rates at the same time to assess if women who were part of the PPA intervention were less likely to have a negative event for themselves or their babies. A group of 15 measures of safety of obstetric care and negative outcomes for women and their babies was compared. Women who were exposed to the PPA intervention had a lower chance of CS, late preterm and early term deliveries. At the same time, the PPA group did not have worse outcomes for women or babies. In terms of safety care, the PPA intervention was associated with both positive and negative effects. For instance, women exposed to the PPA group had a higher chance of not receiving antibiotics to prevent infections when they needed, when compared to standard care.

Perceived Impact of Digital Health Maturity on Patient Experience, Population Health, Health Care Costs, and Provider Experience: Mixed Methods Case Study.

BACKGROUND: Health care organizations understand the importance of new technology implementations; however, the best strategy for implementing successful digital transformations is often unclear. Digital health maturity assessments allow providers to understand the progress made toward technology-enhanced health service delivery. Existing models have been criticized for their lack of depth and breadth because of their technology focus and neglect of meaningful outcomes. OBJECTIVE: We aimed to examine the perceived impacts of digital health reported by health care staff employed in health care organizations across a spectrum of digital health maturity. METHODS: A mixed methods case study was conducted. The digital health maturity of public health care systems (n=16) in Queensland, Australia, was examined using the quantitative Digital Health Indicator (DHI) self-assessment survey. The lower and upper quartiles of DHI scores were calculated and used to stratify sites into 3 groups. Using qualitative methods, health care staff (n=154) participated in interviews and focus groups. Transcripts were analyzed assisted by automated text-mining software. Impacts were grouped according to the digital maturity of the health care worker's facility and mapped to the quadruple aims of health care: improved patient experience, improved population health, reduced health care cost, and enhanced provider experience. RESULTS: DHI scores ranged between 78 and 193 for the 16 health care systems. Health care systems in the high-maturity category (n=4, 25%) had a DHI score of ≥166.75 (the upper quartile); low-maturity sites (n=4, 25%) had a DHI score of ≤116.75 (the lower quartile); and intermediate-maturity sites (n=8, 50%) had a DHI score ranging from 116.75 to 166.75 (IQR). Overall, 18 perceived impacts were identified. Generally, a greater number of positive impacts were reported in health care systems of higher digital health maturity. For patient experiences, higher maturity was associated with maintaining a patient health record and tracking patient experience data, while telehealth enabled access and flexibility across all digital health maturity categories. For population health, patient journey tracking and clinical risk mitigation were reported as positive impacts at higher-maturity sites, and telehealth enabled health care access and efficiencies across all maturity categories. Limited interoperability and organizational factors (eg, strategy, policy, and vision) were universally negative impacts affecting health service delivery. For health care costs, the resource burden of ongoing investments in digital health and a sustainable skilled workforce was reported. For provider experiences, the negative impacts of poor usability and change fatigue were universal, while network and infrastructure issues were negative impacts at low-maturity sites. CONCLUSIONS: This is one of the first studies to show differences in the perceived impacts of digital maturity of health care systems at scale. Higher digital health maturity was associated with more positive reported impacts, most notably in achieving outcomes for the population health aim.

Evaluating the effects of minimum unit pricing in Scotland on the prevalence of harmful drinking: a controlled interrupted time series analysis.

OBJECTIVES: In May 2018, the Scottish Government introduced a minimum unit price (MUP) for alcohol of £0.50 (1 UK unit = 8 g ethanol) to reduce alcohol consumption, particularly among people drinking at harmful levels. This study aimed to evaluate MUP's impact on the prevalence of harmful drinking among adults in Scotland. STUDY DESIGN: This was a controlled interrupted monthly time series analysis of repeat cross-sectional data collected via 1-week drinking diaries from adult drinkers in Scotland (N = 38,674) and Northern England (N = 71,687) between January 2009 and February 2020. METHODS: The primary outcome was the proportion of drinkers consuming at harmful levels (>50 [men] or >35 [women] units in diary week). The secondary outcomes included the proportion of drinkers consuming at hazardous (≥14-50 [men] or ≥14-35 [women] units) and moderate (<14 units) levels and measures of beverage preferences and drinking patterns. Analyses also examined the prevalence of harmful drinking in key subgroups. RESULTS: There was no significant change in the proportion of drinkers consuming at harmful levels (ß = +0.6 percentage points; 95% confidence interval [CI] = -1.1, +2.3) or moderate levels (ß = +1.4 percentage points; 95% confidence interval = -1.1, +3.8) after the introduction of MUP. The proportion consuming at hazardous levels fell significantly by 3.5 percentage points (95% CI = -5.4, -1.7). There were no significant changes in other secondary outcomes or in the subgroup analyses after correction for multiple testing. CONCLUSIONS: Introducing MUP in Scotland was not associated with reductions in the proportion of drinkers consuming at harmful levels but did reduce the prevalence of hazardous drinking. This adds to previous evidence that MUP reduced overall alcohol consumption in Scotland and consumption among those drinking above moderate levels.

How does government policy influence the employment and training of nurse practitioners and physician assistants? A realist analysis using qualitative interviews.

AIMS: The aim of this study was to develop insights into how and why Dutch government policies on deployment and training of nurse practitioners and physician assistants have effect and under what circumstances. DESIGN: A realist analysis using qualitative interviews. METHODS: Data analysis of 50 semi-structured interviews conducted in 2019 with healthcare providers, sectoral and professional associations, and training coordinators. Stratified purposive and snowball sampling were used. RESULTS: Policies stimulated employment and training of nurse practitioners and physician assistants by: (1) contributing to the familiarity of participants in the decision-making process in healthcare providers with and medical doctors' trust in these professions; (2) contributing to participants' motivation in employment and training; and (3) eliminating barriers perceived by medical doctors, managers and directors. The extent to which policies affected employment and training was largely determined by sectoral and organizational circumstances, such as healthcare demand and complexity, and decision-makers in healthcare providers (medical doctors or managers/directors). CONCLUSION: Effectuating familiarity and trust among participants in the decision-making process is a crucial first step. Next, policymakers can motivate participants and lower their perceived barriers by extending the scope of practice, creating reimbursement opportunities and contributing to training costs. Theoretical insights into nurse practitioner and physician assistant employment and training have been refined. IMPACT: The findings highlight how governments, health insurers, sectoral and professional associations, departments, councils, healthcare providers and professionals can facilitate and support nurse practitioner and physician assistant employment and training by contributing to familiarity, trust and motivation, and by clearing perceived barriers.

Meta-evaluation of studies on community physical activity programs in Brazil.

BACKGROUND: The use of the meta-evaluation, especially in health promotion programs, is still scarce. AIM: To verify if the evaluation studies conducted about the Academia da Cidade Programme and the Academia da Saúde Programme comply with the principles and standards of the meta-evaluation. METHODS: This meta-evaluation study was conducted using articles from scientific databases. The parameters of utility, propriety, and accuracy, as defined by the Joint Committee on Standards for Educational Evaluation, and specificity, were applied. The classification of the studies was based on the Stufflebeam's checklist. RESULTS: Of the 18 selected articles, the principle of utility was fully met in 50%, given that 27.8% were classified as very good, 5.6% as good, and 16.7% as fair. The principle of propriety mostly received the result of very good (44.4%), followed by excellent (38.9%), good (11.15), and weak (5.6%). The principle of accuracy was classified as excellent in 44.4% of the studies, considering that in 33.3% it was considered very good; 11.1% good, and 11.1% fair. Specificity was classified as very good in 94.4% of the studies. CONCLUSION: The physical activity community programs evaluations were carried out in accordance to the principles and standards of meta-evaluation tenets. Most studies were classified as excellent regarding the principle of utility and accuracy, or very good as for the principle of propriety and specificity.