Diagnostic Costs Research Articles

A Novel Machine Learning Algorithm for Creating Risk-Adjusted Payment Formulas

Models predicting health care spending and other outcomes from administrative records are widely used to manage and pay for health care, despite well-documented deficiencies. New methods are needed that can incorporate more than 70 000 diagnoses without creating undesirable coding incentives. To develop a machine learning (ML) algorithm, building on Diagnostic Item (DXI) categories and Diagnostic Cost Group (DCG) methods, that automates development of clinically credible and transparent predictive models for policymakers and clinicians. DXIs were organized into disease hierarchies and assigned an Appropriateness to Include (ATI) score to reflect vagueness and gameability concerns. A novel automated DCG algorithm iteratively assigned DXIs in 1 or more disease hierarchies to DCGs, identifying sets of DXIs with the largest regression coefficient as dominant; presence of a previously identified dominating DXI removed lower-ranked ones before the next iteration. The Merative MarketScan Commercial Claims and Encounters Database for commercial health insurance enrollees 64 years and younger was used. Data from January 2016 through December 2018 were randomly split 90% to 10% for model development and validation, respectively. Deidentified claims and enrollment data were delivered by Merative the following November in each calendar year and analyzed from November 2020 to January 2024. Concurrent top-coded total health care cost. Model performance was assessed using validation sample weighted least-squares regression, mean absolute errors, and mean errors for rare and common diagnoses. This study included 35 245 586 commercial health insurance enrollees 64 years and younger (65 901 460 person-years) and relied on 19 clinicians who provided reviews in the base model. The algorithm implemented 218 clinician-specified hierarchies compared with the US Department of Health and Human Services (HHS) hierarchical condition category (HCC) model's 64 hierarchies. The base model that dropped vague and gameable DXIs reduced the number of parameters by 80% (1624 of 3150), achieved an R2 of 0.535, and kept mean predicted spending within 12% ($3843 of $31 313) of actual spending for the 3% of people with rare diseases. In contrast, the HHS HCC model had an R2 of 0.428 and underpaid this group by 33% ($10 354 of $31 313). In this study, by automating DXI clustering within clinically specified hierarchies, this algorithm built clinically interpretable risk models in large datasets while addressing diagnostic vagueness and gameability concerns.

A Swin transformer encoder-based StyleGAN for unbalanced endoscopic image enhancement

With the rapid development of artificial intelligence, automated endoscopy-assisted diagnostic systems have become an effective tool for reducing the diagnostic costs and shortening the treatment cycle of patients. Typically, the performance of these systems depends on deep learning models which are pre-trained with large-scale labeled data, for example, early gastric cancer based on endoscopic images. However, the expensive annotation and the subjectivity of the annotators lead to an insufficient and class-imbalanced endoscopic image dataset, and these datasets are detrimental to the training of deep learning models. Therefore, we proposed a Swin Transformer encoder-based StyleGAN (STE-StyleGAN) for unbalanced endoscopic image enhancement, which is composed of an adversarial learning encoder and generator. Firstly, a pre-trained Swin Transformer is introduced into the encoder to extract multi-scale features layer by layer from endoscopic images. The features are subsequently fed into a mapping block for aggregation and recombination. Secondly, a self-attention mechanism is applied to the generator, which adds detailed information of the image layer by layer through recoded features, enabling the generator to autonomously learn the coupling between different image regions. Finally, we conducted extensive experiments on a private intestinal metaplasia grading dataset from a Grade-A tertiary hospital. The experimental results show that the images generated by STE-StyleGAN are closer to the initial image distribution, achieving a Fréchet Inception Distance (FID) value of 100.4. Then, these generated images are used to enhance the initial dataset to improve the robustness of the classification model, and achieved a top accuracy of 86 %.

Long-term outcomes of very low birth weight infants with intraventricular hemorrhage: a nationwide population study from 2011 to 2019.

Advancements in neonatal care have increased preterm infant survival but paradoxically raised intraventricular hemorrhage (IVH) rates. This study explores IVH prevalence and long-term outcomes of very low birth weight (VLBW) infants in Korea over a decade. Using Korean National Health Insurance data (NHIS,2010-2019), we identified3372 VLBW infants with IVH among 4,129,808 live births.Health-related claims data, encompassing diagnostic codes, diagnostic test costs, and administered procedures were sourced from the NHIS database.The results of the developmental assessments are categorized into four groups based on standard deviation (SD) scores.Neonatal characteristics and complications were compared amongthe groups. Logistic regression models were employed to identify significant changes in the incidence of complications and to calculate odds ratios with corresponding 95% confidence intervals for each risk factor associated with mortality and morbidity in IVH.Long-term growth and developmentwere compared between the two groups(years2010-2013 and 2014-2017). IVH prevalence was 12% in VLBW and 16% in extremely low birth weight (ELBW) infants. Over the past decade, IVH rates increased significantly in ELBW infants (P = 0.0113), while mortality decreased (P = 0.0225). Major improvements in certain neurodevelopmental outcomes and reductions in early morbidities have been observed among VLBW infants with IVH. Ten percent of the population received surgical treatments such as external ventricular drainage (EVD) or a ventriculoperitoneal (VP) shunt, with the choice of treatment methods remaining consistent over time. The IVH with surgical intervention group exhibited higher incidences of delayed development, cerebral palsy, seizure disorder, and growth failure (height, weight, and head circumference) up to 72months of age (P < 0.0001). Surgical treatments were also significantly associated with abnormal developmental screening test results. The neurodevelopmental outcomes of infants with IVH, especially those subjected tosurgical treatments, continue to be a matter of concern. It is imperative to prioritize specialized care for patients receiving surgical treatments and closely monitor their growth and development after discharge to improve developmental prognosis. Supplementary file2 (MP4 77987 kb).

Optimising Alzheimer’s Disease Diagnosis and Treatment: Assessing Cost-Utility of Integrating Blood Biomarkers in Clinical Practice for Disease-Modifying Treatment

BackgroundRecent developments in blood biomarkers (BBM) have shown promising results in diagnosing amyloid pathology in Alzheimer’s Disease (AD). However, information on how these BBMs can best be used in clinical settings to optimise clinical decision-making and long-term health outcomes for individuals with AD is still lacking.ObjectivesWe aim to assess the potential value of BBM in AD diagnosis within the context of disease-modifying treatment (DMT).DesignWe developed a decision analytic model to evaluate the long-term health outcomes using BBM in AD diagnosis. We compared standard of care (SOC) diagnosis workflow to the integration of BBM as a (1) referral decision tool in primary health center (PHC) and (2) triaging tool for invasive CSF examination in specialist memory clinic (MC). We combined a decision tree and a Markov model to simulate the patient’s diagnostic journey, treatment decisions following diagnosis and long-term health outcomes. Input parameters for the model were identified from published literature and registry data analysis. We conducted a cost-utility analysis from the societal perspective using a one-year cycle length and a 30-year (lifetime) horizon.MeasurementsWe reported the simulated outcomes in the percentage of correct diagnosis, costs (in 2022 Euros), quality-adjusted life year (QALY), and incremental cost-effectiveness ratios (ICER) associated with each diagnosis strategy.ResultsCompared to SOC, integrating BBM in PHC increased patient referrals by 8% and true positive AD diagnoses by 10.4%. The lifetime costs for individuals diagnosed with AD were € 249,685 and €250,287, and QALYs were 9.5 and 9.52 in SOC and PHC pathways, respectively. The cost increments were €603, and QALYs gained were 0.01, resulting in an ICER of €48,296. Using BBM in MC reduced the exposure to invasive CSF procedures and costs but also reduced true positive AD diagnoses and QALYs.ConclusionsUsing BBM at PHC to make referral decisions might increase initial diagnostic costs but can prevent high costs associated with disease progression, providing a cost-effective DMT is available, whereas using BBM in MC could reduce the initial evaluation cost but incur high costs associated with disease progression.

IJCM_29A: Expenditure incurred by cancer patients covered under National Health Protection Scheme attending a tertiary care hospital in Mangalore

Background: Over the past decades, cancer has become the second leading cause of death and morbidities around the world, accounting for nearly 1 in 6 of the total global deaths. The cost of treatment depends on the type of cancer, the duration of treatment, the type of hospital, and whether they are covered under any health insurance. Objectives: 1. Cost of cancer treatment, before and after registration under VAS, among cancer patients attending an empanelled tertiary care hospital in South India 2. Pattern of OOPE incurred by households of cancer patients. 3. Proportion of expenditure spent on cancer treatment in comparison to the annual family income. Methodology: A hospital-based cross-sectional study was conducted in tertiary care centre among cancer patients covered under VAS, from April to May 2018. Patients who were not covered under the schemes were excluded from the study. Results: Out of the 150 cancer patients actively receiving cancer treatment, a majority, i.e., 65% of them were females. More than half of them (66%) were in the age group of 20-60 years. Only 9% of patients had additional health insurance to aid their expenditures while the rest were dependent only on VAS. The median (IQR) monthly income of the patient and family members was 153(83;293) USD. The overall median (IQR) cost was 525(230;980) in our patients. Costs before initiation of treatment under VAS constituted almost 90% of direct medical OOPE spent by the patient and his family. The overall mean OOPE in this study was 856 USD. 70% of the patients incurred a monthly cost of ≥40% of their monthly family income and 41% of the patient’s OOPE was more than 100% of their monthly family income. Conclusion: A monthly cost-to-income ratio of 240% is seen in 70% of the patients, Loans were taken and donations received to combat the expenditures. Hence VAS should reimburse the medical cost before enrolment under VAS. VAS can step up and protect its objectives by reimbursing the diagnostic costs and any long-term non-medical costs associated with the illness, as this would help reduce the OOPE by 1/3 making a huge difference to their financial status.

Micro-costing from healthcare professional's perspective and acceptability of cutaneous leishmaniasis diagnostic tools in Morocco: A mixed-methods study.

In Morocco, cutaneous leishmaniasis (CL) represents a concern with three causative parasite species. Despite this, rapid diagnostic test (RDT) for CL is not part of the national control strategy. This study evaluates the acceptability and micro-costing of the CL Detect Rapid Test by Inbios International. The study was conducted from June 2019 to January 2020 and included 46 healthcare professionals from 40 primary healthcare centers and district labs. Data was collected by self-administered questionnaires and interviews and analysed using NVivo, Jamovi, and Python to generate a predictive model and sensitivity analysis by calculating the average Cost-Benefit Ratio for compared CL diagnostic scenarios. The exchange rate is 1 USD = 9.6 MAD (Moroccan Dirham) in November 2019. The CL-RDT received notable acceptance for its user-friendliness and time efficiency compared to traditional microscopy. Micro-costing data revealed that the average unit cost for microscopy is 15 MAD [7-31], whereas 75 MAD [52-131] for CL-RDT. Altogether, the diagnostic cost for microscopy is 115 MAD±4, marginally higher than the 102 MAD±2 for CL-RDT (p = 0,05). Sensitivity analysis identified the most cost-benefit scenarios based on a Cost-Benefit Ratio (CBR). The optimal approach involves using CL-RDT once at a primary healthcare centre (PHC) (CBR = 1.4), especially if the unitary cost is below 79 MAD. The second-best option is using CL-RDT once at a laboratory (CBR = 1.0), which is advantageous if priced under 54 MAD. However, using CL-RDT twice for the same lesion had a less favourable CBR of 0.6 and was only beneficial if priced below 09 MAD. The reference scenario was a single CL-RDT at the PHC followed by microscopy at a laboratory. In conclusion, the forthcoming CL-RDT, expected to feature enhanced sensitivity, is advocated for deployment in resource-limited endemic areas.

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe condition with an uncertain origin and a dismal prognosis. There is presently no precise diagnostic test for ME/CFS, and the diagnosis is determined primarily by the presence of certain symptoms. The current study presents an explainable artificial intelligence (XAI) integrated machine learning (ML) framework that identifies and classifies potential metabolic biomarkers of ME/CFS. Metabolomic data from blood samples from 19 controls and 32 ME/CFS patients, all female, who were between age and body mass index (BMI) frequency-matched groups, were used to develop the XAI-based model. The dataset contained 832 metabolites, and after feature selection, the model was developed using only 50 metabolites, meaning less medical knowledge is required, thus reducing diagnostic costs and improving prognostic time. The computational method was developed using six different ML algorithms before and after feature selection. The final classification model was explained using the XAI approach, SHAP. The best-performing classification model (XGBoost) achieved an area under the receiver operating characteristic curve (AUCROC) value of 98.85%. SHAP results showed that decreased levels of alpha-CEHC sulfate, hypoxanthine, and phenylacetylglutamine, as well as increased levels of N-delta-acetylornithine and oleoyl-linoloyl-glycerol (18:1/18:2)[2], increased the risk of ME/CFS. Besides the robustness of the methodology used, the results showed that the combination of ML and XAI could explain the biomarker prediction of ME/CFS and provided a first step toward establishing prognostic models for ME/CFS.

A Novel Fault Diagnosis Strategy for Diaphragm Pumps Based on Signal Demodulation and PCA-ResNet.

The efficient and accurate identification of diaphragm pump faults is crucial for ensuring smooth system operation and reducing energy consumption. The structure of diaphragm pumps is complex and using traditional fault diagnosis strategies to extract typical fault characteristics is difficult, facing the risk of model overfitting and high diagnostic costs. In response to the shortcomings of traditional methods, this study innovatively combines signal demodulation methods with residual networks (ResNet) to propose an efficient fault diagnosis strategy for diaphragm pumps. By using a demodulation method based on principal component analysis (PCA), the vibration signal demodulation spectrum of the fault condition is obtained, the typical fault characteristics of the diaphragm pump are accurately extracted, and the sample features are enhanced, reducing the cost of fault diagnosis. Afterward, the PCA-ResNet model is applied to the fault diagnosis of diaphragm pumps. A reasonable model structure and advanced residual block design can effectively reduce the risk of model overfitting and improve the accuracy of fault diagnosis. Compared with the visual geometry group (VGG) 16, VGG19, ResNet50, and autoencoder models, the proposed model has improved accuracy by 35.89%, 80.27%, 2.72%, and 6.12%. Simultaneously, it has higher operational efficiency and lower loss rate, solving the problem of diagnostic lag in practical engineering. Finally, a model optimization strategy is proposed through model evaluation metrics and testing. The reasonable parameter range of the model is obtained, providing a reference and guarantee for further optimization of the model.

Study of the list of medicines for the acne treatment and their affordability

Among dermatological diseases, acne (acne vulgaris) is the most common skin disease, which affects almost 9.4% of the world's population, especially 70‒80% of teenagers and young people, as well as 11% of adults after 25 years. According to experts, the financial burden of acne, taking into account the costs of medicines, diagnostics and dermatologist consultations, is quite expensive for patients.&#x0D; The aim of the research was to study the list of medicines for the acne treatment on the domestic market, with an emphasis on dosage forms for external use, and to assess their affordability to the population.&#x0D; The objects of the study were medicines for the treatment of acne. Data analysis of group D10 from the "State Register of Medicinal Products of Ukraine" as of the end of 2023 was carried out. The following methods were used: content analysis, marketing, systematization and generalization, information search.&#x0D; It was investigated that there are 17 medicines for the topical treatment of acne on the market of Ukraine, of which only 11% are domestically produced, the remaining 89% are imported manufacturers, which indicates the high import dependence of this segment. It was found that there is only one domestic manufacturer that offers only one drug, so the development of domestic medicines is urgent.&#x0D; It was found that for the topical treatment of acne in the form of gel 59% of the assortment of drugs for external use, in the form of creams only 18%, in the form of lotion – 12%. Only one position is presented: skin solution and powder for preparation of the solution. The coefficient of adequacy of the solvency of medicines for external and systemic treatment of acne was calculated and it was shown that most of the medicines are expensive.&#x0D; It was found that 17.6% of the studied assortment for external treatment of acne and 50% of drugs for systemic use are not available in pharmacies. The pharmaceutical development of domestic mediсines and the availability of extemporaneous forms for the treatment of acne in pharmacies are relevant. Pharmacoeconomic studies of these medicines are needed to determine which is more cost-effective for the patient to reduce the financial burden. To ensure adherence to acne treatment, patients need to be provided with appropriate pharmaceutical care, especially with topical retinoids, which will help improve treatment outcomes.

Skin in the game: The cost consequences of skin cancer diagnosis, treatment and care in Northern Ireland

BackgroundSkin cancer is a prevalent cancer in the UK. Its rising incidence and mortality rates are expected to result in substantial financial implications, particularly on diagnostic and treatment services for skin cancer management in Northern Ireland (NI). Such anticipated disease increases underscore the need for prevention and control measures that should help guide policymaking and planning efforts. MethodsWe conducted a cost of illness study to assess the economic impact of skin cancer in NI from the healthcare system's perspective, using a bottom-up method, employing NHS reference costs (UK£) for skin cancer diagnosis and treatment patient pathways in 2021/22. Sensitivity analyses varied diagnostic volumes by applying multipliers for benign cases, assuming a diagnostic conversion rate of 6.8%, and examined an alternative chemotherapy regimen compliance rate of 75%. Additionally, proportional cost increases were projected based on future estimated increases of 9% and 28% to malignant melanoma (MM) cases for diagnostic, treatment, and follow-up volumes. ResultsSignificant numbers of non-melanoma skin cancers (NMSC) and MM cases were recorded, 4289 NMSCs and 439 MM cases. The total cost for managing NMSC was £ 3,365,350. Total costs for MM skin cancer were £ 13,740,681, including £ 8,753,494 for procurement, administration, and chemotherapy drug use. Overall healthcare spending on skin cancer care totalled £ 21,167,651. Sensitivity analysis suggested diagnostic cost may increase significantly to £ 12,374,478 based on referral volume assumptions. If base case rates rise by 9 or 28% estimated total costs of treating skin cancer will increase to £ 22.3 million and £ 24.9 million, respectively. ConclusionsSkin cancer management costs in NI totalled ∼£ 21.1 million to £ 32.1 million, depending on diagnostic referral assumptions. Costs have risen ∼10-fold over the past decade for MM due largely to chemotherapy costs. A predicted 28% increase in MM cases by 2040 would lead to ∼£ 3.8 million of additional expenditures, providing a significant challenge for cancer health systems.

Syncope in older adults: challenges, approach and treatment.

Syncope can have devastating consequences, resulting in injuries, accidents or even death. In our ageing society, the subsequent healthcare usage, such as emergency room presentations, surgeries and hospital admissions, forms a significant and growing socioeconomic burden. Causes of syncope in the older adult include orthostatic hypotension, carotid sinus syndrome, vasovagal syncope, structural cardiac abnormalities, cardiac arrhythmias and conduction abnormalities. As stated in the recently published World Falls Guidelines, syncope in older adults often presents as falls, which is either due to amnesia for loss of consciousness, or pre-syncope leading to a fall, especially in those prone to falls with several other risk-factors for falls present. This difference in presentation can hinder the recognition of syncope. In patients with unexplained falls, or in whom the history comprises red flags for potential syncope, special attention to (pre)syncope is therefore warranted. When syncope is mistaken for other causes of a transient loss of consciousness, such as epileptic seizures, or when syncope presents as falls, patients are often referred to multiple specialists, which may in turn lead to excessive and unnecessary diagnostic testing and costs. Specialist services that are able to provide a comprehensive assessment can improve diagnostic yield and minimise diagnostic testing, thus improving patient satisfaction. Comprehensive assessment also leads to reduced length of hospital stay. Increasingly, geriatricians are involved in the assessment of syncope in the older patient, especially given the overlap with falls. Therefore, awareness of causes of syncope, as well as state-of-the-art assessment and treatment, is of great importance.

Comparison of diagnostic outcomes, safety, and cost of Franseen-tip 19G versus 22G needles for endoscopic ultrasound-guided liver biopsies.

Background and study aims Favorable outcomes were noted with refinement in newer endoscopic ultrasound-guided liver biopsy (EUS-LB) needle tips. Still, the overall usefulness and benefit are yet to be well explored. Patients and methods This was a retrospective analysis of patients with EUS-LB (Franseen-tip 19G versus 22G FNB needle) over 2 years. EUS-LB was obtained in a one-pass, two-actuation, modified wet suction technique. Diagnostic yield, fragmentation rate, aggregate specimen length (AL), number of complete portal tracts (CPT), length of longest intact core (LIC), adverse events (AEs) (early), and cost of the procedure (1USD = 82 INR) were compared. Results Fifty-four patients (33 [61.1%], female) successfully underwent EUS-LB with a median age of 46 years (interquartile range [IQR] 34-54); the majority 32 (59.2%) underwent 19G biopsies. There was a significantly increased median (IQR) AL in the 19G compared with 22G (20 mm [19-21] vs. 15 [14-15], P < 0.001), respectively. Similarly, significantly lengthier median LIC and CPT were seen, respectively. A nonsignificant diagnostic yield was noted (100% vs. 90.9%, P = 0.082), respectively. The fragmentation rate was higher in 22G FNB needles (36.4% [95% CI 16-56] vs. 12.5% [95% CI 1-24], respectively; P = 0.038). Seven patients (12.9%) had mild AEs with no difference between groups. The average procedure cost with 19G was INR 63000 (768$), and with 22G needle was INR 54500 (664$). Conclusions The Franseen-tip 19G outperforms 22G with a significantly lower fragmentation rate, longer AL, LIC, and a higher number of CPT with a marginal increase in the procedure cost, without any difference in diagnostic yield and safety.

Improved sensitivity and automation of amulti-step upconversion lateral flow immunoassay using a3D-printed actuation mechanism.

The development of sensitive point-of-care (POC) assay platforms is of interest for reducing the cost and time of diagnostics. Lateral flow assays (LFAs) are the gold standard for POC systems, but their sensitivity as such is inadequate, for example, in the case of cardiac diagnostics. The performance can be improved by incorporating different steps, such as pre-incubation to prolong the interaction time between sample and reporter for immunocomplex formation, and washing steps for background reduction. However, for POC assays, manual steps by the assay conductor are not desired. In this research, upconverting nanoparticles (UCNPs) were coated with poly(acrylic acid) (PAA) and conjugated to anti-cTnI antibodies, yielding non-clustering particles with low non-specific binding. The performance of cTnI-LFA in the PAA-anti-cTnI-UCNPs was compared to thesame UCNPs with a commercial carboxyl surface. A kitchen-timer mechanism was embedded in a 3D-printed housing to produce a low-cost actuator facilitating a timed pre-incubation step for reporter and sample, and a washing step, to enable a multi-step cTnI-LFA with minimized manual labour. PAA-UCNPs showed improved mobility on nitrocellulose compared to those with a commercial surface. The mechanical actuator system was shown to improve sensitivity compared to a labour-intensive multi-step dipstick method, despite pre-incubation occurring during shaking and heating in the dipstick method. The limit of detection decreased from 7.6 to 1.5ng/L cTnI in human plasma. The presented actuator can be easily modified for sensitivity improvement in the LFA for different analytes via pre-incubation and washing steps.

What Do We C in Children With Scurvy? A Case Series Focused on Musculoskeletal Symptoms.

Vitamin C deficiency in children commonly presents with musculoskeletal symptoms such as gait disturbance, refusal to bear weight, and bone or joint pain. We aimed to identify features that could facilitate early diagnosis of scurvy and estimate the cost of care for patients with musculoskeletal symptoms related to scurvy. We conducted a retrospective chart review of patients at a single site with diagnostic codes for vitamin C deficiency, ascorbic acid deficiency, or scurvy. Medical records were reviewed to identify characteristics including presenting symptoms, medical history, and diagnostic workup. The Pediatric Health Information System was used to estimate diagnostic and hospitalization costs for each patient. We identified 47 patients with a diagnosis of scurvy, 49% of whom had a neurodevelopmental disorder. Sixteen of the 47 had musculoskeletal symptoms and were the focus of the cost analysis. Three of the 16 had moderate or severe malnutrition, and 3 had overweight or obesity. Six patients presented to an emergency department for care, 11 were managed inpatient, and 3 required critical care. Diagnostic workups included MRI, computed tomography, echocardiogram, endoscopy, lumbar puncture, and/or EEG. Across all patients evaluated, the cost of emergency department utilization, imaging studies, diagnostic procedures, and hospitalization totaled $470 144 (median $14 137 per patient). Children across the BMI spectrum, particularly those with neurodevelopmental disorders, can develop vitamin C deficiency. Increased awareness of scurvy and its signs and symptoms, particularly musculoskeletal manifestations, may reduce severe disease, limit adverse effects related to unnecessary tests/treatments, and facilitate high-value care.

Systematic Review of Detecting Sleep Apnea Using Artificial Intelligence: An Insight to Convolutional Neural Network Method

Background: Sleep apnea is a prevalent sleep disorder, especially in males and older ages. The common diagnostic methods, including polysomnography (PSG), are expensive, difficult to perform, and time-consuming. Numerous studies are focusing on developing easy-to-perform methods based on artificial intelligence (AI) for the early diagnosis of sleep apnea. This systematic review aimed to gather current methods based on the convolutional neural network (CNN) for the diagnosis of sleep apnea. Methods: Three international electronic databases (PubMed, Web of Science [WoS], and Scopus) were searched from 2010 to October 2023. All studies that have developed CNN-based methods for the diagnosis of sleep apnea and have accomplished the performance tests were included. Finally, the characteristics of the studies were extracted and summarized. Results: A total of 36 studies were included in this systematic review. Various physiological signals have been proposed to detect sleep apnea, including electrocardiogram (ECG), blood oxygen saturation (SpO2), sound signals, respiratory signals, electroencephalogram (EEG), and nasal airflow. Electrocardiogram was the most frequently used signal in the studies, followed by SpO2. The highest reported accuracy was achieved by SpO2 or ECG-based methods and with a one-dimensional CNN (1D-CNN) classifier. Using multiple signals did not necessarily increase the performance of test results. Conclusions: Diagnostic methods based on CNN can be used only as screening tools or home diagnosis of sleep apnea. These methods are easy to perform and can only reduce the diagnostic costs and waiting time for a sleep study in special scenarios. Nevertheless, PSG is still the gold standard for the diagnosis of sleep disorders.

Real-world diagnostic outcomes and cost-effectiveness of genome-wide sequencing for developmental and seizure disorders: Evidence from Canada

PurposeTo determine real-world diagnostic rates, cost trajectories, and cost-effectiveness of exome sequencing (ES) and genome sequencing (GS) for children with developmental and/or seizure disorders in British Columbia, Canada. MethodsBased on medical records review, we estimated real-world costs and outcomes for 491 patients who underwent standard of care (SOC) diagnostic testing at British Columbia Children’s Hospital. Results informed a state-transition Markov model examining cost-effectiveness of 3 competing diagnostic strategies: (1) SOC with last-tier access to ES, (2) streamlined ES access, and (3) first-tier GS. ResultsThrough SOC, 49.4% (95% CI: 40.6, 58.2) of patients were diagnosed at an average cost of C$11,683 per patient (95% CI: 9200, 14,166). Compared with SOC, earlier ES or GS access yielded similar or improved diagnostic rates and shorter times to genetic diagnosis, with 94% of simulations demonstrating cost savings for streamlined ES and 60% for first-tier GS. Net benefit from the perspective of the health care system was C$2956 (95% CI: −608, 6519) for streamlined ES compared with SOC. ConclusionUsing real-world data, we found earlier access to ES may yield more rapid genetic diagnosis of childhood developmental and seizure disorders and cost savings compared with current practice in a Canadian health care system.

Emergency physician cost awareness of common orders in emergency department and awareness impact on medical decisions in Saudi Arabia

Background: With growing emergency department visits, there has been a growth in national health expenditure. This situation is exacerbated by physicians ordering ineffective investigations and procedures. This study aimed to assess the emergency physician&amp;apos;s awareness of cost of diagnostic tests and interventions, and how awareness of costs may impact their medical decision. Methods: This cross-sectional study was conducted among emergency physicians of the Saudi Arabia. The data were collected via self-administered questionnaire disseminated through emails to all physicians. Results: A total of 233 physicians participated, majority of whom were males (73%) and aged 24-34 years-old (70.8%). Of the included physicians, 41.2% were junior residents, and three-quarters (75.5%) of the respondents had never worked in private hospitals. Two-thirds of respondents agreed/strongly agreed that knowing financial cost would affect their clinical practice. Physicians tended to overestimate cost of drugs while underestimate the cost of diagnostics and laboratory tests. The percentage of correct estimates was higher for diagnostics and lab (

Cervical cancer screening and treatment costing in Senegal.

in Senegal, cervical cancer is the leading cause of cancers among women. This study estimated the costs associated with cervical cancer screening and treatment for precancerous lesions from the health system perspective. we estimated costs for screening, diagnostics, and treatment. We conducted a cross-sectional study in seven regions with primary data collected from 50 health facilities. Data collection included structured questionnaires, with secondary data from the Ministry of Health and other sources. A mixed-methods approach combined ingredients-based costing and financial expenditures to estimate direct medical and non-medical costs. All costs are reported in 2019 USD. average costs were $3.71 for visual inspection with acetic acid, $16.49 for Pap smear, and $46.65 for human papillomavirus deoxyribonucleic acid (HPV DNA) testing. Screening cost drivers were clinical exam supplies and clinical equipment for visual inspection with acetic acid, offsite processing of specimens for Pap smear, and lab equipment costs for HPV DNA procedure. The average cost of diagnosis via colposcopy alone was $25.73, and colposcopy with biopsy/endocervical curettage was $74.96. The average cost of treatment followed by one visit for pre-cancerous lesions was $195.24 for loop electrosurgical excision, $47.35 for cryotherapy, and $32.35 for thermal ablation. Clinical equipment and lab costs were the largest contributors to colposcopy and endocervical curettage/biopsy expenses. Clinical equipment made up the largest portion of cryotherapy, loop electrosurgical excision, and thermoablation costs. this study is the first to estimate the costs of HPV screening and treatment in Senegal, which can be used to inform decision-making on cervical cancer investments.

An impedimetric immunosensor for diagnosis of Brazilian spotted fever in blood plasma.

Brazilian spotted fever (BSF) is a serious disease of medical importance due to its rapid evolution and high lethality. The effectiveness of the treatment mainly depends on the rapid diagnosis, which is currently performed by indirect immunofluorescence and PCR tests, which require high costs and laboratory structure. In order to propose an alternative methodology, we sought to develop an impedimetric immunosensor (IM) based on the immobilization of specific IgY antibodies for IgG anti Rickettsia rickettsii, using blood plasma from capybara (Hydrochoerus hydrochaeris), for characterization, validation and applications of the ready IM. IM selectivity was observed when comparing capybara reagent IgG (IgGcr) readings with non-reagent IgG (IgGnr). A reagent IgG calibration curve was obtained, from which the limits of detection (LOD) and quantification (LOQ) of 1.3 ng mL-1 and 4.4 ng mL-1 were calculated, respectively. The accuracy tests showed that different concentrations of IgGcr showed a maximum deviation of 20.0%, with CI between 90.00% and 95.00%. Intermediate precision tests showed a relative standard deviation of 2.09% for researcher 1 and 2.61% for researcher 2, and the F test showed no significant difference between the recovery values found between the two analysts, since Fcal 1.56 < 5.05 and P-value 0.48 > 0, 05. Therefore, an impedimetric immunosensor was developed to detect anti BSF IgG in capybara blood plasma, which greatly contributes to the improvement of diagnostic tests, cost reduction and ease of execution.

Diagnostic device of the sewage pumping station

The diagnostic device of the sewage pumping station for control and accumulation of analog and discrete data of sensors of the sewage pumping station was developed and implemented. The use of such a device allows to achieve a significant increase in the level of user satisfaction, as well as to reduce the costs of diagnostics, maintenance and operation.