Procedural skills workshops for primary care physicians in Israel: a comprehensive analysis.

BACKGROUND: Some of the most common complaints addressed by primary care physicians (PCPs) require manual procedures, such as lacerations repair, abscesses drainage, ingrown toenails removal, dry needling for myofascial pain syndrome, and Epley maneuver for treating benign paroxysmal positional vertigo (BPPV). The aim of this study was to describe the procedural skills workshops program for PCPs implemented in Maccabi Healthcare Services and to investigate how many PCPs have participated and used the skills since the program's inception in 2017. METHODS: In this observational study, we followed all participants in courses from 2017 to 2021. We extracted all procedures performed during these years by PCPs who learned the skill in MHS. RESULTS: During the study period, 620 PCPs participated in workshops for dry needling, soft-tissue and joint injections, BPPV treatment, minor surgical procedures, and spirometry. Most procedures performed were dry needling (average annual number 3,537) and minor surgical procedures (average annual number 361). The average annual use per physician was highest for dry needling (annual average use per physician who used the learned skill was 50.9), followed by soft tissue and joint injections (16.8), minor surgical procedures (14.8), and BPPV treatment (7.5). CONCLUSION: procedural skills workshops may expand PCPs' therapeutic arsenal, thus empowering PCPs and providing more comprehensive care for patients. Some manual skills, such as dry needling, soft tissue injections, and the Epley maneuver, were more likely to be used by participants than other skills, such as spirometry and soft tissue injections.

Use of prescription opioids in Israel and socio-economic correlations between 2010 and 2020.

BACKGROUND: The use of opioids has increased dramatically over the past several years in Israel. The aim of this study was to explore the trends of opioid consumption in Israel over a decade (2010-2020) stratified by socioeconomic status (SES), residence in the periphery, and ethnic background. METHODS: This cross-sectional study included all adult Maccabi Healthcare Services (MHS) patients who filled at least one prescription for opioids during the past decade. In order to standardize dosages and compare different opioid medications, we used the Morphine Milligram Equivalent (MME) conversion factor. We performed The Mann-Kendall test with autocorrelation correction to assess each trend. We then checked the differences between the trends with the Mann-Whitney test (for periphery) and the Kruskal Wallis (for SES and ethnic background). RESULTS: Between the years 2010-2020, 261,270 MHS members met the study's inclusion criteria. The proportions of opioids consumption were 23.9/1000 patients in 2010 and 27.6/1000 patients in 2020, representing a 15% increase. The average daily consumption of opioids was 4.6 and 10.5 MME in 2010 and 2020, respectively, an increase of 227%. The daily MME during 2020 was higher for residents of the periphery compared to non-periphery residents (daily MME of 14.0 compared to 10.1, respectively). Average daily MME increased gradually during the study period for all levels of SES; the values were highest for the low SES group and the lowest for the high SES group (daily MME in 2020 for the lowest, middle, and high SES groups were 15.2 vs. 11.8 vs. 6.7 respectively). CONCLUSIONS: This study highlights that the primary concern in the increase of opioid use is the increasing dosages. The increase in the number of patients using opioids is also significant but to a minor extent. These phenomena disproportionately impact vulnerable populations. Education programs should be offered to physicians regarding the possible harms of long-term use of opioids. These programs should emphasize the risk factors associated with the development of opioid use disorder (OUD) and the caution needed when increasing dosages or switching to higher-potency drugs. Pain clinics and centers for rehabilitation for patients with chronic pain or OUD should be available, not only in central areas but also in the periphery of the country. These clinics and centers should use a holistic approach and a multidisciplinary team that includes specialists in pain and addiction. They should be financially accessible for patients from low SES group and provide solutions in multiple languages.

Risk Stratification Model for Severe COVID-19 Disease: A Retrospective Cohort Study.

BACKGROUND: Risk stratification models have been developed to identify patients that are at a higher risk of COVID-19 infection and severe illness. Objectives To develop and implement a scoring tool to identify COVID-19 patients that are at risk for severe illness during the Omicron wave. METHODS: This is a retrospective cohort study that was conducted in Israel's second-largest healthcare maintenance organization. All patients with a new episode of COVID-19 between 26 November 2021 and 18 January 2022 were included. A model was developed to predict severe illness (COVID-19-related hospitalization or death) based on one-third of the study population (the train group). The model was then applied to the remaining two-thirds of the study population (the test group). Risk score sensitivity, specificity, and positive predictive value rates, and receiver operating characteristics (ROC) were calculated to describe the performance of the model. RESULTS: A total of 409,693 patients were diagnosed with COVID-19 over the two-month study period, of which 0.4% had severe illness. Factors that were associated with severe disease were age (age > 75, OR-70.4, 95% confidence interval [CI] 42.8-115.9), immunosuppression (OR-4.8, 95% CI 3.4-6.7), and pregnancy (5 months or more, OR-82.9, 95% CI 53-129.6). Factors that were associated with a reduced risk for severe disease were vaccination status (patients vaccinated in the previous six months OR-0.6, 95% CI 0.4-0.8) and a prior episode of COVID-19 (OR-0.3, 95% CI 0.2-0.5). According to the model, patients who were in the 10th percentile of the risk severity score were considered at an increased risk for severe disease. The model accuracy was 88.7%. CONCLUSIONS: This model has allowed us to prioritize patients requiring closer follow-up by their physicians and outreach services, as well as identify those that are most likely to benefit from anti-viral treatment during the fifth wave of infection in Israel, dominated by the Omicron variant.

Detection of occult atrial fibrillation with 24-hour ECG after cryptogenic acute stroke or transient ischaemic attack: A retrospective cross-sectional study in a primary care database in Israel.

BACKGROUND: Ischaemic stroke or cerebrovascular accident (CVA) due to occult atrial fibrillation (AF) may cause severe morbidity and mortality. Diagnosing occult AF can be challenging and there is no consensus regarding the optimal duration of screening. A 24-hour Holter electrocardiogram (ECG) is frequently employed to detect occult AF following ischaemic CVA. OBJECTIVES: Demonstration of occult AF detection rate using a 24-hour Holter ECG in a primary care setting with descriptive analyses of independent variables to compare AF detected and non-detected patients. METHODS: This retrospective cross-sectional study utilised primary care data and included patients 50 years and older with a new CVA or transient ischaemic attack (TIA) diagnosis followed by a 24-hour Holter examination within 6 months, between 01 January 2013 and 01 June 2019. The analyses included descriptive statistics comparing demographics and clinical characteristics in patients who had AF or Atrial Flutter (AFL) detection to those who did not. RESULTS: Out of 5015 eligible patients, 66 (1.3%) were diagnosed with AF/AFL, with a number needed to screen of 88.5. Compared with those without AF/AFL detection, those diagnosed were older (75.42 ± 7.89 vs. 69.89 ± 9.88, p = 0.050), had a higher prevalence of hypertension (80.3% vs. 66.8%, p = 0.021) and chronic kidney disease (CKD) (71.2% vs. 44.2%, p < 0.001). CONCLUSION: 24-hour Holter has a low AF/AFL detection rate. Older persons and those with hypertension or CKD are more likely to be detected with AF/AFL using this method.

Validity of diagnostic codes and estimation of prevalence of diabetic foot ulcers using a large electronic medical record database.

AIMS: To assess the validity of the diagnostic codes relating to diabetic foot ulcer (DFU) in the electronic medical records of a large integrated care provider and to assess the prevalence of DFU among its members. MATERIALS AND METHODS: Data were obtained from the diabetes registry of Maccabi Healthcare Services (MHS), a 2.1-million-member sick-fund in Israel, which included 125 665 patients in 2015. We randomly selected and reviewed ~400 patient files from each of the following categories during study period: (1) had a diagnostic code of DFU; (2) had a diagnostic code, or clinical condition suggestive of DFU including: leg-ulcer, amputation, DFU in quartiles proximate to 2015 or abnormality reported by nurse; (3) patients at high risk for DFU (age > 35 and one of the following: peripheral artery disease, neuropathy, DFU during 2011-2014, eGFR<30 mL/min/m2 or foot deformity). The patients' charts were reviewed by study physicians, and DFU was validated or refuted. RESULTS: Relying upon diagnostic codes entered by physicians, the positive predictive value (PPV) was 73.1% (95% CI 67.6-78.2), and the sensitivity was 48.2% (95% CI 45.8-50.7%). The PPV of the diagnostic codes listed by podiatrists were significantly lower, while that of codes listed by nurses was higher but with lower sensitivity. The estimated annual prevalence of DFU in the diabetes registry of MHS was 1.2% (95%CI 1.0-1.5%). CONCLUSIONS: Diagnostic codes alone cannot be used reliably to create a DFU registry. Nevertheless, the data collected provide an estimate of the prevalence of DFU among patients included in the MHS diabetes registry.

A real-world analysis of cancer drug wastage due to oversized vials.

OBJECTIVES: A recent theoretical economic model suggested that oversized vials of cancer drugs lead to $1.8 billion of drug wastage annually in the United States. It is currently unknown how precisely this theoretical model is consistent with the real world. We performed a real-world analysis to assess the economic impact of drug wastage. METHODS: We performed a systematic examination of the usage and wastage of all intravenous cancer drugs in the cancer center of a large tertiary care hospital in Israel. During a period of 1 month, we collected usage and wastage data from the hospital's pharmacy dispensing computerized logs. We calculated the local financial impact using Israeli drug prices list (June 2016) from the ministry of health. We performed an additional analysis using discounted U.S. prices, using the October 2016 Average Sales Prices from the Centers of Medicare and Medicaid Services. RESULTS: Seventy-four injectable anticancer drugs were used during March 2016, and 68 Israeli drug prices were available. The total amount spent on wasted drugs in 1 month was then extrapolated to calculate the annual spending, which was $141,196 per month (5.11% of the total cost) or $1,694,352 per year. Using U.S. prices, the total wastage would be $2,208,876 annually. The 5 drugs that led to the highest expenditure on wastage were bortezomib, trastuzumab, azacytidine, pemetrexed and carfilzomib. There was no wastage of 24 of the 74 drugs. CONCLUSION: This real-world study demonstrates the economic impact of wastage of anticancer drugs on health systems. To decrease wastage, particular attention should be paid to drugs with high usage rates, high cost, and oversized vials.

Detection of Lung Cancer and EGFR Mutation by Electronic Nose System.

INTRODUCTION: Early detection of lung cancer (LC) has been well established as a significant key point in patient survival and prognosis. New highly sensitive nanoarray sensors for exhaled volatile organic compounds that have been developed and coupled with powerful statistical programs may be used when diseases such as LC are suspected. Detection of genetic aberration mutation by nanoarray sensors is the next target. METHODS: Breath samples were taken from patients who were evaluated for suspicious pulmonary lesions. Patients were classified as those with benign nodules, as patients with LC with or without the EGFR mutation, and according to their smoking status. Breath prints were recognized by nanomaterial-based sensor array, and pattern recognition methods were used. RESULTS: A total of 119 patients participated in this study, 30 patients with benign nodules and 89 patients with LC (16 with early disease and 73 with advanced disease). Patients with LC who harbored the EGFR mutation (n = 19) could be discriminated from those with wild-type EGFR (n = 34) with an accuracy of 83%, sensitivity of 79%, and specificity of 85%. Discrimination of early LC from benign nodules had 87% accuracy and positive and negative predictive values of 87.7 and 87.5% respectively. Moderate discrimination (accuracy of 76%) was found between LC of heavy smokers and that of never-smokers or distant past light smokers. CONCLUSIONS: Breath analysis could discriminate patients with LC who harbor the EGFR mutation from those with wild-type EGFR and those with benign pulmonary nodules from those patients with early LC. A positive breath print for the EGFR mutation may be used in treatment decisions if tissue sampling does not provide adequate material for definitive mutation analysis.

Silicon Nanowire Sensors Enable Diagnosis of Patients via Exhaled Breath.

Two of the biggest challenges in medicine today are the need to detect diseases in a noninvasive manner and to differentiate between patients using a single diagnostic tool. The current study targets these two challenges by developing a molecularly modified silicon nanowire field effect transistor (SiNW FET) and showing its use in the detection and classification of many disease breathprints (lung cancer, gastric cancer, asthma, and chronic obstructive pulmonary disease). The fabricated SiNW FETs are characterized and optimized based on a training set that correlate their sensitivity and selectivity toward volatile organic compounds (VOCs) linked with the various disease breathprints. The best sensors obtained in the training set are then examined under real-world clinical conditions, using breath samples from 374 subjects. Analysis of the clinical samples show that the optimized SiNW FETs can detect and discriminate between almost all binary comparisons of the diseases under examination with >80% accuracy. Overall, this approach has the potential to support detection of many diseases in a direct harmless way, which can reassure patients and prevent numerous unpleasant investigations.

Exhaled Breath Analysis for Monitoring Response to Treatment in Advanced Lung Cancer.

INTRODUCTION: The Response Evaluation Criteria in Solid Tumors (RECIST) serve as the accepted standard to monitor treatment efficacy in lung cancer. However, the time intervals between consecutive computerized tomography scans might be too long to allow early identification of treatment failure. This study examines the use of breath sampling to monitor responses to anticancer treatments in patients with advanced lung cancer. METHODS: A total of 143 breath samples were collected from 39 patients with advanced lung cancer. The exhaled breath signature, determined by gas chromatography/mass spectrometry and a nanomaterial-based array of sensors, was correlated with the response to therapy assessed by RECIST: complete response, partial response, stable disease, or progressive disease. RESULTS: Gas chromatography/mass spectrometry analysis identified three volatile organic compounds as significantly indicating disease control (PR/stable disease), with one of them also significantly discriminating PR/stable disease from progressive disease. The nanoarray had the ability to monitor changes in tumor response across therapy, also indicating any lack of further response to therapy. When one-sensor analysis was used, 59% of the follow-up samples were identified correctly. There was 85% success in monitoring disease control (stable disease/partial response). CONCLUSION: Breath analysis, using mainly the nanoarray, may serve as a surrogate marker for the response to systemic therapy in lung cancer. As a monitoring tool, it can provide the oncologist with a quick bedside method of identifying a lack of response to an anticancer treatment. This may allow quicker recognition than does the current RECIST analysis. Early recognition of treatment failure could improve patient care.