Israel Medical Association Journal

In this review, I described the development of the healthcare system in Theresienstadt during the Holocaust, from the establishment of the camp in late 1941 through 1945. Despite the horrific conditions, the Jews established a highly organized and relatively efficient system that was able to deliver excellent medical care to those eligible to receive care. The major factors that enabled development of the system included the heroic efforts of the high-level providers, the trust of patients, a public health approach to prevent epidemics and the perceived propaganda value of a good healthcare system to the Nazi oppressor. There were many challenges, particularly an informal triage policy that largely excluded medical care from the elderly (above age 60 years), mentally ill, and disabled. There were often difficult relations between caregivers related to ageism, gender, and national origin of the providers. Despite these adversities and the eventual futility due to the murder of the vast majority of the inhabitants, the Jews in Theresienstadt clung to life and tried their best to conduct a civilized society, in a large part through the delivery of excellent medical care.

Background: Advancements in artificial intelligence (AI) and natural language processing (NLP) have led to the development of language models such as ChatGPT. These models have the potential to transform healthcare and medical research. However, understanding their applications and limitations is essential.

Objectives: To present a view of ChatGPT research and to critically assess ChatGPT's role in medical writing and clinical environments.

Methods: We performed a literature review via the PubMed search engine from 20 November 2022, to 23 April 2023. The search terms included ChatGPT, OpenAI, and large language models. We included studies that focused on ChatGPT, explored its use or implications in medicine, and were original research articles. The selected studies were analyzed considering study design, NLP tasks, main findings, and limitations.

Results: Our study included 27 articles that examined ChatGPT's performance in various tasks and medical fields. These studies covered knowledge assessment, writing, and analysis tasks. While ChatGPT was found to be useful in tasks such as generating research ideas, aiding clinical reasoning, and streamlining workflows, limitations were also identified. These limitations included inaccuracies, inconsistencies, fictitious information, and limited knowledge, highlighting the need for further improvements.

Conclusions: The review underscores ChatGPT's potential in various medical applications. Yet, it also points to limitations that require careful human oversight and responsible use to improve patient care, education, and decision-making.

In the grand theater of modern medicine, artificial intelligence (AI) has swiped the lead role, with a performance so riveting it deserves an Oscar, or at least a Nobel. From the intricate labyrinths of our arteries to the profound depths of our peepers, AI is the new maestro, conducting symphonies of data with the finesse of a seasoned virtuoso [1,2].

A rise in the incidence of chronic health conditions, notably heart failure, is expected due to demographic shifts. Such an increase places an onerous burden on healthcare infrastructures, with recurring hospital admissions and heightened mortality rates being prominent factors. Efficient chronic disease management hinges on regular ambulatory care and preemptive action. The application of intelligent computational models is showing promise as a key resource in the ongoing management of chronic diseases, particularly in forecasting disease trajectory and informing timely interventions. In this review, we explored a pioneering intelligent computational model by Diagnostic Robotics, an Israeli start-up company. This model uses data sourced from insurance claims to forecast the progression of heart failure. The goal of the model is to identify individuals at increased risk for heart failure, thus enabling interventions to be initiated early, mitigating the risk of disease worsening, and relieving the pressure on healthcare facilities, which will result in economic efficiencies.

Medical imaging data has been at the frontier of artificial intelligence innovation in medicine with many clinical applications. There have been many challenges, including patient data protection, algorithm performance, radiology workflow, user interface, and IT integration, which have been addressed and mitigated over the last decade. The AI products in imaging now fall into three main categories: triage artificial intelligence (AI), productivity AI, and augmented AI, each providing a different utility for radiologists, clinicians, and patients. Adoption of AI products into the healthcare system has been slow, but it is growing. It is typically dictated by return on investment, which can be demonstrated in each use case. It is expected to lead to wider adoption of AI products in imaging into the clinical workflow in the future.

Background: At the beginning of 2020, the coronavirus disease 2019 (COVID-19) pandemic presented a new burden on healthcare systems.

Objectives: To evaluate the impact of the COVID-19 pandemic on the outcome of non-COVID patients in Israel.

Methods: We conducted a retrospective observational cohort study at a tertiary medical center in Israel. From December 2018 until June 2022, 6796 patients were hospitalized in the internal medicine wards. Patients were grouped based on their admission date: admitted during COVID waves (waves group), admitted between waves (interim group), and admitted during the same months in the previous year (former-year group).

Results: Mortality during hospitalization and 30-day mortality were higher in the waves group compared to the interim and former-year groups (41.4% vs. 30.5% and 24%, 19.4% vs. 17.9% and 12.9%, P < 0.001). In addition, 1-year mortality was higher in the interim group than in the waves and former-year group (39.1 % vs. 32.5% and 33.4%, P = 0.002). There were significant differences in the readmissions, both at 1 year and total number. The waves group had higher rates of mechanical ventilation and noradrenaline administration during hospitalization. Moreover, the waves group exhibited higher troponin levels, lower hemoglobin levels, and more abnormalities in liver and kidney function.

Conclusions: Hospitalized non-COVID patients experienced worse outcomes during the peaks of the pandemic compared to the nadirs and the preceding year, perhaps due to the limited availability of resources. These results underscore the importance of preparing for large-scale threats and implementing effective resource allocation policies.

Background: Previous epidemiological studies on shoulder instability evaluated specific and relatively small subgroups of patients.

Objectives: To determine the incidence rate of primary shoulder dislocations.

Methods: Cohort analysis of electronic health records from 2004 to 2019 was conducted in a urban district of a major health maintenance organization (HMO) in Israel. Patients presented with primary shoulder dislocation that was treated with closed reduction in any medical facility within the district. Overall incidence density rates (IDR) of primary shoulder dislocations and stabilization surgeries were determined.

Results: Over a period of 16 years 13,158 patients underwent closed reduction of primary shoulder dislocation. Of those, 712 shoulder stabilization surgeries were performed (5%). The IDR of primary shoulder dislocations were 124 per 100,000 person-years. The IDR of primary shoulder stabilizations were 7 per 100,000 person-years. The peak in the number of dislocations was observed in those 20–29 years old and ≥ 60 years of. In patients under 59 years old, dislocations were more common in men. In those ≥ 60 years of age, dislocations were more common in women. Most shoulder stabilization surgeries were performed on young patients. The annual mean time from the first dislocation to stabilization surgery linearly declined to 6 months in 2019.

Conclusions: The IDR of primary shoulder dislocations calculated from the largest HMO in Israel were 124 per 100,000 person-years. Shoulder dislocations had bimodal age distribution. Overall, 5% of the patients (mainly young) with shoulder dislocations underwent shoulder stabilization surgery during the study period.

Background: Coronavirus disease 2019 (COVID-19) led to two nationwide lockdowns in Israel, reducing both supply and demand for medical services in the Israel Defense Force (IDF). IDF soldiers serve on bases within Israel, and most of them return home at the end of the day, similar to other armies in the world.

Objectives: To analyze the health services provided by the IDF with regard to policy changes during lockdowns.

Methods: We compared medical encounters between different services provided by the IDF Medical Corps. We related them to specific time periods: pre-first lockdown, first lockdown (and corresponding timeframes of the previous 3 years), between lockdowns, second lockdown, and post-second lockdown.

Results: Compared to past periods, we found a similar reduction of 27–30% in primary care medical encounter rates during the two lockdowns: 42–43% in sick days and 50–54% in referrals to the emergency department. Referral rates to all specialist medical encounters and elective surgeries decreased significantly during the first lockdown period and increased 1.2–3.5 times during the second lockdown.

Conclusions: A continuance of the shift to telehealth is required to withstand a future lockdown, with a full supply of secondary medical services attuned to core medical issues relevant for combat personnel. A liberal sick leave policy is required to eliminate unnecessary in-person visits, thus reducing the risk of infection.

Background: Lower extremity amputation related to diabetes is a serious outcome, which can have devastating effects on the patient and family. The epidemiology of amputations has recently been used as a possible measure of the adequacy of medical prevention and treatment of diabetes and diabetic foot complications.

Objectives: To report on patients undergoing amputations at one medical center in Israel, their co-morbidities, and the outcomes.

Methods: A retrospective chart study was conducted of amputees operated between 1 September 2017 and 30 September 2018.

Results: The study population comprised 72 patients who had major amputations for diabetes and/or ischemia, mean age 72 ± 10 years, 74% males, 93% with type 2 diabetes. Mean age corrected Charlson Comorbidity Index was 8.2 ± 2.1 with 90% (65 patients) presenting with a score of 6 or higher. Before the recent deterioration, fewer than 20% of the patients exited their home routinely and 24% had an official diagnosis of dementia. There were 31 below knee amputations (BKA) and 41 above knee amputations (AKA). The 30-day, 3-month, 1-year, and 2-year mortality rates were 15.3%, 27.8%, 43.1%, and 54.2% respectively. Median survival period was 20 months. Survival after AKA was 13.4 ± 20, which was significantly less than after BKA (25.4 ± 2.7, P = 0.097).

Conclusions: Factors other than the quality of management of patients with diabetes and complications may contribute to amputation rates; thus, making speculations from international comparisons of raw amputation rates problematic. This population was less healthy than reported in most studies.

The development of antibiotic agents has revolutionized the treatment of infectious diseases and clinical practice. However, antibiotic overuse, together with biologic evolution, has resulted in escalating antibiotic resistance of bacteria; with the One Health concept, it affects our planet including animals, aquatic wildlife, rivers, groundwater, lakes, sea water, aqua farming, and soil. This situation threatens our ability to treat infections effectively in the near future and raises the alarming question of whether we are getting close to the post-antibiotic era. Several measures are suggested to prevent the apocalyptic consequence of antibiotic overuse, few of which are novel with thinking outside the box.

Background: Environmental, social, and governance (ESG) is a form of international private business self-regulation that aims to contribute to society from a philanthropic, activist, or charitable nature by engaging in or supporting volunteering or ethically oriented practices. The major benefit of ESG is having the organization’s workers recruited for the goal of making the world a better place. There is a growing understanding regarding the extent of the environmental impacts of health services. Therefore, the interest in measuring and reporting the sustainability of health system performance is becoming crucial. As population aging and growth in healthcare demand are two of the main challenges of the current and mainly future health services, performance, and quality measurement as well as sustainability metrices are relevant more than ever.

Objectives: To review the ESG activities at Assuta Medical Centers (AMC) that helped the organization earn the Maala Index Platinum + grade in 2021.

Methods: We reviewed the ESG elements that were implemented at AMC.

Results: AMC entered an ESG process in November 2019 and earned Platinum and Platinum+ grades from the Maala Index in 2020 and 2021, respectively. AMC won the Workforce Diversity prize for having many employees over 60 years of age. AMC activities are detailed as a case study for other health organizations in Israel and worldwide.

Conclusions: A big leading health organization can spearhead sustainable development goals model in Israel and worldwide.

Background: Self-management, an active life routine, and adherence to physical activity are effective in the management of low back pain (LBP). However, delivering effective education and reassurance to patients can be a difficult for practitioners. The enhanced transtheoretical model intervention (ETMI) has shown to be successful and cost effective. The intervention focuses on educating practitioners to reassure patients, empower them to increase physical activity, and improve their self-efficacy.

Objectives: To assess whether ETMI can be implemented among primary care practitioners and to examine whether it reduces pain, disability, and fear avoidance as well as decreasing healthcare utilization. This protocol outlines the methodology for the implementation of ETMI through a hybrid implementation–effectiveness design.

Methods: Two qualitative and mixed-method studies provided a basis for an implementation prospective cohort study. Discussions are followed by a prospective cohort study with pre-and post-intervention measures as well as descriptions retrieving economic and therapeutic outcome data from the Maccabi Healthcare Services (MHS) databases. In addition, a fourth qualitative study was conducted at the midpoint of the implementation to evaluate the process by measuring the perceptions and practice of practitioners. The intervention group was 220 primary care practitioners and their patients (~n=10,000) from the central district of MHS. The control data was provided by other care districts with similar socioeconomic makeup (~n=40,000).

Conclusions: We evaluated the process and outcomes of the implementation of ETMI. We investigated the relationship between the care received (ETMI against treatment as usual) and healthcare utilization, costs, and patient-clinical outcomes.

Too much healthcare is prevalent, wasteful, and harmful. It consists of two separate phenomena: overdiagnosis and overuse. Overdiagnosis is the labeling of a person with a disease or abnormal condition that would not have caused the person harm if left undiscovered. Individuals derive no clinical benefit from overdiagnosis, although they may experience physical, psychological, or financial harm. It has been found that 15–30%, 20–50%, 0–67%, and 50–90% of people with screen detected breast, prostate, lung, and thyroid cancer, respectively, are overdiagnosed. Since many screening tests have trade-off between benefit and harm, a shared decision-making approach is essential. Incidental findings are very common and may also cause overdiagnosis. Overdiagnosis is recognizable in populations and not at the individual level. However, overuse is recognizable at the level of the individual practitioner. Choosing Wisely, an intervention directed at reducing low value care, now faces the challenge of developing interventions that go beyond recommendations. While some of the drivers of overdiagnosis and overuse are similar, different and parallel strategies are needed in order to reduce them. This is one of the major challenges to our health care system.