Reduce Health Care Costs Research Articles

Skin Cancer Diagnosis: Integrating CNN and Machine Learning Models

Skin cancer is serious health concern that arises from abnormal growth of skin cells. It encompasses of three types, melanoma being the most aggressive form of cancer. The skin cancer starts to arise globally so accordingly there is being necessary public awareness, prevention for this, and strategies for early detection. Accurate diagnosis treatment and Early detection are better for effective management which will improve accuracy and efficiency for diagnostic process. Also, the Machine learning and deep learning algorithms we research and analyse for better outcomes and for innovation in fields of skin cancer detection. And for better treatment for patients, to reduce healthcare costs and overall management of skin cancer. Better constituency and through ongoing research we can try to overcome with help of future advancements in technology and the learning algorithm model. According to our reports and research we did through the dataset of skin images ML and deep learning we got 73% through Naïve Bayes 90% accuracy through random forest algorithm and 89% through CNN model algorithm. We do not conclude that Machine learning algorithm can be better since there are many other factors use in different algorithms so results are not based on high accuracy reports. Keywords: Deep learning, CNN model, Machine learning, Skin cancer

Health Care Cost Reductions with Machine Learning-Directed Evaluations during Radiation Therapy - An Economic Analysis of a Randomized Controlled Study.

Machine learning (ML) may cost-effectively direct health care by identifying patients most likely to benefit from preventative interventions to avoid negative and expensive outcomes. System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT; NCT04277650) was a single-institution, randomized controlled study in which electronic health record-based ML accurately identified patients at high risk for acute care (emergency visit or hospitalization) during radiotherapy (RT) and targeted them for supplemental clinical evaluations. This ML-directed intervention resulted in decreased acute care utilization. Given the limited prospective data showing the ability of ML to direct interventions cost-efficiently, an economic analysis was performed. A post hoc economic analysis was conducted of SHIELD-RT that included RT courses from January 7, 2019, to June 30, 2019. ML-identified high-risk courses (≥10% risk of acute care during RT) were randomized to receive standard of care weekly clinical evaluations with ad hoc supplemental evaluations per clinician discretion versus mandatory twice-weekly evaluations. The primary outcome was difference in mean total medical costs during and 15 days after RT. Acute care costs were obtained via institutional cost accounting. Physician and intervention costs were estimated via Medicare and Medicaid data. Negative binomial regression was used to estimate cost outcomes after adjustment for patient and disease factors. A total of 311 high-risk RT courses among 305 patients were randomized to the standard (n=157) or the intervention (n=154) group. Unadjusted mean intervention group supplemental visit costs were $155 per course (95% confidence interval, $142 to $168). The intervention group had fewer acute care visits per course (standard, 0.47; intervention, 0.31; P=0.04). Total mean adjusted costs were $3110 per course for the standard group and $1494 for the intervention group (difference in means, $1616 [95% confidence interval, $1450 to $1783]; P=0.03). In this economic analysis of a randomized controlled, health care ML study, mandatory supplemental evaluations for ML-identified high-risk patients were associated with both reduced total medical costs and improved clinical outcomes. Further study is needed to determine whether economic results are generalizable. (Funded in part by The Duke Endowment, The Conquer Cancer Foundation, the Duke Department of Radiation Oncology, and the National Cancer Institute of the National Institutes of Health [R01CA277782]; ClinicalTrials.gov number, NCT04277650.).

Enhanced recovery after surgery for oncological breast surgery reduces length of stay in a resource limited setting.

Early recovery after surgery (ERAS) protocols in breast surgery optimizes resources and reduces healthcare costs by facilitating early discharges. These protocols are well established in tertiary centres, but not commonly adopted in regional centres. ERAS implementation potentially impacts smaller hospitals significantly, where resources are limited and persistent bed shortages with mounting waitlist pressures exist. Our study evaluates the feasibility of early discharge with the application of our ERAS protocol to mastectomies in a resource-constrained and rural setting. Breast cancer patients who underwent mastectomies with or without reconstruction between January 2017 and July 2023 were retrospectively reviewed. From January 2022, we implemented a standardized ERAS protocol for patients undergoing mastectomy. This incorporated a combination of pre-, intra- and post-operative elements to enhance patient readiness for discharge. Our study compared these patients (post-ERAS group) with the outcomes of mastectomies performed prior to January 2022 (pre-ERAS group). 104 patients were identified. In the post-ERAS group, 74.4% were discharged within 24 h compared to 23.1% in the pre-ERAS group. Length of stay was reduced from 2.26 to 1.42 days. There were no differences in unplanned clinician reviews or early representation to the emergency department between the two groups. Reducing the length of stay without increased complications can be achieved in a resource-limited environment with our protocolized ERAS principals. Our protocol has been instrumental in allowing safe discharges within 24 h. Other regional centres may benefit in adopting strategies implemented by us for their own ERAS protocols in breast cancer surgery.

Outpatient parenteral antimicrobial therapy (OPAT) in Germany: insights and clinical outcomes from the K-APAT cohort study

PurposeOutpatient parenteral antimicrobial therapy (OPAT) offers several key advantages, including enhanced patient quality of life, reduced healthcare costs, and a potential reduction of nosocomial infections. It is acknowledged for its safety and effectiveness. This study provides the first systematic clinical data for Germany, where OPAT has not yet been widely adopted. The aim is to establish a foundational reference point for further research and integration of OPAT into the German healthcare system.MethodsThis prospective observational study descriptively analyses data obtained from a cohort of patients receiving OPAT. Both in- and outpatients from all medical specialties could be recruited. Patients administered the anti-infective medications themselves at home using elastomeric pumps.Results77 patients received OPAT, with a median duration of 15 days and saving 1782 inpatient days. The most frequently treated entities were orthopaedic infections (n = 20, 26%), S. aureus bloodstream infection (n = 16, 21%) and infectious endocarditis (n = 11, 14%). The most frequently applied drugs were flucloxacillin (n = 18, 23%), penicillin G (n = 13, 17%) and ceftriaxone (n = 10; 13%). Only 5% of patients (n = 4) reported to have missed more than one outpatient dose (max. 3 per patient). Only one catheter-related adverse event required medical intervention, and there were no catheter-related infections.ConclusionThe study demonstrates that OPAT can be safely conducted in Germany. In preparation for its broader implementation, crucial next steps include creating medical guidelines, fostering interdisciplinary and inter-sectoral communication, as well as creating financial and structural regulations that facilitate and encourage the adoption of OPAT.Trial registration numberNCT04002453.

Artificial-Intelligence-Based Clinical Decision Support Systems in Primary Care: A Scoping Review of Current Clinical Implementations.

Primary Care Physicians (PCPs) are the first point of contact in healthcare. Because PCPs face the challenge of managing diverse patient populations while maintaining up-to-date medical knowledge and updated health records, this study explores the current outcomes and effectiveness of implementing Artificial Intelligence-based Clinical Decision Support Systems (AI-CDSSs) in Primary Healthcare (PHC). Following the PRISMA-ScR guidelines, we systematically searched five databases, PubMed, Scopus, CINAHL, IEEE, and Google Scholar, and manually searched related articles. Only CDSSs powered by AI targeted to physicians and tested in real clinical PHC settings were included. From a total of 421 articles, 6 met our criteria. We found AI-CDSSs from the US, Netherlands, Spain, and China whose primary tasks included diagnosis support, management and treatment recommendations, and complication prediction. Secondary objectives included lessening physician work burden and reducing healthcare costs. While promising, the outcomes were hindered by physicians' perceptions and cultural settings. This study underscores the potential of AI-CDSSs in improving clinical management, patient satisfaction, and safety while reducing physician workload. However, further work is needed to explore the broad spectrum of applications that the new AI-CDSSs have in several PHC real clinical settings and measure their clinical outcomes.

Cost-Effectiveness of Strategies for Treatment Timing for Perinatally Acquired Hepatitis C Virus

Prevalence of chronic hepatitis C virus (HCV) infection among pregnant people is increasing in the US. HCV is transmitted vertically in 7% to 8% of births. Direct-acting antiviral (DAA) therapy was recently approved for children with HCV who are 3 years or older. The clinical and economic impacts of early DAA therapy for young children with HCV, compared with treating at older ages, are unknown. To develop a state-transition model to project clinical and economic outcomes for children with perinatally acquired HCV to investigate the cost-effectiveness of treating at various ages. The study team modeled the natural history of perinatally acquired HCV to simulate disease progression and costs of a simulated a cohort of 1000 US children with HCV from 3 years old through death. Added data were analyzed January 5, 2021, through July 1, 2022. The study compared strategies offering 8 weeks of DAA therapy at 3, 6, 12, or 18 years old, as well as a comparator of never treating HCV. Outcomes of interest include life expectancy from 3 years and average lifetime per-person health care costs. Other clinical outcomes include cases of cirrhosis, decompensated cirrhosis, and hepatocellular carcinoma (HCC). The study team projected that treating HCV at 3 years old was associated with lower mean lifetime per-person health care costs ($148 162) than deferring treatment until 6 years old ($164 292), 12 years old ($171 909), or 18 years old ($195 374). Projected life expectancy was longest when treating at 3 years old (78.36 life years [LYs]) and decreased with treatment deferral until 6 years old (76.10 LYs), 12 years old (75.99 LYs), and 18 years old (75.46 LYs). In a cohort of 1000 children with perinatally acquired HCV, treating at 3 years old prevented 89 projected cases of cirrhosis, 27 cases of HCC, and 74 liver-related deaths compared with deferring treatment until 6 years old. In sensitivity analyses, increasing loss to follow-up led to even greater clinical benefits and cost savings with earlier treatment. These study results showed that DAA therapy for 3-year-old children was projected to reduce health care costs and increase survival compared with deferral until age 6 years or older. Measures to increase DAA access for young children will be important to realizing these benefits.

Hospital-Level Care at Home for Patients with Cirrhosis.

Patients with cirrhosis have a 30-day readmission rate of over 30%. Novel care delivery models are needed to reduce healthcare costs and utilization associated with cirrhosis care. One such model is Home Hospital (HH), which provides inpatient-level care at home. Limited evidence currently exists supporting HH for cirrhosis patients. The aims of this study were to characterize patients with cirrhosis who received hospital-level care at home in a two-site clinical trial and to describe the care they received. Secondary aims included describing their outcomes, including adverse events, readmissions and mortality. We identified all patients with cirrhosis who enrolled in HH as part of a two-site clinical trial between 2017 and 2022. HH services include daily clinician visits, intravenous and oral medications, continuous vital sign monitoring, and telehealth specialist consultation. We collected sociodemographic data and analyzed HH stays, including interventions, outcomes, adverse events, and follow-up. 22 patients with cirrhosis (45% Hispanic; 50% limited English proficiency, median MELD-Na 12) enrolled in HH during the study period. Interventions included lab chemistries (82%), intravenous medications (77%), specialist consultation (23%), and advanced diagnostics/procedures (23%). The median length of stay was 7days (IQR 4-12); 186 bed-days were saved. Two patients (9%) experienced adverse events (AKI). No patients required escalation of care; 9% were readmitted within 30days. In this two-site study, HH was feasible for patients with cirrhosis, holding promise as a hepatology delivery model. Future randomized trials are needed to further evaluate the efficacy of HH for patients with cirrhosis.

Food as Medicine: FOODRx for Patients with Diabetes and Cardiovascular Disease in Central Minnesota—A PILOT STUDY

The number of food-insecure individuals with diabetes is on the rise. FOODRx is a supplemental healthy food intervention program that gave disease-appropriate food boxes to food-insecure patients with diabetes at their care clinic and included nutrition and recipe materials in the patient’s preferred language (English, Spanish, or Somali). Implemented over a twelve-month period, we analyze FOODRx participants’ pre and post clinical measures, health care usage, and program/clinic satisfaction, and found that participation was linked to post improvements in fasting glucose and HgbA1c levels, reductions in ER visits and healthcare costs, and a decline in patients choosing between medication and food. Glucose levels decreased from 214 to 187 mg/dL and HgbA1c levels decreased from 9.6% to 9.1%. Average ER visits dropped from 1.21 to 1 visit and the reductions in healthcare costs were reflected in a decrease of an average of USD 250,000 in insurance claims. Patients were less likely to experience food insecurity, as measured in number of meals skipped and levels of hunger. Finally, the program improved patient satisfaction with the cultural responsiveness of the information shared with them.

Co-located Heroin Assisted Treatment within primary care: A preliminary analysis of the implications for healthcare access, cost, and treatment delivery in the UK

BackgroundThe UK is experiencing its highest rate of drug related deaths in 25 years. Poor and inconsistent access to healthcare negatively impacts health outcomes for people who use drugs. Innovation in models of care which promote access and availability of physical treatment is fundamental. Heroin Assisted Treatment (HAT) is a treatment modality targeted at the most marginalised people who use drugs, at high risk of mortality and morbidity. The first service-provider initiated HAT service in the UK ran between October 2019 and November 2022 in Middlesbrough, England. The service was co-located within a specialist primary care facility offering acute healthcare treatment alongside injectable diamorphine. MethodsAnalysis of anonymised health records for healthcare costs (not including drug treatment) took place using descriptive statistics prior and during engagement with HAT, at both three (n=15) and six (n=12) months. Primary outcome measures were incidents of wound care, skin and soft tissue infections (SSTIs), overdose (OD) events, unplanned overnight stays in hospital, treatment engagement (general and within hospital care settings) and ambulance incidents. Secondary outcome measures were costs associated with these events. ResultsA shift in healthcare access for participants during HAT engagement was observed. HAT service attendance appeared to support health promoting preventative care, and reduce reactive reliance on emergency healthcare systems. At three and six months, engagement for preventative wound care and treatment for SSTIs increased at the practice. Unplanned emergency healthcare interactions for ODs, overnight hospital stays, serious SSTIs, and ambulance incidents reduced, and there was an increase in treatment engagement (i.e. a reduction in appointments which were not engaged with). There was a decrease in treatment engagement in hospital settings. Changes in healthcare utilisation during HAT translated to a reduction in healthcare costs of 58% within six months compared to the same timeframe from the period directly prior to commencing HAT. ConclusionThis exploratory study highlights the potential for innovative harm reduction interventions such as HAT, co-located with primary care services, to improve healthcare access and engagement for a high-risk population. Increased uptake of primary healthcare services translated to reductions in emergency healthcare use and associated costs. Although costs of HAT provision are substantial, the notable cost-savings in health care should be an important consideration in service implementation planning.

Association between patient activation and delayed discharge in elective laparoscopic cholecystectomy: A prospective cohort analysis

BackgroundImproving patient activation may be an effective way to reduce healthcare costs and improve patient outcomes after surgery. ObjectiveTo determine whether preoperative patient activation is associated with delayed discharge (i.e., length of stay >24 h) after elective laparoscopic cholecystectomy. Postoperative symptoms, unscheduled access to healthcare facilities within seven days of surgery, unplanned hospital readmissions, and postoperative complications were analyzed as secondary outcomes. DesignThis cohort study was a secondary analysis of the DeDiLaCo study (Delayed Discharge after day-surgery Laparoscopic Cholecystectomy) collecting data of patients undergoing elective laparoscopic cholecystectomy during 2021 in Italy. Data was analyzed from June 2022 to April 2023. Setting90 Italian surgical centers participating in the study. Participants4708 adult patients with an instrumental diagnosis of gallbladder disease and undergoing laparoscopic cholecystectomy. Patient activation was assessed using the Italian translation of Patient Activation Measure in the preoperative setting. ResultsOf 4532 cases analyzed the median (IQR) Patient Activation Measure score was 80.3 (71.2–92.3). Participants were on average 55.5 years of age and 58.1 % were female. Two groups based on the activation level were created: 270 (6 %) had low activation, and 4262 had high activation. The low activation level was associated with the likelihood of delayed discharge (odds ratio [OR] 1.47, 95 % CI, 1.11–1.95; P = .008), higher symptom burden (OR 1.99, 95 % CI 1.49–2.66, P < .0001), and unplanned healthcare utilization within seven days after hospital discharge (OR 1.85, 95 % CI, 1.29–2.63; P = .001). There was no difference between the high and low activation groups in the incidence of postoperative complications (OR 1.28, 95 % CI, 0.95–1.73; P = .10) and hospital readmission after discharge (OR 0.95, 95 % CI, 0.30–3.05; P = .93). ConclusionsOur results suggest that patients with low activation have 1.47 times the risk of delayed discharge compared with patients with higher activation, almost twice the risk of the onset of postoperative symptoms, and 1.85 times the risk of unscheduled use of hospital services. Screening for patient activation in the preoperative setting could not only identify patients not suitable for early discharge, but more importantly, help physicians and nurses develop tailored interventions.

Exploring Eating Habits, Healthy Food Awareness, and Inclination toward Functional Foods of Italian Elderly People through Computer-Assisted Telephone Interviews (CATIs).

The continuous increase in life expectancy leads to progressive population ageing, especially in most developed countries. A healthy diet and better consumption of tailored functional foods may represent one of the strategies to postpone or slow down age-related decrements, thus increasing healthy ageing and reducing healthcare costs. This research aimed to explore elderly people's (>65 years old) eating habits and assess their awareness of food-health correlation. In total, 511 Italian seniors answered a CATI (computer-assisted telephone interviewing) questionnaire through a deep, telephone interview to collect information about dietary habits, healthy food awareness, and inclination for functional foods. The elderly were divided into four groups according to gender and age: Early Elderly Female (n = 130), Early Elderly Men (n = 109), Late Elderly Female (n = 157), and Late Elderly Men (n = 115). The groups provided a positive self-assessment of health status and individual diet healthiness, which were both considered over "good enough" (5 on 10-point scale) and showed food consumption habits in line with the Mediterranean Diet (MD) principles. The daily diet was based on fruits, vegetables, bread, and pasta, with extra virgin olive oil as the main fat source, all over "often" consumed (4 on 5-point scale). Old people also showed awareness of different food's healthy properties. Specifically, females were more aware of food's impact on health, considered close to "extremely healthy" (9 on 10-point scale), and strictly followed a MD. Participants also expressed optimistic expectations about functional food efficiency, evaluated as close to "extremely desirable" (8 or 9 on 10-point scale), against age-related problems, highlighting the most important as diabetes, overweight, intestine problems, and low mood. The interviewed elderly were also involved in virtual functional food co-creation, indicating through a basic matrix which, among the most familiar foods, could be the ideal functional food, focusing on fruitsand vegetables. A pleasant odor/flavor, a liquid texture, and a warm serving temperature rather than cold characterized the virtual functional food created. Other positive attributes were liquid and thickness, while acidity and bitterness were among the least desired traits. These findings show how elderly people, despite predictable age-related sensory and cognitive loss, when properly involved and guided, can help envision foods that fit their needs and desires.

Non-adherence to anti-tuberculosis treatment and associated factors among TB patients in public health facilities of Hossana town, Southern Ethiopia, 2022.

Non-adherence to anti-tuberculosis treatment is one of the crucial challenges to improving TB treatment outcomes and reducing healthcare costs. The prevalence of non-adherence to anti-tuberculosis treatment is not well documented in the study context. Therefore, this study was aimed at estimating the prevalence of non-adherence to anti-tuberculosis treatment and associated factors among TB patients attending TB clinics in Hosanna town, Southern Ethiopia, in 2022. An institution-based cross-sectional study was conducted from April to May 2022. A systematic random sampling technique was employed to select a sample of 233 study subjects from all four public health facilities. According to the order of arrival, every second person was interviewed. Data were collected using a structured questionnaire that was created using several works of literature. A multivariable binary logistic regression analysis was used to identify factors associated with non-adherence to anti-TB drugs. The adjusted odds ratio (AOR) with a 95% confidence interval (CI) was estimated. The study included 233 tuberculosis (TB) patients with a response rate of 100%. The prevalence of non-adherence was 18% (95% CI: 15.39, 21.82). Being in the continuation phase (AOR = 3.09, 95% CI: 1.16, 8.23), not attending formal education (AOR = 2.47, 95% CI: 1.12, 5.42), not disclosing TB status to their family (AOR = 2.36, 95% CI: 0.11, 5.04) and having poor TB knowledge (AOR = 3.09, 95% CI: 1.48, 6.48) were significantly associated with non-adherence to TB treatment. Among TB patients, there was a significant prevalence of non-adherence to anti-TB medications. Interventions that target patients with low education status, are in the continuation phase, and do not disclose their TB status to their families are required to improve TB treatment adherence. In addition, improving health education is important to enhance TB knowledge, which has an impact on TB treatment adherence. The need for good drug adherence should be emphasized while counseling TB patients.

Association between Ustekinumab Trough Levels, Serum IL-22, and Oncostatin M Levels and Clinical and Biochemical Outcomes in Patients with Crohn's Disease.

Background: Ustekinumab (UST) has demonstrated effectiveness in treating patients with Crohn's disease. Monitoring treatment response can improve disease management and reduce healthcare costs. We investigated whether UST trough levels (TLs), serum IL22, and Oncostatin M (OSM) levels could be early indicators of non-response by analysing their correlation with clinical and biochemical outcomes in CD. Methods: Patients with CD initiating UST treatment from October 2018 to September 2020 were enrolled at six Italian centres for inflammatory bowel disease (IBD). Clinical and biochemical data were collected at four time points: baseline, second subcutaneous (SC) dose, fourth SC dose, and 52 weeks. TLs were measured during maintenance, at the second SC dose, and at the fourth SC dose. IL-22 and OSM serum levels were assessed at baseline and the second SC dose. We analysed whether TLs, IL22 levels, and OSM serum levels were associated with clinical response, clinical remission, biochemical remission, and endoscopic remission using the appropriate statistical tests. Results: Out of eighty-four initially enrolled patients, five were lost to follow-up, and eleven discontinued the drug before 52 weeks. At the 52-week time point, 47% achieved biochemical remission based on faecal calprotectin levels, and 61.8% achieved clinical remission. TLs at the second SC dose significantly correlated with biochemical remission at the same time point (p = 0.011). However, TLs did not correlate with clinical remission. Baseline OSM levels did not correlate with biochemical or clinical remission or response. IL22 levels notably decreased during UST therapy (p = 0.000), but its values did not correlate with biochemical or clinical remission. Conclusions: UST is an effective therapy for patients with CD. TLs measured at the second SC dose significantly correlated with biochemical remission, emphasising their potential role in treatment monitoring. Levels of OSM and IL-22, despite a significant decrease in the latter during therapy, did not exhibit correlations with clinical or biochemical outcomes in our study. Further studies are needed to confirm these findings.

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence: A Critical Analysis Review.

» The application of artificial intelligence (AI) in the field of orthopaedic surgery holds potential for revolutionizing health care delivery across 3 crucial domains: (I) personalized prediction of clinical outcomes and adverse events, which may optimize patient selection, surgical planning, and enhance patient safety and outcomes; (II) diagnostic automated and semiautomated imaging analyses, which may reduce time burden and facilitate precise and timely diagnoses; and (III) forecasting of resource utilization, which may reduce health care costs and increase value for patients and institutions.» Computer vision is one of the most highly studied areas of AI within orthopaedics, with applications pertaining to fracture classification, identification of the manufacturer and model of prosthetic implants, and surveillance of prosthesis loosening and failure.» Prognostic applications of AI within orthopaedics include identifying patients who will likely benefit from a specified treatment, predicting prosthetic implant size, postoperative length of stay, discharge disposition, and surgical complications. Not only may these applications be beneficial to patients but also to institutions and payors because they may inform potential cost expenditure, improve overall hospital efficiency, and help anticipate resource utilization.» AI infrastructure development requires institutional financial commitment and a team of clinicians and data scientists with expertise in AI that can complement skill sets and knowledge. Once a team is established and a goal is determined, teams (1) obtain, curate, and label data; (2) establish a reference standard; (3) develop an AI model; (4) evaluate the performance of the AI model; (5) externally validate the model, and (6) reinforce, improve, and evaluate the model's performance until clinical implementation is possible.» Understanding the implications of AI in orthopaedics may eventually lead to wide-ranging improvements in patient care. However, AI, while holding tremendous promise, is not without methodological and ethical limitations that are essential to address. First, it is important to ensure external validity of programs before their use in a clinical setting. Investigators should maintain high quality data records and registry surveillance, exercise caution when evaluating others' reported AI applications, and increase transparency of the methodological conduct of current models to improve external validity and avoid propagating bias. By addressing these challenges and responsibly embracing the potential of AI, the medical field may eventually be able to harness its power to improve patient care and outcomes.

Impact of evidence-based guidelines on healthcare utilisation and costs for disc related sciatica in the Netherlands: a population-based, cross-sectional study

ObjectiveThe aim of this study was to assess the impact of high-quality evidence supporting surgical treatment of lumbar disc herniation (LDH) on healthcare practice in the Netherlands by examining changes...

The role of registries in improving health and bridging healthcare, research, education, innovation and development: a research department perspective.

Health registries are organized systems that collect data on individuals with a particular disease, condition or exposure. The aim of this narrative review was to provide an integrated perspective from the Research Department at the Hospital Italiano de Buenos Aires, Argentina, on how health registries can be used as a bridge between healthcare, research, education, innovation and development while addressing ethical challenges. The review includes a description of the experience of a registry implemented at our institution, which has provided healthcare for 170 years, and is committed to support, education and research. We focus on the potential of health registries to provide better value healthcare by reducing healthcare costs and improving health outcomes and quality of care, and to improve medical knowledge. However, we also acknowledge and discuss the challenges that accompany these achievements, such as that of ethical issues. Through effective collaboration and integration with other healthcare stakeholders, health registries can be a powerful tool to promote better health.

The Role of Healthcare Managers in Employee Retention: Do Workers Leave Organizations or Managers?

Healthcare organizations have been facing employee retention challenges since before the Covid-19 pandemic. This latter has solely accelerated turnover rates. Healthcare managers and leaders need to take action to keep their talent while still delivering quality care. The purpose of this paper is to provide a literature review on the subject to examine the role of healthcare managers in employee retention. Understanding how managers influence staff retention is essential to monitoring turnover rates and designing effective strategies for retaining skilled and talented healthcare employees. The findings of this review indicated that healthcare employees who were satisfied with the behavior of their managers were committed to their organization and more likely to remain employed for a long period. Communication, autonomy, respect and recognition, and training and development were significant predictors of job satisfaction, organizational commitment, and staff retention. Improving staff retention strategies is critical to improving the quality of care, reducing healthcare costs, and achieving growth and success. The review concluded that healthcare managers play a crucial role in employee retention. Further exploration of the employee retention challenge is required to better understand this multifaceted area of human resource management.

Implementation of value-based healthcare in ophthalmology: a scoping review

ObjectiveThis review aimed to identify and summarise how value-based healthcare (VBHC) is implemented in the field of ophthalmology.MethodsA scoping review was conducted by searching empirical and non-empirical articles from from...

Coordination of Care to Meet the Quadruple Aim

Coordination of medical services is not a novel framework for reducing healthcare costs while improving patient outcomes and experiences. Nevertheless, this goal has been found to be difficult to enact in practice. The implementation of effective care coordination faces a myriad of challenges: monitoring, sharing, and responding promptly to changes in a patient’s health status; ensuring clear and transparent communication with patients and caregivers; and addressing social determinants of health. As the adult population of the United States continues to get older, the number of patients with multiple chronic conditions is expected to increase drastically, providing a greater imperative for effective care coordination within the medical infrastructure.

Smart Watches Lack Skin Smarts: Current and Future Dermatologic Applications in Device Metrics.

Smartwatches have proven life-saving in medical specialties such as cardiology. Smartwatches actively warn us of arrhythmia risk and loud noise exposure. However, dermatologic health metrics are rarely monitored, and users are never alerted of potential skin health issues. Furthermore, the role of these devices within dermatology has not been evaluated in the literature. This study aims to analyze the current data points monitored by smartwatches and discuss potential adaptations to support dermatologic patient education and improve clinical management. Methods: The top three smartwatches per global market share were identified and analyzed to determine the health data points they monitor and the alerts they provide. These data points were grouped and compared based on their corresponding body systems. Results: Cardiovascular health comprises the highest percentage of data points collected with an average of 41% while dermatologic health averaged only 11%. Conclusion: Dermatology is grossly underrepresented in current smartwatch devices. There is an important need to expand the dermatologic health metrics tracked by adapting existing smartwatch technology. From proactive cancer prevention to disease-specific reactive interventions, smartwatches can play a significant role in improving dermatological health and reducing healthcare costs.