14 research outputs found
The providers of health services in Lebanon: a survey of physicians
BACKGROUND: Emerging from civil distress carries with it major challenges to reforming a health system. One such challenge is to ensure an adequate supply of competent human resources. The objective of this study was to assess the supply of physicians in Lebanon in 1998, with an assessment of their practice patterns and capacity building. METHODS: Lists of members of physician's associations were examined to determine the number of physicians in Lebanon and their geographical distribution. A self-administered survey targeted 388 physicians (5%) randomly stratified by the five regions of Lebanon. Some 377 providers reported information on their demographic profile, practice patterns and development. Further, information on continuing education activities was acquired. RESULTS: In Lebanon, the overall physician-to-population ratio was 248 per 100, 000, characterized by an evident maldistribution at the intracountry regional level. Physicians worked 38 hours per week examining on average 21 patients per day, with an average time of 30 minutes spent per visit. They also reported spending 11% of their time waiting for patients. Respondents reported a very wide range of income, with 90% earning less than USD 2,000 per month. Moreover, the continuing education profile revealed a total of 43.7 hours per year, similar to that required for board certification in many developed countries. Conference attendance was the dominant continuing education activity (95% of respondents) and consumed most of the time allotted for continuing education, reported at 32 hours per year. DISCUSSION AND CONCLUSION: Various economic indicators point to an oversupply of physicians in Lebanon and a poor allocation of their time for capacity building. Therefore, it is crucial for decision-makers to closely monitor the increasing supply of providers and institute appropriate intervention strategies, taking into consideration appropriate provision of good-quality services and ensuring that continuing education activities are well established, organized and monitored
Metabolic syndrome and the likelihood of knee pain and functional disability: evidence from a large middle eastern population-based study
Abstract Objectives Metabolic Syndrome (MetS) has been associated with knee osteoarthritis (KOA) in animal studies, but epidemiologic evidence of the association remains controversial. We investigated the association between MetS and knee pain and functional disability, the hallmarks of KOA, in a Middle Eastern population with high reported MetS rates. Methods A population-based study of adult individuals was conducted between 01/2016 and 03/2019. Data collected included age, sex, blood pressure, body mass index (BMI), waist circumference (WC), and comprehensive metabolic panel blood tests. Knee symptoms were assessed using The Western Ontario and McMaster Arthritis index (WOMAC) The Adult Treatment Panel III criteria was applied to determine if participants had MetS. Multivariable regression was used to determine the association of MetS, and its components, with the WOMAC total and subscale scores. Results Of 6,000 participants enrolled, 15.5% had MetS. The multivariate regression demonstrated that participants with MetS had significantly higher WOMAC total and subscale scores after adjusting for demographic variables; however, these associations were not significant after adjusting for BMI. Multivariate regression examining the association between MetS components and the WOMAC scores showed sex-based significant differences with WOMAC scores; however, the differences were not larger than the minimally clinical important differences. Conclusions This study demonstrated that after adjustment for BMI, neither MetS nor its individual parameters were associated with worse knee symptoms. As such, the association between MetS and worse knee symptoms requires further study
Physician referral patterns and racial disparities in total hip replacement: A network analysis approach.
Efforts to reduce racial disparities in total hip replacement (THR) have focused mainly on patient behaviors. While these efforts are no doubt important, they ignore the potentially important role of provider- and system-level factors, which may be easier to modify. We aimed to determine whether the patterns of interaction among physicians around THR episodes differ in communities with low versus high concentrations of black residents.We analyzed national Medicare claims from 2008 to 2011, identifying all fee-for-service beneficiaries who underwent THR. Based on physician encounter data, we then mapped the physician referral networks at the hospitals where beneficiaries' procedures were performed. Next, we measured two structural properties of these networks that could affect care coordination and information sharing: clustering, and the number of external ties. Finally, we estimated multivariate regression models to determine the relationship between the concentration of black residents in the community [as measured by the hospital service area (HSA)] served by a given network and each of these 2 network properties.Our sample included 336,506 beneficiaries (mean age 76.3 ± SD), 63.1% of whom were women. HSAs with higher concentrations of black residents tended to be more impoverished than those with lower concentrations. While HSAs with higher concentrations of black residents had, on average, more acute care beds and medical specialists, they had fewer surgeons per capita than those with lower concentrations. After adjusting for these differences, we found that HSAs with higher concentrations of black residents were served by physician referral networks that had significantly higher within-network clustering but fewer external ties.We observed differences in the patterns of interaction among physicians around THR episodes in communities with low versus high concentrations of black residents. Studies investigating the impact of these differences on access to quality providers and on THR outcomes are needed
Multivariate models of physician networks and concentration of black residents in U. S. hospitals.
<p>Multivariate models of physician networks and concentration of black residents in U. S. hospitals.</p
Characteristics of HSAs and anchor hospitals in 2011, stratified by the concentration of black residents.
<p>Characteristics of HSAs and anchor hospitals in 2011, stratified by the concentration of black residents.</p
Physician networks in 2 California communities in 2011 with low (A) vs. high (B) concentration of blacks.
<p>(A) Hospital serving fewer black residents in HSA, % black = 0.00, clustering coefficient = 0.39, external ties = 7. (B) Hospital serving more black residents in HSA, % black = 0.13, clustering coefficient = 0.82, external ties = 3.</p
Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy
Abstract When children are discharged from the hospital after surgery, their caregivers often rely on subjective assessments (e.g., appetite, fatigue) to monitor postoperative recovery as objective assessment tools are scarce at home. Such imprecise and one-dimensional evaluations can result in unwarranted emergency department visits or delayed care. To address this gap in postoperative monitoring, we evaluated the ability of a consumer-grade wearable device, Fitbit, which records multimodal data about daily physical activity, heart rate, and sleep, in detecting abnormal recovery early in children recovering after appendectomy. One hundred and sixty-two children, ages 3–17 years old, who underwent an appendectomy (86 complicated and 76 simple cases of appendicitis) wore a Fitbit device on their wrist for 21 days postoperatively. Abnormal recovery events (i.e., abnormal symptoms or confirmed postoperative complications) that arose during this period were gathered from medical records and patient reports. Fitbit-derived measures, as well as demographic and clinical characteristics, were used to train machine learning models to retrospectively detect abnormal recovery in the two days leading up to the event for patients with complicated and simple appendicitis. A balanced random forest classifier accurately detected 83% of these abnormal recovery days in complicated appendicitis and 70% of abnormal recovery days in simple appendicitis prior to the true report of a symptom/complication. These results support the development of machine learning algorithms to predict onset of abnormal symptoms and complications in children undergoing surgery, and the use of consumer wearables as monitoring tools for early detection of postoperative events
2023 American College of Rheumatology and American Association of Hip and Knee Surgeons Clinical Practice Guideline for the Optimal Timing of Elective Hip or Knee Arthroplasty for Patients With Symptomatic Moderate-to-Severe Osteoarthritis or Advanced Symptomatic Osteonecrosis With Secondary Arthritis for Whom Nonoperative Therapy Is Ineffective
OBJECTIVE: To develop evidence-based consensus recommendations for the optimal timing of hip and knee arthroplasty to improve patient-important outcomes including, but not limited to, pain, function, infection, hospitalization, and death at 1 year for patients with symptomatic and radiographic moderate-to-severe osteoarthritis or advanced symptomatic osteonecrosis with secondary arthritis of the hip or knee who have previously attempted nonoperative therapy, and for whom nonoperative therapy was ineffective, and who have chosen to undergo elective hip or knee arthroplasty (collectively referred to as TJA). METHODS: We developed 13 clinically relevant population, intervention, comparator, outcomes (PICO) questions. After a systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used to rate the quality of evidence (high, moderate, low, or very low), and evidence tables were created. A Voting Panel, including 13 physicians and patients, discussed the PICO questions until consensus was achieved on the direction (for/against) and strength (strong/conditional) of the recommendations. RESULTS: The panel conditionally recommended against delaying TJA to pursue additional nonoperative treatment including physical therapy, nonsteroidal antiinflammatory drugs, ambulatory aids, and intraarticular injections. It conditionally recommended delaying TJA for nicotine reduction or cessation. The panel conditionally recommended delay for better glycemic control for patients who have diabetes mellitus, although no specific measure or level was identified. There was consensus that obesity by itself was not a reason for delay, but that weight loss should be strongly encouraged, and the increase in operative risk should be discussed. The panel conditionally recommended against delay in patients who have severe deformity or bone loss, or in patients who have a neuropathic joint. Evidence for all recommendations was graded as low or very low quality. CONCLUSION: This guideline provides evidence-based recommendations regarding the optimal timing of TJA in patients who have symptomatic and radiographic moderate-to-severe osteoarthritis or advanced symptomatic osteonecrosis with secondary arthritis for whom nonoperative therapy was ineffective to improve patient-important outcomes, including pain, function, infection, hospitalization, and death at 1 year. We acknowledge that the evidence is of low quality primarily due to indirectness and hope future research will allow for further refinement of the recommendations