Dissertations / Theses on the topic 'Redness for surgery operations'

Module for testing process mental and emotional state of patient allows for medical psychologist can assistance him. Psychologist knows the plan of his work with the patient, taking into account all specific stages of surgical care. The obtained results show the need for using integrated indicators in assessing readiness patients for surgical operations

This study details the creation of two Simulat1on models for a cardiac surgery specialty in a Midlands hospital The models were designed to help the specialty meet waiting time targets set out by the Government in their NHS Plan. The first model is a spreadsheet data Simulation that gives a general prediction of patients waiting for surgery by time band for up to a year in the future based on previous data. The study uses the qualitative analysis of Interviews and documents to generate the second model The first part of this model is a qualitative causal loop diagram of the cardiac surgery system A quantitative 'Stock & Flow' model is drawn from this qualitative model which gives detailed predict1ons of waiting lists and times and other system variables for the cardiac surgery specialty The system dynamics model is validated it can estimate the maximum number of new outpatient attendances the system can support whilst keeping inpatient waiting times below three months for various configurations of theatre time and Cardiac lntensive Care Unit (CICU) beds The study concludes that CICU beds are a bigger constraint on inpatient waiting times in the cardiac surgery specialty at the hospital than theatre time. Measures to improve waiting times and shorten lists should therefore concentrate on improving patient flow through the CICU, for example more beds in the unit would enable more patients to be treated The model can also demonstrate the use of the theory of constraints in managing waiting lists, which is the method used by the NHS Modernisation Agency in their guidance on wait1ng list management.

Background: Hernia emergencies common surgery. Around 20 million groin hernia operations occur world-wide, and these form 70% of all hernia operations. Incisional hernias complicate 15- 30% of laparotomies and 20% of these present as emergencies. Watchful waiting is often applied for groin, ventral and incisional hernias in patients who are asymptomatic or those who are poor surgical candidates. The factors associated with poor outcomes include - elderly patients, multiple comorbidities, delays in presentation, those which are incarcerated or strangulated and delays in getting to theatre. Management of emergency hernias include resuscitative efforts to address life threatening problems, and thereafter performing the safest and most durable repairs. Aim: We aim to elucidate patient and health care systems factors that contribute to hernia emergency presentations and to document the mortality and morbidity of such presentations in our unit. Method: We aim to review case files of all patients above 18 years of age who had their emergency surgery for a complicated hernia. All elective cases will be excluded. Conclusion: This study will contribute to understanding emergency hernias in south Africa and will seek to improve patient care in our setting. A hernia registry has recently been established and thus we will be able to contribute to its foundation.

Objectives: The thesis seeks to provide an analysis of surgical work and decision making, to identify the basis of the widely observed variation in surgical practice and to indicate what surgeons see as the source(s) of that variation. Against this background, it examines the strengths and limitations of the approach promoted by the evidence-based medicine movement to surgical work. Methods: A qualitative study of surgical practice by urological and gynaecological surgeons in England and the USA involved in the treatment of female urinary stress incontinence. Depth interviews with 29 English surgeons and five American surgeons. Interviews were recorded and transcribed. Observation of 23 operations and additional ethnographic data collection at the hospitals and clinics where these surgeons worked. The observational data consist of near verbatim notes. All these data were analysed using the constant comparative approach described by Glaser and Strauss (1967). A variant of the split-half technique was used to test emerging themes. Results: Surgical practice is contingent: it is dependent on a range of variables, and, it is serendipitous. Three categories of contingency are identified (case, surgeon and external contingency). It is argued that surgical practice entails the complex interplay of these conditional factors and chance happenings. In order to learn to deal with contingency, surgeons learn or acquire practice skills through first hand experience. The thesis explores the role of the surgical apprenticeship and models of learning used by surgeons. Conclusion: The nature of surgical practice presents some fundamental challenges to EBM. The contingent and experiential features of surgical work raise serious doubts about the applicability of EBM to surgery.

Background: In light of the opioid epidemic, reducing excess prescription quantities while tailoring to patient need is key. We previously created an opioid prescribing guideline using retrospective institutional data to satisfy the majority of patients’ opioid needs following inpatient colorectal surgery. Objective: This study sought to prospectively validate an institutional prescribing guideline based on previously-defined opioid consumption patterns following inpatient colorectal operations. Methods: We carried out a cohort study comparing opioid prescribing and consumption patterns before (7/18 – 1/19) and after (9/19 – 2/20) adoption of a tiered opioid prescribing guideline for inpatient elective colorectal operations (colectomies, proctectomies, and ostomy reversals) at a single tertiary care medical center. Opioid use was quantified as Equianalgesic 5mg Oxycodone Pills (EOP), and patients were grouped in three tiers based on opioid consumption in the 24-hours prior to discharge: Tier 1 (0 EOP), Tier 2 (0.1-3 EOP), and Tier 3 (>3 EOP). Our guideline recommended maximum prescriptions of 0 EOP for Tier 1, 12 EOP for Tier 2, and 30 EOP for Tier 3. Results: The study included 100 patients before and 101 after guideline adoption. Demographic and operative variables were similar before and after guideline adoption. Guideline adherence was 85%. Overall, there was a 41% reduction in mean prescription quantity and 53% reduction in excess pills per prescription with no change in opioid consumption or refill rates. Conclusion: Adoption of a tiered opioid prescribing guideline significantly reduced opioid prescription quantity with no change in consumption or refill rates. Standardization of discharge prescriptions based on patient consumption in the 24 hours prior to discharge may be an important step towards minimizing excess prescribing.

Health improvement and financial ruin are often inexorably linked. Nearly 30% of the global burden of disease is surgical [1], and over 30 million annual cases of financial ruin are attributable to accessing surgery [2]. In resource-poor countries, where 70% of all healthcare spending is out-of-pocket [3], catastrophic expenditure for medical care is extremely common [4-6]. In the United States, even those with health insurance face financial catastrophe: nearly two-thirds of bankruptcy is medical, and fully 75% of medically bankrupt individuals were insured at the time of their catastrophic medical bill [7]. Financial ruin is most pronounced among the global poor, among patients with life-threatening conditions, and, increasingly, among the elderly [2, 8-10]. As a result, although the World Health Organization [11], the United Nations [12], and the World Bank [13] have all called for financial risk protection in healthcare, medical impoverishment persists, sometimes forcing individuals into a choice between physical health and financial health. Some choose the former and are willing to incur financial ruin to get care: they sell their assets, borrow, decrease consumption, or, catastrophically, face impoverishment in the pursuit of health [4-6, 14-28]. Others respond to a risk of poverty by not complying with physician recommendations, by seeking alternate providers, or by forgoing care altogether [29-34]. In patients with serious conditions, these choices can be lethal [32, 35]. In the US, national health policy has consistently focused on decreasing out-of-pocket medical costs as a mechanism for health improvement—and not always successfully: two years after the initiation of the Oregon Medicaid expansion, for example, health outcomes had not changed dramatically [36]. Globally, policies to improve access to surgical care either mirror this demand-side focus on out-of-pocket cost reduction or address the supply-side dearth of surgical providers through policies such as task shifting [37-39]. The goal of this dissertation, then, is to examine the effects of these policies and platforms for global surgical delivery on health, on impoverishment, and on inequity, and to determine how individuals value tradeoffs among these outcomes. Chapter 1 investigates the role of government policies for increasing surgical access in public hospitals. This extended cost-effectiveness analysis utilizes publicly available data from Ethiopia to evaluate the health, financial, and equity impacts of nine essential surgical procedures on rural patients. Five policies addressing supply- and demand-side barriers to surgical access are examined: 1) universal public financing (UPF), 2) task shifting (TS), 3) UPF with the addition of vouchers (V) to address the nonmedical costs of care, 4) UPF + TS, and 5) UPF + TS + V. I find that, while all policies are likely to improve health, a tradeoff exists: TS averts deaths most dramatically, but does so at the cost of a large increase in financial catastrophe. UPF is more financially risk protective, but has a much smaller impact on health. Only policies that include vouchers for the non-medical costs of accessing care are found to provide an equitable distribution of benefits; the remaining policies continue to impoverish the poor. Chapter 2 compares surgical delivery by charitable organizations with the governmental policies examined in Chapter 1. Using an agent-based model of cancer care in Uganda, the three common charitable platforms for surgical delivery—two-week “mission trips”, mobile surgical units, and free-standing specialty hospitals—are evaluated against combinations of UPF, TS, and V. In addition to health and catastrophic expenditure, two novel metrics are included to 1) incorporate the familial financial impact of a lack of access and 2) formalize the equitable distribution of benefits into a concentration index. I find that mobile surgical delivery platforms by non-governmental organizations can provide health and financial benefits equitably and efficiently and that they perform well when compared to health-system-strengthening policies. Other charitable platforms are equitable but are not efficient when compared with government policies. The results of this analysis also confirm the finding from Chapter 1 that equitable delivery platforms must address the non-medical costs associated with getting to care. Chapter 3 tests the hypothesis that, in the setting of lethal disease, individuals value cure at all costs. A discrete choice experiment is undertaken in a nationally representative US sample of 2359 individuals. Respondents are asked to choose between two hypothetical treatments for a lethal disease, differing only in their chance of cure and their risk of bankruptcy. I find that the resulting indifference curve is multiplicative, and that Americans are less willing to shoulder high risks of bankruptcy to increase their probability of cure than has been previously assumed. Subgroup and sensitivity analyses do not alter this relationship, although, in some groups, the difference in preference between bankruptcy protection and cure is not statistically significant. In no subgroup, however, do I find evidence a significant preference for cure at any cost in the American population.
Health Policy

If I asked you to think of the riskiest, most serious surgery you can imagine, there’s a good chance the operation that first came to mind would fall into one of two categories: heart surgery or brain surgery. When these oragans are damaged by an injury or disease, the effects may be severe – and the implications of performing surgery on these organs can be grave. Medical breakthroughs are allowing doctors to treat conditions that once required risky surgeries with non-surgical procedures. From catheters to ultrasound beams, these new devices and techniques make real impacts on patients.

In a systematic review and random effects meta-analysis, we evaluated whether obesity is associated with postoperative atrial fibrillation (POAF) in patients undergoing cardiac surgery. Eighteen observational studies that excluded patients with preoperative AF were selected until December 2011 (n=36,147). Obese patients had a modest higher risk of POAF in comparison to non-obese (OR 1.12, 95%CI 1.04-1.21, p=0.002). The association between obesity and POAF did not vary substantially by type of cardiac surgery, study design or year of publication. POAF was significantly associated with higher risk of stroke, respiratory failure, and operative mortality.
Revisión por pares

Abstract The perioperative operating room (OR) is a highly complex, fast-paced environment where countless transactions must be executed with efficiency, speed, and accuracy, and where mistakes of any kind could lead to adverse patient outcome, injury, or death. The surgeon, as leader of the procedure and the OR team, sets the overall climate of the OR and determines how willing (or unwilling) team members are to speak up about potential errors or unsafe patient conditions. This exploration of the relationship between perioperative surgeon leadership style and OR team member job satisfaction fills a gap unaddressed in the literature using items from The Multifactor Leadership Questionnaire (MLQ) and the Safety Attitudes Questionnaire- OR version (SAQ-OR). The MLQ has been used to confirm the intersection of transformational leadership style and positive team behavior in the perioperative surgical OR. The SAQ has proven reliable and valid in the OR for the domain of job satisfaction as measured by OR team members. In this study, 227 OR team members were recruited from LinkedIn professional groups and Facebook groups and completed an electronic survey. Data were analyzed using multifactor regression analyses. Results indicated that passive avoidant surgeon leadership style had the only significant relationship to OR team member job satisfaction. The importance of this study is apparent in findings suggesting that when leaders work to improve their interactions in ways that increase team members' job satisfaction, they improve team members' health, well-being, and overall life satisfaction.

Le système perceptif d’un chirurgien doit s’adapter aux contraintes multisensorielles liées à la chirurgie guidée par l’image. Trois expériences sont conçues pour explorer ces contraintes visuelles et haptiques pour l’apprentissage guidé par l’image. Les résultats montrent que les sujets sont plus rapides et plus précis avec une vision directe. La stéréoscopie 3D n’améliore pas les performances des débutants complets. En réalité virtuelle, la variation de la longueur, largeur, position et complexité de l'objet affecte les performances motrices. La force de préhension appliquée sur un système robotique chirurgical dépend de l'expérience de l'utilisateur. En conclusion, le temps et la précision sont importants, mais la précision doit rester une priorité pour un apprenti. L'homogénéité des groupes d'étude est important pour la recherche sur la formation chirurgicale. Les résultats ont un impact direct sur le suivi des compétences individuelles pour les applications guidées par l'image
Perceptual system of a surgeon must adapt to conditions of multisensorial constrains regard to planning, control, and execution of the image-guided surgical operations. Three experimental setups are designed to explore these visual and haptic constraints in the image-guided training. Results show that subjects are faster and more precise with direct vision compared to image guidance. Stereoscopic 3D viewing does not represent a performance advantage for complete beginners. In virtual reality, variation in object length, width, position, and complexity affect the motor performance. Applied grip force on a surgical robot system depends on the user experience level. In conclusion, both time and precision matter critically, but trainee gets as precise as possible before getting faster should be a priority. Study group homogeneity and background play key role in surgical training research. The findings have direct implications for individual skill monitoring for image-guided applications

Questa tesi riguarda il problema della schedulazione degli interventi nel blocco operatorio di un presidio ospedaliero, noto anche come Operating Theatre Planning & Scheduling. Il blocco operatorio è la struttura che eroga servizi a più alto impatto sui costi di un presidio ospedaliero ed è legato ad attività ad alto rischio. E' quindi fondamentale gestire in modo ottimale questa risorsa. In questa tesi, si considera come caso studio l'applicazione reale di un presidio ospedaliero dell'Emilia Romagna con un orizzonte temporale di una settimana, ovvero la cosiddetta programmazione operativa. L'obiettivo è quello di ottenere un utilizzo efficiente del blocco operatorio, garantendo al contempo la priorità agli interventi più urgenti. Data la complessità del problema, vengono proposti algoritmi euristici che permettano di ottenere buone soluzioni in tempi di calcolo ridotti. Studi precedenti hanno infatti evidenziato la difficoltà di trovare soluzioni ottime al problema, mediante l'utilizzo di solver commerciali per modelli di Programmazione Lineare Intera, senza introdurre ipotesi semplificative. Sono stati elaborati tre algoritmi euristici costruttivi di tipo multi-start che permettono di generare soluzioni ammissibili con diverse caratteristiche. Gli algoritmi si differenziano principalmente per le modalità con cui collocano gli interventi nel tempo disponibile delle risorse (induction room, operating room, recovery room), cercando di migliorarne l’utilizzazione e dando priorità ai pazienti più urgenti. Gli algoritmi sono stati implementati utilizzando il linguaggio JAVA e sono stati testati su istanze realistiche fornite dal presidio ospedaliero. I risultati hanno evidenziato un alto grado di utilizzazione delle sale operatorie, un fattore molto rilevante per una ottimale gestione del blocco operatorio. E' stata, infine, svolta un'analisi di sensitività alla variabilità delle durate.

Knowledge of The Joint Commission's National Patient Safety Goals and an effective provider cooperative practice involving communication and teamwork are essential for the delivery of safe and compliant patient care in the surgical setting. The purpose of this study was to assess the impact of an educational intervention for physicians and nurses designed to increase documentation of compliance with national patient safety standards. As events of noncompliance have impacted patient safety at the hospital where this project was conducted, measures were needed to assess barriers to compliance with standards of practice and to focus educational session plans on identified knowledge-base needs. The goal of this project involved bringing all surgical team members together for educational sessions on safety standards. Pre-intervention and post-intervention assessments of knowledge were administered to study participants. Additionally, random chart documentation audits were conducted before and after the intervention to assess the effectiveness of the education sessions on documentation compliance with the targeted standards. Outcomes of this study included improved knowledge of, and compliance with, national patient safety goals. Results may improve safe patient care at this hospital, reduce costs, and create mutual respect and teamwork, all contributing to the successful achievement of the organization's quality improvement goals.

abstract: Optimization of surgical operations is a challenging managerial problem for surgical suite directors. This dissertation presents modeling and solution techniques for operating room (OR) planning and scheduling problems. First, several sequencing and patient appointment time setting heuristics are proposed for scheduling an Outpatient Procedure Center. A discrete event simulation model is used to evaluate how scheduling heuristics perform with respect to the competing criteria of expected patient waiting time and expected surgical suite overtime for a single day compared to current practice. Next, a bi-criteria Genetic Algorithm is used to determine if better solutions can be obtained for this single day scheduling problem. The efficacy of the bi-criteria Genetic Algorithm, when surgeries are allowed to be moved to other days, is investigated. Numerical experiments based on real data from a large health care provider are presented. The analysis provides insight into the best scheduling heuristics, and the tradeoff between patient and health care provider based criteria. Second, a multi-stage stochastic mixed integer programming formulation for the allocation of surgeries to ORs over a finite planning horizon is studied. The demand for surgery and surgical duration are random variables. The objective is to minimize two competing criteria: expected surgery cancellations and OR overtime. A decomposition method, Progressive Hedging, is implemented to find near optimal surgery plans. Finally, properties of the model are discussed and methods are proposed to improve the performance of the algorithm based on the special structure of the model. It is found simple rules can improve schedules used in practice. Sequencing surgeries from the longest to shortest mean duration causes high expected overtime, and should be avoided, while sequencing from the shortest to longest mean duration performed quite well in our experiments. Expending greater computational effort with more sophisticated optimization methods does not lead to substantial improvements. However, controlling daily procedure mix may achieve substantial improvements in performance. A novel stochastic programming model for a dynamic surgery planning problem is proposed in the dissertation. The efficacy of the progressive hedging algorithm is investigated. It is found there is a significant correlation between the performance of the algorithm and type and number of scenario bundles in a problem instance. The computational time spent to solve scenario subproblems is among the most significant factors that impact the performance of the algorithm. The quality of the solutions can be improved by detecting and preventing cyclical behaviors.
Dissertation/Thesis
Ph.D. Industrial Engineering 2010

碩士
德明財經科技大學
資訊科技與管理研究所
101
ICD-10-CM is the 10th revision of the International Classification of Diseases, and it is commonly used by most industrialized countries, including mainland China. Although the United States of America has not introduced ICD-10 for disease coding yet, but the act has passed the congress which will eventually be effective at October 1st, 2014. If we keep using the out dated ICD-9-CM as our disease classification system, we will face more difficulties on data exchanging with other countries, resulting in a less accurate, out dated database of health care. This article is focused on graphical analysis, enhancing the relation between the 2nd code (Body System) and the 4th code (Body Part), adjusting the order of the 3rd (Operation) and the 4th code, limiting the choice of the 3rd code with the 4th code. This will result in a better accuracy of the 3rd code. As for satisfaction, the Cronbach’s Alpha is larger than 0.5, which is acceptable. All subjects of the test agreed that the system is able to help the coding work.

With increased availability of data in various fields, researchers often need to combine efficient empirical methods with innovative analytical modeling techniques to make data-driven decisions and gain managerial insights from the large-scale raw data. In light of this, my thesis combines empirical methods and analytical modeling to study several data-related problems in the fields of financial economics and healthcare management. The first two parts of the thesis focus on two topics in financial economics: the role of dynamic information in asset pricing and the link between index-based investment and intraday stock dynamics. The last two parts of the thesis study the ICU admission decisions and cardiac surgery scheduling using data from different hospital units. The first part of the thesis focuses on the role of information in financial market. As a fundamental topic in asset pricing, information is known to play an important role in determining asset prices and market volatility. In most of the existing literature, the information environment, i.e., the amount of knowable information, is assumed to be fixed and independent of investor's choice. However, in a dynamic market, the level of available information can vary substantially due to changes in technology and regulations. On the other hand, rational news producers may respond to investors' demand for information. Such effects are commonly seen in the reality, but are less studied in the literature. To bridge this gap, we develop a model of investor information choices and asset prices where the availability of information about fundamentals is time-varying. A competitive research sector produces more information when more investors are willing to pay for that research. This feedback, from investor willingness to pay for information to more information production, generates two regimes in equilibrium, one having high prices and low volatility, the other the opposite. Information dynamics move the market between regimes, creating large price drops even with no change in fundamentals. In our calibration, the model suggests an important role for information dynamics in financial crises. In the second part of this thesis, we investigate how the growth of index-based investing impacts the intraday stock dynamics using a large high-frequency dataset, which consists of 1-second level trade data for all S&P 500 constituents from 2004 to 2018 (500GB). We estimate intraday trading volume, volatility, correlation, and beta using estimators that are statistically efficient under market microstructure noise and observation asynchronicity. We find the intraday patterns indeed change substantially over time. For example, in the recent decade, the trading volume and correlation significantly increase at the end of trading session; the betas of different stocks start dispersed in the morning, but generally move towards one during the day. Besides, the daily dispersion in trading volume is high at the market open and low near the market close. These intraday patterns demonstrate the implication of the growth of index-based strategies and the active-open, passive-close intraday trading profile. We theoretically support our interpretation via a market impact model with time-varying liquidity provision from both single-stock and index-fund investors. In the third part of the thesis, we study the intensive care units (ICUs) admission decisions in a large hospital system. In the case of ICUs, which provide the highest level of care for the most severe patients, it is known that admission rates of some patients decrease as occupancy increases. It is also known that, for at least some conditions, ICU admission is not just a function of patients’ illness, and that a significant proportion of the variation in ICU admission rates is due to hospital, not patient, factors. To understand such variation, we employ two years of data from patients admitted to 21 Kaiser Permanente Northern California ICUs from the ED. We quantify the variation in ICU admission from the ED under varying degrees of ICU and ED occupancy. We find that substantial heterogeneity in admission rates is present, and that it cannot be explained either by patient factors or occupancy levels alone. We use a structural model to understand the extent that intertemporal externalities could account for some of this variation. Using counterfactual simulations, we find that, if hospitals had more information regarding their behaviors, and if it were possible to alter hospital admission processes to incorporate such information, hospitals could reduce their ICU congestion in a safe way. The last part of the thesis focuses on the impact of system workload on service time and quality in the context of cardiac surgeries. Using a detailed data set of more than 5,600 cardiac surgeries in a large hospital, we quantify how surgeon's daily workload level (e.g., number of surgeries) affects surgery duration and patient outcomes. To handle the endogeneity of surgeon's daily workload, we construct instrument variables using hospital operational factors, including the block schedule of surgeons. We find high daily workload of surgeons is associated with longer incision times and worse patient outcomes. Specifically, increased daily workload of surgeons leads to longer post-surgery length-of-stay in ICU and hospital, as well as higher likelihoods of reoperation and readmission for their patients. These results highlight the potential negative impact of surgeon's fatigue under long working hours. We then develop a surgery scheduling model that incorporates the effects of surgeon's daily workload levels.