Assessment of time management practice and associated factors among primary hospitals employees in north Gondar, northwest Ethiopia.

BACKGROUND: Time management practice can facilitate productivity and success, contributing to work effectiveness, maintaining balance and job satisfaction. Thus, this study aimed to assess time management practices and associated factors among employees of primary hospitals in north Gondar. METHODS: An Institutional based cross-sectional study among primary hospital employees in north Gondar was conducted from March to April 2018. A structured and pre-tested questionnaire was used to collect the data. Simple random sampling technique was utilized to select 422 employees. Bivariate and multivariate logistic regression model were done to identify factors associated with time management practice. Adjusted odds ratio (AOR) with a 95% confidence interval (CI) was ascertained to show the strength and direction of association. RESULT: In this study, the prevalence of time management practice was 56.4% (95%CI: 49.3, 61.7). Being satisfied with organizational policies (AOR = 2.16; 95%CI: 1.02-4.68), performance appraisals (AOR: 2.11; 95%CI: 1.32-4.66), compensation and benefits (AOR: 4.18; 95%CI: 2.18-7.99), and planning (AOR: 2.86; 95% CI: 1.42-5.75) were statistically significant factors associated with time management practice. CONCLUSION AND RECOMMENDATION: The overall time management practice among the primary hospital employees was low. Planning, organizational policy, compensation and benefit, performance appraisal, and residence were factors significantly associated with hospital employee's time management practice. Thus managers and employees need to carry out interventions on significant factors to improve the employees' time management practice.

Using operating room turnover time by anesthesia trainee level to assess improving systems-based practice milestones.

BACKGROUND: Operating room (OR) metrics are frequently cited when optimizing cost efficacy and quality of care (Weiss et al, Characteristics of operating room procedures in U.S. hospitals, 2011: Statistical brief #170, 2013; Macario A, Anesthesiology 105:237-240, 2006; Childers et al, JAMA Surg 153:e176233, 2018). Little has been reported to evaluate how anesthesia trainees change anesthesia-related efficiencies in the OR. Statistical correlation may demonstrate awareness and implementation of efficient systems-based practice. METHODS: Utilizing computerized OR information systems, specific data regarding anesthesia controlled turnover times were collected (546 data points) over the course of 4 months. The type of surgery performed, patient's American Society of Anesthesiologists (ASA) physical status and OR turnover times were compared for clinical anesthesia (CA) trainee levels CA1, CA2, CA3 and CRNAs. Standard descriptive statistics were computed. Analysis of variance (ANOVA) was performed to compare the average turnover time. RESULTS: Average OR turnover time was 31 min ranging from 8 to 60 min. There was a significant difference between the OR turnover time of CA-1 (32 min) compared to CA-3 (29 min) (p = 0.017) and CA-1 compared to CRNA (30 min) (p = 0.016). OR turnover time was significantly shorter in CA-3 and CRNA. The analysis showed no differences between OR turnover time of ASA categories. CONCLUSIONS: These findings posit that trainees improve efficiency over time, but that education may for a time come at the expense of productivity. This trend may demonstrate a more profound understanding and mastery of a learner progressing in the graduate medical education system. This interplay plays a key role in clinical and academic shared success.

Assessment of operative times of multiple surgical specialties in a public university hospital.

OBJECTIVE: To evaluate the indicators duration of anesthesia, operative time and time patients stay in the operating rooms of different surgical specialties at a public university hospital. METHODS: It was done by a descriptive cross-sectional study based on the operating room database. The following stages were measured: duration of anesthesia, procedure time and patient length of stay in the room of the various specialties. We included surgeries carried out in sequence in the same room, between 7:00 a.m. and 5 p.m., either elective or emergency. We calculated the 80th percentile of the stages, where 80% of procedures were below this value. RESULTS: The study measured 8,337 operations of 12 surgical specialties performed within one year. The overall mean duration of anesthesia of all specialties was 178.12±110.46 minutes, and the 80th percentile was 252 minutes. The mean operative time was 130.45±97.23 minutes, and the 80th percentile was 195 minutes. The mean total time of the patient in the operating room was 197.30±113.71 minutes, and the 80th percentile was 285 minutes. Thus, the variation of the overall mean compared to the 80th percentile was 41% for anesthesia, 49% for surgeries and 44% for operating room time. In average, anesthesia took up 88% of the operating room period, and surgery, 61%. CONCLUSION: This study identified patterns in the duration of surgery stages. The mean values of the specialties can assist with operating room planning and reduce delays. OBJETIVO: Avaliar os indicadores de tempo da anestesia, da operação e da permanência do paciente em sala de diversas especialidades do centro cirúrgico de um hospital universitário. MÉTODOS: Foi realizado em estudo descritivo transversal a partir da base de dados do centro cirúrgico e mensuradas as seguintes etapas: duração de anestesia, tempo do procedimento e tempo de permanência do paciente em sala das diversas especialidades. Foram incluídas as operações realizadas em sequência na mesma sala, das 7h às 17h, eletivas ou de urgências. Realizamos o calculo do percentil 80 da duração das etapas, onde 80% dos procedimentos ficaram abaixo deste valor obtido. RESULTADOS: O estudo incluiu 8.337 operações realizadas no período de 1 ano de 12 especialidades cirúrgicas. A média geral da duração da anestesia de todas as especialidades foi de 178,12±110,46 minutos, e o percentil 80 foi de 252 minutos. A média do tempo operatório foi 130,45±97,23 minutos, e o percentil 80 foi de 195 minutos. A média do tempo total do paciente em sala operatória foi de 197,30±113,71 minutos, e o percentil 80 foi de 285 minutos. A variação da média geral em relação ao percentil 80 foi de 41% na anestesia, 49% nas operações e 44% no tempo de sala. Na média geral, a anestesia ocupou 88% do tempo de sala e a operação, 61%. CONCLUSÃO: Este estudo identificou padrões nas durações das etapas das operações. A informação das médias históricas das especialidades pode auxiliar no planejamento do centro cirúrgico e diminuir os atrasos.

Assessment of operative times of multiple surgical specialties in a public university hospital / Avaliação dos tempos operatórios das múltiplas especialidades cirúrgicas de um hospital universitário público

ABSTRACT Objective To evaluate the indicators duration of anesthesia, operative time and time patients stay in the operating rooms of different surgical specialties at a public university hospital. Methods It was done by a descriptive cross-sectional study based on the operating room database. The following stages were measured: duration of anesthesia, procedure time and patient length of stay in the room of the various specialties. We included surgeries carried out in sequence in the same room, between 7:00 a.m. and 5 p.m., either elective or emergency. We calculated the 80th percentile of the stages, where 80% of procedures were below this value. Results The study measured 8,337 operations of 12 surgical specialties performed within one year. The overall mean duration of anesthesia of all specialties was 178.12±110.46 minutes, and the 80th percentile was 252 minutes. The mean operative time was 130.45±97.23 minutes, and the 80th percentile was 195 minutes. The mean total time of the patient in the operating room was 197.30±113.71 minutes, and the 80th percentile was 285 minutes. Thus, the variation of the overall mean compared to the 80th percentile was 41% for anesthesia, 49% for surgeries and 44% for operating room time. In average, anesthesia took up 88% of the operating room period, and surgery, 61%. Conclusion This study identified patterns in the duration of surgery stages. The mean values of the specialties can assist with operating room planning and reduce delays.

RESUMO Objetivo Avaliar os indicadores de tempo da anestesia, da operação e da permanência do paciente em sala de diversas especialidades do centro cirúrgico de um hospital universitário. Métodos Foi realizado em estudo descritivo transversal a partir da base de dados do centro cirúrgico e mensuradas as seguintes etapas: duração de anestesia, tempo do procedimento e tempo de permanência do paciente em sala das diversas especialidades. Foram incluídas as operações realizadas em sequência na mesma sala, das 7h às 17h, eletivas ou de urgências. Realizamos o calculo do percentil 80 da duração das etapas, onde 80% dos procedimentos ficaram abaixo deste valor obtido. Resultados O estudo incluiu 8.337 operações realizadas no período de 1 ano de 12 especialidades cirúrgicas. A média geral da duração da anestesia de todas as especialidades foi de 178,12±110,46 minutos, e o percentil 80 foi de 252 minutos. A média do tempo operatório foi 130,45±97,23 minutos, e o percentil 80 foi de 195 minutos. A média do tempo total do paciente em sala operatória foi de 197,30±113,71 minutos, e o percentil 80 foi de 285 minutos. A variação da média geral em relação ao percentil 80 foi de 41% na anestesia, 49% nas operações e 44% no tempo de sala. Na média geral, a anestesia ocupou 88% do tempo de sala e a operação, 61%. Conclusão Este estudo identificou padrões nas durações das etapas das operações. A informação das médias históricas das especialidades pode auxiliar no planejamento do centro cirúrgico e diminuir os atrasos.

An assessment of the quality indicators of operative and non-operative times in a public university hospital / Avaliação dos indicadores de qualidade de tempo operatório e não operatório de um hospital universitário público

ABSTRACT Objective To assess the operative time indicators in a public university hospital. Methods A descriptive cross-sectional study was conducted using data from operating room database. The sample was obtained from January 2011 to January 2012. The operations performed in sequence in the same operating room, between 7:00 am and 5:00 pm, elective or emergency, were included. The procedures with incomplete data in the system were excluded, as well as the operations performed after 5:00 pm or on weekends or holidays. Results We measured the operative and non-operative time of 8,420 operations. The operative time (mean and standard deviation) of anesthesias and operations were 177.6±110 and 129.8±97.1 minutes, respectively. The total time of the patient in operative room (mean and standard deviation) was 196.8±113.2. The non-operative time, e.g., between the arrival of the patient and the onset of anesthesia was 14.3±17.3 minutes. The time to set the next patient in operating room was 119.8±79.6 minutes. Our total non-operative time was 155 minutes. Conclusion Delays frequently occurred in our operating room and had a major effect on patient flow and resource utilization. The non-operative time was longer than the operative time. It is possible to increase the operating room capacity by management and training of the professionals involved. The indicators provided a tool to improve operating room efficiency.

RESUMO Objetivo Avaliar os indicadores de tempo do centro cirúrgico de um hospital universitário para melhoraria de sua eficiência. Métodos Foi realizado um estudo descritivo transversal a partir da base de dados da tecnologia da informação do centro cirúrgico. A amostra foi obtida a partir de janeiro de 2011 a janeiro de 2012. Foram incluídas as operações realizadas em sequência na mesma sala cirúrgica, das 7 às 17h, eletivas ou de urgências. Os procedimentos com dados incompletos no sistema foram excluídos, assim como as operações depois das 17h ou realizadas em fins de semana ou feriados. Resultados Foi medido o tempo operatório e não operatório de 8.420 operações realizadas. Os tempos operatórios (média e desvio padrão) de anestesia e de cirurgia foram 177,6±110 e 129,8±97,1 minutos, respectivamente. O tempo total do paciente em sala cirúrgica (média e desvio padrão) foi de 196,8±113,2. O tempo não operatório, por exemplo, entre a chegada do paciente e o início da anestesia, foi de 14,3±17,3 minutos. O tempo de preparo e entrada do próximo paciente na sala cirúrgica foi 119,8±79,6 minutos. O tempo não operatório total foi de 155 minutos. Conclusão Atrasos frequentes ocorreram nas salas de cirurgia e tiveram um grande efeito sobre o fluxo de pacientes e a utilização de recursos. O tempo não operatório foi maior que o operatório. Portanto, é possível aumentar a capacidade do centro cirúrgico por meio da gestão e do treinamento dos profissionais envolvidos. Os indicadores oferecem uma ferramenta para melhorar a eficiência das salas de cirurgia.

Redefining "time" to meet evolving demands.

The American Association of Critical-Care Nurses (AACN) developed the Clinical Scene Investigator (CSI) Academy for nurses at the bedside to hone leadership and innovation skills to create and sustain lasting change and improve positive patient outcomes. In this first part of a three-part series, we take a look at how the AACN CSI Academy helps clinical nurses cultivate skills that measurably demonstrate how nonproductive time is a misnomer that interferes with achieving optimal patient outcomes.

Implementation and assessment of a fast-track programme to improve communication between primary and specialized care in patients with suspected cancer: how to shorten time between initial symptoms of cancer, diagnosis and initiation of treatment.

PURPOSE: This study aims to asses a cancer fast-track programme (CFP) to shorten the time since a patient with suspicion of cancer is referred by the primary care (PC) physician to the specialized medical team. METHODS: Guidelines for main suspected tumours were designed to help PC physicians to detect and rapidly refer cases to the CFP oncology coordinator, who sent them to the appropriate department to accelerate diagnosis, staging and therapy. All patients analysed in this report were referred from June 2009 to July 2012. RESULTS: A total of 897 suspected cancer cases were submitted and finally 705 were studied. In 205 (29 %) a cancer diagnosis was confirmed within 23 days (median). Therapy was initiated within 46 days after referral (median). Early diagnoses with a potential curative approach were made in 166 (82 %). CONCLUSIONS: This CFP decreased the waiting time for cancer diagnosis, by improving communication between PC physician and specialized care teams. Most patients included in this program could get therapy with curative intent.

An assessment of the quality indicators of operative and non-operative times in a public university hospital.

OBJECTIVE: To assess the operative time indicators in a public university hospital. METHODS: A descriptive cross-sectional study was conducted using data from operating room database. The sample was obtained from January 2011 to January 2012. The operations performed in sequence in the same operating room, between 7:00 am and 5:00 pm, elective or emergency, were included. The procedures with incomplete data in the system were excluded, as well as the operations performed after 5:00 pm or on weekends or holidays. RESULTS: We measured the operative and non-operative time of 8,420 operations. The operative time (mean and standard deviation) of anesthesias and operations were 177.6 ± 110 and 129.8 ± 97.1 minutes, respectively. The total time of the patient in operative room (mean and standard deviation) was 196.8 ± 113.2. The non-operative time, e.g., between the arrival of the patient and the onset of anesthesia was 14.3 ± 17.3 minutes. The time to set the next patient in operating room was 119.8 ± 79.6 minutes. Our total non-operative time was 155 minutes. CONCLUSION: Delays frequently occurred in our operating room and had a major effect on patient flow and resource utilization. The non-operative time was longer than the operative time. It is possible to increase the operating room capacity by management and training of the professionals involved. The indicators provided a tool to improve operating room efficiency.

[Management of time used to treat the chronic patient: a new approach to improve quality of health care]. / Gestión del tiempo de asistencia al paciente crónico: un nuevo enfoque para mejorar la calidad asistencial.

OBJECTIVE: Chronic disease is the main epidemic of the 21st century. It takes up a large part of the social-health budgets that are dedicated to its care. The aim of this study is to analyze if the welfare quality in the management of the chronic patients improves by implementing non-contact care time. MATERIAL AND METHODS: Intervention study conducted in the health care center of Orcasitas (January 2012 - September 2013) in patients with hypertension (357), diabetes (180) and/or ischemic heart disease (60). Health care quality was analyzed through the effectiveness in the program, Tracking Objectives in Primary Care. The intervention group had four physical 10minute consultations/year and three non-physical 10minute consultations/year. The patients in the control group were seen as usual. The data were compared using the McNemar test, chi-square and Cochran's Q test. RESULTS: In the intervention group, the effectiveness increased in the analyzed period by 46%, 54% and 55.9%, respectively, for processes of hypertension, diabetes and dyslipidemia control in ischemic heart disease, whereas in the control group (community of Madrid) it was 2.54%, 1.78%, and 5.44%, respectively, for these processes (statistically significant differences [χ(2)=24.78; χ(2)=39.9 y χ(2)=67.3, P<.0001]). CONCLUSIONS: Thirty minutes/year of non-presential care represents a significant change in the level of control of chronic patients. These results should be considered in the approach strategies to chronic diseases.

Scheduling, revenue management, and fairness in an academic-hospital radiology division.

RATIONALE AND OBJECTIVES: Physician staff of academic hospitals today practice in several geographic locations including their main hospital. This is referred to as the extended campus. With extended campuses expanding, the growing complexity of a single division's schedule means that a naive approach to scheduling compromises revenue. Moreover, it may provide an unfair allocation of individual revenue, desirable or burdensome assignments, and the extent to which the preferences of each individual are met. This has adverse consequences on incentivization and employee satisfaction and is simply against business policy. MATERIALS AND METHODS: We identify the daily scheduling of physicians in this context as an operational problem that incorporates scheduling, revenue management, and fairness. Noting previous success of operations research and optimization in each of these disciplines, we propose a simple unified optimization formulation of this scheduling problem using mixed-integer optimization. RESULTS: Through a study of implementing the approach at the Division of Angiography and Interventional Radiology at the Brigham and Women's Hospital, which is directed by one of the authors, we exemplify the flexibility of the model to adapt to specific applications, the tractability of solving the model in practical settings, and the significant impact of the approach, most notably in increasing revenue by 8.2% over previous operating revenue while adhering strictly to a codified fairness and objectivity. CONCLUSIONS: We found that the investment in implementing such a system is far outweighed by the large potential revenue increase and the other benefits outlined.

Productivity, part 1: getting things done, using e-mail, scanners, reference managers, note-taking applications, and text expanders.

In an era of declining reimbursements and tightening of the job market, today's radiologists are forced to "make do with less." With the rollout of the Patient Protection and Affordable Care Act, commonly called "Obamacare," radiologists will be expected not only to interpret studies but to also take on many additional roles, adding a new layer of complexity to already demanding daily duties. These changes make it more important than ever to develop a personal workflow management system incorporating some of the most potent productivity tools. In this article, the authors discuss current productivity techniques and related software with the most potential to help radiologists keep up with the ever increasing demands on their time at the work place and help us lead more balanced lives.

[Time based management in health care system: the chosen aspects]. / Zarzadzanie czasem w systemie opieki zdrowotnej - wybrane aspekty.

Time-based management (TBM) is the key element of the whole management process. For many years in health care systems of highly developed countries modern and effective methods of time-based management have been implemented in both primary health care and hospitals (emergency departments and operating rooms). Over the past two decades a systematic review of Polish literature (since 1990) and peer reviewed articles published in international journals based on PubMed/Medline (2001-2011) have been carried out. The collected results indicate that the demographic and health changes in the populations are one of the main challenges facing general practitioners in the nearest future. Time-based management needs new and effective tools and skills, i.e., identification of priorities, well designed planning, delegation of the tasks, proper coordination, and creation of primary care teams that include additional members and human resources management. Proper reimbursement of health services, development of IT in health care system, better collection, storage, processing, analysis and exchange of information and research findings will also be needed. The use of innovative technologies, like telemedicine consultations, provides the possibility of reducing waiting time for diagnosis and treatment and in some cases could be applied in terms of secondary care. To improve the efficiency of operating rooms it is necessary to introduce different solutions, such as operating room coordinator involvement, application of automation to guide decision-making or use of robotic tools to assist surgical procedures. Overcrowded emergency departments have a major detrimental effect on the quality of hospital functions, therefore, efforts should be made to reduce them. Time-based management training among physicians and health care management in Poland, as well as the implementation of practice-based solutions still applied in highly developed countries seem to be necessary.

Succeeding as a Clinician Educator: useful tips and resources.

Clinician Educators (CEs) play an essential role in the education and patient care missions of academic medical centers. Despite their crucial role, academic advancement is slower for CEs than for other faculty. Increased clinical productivity demands and financial stressors at academic medical centers add to the existing challenges faced by CEs. This perspective seeks to provide a framework for junior CEs to consider with the goal of maximizing their chance of academic success. We discuss six action areas that we consider central to flourishing at academic medical centers: 1. Clarify what success means and define goals; 2. Seek mentorship and be a responsible mentee; 3. Develop a niche and engage in relevant professional development; 4. Network; 5. Transform educational activities into scholarship; and 6. Seek funding and other resources.