Journal articles: 'Patient demand'

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Wilkinson, Susie. "Complementary therapies - patient demand." International Journal of Palliative Nursing 8, no. 10 (October 2002): 468. http://dx.doi.org/10.12968/ijpn.2002.8.10.10692.

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KIRN, TIMOTHY F. "Buprenorphine Demand Surpassing Patient Limit." Clinical Psychiatry News 34, no. 2 (February 2006): 51. http://dx.doi.org/10.1016/s0270-6644(06)71190-0.

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SHAH, M. V., D. I. JONES, and M. ROSEN. "“PATIENT DEMAND” POSTOPERATIVE ANALGESIA WITH BUPRENORPHINE." British Journal of Anaesthesia 58, no. 5 (May 1986): 508–11. http://dx.doi.org/10.1093/bja/58.5.508.

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Sinderby, Christer. "Ventilatory Assist Driven by Patient Demand." American Journal of Respiratory and Critical Care Medicine 168, no. 7 (October 2003): 729–30. http://dx.doi.org/10.1164/rccm.2307004.

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WELCHEW, E. A., and D. P. BREEN. "Patient-controlled on-demand epidural fentanyl." Anaesthesia 46, no. 6 (June 1991): 438–41. http://dx.doi.org/10.1111/j.1365-2044.1991.tb11678.x.

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Krauss, Oliver, Barbara Franz, and Andreas Schuler. "Automated On-Demand Generation Of Patient Summary Documents." International Journal of Electronics and Telecommunications 61, no. 2 (June 1, 2015): 151–57. http://dx.doi.org/10.1515/eletel-2015-0019.

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Abstract Patient summary documents provide crucial information about a patient, like allergies and adverse reactions, which are necessary for an efficient and safe treatment and offer a quick overview of the patients health status. Automatically generating patient summaries from Electronic Health Records (EHR) reduces the workload of medical personnel. Nevertheless, existing approaches do not take several challenges that occur in live operation into account. Based on a health standard-compliant approach, a system for on-demand generation of patient summaries was implemented and evaluated using real data. This work shows several problems which could be identified. Those problems are not covered sufficiently by current research. Possible approaches to a solution are suggested, which have to be further investigated in future work.

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White, Kathleen M. "Using Continuous SVO2 to Assess Oxygen Supply/Demand Balance in the Critically Ill Patient." AACN Advanced Critical Care 4, no. 1 (February 1, 1993): 134–47. http://dx.doi.org/10.4037/15597768-1993-1011.

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To ensure that tissues arc well oxygenated, oxygen supply and demand are now targets of therapy for the critically ill patient. This chapter reviews the physiologic determinants of oxygen supply, how it is threatened by respiratory or cardiac dysfunction or by hemorrhaged or anemic states, and how it can be assessed in individual patients. Activities and conditions that increase tissue oxygen demand arc examined so that clinicians can identify those patients whose oxygen demands may be excessive and should be controlled. Failure of tissues to consume enough oxygen is explained in patients with critically low delivery or with the maldistributed blood flow state seen in sepsis. The monitoring of mixed venous oxygen saturation is examined as a method of tracking the threats to supply/demand balance and of guiding treatment that can support the adequate oxygenation of tissue

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Corpuz, Michael Q., Christina F. Rusnock, Vhance V. Valencia, and Kyle Oyama. "Medical readiness: evaluating the robustness of medical clinic staffing solutions." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 14, no. 4 (June 10, 2016): 407–19. http://dx.doi.org/10.1177/1548512916650996.

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Medical readiness requires Department of Defense medical clinics to be robust to changes in patient demand. Minor fluctuations in patient demand occur on a regular basis, but major increases can also occur. Major demand increases can result from a number of occurrences, including mass military deployments, medical incidents, outbreaks, and overflow from Veterans’ Affairs clinics. This research evaluates a system of clinics at Wright-Patterson Air Force Base in order to determine its ability to handle a 200% surge in patient demand. In addition, this study evaluates the relative effectiveness of six different staffing mix options to minimize patient wait times, also under the surge demand conditions. This evaluation is conducted using discrete-event simulation to estimate patient wait times and includes a sensitivity analysis of the increased patient demand, as well as a cost–benefit analysis to determine the most cost-effective alternative scenario. The study finds that adjustments to staffing mix enable cost savings while meeting current demands. In addition, the study finds that adjusting the staffing mix will not have a negative impact on patient wait time in the surge conditions, relative to the current staffing mix.

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Dalsania, Ankur K., and Akash P. Kansagra. "Simultaneous patient presentation for endovascular thrombectomy in acute ischemic stroke." Journal of NeuroInterventional Surgery 11, no. 12 (April 27, 2019): 1201–4. http://dx.doi.org/10.1136/neurintsurg-2019-014857.

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BackgroundIncreased demand for endovascular thrombectomy has increased the likelihood of simultaneous patient presentation leading to competing demand for time-critical treatment that could adversely impact patient outcomes. We aimed to quantify the occurrence of simultaneous patient presentation at different patient volumes.MethodsEmpirical distributions for time of patient presentation and case duration were used to probabilistically generate arrival time and case duration for a set annual patient volume, ranging from 1 to 500 cases per year, for 16 000 independent trials at each volume. Time series were generated for each trial to represent the number of cases being performed at each minute of the year. Time series were used to calculate daily thrombectomy demand, annual concurrent demand, and hourly excess demand.ResultsThe patient volumes at which at least one annual occurrence of concurrent demand by two patients was 50% and 97.5% likely were 45 and 101, respectively. The volumes at which at least one annual occurrence of concurrent demand by three patients was 50% and 97.5% likely were 216 and 387, respectively. There was dramatic variation in the occurrence of excess demand by two or more patients throughout the day.ConclusionsThe occurrence of simultaneous presentation by multiple patients for endovascular thrombectomy varies with annual patient volume and time of day. Understanding these trends and the associated patient impact can inform intelligent strategies at regional and national levels for optimizing patient care within real-world financial and operational constraints.

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Kondro, W. "Patient demand and politics push Herceptin forward." Canadian Medical Association Journal 173, no. 4 (August 16, 2005): 347–48. http://dx.doi.org/10.1503/cmaj.050883.

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Dranove, David. "DEMAND INDUCEMENT AND THE PHYSICIAN/PATIENT RELATIONSHIP." Economic Inquiry 26, no. 2 (April 1988): 281–98. http://dx.doi.org/10.1111/j.1465-7295.1988.tb01494.x.

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Weis, J., H. H. Bartsch, F. Hennies, M. Rietschel, M. Heim, G. Adam, U. Gärtner, and A. Ammon. "Complementary Medicine in Cancer Patients: Demand, Patient’ Attitudes and Psychological Beliefs." Oncology Research and Treatment 21, no. 2 (1998): 144–49. http://dx.doi.org/10.1159/000026796.

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Padegimas, Eric M., Mitchell Maltenfort, Mark D. Lazarus, Matthew L. Ramsey, Gerald R. Williams, and Surena Namdari. "Future Patient Demand for Shoulder Arthroplasty by Younger Patients: National Projections." Clinical Orthopaedics and Related Research® 473, no. 6 (March 11, 2015): 1860–67. http://dx.doi.org/10.1007/s11999-015-4231-z.

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Calegari, Rafael, Flavio S. Fogliatto, Filipe R. Lucini, Jeruza Neyeloff, Ricardo S. Kuchenbecker, and Beatriz D. Schaan. "Forecasting Daily Volume and Acuity of Patients in the Emergency Department." Computational and Mathematical Methods in Medicine 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/3863268.

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This study aimed at analyzing the performance of four forecasting models in predicting the demand for medical care in terms of daily visits in an emergency department (ED) that handles high complexity cases, testing the influence of climatic and calendrical factors on demand behavior. We tested different mathematical models to forecast ED daily visits at Hospital de Clínicas de Porto Alegre (HCPA), which is a tertiary care teaching hospital located in Southern Brazil. Model accuracy was evaluated using mean absolute percentage error (MAPE), considering forecasting horizons of 1, 7, 14, 21, and 30 days. The demand time series was stratified according to patient classification using the Manchester Triage System’s (MTS) criteria. Models tested were the simple seasonal exponential smoothing (SS), seasonal multiplicative Holt-Winters (SMHW), seasonal autoregressive integrated moving average (SARIMA), and multivariate autoregressive integrated moving average (MSARIMA). Performance of models varied according to patient classification, such that SS was the best choice when all types of patients were jointly considered, and SARIMA was the most accurate for modeling demands of very urgent (VU) and urgent (U) patients. The MSARIMA models taking into account climatic factors did not improve the performance of the SARIMA models, independent of patient classification.

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Munavalli, Jyoti R., Shyam Vasudeva Rao, Aravind Srinivasan, and GG van Merode. "Integral patient scheduling in outpatient clinics under demand uncertainty to minimize patient waiting times." Health Informatics Journal 26, no. 1 (March 8, 2019): 435–48. http://dx.doi.org/10.1177/1460458219832044.

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This study addressed the problem of scheduling walk-in patients in real time. Outpatient clinics encounter uncertainty in patient demand. In addition, the disparate departments are locally (department-centric) organized, leading to prolonged waiting times for patients. The proposed integral patient scheduling model incorporates the status and information of all departments in the outpatient clinic along with all possible pathways to direct patients, on their arrival, to the optimal path. The developed hybrid ant agent algorithm identifies the optimal path to reduce the patient waiting time and cycle time (time from registration to exit). An outpatient clinic in Aravind Eye Hospital, Madurai, has a huge volume of walk-in patients and was selected for this study. The simulation study was performed for diverse scenarios followed by implementation study. The results indicate that integral patient scheduling reduced waiting time significantly. The path optimization in real time makes scheduling effective and efficient as it captures the changes in the outpatient clinic instantly.

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Allder, Steven, Kate Silvester, and Paul Walley. "Managing capacity and demand across the patient journey." Clinical Medicine 10, no. 1 (February 2010): 13–15. http://dx.doi.org/10.7861/clinmedicine.10-1-13.

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Morgan, Ibrahim. "Managing capacity and demand across the patient journey." Clinical Medicine 10, no. 4 (August 2010): 417.2–418. http://dx.doi.org/10.7861/clinmedicine.10-4-417a.

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Sanderson, B., A. McWilliam, C. Faivre-Finn, A. Choudhury, and T. Mee. "PO-0788: Predicted patient demand for MRI Linac." Radiotherapy and Oncology 119 (April 2016): S370—S371. http://dx.doi.org/10.1016/s0167-8140(16)32038-2.

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Murray, A. "The demand for evening ENT out-patient appointments." Clinical Otolaryngology and Allied Sciences 29, no. 1 (February 2004): 98–101. http://dx.doi.org/10.1111/j.0307-7772.2003.00832.x.

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Hawthorne, Lesleyanne, Julie Toth, and Graeme Hawthorne. "Patient Demand for Bilingual Bicultural Nurses in Australia." Journal of Intercultural Studies 21, no. 2 (August 2000): 193–224. http://dx.doi.org/10.1080/713678942.

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Hu, Yuh-Jyh, and Tien-Hsiung Ku. "Pattern discovery from patient controlled analgesia demand behavior." Computers in Biology and Medicine 42, no. 10 (October 2012): 1005–11. http://dx.doi.org/10.1016/j.compbiomed.2012.08.002.

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Kim, Tongil “TI”, and Diwas KC. "The Impact of Hospital Advertising on Patient Demand and Health Outcomes." Marketing Science 39, no. 3 (May 2020): 612–35. http://dx.doi.org/10.1287/mksc.2019.1153.

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Does hospital advertising influence patient choice and health outcomes? We examine more than 220,000 individual patient-level visits over 24 months in Massachusetts to answer this question. We find that patients are positively influenced by hospital advertising; seeing a television advertisement for a given hospital makes a patient more likely to select that hospital. We also observe significant heterogeneity in patient response depending on insurance status, medical conditions, and demographic factors, like age, gender, and race. For example, patients with more restrictive forms of insurance are less sensitive to advertisements. Our demand model allows us to study the impact of a ban on hospital advertising, which has been recently considered by policy makers. We find that banning hospital advertising can hurt patient health outcomes through increased hospital readmissions. This is because hospital advertisements drive patients to higher-quality hospitals, which tend to advertise more and have lower readmission rates. However, we do not find a significant change in the overall mortality rate.

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Putri, Wulandari Berliani, Vita Widyasari, Juliet Musabula, and Muhammad Jihadul Hayat. "Medicolegal Perspective on Physician-Induced Demand Issue." BESTUUR 9, no. 1 (August 12, 2021): 106. http://dx.doi.org/10.20961/bestuur.v9i1.48281.

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This study sheds light on the extent to which the medical law protects patients' rights from Physician-Induced Demand behavior. This study shows that the term of Physician-Induced Demand has not been recognized in health regulations. Meanwhile, some often fail to recall that medical law has protected patients’ right in the therapeutic transaction between doctor and patient through Act No. 29 of 2004; Minister of Health Regulations number 11 Year 2017; Act No. 44 of 2009, Civil Code and Act No. 36 of 2009. In order to reduce Physician-Induced Demand, establishing a guideline of good clinical practice, including the informed-consent guideline is urgently needed. Government should also control the quality and cost of healthcare providers as well as adequate payment system for physicians.Keywords: Physician-Induced Demand; Medical Law; Legal Protection of Patient.

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Yen, Chia-Rong, Mei-Yung Tsou, Mercedes Susan Mandell, Chia-Tai Chan, Kwok-Hon Chan, Tony Hsiu-Hsi Chen, and Kuang-Yi Chang. "An Analysis of Patient Variables That Influence Intravenous Patient-controlled Analgesic Use of Morphine with Quantile Regression." Anesthesiology 112, no. 3 (March 1, 2010): 688–95. http://dx.doi.org/10.1097/aln.0b013e3181cbd1f3.

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Background Previous studies using linear regression analysis have shown that age, weight, gender, and the site of operation affect intravenous patient-controlled analgesia (IVPCA) narcotic use. However, there are inconsistent observations in the literature. The authors postulate that patient variables could have different effects at various doses of narcotics. To test this hypothesis, the authors analyzed the effect of patient variables on increasing doses of IVPCA narcotic with quantile regression. Methods The authors collected retrospective data from 1,782 patients who received IVPCA for a minimum of 3 days after surgery. The authors used stepwise linear regression model to identify variables that significantly affected the total IVPCA requirements. Quantile regression model was further applied to assess the effects of selected variables on the ascending percentile of IVPCA narcotic use. Results Gender, age, body weight, cancer, and surgical site were identified as significant predictors for IVPCA demand. Body weight had the most and cancer had the least significant effects on total IVPCA demands. The results of quantile regression model revealed that the determinants under consideration varied with different percentiles of IVPCA demand. The patient variables correlated with IVPCA narcotic use differently when the dose exceeded the seventieth to eightieth percentiles compared with other percentiles of narcotic use. Conclusions The authors' findings highlight the heterogeneous postoperative pain requirements among patients and the consequent complex process of efficiently managing postoperative pain.

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Lee, Kyoung Suk, Yoo Mi Cho, Sung Hee Oh, Mi Sook Jung, and Ju Young Yoon. "Evaluation of the Heart Failure in Internet Patient Information: Descriptive Survey Study." International Journal of Environmental Research and Public Health 18, no. 3 (January 25, 2021): 1047. http://dx.doi.org/10.3390/ijerph18031047.

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Patients with heart failure (HF) may not receive enough HF education from their clinicians throughout the course of the illness. Given that information is readily accessible on the Internet, patients with HF may seek HF information online. However, the relevance of online information for patients, the health literacy demand, and quality of the information is unknown. The purpose of this study was to compare the HF topics available online with topics HF patients perceived to be important and to evaluate the health literacy demand and quality of online HF information. The most popular search engines and a website that ranks the popularity of the websites were searched to identify websites with HF information. The health literacy demand and quality of the information were evaluated using the Patient Education Material Evaluation Tool for Print Materials and the DISCERN tool, respectively. First, the HF Patients’ Learning Needs Inventory (HFPLNI) was used to determine whether the websites included the 46 topics identified in this inventory. Patients with HF (n = 126) then completed the HFPLNI to rate the perceived importance on each topic. A chi-square test was used to compare the differences between the topics on the websites and those patients perceived to be important. Of the 46 topics, 39 were less likely to be included on the websites even though patients perceived that they were important topics. Information on the websites (n = 99) was not written could not be easily understood by patients and did not meet the overall health literacy demands of 58.0% and 19.8% of the patients, respectively. Only one-fifth of the websites were rated as fair to good quality. Online HF information had high health literacy demand and was poor quality with mostly generic HF information, which did not meet patients’ information needs. Websites need to be developed reflecting patients’ learning needs with low health literacy demand and good quality.

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Santos, Luciana Soares Costa, and Edinêis de Brito Guirardello. "Nurses' attention demands in the work setting." Revista Latino-Americana de Enfermagem 15, no. 1 (February 2007): 27–33. http://dx.doi.org/10.1590/s0104-11692007000100005.

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This descriptive study aimed to identify attention demand situations experienced by nurses in their workplace and to verify if these demands were judged differently depending on socio-demographic variables. Data were collected through the "Directed Attention Demands" instrument, translated and validated in Brazil. SAS statistics software was used for data analysis. The following demand situations scored higher: "watching a patient suffer", "a number of rapid decisions had to be made", "caring for families with emotional needs", "not enough time to provide emotional support to a patient", and "family teaching required". There were statistical differences for variables such as: age, marital status, professional qualification, work shift and number of hours worked weekly. The importance of these findings should be pointed out to managers and administrators in the adoption of strategies that can minimize these sources of demand for nurses.

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Munavalli, Jyoti R., Shyam Vasudeva Rao, Aravind Srinivasan, and GG van Merode. "An intelligent real-time scheduler for out-patient clinics: A multi-agent system model." Health Informatics Journal 26, no. 4 (February 21, 2020): 2383–406. http://dx.doi.org/10.1177/1460458220905380.

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Scheduling of resources and patients are crucial in outpatient clinics, particularly when the patient demand is high and patient arrivals are random. Generally, outpatient clinic systems are push systems where scheduling is based on average demand prediction and is considered for long term (monthly or bimonthly). Often, planning and actual scenario vary due to uncertainty and variability in demand and this mismatch results in prolonged waiting times and under-utilization of resources. In this article, we model an outpatient clinics as a multi-agent system and propose an intelligent real-time scheduler that schedules patients and resources based on the actual status of departments. Two algorithms are implemented: one for resource scheduling that is based on predictive demand and the other is patient scheduling which performs path optimization depending on the actual status of departments. In order to match resources with stochastic demand, a coordination mechanism is developed that reschedules the resources in the outpatient clinics in real time through auction-bidding procedures. First, a simulation study of intelligent real-time scheduler is carried out followed by implementation of the same in an outpatient clinic of Aravind Eye Hospital, Madurai, India. This hospital has huge patient demand and the patient arrivals are random. The results show that the intelligent real-time scheduler improved the performance measures like waiting time, cycle time, and utilization significantly compared to scheduling of resources and patients in isolation. By scheduling resources and patients, based on system status and demand, the outpatient clinic system becomes a pull system. This scheduler transforms outpatient clinics from open loop system to closed-loop system.

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Yun, J. E. "PMS96 - A DEMAND SURVEY ON PATIENT EDUCATION FOR PATIENTS WITH RHEUMATOID ARTHRITIS." Value in Health 21 (October 2018): S304. http://dx.doi.org/10.1016/j.jval.2018.09.1810.

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Fischer, Gabriel Souto, Rodrigo da Rosa Righi, Cristiano André da Costa, Guilherme Galante, and Dalvan Griebler. "Towards Evaluating Proactive and Reactive Approaches on Reorganizing Human Resources in IoT-Based Smart Hospitals." Sensors 19, no. 17 (September 2, 2019): 3800. http://dx.doi.org/10.3390/s19173800.

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Hospitals play an important role on ensuring a proper treatment of human health. One of the problems to be faced is the increasingly overcrowded patients care queues, who end up waiting for longer times without proper treatment to their health problems. The allocation of health professionals in hospital environments is not able to adapt to the demands of patients. There are times when underused rooms have idle professionals, and overused rooms have fewer professionals than necessary. Previous works have not solved this problem since they focus on understanding the evolution of doctor supply and patient demand, as to better adjust one to the other. However, they have not proposed concrete solutions for that regarding techniques for better allocating available human resources. Moreover, elasticity is one of the most important features of cloud computing, referring to the ability to add or remove resources according to the needs of the application or service. Based on this background, we introduce Elastic allocation of human resources in Healthcare environments (ElHealth) an IoT-focused model able to monitor patient usage of hospital rooms and adapt these rooms for patients demand. Using reactive and proactive elasticity approaches, ElHealth identifies when a room will have a demand that exceeds the capacity of care, and proposes actions to move human resources to adapt to patient demand. Our main contribution is the definition of Human Resources IoT-based Elasticity (i.e., an extension of the concept of resource elasticity in Cloud Computing to manage the use of human resources in a healthcare environment, where health professionals are allocated and deallocated according to patient demand). Another contribution is a cost–benefit analysis for the use of reactive and predictive strategies on human resources reorganization. ElHealth was simulated on a hospital environment using data from a Brazilian polyclinic, and obtained promising results, decreasing the waiting time by up to 96.4% and 96.73% in reactive and proactive approaches, respectively.

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Lucas, Ben, and Harry Doyle. "Thirty years of in-patient consultation-liaison psychiatry at Guy's." Psychiatric Bulletin 19, no. 10 (October 1995): 631–34. http://dx.doi.org/10.1192/pb.19.10.631.

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In order to inform planning decisions, we aim to show how an in-patient consultation-liaison service has changed in 30 years. A year's referral of 175 inpatients was compared with surveys carried out in the same hospital 20 and 30 years previously. Neurosciences continue to refer the greatest percentage of its patients while general medicine produces the greatest demands on the service. There has been a large increase in substance misuse referrals, although other diagnostic groups have similar referral rates. Liaison service planners should be aware of the unmet demand for psychiatric services of the general hospital in-patient population.

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Savage, David W., Douglas G. Woolford, Bruce Weaver, and David Wood. "Developing emergency department physician shift schedules optimized to meet patient demand." CJEM 17, no. 1 (January 2015): 3–12. http://dx.doi.org/10.2310/8000.2013.131224.

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AbstractObjectives: 1) To assess temporal patterns in historical patient arrival rates in an emergency department (ED) to determine the appropriate number of shift schedules in an acute care area and a fast-track clinic and 2) to determine whether physician scheduling can be improved by aligning physician productivity with patient arrivals using an optimization planning model.Methods: Historical data were statistically analyzed to determine whether the number of patients arriving at the ED varied by weekday, weekend, or holiday weekend. Poisson-based generalized additive models were used to develop models of patient arrival rate throughout the day. A mathematical programming model was used to produce an optimal ED shift schedule for the estimated patient arrival rates. We compared the current physician schedule to three other scheduling scenarios: 1) a revised schedule produced by the planning model, 2) the revised schedule with an additional acute care physician, and 3) the revised schedule with an additional fast-track clinic physician.Results: Statistical modelling found that patient arrival rates were different for acute care versus fast-track clinics; the patterns in arrivals followed essentially the same daily pattern in the acute care area; and arrival patterns differed on weekdays versus weekends in the fast-track clinic. The planning model reduced the unmet patient demand (i.e., the average number of patients arriving at the ED beyond the average physician productivity) by 19%, 39%, and 69% for the three scenarios examined.Conclusions: The planning model improved the shift schedules by aligning physician productivity with patient arrivals at the ED.

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Mulligan, E. A. "Protecting patient confidentiality in hospitals." Australian Health Review 21, no. 3 (1998): 67. http://dx.doi.org/10.1071/ah980067.

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As new methods of electronic data storage and distribution appear in hospitals, newchallenges in protecting confidentiality have emerged. At the same time, demands for?seamless? care and the desire to share information between clinicians are motivatinghospitals to relax barriers to the transfer of patient information.Increasing numbers of users at multiple sites compound the difficulty of ensuringinformation systems security. Hospital policy may demand that requests by patientsto restrict the distribution of personal information be respected, while existingelectronic systems are not able to deliver on this promise.Compliance with the Information Privacy Principles of the Commonwealth PrivacyAct 1988 and the Australian Standard 4400?1995 ?Personal privacy protection inhealth care information systems? will provide a useful framework for managing these challenges. However, their implementation will require some forethought.

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Bacilla, Phillip, L. D. Field, and F. H. Savoie. "Arthroscopic bankart repair in a high demand patient population." Arthroscopy: The Journal of Arthroscopic & Related Surgery 13, no. 1 (February 1997): 51–60. http://dx.doi.org/10.1016/s0749-8063(97)90209-7.

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Kan, Jenny, Xinxing Zhu, Tieying Wang, Rongzhu Lu, and Peter S. Spencer. "Chinese patient demand for intravenous therapy: a preliminary survey." Lancet 386 (October 2015): S61. http://dx.doi.org/10.1016/s0140-6736(15)00642-x.

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Seip, B., M. Bretthauer, S. Dahler, J. Friestad, G. Huppertz-Hauss, O. Høie, E. Kittang, et al. "Patient satisfaction with on-demand sedation for outpatient colonoscopy." Endoscopy 42, no. 08 (July 28, 2010): 639–46. http://dx.doi.org/10.1055/s-0030-1255612.

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Castaldo, Anthony J., Christian Jervelund, Deborah Corcoran, Henrik B. Boysen, Sandra C. Christiansen, and Bruce L. Zuraw. "Assessing the cost and quality-of-life impact of on-demand‐only medications for adults with hereditary angioedema." Allergy and Asthma Proceedings 42, no. 2 (March 13, 2021): 108–17. http://dx.doi.org/10.2500/aap.2021.42.200127.

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Background: Novel subcutaneous (SC) prophylactic therapies are transforming the treatment landscape of hereditary angioedema (HAE). Although questions are being raised about their cost, little attention has been paid to the cost and quality of life (QoL) impact of using on-demand‐only medications. Objective: We assessed the overall economic burden of on-demand‐only treatment for HAE and compared patient QoL with patients who received novel SC prophylactic therapies. Methods: US Hereditary Angioedema Association members were invited to complete an anonymous online survey to profile attack frequency, treatment use, and the presence of comorbidities as well as economic and socioeconomic variables. We modeled on-demand treatment costs by using net pricing of medications in 2018, indirect patient and caregiver costs, and attack-related direct billed costs for emergency department admissions, physician office visits, and/or hospitalizations. QoL was assessed by using the Angioedema Quality of Life questionnaire. Results: A total of 1225 patients (31.4%) responded. Of these, 737 adults with HAE (type I or II) met the inclusion criteria and completed the survey. Per patient/year direct costs associated with modeled on-demand‐only treatment totaled $363,795, with additional indirect socioeconomic costs of $52,576 per patient/year. The greatest improvement in QoL was seen in patients who used novel SC prophylactic therapies, with a 59.5% (p < 0.01) improvement in median impairment scores versus on-demand‐only treatment. In addition, patients who used novel SC prophylactic therapies reported a 77% reduction in the number of attacks each year when compared with those who used on-demand‐only treatment. Conclusion: Our real-world patient data showed the cost and QoL burden of HAE treatment with on-demand‐only therapy. Use of novel SC prophylaxis can lead to sizeable reductions in attack frequency and statistically significant and clinically relevant improvements in QoL. These data could be useful to clinicians and patients as they consider therapy options for patients with HAE.

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Rogers, A., V. Entwistle, and D. Pencheon. "Managing demand: A patient led NHS: managing demand at the interface between lay and primary care." BMJ 316, no. 7147 (June 13, 1998): 1816–19. http://dx.doi.org/10.1136/bmj.316.7147.1816.

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Finkelstein, Amy, Matthew Gentzkow, and Heidi Williams. "Sources of Geographic Variation in Health Care: Evidence From Patient Migration*." Quarterly Journal of Economics 131, no. 4 (July 19, 2016): 1681–726. http://dx.doi.org/10.1093/qje/qjw023.

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Abstract We study the drivers of geographic variation in U.S. health care utilization, using an empirical strategy that exploits migration of Medicare patients to separate the role of demand and supply factors. Our approach allows us to account for demand differences driven by both observable and unobservable patient characteristics. Within our sample of over-65 Medicare beneficiaries, we find that 40–50% of geographic variation in utilization is attributable to demand-side factors, including health and preferences, with the remainder due to place-specific supply factors.

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Musy, Sarah N., Olga Endrich, Alexander B. Leichtle, Peter Griffiths, Christos T. Nakas, and Michael Simon. "Longitudinal Study of the Variation in Patient Turnover and Patient-to-Nurse Ratio: Descriptive Analysis of a Swiss University Hospital." Journal of Medical Internet Research 22, no. 4 (April 2, 2020): e15554. http://dx.doi.org/10.2196/15554.

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Background Variations in patient demand increase the challenge of balancing high-quality nursing skill mixes against budgetary constraints. Developing staffing guidelines that allow high-quality care at minimal cost requires first exploring the dynamic changes in nursing workload over the course of a day. Objective Accordingly, this longitudinal study analyzed nursing care supply and demand in 30-minute increments over a period of 3 years. We assessed 5 care factors: patient count (care demand), nurse count (care supply), the patient-to-nurse ratio for each nurse group, extreme supply-demand mismatches, and patient turnover (ie, number of admissions, discharges, and transfers). Methods Our retrospective analysis of data from the Inselspital University Hospital Bern, Switzerland included all inpatients and nurses working in their units from January 1, 2015 to December 31, 2017. Two data sources were used. The nurse staffing system (tacs) provided information about nurses and all the care they provided to patients, their working time, and admission, discharge, and transfer dates and times. The medical discharge data included patient demographics, further admission and discharge details, and diagnoses. Based on several identifiers, these two data sources were linked. Results Our final dataset included more than 58 million data points for 128,484 patients and 4633 nurses across 70 units. Compared with patient turnover, fluctuations in the number of nurses were less pronounced. The differences mainly coincided with shifts (night, morning, evening). While the percentage of shifts with extreme staffing fluctuations ranged from fewer than 3% (mornings) to 30% (evenings and nights), the percentage within “normal” ranges ranged from fewer than 50% to more than 80%. Patient turnover occurred throughout the measurement period but was lowest at night. Conclusions Based on measurements of patient-to-nurse ratio and patient turnover at 30-minute intervals, our findings indicate that the patient count, which varies considerably throughout the day, is the key driver of changes in the patient-to-nurse ratio. This demand-side variability challenges the supply-side mandate to provide safe and reliable care. Detecting and describing patterns in variability such as these are key to appropriate staffing planning. This descriptive analysis was a first step towards identifying time-related variables to be considered for a predictive nurse staffing model.

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Widjaja, Sutono. "Perlindungan Hukum Bagi Pasien Selaku Konsumen terhadap Tindakan Malpraktik di Bidang Kesehatan." JURNAL RECHTENS 9, no. 1 (June 3, 2020): 39–52. http://dx.doi.org/10.36835/rechtens.v9i1.660.

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Malpractice cases are a crime that is very common in Indonesia. Malpractice is basically the actions of professionals who contravene SOPs, codes of ethics, and applicable laws, whether intentional or as a result of negligence resulting in loss or death to others. On the other hand, in the implementation of health services, medical personnel, namely doctors and nurses do not rule out the possibility of an error or negligence. Errors or negligence by doctors in carrying out their professional duties can be fatal both to the body and soul of the patient (in medical/legal terms this incident is called malpractice) and this is of course very detrimental to the patient as a victim of malpractice. As a victim of malpractice that is harmed , of course the patient will demand what is his right. Patients who are victims of malpractice will demand compensation or ask for accountability from the doctor concerned. These demands can be in the form of civil claims, namely compensation, criminal charges, namely imprisonment for perpetrators of malpractice

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Bergenfeld, Irina, Stacy W. Nganga, Courtni A. Andrews, Vincent L. Fenimore, Nancy A. Otieno, Andrew D. Wilson, Sandra S. Chaves, et al. "Provider perspectives on demand creation for maternal vaccines in Kenya." Gates Open Research 2 (July 19, 2018): 34. http://dx.doi.org/10.12688/gatesopenres.12833.1.

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Background. Expansion of maternal immunization, which offers some of the most effective protection against morbidity and mortality in pregnant women and neonates, requires broad acceptance by healthcare providers and their patients. We aimed to describe issues surrounding acceptance and demand creation for maternal vaccines in Kenya from a provider perspective. Methods. Nurses and clinical officers were recruited for semi-structured interviews covering resources for vaccine delivery, patient education, knowledge and attitudes surrounding maternal vaccines, and opportunities for demand creation for new vaccines. Interviews were conducted in English and Swahili, transcribed verbatim from audio recordings, and analyzed using codes developed from interview guide questions and emergent themes. Results. Providers expressed favorable attitudes about currently available maternal immunizations and introduction of additional vaccines, viewing themselves as primarily responsible for vaccine promotion and patient education. The importance of educational resources for both patients and providers to maintain high levels of maternal immunization coverage was a common theme. Most identified barriers to vaccine acceptance and delivery were cultural and systematic in nature. Suggestions for improvement included improved patient and provider education, including material resources, and community engagement through religious and cultural leaders. Conclusions. The distribution of standardized, evidence-based print materials for patient education may reduce provider overwork and facilitate in-clinic efforts to inform women about maternal vaccines. Continuing education for providers should address communication surrounding current vaccines and those under consideration for introduction into routine schedules. Engagement of religious and community leaders, as well as male decision-makers in the household, will enhance future acceptance of maternal vaccines.

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Litvak, Eugene, Peter I. Buerhaus, Frank Davidoff, Michael C. Long, Michael L. McManus, and Donald M. Berwick. "Managing Unnecessary Variability in Patient Demand to Reduce Nursing Stress and Improve Patient Safety." Joint Commission Journal on Quality and Patient Safety 31, no. 6 (June 2005): 330–38. http://dx.doi.org/10.1016/s1553-7250(05)31044-0.

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Sivrikaya, Orhan, and Enar Tunc. "Demand Forecasting for Domestic Air Transportation in Turkey." Open Transportation Journal 7, no. 1 (May 31, 2013): 20–26. http://dx.doi.org/10.2174/1874447820130508001.

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introduction Patients have the right to influence the care they receive, but their wish to participate in care decision-making is unclear. Aim This study investigates whether participation in nursing documentation influences patient participation in care decision-making, mastery, self-esteem, empowerment and depressive feelings among adult in-patients with chronic disease. Materials and Methodology Adult patients (n=39) with chronic diseases were randomized. The intervention group participated in nursing documentation. Upon departure, patients filled in questionnaires about participation in care decision-making, mastery, self-esteem, empowerment and depressive feelings. Results The majority of the patients preferred a collaborative or passive role regarding care decision-making. Lack of knowledge was one reason for non-participation. Having been diagnosed more than five years previously meant stronger empowerment. Conclusion It is a challenge for nurses to find strategies to assess patients’ wishes regarding participation in care decision-making. Nurses must support patients’ knowledge of their disease and empowerment.

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Fitzgerald, Kristin, Lori Pelletier, and Martin A. Reznek. "A Queue-Based Monte Carlo Analysis to Support Decision Making for Implementation of an Emergency Department Fast Track." Journal of Healthcare Engineering 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/6536523.

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Emergency departments (EDs) are seeking ways to utilize existing resources more efficiently as they face rising numbers of patient visits. This study explored the impact on patient wait times and nursing resource demand from the addition of a fast track, or separate unit for low-acuity patients, in the ED using a queue-based Monte Carlo simulation in MATLAB. The model integrated principles of queueing theory and expanded the discrete event simulation to account for time-based arrival rates. Additionally, the ED occupancy and nursing resource demand were modeled and analyzed using the Emergency Severity Index (ESI) levels of patients, rather than the number of beds in the department. Simulation results indicated that the addition of a separate fast track with an additional nurse reduced overall median wait times by 35.8 ± 2.2 percent and reduced average nursing resource demand in the main ED during hours of operation. This novel modeling approach may be easily disseminated and informs hospital decision-makers of the impact of implementing a fast track or similar system on both patient wait times and acuity-based nursing resource demand.

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Colosi, Marc L. "Nurses: when supply fails demand, a patient care catastrophe looms." Nurse Leader 5, no. 6 (December 2007): 46–53. http://dx.doi.org/10.1016/j.mnl.2006.09.015.

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Schwierz, Christoph, Boris Augurzky, Axel Focke, and Jürgen Wasem. "Demand, selection and patient outcomes in German acute care hospitals." Health Economics 21, no. 3 (February 4, 2011): 209–21. http://dx.doi.org/10.1002/hec.1706.

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BRITTEN, NICKY. "Patient Demand for Prescriptions: a View from the Other Side." Family Practice 11, no. 1 (1994): 62–66. http://dx.doi.org/10.1093/fampra/11.1.62.

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Mahutte, C. K., M. Holody, T. P. Maxwell, P. A. Chen, and S. A. Sasse. "Development of a patient-dedicated, on-demand, blood gas monitor." American Journal of Respiratory and Critical Care Medicine 149, no. 4 (April 1994): 852–59. http://dx.doi.org/10.1164/ajrccm.149.4.8143046.

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MOORS, E. H. M., W. P. C. BOON, R. NAHUIS, and R. L. J. VANDEBERG. "USER-PRODUCER INTERACTIONS IN EMERGING PHARMACEUTICAL AND FOOD INNOVATIONS." International Journal of Innovation Management 12, no. 03 (September 2008): 459–87. http://dx.doi.org/10.1142/s1363919608001984.

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In order to study user-producer interaction (UPI) in emerging pharmaceutical and food innovation processes, a classification of user involvement has been developed, including a contextualised view on UPIs. Case studies are performed on two types of UPI: demand articulation in intermediary organisations and interactive learning in consortia, in the pharmaceutical and food sector, respectively.Regarding demand articulation processes, articulation of problems, needs, demands and expectations through agenda-setting practices is important. Expression and evaluation of demands with other factors leads to moblization of creative potential of prospective users and facilitation of emerging innovation processes.Regarding interactive learning, geographical, organisational, regulatory and cognitive proximity conditions could facilitate structures for emerging technology development, and codes and networks for frequent interaction between complementary stakeholders. Demands, concerns and opportunities are articulated by shared visions. Organised UPIs via intermediary user organisations or consortia seem to be the important tools for demand articulation and interactive learning involving patient organisations, researchers and private and public organisations.

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Mahutte, C. K., S. A. Sasse, P. A. Chen, and M. Holody. "Performance of a patient-dedicated, on-demand blood gas monitor in medical ICU patients." American Journal of Respiratory and Critical Care Medicine 150, no. 3 (September 1994): 865–69. http://dx.doi.org/10.1164/ajrccm.150.3.8087363.

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Journal articles on the topic 'Patient demand'

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