Displaying publications 1 - 20 of 71 in total

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  1. Tong WT, Ng CJ, Lee YK, Lee PY
    J Eval Clin Pract, 2020 Jun;26(3):755-764.
    PMID: 31115132 DOI: 10.1111/jep.13161
    RATIONALE, AIMS, AND OBJECTIVES: Few studies focus on patients' views on factors influencing implementation of patient decision aids (PDAs). This study aims to explore patients' views on the factors influencing implementation of an "insulin choice" PDA in a primary care setting.

    METHODS: This study used a descriptive qualitative study design. Interviews were conducted using a semistructured interview guide developed based on the theoretical domains framework. Nine in-depth interviews and three focus group discussions were conducted with patients with type 2 diabetes who have been advised to start insulin or were currently using insulin and those who had been seeking diabetes treatment in the clinic for more than 1 year. Interviews were conducted after the participants were familiarized with the PDA. Data were analysed using a thematic approach.

    RESULTS: Five themes emerged from the data analysis: (a) trust in the physician (patients preferred physicians to other health care providers in delivering the insulin PDA to them as they trusted physicians more when it comes to making decisions such as starting insulin), (b) physician's attitude (patients were more likely to trust a physician who is friendly and sympathetic hence would be more willing to use the insulin PDA), (c) physician's communication style (patients were more willing to use the insulin PDA if the physicians would take time and guide them in the PDA use), (d) conducive environment (patients preferred to read the PDA at home), and (e) cost (patients would not be willing to pay to use the insulin PDA unless they needed it).

    CONCLUSIONS: Patients want physicians to play a major role in the implementation of the insulin PDA; physicians' communication style and commitment may influence implementation outcomes. Health care authorities need to create a conducive environment and provide patients with free access to PDA to promote effective implementation.

    Matched MeSH terms: Decision Support Techniques
  2. Dranitsaris G, Truter I, Lubbe MS, Sriramanakoppa NN, Mendonca VM, Mahagaonkar SB
    Malays J Med Sci, 2011 Oct;18(4):32-43.
    PMID: 22589671 MyJurnal
    Decision analysis (DA) is commonly used to perform economic evaluations of new pharmaceuticals. Using multiples of Malaysia's per capita 2010 gross domestic product (GDP) as the threshold for economic value as suggested by the World Health Organization (WHO), DA was used to estimate a price per dose for bevacizumab, a drug that provides a 1.4-month survival benefit in patients with metastatic colorectal cancer (mCRC).
    Matched MeSH terms: Decision Support Techniques
  3. Mat Lazim NH, Syed A, Lee C, Ahmed Abousheishaa A, Chong Guan N
    Patient Educ Couns, 2024 Jul;124:108266.
    PMID: 38565074 DOI: 10.1016/j.pec.2024.108266
    OBJECTIVE: To examine the use of decision support tools in decision making about antidepressants during conversations between patients with major depressive disorder (MDD) and their psychiatrists.

    METHODS: Theme-oriented discourse analysis of two psychiatric consultation groups: control (n = 17) and intervention (n = 16). In the control group, only a doctor's conversation guide was used; in the intervention group, the conversation guide and a patient decision aid (PDA) were used.

    RESULTS: Psychiatrists mainly dominated conversations in both consultation groups. They were less likely to elicit patient treatment-related perspectives in the intervention group as they focused more on delivering the information than obtaining patient perspectives. However, using PDA in the intervention group slightly encouraged patients to participate in decisional talk.

    CONCLUSION: The decision support tools did promote SDM performance. Using the conversation guide in both consultation groups encouraged the elicitation of patient perspectives, which helped the psychiatrists in tailoring their recommendations of options based on patient preferences and concerns. Using the PDA in the intervention group created space for treatment discussion and fostered active collaboration in treatment decision making.

    PRACTICE IMPLICATIONS: Our findings have implications for SDM communication skills training and critical reflection on SDM practice.

    Matched MeSH terms: Decision Support Techniques*
  4. Syed A, Mohd Don Z, Ng CJ, Lee YK, Khoo EM, Lee PY, et al.
    BMJ Open, 2017 05 09;7(5):e014260.
    PMID: 28490553 DOI: 10.1136/bmjopen-2016-014260
    OBJECTIVE: To investigate whether the use of apatient decision aid (PDA) for insulin initiation fulfils its purpose of facilitating patient-centred decision-making through identifying how doctors and patients interact when using the PDA during primary care consultations.
    DESIGN: Conversation analysis of seven single cases of audio-recorded/video-recorded consultations between doctors and patients with type 2 diabetes, using a PDA on starting insulin.
    SETTING: Primary care in three healthcare settings: (1) one private clinic; (2) two public community clinics and (3) one primary care clinic in a public university hospital, in Negeri Sembilan and the Klang Valley in Malaysia.
    PARTICIPANTS: Clinicians and seven patients with type 2 diabetes to whom insulin had been recommended. Purposive sampling was used to select a sample high in variance across healthcare settings, participant demographics and perspectives on insulin.
    PRIMARY OUTCOME MEASURES: Interaction between doctors and patients in a clinical consultation involving the use of a PDA about starting insulin.
    RESULTS: Doctors brought the PDA into the conversation mainly by asking information-focused 'yes/no' questions, and used the PDA for information exchange only if patients said they had not read it. While their contributions were limited by doctors' questions, some patients disclosed issues or concerns. Although doctors' PDA-related questions acted as a presequence to deliberation on starting insulin, their interactional practices raised questions on whether patients were informed and their preferences prioritised.
    CONCLUSIONS: Interactional practices can hinder effective PDA implementation, with habits from ordinary conversation potentially influencing doctors' practices and complicating their implementation of patient-centred decision-making. Effective interaction should therefore be emphasised in the design and delivery of PDAs and in training clinicians to use them.
    Matched MeSH terms: Decision Support Techniques*
  5. Biswas R, Martin CM, Sturmberg J, Shanker R, Umakanth S, Shanker S, et al.
    J Eval Clin Pract, 2008 Oct;14(5):742-9.
    PMID: 19018905 DOI: 10.1111/j.1365-2753.2008.00998.x
    Evidence based on average patient data, which occupies most of our present day information databases, does not fulfil the needs of individual patient-centred health care. In spite of the unprecedented expansion in medical information we still do not have the types of information required to allow us to tailor optimal care for a given individual patient. As our current information is chiefly provided in disconnected silos, we need an information system that can seamlessly integrate different types of information to meet diverse user group needs. Groups of certain individual medical learners namely patients, medical students and health professionals share the patient's need to increasingly interact with and seek knowledge and solutions offered by others (individual medical learners) who have the lived experiences that they would benefit to access and learn from. A web-based user-driven learning solution may be a stepping-stone to address the present problem of information oversupply in medicine that mostly remains underutilized, as it doesn't meet the needs of the individual patient and health professional user. The key to its success would be to relax central control and make local trust and strategic health workers feel more engaged in the project such that it is truly user-driven.
    Matched MeSH terms: Decision Support Techniques
  6. Lee YK, Lee PY, Ng CJ, Teo CH, Abu Bakar AI, Abdullah KL, et al.
    Inform Health Soc Care, 2018 Jan;43(1):73-83.
    PMID: 28139158 DOI: 10.1080/17538157.2016.1269108
    This study aimed to evaluate the usability (ease of use) and utility (impact on user's decision-making process) of a web-based patient decision aid (PDA) among older-age users. A pragmatic, qualitative research design was used. We recruited patients with type 2 diabetes who were at the point of making a decision about starting insulin from a tertiary teaching hospital in Malaysia in 2014. Computer screen recording software was used to record the website browsing session and in-depth interviews were conducted while playing back the website recording. The interviews were analyzed using the framework approach to identify usability and utility issues. Three cycles of iteration were conducted until no more major issues emerged. Thirteen patients participated: median age 65 years old, 10 men, and nine had secondary education/diploma, four were graduates/had postgraduate degree. Four usability issues were identified (navigation between pages and sections, a layout with open display, simple language, and equipment preferences). For utility, participants commented that the website influenced their decision about insulin in three ways: it had provided information about insulin, it helped them deliberate choices using the option-attribute matrix, and it allowed them to involve others in their decision making by sharing the PDA summary printout.
    Study site: urban tertiary teaching hospital outpatient clinic in Malaysia (primary care clinic, University Malaya Medical Centre, UMMC, Kuala Lumpur, Malaysia)
    Matched MeSH terms: Decision Support Techniques*
  7. Lee YK, Ng CJ
    Z Evid Fortbild Qual Gesundhwes, 2017 Jun;123-124:66-68.
    PMID: 28527637 DOI: 10.1016/j.zefq.2017.05.019
    Shared decision making (SDM) activities in Malaysia began around 2010. Although the concept is not widespread, there are opportunities to implement SDM in both the public and private healthcare sectors. Malaysia has a multicultural society and cultural components (such as language differences, medical paternalism, strong family involvement, religious beliefs and complementary medicine) influence medical decision making. In terms of policy, the Ministry of Health has increasingly mentioned patient-centered care as a component of healthcare delivery while the Malaysian Medical Council's guidelines on doctors' duties mentioned collaborative partnerships as a goal of doctor-patient relationships. Current research on SDM comprises baseline surveys of decisional role preferences, development and implementation of locally developed patient decision aids, and conducting of SDM training workshops. Most of this research is carried out by public research universities. In summary, the current state of SDM in Malaysia is still at its infancy. However, there are increasing recognition and efforts from the academic institutions and Ministry of Health to conduct research in SDM, develop patient decision support tools and initiate national discussion on patient involvement in decision making.
    Matched MeSH terms: Decision Support Techniques
  8. Wong HS, Subramaniam S, Alias Z, Taib NA, Ho GF, Ng CH, et al.
    Medicine (Baltimore), 2015 Feb;94(8):e593.
    PMID: 25715267 DOI: 10.1097/MD.0000000000000593
    Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480 patients who underwent complete surgical treatment for stages I to III breast cancer from 1998 to 2006 were identified from the prospective breast cancer registry of University Malaya Medical Centre, Kuala Lumpur, Malaysia. Calibration was evaluated by comparing the model-predicted overall survival (OS) with patients' actual OS. Model discrimination was tested using receiver-operating characteristic (ROC) analysis. Median age at diagnosis was 50 years. The median tumor size at presentation was 3 cm and 54% of patients had lymph node-negative disease. About 55% of women had estrogen receptor-positive breast cancer. Overall, the model-predicted 5 and 10-year OS was 86.3% and 77.5%, respectively, whereas the observed 5 and 10-year OS was 87.6% (difference: -1.3%) and 74.2% (difference: 3.3%), respectively; P values for goodness-of-fit test were 0.18 and 0.12, respectively. The program was accurate in most subgroups of patients, but significantly overestimated survival in patients aged <40 years, and in those receiving neoadjuvant chemotherapy. PREDICT performed well in terms of discrimination; areas under ROC curve were 0.78 (95% confidence interval [CI]: 0.74-0.81) and 0.73 (95% CI: 0.68-0.78) for 5 and 10-year OS, respectively. Based on its accurate performance in this study, PREDICT may be clinically useful in prognosticating women with breast cancer and personalizing breast cancer treatment in resource-limited settings.
    Matched MeSH terms: Decision Support Techniques*
  9. Bewersdorf JP, Hautmann O, Kofink D, Abdul Khalil A, Zainal Abidin I, Loch A
    Eur J Emerg Med, 2017 Jun;24(3):170-175.
    PMID: 26524675 DOI: 10.1097/MEJ.0000000000000344
    OBJECTIVES: The aim of the study was to identify covariates associated with 28-day mortality in septic patients admitted to the emergency department and derive and validate a score that stratifies mortality risk utilizing parameters that are readily available.

    METHODS: Patients with an admission diagnosis of suspected or confirmed infection and fulfilling at least two criteria for severe inflammatory response syndrome were included in this study. Patients' characteristics, vital signs, and laboratory values were used to identify prognostic factors for mortality. A scoring system was derived and validated. The primary outcome was the 28-day mortality rate.

    RESULTS: A total of 440 patients were included in the study. The 28-day hospital mortality rate was 32.4 and 25.2% for the derivation (293 patients) and validation (147 patients) sets, respectively. Factors associated with a higher mortality were immune-suppressed state (odds ratio 4.7; 95% confidence interval 2.0-11.4), systolic blood pressure on arrival less than 90 mmHg (3.8; 1.7-8.3), body temperature less than 36.0°C (4.1; 1.3-12.9), oxygen saturation less than 90% (2.3; 1.1-4.8), hematocrit less than 0.38 (3.1; 1.6-5.9), blood pH less than 7.35 (2.0; 1.04-3.9), lactate level more than 2.4 mmol/l (2.27; 1.2-4.2), and pneumonia as the source of infection (2.7; 1.5-5.0). The area under the receiver operating characteristic curve was 0.81 (0.75-0.86) in the derivation and 0.81 (0.73-0.90) in the validation set. The SPEED (sepsis patient evaluation in the emergency department) score performed better (P=0.02) than the Mortality in Emergency Department Sepsis score when applied to the complete study population with an area under the curve of 0.81 (0.76-0.85) as compared with 0.74 (0.70-0.79).

    CONCLUSION: The SPEED score predicts 28-day mortality in septic patients. It is simple and its predictive value is comparable to that of other scoring systems.

    Matched MeSH terms: Decision Support Techniques*
  10. Albahri OS, Zaidan AA, Albahri AS, Zaidan BB, Abdulkareem KH, Al-Qaysi ZT, et al.
    J Infect Public Health, 2020 Oct;13(10):1381-1396.
    PMID: 32646771 DOI: 10.1016/j.jiph.2020.06.028
    This study presents a systematic review of artificial intelligence (AI) techniques used in the detection and classification of coronavirus disease 2019 (COVID-19) medical images in terms of evaluation and benchmarking. Five reliable databases, namely, IEEE Xplore, Web of Science, PubMed, ScienceDirect and Scopus were used to obtain relevant studies of the given topic. Several filtering and scanning stages were performed according to the inclusion/exclusion criteria to screen the 36 studies obtained; however, only 11 studies met the criteria. Taxonomy was performed, and the 11 studies were classified on the basis of two categories, namely, review and research studies. Then, a deep analysis and critical review were performed to highlight the challenges and critical gaps outlined in the academic literature of the given subject. Results showed that no relevant study evaluated and benchmarked AI techniques utilised in classification tasks (i.e. binary, multi-class, multi-labelled and hierarchical classifications) of COVID-19 medical images. In case evaluation and benchmarking will be conducted, three future challenges will be encountered, namely, multiple evaluation criteria within each classification task, trade-off amongst criteria and importance of these criteria. According to the discussed future challenges, the process of evaluation and benchmarking AI techniques used in the classification of COVID-19 medical images considered multi-complex attribute problems. Thus, adopting multi-criteria decision analysis (MCDA) is an essential and effective approach to tackle the problem complexity. Moreover, this study proposes a detailed methodology for the evaluation and benchmarking of AI techniques used in all classification tasks of COVID-19 medical images as future directions; such methodology is presented on the basis of three sequential phases. Firstly, the identification procedure for the construction of four decision matrices, namely, binary, multi-class, multi-labelled and hierarchical, is presented on the basis of the intersection of evaluation criteria of each classification task and AI classification techniques. Secondly, the development of the MCDA approach for benchmarking AI classification techniques is provided on the basis of the integrated analytic hierarchy process and VlseKriterijumska Optimizacija I Kompromisno Resenje methods. Lastly, objective and subjective validation procedures are described to validate the proposed benchmarking solutions.
    Matched MeSH terms: Decision Support Techniques*
  11. Ramli AS, Lakshmanan S, Haniff J, Selvarajah S, Tong SF, Bujang MA, et al.
    BMC Fam Pract, 2014;15:151.
    PMID: 25218689 DOI: 10.1186/1471-2296-15-151
    Chronic disease management presents enormous challenges to the primary care workforce because of the rising epidemic of cardiovascular risk factors. The chronic care model was proven effective in improving chronic disease outcomes in developed countries, but there is little evidence of its effectiveness in developing countries. The aim of this study was to evaluate the effectiveness of the EMPOWER-PAR intervention (multifaceted chronic disease management strategies based on the chronic care model) in improving outcomes for type 2 diabetes mellitus and hypertension using readily available resources in the Malaysian public primary care setting. This paper presents the study protocol.
    Matched MeSH terms: Decision Support Techniques
  12. Arshad S, Lihan T, Rahman ZA, Idris WMR
    Environ Sci Pollut Res Int, 2023 Sep;30(41):93760-93778.
    PMID: 37516702 DOI: 10.1007/s11356-023-28764-7
    Globally, around 1.3 billion tonnes of waste are generated annually, and solid waste management has thus become a major concern worldwide. There are projections of a 70% increase in waste generation from 2016 to 2050 owing to urbanization and the rapid growth of the global population. Estimates indicate that around 38,200 tonnes of waste are generated per day in Malaysia, and this volume of waste is significantly shortening the planned life spans of operating sanitary landfills in the country. Batu Pahat is a district in the state of Johor, Malaysia, with a relatively large population of 495,000 and with no record of an operational sanitary landfill. This study was conducted to identify and classify the most suitable sites for sanitary landfill developments in southern Peninsular Malaysia by means of the Analytical Hierarchy Process (AHP), which is recognized as a competent technique for multicriteria decision-making. The resulting landfill site suitability index map established 33.88 km2 of area coverage as very highly suitable for landfill development, while 353.86 km2 of area coverage was classified as unsuitable. Sites 1-6 were identified as the most suitable for landfill activities. Sites 1-5 are situated in agricultural land areas, while site 6 is in a forested land area; this implies public participation and the adoption of compensatory measures in the event of landfill development in these areas, given their socioeconomic importance. The six suitable sites are all at least 2000 m from rivers: 2000-3000 m for sites 1, 3, and 5 and > 3000 m for sites 2, 4, and 6. The six sites are all > 3000 m from fault zones and > 1000 m from flood-prone areas, meaning that occurrences such as fault movements and flooding will have minimal impact on the operational activities of landfills at these sites. The selection of sites 1-6 as very suitable for landfill development was associated with an overall accuracy rating of 93.33% and kappa coefficient score of 0.92 based on accuracy assessment analysis of all sites. This study will guide the actions of policymakers, city planners, and local authorities toward sustainable and environment-friendly landfill development and operation in Batu Pahat and other districts in the state of Johor.
    Matched MeSH terms: Decision Support Techniques
  13. Ng CJ, Lee YK, Abdullah A, Abu Bakar AI, Tun Firzara AM, Tiew HW
    J Eval Clin Pract, 2019 Dec;25(6):1074-1079.
    PMID: 31099120 DOI: 10.1111/jep.13163
    It is common for primary care providers (PCPs) to manage complex multimorbidity. When caring for patients with multimorbidity, PCPs face challenges to tackle several issues within a short consultation in order to address patients' complex needs. Furthermore, some PCPs may lack access to a multidisciplinary team and need to manage multimorbidity within the confine of a PCP-patient partnership only. Instead of attempting to address multiple health issues within a single consultation, it would be more feasible and time effective for PCPs and patients to jointly prioritize the health issue to focus on. Using the Malaysian primary care setting as a case study, a dual-layer-shared decision-making approach is proposed whereby PCPs and patients make decisions on which disease(s) (layer 1) and treatment(s) (layer 2) to prioritize. This dual-layer model aims to address the challenges of short consultation time and limited healthcare resources by encouraging PCPs and patients to discuss, negotiate, and agree on the decision during the consultation to ensure patients' health needs are addressed.
    Matched MeSH terms: Decision Support Techniques
  14. Manap N, Voulvoulis N
    Sci Total Environ, 2014 Oct 15;496:607-623.
    PMID: 25108801 DOI: 10.1016/j.scitotenv.2014.07.009
    The aim of this study was to develop a risk-based decision-making framework for the selection of sediment dredging option. Descriptions using case studies of the newly integrated, holistic and staged framework were followed. The first stage utilized the historical dredging monitoring data and the contamination level in media data into Ecological Risk Assessment phases, which have been altered for benefits in cost, time and simplicity. How Multi-Criteria Decision Analysis (MCDA) can be used to analyze and prioritize dredging areas based on environmental, socio-economic and managerial criteria was described for the next stage. The results from MCDA will be integrated into Ecological Risk Assessment to characterize the degree of contamination in the prioritized areas. The last stage was later described using these findings and analyzed using MCDA, in order to identify the best sediment dredging option, accounting for the economic, environmental and technical aspects of dredging, which is beneficial for dredging and sediment management industries.
    Matched MeSH terms: Decision Support Techniques*
  15. Chen YH, Leong WS, Lin MS, Huang CC, Hung CS, Li HY, et al.
    JACC Cardiovasc Interv, 2016 09 12;9(17):1825-32.
    PMID: 27609258 DOI: 10.1016/j.jcin.2016.06.015
    OBJECTIVES: This study sought to determine predictors for successful endovascular treatment in patients with chronic carotid artery occlusion (CAO).

    BACKGROUND: Endovascular recanalization in patients with chronic CAO has been reported to be feasible, but technically challenging.

    METHODS: Endovascular attempts in 138 consecutive chronic CAO patients with impaired ipsilateral hemisphere perfusion were reviewed. We analyzed potential variables including epidemiology, symptomatology, angiographic morphology, and interventional techniques in relation to the technical success.

    RESULTS: The technical success rate was 61.6%. Multivariate analysis showed absence of prior neurologic event (odds ratio [OR]: 0.27; 95% confidence interval [CI]: 0.10 to 0.76), nontapered stump (OR: 0.18; 95% CI: 0.05 to 0.67), distal internal carotid artery (ICA) reconstitution via contralateral injection (OR: 0.19; 95% CI: 0.05 to 0.75), and distal ICA reconstitution at communicating or ophthalmic segments (OR:0.12; 95% CI: 0.04 to 0.36) to be independent factors associated with lower technical success. Point scores were assigned proportional to model coefficients, and technical success rates were >80% and <40% in patients with scores of ≤1 and ≥4, respectively. The c-indexes for this score system in predicting technical success was 0.820 (95% CI: 0.748 to 0.892; p < 0.001) with a sensitivity of 84.7% and a specificity of 67.9%.

    CONCLUSIONS: Absence of prior neurologic event, nontapered stump, distal ICA reconstitution via contralateral injection, and distal ICA reconstitution at communicating or ophthalmic segments were identified as independent negative predictors for technical success in endovascular recanalization for CAO.

    Matched MeSH terms: Decision Support Techniques
  16. Ng CJ, Lee PY
    Malays Fam Physician, 2021 Mar 25;16(1):2-7.
    PMID: 33948136 DOI: 10.51866/cm0001
    Making healthcare decisions collaboratively between patients and doctors can be challenging in primary care, as clinical encounters are often short. Conflicts between patients and doctors during the decision-making process may affect both patient and doctor satisfaction and result in medico-legal consequences. With the increasing recognition of the importance of patient empowerment, shared decision making (SDM) can serve as a practical consultation model for primary care doctors (PCDs) to guide patients in making informed healthcare choices. Although more research is needed to find effective ways to implement SDM in the real world, the 6-step approach presented in this paper can guide PCDs to practise SDM in their daily practice. Implementation of SDM can be further enhanced by incorporating SDM training into undergraduate and postgraduate curricula and using evidence-based tools such as patient decision aids.
    Matched MeSH terms: Decision Support Techniques
  17. Chew KS, van Merrienboer JJG, Durning SJ
    BMC Med Educ, 2019 Jan 10;19(1):18.
    PMID: 30630472 DOI: 10.1186/s12909-018-1451-4
    BACKGROUND: Establishing a diagnosis is a complex, iterative process involving patient data gathering, integration and interpretation. Premature closure is a fallacious cognitive tendency of closing the diagnostic process before sufficient data have been gathered. A proposed strategy to minimize premature closure is the use of a checklist to trigger metacognition (the process of monitoring one's own thinking). A number of studies have suggested the effectiveness of this strategy in classroom settings. This qualitative study examined the perception of usability of a metacognitive mnemonic checklist called TWED checklist (where the letter "T = Threat", "W = What if I am wrong? What else?", "E = Evidence" and "D = Dispositional influence") in a real clinical setting.

    METHOD: Two categories of participants, i.e., medical doctors (n = 11) and final year medical students (Group 1, n = 5; Group 2, n = 10) participated in four separate focus group discussions. Nielsen's 5 dimensions of usability (i.e. learnability, effectiveness, memorability, errors, and satisfaction) and Pentland's narrative network were adapted as the framework to study the usability and the implementation of the checklist in a real clinical setting respectively.

    RESULTS: Both categories (medical doctors and medical students) of participants found that the TWED checklist was easy to learn and effective in promoting metacognition. For medical student participants, items "T" and "W" were believed to be the two most useful aspects of the checklist, whereas for the doctor participants, it was item "D". Regarding its implementation, item "T" was applied iteratively, items "W" and "E" were applied when the outcomes did not turn out as expected, and item "D" was applied infrequently. The one checkpoint where all four items were applied was after the initial history taking and physical examination had been performed to generate the initial clinical impression.

    CONCLUSION: A metacognitive checklist aimed to check cognitive errors may be a useful tool that can be implemented in the real clinical setting.

    Matched MeSH terms: Decision Support Techniques
  18. Azadnia AH, Taheri S, Ghadimi P, Saman MZ, Wong KY
    ScientificWorldJournal, 2013;2013:246578.
    PMID: 23864823 DOI: 10.1155/2013/246578
    One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.
    Matched MeSH terms: Decision Support Techniques*
  19. Goh KL, Cutler A, Chua AB, Ding RP, Kandasami P, Mazlam MZ, et al.
    J Gastroenterol Hepatol, 1999 Jan;14(1):32-8.
    PMID: 10029275
    The aim of the present study was to determine the cost-efficiency of different duodenal ulcer disease treatment practices in Malaysia. Six Malaysian gastroenterologists met to discuss the direct costs related to Helicobacter pylori (HP) eradication treatment. Five treatment strategies were compared: (i) histamine H2 receptor antagonists (H2RA), acid suppression therapy for 6 weeks followed by maintenance therapy as needed; (ii) bismuth triple + proton pump inhibitor (PPI), bismuth (120 mg, q.i.d.), metronidazole (400 mg; t.i.d.), tetracycline (500 mg, q.i.d.) for 7 days and PPI, b.i.d., for 7 days; (iii) OAC, omeprazole (20 mg, b.i.d.), amoxycillin (1000 mg, b.i.d.) and clarithromycin (500 mg, b.i.d.) for 7 days; (iv) OMC, omeprazole (20mg, b.i.d.), metronidazole (400mg, b.i.d.) and clarithromycin (500 mg, b.i.d.) for 7 days; and (v) OAM, omeprazole (20 mg, b.i.d.), amoxycillin (1000 mg, b.i.d.) and metronidazole (400 mg, b.i.d.) for 7 days. A decision tree model was created to determine which therapy would be the most cost-effective. The model considered eradication rates, resistance to anti-microbial agents, compliance and cost implications of treatment regimens, physician visits and ulcer recurrences during a 1 year time period assumption. The H2RA maintenance therapy was the most expensive treatment at Malaysian Ringgit (MR) 2335, followed by bismuth triple therapy (MR 1839), OMC (MR 1786), OAM (MR 1775) and OAC, being the most cost-effective therapy, at MR 1679. In conclusion, HP eradication therapy is superior to H2RA maintenance therapy in the treatment of duodenal ulcer disease. Of the HP eradication regimens, OAC is the most cost-effective.
    Matched MeSH terms: Decision Support Techniques*
  20. Loo CK, Rajeswari M, Rao MV
    IEEE Trans Neural Netw, 2004 Nov;15(6):1378-95.
    PMID: 15565767
    This paper presents two novel approaches to determine optimum growing multi-experts network (GMN) structure. The first method called direct method deals with expertise domain and levels in connection with local experts. The growing neural gas (GNG) algorithm is used to cluster the local experts. The concept of error distribution is used to apportion error among the local experts. After reaching the specified size of the network, redundant experts removal algorithm is invoked to prune the size of the network based on the ranking of the experts. However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. SGMN adopts self-adaptive learning rates for gradient-descent learning rules. In addition, SGMN adopts a more rigorous clustering method called fully self-organized simplified adaptive resonance theory in a modified form. Experimental results show SGMN obtains comparative or even better performance than GMN in four benchmark examples, with reduced sensitivity to learning parameters setting. Moreover, both GMN and SGMN outperform the other neural networks and statistical models. The efficacy of SGMN is further justified in three industrial applications and a control problem. It provides consistent results besides holding out a profound potential and promise for building a novel type of nonlinear model consisting of several local linear models.
    Matched MeSH terms: Decision Support Techniques*
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