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Clinical decision-making, knowledge support systems, and theory’

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  1. A pandemic affects healthcare delivery and consequently leads to socioeconomic complications. During a pandemic, a community where there lives an asymptomatic patient (AP) becomes a potential endemic zone. Assumi...

    Authors: Daniel Adu-Gyamfi, Fengli Zhang and Albert Kofi Kwansah Ansah

    Citation: BMC Medical Informatics and Decision Making 2020 20:245

    Content type: Research article

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  2. Clinical Decision Support Systems (CDSSs) have recently attracted attention as a method for minimizing medical errors. Existing CDSSs are limited in that they do not reflect actual data. To overcome this limit...

    Authors: Jin-Hyeok Park, Jeong-Heum Baek, Sun Jin Sym, Kang Yoon Lee and Youngho Lee

    Citation: BMC Medical Informatics and Decision Making 2020 20:241

    Content type: Research article

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  3. The present study aims to investigate the role of histogram analysis of intravoxel incoherent motion (IVIM) in the differential diagnosis of benign and malignant breast lesions.

    Authors: Ya-Nan Jin, Yan Zhang, Jing-Liang Cheng, Xiao-Pan Zhang, Ying Hu and Xiao-Ning Shao

    Citation: BMC Medical Informatics and Decision Making 2020 20:239

    Content type: Research article

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  4. Clinical decision aids are used in various medical fields to support patients and clinicians when making healthcare decisions. Few attempts have been made to implement such tools in psychiatry. We developed Tr...

    Authors: Lukas O. Roebroek, Jojanneke Bruins, Philippe Delespaul, Albert Boonstra and Stynke Castelein

    Citation: BMC Medical Informatics and Decision Making 2020 20:234

    Content type: Research article

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  5. Nearly half of all mental health disorders develop prior to the age of 15. Early assessments, diagnosis, and treatment are critical to shortening single episodes of care, reducing possible comorbidity and long...

    Authors: Carolyn E. Clausen, Bennett L. Leventhal, Øystein Nytrø, Roman Koposov, Odd Sverre Westbye, Thomas Brox Røst, Victoria Bakken, Kaban Koochakpour, Ketil Thorvik and Norbert Skokauskas

    Citation: BMC Medical Informatics and Decision Making 2020 20:232

    Content type: Study protocol

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  6. Patients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medi...

    Authors: Jannik Schaaf, Hans-Ulrich Prokosch, Martin Boeker, Johanna Schaefer, Jessica Vasseur, Holger Storf and Martin Sedlmayr

    Citation: BMC Medical Informatics and Decision Making 2020 20:230

    Content type: Research article

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  7. Parkinson’s Disease (PD) is a clinically diagnosed neurodegenerative disorder that affects both motor and non-motor neural circuits. Speech deterioration (hypokinetic dysarthria) is a common symptom, which oft...

    Authors: Ibrahim Karabayir, Samuel M. Goldman, Suguna Pappu and Oguz Akbilgic

    Citation: BMC Medical Informatics and Decision Making 2020 20:228

    Content type: Research article

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  8. Breast cancer is the most prevalent and among the most deadly cancers in females. Patients with breast cancer have highly variable survival lengths, indicating a need to identify prognostic biomarkers for pers...

    Authors: Li Tong, Jonathan Mitchel, Kevin Chatlin and May D. Wang

    Citation: BMC Medical Informatics and Decision Making 2020 20:225

    Content type: Research article

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  9. Access to health care is a fundamental human right, and the provision of affordable, high-quality, and appropriate medicines for maternal and child health is a vital component of a well-functioning health syst...

    Authors: Abel Demerew Hailu and Solomon Ahmed Mohammed

    Citation: BMC Medical Informatics and Decision Making 2020 20:221

    Content type: Research article

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  10. Most cost-effectiveness analyses in the context of cervical cancer prevention involve the use of mathematical models to simulate HPV infection, cervical disease and prevention strategies. However, it is common...

    Authors: David Moriña, José Ignacio Martí, Pedro Puig and Mireia Diaz

    Citation: BMC Medical Informatics and Decision Making 2020 20:211

    Content type: Software

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  11. Clinical analytics is a rapidly developing area of informatics and knowledge mobilisation which has huge potential to improve healthcare in the future. It is widely acknowledged to be a powerful mediator of cl...

    Authors: Kim Sutherland, Wilson Yeung, Yoke Mak and Jean-Frederic Levesque

    Citation: BMC Medical Informatics and Decision Making 2020 20:210

    Content type: Research article

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  12. Gastrointestinal (GI) cancer including colorectal cancer, gastric cancer, pancreatic cancer, etc., are among the most frequent malignancies diagnosed annually and represent a major public health problem worldw...

    Authors: Charles C. N. Wang, Jennifer Jin, Jan-Gowth Chang, Masahiro Hayakawa, Atsushi Kitazawa, Jeffrey J. P. Tsai and Phillip C.-Y. Sheu

    Citation: BMC Medical Informatics and Decision Making 2020 20:208

    Content type: Research article

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  13. The prevalence of medical misinformation on the Internet has received much attention among researchers concerned that exposure to such information may inhibit patient adherence to prescriptions. Yet, little is...

    Authors: Nickolas M. Jones, Dana B. Mukamel, Shaista Malik, Robert S. Greenfield, Andrew Reikes, Nathan D. Wong and Emilie Chow

    Citation: BMC Medical Informatics and Decision Making 2020 20:197

    Content type: Research article

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  14. Drug-laboratory (lab) interactions (DLIs) are a common source of preventable medication errors. Clinical decision support systems (CDSSs) are promising tools to decrease such errors by improving prescription q...

    Authors: Zahra Niazkhani, Mahsa Fereidoni, Parviz Rashidi Khazaee, Afshin Shiva, Khadijeh Makhdoomi, Andrew Georgiou and Habibollah Pirnejad

    Citation: BMC Medical Informatics and Decision Making 2020 20:196

    Content type: Research article

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  15. Nearly half of US adults with diagnosed hypertension have uncontrolled blood pressure. Clinical inertia may contribute, including patient-physician uncertainty about how variability in blood pressures impacts ...

    Authors: Richelle J. Koopman, Shannon M. Canfield, Jeffery L. Belden, Pete Wegier, Victoria A. Shaffer, K. D. Valentine, Akshay Jain, Linsey M. Steege, Sonal J. Patil, Mihail Popescu and Michael L. LeFevre

    Citation: BMC Medical Informatics and Decision Making 2020 20:195

    Content type: Research article

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  16. There are serious safety risks associated with chemotherapy, often associated with interdependencies in regimens administered over months or years. Various strategies are used to manage these risks. Computeriz...

    Authors: Valentina Lichtner, Bryony Dean Franklin, Luciano Dalla-Pozza and Johanna I. Westbrook

    Citation: BMC Medical Informatics and Decision Making 2020 20:193

    Content type: Research article

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  17. Asthma is one of the most common chronic diseases in childhood. Regular follow-up of physiological parameters in the home setting, in relation to asthma symptoms, can provide complementary quantitative insight...

    Authors: M. R. van der Kamp, E. C. Klaver, B. J. Thio, J. M. M. Driessen, F. H. C. de Jongh, M. Tabak, J. van der Palen and H. J. Hermens

    Citation: BMC Medical Informatics and Decision Making 2020 20:192

    Content type: Research article

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  18. Many suggest that shared decision-making (SDM) is the most effective approach to clinical counseling. It is unclear if this applies to surgical decision-making-especially regarding urgent, highly-morbid operat...

    Authors: Laura A. Shinkunas, Caleb J. Klipowicz and Erica M. Carlisle

    Citation: BMC Medical Informatics and Decision Making 2020 20:190

    Content type: Research article

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  19. Shared decision making with older adults living with neurocognitive disorders is challenging for primary healthcare professionals. We studied the implementation of a professional training program featuring an ...

    Authors: Moulikatou Adouni Lawani, Luc Côté, Laetitia Coudert, Michèle Morin, Holly O. Witteman, Danielle Caron, Edeltraut Kroger, Philippe Voyer, Charo Rodriguez, France Légaré and Anik M. C. Giguere

    Citation: BMC Medical Informatics and Decision Making 2020 20:189

    Content type: Research article

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  20. Administrative healthcare databases are widespread and are often standardized with regard to their content and data coding, thus they can be used also as data sources for surveillance and epidemiological resea...

    Authors: Dino Gibertoni, Claudio Voci, Marica Iommi, Benedetta D’Ercole, Marcora Mandreoli, Antonio Santoro and Elena Mancini

    Citation: BMC Medical Informatics and Decision Making 2020 20:185

    Content type: Research article

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  21. Stakeholder engagement is being increasingly recognised as an important way to achieving impact in public health. The WorkHORSE (Working Health Outcomes Research Simulation Environment) project was designed to co...

    Authors: Ffion Lloyd-Williams, Lirije Hyseni, Maria Guzman-Castillo, Chris Kypridemos, Brendan Collins, Simon Capewell, Ellen Schwaller and Martin O’Flaherty

    Citation: BMC Medical Informatics and Decision Making 2020 20:182

    Content type: Research article

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  22. Malignant pleural effusion (MPE) is a common, serious problem predominantly seen in metastatic lung and breast cancer and malignant pleural mesothelioma. Recurrence of malignant pleural effusion is common, and...

    Authors: Cheryl Grindell, Angela Tod, Remi Bec, Daniel Wolstenholme, Rahul Bhatnagar, Parthipan Sivakumar, Anna Morley, Jayne Holme, Judith Lyons, Maryam Ahmed, Susan Jackson, Deirdre Wallace, Farinaz Noorzad, Meera Kamalanathan, Liju Ahmed and Mathew Evison

    Citation: BMC Medical Informatics and Decision Making 2020 20:179

    Content type: Research article

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  23. More information is often thought to improve medical decision-making, which may lead to test overuse. This study assesses which out of 15 laboratory tests contribute to diagnosing the underlying cause of anaem...

    Authors: Michelle M. A. Kip, Martijn L. J. Oonk, Mark-David Levin, Annemarie Schop, Patrick J. E. Bindels, Ron Kusters and Hendrik Koffijberg

    Citation: BMC Medical Informatics and Decision Making 2020 20:178

    Content type: Research article

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  24. Informational discontinuity can have far reaching consequences like medical errors, increased re-hospitalization rates and adverse events among others. Thus the holy grail of seamless informational continuity ...

    Authors: Naveen R. Gowda, Atul Kumar, Sanjay K. Arya and Vikas H

    Citation: BMC Medical Informatics and Decision Making 2020 20:175

    Content type: Research article

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  25. Shared decision-making improves the quality of patient care. Unfortunately, shared decision-making is not yet common practice among vascular surgeons. Thus, decision support tools were developed to assist vasc...

    Authors: S. M. L. de Mik, F. E. Stubenrouch, D. A. Legemate, R. Balm and D. T. Ubbink

    Citation: BMC Medical Informatics and Decision Making 2020 20:172

    Content type: Study protocol

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  26. The exact risk of developing QTc-prolongation when using a combination of QTc-prolonging drugs is still unknown, making it difficult to interpret these QT drug-drug interactions (QT-DDIs). A tool to identify h...

    Authors: Florine A. Berger, Heleen van der Sijs, Matthijs L. Becker, Teun van Gelder and Patricia M. L. A. van den Bemt

    Citation: BMC Medical Informatics and Decision Making 2020 20:171

    Content type: Research article

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  27. Parent-clinician shared decision making is the recommended model for the care of premature infants; thus, clinicians provide prenatal prematurity counseling to parents in the event of a mother’s hospitalizatio...

    Authors: Nicole M. Rau, Mir A. Basir and Kathryn E. Flynn

    Citation: BMC Medical Informatics and Decision Making 2020 20:169

    Content type: Research article

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  28. “Artificial intelligence” (AI) is often referred to as “augmented human intelligence” (AHI). The latter term implies that computers support—rather than replace—human decision-making. It is unclear whether the ...

    Authors: Santiago Romero-Brufau, Kirk D. Wyatt, Patricia Boyum, Mindy Mickelson, Matthew Moore and Cheristi Cognetta-Rieke

    Citation: BMC Medical Informatics and Decision Making 2020 20:167

    Content type: Research article

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  29. Building and validating electronic algorithms to identify patients with specific disease profiles using health data is becoming increasingly important to disease surveillance and population health management. The...

    Authors: Rachael Morkem, Kenneth Handelman, John A. Queenan, Richard Birtwhistle and David Barber

    Citation: BMC Medical Informatics and Decision Making 2020 20:166

    Content type: Research article

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  30. Delay in identifying deterioration in hospitalised patients is associated with delayed admission to an intensive care unit (ICU) and poor outcomes. For the HAVEN project (HICF ref.: HICF-R9–524), we have devel...

    Authors: Simarjot S. Dahella, James S. Briggs, Paul Coombes, Nazli Farajidavar, Paul Meredith, Timothy Bonnici, Julie L. Darbyshire and Peter J. Watkinson

    Citation: BMC Medical Informatics and Decision Making 2020 20:161

    Content type: Research article

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  31. The increasing complexity of current drug therapies jeopardizes patient adherence. While individual needs to simplify a medication regimen vary from patient to patient, a straightforward approach to integrate ...

    Authors: Viktoria S. Wurmbach, Steffen J. Schmidt, Anette Lampert, Eduard Frick, Michael Metzner, Simone Bernard, Petra A. Thürmann, Stefan Wilm, Achim Mortsiefer, Attila Altiner, Lisa Sparenberg, Joachim Szecsenyi, Frank Peters-Klimm, Petra Kaufmann-Kolle, Walter E. Haefeli and Hanna M. Seidling

    Citation: BMC Medical Informatics and Decision Making 2020 20:154

    Content type: Research article

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  32. Patients with diabetes are at an increased risk of readmission and mortality when discharged from hospital. Existing research identifies statistically significant risk factors that are thought to underpin thes...

    Authors: Tim Robbins, Sarah N. Lim Choi Keung, Sailesh Sankar, Harpal Randeva and Theodoros N. Arvanitis

    Citation: BMC Medical Informatics and Decision Making 2020 20:150

    Content type: Research article

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  33. Combining MRI techniques with machine learning methodology is rapidly gaining attention as a promising method for staging of brain gliomas. This study assesses the diagnostic value of such a framework applied ...

    Authors: Carole H. Sudre, Jasmina Panovska-Griffiths, Eser Sanverdi, Sebastian Brandner, Vasileios K. Katsaros, George Stranjalis, Francesca B. Pizzini, Claudio Ghimenton, Katarina Surlan-Popovic, Jernej Avsenik, Maria Vittoria Spampinato, Mario Nigro, Arindam R. Chatterjee, Arnaud Attye, Sylvie Grand, Alexandre Krainik…

    Citation: BMC Medical Informatics and Decision Making 2020 20:149

    Content type: Research article

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  34. Prostate cancer (PCa) represents a significant healthcare problem. The critical clinical question is the need for a biopsy. Accurate risk stratification of patients before a biopsy can allow for individualised...

    Authors: Amirhossein Jalali, Robert W. Foley, Robert M. Maweni, Keefe Murphy, Dara J. Lundon, Thomas Lynch, Richard Power, Frank O’Brien, Kieran J. O’Malley, David J. Galvin, Garrett C. Durkan, T. Brendan Murphy and R. William Watson

    Citation: BMC Medical Informatics and Decision Making 2020 20:148

    Content type: Research article

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  35. The design and internal layout of modern operating rooms (OR) are influencing the surgical team’s collaboration and communication, ergonomics, as well as intraoperative hygiene substantially. Yet, there is no ...

    Authors: Juliane Neumann, Christine Angrick, Celina Höhn, Dirk Zajonz, Mohamed Ghanem, Andreas Roth and Thomas Neumuth

    Citation: BMC Medical Informatics and Decision Making 2020 20:145

    Content type: Research article

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  36. Clinical intuition and nonanalytic reasoning play a major role in clinical hypothesis generation; however, clinicians’ intuition about whether a critically ill child is bacteremic has not been explored. We end...

    Authors: Katherine E. M. Hoops, James C. Fackler, Anne King, Elizabeth Colantuoni, Aaron M. Milstone and Charlotte Woods-Hill

    Citation: BMC Medical Informatics and Decision Making 2020 20:144

    Content type: Research article

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  37. The main objective of phase I cancer clinical trials is to identify the maximum tolerated dose, usually defined as the highest dose associated with an acceptable level of severe toxicity during the first cycle...

    Authors: D. Dinart, J. Fraisse, D. Tosi, A. Mauguen, C. Touraine, S. Gourgou, M. C. Le Deley, C. Bellera and C. Mollevi

    Citation: BMC Medical Informatics and Decision Making 2020 20:134

    Content type: Software

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  38. Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical de...

    Authors: Melissa L. Harry, Daniel M. Saman, Anjali R. Truitt, Clayton I. Allen, Kayla M. Walton, Patrick J. O’Connor, Heidi L. Ekstrom, JoAnn M. Sperl-Hillen, Joseph A. Bianco and Thomas E. Elliott

    Citation: BMC Medical Informatics and Decision Making 2020 20:117

    Content type: Research article

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  39. Learning from routine healthcare data is important for the improvement of the quality of care. Providing feedback on clinicians’ performance in comparison to their peers has been shown to be more efficient for...

    Authors: Kassaye Yitbarek Yigzaw, Andrius Budrionis, Luis Marco-Ruiz, Torje Dahle Henriksen, Peder A. Halvorsen and Johan Gustav Bellika

    Citation: BMC Medical Informatics and Decision Making 2020 20:116

    Content type: Technical advance

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  40. Incorporating patient preference (PP) information into decision-making has become increasingly important to many stakeholders. However, there is little guidance on which patient preference assessment methods, ...

    Authors: Chiara Whichello, Bennett Levitan, Juhaeri Juhaeri, Vaishali Patadia, Rachael DiSantostefano, Cathy Anne Pinto and Esther W. de Bekker-Grob

    Citation: BMC Medical Informatics and Decision Making 2020 20:114

    Content type: Research article

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  41. Early warning scores (EWS) have been developed as clinical prognostication tools to identify acutely deteriorating patients. In the past few years, there has been a proliferation of studies that describe the d...

    Authors: Andrew Hao Sen Fang, Wan Tin Lim and Tharmmambal Balakrishnan

    Citation: BMC Medical Informatics and Decision Making 2020 20:111

    Content type: Research article

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  42. There are increasing examples of linking data on healthcare resource use and patient outcomes from different sectors of health and social care systems. Linked data are generally anonymised, meaning in most jur...

    Authors: Mary P. Tully, Cecilia Bernsten, Mhairi Aitken and Caroline Vass

    Citation: BMC Medical Informatics and Decision Making 2020 20:109

    Content type: Research article

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  43. IT systems in the healthcare field can have a marked sociotechnical impact: they modify communication habits, alter clinical processes and may have serious ethical implications. The introduction of such system...

    Authors: Heiko Waldmüller, Cord Spreckelsen, Hannah Rudat, Norbert Krumm, Roman Rolke and Stephan Michael Jonas

    Citation: BMC Medical Informatics and Decision Making 2020 20:101

    Content type: Research article

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  44. Treatment decision-making by family members on behalf of patients with major stroke can be challenging because of the shock of the diagnosis and lack of knowledge of the patient’s treatment preferences. We aim...

    Authors: A. Visvanathan, G. E. Mead, M. Dennis, W. N. Whiteley, F. N. Doubal and J. Lawton

    Citation: BMC Medical Informatics and Decision Making 2020 20:98

    Content type: Research article

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  45. Constrained budgets within healthcare systems and the need to efficiently allocate resources often necessitate the valuation of healthcare interventions and services. However, when a technological product is d...

    Authors: Emmanouil Mentzakis, Daria Tkacz and Carol Rivas

    Citation: BMC Medical Informatics and Decision Making 2020 20:95

    Content type: Research article

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  46. Medication errors have been identified as the most common preventable cause of adverse events. The lack of granularity in medication error terminology has led pharmacovigilance experts to rely on information i...

    Authors: Nadine Kadi Eskildsen, Robert Eriksson, Sten B. Christensen, Tamilla Stine Aghassipour, Mikael Juul Bygsø, Søren Brunak and Suzanne Lisbet Hansen

    Citation: BMC Medical Informatics and Decision Making 2020 20:94

    Content type: Research article

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  47. Implementation theories, models and frameworks offer guidance when implementing and sustaining healthcare evidence-based interventions. However, selection can be challenging given the myriad of potential optio...

    Authors: Lisa Strifler, Jan M. Barnsley, Michael Hillmer and Sharon E. Straus

    Citation: BMC Medical Informatics and Decision Making 2020 20:91

    Content type: Research article

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  48. Coronary heart disease (CHD) is a leading cause of morbidity and mortality for breast cancer survivors, yet the joint effect of adverse cardiovascular health (CVH) and cardiotoxic cancer treatments on post-tre...

    Authors: Aixia Guo, Kathleen W. Zhang, Kristi Reynolds and Randi E. Foraker

    Citation: BMC Medical Informatics and Decision Making 2020 20:88

    Content type: Research article

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  49. Basal cell carcinoma (BCC) is a slow-growing, rarely lethal skin cancer that affects people 65 years or older. A range of treatment options exist for BCC, but there is little evidence available to guide patien...

    Authors: Alexandra Junn, Neha R Shukla, Lily Morrison, Meghan Halley, Mary-Margaret Chren, Louise C. Walter, Dominick L. Frosch, Dan Matlock, Jeanette S. Torres and Eleni Linos

    Citation: BMC Medical Informatics and Decision Making 2020 20:81

    Content type: Research article

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  50. Screening with prostate-specific antigen (PSA) test for prostate cancer is considered a preference sensitive decision; meaning it does not only depend on what is best from a medical point of view, but also fro...

    Authors: S. Baptista, B. Heleno, A. Teixeira, K. L. Taylor and C. Martins

    Citation: BMC Medical Informatics and Decision Making 2020 20:78

    Content type: Study protocol

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