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Models to Optimise Medication Safety in Elderly and Oncology Inpatients

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Models to Optimise Medication Safety in Elderly and Oncology Inpatients Models to optimise medication safety in elderly and oncology inpatients Ana Šarčević München 2018 Models to optimise medication safety in elderly and oncology inpatients Ana Šarčević Dissertation zum Erwerb des Doctor of Philosophy (Ph.D.) Aus dem Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie an der Medizinischen Fakultät der Ludwig–Maximilians–Universität München vorgelegt von Ana Šarčević aus Zrenjanin, Serbien München, den 2. Juli 2018 Erstgutachter: Prof. Dr. rer. nat. Ulrich Mansmann Zweitgutachter: Prof. Dr. rer. nat. Ulrich Jaehde Tag der mündlichen Prüfung: 21. Dezember 2018 Acknowledgements This thesis represents a significant milestone in five-year cooperation between three working groups in Germany. During that time, I have encountered dozens of remarka- ble individuals who I wish to acknowledge. First and foremost, I would like to express my special appreciation and thanks to my supervisors Prof. Ulrich Mansmann and Prof. Ulrich Jaehde. They have been support- ive since the days I began my academic career. Prof. Mansmann, you had faith in me when I stubbornly wanted to pursue my academic career in patient-oriented research on the ward despite all odds. You gave me the freedom when I needed to move on and supported me remarkably in the field of statistics when I was bogged down. Prof. Jaehde, you have been a tremendous mentor and a role model for me. I would like to thank you for encouraging my research and for allowing me to grow as a research scientist. Your advice, on both research, and on my career has been invaluable. My TAC committee guided me through all these years. Thank you Dr. Albrecht Eisert, on your major contribution on site. Without you, the projects would not have been conducted at the University Hospital RWTH in Aachen. And thank you Prof. Wolfgang Frieß for cooperation and contribution in endurance of my supervisor team. Medication safety research group in Aachen, I am grateful to all of you. Thank you Rebekka for welcoming me into the group. With a great confidence, you forwarded me the project you deeply cared about. Your research enthusiasm and commitment was contagious. Katha, thank you for your contribution in developing my second project and everything you taught me. Sabine, thank you for introducing me to the oncology pharmacy and proofreading the manuscript. I am immensely thankful for all the extra hours you invested in supervising my project on the ward, intensively discussing pa- tient cases with me and with the medical team on the ward. There is no easy way of working 80-hour a week, but your energy, encouragement and versatility of knowledge and abilities made it lighter and more valuable. Caro, Resi, Julia thank you for being there for me in the most diverse situations. Ms Heussen, thank you for being my statis- tical support on site. Statistical discussions with you were joyful. A big thank you goes to oncology ward at the University Hospital RWTH in Aachen. Dr. Stefan Wilop, the ward medical team, and all participating patients, I sincerely I Acknowledgement appreciate your warm welcome on the ward. Without your openness and our fruitful collaboration, the oncology project would not have been possible. Pharmaceutical care research group in Bonn, I am sincerely thankful to all of you too. As an external PhD student, I came to you mostly when I needed help. Thank you for your insightful comments and encouragement, but also for the hard questions that inspired me to broaden my knowledge and widen my research. Munich Medical Research School coordinators and ERAWEB (Erasmus Mundus Western Balkans) coordinators, thank you for your support at various phases of the programme. Thank you ERAWEB programme for making it possible to do a PhD in Germany. During the three years of fellowship I was able to focus entirely on my re- search. Profound gratitude goes to my medical team at the clinical centre in Belgrade and the university hospital in Essen, and astronomical number of friends and acquaintances who supported me during the special game in 2014. They had no influence on PhD work per se, but without them I would have not been able to quickly return to the PhD grind after the most difficult life stage. Prof. Sebastian Bauer, although not being my official supervisor, I am forever thankful to you. Besides being the best physician in the world, you supported me morally and emotionally through the challenges I have faced during this thesis. Ljiksi, thank you for diligently proofreading the manuscript. You are my life friend who deeply understands both my personal and academic struggles. Your uncondition- al love and support provide sunshine in my life. Siki, my soul mate and sister from another mother, thank for the linguistic review of the manuscript. Bel&Uls, thank you for providing me home (in Munich) away from home. That is priceless. You guys are greatly inspiring. Thank you to my flatmates, especially Safi, Zeynep and Jovana for staying with me through all the ups and downs during the PhD life. Leo joined me in the last stage of my PhD, but I could not wish for a better life companion. Thank you my lav. Without my friends I would not be here where I am now. I have been so lucky to have such an army of precious friends around me. A full list of your names does not fit in here. You all know who you are. Finally, above all, it is my family I want to thank to: my sister Jelena, my mom Tatjana and my dad Zoran. This thesis is for you guys. II Content 1 Introduction _________________________________________ 1 2 Model I ____________________________________________ 7 Multi-professional medication safety model reducing drug-related readmission in care-dependent elderly - study protocol ____________ 7 2.1 Introduction ______________________________________ 7 2.1.1 Objectives __________________________________________________________________________________ 13 2.2 Methods _________________________________________ 14 2.2.1 Patient recruitment _______________________________________________________________________ 14 2.2.2 Participant timeline _______________________________________________________________________ 17 2.2.3 Geriatric assessment ______________________________________________________________________ 18 2.2.4 Control group ______________________________________________________________________________ 18 2.2.5 Intervention group ________________________________________________________________________ 19 2.2.6 Follow-up __________________________________________________________________________________ 21 2.2.7 Patient interview __________________________________________________________________________ 22 2.2.8 Focus group ________________________________________________________________________________ 24 2.3 Data management _________________________________ 25 2.3.1 Study instruments _________________________________________________________________________ 26 2.3.2 Outcome variables ________________________________________________________________________ 28 2.3.3 Outcome assessment panel _______________________________________________________________ 28 2.3.4 Statistical analysis _________________________________________________________________________ 29 2.4 Ethics and dissemination ____________________________ 30 2.5 Discussion _______________________________________ 31 3 Model II ___________________________________________ 34 Development of a prediction model to estimate the risk of drug-related problems on the oncology ward – pilot study ___________________ 34 3.1 Introduction _____________________________________ 34 3.1.1 Study background _________________________________________________________________________ 44 3.1.2 Objectives __________________________________________________________________________________ 45 3.2 Methods ________________________________________ 46 3.2.1 Study design _______________________________________________________________________________ 46 3.2.2 Setting ______________________________________________________________________________________ 47 3.2.3 Data management _________________________________________________________________________ 47 III Content 3.2.4 Participants ________________________________________________________________________________ 49 3.2.5 Intervention: pharmaceutical care _______________________________________________________ 51 3.2.6 Study measures ____________________________________________________________________________ 53 3.2.7 Drug-related problem prediction model _________________________________________________ 65 3.2.8 Bias __________________________________________________________________________________________ 66 3.3 Results __________________________________________ 68 3.3.1 Participants ________________________________________________________________________________ 68 3.3.2 Adverse drug reaction risk score _________________________________________________________ 76 3.3.3 Drug-drug interactions ____________________________________________________________________ 77 3.3.4 Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAETM) ____________________________________________________________________________ 78 3.3.5 Drug-related problems ____________________________________________________________________ 84 3.3.6 Drug-related problem prediction model _________________________________________________ 88 3.4 Discussion ______________________________________ 101 3.4.1 Participants ______________________________________________________________________________
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