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Additional file 2. Survey results.

Additional file 1. Interview & Survey.

Additional file 3. Details of the cost-minimisation analysis.

To enable patients with rheumatoid arthritis (RA) and their healthcare professionals to choose the optimal treatment, it is crucial to accurately assess the current state of inflammatory activity. The objectives of this study were to (1) investigate the perspective of RA patients on their insight into the current status of their disease, and to (2) investigate the patients’ perspective on the possible added value of a monitoring device based on optical spectral transmission—called the HandScan—that measures the location and severity of joint inflammation. A survey was distributed online among patients with RA in the Netherlands. Four-hundred and eight patients with RA completed the survey. Of these, 298 (73%) felt they have sufficient insight into their current disease status. Most respondents perceived either a large (n = 242; 59%) or small (n = 148; 36%) added value of the HandScan in their monitoring process, mostly because the device provides additional knowledge on the presence of inflammation. This perceived added value was higher for respondents experienced with the device (n = 46; p = .04). Respondents preferred monitoring with the device on every (n = 192; 47%) or most (n = 171; 42%) visits to the outpatient clinic, or even more often than on every visit (n = 17; 4%). Monitoring RA using an optical spectral transmission device is seen by patients as a possibly valuable addition to the monitoring process of inflammatory activity during visits to an outpatient clinic. Their main reason was that the device can increase insight into their current disease status. More insight may support patients in discussing treatment options with their rheumatologist.

Supplemental material, sj-pdf-1-mdm-10.1177_0272989X211016307 for Choosing a Metamodel of a Simulation Model for Uncertainty Quantification by Tiago M. de Carvalho, Joost van Rosmalen, Harold B. Wolff, Hendrik Koffijberg and Veerle M. H. Coupé in Medical Decision Making

Additional file 1: Figure S1. Inverted Kaplan-Meier showing time (years) from first visit to the Pediatric Rheumatology Clinic to A) start the first c-DMARD and B) start the first b-DMARD.

Supplemental material, sj-pdf-1-mdm-10.1177_0272989X211016307 for Choosing a Metamodel of a Simulation Model for Uncertainty Quantification by Tiago M. de Carvalho, Joost van Rosmalen, Harold B. Wolff, Hendrik Koffijberg and Veerle M. H. Coupé in Medical Decision Making

Supplemental material, sj-docx-1-mdm-10.1177_0272989X211016307 for Choosing a Metamodel of a Simulation Model for Uncertainty Quantification by Tiago M. de Carvalho, Joost van Rosmalen, Harold B. Wolff, Hendrik Koffijberg and Veerle M. H. Coupé in Medical Decision Making

Additional file 1. Appendix.

Additional file 1. This file contains the reference values of the 15 laboratory tests, extensive descriptions of the multinomial and the binomial logistic regression model, the assumptions that have been tested, as well as the detailed results of the multinomial logistic regression model, of the best subset selection and of the variance inflation factor.

Supplemental material, appendix.rjf_online_supp for Introduction to Metamodeling for Reducing Computational Burden of Advanced Analyses with Health Economic Models: A Structured Overview of Metamodeling Methods in a 6-Step Application Process by Koen Degeling, Maarten J. IJzerman, Mariel S. Lavieri, Mark Strong and Hendrik Koffijberg in Medical Decision Making

Literature search. This file contains the extensive description of the literature search, which was used to identify criteria relevant for the analytical hierarchy process. (PDF 103 kb)

Results of interviews and analytical hierarchy process. This supplementary file contains an overview of the detailed results of the analysis of the analytical hierarchy process (AHP), including the weighting of the subcriteria, the group inconsistency and missing judgements during the analytical hierarchy process session, as well as the preferences regarding the subcriteria for the two alternatives (i.e. point-of-care (POC) C-reactive protein (CRP) vs. CRP in a central laboratory, as well as POC glycated haemoglobin (HbA1c) vs. HbA1c in a central laboratory). (DOCX 73 kb)

Graphical representation of the validation studies executed by semi-automated and manual validation. The file consists of four supplementary figures. Figure S1. represents the calibration and discrimination of CancerMathâ s prediction tool for 5-year overall survival, executed by both validation methods. Figure S2. shows the calibration and discrimination of the INFLUENCE prediction tool for the 5-year risk on a locoregional recurrence, executed by both validation methods. Figure S3. shows the calibration and discrimination of the PPAM prediction tool for the risk on axillary lymph node metastasis for both validation methods. Figure S4.s shows the calibration and discrimination of PREDICTâ s prediction tool for 5-year overall survival, for both types of validation. (PDF 744 kb)

Supplemental material, Supplementary_Materials_1_20180914.rjf_online_supp for Comparing Strategies for Modeling Competing Risks in Discrete-Event Simulations: A Simulation Study and Illustration in Colorectal Cancer by Koen Degeling, Hendrik Koffijberg, Mira D. Franken, Miriam Koopman and Maarten J. IJzerman in Medical Decision Making

Results of sensitivity analysis. (DOCX 571 kb)

Overview of model input parameters and assumptions used. (DOCX 41 kb)

Supplemental material, DS_10.1177_0272989X18797948 for Value of Information Choices That Influence Estimates: A Systematic Review of Prevailing Considerations by Hendrik Koffijberg, Claire Rothery, Kalipso Chalkidou and Janneke Grutters in Medical Decision Making

Supplemental material, Supplementary_Materials_2.rjf_online_supp for Comparing Strategies for Modeling Competing Risks in Discrete-Event Simulations: A Simulation Study and Illustration in Colorectal Cancer by Koen Degeling, Hendrik Koffijberg, Mira D. Franken, Miriam Koopman and Maarten J. IJzerman in Medical Decision Making

Includes: 1.1) Detailed discussion of the Bootstrap approach, 1.2) Detailed discussion of the MVNorm approach, 1.3) Description of the simulation study model, 1.4) Description of the case study model, 1.5) Parameter estimates for the simulation study, 1.6) Kullback-Leibler Divergence for the simulation study, 1.7) Incremental cost-effectiveness planes for all case study analyses, 1.8) CEACs for all case study analyses, and 1.9) References. (PDF 722 kb)

Model input parameters. This file contains an overview of all model input parameters, including the value used in the model, the 95% confidence interval, the distribution used, and the data source (DOCX 73 kb)

Occurrence of data quality concepts in existing EHR quality assessment or data linkage frameworks. Table S2.1. Distribution of number of pending diagnoses per transfusion. Figure S2.1. Time patterns in number of donations, products and donors. Figure S2.2. Time patterns in number of transfusions by product type. Figure S2.3. Time patterns in % of transfusion that initially could not be linked to products issued. Figure S2.4. Comparison with previous literature: Distribution of blood products over age and gender, by product type. Table S3. Data validity outcomes reported in the literature for studies that use transfusion databases. Text. Similarities with other operationalizations of data validity. (DOCX 205Â kb)

Occurrence of data quality concepts in existing EHR quality assessment or data linkage frameworks. Table S2.1. Distribution of number of pending diagnoses per transfusion. Figure S2.1. Time patterns in number of donations, products and donors. Figure S2.2. Time patterns in number of transfusions by product type. Figure S2.3. Time patterns in % of transfusion that initially could not be linked to products issued. Figure S2.4. Comparison with previous literature: Distribution of blood products over age and gender, by product type. Table S3. Data validity outcomes reported in the literature for studies that use transfusion databases. Text. Similarities with other operationalizations of data validity. (DOCX 205Â kb)

Results of partial perfect value of information analysis. This file contains an overview of the results of the partial perfect value of information analysis (DOCX 13 kb)

Overview of model assumptions. This file contains an overview of all assumptions that have been used in the health economic analysis (DOCX 18 kb)