Table 1
Methodological quality appraised using the Medical Education Research Study Quality Instrument (MERSQI): operational considerations for cost evaluations and prevalence
|
Domain: Item |
Operational adjustments |
Level |
Prevalence N (%) (N = 62) |
|---|---|---|---|
|
Study design |
Added option for economic modeling studies (score 1.5) |
1‑group post-only (1) |
6 (10%) |
|
1‑group pre-post, or modeling (1.5) |
20 (32%) | ||
|
2‑group non-randomized (2) |
16 (26%) | ||
|
2‑group randomized (3) |
20 (32%) | ||
|
Sampling: No. of institutions studied |
No change |
1 (0.5) |
54 (87%) |
|
2 (1) |
1 (2%) | ||
|
>2 (1.5) |
7 (11%) | ||
|
Sampling: Response rate |
For cost data: Data derived from large record sets unlikely to reflect bias (e.g., institutional electronic health record or regional claims database) count as high (score 1.5) |
<50% or not specified (0.5) |
24 (39%) |
|
50–74% (1) |
7 (11%) | ||
|
≥75% or large record |
31 (50%) | ||
|
Type of data (data source) |
For cost data: Details of resource quantitation (both data source and quantity [number of units, not just total cost]) count as high (score 3). Cost alone counts as low (score 1) |
Self-reported data, or cost without resource quantitation (1) |
8 (13%) |
|
Objective measurement, or cost with data source and quantity (3) |
54 (87%) | ||
|
Validation of evaluation instrument: Content |
For cost data: “The degree to which the cost estimation encompasses all aspects of the true cost, encompassing processes to both identify and measure cost” [15]. Evidence could include use of a formal framework (e.g., the Ingredients Method) or the involvement of experts in planning, empiric identification and selection of relevant resources (e.g., time-motion studies or process mapping), and substantiation that a robust data source was used to select, quantitate, or price resources (e.g., detailed description of a computer database) |
Reported (1) |
8 (13%) |
|
Validation of evaluation instrument: Internal structure |
For cost data: “The degree to which the cost estimate is reproducible if the same method is followed” [15]. Evidence could include replicability of the valuation or analysis (e.g., robust examination of the uncertainty of input parameter estimates [sensitivity analysis], independent valuation of costs by two investigators [inter-rater reliability], or comparing cost estimates derived at two different time points [temporal stability]) |
Reported (1) |
9 (15%) |
|
Validation of evaluation instrument: Relations with other variables |
For cost data: “The degree to which the cost estimate relates to cost estimates formed using alternative approaches” [15]. Evidence could include examining predicted associations among results obtained using alternative approaches to economic modeling (e.g., sensitivity analysis comparing different base assumptions, valuation methods, statistical models, or economic theories) |
Reported (1) |
1 (2%) |
|
Data analysis: Appropriateness |
For cost data: The following count as “appropriate” (score 1): cost effectiveness ratio, net benefit, or other similar analysis of cost data |
Inappropriate for study design (0) |
37 (60%) |
|
Appropriate (1) |
25 (40%) | ||
|
Data analysis: Complexity |
For cost data: The following count as “beyond descriptive” (score 2): cost effectiveness ratio, net benefit, visual display of cost-effectiveness |
Descriptive analysis only (1) |
37 (60%) |
|
Beyond descriptive analysis (2) |
25 (40%) | ||
|
Outcomes |
For cost outcomes: As per Foo, we distinguished education costs in a “test setting” or a “real setting,” namely: “Test settings are those in which the context does not match how the intervention would be utilized in actual practice (e.g., a hypothetical program that was not actually implemented). Real settings are where the intervention is evaluated in a context similar to its anticipated utilization in practice (e.g., an evaluation of a program that is taught to real students)” [15]. However, we assigned points differently than Foo: score 1.5 for cost of education in test setting, score 2 for cost of education in real setting, score 3 for health care costs. Outcomes estimated from previously published research (including health care costs and non-cost outcomes) also score 1.5 |
Knowledge, skills, or education costs in a “test” or hypothetical training setting, or estimated from literature (1.5) |
1 (2%) |
|
Behaviors in practice or education costs in a “real” training setting (2) |
25 (40%) | ||
|
Patient effects, including health care costs (3) |
36 (58%) |
For each item in a given study, the design feature (study design, outcome, evaluation instrument, etc.) that supported the highest level of coding was selected. For example, for a study reporting both cost and effectiveness (non-cost) outcomes, the outcome corresponding to the highest-scoring level was selected for coding (and as a result, in some cases the design features in the cost evaluation [i.e., the features coded in this review] are less than those reported in this table)
Fig. 1
Reporting quality as per CHEERS guideline criteria. N = 62 except as indicated. Numbers in [brackets] indicate item number in CHEERS checklist [10]. Details on abstract reporting are provided in Fig. 2. Operational considerations used in coding are provided in Tab. S1 in ESM
Fig. 2
Reporting quality of abstract. N = 56 studies with abstract, except as indicated
