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Table 2 Summary of methodological strengths and weaknesses

From: The contribution of benchmarking to quality improvement in healthcare. A systematic literature review

#

First author; Year

Length of follow-up time

Performance evaluation strategy

Patient population

Limitations

Control for biases

1

Cronenwett et al. 2007 [33]

3 years

Time trend

Clearly defined sample of patients undergoing vascular surgery

-Risk adjustment was not performed.

-Only processes of care were evaluated.

None specified in the article.

2

Campion et al. 2011 [34]

4 years

Performance compared between initial and later participants

Sample of end-of-life cancer patients defined by age, sex and tumor type

-Risk adjustment was not performed.

-Only processes of care were evaluated.

None specified in the article.

3

Stern et al. 2011 [35]

5 years

Time trend

Clearly defined sample of cystic fibrosis patients.

Limited number of care centers involved

-The performance of each center was analyzed separately

-Analysis was age-adjusted for certain indicators

4

Hermans et al. 2013 [36]

1 year

RCT

Clearly defined sample of diabetic patients

-Short follow-up time.

-Highly heterogeneous group of care settings involved

-Use of control group.

-Differences between patients as well as care settings were accounted for in the analysis

5

Merle et al. 2009 [37]

6 months

Before/after comparison

Clearly defined sample of patients undergoing surgical care for hip fracture.

-Short follow-up time

-Small number of hospitals involved.

-No use of control group

Analysis performed for each hospital involved.

6

Hall et al. 2009 [38]

3 years

Time trend

Sample of patients undergoing general and vascular surgery

-Self selection of centers, thus the results may not be representative of the population.

-The analysis is based on sampling.

Different modelling approaches were used to control for differences between patients.

7

Tepas III et al. 2014 [39]

15 months

Time trend

Sample of patients undergoing general and vascular surgery.

-Short follow-up period.

-Little information on patient population.

Risk-adjustment was performed.

8

Nuti et al. 2016 [40]

5 years

Time trend

General population

-Highly aggregated data analysis (regional level)

-Use of composite indicator that is based on 14 indicators.

-Population-based study

-Data was standardized for age and sex

9

Govaert et al. 2016 [41]

3 years

Time trend

-Population-based

-Clearly defined sample of patients undergoing surgery for colorectal cancer.

-Only short-term survival was considered.

-Population-based study

-Risk-adjustment was performed to account for differences between patients.

-External data validation performed

10

Piccoliori et al. 2020 [42]

3 years

Before/after comparison

Sample of patients with chronic conditions.

-Small-scale study

-Results were not adjusted for differences between care providers or patients

-Little information on patient population

-Information bias was diminished by removing prevalences from the analysis.

11

Qvist et al. 2004 [43]

1 year

Time trend

Few information on patients characteristics as the focus of the analysis is on the providers

-Short follow-up time period

-No risk adjustment was performed.

None specified in the article.

12

Nuti et al. 2013 [44]

4 years

Time trend

General population

-Highly aggregated data analysis (regional level)

-Population-based study

-Data was standardized for the population’s health needs

13

Van Leersum et al. 2013 [45]

2 years

Time trend

-Population-based

-Clearly defined sample of patients undergoing surgery for colorectal cancer.

- Short follow-up time period

-Population-based study

-The data was adjusted for differences between patients.

-External data validation was performed

14

Margeirsdottir et al. 2010 [46]

5 years

Time trend

-Population-based

-Clearly defined sample of pediatric patients with diabetes.

-No information on non-participants

-Population-based study

-Adjustment for patient age and duration of disease was performed.

-All measurements were standardized.

15

Kodeda et al. 2015 [47]

18 years

Time trend

-Population-based

- Clearly defined sample of patients with colorectal cancer.

-Lack of external data validation

-Absence of control group

-Population-based study

-Longer follow-up time period.

16

Pinnarelli et al. 2011 [48]

3 years

Time trend

-Population-based

- Clearly defined sample of patients undergoing surgical care for hip fracture.

-A number of confounders including patient co-morbidities could not be controlled for in the analysis.

-Population-based study

-Risk-adjustment of performance was performed.

17

Miyata et al. 2012 [49]

4 years

Performance compared between initial and later participants

Clearly defined sample of patients undergoing coronary artery bypass graft (CABG)

-Limited number of participants involved

-Risk-adjustment of performance was performed