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Shojania KG, Ranji SR, Shaw LK, et al. Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies (Vol. 2: Diabetes Care). Rockville (MD): Agency for Healthcare Research and Quality (US); 2004 Sep. (Technical Reviews, No. 9.2.)

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Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies (Vol. 2: Diabetes Care).

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Appendix FCalculation of effective sample sizes for trials with clustering

A substantial number of studies exhibited “clustering,” in that the units of analysis were patient level outcomes but the unit of allocation had been clusters of patients (e.g., randomization involved providers or clinics). The significance of clustering is that patients within a cluster are not independent - i.e., patients at one clinic have greater resemblance to each other than to patients at other sites or cared for by other providers in the trial. Unit of analysis errors do not affect point estimates for effect sizes, but they may spuriously narrow the associated confidence interval, potentially leading to a false-positive result in a trial.18 To avoid the same inflation of precision in our analysis, we calculated an effective sample size* for each study. Importantly, from the point of view of our analysis, the degree to which investigators acknowledged or accounted for cluster effects did not affect our analysis, except in so far as investigators who did consider cluster effects in the design or analysis of the trial were more likely to report data such as the number of providers randomized, rather than just the total numbers of patients in each group, as well as provide more technical details, such as values for the intra-cluster coefficient (ICC). 911

The table below compares the effective and originally reported sample sizes for effective sample sizes. Only values at baseline in the control and intervention groups are shown, but the same calculations were carried out for reported sample sizes in the post-intervention period for all study groups. Because so few studies reported ICC values,911 we imputed values based on published estimates. Specifically, we used ICC=0.03 for the HbA1c outcome and ICC=0.10 for measures of provider adherence, based no the midpoints of published values for process and outcome measures in primary care settings. 3 As a sensitivity analysis, we re-ran the effective sample size calculations and regression analyses with the upper bounds of these ranges (ICC=0.10 and ICC=0.33, for outcome and process measures, respectively), with no substantial impacts no the results.

Table F1Reported vs. effective sample sizes for clustered studies evaluating reduction in HbA1c

No. of clustersReported N(patients)Effective N(patients)Percent reduction (%)
Benjamin 199912 21064657
Boucher 199713 618310543
Olivarius 200114 4848748572
de Sonnaville 199715 2856337633
Frijling 20029 1231430112821
Groeneveld 200116 1522416526
Hetlevik 200017 3073345238
Hirsch 200218 21094658
Kiefe 200119 84135297428
Kinmonth 199810 4224019718
Kogan 200320 4428324912
Litzelman 199321 435311169
Mazzuca 198622 1312710418
McDermott 200123 2167838044
Meigs 200311 6659837737
O'Connor 199624 22416075
Ovhed 200025 23946683
Reed 200126 918912335
Renders 200127 2738929125
Wagner 200128 3460942530
Walker 200129 23456581
Deeb 198830 663617373
Feder 199531 2421210
Legorreta 199632 22055872
Hartmann 199533 1737624635
Walker 200129 23456581
Legorreta 199632 21855570
Branger 199934 3227522717
Mazzuca 198622 1412010116
*

Effective N equals sample size adjusted for presence of clustering. It was calculated as NEffective = (k*m) / (1 + (m-1)*r), where 'k 'is the number of clusters, ‘m’ is the number of patients per cluster, and ‘r’ is the intracluster coefficient (ICC). When r = 0, then NEffective = k*m (i.e., the reported sample size) When r = 1, then NEffective = k(i.e., the number of clusters) 18

Appendix F References

1.
Kerry SM, Bland JM. Sample size in cluster randomisation. BMJ. 1998;316:549. [PMC free article: PMC2665662] [PubMed: 9501723]
2.
Kerry SM, Bland JM. Statistics notes: The intracluster correlation coefficient in cluster randomisation. BMJ. 1998;316:1455–1460. [PMC free article: PMC1113123] [PubMed: 9572764]
3.
Campbell MK, Mollison J, Grimshaw JM. Cluster trials in implementation research: estimation of intracluster correlation coefficients and sample size. Stat Med. 2001;20:391–399. [PubMed: 11180309]
4.
Torgerson DJ. Contamination in trials: is cluster randomisation the answer? BMJ. 2001;322:355–357. [PMC free article: PMC1119583] [PubMed: 11159665]
5.
Donner A, Piaggio G, Villar J. Meta-analyses of cluster randomization trials. Power considerations. Eval Health Prof. 2003;26:340–351. [PubMed: 12971203]
6.
Donner A, Klar N. Issues in the meta-analysis of cluster randomized trials. Stat Med. 2002;21:2971–2980. [PubMed: 12325113]
7.
Donner A, Piaggio G, Villar J. Statistical methods for the meta-analysis of cluster randomization trials. Stat Methods Med Res. 2001;10:325–338. [PubMed: 11697225]
8.
Localio AR, Berlin JA, Ten Have TR, Kimmel SE. Adjustments for center in multicenter studies: an overview. Ann Intern Med. 2001;135:112–123. [PubMed: 11453711]
9.
Frijling BD, Lobo CM, Hulscher ME. et al. Multifaceted support to improve clinical decision making in diabetes care: a randomized controlled trial in general practice. Diabet Med. 2002;19:836–842. [PubMed: 12358871]
10.
Kinmonth AL, Woodcock A, Griffin S, Spiegal N, Campbell MJ. Randomised controlled trial of patient centred care of diabetes in general practice: impact on current wellbeing and future disease risk. The Diabetes Care From Diagnosis Research Team. BMJ. 1998;317:1202–1208. [PMC free article: PMC28704] [PubMed: 9794859]
11.
Meigs JB, Cagliero E, Dubey A. et al. A controlled trial of web-based diabetes disease management: the MGH diabetes primary care improvement project. Diabetes Care. 2003;26:750–757. [PubMed: 12610033]
12.
Benjamin EM, Schneider MS, Hinchey KT. Implementing practice guidelines for diabetes care using problem-based learning. A prospective controlled trial using firm systems. Diabetes Care. 1999;22:1672–1678. [PubMed: 10526733]
13.
Boucher BJ, Claff HR, Edmonson M. et al. A pilot Diabetic Support Service based on family practice attenders: comparison with diabetic clinics in east London. Diabet Med. 1987;4:480–484. [PubMed: 2959442]
14.
Olivarius NF, Beck-Nielsen H, Andreasen AH, Horder M, Pedersen PA. Randomised controlled trial of structured personal care of type 2 diabetes mellitus. BMJ. 2001;323:970–975. [PMC free article: PMC59690] [PubMed: 11679387]
15.
de Sonnaville JJ, Bouma M, Colly LP, Deville W, Wijkel D, Heine RJ. Sustained good glycaemic control in NIDDM patients by implementation of structured care in general practice: 2-year follow-up study. Diabetologia. 1997;40:1334–1340. [PubMed: 9389427]
16.
Groeneveld Y, Petri H, Hermans J, Springer M, IN. An assessment of structured care assistance in the management of patients with type 2 diabetes in general practice. Scandinavian Journal of Primary Health Care. 2001;Vol 19:30. [PubMed: 11303543]
17.
Hetlevik I, Holmen J, Kruger O, Kristensen P, Iversen H, Furuseth K. Implementing clinical guidelines in the treatment of diabetes mellitus in general practice. Evaluation of effort, process, and patient outcome related to implementation of a computer-based decision support system. Int J Technol Assess Health Care. 2000;16:210–227. [PubMed: 10815366]
18.
Hirsch IB, Goldberg HI, Ellsworth A. et al. A multifaceted intervention in support of diabetes treatment guidelines: a controlled trial. Diabetes Res Clin Pract. 2002;58:27–36. [PubMed: 12161054]
19.
Kiefe CI, Allison JJ, Williams OD, Person SD, Weaver MT, Weissman NW. Improving quality improvement using achievable benchmarks for physician feedback: a randomized controlled trial. JAMA. 2001;285:2871–2879. [PubMed: 11401608]
20.
Kogan JR, Reynolds EE, Shea JA. Effectiveness of report cards based on chart audits of residents' adherence to practice guidelines on practice performance: a randomized controlled trial. Teach Learn Med. 2003;15:25–30. [PubMed: 12632705]
21.
Litzelman DK, Slemenda CW, Langefeld CD. et al. Reduction of lower extremity clinical abnormalities in patients with non-insulin-dependent diabetes mellitus. A randomized, controlled trial. Ann Intern Med. 1993;119:36–41. [PubMed: 8498761]
22.
Mazzuca SA, Moorman NH, Wheeler ML. et al. The diabetes education study: a controlled trial of the effects of diabetes patient education. Diabetes Care. 1986;9:1–10. [PubMed: 3948638]
23.
McDermott RA, Schmidt BA, Sinha A, Mills P. Improving diabetes care in the primary healthcare setting: a randomised cluster trial in remote Indigenous communities. Med J Aust. 2001;174:497–502. [PubMed: 11419768]
24.
O'Connor PJ, Rush WA, Peterson J. et al. Continuous quality improvement can improve glycemic control for HMO patients with diabetes. Arch Fam Med. 1996;5:502–506. [PubMed: 8930220]
25.
Ovhed I, Johansson E, Odeberg H, Rastam L. A comparison of two different team models for treatment of diabetes mellitus in primary care. Scand J Caring Sci. 2000;14:253–258. [PubMed: 12035216]
26.
Reed RL, Revel AO, Carter A, Saadi HF, Dunn EV. A clinical trial of chronic care diabetic clinics in general practice in the United Arab Emirates: a preliminary analysis. Arch Physiol Biochem. 2001;109:272–280. [PubMed: 11880932]
27.
Renders CM, Valk GD, Franse LV. et al. Long-term effectiveness of a quality improvement program for patients with type 2 diabetes in general practice. Diabetes Care. 2001;24:1365–1370. [PubMed: 11473071]
28.
Wagner EH, Grothaus LC, Sandhu N. et al. Chronic care clinics for diabetes in primary care: a system-wide randomized trial. Diabetes Care. 2001;24:695–700. [PubMed: 11315833]
29.
Walker EA, Engel SS, Zybert PA, IN. Dissemination of diabetes care guidelines: lessons learned from community health centers. Diabetes Educator. 2001;27:101–110. [PubMed: 11912611]
30.
Deeb LC, Pettijohn FP, Shirah JK, Freeman G. Interventions among primary-care practitioners to improve care for preventable complications of diabetes. Diabetes Care. 1988;11:275–280. [PubMed: 3416683]
31.
Feder G, Griffiths C, Highton C, Eldridge S, Spence M, Southgate L. Do clinical guidelines introduced with practice based education improve care of asthmatic and diabetic patients? A randomised controlled trial in general practices in east London. BMJ. 1995;311:1473–1478. [PMC free article: PMC2543702] [PubMed: 8520339]
32.
Legorreta AP, Peters AL, Ossorio RC, Lopez RJ, Jatulis D, Davidson MB. Effect of a comprehensive nurse-managed diabetes program: an HMO prospective study. Am J Manag Care. 1996;2:1024–1030.
33.
Hartmann et al. Effects of peer-review groups on physicians' practice. Eur J Gen Pract. 1995;1:107.
34.
Branger PJ, van't Hooft A, van der Wouden JC, Moorman PW, van Bemmel JH. Shared care for diabetes: supporting communication between primary and secondary care. Int J Med Inf. 1999;53:133–142. [PubMed: 10193883]

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