Open Access

Measuring quality of diabetes care by linking health care system administrative databases with laboratory data

  • Helena Klomp1,
  • Roland F Dyck2, 3Email author,
  • Nirmal Sidhu1,
  • Paul J Cascagnette1 and
  • Gary F Teare1, 3
BMC Research Notes20103:233

DOI: 10.1186/1756-0500-3-233

Received: 9 March 2010

Accepted: 31 August 2010

Published: 31 August 2010

Abstract

Background

Chronic complications of diabetes can be reduced through optimal glycemic and lipid control as evaluated through measurement of glycosylated hemoglobin (A1C) and low-density lipoprotein cholesterol (LDL-C). We aimed to produce measures of quality of diabetes care in Saskatchewan and to identify sub-groups at particular risk of developing complications.

Findings

Prevalent adult cases of diabetes in 2005/06 were identified from administrative databases and linked with A1C and LDL-C tests measured in centralized laboratories. A1C results were performed in 33,927 of 50,713 (66.9%) diabetes cases identified in Saskatchewan, and LDL-C results were performed in 12,031 of 24,207 (49.7%) cases identified within the province's two largest health regions. The target A1C of <= 7.0% and the target LDL-C of <2.5 mmol/L were achieved in 48.3% and 45.1% of diabetes cases respectively. The proportions were lower among those who were female, First Nations, non-urban, younger and in lower income quintiles. The same groups experienced poorer glycemic control (exception females), and poorer lipid control (exception First Nations people). Among non-Aboriginal people, younger diabetic females were least likely to receive lipid lowering agents.

Conclusions

Linkage of laboratory with administrative data is an effective method of assessing quality of diabetes care on a population basis and to identify sub-groups requiring particular attention. We found that less than 50% of Saskatchewan people with diabetes achieved optimal glycemic and lipid control. Disparities were most evident among First Nations people and young women. The indicators described can be used to provide standardized information that would support quality improvement initiatives.

Background

Canadians are experiencing an epidemic of diabetes [1, 2] that disproportionately affects First Nations people [3, 4]. Although this has serious consequences for individuals, families and the health care system largely because of chronic complications, these can be lessened with improved glycemic and lipid control [5, 6].

The Canadian Diabetes Association publishes clinical practice guidelines that include target values for glycosylated hemoglobin (A1C) and low-density lipoprotein cholesterol (LDL-C) [7]. We evaluated testing frequency and outcome measures of A1C and LDL-C indicators to produce population measures of quality of diabetes care and to identify sub-groups at particular risk for complications. This was achieved on a population basis through linkage of laboratory data with health care system administrative data.

Methods

Study Populations

This 2005/06 population based study of diabetes care in Saskatchewan was approved by the University of Saskatchewan, Saskatoon Health Region and Regina Qu'Appelle Health Region Ethics Review Boards. Study populations were identified from Ministry of Health databases used to administer health care to 99% of the provincial population [8]. Beneficiaries were sub-divided into First Nations people (FN) and other Saskatchewan residents (OSK) by age and sex. FN are indigenous to Canada and included those registered under Section 6 of the Indian Act [9]. Most OSK are of European origin but include non-registered FN (<0.5%) and Métis (about 5%) [10]. The provincial population was approximately one million people and >10% were FN [11].

Diabetic adults aged 20 years and older were identified using a validated algorithm [12] based on National Diabetes Surveillance System (NDSS) case definitions [13]. These required one hospitalization with a discharge diagnosis of diabetes (ICD-9 250.x or ICD-10-CA E10-E14.xxx), or two physician service claims for diabetes within any 730 day period. Gestational diabetes cases were excluded. We were not able to distinguish between types 1 and 2 diabetes but <2% of incident diabetes cases in Canada are <20 years [14], the group with the highest type 1 diabetes incidence [15].

We define the diabetes incident year as the first fiscal year (April1 to March 31) in which an individual meets the diabetes case definition when there has been no prior diabetes diagnosis for at least two years. Thereafter, for each year that an individual is covered by Saskatchewan Health, the individual is a prevalent case. Only prevalent cases of diabetes counted on the first day (April 1) of the 2005/06 fiscal year were included in this study; they comprised the core denominators for our analyses.

Linkage of Diabetes Cases with Laboratory Data

Using encrypted unique identifiers, prevalent cases of diabetes were linked with laboratory data from centralized laboratories in the two largest Health Regions in Saskatchewan (Saskatoon and Regina/Qu'Appelle). This data accounted for nearly 100% of A1C tests and 50% of LDL-C tests performed in the province.

Quality of Diabetes Care Indicators

Because this study predated the 2008 clinical practice guidelines [7], we used an A1C target of ≤7.0% for glycemic control and an LDL-C target of <2.5 mmol/L (now <2.0 mmol/L) for lipid control as published in 2003 [16]. A1C testing was recommended at diabetes diagnosis and then 3-4 times per year; LDL-C testing was recommended at diabetes diagnosis and then every 1-3 years as clinically indicated. Finally, we chose an A1C of >= 9.0% to indicate very poor glycemic control and a LDL-C of >= 2.5 mmol/L as a level when use of lipid lowering drugs should be considered.

Based on the above, the quality of care indicators were: proportion of diabetes cases tested for A1C in 2005/06; of those tested, the proportion with a most recent A1C <= 7.0%, a most recent A1C >= 9.0% and the mean of most recent A1C tests; proportion with >= 2 A1C tests/year; proportion with >= 3 A1C tests/year; proportion of diabetes cases with A1C <= 7.0% by frequency of testing (1, 2, 3, 4+ tests/year); proportion of diabetes cases ever tested for LDL-C in 2005/06; of those, the proportion with a latest LDL-C <2.5 mmol/L, and the mean LDL-C; and proportion of OSK diabetes cases with an LDL-C >= 2.5 mmol/L dispensed a lipid lowering drug (not available for FN). Overall results as well as by sex, ethnicity, location, age group and income quintile were calculated. Detailed descriptions of indicator derivations can be found in the Saskatchewan Health Quality Council 2008 Quality Insight report's Technical Appendix [17].

Analyses

Most comparisons were made between groups within specific demographic sub-populations. Mean A1C and LDL-C values were compared using two tailed t-tests for two groups and one way Anova for multiple groups. For between group comparisons, we chose a reference group and calculated OR's with 95% confidence intervals for the remaining groups. Tests for linear trend (one sided and two sided) were used to compare within group proportions of diabetes cases with A1C <= 7.0% by frequency of testing. Data abstraction and analyses were carried out using SAS software version 9.1.3. A p value of <= 0.05 was considered significant.

Results

Of the 50,713 prevalent diabetes cases in Saskatchewan during 2005/06 (Table 1), 24,188 were female (47.7%) and 6,184 were FN (12.2%). A majority (53.5%) were urban dwellers and 81% were >= 50 years. Almost half were in the lowest two income quintiles (48.3%).
Table 1

Outcomes of A1C testing among Saskatchewan adults with Diabetes by Demographic Characteristics

Characteristic

Number of persons with diabetes†

Tested for A1C

Number of persons tested

A1C <= 7.0%

A1C >= 9.0%

Mean A1C

  

%

OR (95% CI)

 

%

OR (95% CI)

%

OR (95% CI)

 

ALL SASK

50713

66.9

 

33920

48.3

 

12.6

 

7.4

female

24188

66.0

0.95(0.92-0.99)

15971

50.4

1.16(1.11-1.21)

12.3

0.95(0.89-1.01)

7.4 1

male*

26525

67.7

 

17949

46.5

 

12.9

 

7.5

ETHNICITY

         

FN

6184

59.0

0.72(0.68-0.76)

3646

40.6

0.80(0.74-0.86)

25.5

2.05(1.88-2.24)

8.0 1

OSK*

44529

68.0

 

30274

49.3

 

11.1

 

7.4

LOCATION

         

urban*

27147

68.4

 

18563

49.9

 

11.9

 

7.4

non-urban

23508

65.2

0.86(0.83-0.89)

15333

46.5

0.86(0.82-0.90)

13.6

1.23(1.15-1.31)

7.5 1

AGE (years)

         

20-29

686

51.2

0.55(0.47-0.64)

351

40.2

0.56(0.45-0.69)

24.5

4.26(3.31-5.49)

8.1 1

30-39

2652

54.3

0.62(0.57-0.67)

1439

37.0

0.49(0.44-0.55)

27.4

4.96(4.33-5.67)

8.1 1

40-49

6287

62.1

0.85(0.80-0.90)

3902

42.1

0.61(0.57-0.66)

20.6

3.39(3.06-3.76)

7.8 1

50-59

10663

69.8

1.20 (1.4-1.26)

7443

44.4

0.68(0.64-0.72)

16.6

2.58(2.36-2.83)

7.6 1

60-69

11596

72.5

1.37(1.30-1.44)

8408

48.1

0.79(0.74-0.83)

10.6

1.54(1.40-1.70)

7.4 1

≥70*

18829

65.7

 

12377

54.3

 

7.1

 

7.2

INCOME QUINTILE

         

lowest

12991

63.1

0.76(0.72-0.81)

8195

46.0

0.81(0.75-0.86)

15.7

1.53(1.38-1.69)

7.6 1

second

11496

66.3

0.86(0.82-0.92)

7626

47.1

0.83(0.78-0.89)

13.4

1.31(1.18-1.45)

7.5 1

third

8615

68.8

0.96(0.90-1.02)

5923

50.3

0.94(0.88-1.01)

10.9

1.06(0.94-1.19)

7.3 1

fourth

7589

68.8

0.95(0.89-1.02)

5220

48.2

0.87(0.81-0.94)

11.3

1.08(0.96-1.22)

7.4 1

highest*

9436

69.9

 

6593

51.2

 

10.7

 

7.3

All rates are crude rates

*Reference category

†Includes prevalent diabetes cases aged 20 years and older at beginning of fiscal year 2005/06

Values in this table are based on the last A1C result reported for year

1 p < = 0.0001

Overall, 66.9% of people with diabetes had an A1C level done during 2005/06. Younger, female, non-urban people and those with lowest incomes were less likely to have an A1C test compared to their respective counterparts. However, the diabetic groups least likely to have an A1C test were those under age 40 (53.7%) and FN (59%). With the exception of females, the same demographic groups with fewest A1C tests also experienced the poorest A1C results. FN and those under age 40 exhibited the worst results with mean A1Cs of 8.0% and 8.1% respectively. The group with the best A1C profile were those aged 70+ (54.3% had A1Cs <= 7%, 7.1% had A1Cs >= 9% and the mean A1C was 7.2%).

Overall, 38.4% of adults with diabetes had >= 2 and 17.5% had >= 3 A1C tests during 2005/06 (Table 2). Results were similar between males and females. Non-urban people were less likely than urban dwellers to have >1 A1C tests during the year. However, those tested least frequently were FN.
Table 2

Frequency of A1C testing among Saskatchewan adults with Diabetes by Demographic Characteristics

 

Number of persons with diabetes*

Persons with >= 2 A1C tests/year

Persons with >= 3 A1C tests/year

  

number

%

OR (95% CI)

number

%

OR (95% CI)

ALL SASK

48200

18256

38.4

 

8436

17.5

 

female

23028

8767

38.1

0.99(0.95-1.03)

4000

17.4

1.00(0.95-1.04)

male†

25172

9759

38.8

 

4436

17.6

 

ETHNICITY

       

FN

5959

1747

29.3

0.69(0.65-0.74)

692

11.6

0.65(0.60-0.71)

OSK†

42241

16779

39.7

 

7744

18.3

 

LOCATION

       

urban†

25809

10351

40.1

 

4855

18.8

 

non-urban

22338

8160

36.5

0.85(0.82-0.88)

3572

16.0

0.81(0.77-0.85)

All rates are crude rates

*Includes prevalent diabetes cases aged 20 years and older at beginning of fiscal year 2005/06 and who survived the year with SK Ministry of Health insurance coverage

†Reference category

Overall, the proportion of diabetic people with target A1Cs decreased from 49.1% of those tested once to 47.3% of those tested >= 4 times (Table 3). This downward trend was mirrored in males and OSK. Only FN experienced an improvement in target A1C by frequency of testing (38.9% of those tested once to 44.9% of those tested >= 4 times).
Table 3

Outcomes of A1C Testing by Frequency of Testing among Saskatchewan Adults with Diabetes

 

Persons with only 1 A1C test/year

Persons with 2 A1C tests/year

Persons with 3 A1C tests/year

Persons with >= 4 A1C tests/year

Test for linear trend

 

n*

% A1C

<= 7.0

n†

% A1C <= 7.0

n†

% A1C <= 7.0

n†

% A1C <= 7.0

 

ALL SASK

15034

49.1

10336

48.0

5371

47.5

3179

47.3

 

female

7059

51.3

4864

49.8

2581

49.1

1467

49.7

p = 0.0259 (1 sided) = 0.0517 (2 sided)

Male

7975

47.1

5472

46.4

2790

46.0

1712

45.3

p = 0.0711 (1 sided) = 0.1422 (2 sided)

ETHNICITY

         

FN

1866

38.9

1073

41.0

453

44.8

254

44.9

p = 0.0035 (1 sided) = 0.0070 (2 sided)

OSK

13168

50.5

9263

48.8

4918

47.7

2925

47.6

p = 0.0001 (1 sided) = 0.0001 (2 sided)

All rates are crude rates

* Denominator is all prevalent diabetes cases aged 20 years and older at the beginning of fiscal year 2005-06

† Includes prevalent diabetes cases defined at beginning of fiscal year 2005/06 and who survived the year with SK Ministry of Health insurance coverage

A1C values in this table are based on the last A1C result reported for year

Table 4 shows results of LDL-C testing among adults with diabetes in Saskatchewan's two most populous Health Regions. Of the 24,207 prevalent diabetes cases, 11,294 were female (46.7%) and 2,321 were FN (9.6%). Most were urban (77.3%) and the majority were aged 50+ (80.3%). Almost half (48.7%) were in the lowest two income quintiles.
Table 4

LDL Cholesterol Indicator outcomes among Diabetic adults in Two Saskatchewan Health regions by Demographic Characteristics

 

Number of persons with diabetes†

Tested for LDL-C

Number of persons tested

LDL-C < 2.5 mmol/L

Mean LDL-C

  

%

OR (95% CI)

 

%

OR (95% CI)

Mmol/L

Significance

TOTAL

24207

49.7

 

12019

45.1

 

2.7

 

female

11294

47.6

0.89(0.85-0.94)

5379

41.3

0.76(0.78-0.81)

2.8

p < 0.0001

male*

12913

51.4

 

6640

48.2

 

2.6

 

ETHNICITY

        

FN

2321

29.2

0.38(0.35-0.42)

677

47.9

1.26(1.07-1.47)

2.6

p = 0.19

OSK*

21886

51.8

 

11342

44.9

 

2.7

 

LOCATION

        

urban*

18702

57.1

 

10679

45.0

 

2.7

 

non-urban

5476

24.1

0.23(0.22-0.25)

1322

46.2

1.03(0.92-1.15)

2.7

p = 0.18

AGE (years)

        

20-29

358

29.1

0.49(0.39-0.62)

104

42.3

0.84(0.57-1.25)

2.8

 

30-39

1379

35.1

0.64(0.57-0.72)

484

39.5

0.75(0.62-0.91)

2.8

 

40-49

3040

46.8

1.04(0.96-1.13)

1423

42.1

0.82(0.73-0.93)

2.7

 

50-59

5268

54.5

1.41(1.32-1.51)

2871

43.4

0.85(0.77-0.94)

2.7

p = 0.0002

60-69

5428

57.9

1.62(1.51-1.74)

3144

46.7

0.98(0.89-1.07)

2.7

 

≥ 70*

8734

45.7

 

3993

46.9

 

2.7

 

INCOME QUINTILE

        

lowest

6170

45.8

0.74(0.69-0.81)

2826

44.1

0.91(0.81-1.02)

2.7

 

second

5630

48.4

0.81(0.74-0.88)

2726

44.6

0.91(0.81-1.02)

2.7

 

third

4499

49.9

0.85(0.78-0.92)

2247

45.1

0.93(0.82-1.04)

2.7

p < 0.02

fourth

4044

52.3

0.93(0.85-1.01)

2116

45.1

0.92(0.81-1.03)

2.7

 

highest*

3770

54.8

 

2067

47.4

 

2.6

 

All rates are crude rates

* Reference category

† Includes prevalent diabetes cases aged 20 years and older at beginning of fiscal year 2005/06 in Saskatchewan's two largest Health Regions

Overall, 49.7% of diabetic adults had at least one LDL-C test during 2005/06. Younger, female, non-urban people and those with lowest incomes were less likely to have an LDL-C test than reference groups. However, those least likely to have an LDL-C test were younger people and FN (29.2% versus 51.8% of OSK). Females displayed among the poorest LDL-C outcomes with only 41.3% achieving target LDL-C levels compared to 48.2% of males. Mean LDL-C was also poorer for females (2.8 mmol/L) compared to males (2.6 mmol/L). In contrast to A1C findings, FN and non-urban diabetic people were more likely to achieve target LDL-C levels than their OSK and urban counterparts.

During 2005/06, 41,934 diabetic OSK lived in Saskatchewan for the entire year. Of those, 36.9% were prescribed a lipid lowering agent compared to 38.6% of 20,714 diabetic OSK living in Saskatchewan's two most populous Health Regions. Table 5 shows that 6,914 diabetic OSK in the two Health Regions had a most recent LDL-C level >= 2.5 mmol/L, but only 39.2% of those received a lipid lowering drug. Although no significant differences were found by location and income quintile, there was a trend for better treatment rates with increasing income. The lowest treatment rates were observed in the oldest and youngest subjects, and among women. However, both males (27.0%) and females (18.8%) under age 40 were least likely to receive treatment.
Table 5

Use of Lipid Lowering Drugs among Diabetic OSK With LDL-C >= 2.5 MMOL/L by Demographic Characteristics

 

Persons with

LDL-C ≥ 2.5 mmol/L†

Persons dispensed a lipid lowering drug

Crude rate (%)

OR (95% CI)

TOTAL

6914

2711

39.2

 

AGE (years) Female

    

20-39

165

31

18.8

0.38 (0.26-0.58)

40-49

389

123

31.6

0.77 (0.60-0.98)

50-59

723

305

42.2

1.21 (1.00-1.46)

60-69

795

329

41.4

1.17 (0.97-1.41)

≥ 70*

1157

435

37.6

 

AGE (years) Male

    

20-39

152

41

27.0

0.72 (0.50-1.06)

40-49

428

174

40.7

1.34 (1.07-1.69)

50-59

978

442

45.2

1.61 (1.35-1.93)

60-69

1003

451

45.0

1.60 (1.34-1.91)

≥ 70*

1124

380

33.8

 

LOCATION

    

urban*

6196

2416

39.0

 

non-urban

704

288

40.9

1.09 (0.9-1.3)

INCOME QUINTILE

    

lowest

1544

569

36.9

0.92 (0.79-1.08)

second

1566

606

38.7

0.97 (0.83-1.13)

third

1320

515

39.0

0.96 (0.82-1.13)

fourth

1267

525

41.4

1.05 (0.90-1.24)

highest*

1191

482

40.5

 

*Reference category

Drug prescribing data was not available for FN, hence, analysis for lipid lowering prescribing indicators was limited to OSK

Data are stratified by sex because age-sex interaction was present

† Sub-group of prevalent diabetes cases aged 20 years and older at beginning of fiscal year 2005/06 in Saskatchewan's two largest Health Regions

Discussion

We measured A1C and LDL-C quality of care indicators in Saskatchewan's diabetic population by linking health care system administrative data with laboratory data. While over 2/3 of people with diabetes received A1C testing, less than 50% achieved target levels and 12.6% exhibited very poor glycemic control. Almost 50% of the study population received LDL-C testing but only 45.1% of those achieved target levels and only 39.2% of those with values above the target of 2.5 mmol/L were prescribed a lipid lowering drug.

Diabetic adults who were female, FN, non-urban, younger or in lower income quintiles were less likely to receive A1C and LDL-C testing. Apart from females, the same groups also experienced poorer glycemic control. While younger subjects and those with lower incomes also displayed poorer LDL-C results, the largest disparity was observed between sexes. Females had higher mean LDL-C concentrations and were less likely to achieve target LDL-C levels. Despite that, diabetic OSK females with sub-optimal LDL-C were the group least likely to receive a lipid lowering agent. This was particularly evident in younger women, so likely included individuals with type 1 diabetes. A somewhat unexpected finding was that FN exhibited better LDL-C profiles than OSK. In the context of overall evidence for poorer quality of diabetes care, this observation suggests that there may be underlying differences in lipid metabolism between FN and OSK [18].

The proportion of diabetic people achieving target A1C levels decreased with frequency of testing among OSK but increased among FN. The reasons behind the former finding are complex but possibly explained in part by more frequent follow-up care in those with more brittle or complicated diabetes histories. In contrast, the small numbers of FN with more frequent A1C testing likely represented a subgroup with better diabetes care. This suggests that the overall poorer glycemic control experienced by FN may be subject to improvement through closer monitoring.

Although some of the statistically significant differences found here (particularly for mean A1C and LDL-C) may not be clinically problematic, it is important to highlight that the poorest overall results with respect to frequency of testing and achievement of target values, occurred among diabetic FN people and were substantive. While not unexpected, these findings provide evidence for ethnic-based disparities in quality of diabetes care. This is reflected in higher rates of many diabetes complications including amputations, strokes and end stage renal disease, as well as in higher mortality rates among FN as we have recently shown using the same methodology [19]. Although the reasons behind these disparities are perplexing in the context of a universal health care system, a recent national survey of diabetes care in FN communities shows promise in elucidating at least some of the underlying problems by examining individual level factors [20]. Furthermore, these sobering findings and their causes are highly relevant to other indigenous and developing populations who are also experiencing disproportionate rates of diabetes and diabetes complications [21].

Strengths of this study include employment of a validated algorithm to identify diabetes cases [12], inclusion of total Saskatchewan populations, ability to carry out a linkage between laboratory and health care system administrative data, and the ability to sub-divide the population by ethnicity. A significant limitation in the use of secondary data to conduct diabetes research is the unavailability of important individual level health determinants such as smoking, hypertension, and obesity as well as the inability to determine the impact of acculturation on First Nations people. Other limitations included an inability to identify people of Aboriginal heritage other than FN, but this reduces the true differences between FN and OSK. Second, identifying cases using administrative data may underestimate the incidence and prevalence of diabetes [12]. Third, although we could not differentiate between types 1 and 2 diabetes, most Canadian adults with diabetes have T2DM [14]; the proportion is even higher for FN [15]. Nonetheless, it is likely that the A1C and LDL-C indicator results for younger people with diabetes are partly attributable to OSK with type 1 diabetes. Finally, there may be overlap between the demographic groups that we have described. In particular, poorer results for FN in A1C indicators may be partly related to younger age and lower incomes (or vice versa). However, that would not explain the poor results among young OSK (particularly females) regarding treatment with lipid lowering agents.

Conclusions

Linkage of laboratory data with health care system administrative data can be used to provide standardized information for people with diabetes on a population basis that can be used to identify deficiencies in care and support quality improvement initiatives. The potential to do so exists throughout Canada and other jurisdictions with universal health care systems and/or electronic medical records serving large patient groups. For example, a recent study described the utilization and outcomes of A1C testing among people with diabetes in eastern Ontario [22]. Although their results were consistent with those reported here, they did not provide information for FN.

We have now shown that less than 50% of diabetes cases in Saskatchewan achieved optimal glycemic and lipid control and even smaller proportions were tested as frequently as recommended. Furthermore, disparities were most evident among FN who exhibited substantially lower testing rates and poorer glycemic control than others. The fact that significant gaps exist between evidence-based guidelines for diabetes care and their implementation is a cause for concern. These findings should provide an impetus for understanding those gaps, and for developing and monitoring new strategies designed to improve the quality of diabetes care.

Declarations

Acknowledgements

This study was supported by internal funding from the Saskatchewan Health Quality Council and the University of Saskatchewan.

DISCLAIMER: This study is based in part on non-identifiable data provided by the Saskatchewan Ministry of Health. The interpretations and conclusions contained herein are not intended to represent those of the Government of Saskatchewan or the Saskatchewan Ministry of Health.

Authors’ Affiliations

(1)
The Division of Quality Measurement and Analysis, Saskatchewan Health Quality Council
(2)
Department of Medicine, Royal University Hospital, University of Saskatchewan
(3)
Department of Community Health and Epidemiology, Royal University Hospital, University of Saskatchewan

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© Dyck et al; licensee BioMed Central Ltd. 2010

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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