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Hospital factors and patient characteristics in the treatment of colorectal cancer: a population based study

  • Carlotta Sacerdote1Email author,
  • Ileana Baldi1,
  • Oscar Bertetto2,
  • Daniela DiCuonzo1,
  • Enzo Farina3,
  • Eva Pagano1,
  • Rosalba Rosato1, 4,
  • Carlo Senore5,
  • Franco Merletti1 and
  • Giovannino Ciccone1
BMC Public Health201212:775

DOI: 10.1186/1471-2458-12-775

Received: 29 December 2011

Accepted: 5 September 2012

Published: 12 September 2012

Abstract

Background

The present study focuses on the analysis of social, clinical and hospital characteristics that can lead to disparities in the management and outcome of care. To that end, indicators of the quality of initial treatment delivered to newly-diagnosed colorectal cancer patients in a North-Western Region of Italy, were investigated using administrative data.

Methods

The cohort includes all incident colorectal cancer patients (N = 24,187) selected by a validated algorithm from the Piedmont Hospital Discharge Record system over an 8-year period (2000–2007).

Three indicators of quality of care in this population-based cohort were evaluated: the proportion of preoperative radiotherapy (RT) and of abdominoperineal (AP) resection in rectal cancer patients, and the proportion of postoperative in-hospital mortality in colorectal cancer patients.

Results

Among rectal cancers, older patients were less likely to have preoperative RT, and more likely to receive an AP resection compared to younger patients. The probability of undergoing preoperative RT and AP resection was reduced in females compared to males (odds ratio (OR) 0.77, 95% confidence interval (CI) 0.64-0.93 and OR 0.78, 95%CI 0.69-0.89, respectively). However, there was a trend of increasing RT over time (p for trend <0.01). The probability of undergoing AP resection was increased in less-educated patients and in hospitals with a low caseload.

A higher risk of postoperative in-hospital mortality was found among colorectal cancer patients who were older, male, (female versus male OR 0.71, 95%CI 0.60-0.84), unmarried (OR 1.32, 95%CI 1.09-1.59) or with unknown marital status.

Conclusions

The study provides evidence of the importance of social, clinical and hospital characteristics on the equity and quality of care in a Southern European country with an open-access public health care system.

Keywords

Colorectal cancer Quality of care Radiotherapy In-hospital mortality Hospital discharges

Background

Colorectal cancer is a common malignancy and its incidence is increasing in industrialized countries [1]. While there are several studies on new drugs for colorectal cancer [24], fewer studies have been conducted to assess the appropriateness and equity of care provided to colorectal cancer patients at a population level [57].

Administrative data provide information on quality of care, and monitor indicators of care that can be used for assessment at a population- and hospital-level [8, 9]. The linkage of different administrative sources provides an efficient method for gathering data on individual patterns of care [10]. Although clinical data available in administrative databases are considered limited in accuracy [11], their validity should be specifically assessed, as variations exist not only between countries and periods, but also between variables included. The use of administrative data in the assessment of quality of care among colorectal cancer patients is common in the United States [12, 13], Canada [14] and Northern Europe (United Kingdom, Sweden and Denmark) [6, 7, 15]. To our knowledge, there are no published population-based studies on the quality of care among colorectal cancer patients in Southern Europe.

Preoperative radiotherapy (RT) in stage II or III rectal cancer has been recommended by regional guidelines since 2001 [16] and recently confirmed [17] to aid in the reduction of local recurrences and tumor shrinkage before surgery. In the last 10 years in Europe, total mesorectal excision with sphincter-sparing procedure is the preferred choice over sphincter-ablating procedures. The shift toward sphincter-sparing procedures with the preservation of normal bowel activity is the result of several studies that have indicated similar outcomes [12] and improved quality of life [13, 1820]. An abdominoperineal (AP) resection, which denotes permanent colostomy, is unavoidable in some circumstances. However, surgeons with a higher caseload of rectal cancer patients, have been shown to perform a lower proportion of AP resections and have patients with better survival [14, 15, 2123]. Finally postoperative in-hospital mortality has frequently been used as a measure of quality of care, but careful risk adjustment is needed to minimize the role of unbalanced case-mix distribution between providers [24]. All these indicators have been used in several studies that analyzed hospital statistics [7, 14, 25].

The present study focuses on the analysis of non-clinical factors that can lead to disparities in the management and outcome of care. To that end, social, clinical and hospital determinants of the quality of initial treatment delivered to newly-diagnosed colorectal cancer patients who underwent a surgical procedure between 2000 and 2007 in the Piedmont Region (North-Western Italy) were investigated, using routinely available administrative data.

Methods

Study population

The study cohort of incident colorectal cancer cases in the resident population of the Piedmont Region (about 4.3 million inhabitants) was identified from the Piedmont Hospital Discharge Record (HDR) system over an 8-year period using a validated algorithm [26] based on combinations of diagnostic and surgical procedure codes according to the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM). The HDR system routinely collects both inpatients and day-care activity from all regional private and public hospitals publicly funded. The Italian National Health Service covers the entire population and private funding is residual, particularly for life-threatening diseases like cancer. Providers, both public and private, including hospitals outside the region, to be reimbursed by the NHS need to deliver a Hospital Discharge Record. As a consequence, all the in-patient and day-care activities are included in the database for administrative purpose. Patient’s HDRs are identified by means of an encrypted unique identification code based on the tax identification number. Multiple records relative to each patient are linked by means of this encrypted code.

Among all patients discharged between January 1, 2000 and December 31, 2007 with a surgical diagnosis-related group (DRG) claim, those with a diagnosis of malignant neoplasm of the colon (ICD-9-CM: 153.0-153.9) or malignant neoplasm of the rectum or rectosigmoid junction (ICD-9-CM: 154.0-154.1, 154.8) were selected (N = 29,248). Of this cohort, patients with potentially prevalent cancer (those who had been hospitalized at any time during the previous 5 years with either colon or rectal cancer), as well as those with a history of colorectal cancer (ICD-9-CM V10.05-V10.06), were excluded (N = 3,946).

Of the remaining 25,302 incident colorectal cancer cases, an additional 1,115 cases (4.4%) that were discharged from extra-regional hospitals were excluded (Figure 1). Patients were classified as colon cancer and rectal cancer patients on the basis of the site of the tumors. The 142 patients with a double lesion in colon and rectum were classified as rectal cancer patients.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2458-12-775/MediaObjects/12889_2011_Article_4861_Fig1_HTML.jpg
Figure 1

Flow chart of inclusion of colorectal cancer patients into the cohort.

Patient characteristics

The HDR system routinely includes patient’s demographic data, admission and discharge dates, admission referral source, discharge status, up to six ICD-9-CM discharge diagnostic and procedure codes, the regional code of the facility, the diagnosis-related group and its tariff.

Firstly, the surgical approach was classified as palliative or curative; this last group was then split according to the surgical procedure performed: AP resection (ICD9: 48.5, 48.62) or other resections (ICD9: 45.4x-45.8x, 48.3x-48.4x, 48.61, 48.63-48.69). Cases were classified as having concomitant obstruction (ICD-9-CM 560.9), perforation (ICD-9-CM 569.83), or an emergency admission (OPE) or not.

Using all the diagnosis codes from the first surgical admission, disease staging [27] was used to classify patients into two broad categories, according to the absence or presence of loco-regional or distant metastases. To maximize ascertainment of comorbidity, all hospital discharges that occurred within 12 months before the indexed surgical admission were identified, and all the coded diagnoses used to calculate comorbidity by the Charlson index (hereafter referred to as comorbidity), as adapted by Romano et al. for use with claims data [28].

Additionally, for each patient, the risk-of-mortality score was calculated using the 3 M all-patient-refined (APR)-DRG classification system, V20 [29] classified in the categories low, medium, high and extreme. This proprietary software package assigns a value from 1 to 4 to each patient in each APR-DRG group, corresponding to increasing risk of death. This score is generated using data on age, the presence of comorbidities, and some procedures and their interactions, thereby allowing a meaningful risk adjustment tool for outcome analyses.

Hospital volume was classified into three classes according to annual caseload of colorectal surgical resection procedures (≤10, 11–25 and >25 for rectal cancer and <25, 26–60 and >60 for colon cancer), based on categories presented in the recommendations of the regional guidelines [16]. Hospitals were also categorized according to the presence of a RT service.

For each patient, accessibility to preoperative RT was measured as the distance between their residence and the nearest RT service, by car and under normal traffic conditions, [30]. Three categories were defined: same city or less than 15 minutes; 15 to less than 30 minutes; 30 minutes or more.

Outcomes

Three indicators of quality of care were selected: the proportions of rectal cancer patients who received preoperative RT or abdominoperineal (AP) resection, and the proportion of all colorectal cancer patients who died post-operatively in hospital.

Statistical analysis

Random-intercept logistic regression models were used to analyze data, accounting for within-hospital outcome correlation. The logistic models included patients’ age (≤60, 61–70, 71–80 or >80 years old), gender, education level (categorized as ‘secondary or more’, ‘intermediate’, ‘primary’ or ‘unknown’), marital status (classified as ‘married’, ‘unmarried’: single, separated, divorced, or widowed, and ‘unknown’) and year of admission. Given the strong correlation between APR-DRG risk-of-mortality score, tumor stage and comorbidity (Charlson index 0, >1), these predictors were not included in the models simultaneously.

The results are expressed as odds ratios (OR) and 95% confidence intervals (95%CI). Statistical analyses were performed using STATA (version 9.2) software.

Validation

In this study the method used to identify incident colorectal cancer cases included in the study cohort sample was validated first, followed by the indicators obtained from the HDR system.

The algorithm adopted to identify colorectal cancer cases in this study cohort has been previously validated using the data of the Piedmont Cancer Registry as a reference standard (positive predictive value of the identification algorithm was 89.9%, 95%CI 87.3-92.1) [26].

The accuracy of key variables obtained from the HDR system was further validated using a sample of 605 patients randomly selected from the same study population as a reference standard (aged 50–69, surgically treated during 2001–2002). In this high-resolution sample, for each patient we abstracted and analyzed all clinical records of surgical, and RT hospitalization identified from the HDR system (2001–2005), and found 100% reproducibility for the variables “emergency admission” and “mortality”. Furthermore 96% of the colorectal cancers (n = 580) are histopathologically confirmed. Table 1 shows the validation data for “type of cancer”, “type of surgery” and “presence of metastasis”.
Table 1

Validation results based on a survey of 605 clinical records (the high-resolution sample)

 

High-resolution sample (gold standard)

   

Colon

Rectum

Missing

TOTAL

  

Colon

181

6

0

187

 

Type of cancer

Rectum

28

390

0

418

  

TOTAL

209

396

0

605

   

Curative intent

Palliative intent

Missing

TOTAL

  

Curative intent

567

32

0

599

 

Type of surgery

Palliative intent

5

1

0

6

  

TOTAL

572

33

0

605

Study cohort sample

  

AP resection

Minor resection

Missing

TOTAL

  

AP resection

78

11

0

89

 

Surgery for rectal cancer

Minor resection

15

281

5

301

  

Missing

0

0

0

0

  

TOTAL

93

292

5

390

   

Yes

No

Missing

 
  

Yes

65

2

0

65

 

Presence of metastasis

No

25

509

6

540

  

Missing

0

0

0

0

  

TOTAL

90

511

6

605

AP: abdominoperineal.

Ethical issues

The study is a retrospective clinical audit to monitor the quality of treatment, delivered to colorectal cancer patients. It has been conducted as recommended in the regional guidelines [16], by the Centro di Riferimento per l'Epidemiologia e la Prevenzione Oncologica in Piemonte under the mandate of the regional health authority, using preexisting encrypted administrative data. For these reasons this project was exempt from ethical review.

Results

During the 8-year period, 25,302 patients with incident colorectal cancer were identified: 24,187 were treated in the Piedmont Region and 1,115 (4.4%) in extra-regional hospitals.

Figure 1 depicts the flow-chart of the inclusion of colorectal cancer patients in the cohort: 22,289 (92%) potentially curative resections were identified in 15,256 and 7,033 colon and rectal cancer patients respectively.

Among the 5,437 rectal cancer patients who underwent an elective intervention, 727 (13.4%) underwent preoperative RT (Table 2). Older patients were less likely to have RT before surgery. The probability to undergoing RT was also reduced in females versus males (OR 0.77, 95%CI 0.64-0.93), and, as expected, for patients with comorbidity (Charlson index ≥1 OR 0.73, 95%CI 0.59-0.90) or metastases (0.47, 95%CI 0.35-0.65). Furthermore, there was an unexpected effect of educational level: less-educated patients had a higher probability of receiving neoadjuvant RT. There was a clear trend of increasing RT over time (P for trend <0.01). Patients were more likely to receive RT if the hospital where the surgery was performed had a RT service (OR 2.24, 95%CI 1.77-2.85). Almost 47% of the sample lived in a city that had a RT service, and about 16% of patients lived 30 minutes or more away from a RT service. The adjusted OR to receive neoadjuvant RT tended to decrease with increasing distance between a patient’s residence and RT service (P for trend = 0.06). We performed a sensitivity analysis, including in the model the hospital volume instead of RT service. The results of this model are similar for all variables and the adjusted OR to receive neoadjuvant RT decreased with decreasing of the hospital volume lower than 25 case at year (11–25 cases/year versus >25 cases/year OR 0.84, 95%CI 0.41-0.98).
Table 2

Preoperative radiotherapy (RT) (followed by planned surgical admission) in 5,437 incident rectal cancer patients

 

Total (N=5437)

Preoperative RT (N=727)

Random-effect model*

 

No.

%

OR

95% CI

P

Age (years)

     

 ≤60

1,082

19.2

1

 

<0.001

 61-70

1,707

14.8

0.71

(0.57-0.90)

 

 71-80

1,958

11.4

0.51

(0.40-0.65)

 

 >80

690

6.1

0.24

(0.16-0.35)

 

Gender

     

 Male

3,375

14.2

1

 

0.03

 Female

2,062

12.1

0.77

(0.64-0.93)

 

Educational level

     

 Secondary or more

813

13.9

1

 

<0.001

 Intermediate

1,244

15.3

1.35

(1.03-1.77)

 

 Primary

2,869

11.7

1.41

(1.09-1.83)

 

 Unknown

511

17.4

1.16

(0.79-1.71)

 

Marital status

     

 Married

3,720

13.3

1

 

<0.001

 Unmarried

1,352

11.5

0.99

(0.80-1.23)

 

 Unknown

365

20.8

0.84

(0.58-1.20)

 

Disease staging

     

 Absence of metastases

4,836

13.9

1

 

0.01

 Presence of metastases

601

8.8

0.47

(0.35-0.65)

 

Comorbidity (Charlson index)

     

 0

4,068

14.1

1

 

0.01

 ≥1

1,369

11.2

0.73

(0.59-0.90)

 

Year of admission

     

 2000

654

6.9

1

 

<0.001

 2001

706

9.6

1.51

(1.00-2.29)

 

 2002

617

12.3

1.96

(1.30-2.95)

 

 2003

607

15.3

2.76

(1.85-4.11)

 

 2004

729

16.0

2.98

(2.02-4.40)

 

 2005

691

16.5

2.90

(1.96-4.29)

 

 2006

738

15.2

2.82

(1.90-4.17)

 

 2007

695

14.7

3.04

(2.03-4.56)

 

RT service

     

 Absent

2,775

9.4

1

 

<0.001

 Present

2,662

17.5

2.24

(1.77-2.85)

 

Distance to RT service (min.)

     

 Same city or <15’

2,576

15.6

1

 

<0.001

 15’ to <30’

1,984

12.2

0.97

(0.80-1.18)

 

 ≥30’

877

9.6

0.82

(0.60-1.12)

 

Hospital volume (annual caseload)

     

 >25

3,076

17.6

-

*

<0.001

 11-25

1,778

6.8

-

*

 

 ≤10

583

11.1

-

*

 

*Given the correlation between hospital volume and presence of RT service, these predictors were not included in the models simultaneously.

Unmarried includes single, separated, divorced and widowed.

OR: odds ratio, CI: confidence interval, APR-DRG: all-patient-refined-diagnosis-related group, RT: radiotherapy.

Table 3 shows the proportion of patients receiving AP resection versus other, more conservative resections, among 7,033 rectal cancer patients, for each variable in the model. Patients older than 70 years were more likely to receive an AP resection compared to patients aged 60 years or younger. The probability of receiving AP resection also increased in less-educated patients and in hospitals with a low volume. AP resection was performed less frequently in women (OR 0.78, 95%CI 0.69-0.89). There was no independent association between disease stage, Charlson index, year of admission or emergency admission and having an AP resection for rectal cancer.
Table 3

Abdominoperineal (AP) resection* versus other resections (reference group) in 7,033 incident rectal cancer patients

 

Total (N = 7033)

AP resection (N = 727)

Random-effect model

 

No.

%

OR

(95% CI)

P

Age (years)

     

 ≤60

1,342

17.4

1

 

<0.001

 61-70

2,083

20.7

1.10

(0.91-1.33)

 

 71-80

2,536

23.9

1.30

(1.08-1.56)

 

 >80

1,072

24.6

1.38

(1.11-1.71)

 

Gender

     

 Male

4,275

23.0

1

 

0.002

 Female

2,758

19.9

0.78

(0.69-0.89)

 

Educational level

     

 Secondary or more

969

17.7

1

 

<0.001

 Intermediate

1,516

19.2

1.11

(0.90-1.38)

 

 Primary

3,796

23.9

1.40

(1.16-1.70)

 

 Unknown

752

22.1

1.29

(0.97-1.70)

 

Marital status

     

 Married

4,651

21.3

1

 

0.002

 Unmarried§

1,854

24.2

1.17

(1.02-1.35)

 

 Unknown

528

17.6

0.83

(0.63-1.10)

 

OPE

     

 No

5,437

22.5

1

 

0.05

 Yes

1,596

19.6

0.87

(0.75-1.01)

 

Disease staging

     

 Absence of metastases

6,180

21.8

1

 

0.82

 Presence of metastases

853

22.3

1.11

(0.93-1.32)

 

Comorbidity (Charlson index)

     

 0

5,174

21.5

1

 

0.24

 ≥1

1,859

22.8

1.01

(0.89-1.16)

 

Year of admission

     

 2000

861

23.0

1

 

0.04

 2001

887

23.9

1.12

(0.89-1.41)

 

 2002

789

23.7

1.06

(0.84-1.35)

 

 2003

825

19.1

0.87

(0.68-1.11)

 

 2004

961

20.0

0.92

(0.73-1.16)

 

 2005

906

22.2

1.02

(0.80-1.28)

 

 2006

923

23.4

1.08

(0.86-1.36)

 

 2007

881

19.4

0.85

(0.67-1.09)

 

Hospital volume (annual caseload)

     

 >25

3,688

20.6

1

 

0.001

 11-25

2,560

22.1

1.03

(0.81-1.31)

 

 ≤10

785

26.6

1.37

(1.03-1.82)

 

*ICD9: 48.5, 48.62. ICD9: 45.4x-45.8x, 48.3x-48.4x, 48.61, 48.63-48.69.

Cases with obstruction or perforation or in emergency admission were classified in the OPE category.

§Unmarried includes single, separated, divorced and widowed.

OR: odds ratio, CI: confidence interval, APR-DRG: all-patient-refined-diagnosis-related group, OPE: obstruction, perforation or emergency admission.

The postoperative in-hospital mortality in 22,289 colorectal cancer patients is shown in Table 4. During the study period, 841 patients died in the hospital after a surgery with curative intent. The median length-of-stay in the hospital after surgery was 10 days (interquartile range 5 days) and 11 days (interquartile range 18 days) for deceased and alive colon cancer patients respectively, and 11 days (interquartile range 6 days) and 12 days (interquartile range 19 days) for deceased and alive colon cancer patients respectively. The odds of dying in hospital in older patients, notably the 71-80-year and over-80-year groups, was two-to-three times higher compared to patients aged 60 years or younger. Patients at higher risk of postoperative in-hospital mortality were male (females versus males OR 0.71, 95%CI 0.60-0.84), unmarried or with unknown marital status (OR 1.32, 95%CI 1.09-1.59 and OR 1.65, 95%CI 1.20-2.29 respectively), and with an emergency admission (OR 1.54, 95%CI 1.29-1.85). Furthermore, there was a trend of decreasing mortality risk over time. After adjustment for other variables, hospital volume, as measured by annual caseload, did not show any effect on mortality.
Table 4

Postoperative in-hospital mortality in 22289 incident colorectal cancer patients after curative surgery

 

Total (N = 22289)

Unadjusted mortality

Random-effect model*

 

No.

%

OR

95% CI

P

Age (years)

     

 ≤60

3,910

1.0

1

  

 61-70

6,224

1.9

1.76

(1.20-2.57)

<0.001

 71-80

8,124

4.0

2.30

(1.61-3.28)

 

 >80

4,031

8.9

3.34

(2.33-4.79)

 

Gender

     

 Male

12,309

4.0

1

 

0.36

 Female

9,980

3.5

0.71

(0.60-0.84)

 

Educational level

     

 Secondary or more

3,165

1.2

1

 

<0.001

 Intermediate

4,745

2.6

1.14

(0.82-1.58)

 

 Primary

11,625

4.4

1.25

(0.95-1.67)

 

 Unknown

2,754

5.2

1.60

(1.10-2.32)

 

Marital status

     

 Married

14,221

3.1

1

 

<0.001

 Unmarried

6,212

5.0

1.32

(1.09-1.59)

 

 Unknown

1,856

5.5

1.65

(1.20-2.29)

 

OPE

     

 No

14,558

1.8

1

 

<0.001

 Yes

7,731

7.5

1.54

(1.29-1.85)

 

Disease staging

     

 Absence of metastases

19,064

3.5

-

 

<0.001

 Presence of metastases

3,225

5.7

-

  

Comorbidity (Charlson index)

     

 0

16,145

3.2

-

 

<0.001

 ≥1

6,144

5.4

-

  

Year of admission

     

 2000

2,458

4.1

1

 

0.55

 2001

2,583

3.4

0.82

(0.59-1.14)

 

 2002

2,651

4.1

0.95

(0.69-1.29)

 

 2003

2,687

3.9

0.75

(0.55-1.03)

 

 2004

2,924

4.4

0.77

(0.57-1.05)

 

 2005

2,930

3.3

0.53

(0.38-0.73)

 

 2006

3,006

3.5

0.54

(0.39-0.74)

 

 2007

3,050

3.6

0.49

(0.34-0.68)

 

Tumor site

     

 Colon

15,256

4.1

1

 

<0.001

 Rectum

7,033

3.1

1.05

(0.87-1.27)

 

Hospital volume (annual caseload)

     

 >60

9,371

3.5

1

 

0.10

 26-60

9,430

3.9

0.87

(0.64-1.19)

 

 <25

3,488

4.3

1.14

(0.76-1.69)

 

APR-DRG risk-of-mortality score

     

 Low

12,740

0.8

1

 

<0.001

 Medium

7,869

3.9

4.47

(3.54-5.66)

 

 High

1,359

19.1

25.77

(19.80-33.54)

 

 Extreme

321

56.7

153.03

(109.81-213.27)

 

*Given the correlation between APR-DRG risk-of-mortality score, tumor stage and comorbidity score these predictors were not included in the models simultaneously.

‡Unmarried includes single, separated, divorced and widowed.

OR: odds ratio; CI: confidence interval; APR-DRG: all-patient-refined-diagnosis-related group; OPE: obstruction, perforation or emergency admission.

Discussion

This study focused on the relationship between social, clinical and hospital characteristics and postoperative in-hospital mortality after treatment for colorectal cancer. For rectal cancer patients only, the associations of such factors with the use of neoadjuvant RT and AP resection rates were also investigated.

In our population, older people with rectal cancer were less frequently treated with preoperative RT, were more likely to undergo AP resections and to die during hospitalization. A reason for the lower rate of preoperative RT may be that elderly patients were excluded from RT, either for medical reasons or as a consequence of difficult accessibility to RT facilities [31]. Previous studies suggested that elderly patients are usually diagnosed at advanced stages [32]. In addition, the older patients of the cohort present with a higher burden of comorbidities, which could also explain the lower probability to undergo a more conservative surgery, and the higher in-hospital mortality.

Male patients in our study underwent AP more often, had a higher in-hospital mortality and were more likely to have RT before rectal cancer surgery. Previous studies observed that survival after colorectal cancer resection is better in women than in men [33, 34]. In particular, in a recent study in the United States, Paulson noted that women have a longer survival compared with men – despite the fact that they are more likely to have an emergency admission and at an older age – and they receive less aggressive medical treatment [35].

In the population of the Piedmont Region, marital status had a clear effect on in-hospital mortality, with unmarried patients and those with unknown marital status showing a significantly higher mortality risk than married patients. A possible explanation for this difference is diagnostic delay, which may affect the extent of disease at diagnosis, or differences in access to health care services [36]. However, a protective effect of family caregivers during hospitalization cannot be excluded.

Less-educated patients have a significantly higher probability to undergo preoperative RT. This is an unexpected finding, as less-educated people also have a higher risk to undergo AP resection and to die after colorectal surgery than more-educated people. Access to public health care services is provided free in Italy, and hospital admission is not clearly determined by social class [37]. Nevertheless, the higher rate of preoperative RT in less-educated patients may reflect a residual confounding by disease stage, with a lower proportion of early, screen-detected cases in this group (without indication for RT), as we already reported some years ago [38].

An extensive body of literature suggests that a hospital’s surgical volume of surgeries and hospital procedures is predictive of short- and long-term outcomes in patients undergoing complex medical and surgical procedures [22, 3942]. In our study, a hospital’s annual caseload was a predictor of the type of surgery performed among rectal cancer patients but not of in-hospital mortality. Finally, we found the presence of a RT service in the hospital where surgery was performed, and the distance between the patient’s residence and the nearest RT facility, to be two important predictive factors for preoperative RT. Most of these results, such as the role of comorbidity [43], hospital volume [39] and distance to RT facilities [42], have been reported by other studies, mostly from the United States. As such, this study has its added value in confirming the importance of these factors to the equity and quality of care in a Southern European country with an open-access public health care system.

The present study shares the limitations of research that uses routinely-collected data with respect of the completeness and accuracy of data coding and the use of limited clinical variables. In particular the lack of information on cancer stage could cause an underestimation of the proportion of incident rectal cancer that received the RT. Nevertheless, we performed an accurate validation of variables with the local cancer registry and a high-resolution clinical sample that confirmed the reliability of these administrative data. On the other hand, the major strength of our study is the population coverage and the availability of standardized data for a relatively long period.

Conclusion

The study provides evidence of the importance of social, clinical and hospital patient characteristics on the equity and quality of care in a Southern European country with an open-access public health care system. Furthermore it offers an example of how these factors allow for the maintenance of a monitoring system that can be used to assess key indicators of process and outcome of initial treatment of colorectal cancer over time, with acceptable accuracy, at minimal cost.

Abbreviations

RT: 

Preoperative radiotherapy

AP: 

Abdominoperineal

OR: 

Odds ratio

95%CI: 

95% confidence interval

HDR: 

Hospital discharge record

DRG: 

Diagnosis-related group

OPE: 

Obstruction perforation or emergency admission.

Declarations

Acknowledgements

This study was supported by grants of Compagnia di San Paolo, the “Ricerca Finalizzata” of the Piedmont Region and the grant “Dì Sette” of Cassa di Risparmio di Torino.

Authors’ Affiliations

(1)
Cancer Epidemiology Unit, San Giovanni Battista Hospital, CPO Piemonte and University of Turin
(2)
Medical Oncology Unit, San Giovanni Battista Hospital
(3)
General Surgery Unit, San Giovanni Battista Hospital
(4)
Department of Psychology, University of Turin
(5)
Cancer Epidemiology Unit, San Giovanni Battista Hospital, CPO Piemonte

References

  1. Parkin DM, Bray F, Ferlay J, Pisani P: Global cancer statistics, 2002. CA Cancer J Clin. 2005, 55 (2): 74-108. 10.3322/canjclin.55.2.74.View ArticlePubMedGoogle Scholar
  2. Cunningham D, Atkin W, Lenz HJ, Lynch HT, Minsky B, Nordlinger B, Starling N: Colorectal cancer. Lancet. 2010, 375 (9719): 1030-1047. 10.1016/S0140-6736(10)60353-4.View ArticlePubMedGoogle Scholar
  3. Hind D, Tappenden P, Tumur I, Eggington S, Sutcliffe P, Ryan A: The use of irinotecan, oxaliplatin and raltitrexed for the treatment of advanced colorectal cancer: systematic review and economic evaluation. Health Technol Assess. 2008, 12 (15): iii-ix-xi-162.View ArticlePubMedGoogle Scholar
  4. Julien LA, Thorson AG: Current neoadjuvant strategies in rectal cancer. J Surg Oncol. 2010, 101 (4): 321-326. 10.1002/jso.21480.View ArticlePubMedGoogle Scholar
  5. Bradley CJ, Given CW, Dahman B, Fitzgerald TL: Adjuvant chemotherapy after resection in elderly Medicare and Medicaid patients with colon cancer. Arch Intern Med. 2008, 168 (5): 521-529. 10.1001/archinternmed.2007.82.View ArticlePubMedGoogle Scholar
  6. Egeberg R, Halkjaer J, Rottmann N, Hansen L, Holten I: Social inequality and incidence of and survival from cancers of the colon and rectum in a population-based study in Denmark, 1994–2003. Eur J Cancer. 2008, 44 (14): 1978-1988. 10.1016/j.ejca.2008.06.020.View ArticlePubMedGoogle Scholar
  7. Tilney HS, Heriot AG, Purkayastha S, Antoniou A, Aylin P, Darzi AW, Tekkis PP: A national perspective on the decline of abdominoperineal resection for rectal cancer. Ann Surg. 2008, 247 (1): 77-84. 10.1097/SLA.0b013e31816076c3.View ArticlePubMedGoogle Scholar
  8. Aylin P, Bottle A, Majeed A: Use of administrative data or clinical databases as predictors of risk of death in hospital: comparison of models. BMJ. 2007, 334 (7602): 1044-10.1136/bmj.39168.496366.55.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Hansell A, Bottle A, Shurlock L, Aylin P: Accessing and using hospital activity data. J Public Health Med. 2001, 23 (1): 51-56. 10.1093/pubmed/23.1.51.View ArticlePubMedGoogle Scholar
  10. Kahn KL, Malin JL, Adams J, Ganz PA: Developing a reliable, valid, and feasible plan for quality-of-care measurement for cancer: how should we measure?. Med Care. 2002, 40 (6 Suppl): III73-III85.PubMedGoogle Scholar
  11. Green J, Wintfeld N: How accurate are hospital discharge data for evaluating effectiveness of care?. Med Care. 1993, 31 (8): 719-731. 10.1097/00005650-199308000-00005.View ArticlePubMedGoogle Scholar
  12. Beart RW, Steele GD, Menck HR, Chmiel JS, Ocwieja KE, Winchester DP: Management and survival of patients with adenocarcinoma of the colon and rectum: a national survey of the Commission on Cancer. J Am Coll Surg. 1995, 181 (3): 225-236.PubMedGoogle Scholar
  13. Morris AM, Billingsley KG, Baxter NN, Baldwin LM: Racial disparities in rectal cancer treatment: a population-based analysis. Arch Surg. 2004, 139 (2): 151-155. 10.1001/archsurg.139.2.151. discussion 156View ArticlePubMedGoogle Scholar
  14. Porter GA, Soskolne CL, Yakimets WW, Newman SC: Surgeon-related factors and outcome in rectal cancer. Ann Surg. 1998, 227 (2): 157-167. 10.1097/00000658-199802000-00001.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Martling A, Cedermark B, Johansson H, Rutqvist LE, Holm T: The surgeon as a prognostic factor after the introduction of total mesorectal excision in the treatment of rectal cancer. Br J Surg. 2002, 89 (8): 1008-1013. 10.1046/j.1365-2168.2002.02151.x.View ArticlePubMedGoogle Scholar
  16. Regione, Piemonte: Tumori del Colon-Retto. Linee guida clinico organizzative per la Regione Piemonte. Commissione Oncologica Regionale. 2001, Turin, Italy: Assessorato SanitàGoogle Scholar
  17. Wong RK, Berry S, Spithoff K, Simunovic M, Chan K, Agboola O, Dingle B: Preoperative or postoperative therapy for stage II or III rectal cancer: an updated practice guideline. Clin Oncol (R Coll Radiol). 2010, 22 (4): 265-271. 10.1016/j.clon.2010.03.002.View ArticleGoogle Scholar
  18. Ng AK, Recht A, Busse PM: Sphincter preservation therapy for distal rectal carcinoma: a review. Cancer. 1997, 79 (4): 671-683. 10.1002/(SICI)1097-0142(19970215)79:4<671::AID-CNCR3>3.0.CO;2-H.View ArticlePubMedGoogle Scholar
  19. Ramsey SD, Andersen MR, Etzioni R, Moinpour C, Peacock S, Potosky A, Urban N: Quality of life in survivors of colorectal carcinoma. Cancer. 2000, 88 (6): 1294-1303. 10.1002/(SICI)1097-0142(20000315)88:6<1294::AID-CNCR4>3.0.CO;2-M.View ArticlePubMedGoogle Scholar
  20. Renner K, Rosen HR, Novi G, Holbling N, Schiessel R: Quality of life after surgery for rectal cancer: do we still need a permanent colostomy?. Dis Colon Rectum. 1999, 42 (9): 1160-1167. 10.1007/BF02238568.View ArticlePubMedGoogle Scholar
  21. Simons AJ, Ker R, Groshen S, Gee C, Anthone GJ, Ortega AE, Vukasin P, Ross RK, Beart RW: Variations in treatment of rectal cancer: the influence of hospital type and caseload. Dis Colon Rectum. 1997, 40 (6): 641-646. 10.1007/BF02140891.View ArticlePubMedGoogle Scholar
  22. Borowski DW, Bradburn DM, Mills SJ, Bharathan B, Wilson RG, Ratcliffe AA, Kelly SB: Volume-outcome analysis of colorectal cancer-related outcomes. Br J Surg. 2010, 97 (9): 1416-1430. 10.1002/bjs.7111.View ArticlePubMedGoogle Scholar
  23. van Gijn W, Gooiker GA, Wouters MW, Post PN, Tollenaar RA, van de Velde CJ: Volume and outcome in colorectal cancer surgery. Eur J Surg Oncol. 2010, 36 (Suppl 1): S55-S63.View ArticlePubMedGoogle Scholar
  24. Iezzoni L: Risk adjustment for measuring health care outcomes. 2003, Chicago: Health Administration Press, 3Google Scholar
  25. Raine R, Wong W, Scholes S, Ashton C, Obichere A, Ambler G: Social variations in access to hospital care for patients with colorectal, breast, and lung cancer between 1999 and 2006: retrospective analysis of hospital episode statistics. BMJ. 2010, 340: b5479-10.1136/bmj.b5479.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Baldi I, Vicari P, Di Cuonzo D, Zanetti R, Pagano E, Rosato R, Sacerdote C, Segnan N, Merletti F, Ciccone G: A high positive predictive value algorithm using hospital administrative data identified incident cancer cases. J Clin Epidemiol. 2008, 61 (4): 373-379. 10.1016/j.jclinepi.2007.05.017.View ArticlePubMedGoogle Scholar
  27. Gonnella JS, Louis DZ: Disease staging classification system. Med Care. 1987, 25 (4): 360-10.1097/00005650-198704000-00009.View ArticlePubMedGoogle Scholar
  28. Romano PS, Roos LL, Jollis JG: Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol. 1993, 46 (10): 1075-1079. 10.1016/0895-4356(93)90103-8. discussion 1081–1090View ArticlePubMedGoogle Scholar
  29. Averill R, Goldfield N, Hughes J, Bonazelli J, Mc Cullough E, Steinbeck B, Mullin R, AT: All Patient Refined–Diagnosis-Related Groups (APR-DRGS) Version 20.0: Methodology Overview. Health Information Systems. 2003, Wallingford, CT: 3 M Health Information SystemsGoogle Scholar
  30. IRES: Matrix of distances between Piedmont town. Collana Banca Dati. 2004, Turin: Piemonte Servizio di Epidemiologia-ASL 5Google Scholar
  31. Zeber JE, Copeland LA, Hosek BJ, Karnad AB, Lawrence VA, Sanchez-Reilly SE: Cancer rates, medical comorbidities, and treatment modalities in the oldest patients. Crit Rev Oncol Hematol. 2008, 67 (3): 237-242. 10.1016/j.critrevonc.2008.02.002.View ArticlePubMedGoogle Scholar
  32. Aparicio T, Navazesh A, Boutron I, Bouarioua N, Chosidow D, Mion M, Choudat L, Sobhani I, Mentre F, Soule JC: Half of elderly patients routinely treated for colorectal cancer receive a sub-standard treatment. Crit Rev Oncol Hematol. 2009, 71 (3): 249-257. 10.1016/j.critrevonc.2008.11.006.View ArticlePubMedGoogle Scholar
  33. Morris AM, Billingsley KG, Hayanga AJ, Matthews B, Baldwin LM, Birkmeyer JD: Residual treatment disparities after oncology referral for rectal cancer. J Natl Cancer Inst. 2008, 100 (10): 738-744. 10.1093/jnci/djn145.View ArticlePubMedGoogle Scholar
  34. McArdle CS, McMillan DC, Hole DJ: Male gender adversely affects survival following surgery for colorectal cancer. Br J Surg. 2003, 90 (6): 711-715. 10.1002/bjs.4098.View ArticlePubMedGoogle Scholar
  35. Paulson EC, Wirtalla C, Armstrong K, Mahmoud NN: Gender influences treatment and survival in colorectal cancer surgery. Dis Colon Rectum. 2009, 52 (12): 1982-1991. 10.1007/DCR.0b013e3181beb42a.View ArticlePubMedGoogle Scholar
  36. Johansen C, Schou G, Soll-Johanning H, Mellemgaard A, Lynge E: Influence of marital status on survival from colon and rectal cancer in Denmark. Br J Cancer. 1996, 74 (6): 985-988. 10.1038/bjc.1996.470.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Le H, Ziogas A, Lipkin SM, Zell JA: Effects of socioeconomic status and treatment disparities in colorectal cancer survival. Cancer Epidemiol Biomarkers Prev. 2008, 17 (8): 1950-1962. 10.1158/1055-9965.EPI-07-2774.View ArticlePubMedGoogle Scholar
  38. Ciccone G, Prastaro C, Ivaldi C, Giacometti R, Vineis P: Access to hospital care, clinical stage and survival from colorectal cancer according to socio-economic status. Ann Oncol. 2000, 11 (9): 1201-1204. 10.1023/A:1008352119907.View ArticlePubMedGoogle Scholar
  39. Gruen RL, Pitt V, Green S, Parkhill A, Campbell D, Jolley D: The effect of provider case volume on cancer mortality: systematic review and meta-analysis. CA Cancer J Clin. 2009, 59 (3): 192-211. 10.3322/caac.20018.View ArticlePubMedGoogle Scholar
  40. Iversen LH, Harling H, Laurberg S, Wille-Jorgensen P: Influence of caseload and surgical speciality on outcome following surgery for colorectal cancer: a review of evidence. Part 2: long-term outcome. Colorectal Dis. 2007, 9 (1): 38-46. 10.1111/j.1463-1318.2006.01095.x.View ArticlePubMedGoogle Scholar
  41. Salz T, Sandler RS: The effect of hospital and surgeon volume on outcomes for rectal cancer surgery. Clin Gastroenterol Hepatol. 2008, 6 (11): 1185-1193. 10.1016/j.cgh.2008.05.023.View ArticlePubMedPubMed CentralGoogle Scholar
  42. Jones AP, Haynes R, Sauerzapf V, Crawford SM, Zhao H, Forman D: Travel time to hospital and treatment for breast, colon, rectum, lung, ovary and prostate cancer. Eur J Cancer. 2008, 44 (7): 992-999. 10.1016/j.ejca.2008.02.001.View ArticlePubMedGoogle Scholar
  43. Iversen LH, Norgaard M, Jacobsen J, Laurberg S, Sorensen HT: The impact of comorbidity on survival of Danish colorectal cancer patients from 1995 to 2006–a population-based cohort study. Dis Colon Rectum. 2009, 52 (1): 71-78. 10.1007/DCR.0b013e3181974384.View ArticlePubMedGoogle Scholar
  44. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/12/775/prepub

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© Sacerdote et al.; licensee BioMed Central Ltd. 2012

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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