Can Cancer Patients Seeking a Second Opinion Get Better Care?

, ,
The American Journal of Managed Care, May 2013, Volume 19, Issue 5

Colorectal resection patients in Taiwan with heavy hospital shopping behaviors got better surgical care than those who did not shop or hospitals.

Objectives:

To investigate whether cancer patients who sought a second opinion received better medical care.

Study Design:

A total of 1358 newly diagnosed colorectal cancer patients undergoing resection were identified from Taiwan’s National Health Insurance Research Database between 2004 and 2008. The frequency of doctor shopping and hospital shopping in the 6 months before resection was used to define “seeking a second opinion.”

Methods:

A generalized hierarchical linear model was used to determine the influence of doctor shopping and hospital shopping on in-hospital complications and prolonged hospitalization after colorectal resection.

Results:

The risk of in-hospital complications for heavy doctor shoppers was significantly higher than that for patients who were not doctor shoppers (odds ratio [OR] = 1.675, P = .037). However, the risk was significantly lower for heavy hospital shoppers compared with those who were not hospital shoppers (OR = 0.272, P = .007). The frequency of doctor shopping and hospital shopping was not significantly associated with prolonged hospitalization.

Conclusions:

For colorectal resection patients, the selection of a proper hospital for surgery resulted in better surgical care. The quality of surgical care was worse with heavy doctor shopping. We suggest that healthcare authorities disclose data about the quality of a hospital’s cancer treatment to increase patient access to such information. This may help patients find quality healthcare providers more quickly and reduce the waste of medical resources resulting from the long process of seeking medical care.

Am J Manag Care. 2013;19(5):380-387Seeking second opinions increases the cost of medical care. However, seeking second opinions might be recommended for cancer patients due to the variety of cancer treatments.

  • Among colorectal resection patients in Taiwan, those who were heavy hospital shoppers had a lower risk of in-hospital complications, whereas those who were heavy doctorshoppers had a higher risk of in-hospital complications.

  • Prolonged hospitalization was not significantly affected by frequencies of hospital shopping and doctor shopping.

  • Information on quality of cancer care should be disclosed to help patients shorten their process of seeking medical care.

The development of public insurance and the availability of media for medical information have reduced the obstacles that hinder patients from seeking medical care and raised patients’ consumer awareness.1 With the ability to choose a preferred treatment, patients can seek a second opinion for the same illness to receive better quality of medical care.2 Unlike the 1-way medical care of the past, patients can now not only spontaneously seek the medical care that they need, but also change their healthcare provider if they are dissatisfied with their first provider.3 However, in view of increasing medical expenses, many researchers have examined hospital shopping or doctor shopping to test the hypothesis that seeking a second opinion could cause a financial burden on the medical care system.4-6

Seeking a second opinion is defined as seeking medical care from more than 1 physician for the same condition. Compared with the judgment made by only 1 physician, a diagnosis made by multiple doctors is considered less likely to be inaccurate and can reduce a patient’s anxiety. 4,7,8 Most previous studies have evaluated the seeking of a second opinion by patients with specific conditions such as upper respiratory diseases, pulmonary tuberculosis, cancers, neurologic disorders, or polypharmacy. 5,9-11 A patient’s targets for comparison include both physicians and hospitals. Factors influencing a patient’s choice of a hospital include reputation, service volume, location, cost, and the patient’s own previous experiences.12-14 Factors important in the choice of a physician include the physician’s attitude, treatment recommendations, and patient satisfaction with that physician’s care.15-17 Patients select a preferred care provider after a thorough comparison of all these factors.

There are 3 broad areas in the research on seeking a second opinion. One area of research has been to study the characteristics of patients who are on the receiving end of poor communication.2,18,19 A second area involves investigation into the motives for seeking a second opinion.18,20 A few studies have evaluated the results after seeking a second opinion.18,21-23 Some earlier studies found that improperly seeking a second opinion could waste medical resources and should be avoided.18 In addition, patients tended to feel even more lost if the second physician made the same diagnosis. Conversely, some researchers suggested that when there are diagnostic differences between the first and second opinions,the second opinion could be helpful for providing proper medical care and avoiding excessive or insufficient treatment.21,22

Due to the nature of their disease and the potential harm from toxic treatment modalities, cancer patients are more likely to seek a second opinion. According to studies, nearly 60% of cancer patients have sought a second opinion.24,25 A diagnosis of cancer is a great shock to a patient, and cancer patients often have many questions about their diagnosis and treatment. If they do not obtain satisfactory answers from the first physician, patients go to other doctors for reassurance about their disease.10,18 In some instances, seeking a second opinion is beneficial for cancer patients. Reassurance from another physician could increase a patient’s confidence in the treatment. Furthermore, there may be differences in testing methods, medications, therapeutic techniques, and medical teams in different hospitals. During the process of seeking a second opinion, patients can choose a medical technology that is newer, more effective, or more suitable for them.10 Because of patient psychological factors and the development of therapeutic technologies, perhaps second opinions should be advised for cancer patients.

Although seeking a second opinion is increasingly common for cancer patients, little is known about the relationship between seeking a second opinion and the outcomes of medical care. Therefore, we investigated whether cancer patients who sought second opinions received better medical care. Through the process of hospital or surgeon selection, we assumed that patients had more chances to choose a better medical team with better therapeutic skills. Therefore, we inferred that seeking a second opinion could be helpful in getting better care. Using colorectal resection patients as an example, the aim of this study was to determine the relationship between seeking a second opinion and therapeutic outcome.

METHODS

Study data came from Taiwan’s National Health Insurance Research Database (NHIRD), which was provided by the Bureau of National Health Insurance in Taiwan for research purposes. The National Health Insurance program in Taiwan contains data on more than 99% of the entire population of 23.74 million people. The NHIRD is a national and representative database that contains comprehensive claim records of outpatient, inpatient, and emergency care. These data were cross-checked and validated to ensure accuracy.26,27 We used the database for a sampled cohort of 1 million people from 2004 to 2008. We also used admission files from the population-based inpatient expenditures database from 2004 to 2005.

From the hospitalization claims data of 1 million randomly chosen patients in NHIRD from July 2004 to November 2008, we identified patients who were newly diagnosed with colorectal cancer as a primary or secondary diagnosis 6 months before surgery (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes 153.XX or 154.XX). We excluded patients with anal tumors (ICD-9-CM code 154.2) because surgical resection is not usually considered first-line treatment for this disease. For patients who underwent multiple surgical resections, data from only the first operation were analyzed.

We used doctor shopping and hospital shopping in the 6 months before surgery as second opinion—seeking behaviors. The number of physicians or hospitals that patients consulted about their colorectal cancer was calculated after the operating physician or hospital was excluded. Patients who shopped for 0, 1, and 2 or more physicians were classified as non–doctor shoppers, light doctor shoppers, and heavy doctor shoppers, respectively. Hospital shoppers were classified using the same criteria. Sex, age, Charlson Comorbidity Index (CCI) score, urbanization level, site of the tumor, use of preoperative screening colonoscopy, and use of preoperative chemotherapy were controlled for in the analyses. The urbanization level, which was developed by the Taiwan National Health Research Institute, was stratified into 7 classifications ( I, II, III, IV, and >V)and ranged from greater to lower degrees of urbanization in the analyses.28 Hospital characteristics obtained from the population-based inpatient expenditures database included in the analysis were accreditation level (academic medical center, regional, district), ownership (public, private), and average annual hospital volume for colorectal cancer surgery in 2004 and 2005.

Based on the study objective and the limitations of secondary data, we used in-hospital complications and prolonged hospitalization as the indicators of surgical outcome. Mortality has been used to measure the quality of operations, and many studies have used mortality as a quality indicator following colorectal resection.29-33 The low number of deaths during a short surgical period, however, may result in a poor level of statistical confidence. Zheng and colleagues34 suggested overcoming this problem by improving the selection of indicators, extending the study period, or enlarging the sample size. Therefore, we used in-hospital complications and prolonged hospitalization, which are intermediate clinical indicators, as the outcome measures. In-hospital complications were defined as infections and cardiovascular, respiratory, gastrointestinal, urologic, or other complications.35-37 Patients who developed any of these conditions were classified as having in-hospital complications. To avoid overestimating the incidence of complications, patients presenting with comorbidities 1 month before surgery were excluded. Not all complications are the result of bad care or lower technical skills, and the correlation between comorbidities and complications has been observed in colorectal cancer patients.38 Therefore, prognostic factors, including patient characteristics and comorbid conditions, were controlled for in our analysis to reduce estimation bias. Furthermore, prolonged hospitalization was defined as a length of stay of more than 14 days.

The x2 test (or Fisher exact test, as appropriate) was used to explore the relationship between seeking a second opinion and outcomes of surgical care. In addition, data in the present study had a hierarchical structure, with patients nested within physicians and physicians nested within hospitals because the clustering effect and the dependence of observations within groups made the traditional regression model unsuitable. Considering the same size and that the dependent variables were binary outcomes, the 2-level hierarchical generalized linear model was applied (level 1 was the patient level; level 2 was the hospital level). The analyses were performed using the SPSS 17.0 (SPSS Inc, Chicago, Illinois) and HLM 6.02 (Scientific Software International, Inc, Skokie, IL) software packages. Significance was defined as a 2-sided P value of <.05.

Along with the hierarchical linear model, a null model with no predictor variables at any level was first used to verify suitability. A null model can measure the magnitude of variation in an outcome measure across the different levels. The proportion of the variance across different levels can be expressed as an inter-class correlation coefficient (ICC). For the 2-level dichotomous outcome model, the ICC between level 2 and the total variation was represented as σ2/(σ2 + π2/3).39After confirming the existence of significant variances among groups, further mean-as-outcomes models were applied to predict the intercept in level 1.

RESULTS

Table 1

The study subjects included 1358 patients from 77 hospitals.Patient characteristics and surgical outcomes are shown in . There were 767 (56.5%), 434 (32.0%), and 157 (11.6%) non—doctor shoppers, light doctor shoppers, and heavy doctor shoppers, respectively. The non–hospital shoppers, light hospital shoppers, and heavy hospital shoppers totalled 978 (72.0%), 334 (24.6%), and 46 (3.4%), respectively. There were 77 hospitals where patients underwent surgery. Among hospitals, 24.7%, 61.0%, and 14.3% were academic medical centers, regional hospitals, and district hospitals, respectively. There were 22 (28.6%) public hospitals and 55 (71.4%) private hospitals. The mean annual hospital volume for colorectal surgery was 99.3 (±128.8) patients. Complications during hospitalization occurred in 255 (18.8%) of patients, and prolonged hospitalization occurred in 631 (47.3%) of the 1333 patients who survived at least 14 days after resection.

Table 2

shows the relationships between seeking a second opinion and surgical outcomes. The incidence of in-hospital complications was 19.6%, 17.1%, and 19.7% for non—doctor shoppers, light doctor shoppers, and heavy doctor shoppers,respectively. The incidence of prolonged hospitalization was 48.8%, 46.7%, and 41.9% for non–doctor shoppers, light doctor shoppers, and heavy doctor shoppers, respectively. The frequency of doctor shopping was not significantly associated with surgical outcomes after a bivariate analysis. The incidence of in-hospital complications was 19.3%, 18.6%, and 8.2% for non–hospital shoppers, light hospital shoppers, and heavy hospital shoppers, respectively. Heavy shoppers had the lowest incidence of in-hospital complications, but this difference was not statistically significant. The incidence of prolonged hospitalization was 49.3%, 42.4%, and 41.3% for non–hospital shoppers, light hospital shoppers, and heavy hospital shoppers, respectively. Non–hospital shoppers had the highest incidence of prolonged hospitalization, but this difference was not statistically significant.

The results of the null models of hierarchical linear models demonstrated a significant variation in surgical outcomes among hospitals. The ICC of patients with the same hospital was 5.27% [0.114/(0.183 + 3.289); P = .003] for in-hospital complications, and the ICC of patients with the same hospital was 19.37% [0.790/(0.790 + 3.289); P <.001] for prolonged hospitalization. The variance in the null model was significant in level 2, suggesting that there were significant differences in the incidence of in-hospital complications and prolonged hospitalization among patients of different hospitals.This result indicates that it is suitable to use a generalized hierarchical linear model and further mean-as-outcomesmodels. In further models, patient-level predictors were included in level 1, resulting in this equation:

log (Pij/1 — Pij ) = π0j + π1j(sex)ij +

π2j(age)ij + π3j(CCI)ij + π4j(urbanization levels I)ij + π5j(urbanization levels II)ij + π6j(urbanization levels III)ij + π7j(urbanization levels IV)ij + π8j(site of tumor)ij + π9j(chemotherapy)ij + π10j(colonoscopy)ij + π11j(light doctor shopping)ij + π12j(heavy doctor shopping)ij + π13j(light hospital shopping)ij + π14j(heavy hospital shopping)ij. Further, hospital predictors are included in level 2, resulting in equations of π0j = β00 + β01(academic medical center) j + β02(regional hospital)j + β03(public hospital)j + β04(hospital volume)j + e0j. Age, CCI, and hospital volume were continuous variables. Therefore, we entered them in the model by subtracting them from the grand mean.

Table 3

shows the results of mean-as-outcomes models of hierarchical generalized linear models. The initial incidence of in-hospital complications was 21.32% (0.271/[1 + 0.271]). The risk of in-hospital complications was significantly higher for men than for women (odds ratio [OR] = 1.333; P = .003). The risk also increased significantly in older patients (OR = 1.023; P <.001) and those with higher CCI scores (OR =1.076; P = .004), and the risk of in-hospital complications was significantly lower for those who received the preoperative screening colonoscopy (OR = 0.648; P = .006). After adjusting for other characteristics, heavy doctor shoppers were at a higher risk of in-hospital complications than non—doctor shoppers (OR = 1.675; P =.037). Conversely, heavy hospital shoppers had a lower risk of in-hospital complications than non—hospital shoppers (OR = 0.272; P = .007). The average incidence of prolonged hospitalization was estimated as 41.28% (0.703/[1 +0.703]) among hospitals. The risk of prolonged hospitalization also increased significantly in older patients (OR = 1.028; P <.001) and those with higher CCI scores (OR =1.059; P = .001). However, the frequencies of hospital shopping and doctor shopping were not significant predictors of prolonged hospitalization after adjusting for other characteristics.

DISCUSSION

We found that the factors that influenced the incidence of in-hospital complications for colorectal resection patients were sex, age, CCI score, the screening colonoscopy, doctor shopping frequency, and hospital shopping frequency. After controlling for patient and hospital characteristics, heavy doctor shoppers were at a higher risk of in-hospital complications than non—doctor shoppers. Conversely, heavy hospital shoppers had a lower risk of in-hospital complications than non–hospital shoppers. In addition, prolonged hospitalization was significantly influenced by age, CCI score, and whether a patient had the preoperative screening colonoscopy. Nevertheless, after controlling for patient and hospital characteristics, the frequencies of doctor shopping and hospital shopping were not significantly associated with prolonged hospitalization.

With regard to the risk of in-hospital complications, we found that heavy doctor shoppers were at a higher risk than non—doctor shoppers, which suggests that the quality of care was not enhanced for patients who were heavy doctor shoppers. Previous studies have demonstrated that a patient’s choice of a physician is influenced by the professional knowledge, skills, and attitude of the physician. Patients can obtain more accurate therapeutic information after seeking a second opinion, which leads to a higher level of satisfaction with their treatment.17,40 Our finding is not in accordance with the results of several previous studies, although no previous study has discussed the effect of doctor shopping on treatment outcomes in detail. This finding was not surprising, as it confirmed what previous researchers have discovered about the generally poor health status of frequent doctor shoppers.2 A possible reason for heavy doctor shoppers being at higher risk for in-hospital complications than non—doctor shoppers is that a longer delay from diagnosis to surgery negatively affects surgical outcomes. Some studies have indicated that longer delays for cancer surgery potentially influence prognosis.41,42 Therefore, we inferred that the behaviors of heavy doctor shoppers might increase the delay from diagnosis to surgery, which may result in worse surgical outcomes.

Another important finding in this study was that hospital shopping was significantly correlated with in-hospital complications. Heavy hospital shoppers had a lower risk of in-hospital complications than non—hospital shoppers. Previous studies have shown that hospital quality is 1 of the reasons why patients select a hospital for surgery. Patients choose a high-quality hospital based on a physician’s recommendation, hospital reputation, or quality reports.13,14,43 In the present study, the effect of heavy hospital shopping on the incidence of in-hospital complications was not in favor of heavy doctor shopping. There may be more variation in the quality of hospitals than in the quality of physicians. Developing medical technologies have made medical care more complex, and complicated patients need professional teamwork for successful treatment. Other than physician skills, the quality of care is also correlated with hospital equipment and the abilities of medical professionals.44 Cancer care requires the coordination of physicians, nurses, medical laboratory scientists, radiologists, and nutrition support staff, and several studies have reported that surgical outcomes are associated with professional staffing.45 In addition, quality-of-care problems that lead to surgical complications include problems with technical care during a surgical procedure, problems with medications administered, failure to provide preventive care, and failure to monitor a patient’s condition or medications.46,47 Preventing complications was associated not only with the skills of physicians and support staff, but also with the processes of care. The superior technique of medical professionals and superior management of a hospital can prevent and detect complications at an early stage. By receiving treatment in capable hospitals, patients can obtain better surgical care and higher-quality therapy.

In contrast, doctor shopping and hospital shopping conferred no significant effect on prolonged hospitalization, although they did significantly affect the risk of in-hospital complications. A possible explanation for this finding may be that prolonged hospitalization is both a medical indicator and a managerial indicator. In the present study, prolonged hospitalization, a measure for quality of care, conflicted somewhat with the pressures to decrease health utilization.48 Therefore, we suggest that other outcome measures (eg, recurrence, readmission rate) be considered to better examine quality of care.

There are several limitations in this study. First, we did not have information on cancer staging, which is an important factor that impacts surgical outcomes and is also an influential factor for patients seeking a second opinion. Nevertheless, the use of screening colonoscopy, which can effectively identify cancers in early stages, was controlled for in these analyses. Second, we used administrative data to determine the incidence of in-hospital complications. However, the accuracy of administrative data remains in doubt, as highlighted in previous studies.49 In the present study, the complication rate might be underestimated due to coding inaccuracies. Furthermore, all complications do not result from bad care. Although patient characteristics were controlled for in the present study, the use of complications as an intermediate outcome indicator is still limited. Conversely, using postoperative unplanned procedures as a complication marker may facilitate future outcome studies.50

CONCLUSIONS

This is the first study, to our knowledge, to test the effects of seeking a second opinion on surgical outcomes in cancer patients. We found that colorectal cancer patients can obtain a higher quality of surgical care by selecting a hospital for their operation. However, heavy doctor shopping may be unfavorable to the quality of surgical care. We inferred that hospital shopping may be beneficial for patient care. Therefore, we suggest that healthcare authorities increase patient access to information about the quality of cancer care in various hospitals. This information may help patients shorten the process of finding quality healthcare providers; at the same time, it may help reduce the waste of medical resources that result from the long process of seeking care.Author Affiliations: Long-term Care Insurance Preparatory Task Force (H-RC), Department of Health, Executive Yuen, Taiwan; Institute of HealthPolicy and Management (H-RC, M-CY, K-PC), National Taiwan University, Taipei, Taiwan.

Author Disclosures: The authors (H-RC, M-CY, K-PC) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Funding Source: None.

Authorship Information: Concept and design (H-RC, M-CY, K-PC); acquisition of data (H-RC); analysis and interpretation of data (H-RC, K-PC);drafting of the manuscript (H-RC, K-PC); critical revision of the manuscript for important intellectual content (K-PC); statistical analysis (H-RC, K-PC); provision of study materials or patients (H-RC); obtaining funding (H-RC);administrative, technical, or logistic support (M-CY,); and supervision (MCY, K-PC).

Address correspondence to: Kuo-Piao Chung, PhD, No 17, Xu-Zhou Road, Taipei, Taiwan 100, Taiwan. E-mail: kpchung@ntu.edu.tw.1. Harris KM. How do patients choose physicians? evidence from a national survey of enrollees in employment-related health plans. Health Serv Res. 2003;38(2):711-732.

2. Sato T, Takeichi M, Hara T, Koizumi S. Second opinion behaviour among Japanese primary care patients. Br J Gen Pract. 1999;49(444): 546-550.

3. Marquis MS, Davies AR, Ware JE Jr. Patient satisfaction and change in medical-care provider: a longitudinal study. Med Care. 1983;21(8): 821-829.

4. Hagihara A, Tarumi K, Odamaki M, Nobutomo K. A signal detection approach to patient-doctor communication and doctor-shopping behaviour among Japanese patients. J Eval Clin Pract. 2005;11(6): 556-567.

5. Wang MJ, Lin SP. Study on doctor shopping behavior: insight from patients with upper respiratory tract infection in Taiwan. Health Policy. 2010;94(1):61-67.

6. Rosenberg SN, Gorman SA, Snitzer S, Herbst EV, Lynne D. Patient reactions and physician-patient communication in a mandatory surgical second-opinion program. Med Care. 1989;27(5):466-477.

7. Links M, Aghmesheh M. Second opinions: agendas and ego. Acta Oncol. 2009;48(8):1210-1213.

8. Moumjid N, Gafni A, Bremond A, Carrere MO. Seeking a second opinion: do patients need a second opinion when practice guidelines exist? Health Policy. 2007;80(1):43-50.

9. Wieske L, Wijers D, Richard E, Vergouwen MD, Stam J. Second opinions and tertiary referrals in neurology: a prospective observational study. J Neurol. 2008;255(11):1743-1749.

10. Sikora K. Second opinions for patients with cancer. BMJ. 1995; 311(7014):1179-1180.

11. Chou LF, Chen TJ. Relationship of doctor shopping and polypharmacy: a nationwide study in Taiwan. Value Health. 2008;11(3):A39.

12. Sloane G, Tidwell P, Horsfield M. Identification of the decision maker for a patient’s hospital choice: who decides which hospital? J Hosp Mark. 1999;13(1):57-77.

13. Marang-van de Mheen PJ, Dijs-Elsinga J, Otten W, et al. The importance of experienced adverse outcomes on patients’ future choice of a hospital for surgery. Qual Saf Health Care. 2010;19(6):e16.

14. Losina E, Plerhoples T, Fossel AH, et al. Offering patients the opportunity to choose their hospital for total knee replacement: impact on satisfaction with the surgery. Arthritis Rheum. 2005;53(5):646-652.

15. Kasteler J, Kane RL, Olsen DM, Thetford C. Issues underlying prevalence of “doctor-shopping” behavior. J Health Soc Behav. 1976; 17(4):329-339.

16. Philip J, Gold M, Schwarz M, Komesaroff P. An exploration of the dynamics and influences upon second medical opinion consultations in cancer care. Asia Pac J Clin Oncol. 2011;7(1):41-46.

17. Schmittdiel J, Selby JV, Grumbach K, Quesenberry CP Jr. Choice of a personal physician and patient satisfaction in a health maintenance organization. JAMA. 1997;278(19):1596-1599.

18. Philip J, Gold M, Schwarz M, Komesaroff P. Second medical opinions: the views of oncology patients and their physicians. Support Care Cancer. 2010;18(9):1199-1205.

19. Sutherland LR, Verhoef MJ. Why do patients seek a second opinion or alternative medicine? J Clin Gastroenterol.1994;19(3):194-197.

20. Tattersall MH, Dear RF, Jansen J, et al. Second opinions in oncology: the experiences of patients attending the Sydney Cancer Centre. Med J Aust. 2009;191(4):209-212.

21. Hahm GK, Niemann TH, Lucas JG, Frankel WL. The value of second opinion in gastrointestinal and liver pathology. Arch Pathol Lab Med. 2001;125(6):736-739.

22. Schrader M, Weissbach L, Hartmann M, et al. Burden or relief: do second-opinion centers influence the quality of care delivered to patients with testicular germ cell cancer? Eur Urol. 2010;57(5):867-872.

23. Tam KF, Cheng DK, Ng TY, Ngan HY. The behaviors of seeking a second opinion from other health-care professionals and the utilization of complementary and alternative medicine in gynecologic cancer patients. Support Care Cancer. 2005;13(9):679-684.

24. Mellink WA, Dulmen AM, Wiggers T, Spreeuwenberg PM, Eggermont AM, Bensing JM. Cancer patients seeking a second surgical opinion: results of a study on motives, needs, and expectations. J Clin Oncol. 2003;21(8):1492-1497.

25. Hewitt M, Breen N, Devesa S. Cancer prevalence and survivorship issues: analyses of the 1992 National Health Interview Survey. J Natl Cancer Inst. 1999;91(17):1480-1486.

26. Wu JC, Chen YC, Liu L, et al. Increased risk of stroke after spinal cord injury: a nationwide 4-year follow-up cohort study. Neurology. 2012;78(14):1051-1057.

27. Lin CC, Lai MS, Syu CY, Chang SC, Tseng FY. Accuracy of diabetes diagnosis in health insurance claims data in Taiwan. J Formos Med Assoc. 2005;104(3):157-163.

28. Liu CY, Hung YT, Chuang YL, et al. Incorporating development stratification of Taiwan townships into sampling design of large scale health interview survey [in Chinese]. J Health Manage. 2006;4(1):1-22.

29. Chen YJ, Wu CY, Chen TJ, et al. The risk of cancer in patients with psoriasis: a population-based cohort study in Taiwan [published correctionappears in J Am Acad Dermatol. 2012;66(3):368]. J Am Acad Dermatol. 2011;65(1):84-91.

30. Dobie SA, Baldwin LM, Dominitz JA, Matthews B, Billingsley K, Barlow W. Completion of therapy by Medicare patients with stage III colon cancer. J Natl Cancer Inst. 2006;98(9):610-619.

31. Heriot AG, Tekkis PP, Smith JJ, et al. Prediction of postoperative mortality in elderly patients with colorectal cancer. Dis Colon Rectum. 2006;49(6):816-824.

32. Khan MR, Bari H, Raza SA. Early postoperative outcome after curative colorectal cancer surgery. Singapore Med J. 2011;52(3):195-200.

33. Stillwell AP, Buettner PG, Siu SK, Stitz RW, Stevenson AR, Ho YH. Predictors of postoperative mortality, morbidity, and long-term survival after palliative resection in patients with colorectal cancer. Dis Colon Rectum. 2011;54(5):535-544.

34. Zheng H, Zhang W, Ayanian JZ, Zaborski LB, Zaslavsky AM. Profiling hospitals by survival of patients with colorectal cancer. Health Serv Res. 2011;46(3):729-746.

35. Longo WE, Virgo KS, Johnson FE, et al. Outcome after proctectomy for rectal cancer in Department of Veterans Affairs Hospitals: a report from the National Surgical Quality Improvement Program. Ann Surg. 1998;228(1):64-70.

36. Zaheer S, Pemberton JH, Farouk R, Dozois RR, Wolff BG, Ilstrup D. Surgical treatment of adenocarcinoma of the rectum. Ann Surg. 1998; 227(6):800-811.

37. Lehnert T, Methner M, Pollok A, Schaible A, Hinz U, Herfarth C. Multivisceral resection for locally advanced primary colon and rectal cancer: an analysis of prognostic factors in 201 patients. Ann Surg. 2002; 235(2):217-225.

38. Ouellette JR, Small DG, Termuhlen PM. Evaluation of Charlson-Age Comorbidity Index as predictor of morbidity and mortality in patients with colorectal carcinoma. J Gastrointest Surg. 2004;8(8):1061-1067.

39. Snijders TRB, Bosker RJ. Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. 1st ed. London: Sage Publications Ltd; 1999.

40. Bornstein BH, Marcus D, Cassidy W. Choosing a doctor: an exploratory study of factors influencing patients’ choice of a primary care doctor. J Eval Clin Pract. 2000;6(3):255-262.

41. Richards MA, Westcombe AM, Love SB, Littlejohns P, Ramirez AJ. Influence of delay on survival in patients with breast cancer: a systematic review. Lancet. 1999;353(9159):1119-1126.

42. Oudhoff JP, Timmermans DR, Bijnen AB, van der Wal G. Waiting for elective general surgery: physical, psychological and social consequences. ANZ J Surg. 2004;74(5):361-367.

43. Dijs-Elsinga J, Otten W, Versluijs MM, et al. Choosing a hospital for surgery: the importance of information on quality of care. Med Decis Making. 2010;30(5):544-555.

44. Undre S, Koutantji M, Sevdalis N, et al. Multidisciplinary crisis simulations: the way forward for training surgical teams. World J Surg. 2007;31(9):1843-1853.

45. Yasunaga H, Hashimoto H, Horiguchi H, Miyata H, Matsuda S. Variation in cancer surgical outcomes associated with physician and nurse staffing: a retrospective observational study using the Japanese Diagnosis Procedure Combination Database. BMC Health Serv Res. 2012; 12:129.

46. Weingart SN, Iezzoni LI, Davis RB, et al. Use of administrative data to find substandard care: validation of the complications screening program. Med Care. 2000;38(8):796-806.

47. Pronovost PJ, Jenckes MW, Dorman T, et al. Organizational characteristics of intensive care units related to outcomes of abdominal aortic surgery. JAMA. 1999;281(14):1310-1317.

48. Nascimbeni R, Cadoni R, Di Fabio F, Casella C, Salerni B. Hospitalization after open colectomy: expectations and practice in general surgery. Surg Today. 2005;35(5):371-376.

49. Cheng CL, Kao YH, Lin SJ, Lee CH, Lai ML. Validation of the National Health Insurance Research Database with ischemic stroke cases in Taiwan. Pharmacoepidemiol Drug Saf. 2011;20(3):236-242.

50. Morris AM, Baldivin LM, Matthews B, et al. Reoperation as a quality indicator in colorectal surgery: a population-based analysis. Ann Surg. 2007;245(1):73-79.