Skip to main content
PMC home page
Journal of Oncology Practice logoLink to Journal of Oncology Practice
. 2015 Oct 13;12(2):155–156. doi: 10.1200/JOP.2015.004200

ReCAP: Impact of Multidisciplinary Care on Processes of Cancer Care: A Multi-Institutional Study

Eberechukwu Onukwugha 1,✉, Nicholas J Petrelli 1, Kathleen M Castro 1, James F Gardner 1, Jinani Jayasekera 1, Olga Goloubeva 1, Ming T Tan 1, Erica J McNamara 1, Howard A Zaren 1, Thomas Asfeldt 1, James D Bearden III 1, Andrew L Salner 1, Mark J Krasna 1, Irene Prabhu Das 1, Steve B Clauser 1
PMCID: PMC4960465  PMID: 26464497

Abstract

QUESTION ASKED:

What is the relationship between the level of implementation of multidisciplinary care (MDC) and various processes of cancer care (eg, time to treatment receipt, evaluation for enrollment onto a clinical trial) among community cancer centers serving patients diagnosed with colon, rectal, or lung cancer? There is limited generalizable evidence on this topic. It is important to answer this question using data that can generalize across cancer patients, the majority of whom receive treatment in a community cancer center.

SUMMARY ANSWER:

Focusing on the time to receipt of cancer-directed treatment as one key process of cancer care in this patient population, we found that the answer to our question depended on the MDC assessment area and tumor site (Table 1). Among patients with colon cancer, higher MDC levels of physician engagement (ie, a higher level of physician engagement at the institutional level) were associated with a shorter time to treatment receipt, whereas higher MDC levels of case planning were associated with a longer time to treatment receipt. Among patients with rectal cancer, higher MDC levels of physician engagement were associated with a shorter time to cancer-directed treatment receipt, whereas higher MDC levels of evaluation for enrollment onto clinical trials were associated with a longer time to treatment receipt. Among patients with lung cancer, there was no association between the MDC areas of assessment and the time to cancer-directed treatment receipt.

Table 1.

Multivariable Analyses of the Associations Between MDC Implementation and Time to Cancer-Directed Treatment Receipt

Variable Lung (n = 560)* Colon (n = 378)* Rectal (n = 141)*
HR 95% CI HR 95% CI HR 95% CI
Case planning
    Low Reference Reference Reference
 High 0.78 0.47 1.28 0.65† 0.49 0.85 1.26 0.66 2.42
Physician engagement
    Low Reference Reference Reference
    Moderate 0.87 0.48 1.58 1.50‡ 1.19 1.89 2.61† 1.06 6.44
    High 0.98 0.46 2.10 2.66‡ 1.70 4.17 4.87† 1.41 16.78
Care coordination
    Low Reference Reference Reference
    Moderate 0.78 0.55 1.11 0.67 0.37 1.23 1.26 0.75 2.12
    High 0.64 0.24 1.69 0.55 0.27 1.10 0.36 0.11 1.15
Clinical trial
    Low Reference Reference Reference
    High 0.88 0.57 1.36 1.48 0.84 2.58 0.54* 0.31 0.95
Open in a new tab

NOTE. Hazard ratios were adjusted for patient clinical and demographic measures: age, race, ethnicity, diagnosis year, gender, and cancer center geographic classification (rural/urban). The final specification of each multivariate regression model varied with the disease site and outcome measure due to differences in sample sizes and in the performance of the statistical models (eg, model fit, convergence).

Abbreviations: HR, hazard ratio (covariate adjusted); MDC, multidisciplinary care.

*

Controlling for age, year of diagnosis, gender, cancer center location and race.

†

P < .05.

‡

P< .001.

METHODS:

We collected data for patients receiving care at 14 National Cancer Institute (NCI) community cancer centers. We characterized the NCI community cancer centers according to their level of MDC implementation across seven MDC assessment areas and over time. Using statistical regression models, we investigated the relationship between the level of MDC implementation and various process measures, including time to treatment receipt, clinical trial evaluation, receipt of multimodality treatment, and adherence to treatment guidelines published by the National Comprehensive Cancer Network.

BIAS, CONFOUNDING FACTOR(S), DRAWBACKS:

In the absence of a validated MDC assessment tool, the NCI community cancer centers used a nonvalidated tool. Additional institutional-level data would have been useful for characterizing norms and practices that may have differed across cancer centers and potentially explained variation in care processes. Although we controlled for patient demographic characteristics, baseline data were not available to document patient comorbidity or performance status level. To the extent that cancer centers at higher levels of MDC implementation may have been more likely to treat clinically complex patients, the inability to control for potential confounding bias caused by patient case mix may have influenced the study results.

REAL-LIFE IMPLICATIONS:

MDC models are important decision-making forums in current oncology practice. They involve oncologists in generating a comprehensive and coordinated plan of care for patients. Although MDC is purported to offer benefits to patients, there is limited generalizable evidence regarding the benefit to individuals receiving care at community cancer centers in the United States. Across various care processes that are important for characterizing cancer care, this study’s results indicate that changes in the level of MDC implementation could differentially affect the process of care, depending on the MDC area of assessment and the cancer site. In addition, the study results can be used to generate hypotheses for future studies among individuals diagnosed with colon, rectal, or lung cancer.

Footnotes

This work was completed while S.B.C. was employed at the National Cancer Institute and does not reflect the policy or position of the Patient Centered Outcomes Research Institute.

J Oncol Pract. 2015 Oct 13;12(2):157–168. doi: 10.1200/JOP.2015.004200

Original Contribution: Impact of Multidisciplinary Care on Processes of Cancer Care: A Multi-Institutional Study

Eberechukwu Onukwugha 1,✉, Nicholas J Petrelli 1, Kathleen M Castro 1, James F Gardner 1, Jinani Jayasekera 1, Olga Goloubeva 1, Ming T Tan 1, Erica J McNamara 1, Howard A Zaren 1, Thomas Asfeldt 1, James D Bearden III 1, Andrew L Salner 1, Mark J Krasna 1, Irene Prabhu Das 1, Steve B Clauser 1

MDC implementation level was associated with processes of care, and direction of association varied across MDC assessment areas.

Abstract

Purpose:

The role of multidisciplinary care (MDC) on cancer care processes is not fully understood. We investigated the impact of MDC on the processes of care at cancer centers within the National Cancer Institute Community Cancer Centers Program (NCCCP).

Methods:

The study used data from patients diagnosed with stage IIB to III rectal cancer, stage III colon cancer, and stage III non–small-cell lung cancer at 14 NCCCP cancer centers from 2007 to 2012. We used an MDC development assessment tool—with levels ranging from evolving MDC (low) to achieving excellence (high)—to measure the level of MDC implementation in seven MDC areas, such as case planning and physician engagement. Descriptive statistics and cluster-adjusted regression models quantified the association between MDC implementation and processes of care, including time from diagnosis to treatment receipt.

Results:

A total of 1,079 patients were examined. Compared with patients with colon cancer treated at cancer centers reporting low MDC scores, time to treatment receipt was shorter for patients with colon cancer treated at cancer centers reporting high or moderate MDC scores for physician engagement (hazard ratio [HR] for high physician engagement, 2.66; 95% CI, 1.70 to 4.17; HR for moderate physician engagement, 1.50; 95% CI, 1.19 to 1.89) and longer for patients with colon cancer treated at cancer centers reporting high 2MDC scores for case planning (HR, 0.65; 95% CI, 0.49 to 0.85). Results for patients with rectal cancer were qualitatively similar, and there was no statistically significant difference among patients with lung cancer.

Conclusion:

MDC implementation level was associated with processes of care, and direction of association varied across MDC assessment areas.

INTRODUCTION

Multidisciplinary care (MDC) is an integrated team approach in which health care professionals consider all relevant treatment options and collaboratively develop individual treatment plans for patients.1 The UK Department of Health defines the MDC team as a “group of people of different health-care disciplines which meets together at a given time to discuss a given patient and who are each able to contribute independently to the diagnostic and treatment decisions about the patient.”2 MDC models are important decision-making forums in oncology to prospectively generate comprehensive and coordinated plans of care for patients.3 MDC is purported to offer benefits for patients and providers.4,5 Studies have quantified the impact of MDC on processes of care as well as patient, provider, and system outcomes.1,5-16 Available evidence indicates that there are measurable advantages to coordinating care through multidisciplinary conferences.1,7,11,17-19 One study documented an increase in the percentage of patients receiving complete staging and increased likelihood of adherence to clinical care guidelines, concurrent with a smaller interval from diagnosis to treatment among patients with esophageal cancer.11 Another study reported significantly shorter delay to initiation of definitive therapy and longer overall and progression-free survival in thoracic oncology.6 Conversely, another study found little association with health services use, quality, or outcomes among patients with lung cancer.20

Prior studies have used various definitions of MDC and have mostly focused on single institutions or specific practice settings.16,20 The lack of a uniform definition for MDC has limited the ability to compare relationships between MDC and processes of care, including guideline adherence, treatment receipt, and clinical trial enrollment, across multiple institutions and for different disease sites.4 There exists a knowledge gap with respect to generalizable evidence regarding the effect of MDC on processes of care across different cancer types.4,17

This multilevel descriptive study was designed by investigators in the National Cancer Institute Community Cancer Centers Program (NCCCP) in collaboration with colleagues at the University of Maryland Baltimore to investigate processes of multidisciplinary care with an eye toward addressing the gaps in evidence. The National Cancer Institute launched the NCCCP in 2007, with 16 geographically dispersed community hospital–based cancer centers working to improve the quality of cancer care, increase patient participation in clinical trials, and reduce cancer disparities.21 The NCCCP defined a model of prospective MDC and developed a self-assessment tool22 to measure and guide MDC program development. We investigated the relationship between MDC program maturity level at the organizational level (using site-reported data from MDC self-assessment tool) and processes of care for patients with colon, rectal, or lung cancer at NCCCP institutions.18

We hypothesized that treatment receipt in cancer centers reporting higher MDC levels would be associated with improved processes of care, as reflected by: (1) shorter time to initial therapy receipt, (2) increased likelihood of multimodality therapy receipt, (3) increased likelihood of clinical trial enrollment evaluation, and (4) increased likelihood of adherence to National Comprehensive Cancer Network (NCCN) treatment guidelines. A secondary aim of the study was to demonstrate feasibility of collecting patient and institutional data from various community cancer centers for use in testing hypotheses related to MDC implementation.

METHODS

Study Design and Population

The study was designed using retrospective and prospective data collected from the centers on patients diagnosed with cancer between July 2007 and December 2012. The study included patients with stage III non–small-cell lung cancer (NSCLC), stage III colon cancer, or stage IIB to III rectal cancer if they met the following criteria: (1) age ≥ 18 years at time of diagnosis, (2) English speaking (native or non-native), (3) first or only cancer diagnosis, and (4) all of first course of treatment received at the reporting NCCCP cancer center.

Data Collection

The following sources were used to collect cancer center–level and patient-level data: (1) the NCCCP-developed MDC selfassessment tool, (2) the Rapid Quality Reporting System (RQRS) and, (3) a study-specific data collection spreadsheet.

Cancer Center–Level Data

Each cancer center retrospectively provided annual data from 2007 to 2012 that quantified their extent of MDC implementation based on the self-assessed levels using the NCCCP tool (Table 1). The NCCCP cancer centers developed the tool, which is described in depth by Swanson et al.22 The nonvalidated tool was created to help the cancer centers assess MDC programs over time. Cancer center staff used various sources of information to assess MDC implementation, including patient medical records, internal reports, and personal communication with individuals knowledgeable about the operations of the cancer centers. We used the reported assessment levels—with a scale ranging from 1 (evolving MDC [low]) to 5 (achieving excellence [high])—to measure MDC implementation in seven MDC areas, such as case planning and physician engagement. The levels were grouped into dichotomous (low or high) and trichotomous (low, moderate, or high) variables based on guidance from coauthors knowledgeable about the origins of the MDC tool. The low group represented the referent category in all assessment areas.

Table 1.

MDC Assessment Areas and Levels of Implementation

Assessment Area Level of MDC Implemented
Evolving MDC (1) Developing MDC (2) MDC (3) Moving Toward Excellence (4) Achieving Excellence (5)
Case planning Care planning is asynchronous, with patient presenting to multiple physician offices without shared medical record; 100% of patient cases reviewed retrospectively Care planning is asynchronous, with patient presenting to multiple physician offices with shared medical record Most care planning is asynchronous, but some patient care plans are discussed in multidisciplinary conferences occurring weekly All patient care planning is done through multidisciplinary conference occurring ≥ weekly; 100% of patient cases reviewed prospectively All patient care planning is done through multidisciplinary conference occurring while patient encounters care; 100% of patient cases reviewed prospectively
Open in a new tab

Abbreviations: EMR, electronic medical record; MDC, multidisciplinary care; NA, not applicable.

*

Collected patient-level data indicating whether case planning was conducted with or without patient present.

Patient-Level Data

Demographic and clinical characteristics, including NCCN guideline compliance for patient cases of colon or rectal cancer, were extracted from the RQRS, a reporting and quality improvement system developed by the Commission on Cancer of the American College of Surgeons.23 Patient-level data for patients with lung cancer were not available in the RQRS, and the research team collaborated with the American College of Surgeons to establish a mechanism within the National Cancer Data Base whereby patient-level demographic and clinical data for these patient cases were provided to the research team.

The cancer centers provided additional patient-level data that were unavailable in the RQRS via a data collection spreadsheet. The spreadsheet included NCCN guideline adherence and multimodality therapy receipt data for patients with stage III NSCLC and clinical trial evaluation and enrollment status for all three disease sites. The NCCCP cancer centers completed the spreadsheet monthly to reflect newly diagnosed patient cases and updates for existing patient cases. The research team provided cancer center staff with a standard operating procedures manual to ensure uniform definitions of NCCN guideline adherence for patients with stage III NSCLC.

We merged cancer center–level MDC data with the patient-level data based on the patient's year of diagnosis and the cancer center at which the patient was diagnosed. Patients were categorized based on MDC score in the diagnosis year. For example, if cancer center X had a score of 3 in 2011 and 5 in 2012 for case planning, patients diagnosed at cancer center X in year 2011 would be assigned a score of 3 for case planning, and those diagnosed in 2012 would be assigned a score of 5. The research study was approved by institutional review boards at the National Cancer Institute, the University of Maryland Baltimore, and participating NCCCP cancer centers.

Data Analysis

Descriptive, bivariable, and multivariable data analyses were conducted for each disease site separately. The relationship between MDC implementation and processes of care varied across separate dimensions of the MDC assessment tool, and thus, relationships were considered separately for each MDC assessment area. Unadjusted associations between each of the organizational-level variables (ie, MDC areas of assessment) and process outcomes (eg, clinical trial evaluation) were explored (Data Supplement). Multivariate models were used to examine the adjusted relationship between the reported MDC level and patients' care process, controlling for age, race (eg, white), ethnicity (ie, Hispanic), diagnosis year, sex, and cancer center geographic classification (urban v rural). Parameters in regression models of binary responses were estimated, adjusting for clustering at the level of the NCCCP cancer center, using generalized estimating equations with a logit link function and exchangeable correlation structure. Marginal Cox regression models for clustered data were used for modeling time-to-event outcomes.24 Parameter estimates for four assessment areas (case planning, physician engagement, clinical trials, and care coordination) are listed in Table 2. Results for the three remaining assessment areas (financial, medical records, and infrastructure) were not clinically meaningful (data not shown). We performed analyses using SAS software (version 9.2; SAS Institute, Cary, NC) and STATA software (version 10.0; STATA, College Station, TX).

Table 2.

Multivariate Analyses of Associations Between MDC Implementation and Processes of Care for Patients With Lung, Colon, or Rectal Cancer

Variable Lung Cancer (n = 560) Colon Cancer (n = 378) Rectal (n = 141)
Adjusted OR* 95% CI Adjusted OR* 95% CI Adjusted OR*† 95% CI
Case planning
 Clinical trial evaluation
  Low Referent Referent Referent
  High 1.25 0.71 to 2.20 1.10 0.52 to 2.34 0.41 0.01 to 12.23
 NCCN guideline adherence
  Low Referent NA‡ Referent
  High 2.21 0.88 to 5.57 0.31 0.05 to 1.99
 Multimodality treatment
  Low Referent NA§ NA§
  High 1.67 0.90 to 3.09
 Time to treatment receipt, HR
  Low Referent Referent Referent
  High 0.78 0.47 to 1.28 0.65‖ 0.49 to 0.85 1.26 0.66 to 2.42
Physician engagement
 Clinical trial evaluation
  Low Referent Referent Referent
  Moderate 0.61 0.23 to 1.59 1.00 0.22 to 4.48
  High 2.24 0.37 to 13.68 2.09 0.16 to 27.22
 NCCN guideline adherence
  Low Referent NA‡ Referent
  Moderate 0.61 0.23 to 1.61
  High 1.51 0.50 to 4.55
 Multimodality treatment
  Low Referent NA§ NA§
  Moderate 0.41 0.15 to 1.08
  High 1.15 0.41 to 3.21
 Time to treatment receipt, HR
  Low Referent Referent Referent
  Moderate 0.87 0.48 to 1.58 1.50# 1.19 to 1.89 2.61# 1.06 to 6.44
  High 0.98 0.46 to 2.10 2.66# 1.70 to 4.17 4.87# 1.41 to 16.78
Care coordination
 Clinical trial evaluation
  Low Referent Referent Referent
  Moderate 1.27 0.65 to 2.48 0.67 0.19 to 2.39 0.71 0.44 to 1.14
  High 0.17 0.00 to 6.27 0.68 0.09 to 5.24 1.20 0.07 to 19.28
 NCCN guideline adherence
  Low Referent NA‡ Referent
  Moderate 1.23 0.41 to 3.66 2.40 0.45 to 12.79
  High 6.28‖ 1.47 to 26.90 2.68 0.30 to 24.21
 Multimodality treatment
  Low Referent NA§ NA§
  Moderate 1.91 0.82 to 4.50
  High 10.94‖ 1.68 to 71.42
 Time to treatment receipt, HR
  Low Referent Referent Referent
  Moderate 0.78 0.55 to 1.11 0.67 0.37 to 1.23 1.26 0.75 to 2.12
  High 0.64 0.24 to 1.69 0.55 0.27 to 1.10 0.36 0.11 to 1.15
Clinical trials
 Clinical trial evaluation
  Low Referent Referent Referent
  High 0.79 0.24 to 2.59 0.90 0.37 to 2.21 0.86 0.13 to 5.62
 NCCN guideline adherence
  Low Referent NA‡ Referent
  High 1.07 0.30 to 3.74 0.52 0.08 to 3.24
 Multimodality treatment
  Low Referent NA§ NA§
  High 0.94 0.32 to 2.72
 Time to treatment receipt, HR
  Low Referent Referent Referent
  High 0.88 0.57 to 1.36 1.48 0.84 to 2.58 0.54‖ 0.31 to 0.95
Open in a new tab

NOTE. ORs were adjusted for patient clinical and demographic measures: age, race, ethnicity, diagnosis year, sex, and cancer center geographic classification (rural v urban). Final specification of each multivariate regression model varied with disease site and outcome measure because of differences in sample sizes and in performance of statistical models (eg, model fit, convergence).

Abbreviations: HR, hazard ratio; MDC, multidisciplinary care; NA, not applicable; NCCN, National Comprehensive Cancer Network; OR, odds ratio.

*

Controlling for age, year of diagnosis, sex, cancer center location, and race.

†

Controlling for following variables in clinical trial evaluation and NCCN guideline adherence models: age, year of diagnosis, and sex.

‡

NCCN guideline–adherent treatment was administered to 98% of patients with colon cancer.

§

Measure was not collected for patients with colon or rectal cancer.

‖

P < .05.

Physician engagement MDC assessment area was excluded from final model for patients with rectal cancer because of lack of convergence.

#

P < .001.

RESULTS

Application of the study inclusion and exclusion criteria resulted in 1,079 patients from 14 of 16 available NCCCP institutions. One NCCCP institution contributed a small sample of patients and was excluded. Another NCCCP institution did not feel that the MDC tool was appropriate for describing its cancer program and was excluded. On average, the included NCCCP cancer centers reported 1,612 (minimum, n = 486; maximum, n = 3,133) new patient cases of cancer annually. Among treating physicians at the cancer centers, 40% were in private practice, and 60% were either employed by the health system or operating under contract. Study results are provided separately for patients diagnosed with lung, colon, or rectal cancer. The final specification of each multivariate regression model varied with disease site and outcome measure because of differences in sample size and in performance of the statistical models (eg, model fit, convergence).

Lung Cancer

A total of 560 patients with stage III NSCLC were analyzed; 48% were women, 15% were African American, and 12% received treatment at cancer centers located in rural settings. Median age of patients in the sample was 67 years (range, 38 to 90 years). Overall, 48% of patients were evaluated for clinical trial enrollment, 68% received NCCN-adherent treatment, and 61% received multimodality therapy. Median time to treatment from date of diagnosis was 33 days (95% CI, 29 to 35 days). A majority of patients with lung cancer were treated in cancer centers reporting high MDC levels (ie, level 4 or 5) for case planning (66% of patients), coordination of care (72% of patients), and clinical trials (84% of patients; Table 3). Multivariate results are listed in Table 2 (detailed results are provided in Data Supplement). The likelihood of receiving guideline-adherent treatment was higher among patients treated in cancer centers reporting high MDC levels for care coordination compared with those receiving care in cancer centers reporting low MDC levels for care coordination (odds ratio [OR], 6.28; 95% CI, 1.47 to 26.90; P = .01). The odds of receiving multimodality therapy were higher among patients treated at cancer centers reporting high MDC levels based on care coordination compared with the referent patient group (OR, 10.94; 95% CI, 1.68 to 71.42; P = .01).

Table 3.

Patient Demographic and Clinical Characteristics

Characteristic/Variable Lung Cancer (n = 560) Colon Cancer (n = 378) Rectal Cancer (n = 141)
No. % No. % No. %
Demographic/Clinical
Race/ethnicity
    White, non-Hispanic 457 81.6 285 75.4 114 80.9
    African American, non-Hispanic 86 15.4 55 14.6 17 12.1
    Hispanic 4 0.7 16 4.2 1 0.7
    Other 8 1.4 8 2.1 6 4.3
    Missing 5 0.9 14 3.7 3 2.1
Age, years
    18-55 101 18.0 119 31.5 64 45.4
    56-65 151 27.0 113 29.9 47 33.3
    ≥ 66 308 55.0 146 38.6 30 21.3
Sex
    Male 293 52.3 202 53.4 82 58.2
    Female 267 47.7 176 46.6 59 41.8
Cancer center location
    Urban 495 88.4 336 88.9 130 92.2
    Rural 65 11.6 42 11.1 11 7.8
Year of diagnosis
    2007-2008 194 34.6 125 33.1 44 31.2
    2009 134 23.9 109 28.8 55 39.0
    2010 128 22.9 80 21.2 26 18.4
    2011-2012 104 18.6 64 16.9 16 11.4
Processes of Cancer Care
Evaluated for clinical trial
    Yes 267 47.7 216 57.1 78 55.3
    No 293 52.3 162 42.9 63 44.7
Enrolled onto clinical trial (among those evaluated)
    Yes 97 17.3 86 22.8 33 23.4
    No 170 30.4 130 34.4 45 31.9
    Not evaluated 293 52.3 162 42.9 63 44.7
Adherence to NCCN treatment guidelines
    Yes 357 63.7 371 98.1 124 87.9
    No 117 20.9 7 1.9 17 12.1
    Missing 86 15.4 — — — —
Receipt of multimodality therapy
    Yes 341 60.9 NA NA NA NA
    No 219 39.1 NA NA NA NA
Death
    Dead 383 68.4 64 16.9 16 11.4
    Alive 177 31.6 314 83.1 125 88.7
MDC Assessment Areas and Levels of Implementation
Case planning
    Low 148 26.4 174 46.0 76 53.9
    High 367 65.5 147 38.9 55 39.0
    Missing 45 8.0 57 15.1 10 7.1
Physician engagement
    Low 159 28.4 154 40.7 72 51.1
    Moderate 365 65.2 193 51.1 56 39.7
    High 36 6.4 31 8.2 13 9.2
Coordination of care
    Low 75 13.4 64 16.9 28 19.9
    Moderate 82 14.6 147 38.9 55 39.0
    High 403 72.0 167 44.2 58 41.1
Infrastructure
    Low 134 23.9 176 46.6 79 56.0
    High 426 76.1 202 53.4 62 44.0
Financial
    Low 175 31.2 217 57.4 85 60.3
    High 385 68.8 161 42.6 56 39.7
Clinical trials
    Low 90 16.1 57 15.1 36 25.5
    High 470 83.9 321 84.9 105 74.5
Medical records
    Low 441 78.8 304 80.4 118 83.7
    High 119 21.2 74 19.6 23 16.3
Open in a new tab

Abbreviations: NA, not applicable; NCCN, National Comprehensive Cancer Network.

Colon Cancer

Among the 378 patients diagnosed with stage III colon cancer, 47% were women, 15% were African American, and 11% received treatment at cancer centers located in rural settings. Median age of patients in the sample was 61 years (range, 19 to 79 years). Overall, 57% were evaluated for clinical trial enrollment, and 98% received NCCN-adherent treatment (Table 3). Median time to treatment from date of diagnosis was 7 days (95% CI, 5 to 9 days). A large proportion of patients were treated in cancer centers reporting high MDC levels for care coordination (44% of patients) and clinical trials (85% of patients; Table 3). Multivariate analysis (Table 2) showed that time to treatment was shorter among patients treated in cancer centers reporting high or moderate MDC levels for physician engagement compared with patients treated in centers reporting low MDC levels for physician engagement (HR for high physician engagement, 2.66; 95% CI, 1.70 to 4.17; P < .01; HR for moderate physician engagement, 1.50; 95% CI, 1.19 to 1.89; P < .01). Time to treatment was longer among patients at cancer centers reporting high MDC levels for case planning compared with those reporting low levels of MDC for case planning (HR, 0.65; 95% CI, 0.49 to 0.85; P < .01). Detailed results from the multivariate analysis are provided in the Data Supplement.

Rectal Cancer

A total of 141 patients were diagnosed with stage IIB to III rectal cancer; 42% were women, 12% were African American, and 8% received treatment at a cancer center located in a rural setting. Median age of the sample was 57 years (range, 19 to 79 years). Overall, 55% were evaluated for clinical trial enrollment, and 88% received NCCN-adherent treatment (Table 3). Median time to treatment from date of diagnosis was 25 days (95% CI, 22 to 28 days). A large proportion of patients were treated in cancer centers reporting high MDC levels for care coordination (41% of patients) and clinical trials (75% of patients; Table 3). Multivariate analysis (Table 2) indicated that time to treatment was shorter among patients treated in cancer centers reporting high or moderate MDC levels for physician engagement compared with those reporting low MDC levels for physician engagement (HR for high physician engagement, 4.87; 95% CI, 1.41 to 16.78; P = .01; HR for moderate physician engagement, 2.61; 95% CI, 1.06 to 6.44; P = .04.) Conversely, time to treatment was longer among patients treated at cancer centers reporting high MDC levels for the clinical trial assessment area compared with those reporting low levels of MDC in this area (HR for clinical trials, 0.54; 95% CI, 0.31 to 0.95; P < .01). The physician engagement variable was excluded from the clinical trial and guideline adherence regression models because of a lack of model convergence. Detailed results from the multivariate analysis are provided in the Data Supplement.

DISCUSSION

Evidence that details the impact of prospective multidisciplinary treatment planning is important to health systems. Given that the management of stage IIB to III rectal cancer, stage III colon cancer, and stage III NSCLC is amenable to the use of multiple treatment modalities, we focused on these disease sites. Our study leverages the simultaneous adoption of a single approach to assessing MDC implementation across multiple cancer centers to investigate the association between MDC levels and processes of care. By employing a framework22 and analytic approach that defined an MDC program using distinct assessment areas, we identified differences across areas and disease sites. Several findings were consistent with our study hypotheses. Among patients with lung cancer, a higher MDC level for coordination of care was associated with increased likelihood of multimodality therapy and increased likelihood of guideline-adherent care. Patients with lung cancer treated at centers with high levels for case planning and physician engagement were more likely to be evaluated for clinical trial enrollment, supporting the premise that prospective MDC provides a venue for discussion of treatment standards and promotion of clinical trial awareness. Lung and rectal cancer treatment involves radiotherapy and chemotherapy coordination, whereas colon cancer involves either surgery alone or surgery followed by postoperative chemotherapy only, which would require less coordination. Multimodality treatment can be simultaneous or consecutive, palliative or with curative intent, and can involve multiple physicians over the course of months or years.10 As surgeons, medical and radiation oncologists, and other physicians and nonphysicians become involved in the care of patients receiving multimodality treatment, developing a treatment plan that encompasses the expertise of all these providers becomes complex. Among patients with colon or rectal cancer, a higher physician engagement MDC level was associated with a shorter time to treatment. These patients were treated at centers that reported high levels of clinical trial evaluation and either moderate or high levels of care coordination, which could explain system efficiency.

Our study contributes unique evidence for generating hypotheses regarding the role of MDC in processes of care among patients diagnosed with lung, colon, or rectal cancer. Currently, there is limited evidence in this area. Findings in the thoracic oncology setting indicate that MDC was associated with an increased likelihood of treatment receipt25 and that there is a limited role for MDC input with regard to improved clinical decision making.26 One study documented that deviation from recommendations provided by a thoracic MDC group could be associated with worse outcomes, such as a delay to onset of therapy and shorter overall and progression-free survival among patients with lung cancer.6 In the colon and rectal cancer setting, one study found that the established management plan for patients with complex cases of colon or rectal cancer changed after multidisciplinary team discussions.27

More generally, studies in the oncology setting have identified organizational-level characteristics of MDC28-30 and investigated health and process outcomes of care associated with MDC and performance improvements in multidisciplinary teams.17,31-33 Although the evidence has been mixed regarding the effectiveness of MDC, it is difficult to make comparisons across studies because of the lack of a standard definition of MDC, variation in the measurement of MDC performance, and differences in the outcomes assessed. There are challenges with attributing differences in patient outcomes to processes of MDC, given the nature of cancer treatment planning. Nonetheless, the implications of process improvements at the institutional level are important to understand, given that improvements in these characteristics are possible, as demonstrated by the improvements across NCCCP institutions over time. Future studies could explore alternate modeling approaches, including disaggregation of the levels of MDC scores or a systems approach investigating the role of MDC using synergistic areas of assessment that have been used in assessing the performance of multidisciplinary teams.29,34,35

Our study results are unique in highlighting the complexity that exists in terms of the relationship between MDC implementation and care processes across assessment areas and across disease sites. This complexity is underappreciated when a less nuanced MDC definition is employed, a single institution is involved in the study, or results are examined for a single disease site. Recognizing that the definition and implementation of MDC can vary across disease settings, geographic locations, and institutions,4,36 our study includes data from geographically diverse cancer centers and for three tumor types that are particularly amenable to multiple treatment modalities.

Our study is not without limitations. The NCCCP centers did not use a validated tool to measure their MDC programs; no validated tools were available to assess MDC at the time that the study was initiated. Additional institutional-level data would have been useful for characterizing norms and practices (eg, resources, infrastructure, institutional support, staff composition) that may have differed across cancer centers and potentially explained variation in care processes.37 There was no distinction between institutions that used multidisciplinary tumor conferences without the patient present and conferences attended by the patient. Although we controlled for patient demographic characteristics, baseline data were not available to document patient comorbidity or performance status. To the extent that cancer centers with higher levels of MDC implementation may have been more likely to treat patients with complex cases of cancer, the inability to control for potential confounding bias resulting from patient case mix may have influenced the study results.

Our study demonstrated the feasibility of collecting the requisite patient and clinical data in community cancer centers while providing preliminary evidence regarding the multifaceted relationship between MDC and processes of care. Additional information to characterize MDC programs, including staff composition, patient volume, patient involvement, and quality-of-care metrics for the institution, may be useful in future studies. Building on the current study, future research is needed to elucidate the relationship between MDC and health outcomes among individuals diagnosed with cancer and to develop metrics for evaluating and validating the MDC self-assessment tool.

Supplementary Material

Data Supplement
supp_12_2_155__index.html (2.5KB, html)

Acknowledgment

Supported by federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the US Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. We wish to recognize the tremendous effort put forth by the cancer registrars involved in this study. We are grateful to Jenny Starliper and Lily Jiang from Leidos Biomedical Research for their support of this study. We are grateful to the following National Cancer Institute Community Cancer Centers Program (NCCCP) cancer centers and their NCCCP principal investigators for their contributions to this effort: Ascension Health Columbia St Mary's, Billings Clinic, Catholic Health Initiatives cancer centers (Good Samaritan, Penrose–St Francis Health Services, St Elizabeth Regional Medical Center, St Francis Medical Center, and St Joseph Medical Center), Helen F. Graham Cancer Center at Christiana Care, Hartford Hospital, Our Lady of the Lake Regional Medical Center, Sanford University of South Dakota Medical Center, Spartanburg Regional Healthcare System, St Joseph Health, and St Joseph's/Candler.

AUTHOR CONTRIBUTIONS

Conception and design: Eberechukwu Onukwugha, Nicholas J. Petrelli, Kathleen M. Castro, Olga Goloubeva, Thomas Asfeldt, Andrew L. Salner, Mark J. Krasna, Steve B. Clauser

Provision of study materials or patients: Nicholas J. Petrelli, Howard A. Zaren, Thomas Asfeldt, James D. Bearden III, Andrew L. Salner, Mark J. Krasna

Collection and assembly of data: Eberechukwu Onukwugha, Nicholas J. Petrelli, Kathleen M. Castro, James F. Gardner, Jinani Jayasekera, Erica J. McNamara, Howard A. Zaren, Thomas Asfeldt, James D. Bearden III, Andrew L. Salner, Mark J. Krasna

Data analysis and interpretation: Eberechukwu Onukwugha, Nicholas J. Petrelli, Kathleen M. Castro, Jinani Jayasekera, Olga Goloubeva, Ming T. Tan, Andrew L. Salner, Mark J. Krasna, Irene Prabhu Das, Steve B. Clauser

Manuscript writing: All authors

Final approval of manuscript: All authors

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

Impact of Multidisciplinary Care on Processes of Cancer Care: A Multi-Institutional Study

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or jop.ascopubs.org/site/misc/ifc.xhtml.

Eberechukwu Onukwugha

Honoraria: IMS Health

Consulting or Advisory Role: AstraZeneca

Research Funding: Bayer Healthcare Pharmaceuticals

Nicholas J. Petrelli

No relationship to disclose

Kathleen M. Castro

No relationship to disclose

James Gardner

No relationship to disclose

Jinani Jayasekera

No relationship to disclose

Olga Goloubeva

No relationship to disclose

Ming T. Tan

No relationship to disclose

Erica J. McNamara

No relationship to disclose

Howard A. Zaren

Consulting or Advisory Role: bioTheranostics

Travel, Accommodations, Expenses: bioTheranostics

Thomas Asfeldt

No relationship to disclose

James D. Bearden III

No relationship to disclose

Andrew L. Salner

Consulting or Advisory Role: Best Doctors

Mark J. Krasna

Consulting or Advisory Role: Varian

Irene Prabhu Das

No relationship to disclose

Steve B. Clauser

No relationship to disclose

References

  • 1.Chirgwin J, Craike M, Gray C, et al. Does multidisciplinary care enhance the management of advanced breast cancer?: evaluation of advanced breast cancer multidisciplinary team meetings. J Oncol Pract. 2010;6:294–300. doi: 10.1200/JOP.2010.000017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.UK Department of Health. Manual for Cancer Services, 2004. http://webarchive.nationalarchives.gov.uk/
  • 3.Sidhom MA, Poulsen MG. Multidisciplinary care in oncology: Medicolegal implications of group decisions. Lancet Oncol. 2006;7:951–954. doi: 10.1016/S1470-2045(06)70942-1. [DOI] [PubMed] [Google Scholar]
  • 4.Hong NJ, Wright FC, Gagliardi AR, et al. Examining the potential relationship between multidisciplinary cancer care and patient survival: An international literature review. J Surg Oncol. 2010;102:125–134. doi: 10.1002/jso.21589. [DOI] [PubMed] [Google Scholar]
  • 5.Lamb BW, Green JS, Benn J, et al. Improving decision making in multidisciplinary tumor boards: Prospective longitudinal evaluation of a multicomponent intervention for 1,421 patients. J Am Coll Surg. 2013;217:412–420. doi: 10.1016/j.jamcollsurg.2013.04.035. [DOI] [PubMed] [Google Scholar]
  • 6.Osarogiagbon RU, Phelps G, McFarlane J, et al. Causes and consequences of deviation from multidisciplinary care in thoracic oncology. J Thorac Oncol. 2011;6:510–516. doi: 10.1097/JTO.0b013e31820b88a7. [DOI] [PubMed] [Google Scholar]
  • 7.Baldwin LM, Taplin SH, Friedman H, et al. Access to multidisciplinary cancer care: Is it linked to the use of breast-conserving surgery with radiation for early-stage breast carcinoma? Cancer. 2004;100:701–709. doi: 10.1002/cncr.20030. [DOI] [PubMed] [Google Scholar]
  • 8.Devitt B, Philip J, McLachlan SA. Team dynamics, decision making, and attitudes toward multidisciplinary cancer meetings: Health professionals' perspectives. J Oncol Pract. 2010;6:e17–e20. doi: 10.1200/JOP.2010.000023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Litton G, Kane D, Clay G, et al. Multidisciplinary cancer care with a patient and physician satisfaction focus. J Oncol Pract. 2010;6:e35–e37. doi: 10.1200/JOP.2010.000028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Freeman RK, Van Woerkom JM, Vyverberg A, et al. The effect of a multidisciplinary thoracic malignancy conference on the treatment of patients with lung cancer. Eur J Cardiothorac Surg. 2010;38:1–5. doi: 10.1016/j.ejcts.2010.01.051. [DOI] [PubMed] [Google Scholar]
  • 11.Freeman RK, Van Woerkom JM, Vyverberg A, et al. The effect of a multidisciplinary thoracic malignancy conference on the treatment of patients with esophageal cancer. Ann Thorac Surg. 2011;92:1239–1242. doi: 10.1016/j.athoracsur.2011.05.057. discussion 1243. [DOI] [PubMed] [Google Scholar]
  • 12.Petty JK, Vetto JT. Beyond doughnuts: Tumor board recommendations influence patient care. J Cancer Educ. 2002;17:97–100. doi: 10.1080/08858190209528807. [DOI] [PubMed] [Google Scholar]
  • 13.Kurpad R, Kim W, Rathmell WK, et al. A multidisciplinary approach to the management of urologic malignancies: Does it influence diagnostic and treatment decisions? Urol Oncol. 2011;29:378–382. doi: 10.1016/j.urolonc.2009.04.008. [DOI] [PubMed] [Google Scholar]
  • 14.Gomella LG, Lin J, Hoffman-Censits J, et al. Enhancing prostate cancer care through the multidisciplinary clinic approach: A 15-year experience. J Oncol Pract. 2010;6:e5–e10. doi: 10.1200/JOP.2010.000071. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Gardner TB, Barth RJ, Zaki BI, et al. Effect of initiating a multidisciplinary care clinic on access and time to treatment in patients with pancreatic adenocarcinoma. J Oncol Pract. 2010;6:288–292. doi: 10.1200/JOP.2010.000041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Keating NL, Landrum MB, Lamont EB, et al. Tumor boards and the quality of cancer care. J Natl Cancer Inst. 2013;105:113–121. doi: 10.1093/jnci/djs502. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Houssami N, Sainsbury R. Breast cancer: Multidisciplinary care and clinical outcomes. Eur J Cancer. 2006;42:2480–2491. doi: 10.1016/j.ejca.2006.05.023. [DOI] [PubMed] [Google Scholar]
  • 18.Clauser SB, Johnson MR, O'Brien DM, et al. Improving clinical research and cancer care delivery in community settings: Evaluating the NCI community cancer centers program. Implement Sci. 2009;4:63. doi: 10.1186/1748-5908-4-63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Chang JH, Vines E, Bertsch H, et al. The impact of a multidisciplinary breast cancer center on recommendations for patient management: The University of Pennsylvania experience. Cancer. 2001;91:1231–1237. doi: 10.1002/1097-0142(20010401)91:7<1231::aid-cncr1123>3.0.co;2-k. [DOI] [PubMed] [Google Scholar]
  • 20.Pawlik TM, Laheru D, Hruban RH, et al. Evaluating the impact of a single-day multidisciplinary clinic on the management of pancreatic cancer. Ann Surg Oncol. 2008;15:2081–2088. doi: 10.1245/s10434-008-9929-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Johnson MR, Clauser SB, Beveridge JM, et al. Translating scientific advances into the community setting: The National Cancer Institute Community Cancer Centers Program pilot. Oncol Issues. 2009;2009:24–28. . www.strategicvisionsinhealthcare.com/wp-content/uploads/2012/03/CancerArticle-accc-pdf.pdf. [Google Scholar]
  • 22.Swanson PL, Strusowski P, Asfeldt T, et al. Expanding multidisciplinary care in community cancer centers: An MDC assessment tool developed by the NCCCP. http://ncccp.cancer.gov/files/MDC_Article_JAN_FEB_2011-508.pdf.
  • 23.Stewart AK, McNamara E, Gay EG, et al. The Rapid Quality Reporting System: A new quality of care tool for CoC-accredited cancer programs. J Registry Manag. 2011;38:61–63. [PubMed] [Google Scholar]
  • 24.Lee EW, Wei L, Amato DA, et al. Cox-type regression analysis for large numbers of small groups of correlated failure time observations. In: Klein JP, Goel PK, editors. Survival Analysis: State of the Art. Dordrecht, the Netherlands: Kluwer Academic Publishers; 1992. pp. 237–247. [Google Scholar]
  • 25.Boxer MM, Vinod SK, Shafiq J, et al. Do multidisciplinary team meetings make a difference in the management of lung cancer? Cancer. 2011;117:5112–5120. doi: 10.1002/cncr.26149. [DOI] [PubMed] [Google Scholar]
  • 26.Kee F, Owen T, Leathem R. Decision making in a multidisciplinary cancer team: Does team discussion result in better quality decisions? Med Decis Making. 2004;24:602–613. doi: 10.1177/0272989X04271047. [DOI] [PubMed] [Google Scholar]
  • 27.Ryan J, Faragher I. Not all patients need to be discussed in a colorectal cancer MDT meeting. Colorectal Dis. 2014;16:520–526. doi: 10.1111/codi.12581. [DOI] [PubMed] [Google Scholar]
  • 28.Kersten C, Cvancarova M, Mjåland S, et al. Does in-house availability of multidisciplinary teams increase survival in upper gastrointestinal-cancer? World J Gastrointest Oncol. 2013;5:60–67. doi: 10.4251/wjgo.v5.i3.60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Lamb BW, Wong HW, Vincent C, et al. Teamwork and team performance in multidisciplinary cancer teams: Development and evaluation of an observational assessment tool. BMJ Qual Saf. 2011;20:849–856. doi: 10.1136/bmjqs.2010.048660. [DOI] [PubMed] [Google Scholar]
  • 30.Morris E, Haward R, Gilthorpe M, et al. The impact of the Calman–Hine report on the processes and outcomes of care for Yorkshire's colorectal cancer patients. Br J Cancer. 2006;95:979–985. doi: 10.1038/sj.bjc.6603372. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Forrest LM, McMillan DC, McArdle CS, et al. An evaluation of the impact of a multidisciplinary team, in a single centre, on treatment and survival in patients with inoperable non-small-cell lung cancer. Br J Cancer. 2005;93:977–978. doi: 10.1038/sj.bjc.6602825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Eaker S, Dickman PW, Hellström V, et al. Regional differences in breast cancer survival despite common guidelines. Cancer Epidemiol Biomarkers Prev. 2005;14:2914–2918. doi: 10.1158/1055-9965.EPI-05-0317. [DOI] [PubMed] [Google Scholar]
  • 33.Fleissig A, Jenkins V, Catt S, et al. Multidisciplinary teams in cancer care: Are they effective in the UK? Lancet Oncol. 2006;7:935–943. doi: 10.1016/S1470-2045(06)70940-8. [DOI] [PubMed] [Google Scholar]
  • 34.Taylor C, Atkins L, Richardson A, et al. Measuring the quality of MDT working: An observational approach. BMC Cancer. 2012;12:202. doi: 10.1186/1471-2407-12-202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Taylor C, Brown K, Lamb B, et al. Developing and testing TEAM (Team Evaluation and Assessment Measure), a self-assessment tool to improve cancer multidisciplinary teamwork. Ann Surg Oncol. 2012;19:4019–4027. doi: 10.1245/s10434-012-2493-1. [DOI] [PubMed] [Google Scholar]
  • 36.Carey M, Sanson-Fisher R, Lotfi-Jam K, et al. Multidisciplinary care in cancer: Do the current research outputs help? Eur J Cancer Care (Engl) 2010;19:434–441. doi: 10.1111/j.1365-2354.2009.01105.x. [DOI] [PubMed] [Google Scholar]
  • 37.Jazieh A-R, Al Hadab A, Howington J. Thoracic oncology multidisciplinary teams: Between the promises and challenges. Ann Thorac Med. 2008;3:34–37. doi: 10.4103/1817-1737.38395. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Journal of Oncology Practice are provided here courtesy of American Society of Clinical Oncology

RESOURCES