J. Racial and Ethnic Health Disparities DOI 10.1007/s40615-015-0084-0
Minority Use of a National Cancer Institute-Designated Comprehensive Cancer Center and Non-specialty Hospitals in Two Florida Regions Dawood H. Sultan & Jemal Gishe & Angella Hanciles & Meg M. Comins & Claire M. Norris
Received: 7 October 2014 / Revised: 4 December 2014 / Accepted: 5 January 2015 # W. Montague Cobb-NMA Health Institute 2015
Abstract Purpose To examine cancer treatment disparities at a National Cancer Institute-designated comprehensive cancer center (NCI-CCC) and non-specialty hospitals. Materials and Methods Florida hospital discharge datasets were used. ICD9-CM codes were used to define patients with female reproductive organ cancers (FROC), male reproductive organ cancers (MROC), and OTHER cancer diagnoses. A total of 7462 NCI-CCC patients and 21,875 non-specialty hospital patients were included in the statistical analysis. Data analysis was conducted in SAS 9.2.
D. H. Sultan (*) : M. M. Comins Department of Health Policy and Management, College of Public Health, University of South Florida, 13201 Bruce B. Downs BLVD, MDC 56, Tampa, FL 33612-3805, USA e-mail: [email protected] D. H. Sultan e-mail: [email protected]
Results Increases in age reduced the odds of receiving treatment at the NCI-CCC. Male patients were more likely than female patients to be treated at the NCI-CCC. Age-adjusted odds of African American and Hispanic out/inpatients being treated at the NCI-CCC were significantly lower than those of White out/inpatients. Only patients with workers’ compensation, charity, or other insurance had higher odds of being treated at the NCI-CCC. The odds of minority patients receiving outpatient treatment at the NCI-CCC declined after 2005. The odds of receiving inpatient treatment at the NCI-CCC significantly increased after 2006. Conclusions More targeted outreach by the NCI-CCC is required. However, we expect the creation of local Accountable Care Organizations (ACOs) to reduce the numbers of minority and older patients at the NCI-CCC. Coordinated quality care at ACOs implies a potential for retaining the patient market share held by non-specialty hospitals and a potential for increased demand for ACO care by minority and older patients. Keywords Comprehensive Cancer Center . Minority . African American . Hispanic
M. M. Comins e-mail: [email protected] J. Gishe : A. Hanciles Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, 13201 Bruce B. Downs BLVD, MDC 56, Tampa, FL 33612-3805, USA J. Gishe e-mail: [email protected] A. Hanciles e-mail: [email protected] C. M. Norris Louisiana Board of Regents, 1201 N. Third St., Suite 6-200, Baton Rouge, LA 70802, USA e-mail: [email protected]
Introduction Through its designated cancer centers program, the National Cancer Institute (NCI) recognized 68 regional healthcare centers as centers of excellence in cancer research and patient treatment [1, 2]. Of these, 41 are comprehensive cancer centers [2]. A comprehensive cancer center Bmust demonstrate reasonable depth and breadth of research in each of three major areas: laboratory, clinical, and population-based research, as well as substantial transdisciplinary research that bridges these scientific areas. In addition, a comprehensive center must also demonstrate professional and public education and outreach
J. Racial and Ethnic Health Disparities
capabilities, including the dissemination of clinical and public health advances in the communities it serves.^ [2] NCIdesignated cancer centers are credited with providing multidisciplinary and state of the art cancer treatment and expertise in rare cancers [2]. Patients treated at NCI-designated cancer centers are shown to experience lower cancer surgical mortality and superior treatment outcomes [3–5]. However, the use of treatment services provided by NCI-designated comprehensive cancer centers (NCI-CCCs) by ethnic minority patients has not been extensively studied [6]. This is more so in the case of the African American and Hispanic minority patients considered in this study. One of the only two studies which examined minority use of NCI cancer centers relied on a sample of African American Medicare patients only and did not account for whether the patients were treated at an NCI-designated cancer canter or a NCI-CCC [7]. The other study examined the use by White, Black, Hispanic, and Asian/Pacific Islander cancer patients in California but, similarly, did not clearly differentiate them in terms of whether their treatments were received at an NCI-designated cancer center or a NCI-CCC [6]. To our knowledge, minority use of NCI-CCCs is not studied in detail. Using patient hospital discharge records from an all-payer, all-provider, all-age, all-gender, racially, and ethnically diverse dataset, this study attempts to determine (1) whether or not the racial/ethnic and age distributions of cancer patients in a NCICCC differ from distributions in non-specialty hospitals in healthcare service regions surrounding the NCI-CCC and (2) whether or not patient demographics, insurance status, cancer diagnosis, location, and time of cancer treatment influence minority use of NCI-CCC. We mainly hypothesize that patient age, gender, ethnicity, geographic location, insurance status, type of diagnosis, and year of diagnosis were important determinants of whether or not African American and Hispanic cancer patients use a NCI-CCC for cancer treatment and care. This study falls within the body of scientific research which attempts to determine the role of healthcare institutions, healthcare providers, and individual patients in the creation of ethnic and racial disparities in access to and utilization of available cancer treatment and care services. Outlining disparities in cancer treatment and care service use and the associations of patients’ demographic, socioeconomic, and other characteristics with access to quality cancer care are important tools for informing community outreach to improve minority access to NCI-CCCs and for adding to the scientific evidence relevant to the overall understanding of disparities in cancer treatment.
Materials and Methods Sources of Data Though statewide cancer statistics are available from the Florida Cancer Data System [7], we chose to use in our analysis
data provided by the Florida Agency for Health Care Administration (AHCA). We are more familiar with AHCA datasets and have used them in prior research. Also, the datasets were readily available at the time this manuscript was conceived. Outpatient data (for the years 2005–2010) and inpatient data (for the years 2006–2011) were obtained from service information in the Florida hospital discharge datasets, maintained by the AHCA Office of Data Dissemination and Communication. The Agency for Health Care Administration was statutorily created by Chapter 20 of the Florida Statutes as the primary health policy and healthcare planning agency for the state. Among other responsibilities, the agency regulates the licensure of the state’s 45,000 healthcare facilities and maintains and shares healthcare data through the Florida Center for Health Information and Policy Analysis [8]. AHCA’s Florida hospital discharge datasets contain information on all-payers, all-providers, all-ages, all-gender, and patient race/ethnicity. Patient discharge records from healthcare facilities reporting to AHCA contain International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9-CM) codes indicating the primary diagnosis for an admission and the primary procedure performed during the index admission. The datasets also include an identifier of the healthcare facility region and a unique identification number for each hospital and each index admission. At the time of statistical analysis, outpatient data were available only up to 2010. Also, prior to 2005, the inpatient dataset was in a format which we could not import into the statistical software used for data analysis. These are the reasons why the datasets presented in this manuscript have different start/end dates. However, the different dates have no effect on the substantive interpretations provided in this paper. The paper dealt separately with inpatients and outpatients who could be examined at the same or different time periods. Study Population ICD9-CM codes were used to identify patients with a primary diagnosis of female reproductive organ cancer (FROC) [ICD9-CM codes 179, 180, 182, 183, and 184], male reproductive organ cancer (MROC) [ICD9-CM codes 185, 186, 187], and OTHER cancer diagnoses including FROC-related malignant neoplasm of female breast [ICD9-CM codes 174.09], MROC-related malignant neoplasm of male breast [ICD9CM codes 175.0-9], and malignant neoplasm of trachea bronchus and lung [ICD9-CM codes 162.0-9]. These codes define Bcancers that are diagnosed with the greatest frequency in the United States, excluding nonmelanoma skin cancers^ [9]. Since this study examines patient distributions and odds of cancer treatment by hospital type (NCI-CCC versus non-specialty) in two healthcare service regions surrounding the NCICCC, we included only patients served at the NCI-CCC and reporting hospitals in Florida health regions 5 and 6. These
J. Racial and Ethnic Health Disparities
regions comprise the following counties: Pinellas, Pasco, Hardee, Highlands, Hillsborough, Manatee, and Polk. All outpatients and inpatients from regions 5 and 6 and the NCI-CCC with FROC, MROC, and OTHER diagnoses identified for this study were included in the analysis. All third-party payers charged for index admissions were also included. A total of 29,337 patients met the inclusion criteria: (1) assigned ICD9-CM code indicating either a FROC, MROC or OTHER diagnosis for index admission at the NCI-CCC, or a reporting non-specialty hospital in Florida regions 5 and 6 and (2) receiving cancer treatment between the years 2005 and 2010 as outpatient and 2006 and 2011 as inpatient. Of these, a total of 7462 were NCI-CCC patients (5384 outpatients and 2078 inpatients) and the remaining 21,875 were non-specialty hospital patients (12,639 outpatients and 9236 inpatients). Study Variables The datasets used in this study included information on patient age, gender, ethnicity, type of health insurance, cancer diagnosis, year of cancer treatment, the county of the cancer treatment facility. In the statistical analysis conducted on the outpatient and inpatient datasets, patient age was measured in years. Patient gender was measured as a binary (0,1) variable. Patient race/ethnicity was measured as a four-item (1–4) categorical variable (Black, White, Hispanic, and Other, respectively). In this study, the African American (interchangeably identified as Black) patients in the data analysis did not include self-identified Black Hispanics. Likewise, White patients in the analysis did not include self-identified White Hispanics. Patients identified as Hispanic, White Hispanic, or Black Hispanic were grouped under the Hispanic ethnic designation. All patients who reported another race/ethnicity were defined as Other. The Other race/ethnicity category did not include Black, White, Hispanic, Black Hispanic, or White Hispanic patients. Insurance status was defined as a five-item categorical variable: (1) indicating Medicare, Medicare Health Maintenance Organization (HMO), and Medicare Preferred Provider Organization (PPO) (referred to as Insur1); (2) indicating Medicaid and Medicaid HMO (referred to as Insur2); (3) indicating commercial insurance, commercial HMO, commercial PPO, and self-pay (referred to as Insur3); (4) indicating workers’ compensation, charity, and other (referred to as Insur4); and (5) indicating CHAMPUS, VA, state/local government and Kidcare (referred to as Insur5). Cancer treatment years were assigned 1–6 values for outpatient and inpatient datasets, respectively. The location of the cancer treatment facility is measured as a seven-item categorical variable: (1) indicating Highlands County, (2) indicating Hillsborough County, (3) indicating the NCI-CCC, (4) indicating Manatee County, (5) indicating Pasco County, (6) indicating Pinellas County, and (7) indicating Polk County. Location identifiers 1, 2, 4, 5, 6, and 7 were collapsed into a single category which
was contrasted with the NCI-CCC to create a binary (0,1) variable indicating whether a treatment facility was located in Florida Region 5 and 6 or the NCI-CCC. A binary (0,1) variable measuring whether a patient was treated at a nonspecialty hospital or at the NCI-CCC was used as dependent variable for logistic regression models fitted to the outpatient and inpatient datasets. Statistical Analysis The independent samples t test was conducted to compare the mean age of outpatients and inpatients at the NCI-CCC and non-specialty hospitals. Chi-square test was used to compare the use of the NCI-CCC and local non-specialty hospitals among racial groups by outpatient-inpatient index admission status. Multivariate logistic regression models were used to estimate the odds of using the NCI-CCC versus local nonspecialty hospitals. We considered non-linearity and interaction terms. The two logistic regression models we estimated satisfied the convergence criterion (GCOV=1E-8), and the likelihood ratio test for global null hypothesis for beta=0 has a p value of
Minority Use of a National Cancer Institute-Designated Comprehensive Cancer Center and Non-specialty Hospitals in Two Florida Regions Dawood H. Sultan & Jemal Gishe & Angella Hanciles & Meg M. Comins & Claire M. Norris
Received: 7 October 2014 / Revised: 4 December 2014 / Accepted: 5 January 2015 # W. Montague Cobb-NMA Health Institute 2015
Abstract Purpose To examine cancer treatment disparities at a National Cancer Institute-designated comprehensive cancer center (NCI-CCC) and non-specialty hospitals. Materials and Methods Florida hospital discharge datasets were used. ICD9-CM codes were used to define patients with female reproductive organ cancers (FROC), male reproductive organ cancers (MROC), and OTHER cancer diagnoses. A total of 7462 NCI-CCC patients and 21,875 non-specialty hospital patients were included in the statistical analysis. Data analysis was conducted in SAS 9.2.
D. H. Sultan (*) : M. M. Comins Department of Health Policy and Management, College of Public Health, University of South Florida, 13201 Bruce B. Downs BLVD, MDC 56, Tampa, FL 33612-3805, USA e-mail: [email protected] D. H. Sultan e-mail: [email protected]
Results Increases in age reduced the odds of receiving treatment at the NCI-CCC. Male patients were more likely than female patients to be treated at the NCI-CCC. Age-adjusted odds of African American and Hispanic out/inpatients being treated at the NCI-CCC were significantly lower than those of White out/inpatients. Only patients with workers’ compensation, charity, or other insurance had higher odds of being treated at the NCI-CCC. The odds of minority patients receiving outpatient treatment at the NCI-CCC declined after 2005. The odds of receiving inpatient treatment at the NCI-CCC significantly increased after 2006. Conclusions More targeted outreach by the NCI-CCC is required. However, we expect the creation of local Accountable Care Organizations (ACOs) to reduce the numbers of minority and older patients at the NCI-CCC. Coordinated quality care at ACOs implies a potential for retaining the patient market share held by non-specialty hospitals and a potential for increased demand for ACO care by minority and older patients. Keywords Comprehensive Cancer Center . Minority . African American . Hispanic
M. M. Comins e-mail: [email protected] J. Gishe : A. Hanciles Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, 13201 Bruce B. Downs BLVD, MDC 56, Tampa, FL 33612-3805, USA J. Gishe e-mail: [email protected] A. Hanciles e-mail: [email protected] C. M. Norris Louisiana Board of Regents, 1201 N. Third St., Suite 6-200, Baton Rouge, LA 70802, USA e-mail: [email protected]
Introduction Through its designated cancer centers program, the National Cancer Institute (NCI) recognized 68 regional healthcare centers as centers of excellence in cancer research and patient treatment [1, 2]. Of these, 41 are comprehensive cancer centers [2]. A comprehensive cancer center Bmust demonstrate reasonable depth and breadth of research in each of three major areas: laboratory, clinical, and population-based research, as well as substantial transdisciplinary research that bridges these scientific areas. In addition, a comprehensive center must also demonstrate professional and public education and outreach
J. Racial and Ethnic Health Disparities
capabilities, including the dissemination of clinical and public health advances in the communities it serves.^ [2] NCIdesignated cancer centers are credited with providing multidisciplinary and state of the art cancer treatment and expertise in rare cancers [2]. Patients treated at NCI-designated cancer centers are shown to experience lower cancer surgical mortality and superior treatment outcomes [3–5]. However, the use of treatment services provided by NCI-designated comprehensive cancer centers (NCI-CCCs) by ethnic minority patients has not been extensively studied [6]. This is more so in the case of the African American and Hispanic minority patients considered in this study. One of the only two studies which examined minority use of NCI cancer centers relied on a sample of African American Medicare patients only and did not account for whether the patients were treated at an NCI-designated cancer canter or a NCI-CCC [7]. The other study examined the use by White, Black, Hispanic, and Asian/Pacific Islander cancer patients in California but, similarly, did not clearly differentiate them in terms of whether their treatments were received at an NCI-designated cancer center or a NCI-CCC [6]. To our knowledge, minority use of NCI-CCCs is not studied in detail. Using patient hospital discharge records from an all-payer, all-provider, all-age, all-gender, racially, and ethnically diverse dataset, this study attempts to determine (1) whether or not the racial/ethnic and age distributions of cancer patients in a NCICCC differ from distributions in non-specialty hospitals in healthcare service regions surrounding the NCI-CCC and (2) whether or not patient demographics, insurance status, cancer diagnosis, location, and time of cancer treatment influence minority use of NCI-CCC. We mainly hypothesize that patient age, gender, ethnicity, geographic location, insurance status, type of diagnosis, and year of diagnosis were important determinants of whether or not African American and Hispanic cancer patients use a NCI-CCC for cancer treatment and care. This study falls within the body of scientific research which attempts to determine the role of healthcare institutions, healthcare providers, and individual patients in the creation of ethnic and racial disparities in access to and utilization of available cancer treatment and care services. Outlining disparities in cancer treatment and care service use and the associations of patients’ demographic, socioeconomic, and other characteristics with access to quality cancer care are important tools for informing community outreach to improve minority access to NCI-CCCs and for adding to the scientific evidence relevant to the overall understanding of disparities in cancer treatment.
Materials and Methods Sources of Data Though statewide cancer statistics are available from the Florida Cancer Data System [7], we chose to use in our analysis
data provided by the Florida Agency for Health Care Administration (AHCA). We are more familiar with AHCA datasets and have used them in prior research. Also, the datasets were readily available at the time this manuscript was conceived. Outpatient data (for the years 2005–2010) and inpatient data (for the years 2006–2011) were obtained from service information in the Florida hospital discharge datasets, maintained by the AHCA Office of Data Dissemination and Communication. The Agency for Health Care Administration was statutorily created by Chapter 20 of the Florida Statutes as the primary health policy and healthcare planning agency for the state. Among other responsibilities, the agency regulates the licensure of the state’s 45,000 healthcare facilities and maintains and shares healthcare data through the Florida Center for Health Information and Policy Analysis [8]. AHCA’s Florida hospital discharge datasets contain information on all-payers, all-providers, all-ages, all-gender, and patient race/ethnicity. Patient discharge records from healthcare facilities reporting to AHCA contain International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9-CM) codes indicating the primary diagnosis for an admission and the primary procedure performed during the index admission. The datasets also include an identifier of the healthcare facility region and a unique identification number for each hospital and each index admission. At the time of statistical analysis, outpatient data were available only up to 2010. Also, prior to 2005, the inpatient dataset was in a format which we could not import into the statistical software used for data analysis. These are the reasons why the datasets presented in this manuscript have different start/end dates. However, the different dates have no effect on the substantive interpretations provided in this paper. The paper dealt separately with inpatients and outpatients who could be examined at the same or different time periods. Study Population ICD9-CM codes were used to identify patients with a primary diagnosis of female reproductive organ cancer (FROC) [ICD9-CM codes 179, 180, 182, 183, and 184], male reproductive organ cancer (MROC) [ICD9-CM codes 185, 186, 187], and OTHER cancer diagnoses including FROC-related malignant neoplasm of female breast [ICD9-CM codes 174.09], MROC-related malignant neoplasm of male breast [ICD9CM codes 175.0-9], and malignant neoplasm of trachea bronchus and lung [ICD9-CM codes 162.0-9]. These codes define Bcancers that are diagnosed with the greatest frequency in the United States, excluding nonmelanoma skin cancers^ [9]. Since this study examines patient distributions and odds of cancer treatment by hospital type (NCI-CCC versus non-specialty) in two healthcare service regions surrounding the NCICCC, we included only patients served at the NCI-CCC and reporting hospitals in Florida health regions 5 and 6. These
J. Racial and Ethnic Health Disparities
regions comprise the following counties: Pinellas, Pasco, Hardee, Highlands, Hillsborough, Manatee, and Polk. All outpatients and inpatients from regions 5 and 6 and the NCI-CCC with FROC, MROC, and OTHER diagnoses identified for this study were included in the analysis. All third-party payers charged for index admissions were also included. A total of 29,337 patients met the inclusion criteria: (1) assigned ICD9-CM code indicating either a FROC, MROC or OTHER diagnosis for index admission at the NCI-CCC, or a reporting non-specialty hospital in Florida regions 5 and 6 and (2) receiving cancer treatment between the years 2005 and 2010 as outpatient and 2006 and 2011 as inpatient. Of these, a total of 7462 were NCI-CCC patients (5384 outpatients and 2078 inpatients) and the remaining 21,875 were non-specialty hospital patients (12,639 outpatients and 9236 inpatients). Study Variables The datasets used in this study included information on patient age, gender, ethnicity, type of health insurance, cancer diagnosis, year of cancer treatment, the county of the cancer treatment facility. In the statistical analysis conducted on the outpatient and inpatient datasets, patient age was measured in years. Patient gender was measured as a binary (0,1) variable. Patient race/ethnicity was measured as a four-item (1–4) categorical variable (Black, White, Hispanic, and Other, respectively). In this study, the African American (interchangeably identified as Black) patients in the data analysis did not include self-identified Black Hispanics. Likewise, White patients in the analysis did not include self-identified White Hispanics. Patients identified as Hispanic, White Hispanic, or Black Hispanic were grouped under the Hispanic ethnic designation. All patients who reported another race/ethnicity were defined as Other. The Other race/ethnicity category did not include Black, White, Hispanic, Black Hispanic, or White Hispanic patients. Insurance status was defined as a five-item categorical variable: (1) indicating Medicare, Medicare Health Maintenance Organization (HMO), and Medicare Preferred Provider Organization (PPO) (referred to as Insur1); (2) indicating Medicaid and Medicaid HMO (referred to as Insur2); (3) indicating commercial insurance, commercial HMO, commercial PPO, and self-pay (referred to as Insur3); (4) indicating workers’ compensation, charity, and other (referred to as Insur4); and (5) indicating CHAMPUS, VA, state/local government and Kidcare (referred to as Insur5). Cancer treatment years were assigned 1–6 values for outpatient and inpatient datasets, respectively. The location of the cancer treatment facility is measured as a seven-item categorical variable: (1) indicating Highlands County, (2) indicating Hillsborough County, (3) indicating the NCI-CCC, (4) indicating Manatee County, (5) indicating Pasco County, (6) indicating Pinellas County, and (7) indicating Polk County. Location identifiers 1, 2, 4, 5, 6, and 7 were collapsed into a single category which
was contrasted with the NCI-CCC to create a binary (0,1) variable indicating whether a treatment facility was located in Florida Region 5 and 6 or the NCI-CCC. A binary (0,1) variable measuring whether a patient was treated at a nonspecialty hospital or at the NCI-CCC was used as dependent variable for logistic regression models fitted to the outpatient and inpatient datasets. Statistical Analysis The independent samples t test was conducted to compare the mean age of outpatients and inpatients at the NCI-CCC and non-specialty hospitals. Chi-square test was used to compare the use of the NCI-CCC and local non-specialty hospitals among racial groups by outpatient-inpatient index admission status. Multivariate logistic regression models were used to estimate the odds of using the NCI-CCC versus local nonspecialty hospitals. We considered non-linearity and interaction terms. The two logistic regression models we estimated satisfied the convergence criterion (GCOV=1E-8), and the likelihood ratio test for global null hypothesis for beta=0 has a p value of
