partnering toward a healthier future - adventist healthcare · 2012-12-02 · improving the health...

Partnering Toward a Healthier Future 2012 PROGRESS REPORT

Adventist HealthCare Health Equity Report

Compilation, analytics, and graphic design by Center on Health Disparities

Tiffany Capeles, MBA Talya Frelick, MPH

Marilyn Lynk, PhD

Mary Manan

Eme Martin, MPH

Marcos Pesquera, RPh, MPH

Deidre Washington, PhD

www.adventisthealthcare.com/disparities

Table of Contents

Acknowledgments 4 Highlights 5 Introduction 6 Background 9 Overview of Patient Populations 13 1. Snapshot of Diversity 15 2. Where We See Our Patients 18 Hospital Data 22 1. Cancer 23 2. Inpatient Clinical Quality Indicators 27 3. Hospital Readmission Rates 34 4. Patient Experience 37 Conclusion and Recommendations 43 References 46

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Acknowledgments THE CENTER ON HEALTH DISPARITIES AT ADVENTIST HEALTHCARE WAS CREATED TO raise community awareness about local health disparities, improve capacity to deliver population-based care, and develop solutions to eliminate local disparities in health care. We recognize the importance of collecting comprehensive data from hospital populations in order to identify and monitor racial disparities in health care, access, and outcomes. Though this report cannot describe all of the data needed to address disparities, it focuses on what data we have, what data we need, and how we can improve our monitoring and reporting capabilities. This report would not have been possible without the help of various people throughout the Adventist HealthCare system, including leadership and staff in system quality, business intelligence, market analysis, medical coding, language services, information systems, and communications and marketing. At each hospital, we were fortunate to work with coordinators of cancer registry and core measure data. Within the Center on Health Disparities, our research staff and interns played a major role in analyzing and presenting the data herein.

“[Transparency—public reporting of performance information—]…is crucial. It is the cornerstone of the cultural transformation that our health care organizations need to undergo to become safe.”1

ACKNOWLEDGMENTS

Republished from ABC News Radio and Pellucid

| 5 HIGHLIGHTS

Highlights from the 2012 Adventist HealthCare Health Equity Report THE 2012 ADVENTIST HEALTHCARE HEALTH EQUITY REPORT INCLUDES INFORMATION about patients treated at Shady Grove Adventist Hospital and Washington Adventist Hospital in 2011 and examines the intersection of quality and health equity. As part of its mission, the Center on Health Disparities works to address and eliminate health disparities and promote health equity in the communities served by Adventist HealthCare. As Adventist HealthCare is continuously striving to provide the highest quality of care, it recognizes that the provision of high quality care and the promotion of health equity are inextricably linked. The Agency for Healthcare Research and Quality ( A HRQ ) , through publication of its annual reports, presents a compelling case for improving overall quality by addressing the disparities observed in certain core quality measures. Collecting and reporting accurate patient data is essential to developing data-driven interventions to eliminate disparities and provide high-quality, equitable care. It is important to emphasize that the data and analyses presented here are exploratory. The report illustrates how Adventist HealthCare and other hospitals can report quality performance using a health equity framework. Any differences discussed here may be the result of procedural differences in the way these data were recorded and/or reported, rather than an actual difference in compliance with a specific process of care measure and/or disparate treatment across groups. Further analysis is required to determine the reasons why these differences exist. For both hospitals, we analyzed data on the core quality measures reported to the Centers for Medicare and Medicaid Services in 2011 in the following areas: acute myocardial infarction ( A MI ) , heart failure ( H F ) , pneumonia ( PN) , and surgical care ( SCIP ) . We did not find significant differences by either race or ethnicity in most of the core quality measures, except in a few cases. At one hospital, both Asian and Black patients appeared less likely than White patients to have perioperative temperature management. Also, Black patients appeared less likely to have recommended venous thromboembolism ( VTE ) prophylaxis ordered compared to Asian or White patients. Analysis of quality performance data may be used to identify disparities in care and inform targeted quality improvement interventions to address them. The Health Equity Report in its totality is meant to convey general information about the patient population served at Adventist HealthCare hospitals, where they receive care, and the quality of care received. A majority of the information presented here is descriptive and discussion of findings is exploratory; data limitations and other factors must be carefully considered before any conclusions can be made about care quality and patient outcomes. However, we hope that the publication of this report will be viewed by other healthcare organizations and community stakeholders as a big, important step by Adventist HealthCare to ensure transparency and accountability for performance excellence.

Introduction

| 7 INTRODUCTION

ADVENTIST HEALTHCARE ’ S MISSION IS TO DEMONSTRATE GOD ’ S CARE BY improving the health of people and communities through a ministry of physical, mental and spiritual healing. With the increasing racial and ethnic diversity of residents in the Washington, D.C. metropolitan area, addressing the needs of medically underserved minority and low-income populations is inextricably linked to fulfillment of Adventist HealthCare ’ s mission. In 2007, the Center on Health Disparities ( the Center ) was created to address and eliminate health disparities and inequalities in the communities served by Adventist HealthCare ( AHC ) , including Montgomery, Prince George ’ s and Frederick Counties in Maryland, as well as Washington, D.C. Health disparities are differences “ in which disadvantaged social groups—such as the poor, racial/ethnic minorities, women, or other groups who have persistently experienced social disadvantage or discrimination—systematically experience worse health or greater health risks than more advantaged social groups. ” 2 As part of its mission, the Center works with Adventist HealthCare hospitals to understand the diverse patient populations they serve, monitor racial or ethnic differences in quality of care, and address disparities in order to provide high-quality and equitable care for all patients. Since 2007, the Center has held yearly conferences and released annual progress reports describing the cultural diversity of the tri-county area, highlighting community initiatives to promote health equity, and sharing best practices from local and national programs to eliminate health disparities.3-4 Since 2003, the Agency for Healthcare Research and Quality ( A HRQ ) has published two annual reports on national trends in the quality of health care provided to American people and on disparities in healthcare delivery. Last year, for the first time, AHRQ published the findings from both the 2010 National Healthcare Quality Report and the 2010 National Healthcare Disparities Report together in a single executive summary to reinforce the need to consider both the quality of care and disparities in care simultaneously when assessing the healthcare system. This year again, AHRQ released the 2011 National Healthcare Disparities Report and the 2011 National Healthcare Quality Report together.5-6 ( For more information on the 2011 National Healthcare Quality and Disparities Reports, visit: http://www.ahrq.gov/qual/qrdr11.htm. ) One of the major themes to emerge from the two reports is that healthcare quality—though improving—is suboptimal, particularly for minorities and low-income groups. For example, 77% of the quality measures related to the treatment of acute illness or injury showed improvement. Acute treatment includes a high proportion of hospital measures, many of which are tracked by the Centers for Medicare and Medicaid Services ( CMS) . Measures that showed improvement include:

• Hospital patients with heart attack who received percutaneous coronary intervention within 90 minutes of arrival,

• Hospital patients with heart failure and left ventricular systolic dysfunction who were prescribed ACE inhibitor or angiotensin receptor blockers ( ARB ) at discharge, and

Introduction

8 | INTRODUCTION

• Adult surgery patients who had prophylactic antibiotics discontinued within 24 hours after surgery end time.

In addition to these quality measures, there are also disparities-specific measures that showed improvement . For example, in the area of congestive heart failure-related admissions, the gap between Blacks and Whites, as well as that between Hispanics and non-Hispanic Whites, has been decreasing. While quality is improving, access to health care and disparities, however, are not. In some cases, in fact, the disparities worsened. Measures where disparities worsened at the most rapid rates include:

• Maternal deaths per 100,000 live births ( g ap widening between Blacks and Whites ) ; • Breast cancer diagnosed at advanced stage per 100,000 women age 40 and over ( gap

widening between Blacks and Whites ) ; and • Adults age 40 and over who have ever received a colonoscopy, sigmoidoscopy, or

proctoscopy ( g ap widening between American Indians/Alaskan Natives and Whites AND between the poor and those with higher income ) .

What is clear from the 2011 AHRQ Reports is that we have a lot more to do to achieve a healthcare system that provides high-quality care for all people in the U.S. regardless of race, ethnicity, age, language, income or location.7 The purpose of the 2012 Adventist HealthCare Health Equity Report is to help inform primarily our hospitals ’ quality executives and other leaders about the diverse populations we serve and the quality of care they receive at our hospitals. We also hope to use this information to monitor and improve quality of care by identifying any disparities that may exist in the care provided to our patients. In doing so, we can develop targeted interventions to eliminate disparities and provide the highest quality of care to all of Adventist HealthCare ’s patients. About the 2012 Health Equity Report This report is meant to convey general information about the patient population served at Adventist HealthCare hospitals, where they receive care, and the quality of care received. The first section of the report describes self-reported demographic characteristics of the patient populations seen at each hospital in 2011, namely race, ethnicity and preferred language. The settings in which patients were treated ( inpatient, outpatient, and emergency department ) are described in the next section. In the Cancer section, we describe the race, ethnicity, and age ( at diagnosis ) of cancer patients by type of cancer. The following section presents quality indicators, stratified by race and ethnicity, for four core measures: heart failure, acute myocardial infarction, pneumonia and surgical care improvement. In the Hospital Readmissions section, we present 30-day all-cause readmission rates for 2011. We also present heart failure and acute myocardial infarction readmission rates, using the Admission-Readmission Revenue ( A RR ) methodology. Finally, in the Patient Experience section, we present inpatient responses to the Hospital Consumer Assessment of Healthcare Providers and Systems ( H CAHPS ) Survey, stratified by race and ethnicity. We also include information on utilization of interpreter services at both hospitals.

Background

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Local Populations POPULATION DEMOGRAPHICS ARE RAPIDLY CHANGING IN THE STATE OF MARYLAND, particularly among residents living in Montgomery and Prince George ’ s Counties. The most recent U.S. Census showed that between 2000 and 2010, Montgomery County became a “ majority-minority ” county for the first time: more than 50% of the residents identified their race using a category other than “ non-Hispanic White ” .8 The Hispanic population in the county grew 64.4 percent in the last decade ( 1 7 percent of the county is Hispanic or Latino ) .9 Almost 30% of Montgomery County residents were foreign-born, and 36% spoke a language other than English at home. As is illustrated in this Health Equity Report, the patient population of both Shady Grove Adventist Hospital and Washington Adventist Hospital reflects the rich diversity of residents living in the communities they serve. Disparities in Health and Health Care The Institute of Medicine report, Unequal Treatment, highlighted inequities in health and health care showing that racial and ethnic minorities receive a lower quality of care than whites.10 Furthermore, these inequities exist even when controlling for differences in socioeconomic status, insurance coverage, health status, and other factors. There has been a myriad of evidence showing the pervasive existence of disparities in quality of health care ( such as differences in available treatments, communication between patients and providers, and bias among providers and staff ) , access to care ( barriers to care like language proficiency, health literacy, and insurance status, or differences in healthcare utilization among different populations ) , different levels and types of care ( s uch as primary vs. emergency care) , clinical conditions ( cardiovascular care, cancer treatments, diabetes care, end-stage renal disease and kidney transplantation) , and healthcare settings ( e.g., hospitals and emergency departments ) .11-13 The Center ’ s 2011 progress report examined the disproportionate effect disparities have on minorities and the poor. According to the report, minorities face the highest mortality rates for heart disease, stroke and cancer. There are many reasons why health disparities are so widespread and persistent. Factors such as race, ethnicity, and gender, as well as where people live or work, housing conditions, and access to nutritious food sources, can strongly influence health and access to health care.14-15 Other factors like socioeconomic status, primary language, culture, health literacy, and differences in access to or quality of care contribute to health disparities as well. Take primary language for example. The language barriers encountered by limited English proficient or LEP patients seeking health care can adversely affect health outcomes in many different ways. LEP patients tend to have poorer self-reported health status compared to patients speaking English only.16 Language barriers can lead to poor patient-provider communication, which is a significant predictor of patient utilization of preventive health services, including screenings.17 Furthermore, barriers to

Background

BACKGROUND

| 11 BACKGROUND

communication can impede access to health care, lower the quality of care, lead to an increased risk for adverse medical events, result in dissatisfaction with care, and have significant impact on critical processes in care, such as obtaining informed consent. 18-22 In order to address disparities in health and health care, hospitals and other healthcare organizations must be able to identify and monitor differences in the patient population and the barriers they face when accessing health care. Standardized collection of patient demographic information—race, ethnicity, language preference, and country of origin—is essential to monitor disparities in care. Race and ethnicity data should be analyzed, reviewed internally, and reported regularly in order to identify disparities in quality of care, patient experience, and health outcomes, and target efforts to address them.23 As a result of federal and state policies regarding the collection and meaningful use of patient demographic data to reduce health disparities ( i.e., Patient Protection and Affordable Care Act, American Recovery and Reinvestment Act ( ARRA) / Health Information Technology for Economic and Clinical Health Act ( HITECH ) , and Maryland Health Improvement and Disparities Reduction Act of 2012 ) , hospitals are required to use and report patient race and ethnicity data using U.S. Office of Management and Budget ( O MB ) categories.24 The use of these data to monitor quality of care and inform quality improvement efforts is equally important. Health Reform On June 28, 2012, the Supreme Court upheld the Patient Protection and Affordable Care Act ( ACA ) to reform the nation ’ s healthcare system and improve the health of millions of people. Provisions related to achieving health equity include: ( 1 ) expanding access to health insurance to uninsured individuals; ( 2 ) improving quality of care through better measurement and reporting and the use of evidence-based practices to ensure patient-centered care; and ( 3 ) improving the type of care all Americans receive focusing on access, equity, and prevention.25 Most importantly, the ACA explicitly describes the need to collect demographic information from patients to monitor trends in health disparities. Hospitals are required to collect data on patient race, ethnicity, and language and use it in a meaningful way to improve healthcare delivery, patient outcomes, and population health. Collecting patient race and ethnicity data accurately is necessary in order to assess quality of care stratified by race and ethnicity categories and report performance measures. With health reform provisions focusing on the needs of medically underserved and disadvantaged populations, an increasing number of people seeking care and services from healthcare providers—now, and in the future—will be racial and ethnic minorities. Patient Experience and Patient-centered Quality Care Patient-centeredness—one of the six healthcare quality aims identified in the Institute of Medicine ’ s report, Crossing the Quality Chasm 26—is highly related to healthcare quality and positive patient experience. Information gathered through patient experience surveys and interviews elicit feedback from patients about what they did ( or did not ) experience in their interactions with healthcare providers or systems.27 These surveys include items that address issues of access, communication,

12 | BACKGROUND

and respect in the patient-provider relationship, and other interpersonal aspects of health care that patients value. Positive patient experience can affect clinical practice and patient outcomes ( e.g., good rapport and trust in the provider-patient relationship, effective communication, fewer errors, patient engagement in care, adherence to treatment recommendations, and improved health status ) . Evidence shows that positive patient experience is related to better process of care outcomes for disease prevention and management.28 Monitoring and addressing less than desirable reports of patients ’ experiences with care makes good business sense as well. Ensuring a positive patient experience can result in positive outcomes for healthcare organizations in the form of financial incentives for high quality health care ( e .g., reimbursements from Medicare/Medicaid and state programs ) , lower risk of complaints and lawsuits for medical malpractice, better provider-patient relationships, greater patient loyalty, and better system quality performance, all of which may lead to lower turnover and greater satisfaction among employees.29 Moreover, organizational cultural competence among leaders and staff, and equity in services, policies, and procedures can improve patients ’ access to and overall experiences with care. There are compelling reasons why hospitals and other community organizations should focus on improving quality and eliminating health disparities. Essential to motivating hospitals to improve care is public reporting of information about hospital performance and quality indicators, patient experiences of care, utilization of services, access to care, and health status. The goal of this report is to describe a set of outcomes for Adventist HealthCare acute care hospital patients by race, ethnicity, and language. A majority of the information presented here is descriptive and the data analyses exploratory. Because factors that contribute to disparities are numerous and complex, detailed discussion and interpretation about our findings is beyond the scope of this report. Data limitations and other factors such as access to care and specific conditions must be considered carefully before any conclusions can be made about care quality and patient outcomes.

Overview of Patient Populations

“ F rom the perspectives of quality and safety, diversity and equity are cornerstones for improvement efforts.” 3 0

| 15 PATIENT POPULATIONS

SNAPSHOT OF DIVERSITY: Adventist HealthCare IN THIS FIRST SECTION, WE PRESENT A ‘ SNAPSHOT ’ OF THE PATIENT POPULATION treated at Shady Grove Adventist Hospital ( SGAH ) and Washington Adventist Hospital ( W AH ) over the past calendar year. As healthcare providers, it is important that we know who lives in the communities served by Adventist HealthCare. These communities—and their healthcare needs—are increasingly diverse. In addition, expanding access to care for these populations is directly related to an increased amount of cross-cultural interaction in the healthcare environment, which can influence communication and clinical decision making. Adventist HealthCare’ s strategy to deliver population-based care through medical and chronic disease management is crucial to addressing the needs of diverse populations. Having a general knowledge about the demographic characteristics of our communities is the first step toward eliminating health disparities among vulnerable populations. Data Source The data for the Snapshot of Diversity and Where We See Our Patients sections were obtained from hospital patient electronic medical records. This is not a sample; the percentages reflect all patients seen at each hospital in 2011. However, for some patients, race, ethnicity or preferred language data may be unknown and/or missing.

1. Snapshot of Diversity

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SNAPSHOT OF DIVERSITY: Shady Grove Adventist Hospital Table 1 presents the percentage of patients treated at SGAH during the 12-month period between January and December 2011, stratified by patient race/ethnicity. Figure 1 presents the same information in a pie chart. ( S GAH patients include patients treated at the main hospital in Rockville, Maryland, as well as the Shady Grove Adventist Emergency Center in Germantown, Maryland. ) Table 1 shows that the majority of patients seen at SGAH in 2011 are White/non-Hispanic ( 4 7% ) .Black/non-Hispanic patients made up 23% of the patient population, Hispanic patients approximately 16%, and Asian/Pacific Islanders about 9%. This distribution of patients is similar to the distribution seen in 2010; however, the percentage of Black patients and Asian patients increased slightly, while the percentage of White/non-Hispanic patients decreased slightly. Table 1 and Figure 1. Patient Population by Race/Ethnicity for SGAH from January– December 2011 ( N =158,451)

*Column does not total to 100% due to missing data. Data were missing for 2,920 patients.

Table 2 presents the percentage of patients treated at SGAH during the 12-month period between January 2011 and December 2011, stratified by preferred language. More than 6% of patients seen expressed a preference to communicate in a language other than English, representing nearly 10,000 patients. Table 2. Patient Population by Preferred Language for SGAH from January – December 2011 ( N =158,451)

PATIENT POPULATIONS

Preferred Language Percentage of all SGAH patients English 88.7 Spanish 3.9 Other 2.3 Unknown 5.1

Patient Race/Ethnicity

Percentage of all SGAH

patients* Any Race/Hispanic 15.9 White/ Non-Hispanic 46.7 Black/ Non-Hispanic 23.1 Asian or Pacific Is-lander/Non-Hispanic

8.8

Other Race/Non-Hispanic

3.7

Any Race/Hispanic,

15.9

White/ Non‐Hispanic, 46.7

Black/ Non‐Hispanic, 23.1

Asian or Pacific Islander/Non‐Hispanic, 8.8

Other Race/Non‐Hispanic, 3.7

| 17

Any Race/ Hispanic, 28.8%

White/ Non‐

Hispanic, 20.0%

Black/ Non‐

Hispanic, 42.4%

Asian or Pacific‐Islander/ Non‐

Hispanic, 4.1%

Other Race/Non‐Hispanic, 2.8%

PATIENT POPULATIONS

SNAPSHOT OF DIVERSITY: Washington Adventist Hospital Table 3 presents the percentage of patients treated at WAH over the 12-month period between January 2011 and December 2011, stratified by patient race/ethnicity. Figure 2 presents the same information in a pie chart. Table 3 shows that the majority of patients treated at WAH in 2011 were Black ( 4 2% ) . About 29%were Hispanic and 20% were White. This distribution of patients is also very similar to the distribution observed in 2010, with slight increases in the percentage of Hispanic patients, and very slight decreases in Black, White and Asian patients.

Table 3 and Figure 2. Patient Population by Race/Ethnicity for WAH from January –December 2011 ( N =83,990) Note: The table and figure have been revised.

*Column does not total to 100% due to missing data. Data were missing for 1,593 patients.

Table 4 presents the percentage of patients treated at WAH between January and December 2011, stratified by preferred language. Approximately 15% of patients seen expressed a preference to communicate in a language other than English, representing more than 10,000 patients. Table 4. Patient Population by Preferred Language for WAH from January –December 2011 ( N =83,990) Note: The table has been revised.

Patient Race/Ethnicity

Percentage of all WAH patients*

Any Race/Hispanic 28.8 White/ Non-Hispanic 20.0 Black/ Non-Hispanic 42.4 Asian or Pacific Is-lander/Non-Hispanic

4.1


2.8

Preferred Language Percentage of all WAH patients* English 83.2 Spanish 11.9 Other 1.8 Unknown 3.1

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Percentage of all Hospital Patients*

Percent Inpatient*

( N =24,542)

Percent Outpatient*

( N =47,525)

Percent Emergency Department* ( N =86,384)

Any Race/ Hispanic

15.9 12.7 14.1 17.8

White/ Non-Hispanic

46.7 51.2 51.2 43.0

Black/ Non-Hispanic

23.1 18.7 16.8 27.8

Asian or Pacific Islander/ Non-Hispanic

8.8 12.8 11.3 6.3

Other Race/ Non-Hispanic

3.7 3.3 3.2 4.0

PATIENT POPULATIONS

WHERE WE SEE OUR PATIENTS: Shady Grove Adventist Hospital TABLE 5 PRESENTS THE PERCENTAGE OF PATIENTS TREATED AT SGAH IN 2011, stratified by both race/ethnicity and the setting in which they were seen ( inpatient, outpatient, or emergency department ) . Patients with an unknown and/or missing race/ethnicity ( N=2,920) were not included in these calculations. In Table 5, the percentages are calculated by setting, with the columns totaling to 100%. Table 5 shows that the distribution of the patients by setting aligns generally with the overall distribution of patients by race/ethnicity. ( T he first column in Table 5 repeats the information presented in Table 1 above. ) However, different patterns of utilization emerge for different race/ethnicities, as shown in the last three columns of Table 5. For example, Hispanic patients represent 16% of all patients seen, but 18% of patients seen in the emergency department ( E D ) , indicating slightly higher rates of utilization of the ED. Hispanics account for 13% and 14% of inpatients and outpatients, respectively, in each case less than the overall percentage. By comparison, White patients account for 47% of all patients seen, yet they account for only 43% of patients seen in the ED, indicating lower rates of utilization of the ED. With regard to ED utilization, Black patients most closely resemble the pattern of Hispanic patients ( higher rates of utilization ) , while Asian patients most closely resemble White patients ( lower rates of utilization ) . High rates of ED utilization may be associated with not having a primary physician or medical home, or being under- or uninsured.31-32

Table 5. Where We See Our Patients ( SGAH ) from January –December 2011 ( N =158,451)

*Columns do not total to 100% due to missing data. Data were missing for 2,920 patients.

2. Where We See Our Patients


Figure 3 presents the hospital utilization patterns of White, Black, Asian, and Hispanic patients, without regard to total numbers. For example, of all Hispanic patients seen at SGAH in 2011, more than half were seen in the ED. The same can be said for Black patients. For both Hispanic and Black patients, more than 60% of patients, nearly two-thirds, were seen in the ED. In contrast, just half of the White patients were seen in the ED. Asian patients had the lowest rate of ED use ( 39% ) . Figure 3 also shows that Asian and White patients had higher rates of inpatient care.

Figure 3. Patient Distribution at SGAH from January– December 2011 by Patient Race

Emergency Department,

50%

Inpatient, 17%

Outpatient, 33%

Distribution of White Patients (N=73,977)


65%

Inpatient, 13%

Outpatient, 22%

Distribution of Black Patients (N=36,565)


39%

Inpatient, 23%

Outpatient, 38%

Distribution of Asian Patients (N=13,948)


61%

Inpatient, 12%

Outpatient, 27%

Distribution of Hispanic Patients (N=25,207)

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WHERE WE SEE OUR PATIENTS: Washington Adventist Hospital Table 6 presents the percentage of patients treated at WAH in 2011, stratified by both race/ethnicity and the setting in which they were seen ( i npatient, outpatient, or emergency department ) . Patients with an unknown and/or missing race/ethnicity ( N=1,593 ) were not included in these calculations. In Table 6, the percentages are calculated by setting, with the columns totaling to 100%. Table 6 shows that the distribution of patients by setting aligns generally with the overall distribution of patients by race/ethnicity. ( T he first column in Table 6 repeats the information presented in Table 3 above. ) However, similar to what was observed at SGAH, different patterns of utilization emerge for different race/ethnicities, as seen in the last three columns. For example, Hispanic patients represent 29% of all patients seen, but nearly 37% of patients seen in the emergency department, indicating higher rates of utilization of the ED. Black patients, who represent about 43% of all patients seen, did not show any remarkable rates of utilization in any of the settings, with all percentages hovering between 42 and 45%. By comparison, White patients and Asian patients had lower rates of ED utilization compared to their overall population distribution.

Table 6. Where We See Our Patients ( WAH ) from January –December 2011 ( N =83,990) Note: The table has been revised.

*Columns do not total to 100% due to missing data. Data were missing for 1,593 patients. Figure 4 presents the hospital utilization patterns of White, Black, Asian, and Hispanic patients at WAH without regard to the total number of patients. Nearly 60% of Hispanic patients treated at WAH received care in the ED; only 18% were inpatients. White patients were seen primarily in an outpatient setting ( 46% ) , while 33% received care in the ED. Asian patients were seen in outpatient settings primarily, also ( 57% ) . Finally, of all Black patients seen, just about half ( 48%) , were seen in the ED.

PATIENT POPULATIONS

Percentage of all Hospital Patients*

Percent Inpatient *

( N =15,735)

Percent Outpatient*

( N =28,483)

Percent Emergency Department* ( N =38,179)

Any Race/Hispanic 28.8 26.2 19.6 36.9 White/Non-Hispanic

20.0 21.5 26.7 14.3

Black/Non-Hispanic

42.4 40.1 41.3 44.2

Asian or Pacific Islander/Non-Hispanic

4.1 3.8 6.7 2.3


2.8 4.4 3.5 1.5


Figure 4. Patient Distribution at WAH from January – December 2011 by Patient Race Note: The figure has been revised.


58%Inpatient, 18%

Outpatient, 24%

Dis tribution of Hispanic Patients (N=24,216)


33%

Inpatient, 21%

Outpatient, 46%

Dis tribution of White Patients (N=16,791)


48%

Inpatient, 18%

Outpatient, 34%

Dis tribution of Black Patients (N=35,622)


25%

Inpatient, 18%Outpatient, 57%

Dis tribution of AsianPatients (N=3,462)

22 |

Hospital Data

| 23 HOSPITAL DATA

DISEASE-SPECIFIC RACIAL AND ETHNIC HEALTH DISPARITIES HAVE BEEN WELL- documented for several years. Diseases where disparities have been documented include cancer, diabetes, HIV/AIDS, and heart disease, to name only a few. Examining disease-specific disparities in morbidity, mortality, and other outcomes can provide valuable insight into where efforts and resources to reduce and/or eliminate disparities should be focused. In this report, we decided to focus on cancer, as one of the most prevalent diseases in the country. Maryland had the 21st highest cancer mortality rate in the United States for the period 2003– 2007, a significant improvement from the rate between 1986 and 1990.33 The National Cancer Institute defines cancer health disparities as adverse differences in cancer incidence, cancer prevalence, cancer death, cancer survivorship, and burden of cancer or related health conditions that exist among specific population groups in the United States.34 According to the U.S. Office of Minority Health, breast cancer is diagnosed 10% less frequently in African American women than White women; however, African American women are 36% more likely to die from the disease.35 African American men have higher rates of colorectal cancer incidence and mortality compared with other racial groups. Asian/Pacific Islander men and women have higher incidence and mortality rates for stomach and liver cancer. For some populations, lower rates of screening and follow-up could lead to later diagnosis and treatment and higher mortality. For example, in the tri-county area served by Adventist HealthCare, cancer incidence rates are comparable; however, mortality rates are typically higher for minority populations.36 Understanding health disparities in cancer and cultural differences in perceptions of the illness is critical to ensure the provision of culturally competent cancer care. The National Cancer Institute and Centers for Disease Control and Prevention have additional information about health disparities in cancer, factors that contribute to disparities, and strategies for reducing them, including physicians' recommendations for screening and early detection. Data Source The American College of Surgeons Commission on Cancer ( CoC ) requires that accredited programs ( i ncluding both Shady Grove and Washington Adventist Hospitals ) maintain a Cancer Registry of most tumors diagnosed with and/or initially treated at a hospital. These registries contain a wealth of demographic and clinical information on patients diagnosed and/or treated for cancer each year. Information abstracted from the 2011 registries at SGAH and WAH is presented below. ( N ote: For both hospitals, the registry was not complete at the time this data was obtained. The registry was complete for approximately 11 months of 2011. ) It is important to stress that the data presented here are not intended to be indicative of cancer prevalence, nor of cancer disparities, in the Washington, D.C. region. Rather, the data here are intended to convey the composition of patients who were diagnosed or initially treated for cancer at

1. Cancer ( Selected Populations )

24 |

SGAH and WAH in 2011. ( S ee the Center on Health Disparities’ 2011 Progress Report for more comprehensive data on cancer prevalence and cancer disparities locally. http://www.adventisthealthcare.com/pdf/AHC-CHD-ProgressReport-2011.pdf ) . Since many factors, including socio-demographic, cultural, and religious factors, may influence where a person seeks treatment ( i ndeed, if they seek treatment at all ) , a single hospital registry cannot be considered a representative sample of the larger region ( i.e., it may include a highly self-selective sample) . Also, no oncologists or other clinicians were consulted to interpret the data from the registries for this report. Therefore, patient categorization by type of cancer may differ slightly from histologic classification. 2011 CANCER REGISTRY: Shady Grove Adventist Hospital At the time the 2011 SGAH cancer registry was analyzed, it included 774 unique patient IDs. Figure 5 shows the distribution of White patients included on the registry, by type of cancer. A total of 559 patients had White listed as their primary race. The most prevalent cancer among White patients was breast cancer; more than one-fifth of the patients ( approximately 21% ) had this diagnosis. Following breast cancer was prostate cancer ( approximately 14% ) . Lung, colorectal, and thyroid cancer rounded out the top five at SGAH.

Figure 6 shows the distribution of Black patients included on the SGAH cancer registry, by type of cancer. The distribution is very similar to that of White patients; breast, prostate, thyroid, lung, and colorectal cancers are included in the top five. One hundred and eighteen ( 118) Black patients were included in the registry. The majority of the other 97 patients in the SGAH cancer registry had Asian listed as their primary race. The following nationalities were represented: Chinese ( N =30 ) , Japanese ( N=2 ) , Filipino ( N =10 ) , Korean ( N=11) , Vietnamese ( N=14 ) , Asian Indian ( N =15 ) , and Pakistani ( N=4 ) .

HOSPITAL DATA

Breast, 21%

Prostate, 14%

Lung, 11%

Colorectal, 9%

Thyroid, 11%

Renal Pelvis, Ureter, Bladder, 6%

Kidney, 3%

Others (& Unknown), 25%

Figure 5. White Patients on 2011 SGAH Cancer Registry by Type of Cancer (N=559)

Breast, 20%

Prostate, 14%

Lung, 7%

Colorectal, 8%

Thyroid, 9%Renal Pelvis, Ureter,

Bladder, 7%

Bone Marrow, 5%


Figure 6. Black Patients on 2011 SGAH Cancer Registry by Type of Cancer (N=118)

| 25 HOSPITAL DATA

Average Age at Cancer Diagnosis Figures 5 and 6 show that the distribution of patients by type of cancer was fairly similar for White and Black patients. However, the average age at time of diagnosis ( without respect to type of cancer ) shows a larger difference. The average age at diagnosis for White patients was 62.1 years old, for Black patients, 57.4 years old, and across all Asian patients, 63.3 years old. However, the average age at diagnosis for the different Asian nationalities ranged from a low of 55.6 years for Vietnamese patients, to a high of 62.9 years for Korean patients. Ethnicity The cancer registry also includes the patient ’ s ethnicity, separately from race. Approximately 7% ( N =52 ) of the patients included on the SGAH cancer registry were Hispanic/Latino. Of these, the majority were from Central or South America. The two most common cancers at SGAH for persons of Hispanic origin were thyroid and breast. The average age at diagnosis for Hispanic patients was 55.6 years old. 2011 CANCER REGISTRY: Washington Adventist Hospital At the time the 2011 WAH cancer registry was obtained, it included 315 unique patient IDs. Figure 7 shows the distribution of White patients included on the registry, by type of cancer. A total of 110 patients had White listed as their primary race. The most prevalent cancer among White patients was breast cancer ( 23% ) . Prostate, lung, and colorectal cancers rounded out the top four.

Figure 8 shows the distribution of Black patients included on the WAH cancer registry, by type of cancer. There were 156 Black patients included on the registry. For Black patients, the most prevalent type of cancer seen was prostate cancer, followed by breast cancer. An additional 33 people on the WAH tumor registry were Asian. The four most common nationalities were Korean ( N =8 ) , Chinese ( N=5) , Vietnamese ( N=5 ) , and Asian Indian ( N=5 ) .

Breast, 23%

Prostate, 12%

Lung, 13%Colorectal, 14%


Figure 7. White Patients on WAHTumor Registry by Type of Cancer, 2011

Figure 8. Black Patients on WAHTumor Registry by Type of Cancer, 2011

Breast, 19%

Prostate, 22%

Lung, 12%

Colorectal, 10%

Pancreatic, 5%


26 |

Average Age at Cancer Diagnosis The average age at diagnosis for White patients was 64.4 years old and for Black patients, it was slightly lower ( 6 3.2 ) . Asian patients ( across all nationalities ) had the highest average age at diagnosis ( 6 8.8 years old) . Ethnicity Approximately 17% ( N=54 ) of the patients included on the cancer registry were Hispanic/Latino. Of these, the majority were from Central or South America. The two most common cancers at WAH for persons of Hispanic origin were breast and colorectal. The average age at diagnosis was 55.4 years old for Hispanic patients.

“Quality and disparities data can be used together to target interventions.”37

HOSPITAL DATA

MARYLAND HEALTH IMPROVEMENT AND DISPARITIES REDUCTION ACT OF 2012

Policies such as the Maryland Health Improvement and Disparities Reduction Act of 2012 recently signed into law on April 2012 by Governor Martin O ’ M alley aim to reduce health disparities in our communities. Under the new law, community-based organizations can submit proposals to the Maryland Department of Health and Mental Hygiene and the Community Health Resources Commission asking to designate certain underserved areas as Health Enterprise Zones ( HEZs ) . Once designated, incentives will be provided within the HEZ to primary care practitioners, community-based organizations and/or local health departments to expand access to care, improve health, and promote equity. An important goal of this act is to reduce rates of chronic and often preventable illnesses. By passing this legislation, Maryland is taking important steps to change current trends and improve health for all of our state ’ s residents.

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QUALITY IMPROVEMENT SHOULD INHERENTLY INCLUDE EFFORTS TO REDUCE AND eliminate racial and ethnic health disparities in health care. As discussed earlier in the Introduction of this report, AHRQ releases the NHQR and NHDR annually to highlight the importance of integrating activities to improve quality and reduce disparities. The U.S. has become increasingly diverse such that the overall health status of many Americans essentially reflects that of nonwhite minority populations. A large number of minorities suffer from chronic diseases that are largely preventable such as hypertension and diabetes.39-41 Moreover, the cost of treating these diseases is high. A study by LaVeist et al. ( 2009 ) for the Joint Center for Political and Economic Studies found that from 2003 –2006, close to 31% of direct medical care expenses for African Americans, Asians, and Hispanics were due to health inequalities.42 Health disparities accounted for almost $230 billion in direct costs. Once indirect costs were also factored in ( e.g., premature death and loss of productivity and wages ) , health disparities accounted for $1.24 trillion during the same period. Focusing on improving the health outcomes of minority populations should be a priority. Reducing health disparities will have an impact on all Americans as we focus on improving healthcare quality, promoting health equity, and reducing the cost of health care across the nation. Data Source The data for these measures were extracted from Quantros, the vendor that Adventist HealthCare uses to manage information related to the reporting of quality core measures. Due to a mid-year changeover in vendors, information was only available from the third quarter of 2011 forward. Earlier information from the previous vendor was not available. Quantros does not abstract and continue to record data for core measures that have been discontinued. This is worth noting because a number of the core measures from previous years were discontinued as of January, 2012. On the other hand,

2. Inpatient Clinical Quality Indicators ROBERT WOOD JOHNSON FOUNDATION QUALITY IMPROVEMENT COLLABORATIVE

Siegel et al. ( 2 012 ) report results from a collaborative program where 10 hospitals with large minority populations monitored the quality of care provided to patients during a one-year period.38 A main focus of the Expecting Success: Excellence in Cardiac Care project was standardized collection of patient race, ethnicity, and language information and analysis of quality data by these demographic characteristics. Within the first 6 months of the collaborative, there were significant disparities found at three of the hospitals for a primary diagnosis of acute myocardial infarction ( A MI ) and/or heart failure ( HF ) for Black vs. While patients ( AMI and HF ) and for Hispanic vs. non-Hispanic patients ( H F ) . However, by the end of the collaborative ( final 6 months ) the disparities disappeared in all cases, indicating that the quality of care improved for patients. Overall findings revealed improvements in the quality of care provided to patients at 7 out of 10 hospitals. Patient race, ethnicity, and language data collection is important to monitor and improve quality of care at hospitals with diverse patient populations.

28 | HOSPITAL DATA

new measures in a number of new categories are being introduced at the same time. Thus, the contents of this portion of the report may change significantly from year to year. After the percentages were calculated, a chi-square analysis was performed to test the statistical significance of differences by race and ethnicity. There had to be at least 25 patients per cell for a test to be statistically valid. This data represents a sample from the patient population. Therefore, when the data are stratified by race and/or ethnicity, it reduces the sample size. Also, for some of the items, race or ethnicity data may be missing. These limitations must be considered when examining the findings presented here.

QUALITY INDICATORS: Shady Grove Adventist Hospital Table 7 shows quality indicators in four core areas—pneumonia, heart failure, acute myocardial infarction, and surgical care—for the 6-month period between July and December 2011. For additional information see, http://mhcc.maryland.gov/consumerinfo/hospitalguide/hospital_ guide/reports/find _a _quality _measure/index.asp?currentStatus=H. The overall facility score for each indicator is provided, as well as the percentage when stratified by patient race. Data for patients who identified as American Indian/Alaskan Native or Native Hawaiian/Pacific Islander are not included because of extremely small sample size. There were no statistically significant differences by race for any of the indicators.

CASE STUDY: MONTGOMERY COUNTY HOSPITAL CARE EQUITY INITIATIVE

In 2008 –2009, the Engelberg Center for Health Care Reform at the Brookings Institution—in collaboration with Adventist HealthCare and other Montgomery County hospitals—collected patient race, ethnicity, and language data in order to build their capacity to examine local health disparities, measure racial/ethnic healthcare equity, and enhance healthcare quality improvement efforts. The Montgomery County Hospital Care Equity Initiative ( MCHCEI ) was designed to provide a model for aggregating regional hospital performance data in order to measure and monitor health disparities at the local level. The goals of the program were to:

• Improve patient demographic data collection in order to accurately quantify racial and ethnic disparities in health care

• Engage and communicate with the hospital and broader public health community and race and ethnicity data collection and use, and

• Build greater collaboration among community stakeholders to address disparities in health care.

Five Montgomery County hospitals participated in this initiative, including Shady Grove Adventist Hospital and Washington Adventist Hospital. The process of care quality measures selected for inclusion included those already required to be reported to the Maryland Health Services Cost Review Commission: pneumonia, heart failure, acute myocardial infarction, and surgical care. Results of this project were published and discussed at the High Value HealthCare conference in March 2010.43

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SHADY GROVE ADVENTIST HOSPITAL

MEASURE

July - December, 2011

Numeratora Denominatora Facility Asian

Black/African

American White Pneumonia (PN)

Overall Pneumonia Care 417 430 97.0% 96.2% 97.9% 96.8% PN-2 Pneumococcal Vaccination 83 91 91.2% 83.3% 100.0% 89.8% PN-3a Blood Culture Performed Before or After ICU Arrival 157 158 99.4% 100.0% 100.0% 99.0% PN-3b - Blood Cultures Obtained in ED Prior to 1st Antibiotic 107 107 100.0% 100.0% 100.0% 100.0% PN-4 Adult Smoking Cessation Advice/Counseling 138 138 100.0% 100.0% 100.0% 100.0% PN-5c Initial Antibiotic Received w/i 6 Hours of Hospital Arrival 94 97 96.9% 100.0% 95.7% 96.8% PN-6 Antibiotics for CAP in Immunocompetent Patients 119 119 100.0% 100.0% 100.0% 100.0% PN-7 Influenza Vaccine 108 113 95.6% 100.0% 92.0% 95.9%

Heart Failure (HF) Overall Heart Failure Care 244 248 98.4% 100.0% 100.0% 97.6% HF-1 Discharge Instructions 122 136 89.7% 100.0% 86.7% 89.8% HF-2 LVF Assessment 36 36 100.0% 100.0% 100.0% 100.0% HF-3 ACEI or ARB for LVSD 244 248 98.4% 100.0% 100.0% 97.6% HF-4 Adult Smoking Cessation Advice/Counseling 328 328 100.0% 100.0% 100.0% 100.0%

Acute Myocardial Infarction (AMI) Overall AMI Care 350 354 98.9% 96.4% 100.0% 99.1% AMI-1 Aspirin at Arrival 30 30 100.0% 100.0% 100.0% 100.0% AMI-2 Aspirin Prescribed at Discharge 56 56 100.0% 100.0% 100.0% 100.0% AMI-3 ACEI or ARB for LVSD 112 112 100.0% 100.0% 100.0% 100.0% AMI-4 Adult Smoking Cessation Advice/Counseling 104 104 100.0% 100.0% 100.0% 100.0% AMI-5 Beta Blocker Prescribed at Discharge 50 50 100.0% 100.0% 100.0% 100.0%

AMI-8a Primary PCI Received w/i 90 Minutes of Hospital Arrival 102 106 96.2% 90.9% 100.0% 96.9% AMI-10 Statin Prescribed at Discharge 54 54 100.0% 100.0% 100.0% 100.0%

Surgical Care Improvement Project (SCIP) Overall SCIP Care 1468 1510 97.2% 91.7% 97.3% 98.0% SCIP-Inf-1a Prophylactic Antibiotic w/i 1 Hour Prior to Surgical Incision 260 268 97.0% 100.0% 97.1% 96.6% SCIP-Inf-2a Prophylactic Antibiotic Selection for Surgical Pa-tients 254 256 99.2% 100.0% 100.0% 98.8% SCIP-Inf-3a Prophylactic Antibiotics Discontinued w/i 24 Hours After Surgery End Time 266 276 96.4% 100.0% 94.3% 96.7% SCIP-Inf-6 Surgery Patients with Appropriate Hair Removal 48 48 100.0% 100.0% 100.0% 100.0% SCIP-Inf-9 Urinary Catheter Removed Postoperative Day (POD) 1 or POD 2 210 210 100.0% 100.0% 100.0% 100.0% SCIP-Inf-10 Surgery Patients with Perioperative Temperature Management 6 6 100.0% 100.0% 100.0% 100.0% SCIP-Card-2 Surgery Patients on Beta-Blocker Prior to Arrival Who Received Beta-Blocker During the Perioperative Period 436 436 100.0% 100.0% 100.0% 100.0% SCIP-VTE-1 Surgery Patients with Recommended VTE Prophy-laxis Ordered 102 112 91.1% 50.0% 92.9% 97.2% SCIP-VTE-2 Surgery Patients who Received Appropriate VTE Prophylaxis 102 114 89.5% 50.0% 92.9% 94.6%

Table 7. Inpatient Quality Measures by Race for Shady Grove Adventist Hospital

30 | HOSPITAL DATA

SHADY GROVE ADVENTIST HOSPITAL

MEASURE July - December, 2011

Numeratora Denominatora Facility Non-

Hispanic Hispanic

Pneumonia (PN)

Overall Pneumonia Care 481 496 97.0% 97.0% 96.9% PN-2 Pneumococcal Vaccination 95 103 92.2% 92.8% 83.3% PN-3a Blood Culture Performed Before or After ICU Arrival 179 180 99.4% 99.4% 100.0% PN-3b - Blood Cultures Obtained in ED Prior to 1st Antibiotic 123 124 99.2% 99.1% 100.0% PN-4 Adult Smoking Cessation Advice/Counseling 162 162 100.0% 100.0% 100.0% PN-5c Initial Antibiotic Received w/i 6 Hours of Hospital Arrival 108 113 95.6% 97.1% 75.0% PN-6 Antibiotics for CAP in Immunocompetent Patients 135 135 100.0% 100.0% 100.0% PN-7 Influenza Vaccine 128 134 95.5% 95.1% 100.0%

Heart Failure (HF) Overall Heart Failure Care 256 260 98.5% 98.3% 100.0% HF-1 Discharge Instructions 132 148 89.2% 88.2% 100.0% HF-2 LVF Assessment 38 38 100.0% 100.0% 100.0% HF-3 ACEI or ARB for LVSD 256 260 98.5% 98.3% 100.0% HF-4 Adult Smoking Cessation Advice/Counseling 344 344 100.0% 100.0% 100.0%

Acute Myocardial Infarction (AMI) Overall AMI Care 354 358 98.9% 98.8% 100.0% AMI-1 Aspirin at Arrival 30 30 100.0% 100.0% 100.0% AMI-2 Aspirin Prescribed at Discharge 56 56 100.0% 100.0% 100.0% AMI-3 ACEI or ARB for LVSD 116 116 100.0% 100.0% 100.0% AMI-4 Adult Smoking Cessation Advice/Counseling 106 106 100.0% 100.0% 100.0% AMI-5 Beta Blocker Prescribed at Discharge 50 50 100.0% 100.0% 100.0% AMI-8a Primary PCI Received w/i 90 Minutes of Hospital Arrival 102 106 96.2% 96.0% 100.0% AMI-10 Statin Prescribed at Discharge 54 54 100.0% 100.0% 100.0%

Surgical Care Improvement Project (SCIP) Overall SCIP Care 1584 1626 97.4% 97.4% 97.9% SCIP-Inf-1a Prophylactic Antibiotic w/i 1 Hour Prior to Surgical Incision 280 288 97.2% 97.0% 100.0% SCIP-Inf-2a Prophylactic Antibiotic Selection for Surgical Patients 274 276 99.3% 99.2% 100.0% SCIP-Inf-3a Prophylactic Antibiotics Discontinued w/i 24 Hours After Surgery End Time 286 296 96.6% 97.1% 90.0% SCIP-Inf-6 Surgery Patients with Appropriate Hair Removal 54 54 100.0% 100.0% 100.0% SCIP-Inf-9 Urinary Catheter Removed Postoperative Day (POD) 1 or POD 2 230 230 100.0% 100.0% 100.0% SCIP-Inf-10 Surgery Patients with Perioperative Temperature Manage-ment 6 6 100.0% 100.0% n.a. SCIP-Card-2 Surgery Patients on Beta-Blocker Prior to Arrival Who Received Beta-Blocker During the Perioperative Period 470 470 100.0% 100.0% 100.0% SCIP-VTE-1 Surgery Patients with Recommended VTE Prophylaxis Ordered 110 120 91.7% 91.5% 100.0% SCIP-VTE-2 Surgery Patients who Received Appropriate VTE Prophy-laxis 110 122 90.2% 90.0% 100.0%

Table 8. Inpatient Quality Measures by Ethnicity for Shady Grove Adventist Hospital

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Table 8 shows the same quality indicators, stratified by patient ethnicity. There were no statistically significant differences by ethnicity for any of the indicators. QUALITY INDICATORS: Washington Adventist Hospital Table 9 shows the quality indicators at WAH, stratified by patient ethnicity. There were no significant differences in the indicators for pneumonia or heart failure. There were two differences in indicators for surgical care: both Asian and Black patients appeared less likely than White patients to have perioperative temperature management, and Black patients appeared less likely than Asian or White patients to have recommended venous thromboembolism ( VTE ) prophylaxis ordered . Again, further analysis is required to determine the reason why this difference exists. These findings may be due to systematic differences in the way data were recorded and/or reported, rather than actual differences in compliance with the process of care measure and/or disparate treatment across groups. Table 10 shows the quality measures by ethnicity for WAH. There were no statistical differences in any of the indicators.

A ROADMAP FOR HOSPITALS

The Joint Commission developed a roadmap for hospitals to help them ensure the provision of high-quality health care incorporating effective communication, cultural competence, and patient- and family-centered care practices throughout the continuum of care. Advancing Effective Communication, Cultural Competence and Patient-and-Family-Centered Care describes methods for hospitals to begin or improve upon their efforts to ensure that all patients receive the same high quality care during admission, assessment, treatment, end-of-life care, and discharge and transfer.44 For more information, see http://www.jointcommission.org/assets/1/6/aroadmapforhospitalsfinalversion727.pdf.

32 | HOSPITAL DATA

WASHINGTON ADVENTIST HOSPITAL

MEASURE

July - December, 2011

Numeratora Denominatora Facility Asian

Black/African

American White

Pneumonia (PN)

Overall Pneumonia Care 363 364 99.7% 100.0% 100.0% 99.1% PN-2 Pneumococcal Vaccination 86 86 100.0% 100.0% 100.0% 100.0% PN-3a Blood Culture Performed Before or After ICU Arrival 115 115 100.0% 100.0% 100.0% 100.0% PN-3b - Blood Cultures Obtained in ED Prior to 1st Antibiotic 80 81 98.8% 100.0% 100.0% 95.8% PN-4 Adult Smoking Cessation Advice/Counseling 109 110 99.1% 100.0% 98.5% 100.0% PN-5c Initial Antibiotic Received w/i 6 Hours of Hospital Arrival 76 77 98.7% 100.0% 98.0% 100.0% PN-6 Antibiotics for CAP in Immunocompetent Patients 101 101 100.0% 100.0% 100.0% 100.0% PN-7 Influenza Vaccine 96 96 100.0% 100.0% 100.0% 100.0%

Heart Failure (HF)

Overall Heart Failure Care 212 214 99.1% 100.0% 100.0% 97.6% HF-1 Discharge Instructions 104 124 83.9% 100.0% 79.5% 90.9% HF-2 LVF Assessment 46 48 95.8% n.a. 91.7% 100.0% HF-3 ACEI or ARB for LVSD 212 214 99.1% 100.0% 100.0% 97.6% HF-4 Adult Smoking Cessation Advice/Counseling 324 324 100.0% 100.0% 100.0% 100.0%

Acute Myocardial Infarction (AMI)

Overall AMI Care 618 624 99.0% 100.0% 98.4% 99.3% AMI-1 Aspirin at Arrival 10 12 83.3% 100.0% 75.0% 100.0% AMI-2 Aspirin Prescribed at Discharge 28 30 93.3% 100.0% 85.7% 100.0% AMI-3 ACEI or ARB for LVSD 252 252 100.0% 100.0% 100.0% 100.0% AMI-4 Adult Smoking Cessation Advice/Counseling 234 234 100.0% 100.0% 100.0% 100.0% AMI-5 Beta Blocker Prescribed at Discharge 36 38 94.7% 100.0% 100.0% 87.5% AMI-8a Primary PCI Received w/i 90 Minutes of Hospital Arrival 292 292 100.0% 100.0% 100.0% 100.0% AMI-10 Statin Prescribed at Discharge 30 34 88.2% 100.0% 75.0% 100.0%

Surgical Care Improvement Project (SCIP)

Overall SCIP Care 1392 1458 95.5% 96.6% 94.9% 96.0% SCIP-Inf-1a Prophylactic Antibiotic w/i 1 Hour Prior to Surgical Incision 172 182 94.5% 100.0% 93.6% 94.3% SCIP-Inf-2a Prophylactic Antibiotic Selection for Surgical Patients 164 170 96.5% 88.9% 97.7% 96.9% SCIP-Inf-3a Prophylactic Antibiotics Discontinued w/i 24 Hours After Surgery End Time 174 182 95.6% 100.0% 95.7% 94.4% SCIP-Inf-6 Surgery Patients with Appropriate Hair Removal 40 40 100.0% 100.0% 100.0% 100.0% SCIP-Inf-9 Urinary Catheter Removed Postoperative Day (POD) 1 or POD 2 184 200 92.0% 90.9% 93.0% 90.6% SCIP-Inf-10 Surgery Patients with Perioperative Temperature Management 156 162 96.3% 75.0% 93.9% 100.0% SCIP-Card-2 Surgery Patients on Beta-Blocker Prior to Arrival Who Received Beta-Blocker During the Perioperative Period 318 336 94.6% 92.3% 96.5% 92.9% SCIP-VTE-1 Surgery Patients with Recommended VTE Prophy-laxis Ordered 262 270 97.0% 100.0% 94.1% 100.0% SCIP-VTE-2 Surgery Patients who Received Appropriate VTE Prophylaxis 262 278 94.2% 100.0% 91.4% 96.7%

Table 9. Inpatient Quality Measures by Race for Washington Adventist Hospital

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WASHINGTON ADVENTIST HOSPITAL

MEASURE July - December, 2011

Numeratora Denominatora Facility Non-

Hispanic Hispanic

Pneumonia (PN) Overall Pneumonia Care 364 365 99.7% 99.7% 100.0% PN-2 Pneumococcal Vaccination 86 86 100.0% 100.0% 100.0% PN-3a Blood Culture Performed Before or After ICU Arrival 116 116 100.0% 100.0% 100.0% PN-3b - Blood Cultures Obtained in ED Prior to 1st Antibiotic 80 81 98.8% 98.6% 100.0% PN-4 Adult Smoking Cessation Advice/Counseling 110 111 99.1% 99.0% 100.0% PN-5c Initial Antibiotic Received w/i 6 Hours of Hospital Arrival 76 77 98.7% 98.6% 100.0% PN-6 Antibiotics for CAP in Immunocompetent Patients 101 101 100.0% 100.0% 100.0% PN-7 Influenza Vaccine 97 97 100.0% 100.0% 100.0%

Heart Failure (HF) Overall Heart Failure Care 212 214 99.1% 98.9% 100.0% HF-1 Discharge Instructions 104 124 83.9% 84.3% 81.8% HF-2 LVF Assessment 46 48 95.8% 94.7% 100.0% HF-3 ACEI or ARB for LVSD 212 214 99.1% 98.9% 100.0% HF-4 Adult Smoking Cessation Advice/Counseling 328 328 100.0% 100.0% 100.0%

Acute Myocardial Infarction (AMI) Overall AMI Care 698 704 99.1% 99.1% 100.0% AMI-1 Aspirin at Arrival 10 12 83.3% 80.0% 100.0% AMI-2 Aspirin Prescribed at Discharge 30 32 93.8% 92.3% 100.0% AMI-3 ACEI or ARB for LVSD 286 286 100.0% 100.0% 100.0% AMI-4 Adult Smoking Cessation Advice/Counseling 268 268 100.0% 100.0% 100.0% AMI-5 Beta Blocker Prescribed at Discharge 40 42 95.2% 95.0% 100.0% AMI-8a Primary PCI Received w/i 90 Minutes of Hospital Arrival 332 332 100.0% 100.0% 100.0% AMI-10 Statin Prescribed at Discharge 34 38 89.5% 88.2% 100.0%

Surgical Care Improvement Project (SCIP) Overall SCIP Care 1428 1496 95.5% 95.6% 94.7% SCIP-Inf-1a Prophylactic Antibiotic w/i 1 Hour Prior to Surgical Incision 176 186 94.6% 93.6% 100.0% SCIP-Inf-2a Prophylactic Antibiotic Selection for Surgical Patients 168 174 96.6% 97.2% 93.3% SCIP-Inf-3a Prophylactic Antibiotics Discontinued w/i 24 Hours After Sur-gery End Time 178 186 95.7% 96.1% 93.8% SCIP-Inf-6 Surgery Patients with Appropriate Hair Removal 40 42 95.2% 94.4% 100.0% SCIP-Inf-9 Urinary Catheter Removed Postoperative Day (POD) 1 or POD 2 190 206 92.2% 90.5% 100.0% SCIP-Inf-10 Surgery Patients with Perioperative Temperature Manage-ment 160 166 96.4% 96.1% 100.0% SCIP-Card-2 Surgery Patients on Beta-Blocker Prior to Arrival Who Re-ceived Beta-Blocker During the Perioperative Period 326 344 94.8% 95.1% 92.9% SCIP-VTE-1 Surgery Patients with Recommended VTE Prophylaxis Or-dered 270 278 97.1% 97.5% 94.4% SCIP-VTE-2 Surgery Patients who Received Appropriate VTE Prophy-laxis 270 286 94.4% 94.4% 94.4%

Table 10. Inpatient Quality Measures by Ethnicity for Washington Adventist Hospital

34 | HOSPITAL DATA

HOSPITALIZATION RATES ARE OFTEN HIGHER FOR INDIVIDUALS FROM LOW-INCOME communities compared to those living in high-income communities. The Agency for Healthcare Research and Quality evaluated the national frequency and costs of preventable hospitalizations and found that rates of hospitalization for all 12 adult medical conditions evaluated were higher for patients residing in the lowest-income communities than for those living in the highest-income communities.45 Hospital readmission rates, as well, can vary depending on several factors, including income, race, health condition, hospital, patient case mix, state laws and Medicare coverage. A study published in the Journal of the American Medical Association reported that one in five Medicare patients were readmitted to a hospital 30 days after discharge. When the researchers analyzed the data by race, they found that older African-American individuals had 13% greater odds of being readmitted than older people from other races.46 One of the provisions in the health care reform law ( discussed above ) addresses the issue of readmissions. Starting in federal fiscal year ( FFY ) 2013, hospitals across the country will see their reimbursements affected by higher than expected readmission rates. Initially, this provision will focus on readmissions related to heart failure, acute myocardial infarction, and pneumonia. The Centers for Medicare and Medicaid Services ( CMS) may withhold up to 1% of all inpatient Medicare payments in FFY 2013, up to 2 % in FFY 2014, and up to 3% in FFY 2015. Also starting in FFY 2015, these changes will extend to other conditions, including chronic obstructive pulmonary disease and coronary bypass grafting. In preparation for these changes, hospitals must have a strong understanding of which patients have an increased likelihood for readmission. Addressing racial disparities such as those observed in the Joynt et al. study described above will improve overall admission rates, thereby reducing the penalty to be incurred from the provisions outlined in the ACA. Although we focus on race in this report, other socio-demographic factors, such as income, payer ( insurance ) status, or zip code, may also provide valuable insight into likelihood of readmission. Hospitals can then use this information to collaborate with community partners and develop innovative programs to reduce potentially preventable hospital readmissions for these serious conditions. Data Sources Data for the readmissions calculations come from an internal Adventist HealthCare readmissions database. The readmission rates were calculated using a methodology similar to the Maryland HSCRC ’ s Admission-Readmission Revenue ( ARR) arrangement. The source of the data was our ARR Readmission Database ( includes readmissions back to the same hospital ) . We started with 2011 discharges excluding one-day stays and patients that died during the year and had no discharge prior to death. The patients in the heart failure and acute myocardial infarction readmission rate calculations were identified by their All-Patient-Refined Diagnosis Related Group ( APR-DRG ) classification: 194 ( heart failure ) or 190 ( acute myocardial infarction ) .

3. Hospital Readmission Rates

| 35 HOSPITAL DATA

The numerator and denominator for each calculation were identified as follows:

• All Cause Numerator: Readmission within 30 days, Denominator: 2011 Discharges as described above.

• Heart Failure APR 194

Numerator: Readmissions following a HF discharge, Denominator: 2011 HF Discharges as described above.

• Acute Myocardial Infarction APR 190

Numerator: Readmissions following an AMI discharge, Denominator: 2011 AMI Discharges as described above.

Also, for some patients, race/ethnicity data was unknown or missing. It is important to emphasize that these are exploratory analyses. These simple calculations are intended to demonstrate one approach for identifying patients most at risk for readmission following discharge. Hospitals may consider other new and innovative methods to identify and support patients at high risk for readmission, especially in light of new reimbursement policies. Adventist HealthCare uses case management application software to monitor patients who are readmitted. Case managers work with and refer high-risk patients to available resources in their community to prevent future readmissions. In some cases, a hospital readmission may be appropriate and unavoidable. However, in other cases, a readmission may be potentially preventable. Potentially preventable readmissions can occur due to lack of follow-up care coordination, medical errors or adverse events, poor patient adherence to medical recommendations, or poor communication. These factors must be considered when examining the findings presented here.

Republished from Todd Bigelow Photography

36 |

Race or Ethnicity All Cause 30-day Readmission Rate

HF 30-day Re-admission Rate

AMI 30-day Re-admission Rate

Hispanic 4.9% 36.0% 25.0%

Asian/non-Hispanic 4.6% 8.7% 6.3%

Black/non-Hispanic 8.2% 23.6% 20.0%

White/non-Hispanic 7.2% 14.0% 21.0%

HOSPITAL DATA

READMISSIONS: Shady Grove Adventist Hospital Table 11 shows all-cause 30-day readmission, as well as readmission rates for heart failure and acute myocardial infarction. The overall all-cause 30-day readmission rate for SGAH patients was 6.5%. All-cause readmissions stratified by race/ethnicity ranged from 4.6% to 8.2%. Table 11. All Cause, Heart Failure, and AMI 30-Day Readmission Rates at SGAH for 2011 by Race/Ethnicity READMISSIONS: Washington Adventist Hospital Table 12 below shows all-cause 30-day readmission, as well as readmission rates for heart failure and acute myocardial infarction at WAH in 2011. The overall all-cause 30-day readmission rate for WAH patients was 7.74%. All-cause readmissions stratified by race/ethnicity ranged from 4.2% to 10.1%. Table 12. All Cause, Heart Failure, and AMI 30-Day Readmission Rates at WAH for 2011 by Race/Ethnicity

Race or Ethnicity All Cause 30-day Readmission Rate

HF 30-day Re-admission Rate

AMI 30-day Re-admission Rate

Hispanic 4.2% 17.9% 0%

Asian/non-Hispanic 8.0% 0% 7.7%

Black/non-Hispanic 9.9% 16.4% 11.5%

White/non-Hispanic 10.1% 11.8% 0%

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MEASURING, REPORTING, AND IMPROVING PATIENT EXPERIENCES WITH CARE IS AN important part of improving healthcare quality. A recent brief from the Robert Wood Johnson Foundation ( R WJF ) notes that data about patients ’ experiences in the healthcare system and interactions with providers are concrete and actionable. These data provide useful, patient-centered information for improving aspects of care that patients value. As discussed earlier, patient-centeredness is one of six key areas of healthcare quality improvement.47 Achieving these six aims is an integral part of Adventist HealthCare’ s strategy for attaining performance excellence by being transparent ( e .g., disclosing errors and reporting lessons learned internally and publicly ) and accountable for continuous improvement of safety ( p rocesses, practices, and results ) .

The use of existing validated instruments for measuring patient experience ( e.g., Consumer Assessment of Healthcare Providers and Systems or CAHPS ) is a critical tool for identifying patient-level and system-level issues, assessing effectiveness at meeting targets, and implementing actions that lead to improvements. HealthStream ( HSTM, a provider of software for the healthcare industry ) collects data from Adventist HealthCare hospital inpatients using the Hospital Consumer Assessment of Healthcare Providers and Systems ( HCAHPS ) Survey. Survey responses are shared with the Centers of Medicare and Medicaid Services ( CMS) , who in turn reports them to the public via Hospital Compare ( see www.hospitalcompare.hhs.gov ) . Quality and CAHPS data, may be used to improve the quality of care and experiences with healthcare providers throughout the continuum of care. Because of the diversity of our patient populations and the pervasive health disparities among people in the communities we serve, it is critical that we examine both quality and patient experience information stratified by race and ethnicity. There are studies that examine differences in patient experiences by race and ethnicity using validated measures such as CAHPS.49 Compared with whites, non-white patients are more likely to report problems with receiving care and being respected ( Latino patients ) , provider responsiveness, and communicating with providers ( African American patients ) .50-51 However, Latino and African Americans provide higher overall ratings of care. A number of factors such as age, health literacy, health status, and race/ethnicity or cultural beliefs can affect ratings of care.52 More research is

4. Patient Experience ( H CAHPS and Language Access/Interpreter Services )

HOSPITAL DATA

THE CASE OF ACUTE MYOCARDIAL INFARCTION

In a study by Fremont et al. ( 2001 ) , acute myocardial infarction ( A MI ) patients who reported more problems with care were more likely to have poor health outcomes one month and 12-months post-discharge than patients who reported fewer problems. The same study showed that good primary care experience mediates the effects of poor inpatient experience for patients hos-pitalized for AMI.48

38 |

needed to determine whether differences in ratings stem from actual differences in quality of care or from differences in patient perceptions, expectations or response styles.53 For instance, some Latino and Asian cultural beliefs include being respectful and giving deference to physicians, which can lead to higher ratings. Blacks or African Americans, who have suffered historical injustices and institutional discrimination in healthcare settings may rate their overall care better than other groups because they have lower expectations of care in the first place. Data Source The data for this analysis comes from the HealthStream Insights Online database, which contains responses from the HCAHPS Survey. We analyzed responses to selected questions from patients who were discharged from SGAH and WAH between January and December 2011. The percentages represent the top box score, which is the percent of patients who responded with the highest rating ( i .e., if 5 is the highest rating on a scale of 1 to 5, the percentage of patients who responded “ 5 ” ) . The columns HSTM are the top box scores that represent the 50th percentile of national hospitals in the HealthStream ( HSTM) database. These data represent a sample from the inpatient population. Therefore, when the data are stratified by race and/or ethnicity, it reduces the sample size. For Native Hawaiian/Pacific Islanders and American Indians/Alaskan Natives, the adjusted Ns were typically low, less than 100. These results are not presented here. The sample size may also vary by question, as some patients may have declined to answer certain questions. Also, for some of the patients, race or ethnicity data may be missing.

As quoted by Denice Cora-Bramble, MD, MBA, “Measures evaluating patient engagement and experience are essential to eliminating disparities and supporting culturally competent care for all patients.”54

HOSPITAL DATA

PATIENT-CENTERED COMMUNICATION STANDARDS

The U.S. Department of Health and Human Services’ Office of Minority Health developed the Culturally and Linguistically Appropriate Services (CLAS) Standards to ensure that all people entering the healthcare system receive equitable and effective treatment in a culturally and linguistically appropriate manner. The Joint Commission’s patient-centered communication standards require documentation of patient information, particularly a patient’s communication needs such as preferred language for discussing health care, as well as other important patient information. Hospitals’ ability to effectively and proactively comply with such mandates has a positive impact on the bottom line. Adventist HealthCare has culturally and linguistically appropriate services policies on proper documentation of a patient’s language (including sign language) and the use of interpreter services in order to comply with federal law and regulatory requirements (AHC Policy #1.14).

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HCAHPS: Shady Grove Adventist Hospital Table 13 shows the responses to selected HCAHPS questions from inpatients discharged in 2011. The columns titled All SGAH Patients and HSTM Top Box % show the top box percentages for SGAH and the 50% percentile of the HealthStream database, respectively; the HSTM Top Box percentages may be considered a benchmark of national hospitals. The columns titled White Patients, Black Patients, and Asian Patients show the top box percentages in response to each question; a patient may only be included in more than one of these columns if he or she identified as multi-racial. The column titled Hispanic patients is highlighted separately because ethnicity was a separate question from race. Therefore race and ethnicity are not mutually exclusive in this table. That is, a patient who identified himself as both Black and Hispanic is included in both columns in the table below. Table 13. Selected Responses to HCAHPS Questions for Patients Discharged from SGAH in 2011, by

Patient Race and Ethnicity

* Percents averaged across all persons self-identifying as of Hispanic or Latino origin. Includes Puerto Ricans, Mexicans, Mexican-Americans, Chicanos, Cubans, and others.

All SGAH Patients ( % Top

Box )

White Patients ( % Top

Box )

Black Patients ( % Top

Box )

Asian Patients ( % Top

Box )

Hispanic Patients* ( % Top

Box )

HSTM Top

Box %

Likely to Recommend 65.9 63.0 61.3 75.2 76.0 72.7 Overall rating of hospital 56.7 54.1 56.3 51.9 68.8 68.6 Courtesy of Doctors 81.3 79.0 86.2 80.4 88.2 87.4 Doctors listen carefully 74.4 70.3 79.1 77.4 82.9 80.0 Clear communication by doctors

72.1 68.9 78.5 75.0 79.2 76.4

Courtesy of Nurses 78.1 74.4 80.3 76.4 81.5 85.2 Nurses Listen carefully 67.2 62.6 71.3 73.7 76.6 76.7 Clear communication by nurses

68.1 66.0 72.4 68.4 71.5 74.9

Talking about help after discharge

76.7 75.1 76.0 80.7 78.1 82.3

Providing written discharge instructions

85.4 84.5 86.0 86.3 88.7 87.1

HOSPITAL DATA

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HCAHPS: Washington Adventist Hospital Table 14 shows the responses of inpatients discharged from WAH in 2011 to selected HCAHPS questions.

Table 14. Selected Responses to HCAHPS Questions for Patients Discharged from WAH in 2011, by

Patient Race and Ethnicity

* Percents averaged across all persons self-identifying as of Hispanic or Latino origin. Includes Puerto Ricans, Mexicans, Mexican-Americans, Chicanos, Cubans, and others.

HOSPITAL DATA

All WAH ( % Top

Box )

White Patients ( % Top

Box )

Black Patients ( % Top

Box )

Asian Patients ( % Top

Box )

Hispanic Patients* ( % Top

Box )

HSTM Top

Box %

Likely to Recommend 67.9 68.5 68.8 66.7 65.1 72.7

Overall rating of hospital 61.3 61.0 62.6 60.3 60.7 68.6

Courtesy of Doctors 84.4 82.9 84.7 79.7 91.8 87.4

Doctors listen carefully 77.5 71.7 81.7 78.1 85.9 80.0

Clear communication by doctors

77.0 73.0 78.1 84.4 83.5 76.4

Courtesy of Nurses 81.2 79.4 85.2 76.3 75.6 85.2

Nurses Listen carefully 70.5 64.5 75.8 66.2 66.7 76.7

Clear communication by nurses

69.5 66.5 73.3 63.1 75.9 74.9

Talking about help after discharge

78.6 82.9 77.2 83.1 78.2 82.3

Providing written discharge instructions

83.7 86.4 80.5 91.4 88.8 87.1

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INTERPRETER SERVICES Effective patient-provider communication is essential to providing high-quality, patient-centered care, and is necessary for patient safety. Adventist HealthCare is committed to providing care that is safe, effective, efficient, patient-centered, and equitable. With Joint Commission standards on patient-centered communication and National Quality Forum practices for measuring and reporting cultural competency, it is important that our healthcare system and hospital facilities take the necessary steps to identify and monitor patients ’ needs, care, and services at all points of contact. By some estimates, more than 25% of Hispanic, Asian, and Pacific Islander families are linguistically isolated, meaning that no member of the family older than 14 years old speaks English very well.55 Limited English proficient ( L EP ) and linguistically isolated residents often face language barriers when communicating with those outside of their community; they also present various challenges for healthcare systems in providing culturally and linguistically appropriate services for the population. A necessary response to this continuous population shift includes the provision of language services for the LEP population in different healthcare settings. The availability and use of trained and qualified interpreters throughout the care continuum is paramount to ensuring equal access to health information and crucial for treatment adherence, patient safety, and quality care.56 Studies have demonstrated that qualified and professional interpretation services improve communication between providers and LEP patients, access to care ( use of services ) , and patient satisfaction.57-60

An important component of providing high-quality care includes offering language services to patients with limited English proficiency that prefer to communicate with their provider in a language other than English. Adventist HealthCare offers several language access services. These include on-site full-time Spanish interpreters, Qualified Bilingual Staff, on-call contracted interpreters, video remote interpreting for the deaf and hard of hearing, and a telephone interpretation service that provides foreign language interpretation in over 180 different languages, 7 days a week, 24 hours a day. Figure 9 shows the languages most frequently requested for interpretation by phone at Shady Grove Adventist Hospital ( SGAH ) .61 More than 10,000 calls were made during this time period. The total call time was more than 93,000 minutes. As seen in Figure 9, the majority of the calls placed were for Spanish language interpretation, followed by Mandarin, Korean, and Russian. In addition to the languages highlighted below, calls were placed for more than 60 additional languages ( All Others, 10.5% ) , underscoring the rich diversity of the patients treated at SGAH.

“Interventions to improve patient-provider communication [have been] identified as an important strategy for addressing the numerous, documented racial and ethnic disparities in health care.”62

HOSPITAL DATA

42 |

Figure 10 shows the languages most frequently requested for interpretation by phone at WAH from July 2011 through July 2012. More than 10,000 calls were made during this time period. The total call time was more than 78,000 minutes. As seen in Figure 10, the majority of the calls placed were also for Spanish language interpretation, followed by French, Vietnamese, and Mandarin. In addition to the languages highlighted below, calls were placed for more than 40 additional languages ( All others, 5.4% ) .

Spanish, 67.0%Mandarin,

8.6%

Korean, 4.5%

Russian, 4.1%

Cantonese, 2.7%

French, 2.6%All Others, 10.5%

Figure 9. Telephone Language Interpreter Use at SGAHby Number of Calls, July 2011–July 2012

Spanish, 85.5%

French, 2.8%

Vietnamese, 1.9%

Mandarin, 1.8%

Amharic, 1.6%Korean, 1.0%

All Others, 5.4%

Figure 10. Telephone Language Interpreter Use at WAHby Number of Calls, July 2011–July 2012

HOSPITAL DATA

| 43

Conclusion and Recommendations

1. Improve patient demographic data collection and increase transparency by reporting hospital performance data by race, ethnicity, and language preference data. 2. Monitor differences in quality of care and healthcare outcomes to inform hospitals ’ strategic goals, develop community outreach programs, and target quality im-provement efforts. 3. Implement data-driven interventions to improve health-care quality and outcomes. 4. Promote the provision of culturally competent, patient-centered care.

Recommendations

| 45 RECOMMENDATIONS

THE 2012 ADVENTIST HEALTHCARE HEALTH EQUITY REPORT PRESENTS A comprehensive snapshot of the patient populations—stratified by race, ethnicity, and language—that received care at Washington Adventist Hospital ( WAH ) and Shady Grove Adventist Hospital ( S GAH ) in 2011. As 2010 Census data indicates, diversity in the Washington, D.C. metro area continues to grow, and the patient populations at these hospitals reflect the communities in which they are located. This increasing diversity underscores the value of increasing cultural awareness, knowledge, and skills of healthcare professionals and staff to promote culturally competent care and services to community residents. In addition to describing patient demographics, this report provides information about cancer diagnoses, hospital readmission rates, quality indicators, patient experiences with care, and language access/interpreter services for different populations receiving care at Adventist HealthCare hospitals. Socioeconomic factors, barriers to care, and differences in health status are just some of the factors that lead to inequalities in care among minority populations. Accurate data collection and rigorous analysis are necessary to identify the source of any differences in quality of care or healthcare outcomes by patient race, ethnicity, and preferred language within any hospital system. Patient registrars, quality coordinators, clinical staff, and other hospital employees should receive training on what patient data are collected, why it is important, and how it is used to improve quality of care for all patients. Once this is achieved, hospitals can implement data-driven interventions to improve healthcare quality and outcomes. Quality measures, readmissions, patient experience, and other data about hospital performance should be used to inform hospitals ’ strategic goals, develop community outreach programs, and target quality improvement efforts. It is crucial that senior leaders, healthcare providers, and researchers share resources and collaborate to monitor health outcomes for patients and examine differences by race, ethnicity, and language preference using evidence-based research methodologies. As mentioned earlier in this report, data limitations and other factors such as access to care and specific conditions must be carefully considered before any conclusions can be made about care quality and patient outcomes. When hospitals are open about the successes and failures of its systems ( i.e., demonstrating transparency and accountability ) , they build lasting trust and confidence among people in the communities they serve. Moreover, satisfaction increases among hospital employees who are then motivated to contribute to organizational success. Looking to the future, we will continue to examine the intersection of quality care and health equity, and report our success and challenges in eliminating health disparities with a commitment to achieving performance excellence and improving the health of our communities.

Conclusion and Recommendations

46 |

1. Leape, L.L. (2010). Transparency about performance is an essential part of improving quality of care and safety in hospitals. Perspectives on Health Reform: The Commonwealth Fund, p. 3.

2. Braveman, P. (2006). Health disparities and health equity: Concepts and measurement. Annual Review of Public Health, 27(1), 167–194.

3. Center on Health Disparities. (2007). Partnering toward a healthier future: Eliminating health disparities in Frederick, Montgomery, and Prince George’s counties in Maryland. Adventist HealthCare. Rockville, MD.

4. Center on Health Disparities. (2011). Partnering toward a healthier future: Health disparities in the era of reform implementation. Adventist HealthCare. Rockville, MD.

5. Agency for Healthcare Research and Quality. (2011). National healthcare disparities report. Rockville, MD.

6. Agency for Healthcare Research and Quality. (2011). National healthcare quality report. Rockville, MD.

7. The AHRQ Reports also include data on disparities in those 65+ years old compared to those age 18–44, and based on state of residence. None of these measures were included as examples here.

8. U.S. Bureau of the Census (2011). Profile of General Population and Housing Characteristics. Retrieved from http://planning.maryland.gov/msdc/

9. U.S. Bureau of the Census (2011). The Hispanic Population: 2010. 2010 Census Briefs. SR Ennis, M Ríos-Vargas, and NG Albert. U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census Bureau, May 2011. Retrieved from http://www.census.gov/prod/cen2010/briefs/c2010br-04.pdf.

10. Institute of Medicine. (2003). Unequal treatment: Confronting racial and ethnic disparities in health care. Washington, DC: National Academy Press.

11. Ibid. 6 12. Ibid. 4 13. Ibid. 10 14. Center on Health Disparities. (2010). Social determinants

of health: Promoting health equity through social initiatives. Adventist HealthCare. Rockville, MD.

15. Ibid. 10 16. Ponce, N., Hays, R., & Cunningham, W. (2006). Linguistic

disparities in health care access and health status among older adults. Journal of General Internal Medicine, 21(7), 786–791.

17. Carcaise-Edinboro, P., & Bradley, C.J. (2008). Influence of patient-provider communication on colorectal cancer screening. Medical Care, 46(7), 738–745.

18. Cohen, A., Rivara, F., Marcuse, E., McPhillips, H., & Davis, R. (2005). Are language barriers associated with serious medical events in hospitalized pediatric patients? Pediatrics, 116(3), 575–579.

19. Ibid. 16 20. Divi, C., Koss, R.G., Schmaltz, S.P., & Loeb, J.M. (2007).

Language proficiency and adverse events in U.S. hospitals: A pilot study. International Journal for Quality in Health Care, 19(2), 60–7.

21. Flores, G. (2006). Language barriers to health care in the United States. New England Journal of Medicine, 355(3), 229–231.

22. Schenker, Y., Wang, F., Selig, S., Ng, R., & Fernandez, A. (2007). The impact of language barriers on documentation of informed consent at a hospital with on-site interpreter services. Journal of General Internal Medicine, 22(1), 294–9.

23. National Research Council. (2004). Eliminating health disparities: Measurement and data needs. Washington, DC: The National Academies Press.

24. The federal categories that define race are American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White. The federal definitions of ethnicity are Hispanic or Latino and Non-Hispanic or Latino.

25. Andrulis, D.P., Siddiqui, N.J., Purtle, J.P., and Ducho, L. (2010). Patient Protection and Affordable Care Act of 2010: Advancing Health Equity for Racially and Ethnically Diverse Populations. Joint Center for Political and Economic Studies: Washington, DC.

26. Institute of Medicine. (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academy Press.

27. Robert Wood Johnson Foundation (RWJF) Brief. (2011). Good for Health, Good for Business: The case for measuring patient experience of care. Retrieved from http://www.rwjf.org/files/research/71848.pdf

28. Sequist, T.D., Schneider, E.C., Anastario, M., Odigie, E.G., Marshall, R., Rogers, W.H., & Safran, D. (2008). Quality monitoring of physicians: Linking patients’ experiences of care to clinical quality and outcomes. JGIM: Journal of General Internal Medicine, 23(11), 1784–1790.

29. Ibid. 27 30. Cordova, R., Beaudin, C., & Iwanabe, K. (2010).

Addressing diversity and moving toward equity in hospital care. Frontiers of Health Services Management, 26(3), 19–34.

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| 47 REFERENCES

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45. Agency for Healthcare Research and Quality. (2008). 2007 National healthcare disparities report. Rockville, MD.

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47. Ibid. 26 48. Fremont, A.M., Clearly, P.D., Hargraves, J., Rowe, R.M.,

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53. Murray-García, J, Selby, J., Schmittdiel, J., Grumbach, K., & Quesenberry, C. (2000). Racial and ethnic differences in a patient survey: Patients' values, ratings, and reports regarding physician primary care performance in a large health maintenance organization. Medical Care, 38(3), 300–310.

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55. Ibid. 18 56. Tang, G., Lanza, O., Rodriguez, F.M. (2011). The

language of diversity. Diversity Executive, 4(3), 44–47. 57. Jacobs, E., Chen, A., Karliner, L., Agger-Gupta, N., &

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58. Bernstein, J., Bernstein, E., Dave, A., Hardt, E., James, T., Linden, J., & … Safi, C. (2002). Trained medical interpreters in the emergency department: effects on services, subsequent charges, and follow-up. Journal of Immigrant Health, 4(4), 171–176.

48 |

59. Jacobs, E. A., Lauderdale, D. S., Meltzer, D., Shorey, J. M., Levinson, W., & Thisted, R. A. (2001). Impact of interpreter services on delivery of health care to limited–English-proficient patients. JGIM: Journal of General Internal Medicine, 16(7), 468–474.

60. Lee, L. J., Batal, H. A., Maselli, J. H., & Kutner, J. S. (2002). Effect of Spanish interpretation method on patient satisfaction in an urban walk-in clinic. Journal of General Internal Medicine, 17(8), 641–646.

61. AHC began its contract with a new vendor, Cyracom, in July 2011 through July 2012. The data are based on calls made to Cyracom telephone interpreters.

62. Johnson, R., Roter, D., Powe, N., & Cooper, L. (2004). Patient race/ethnicity and quality of patient-physician communication during medical visits. American Journal of Public Health, 94(12), 2084–2090.

REFERENCES

Washington Adventist Hospital ● Shady Grove Adventist Hospital Hackettstown Regional Medical Center ● Adventist Rehabilitation Hospital of Maryland

Adventist Behavioral Health ● Adventist Home Care Services ● Shady Grove Adventist Emergency Center The Regional S. Lourie Center for Infants and Young Children

Adventist HealthCare Center on Health Disparities 1801 Research Boulevard ･ Suite 300 ･ Rockville, MD 20850 ･ 301-315-3677

http://www.adventisthealthcare.com/disparities

partnering toward a healthier future - adventist healthcare · 2012-12-02 · improving the health...

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