Chapter 8. Health System Infrastructure

National Healthcare Disparities Report, 2011

In its 2010 report Future Directions for the National Healthcare Quality and Disparities Report, the Institute of Medicine (IOM, 2010) recommended that future editions of the National Healthcare Quality Report (NHQR) and National Healthcare Disparities Report (NHDR) include data on the health care system's infrastructure capabilities. According to the IOM:

[T]hese components are not necessarily health care aims/attributes in themselves, but are a means to those aims since they are elements of the health care system that better enable the provision of quality care... health systems infrastructure are of interest to the extent that they improve effectiveness, safety, timeliness, patient-centeredness, access, or efficiency.

Acknowledging that the measures and data to assess the strength and capabilities of the health care infrastructure have not been well developed, the IOM identified structural elements that may affect quality improvement. Key elements include:

  • Information systems for data collection, quality improvement analysis, and clinical communication support.
  • An adequate and well-distributed workforce.
  • Organizational capacity to support emerging models of care, cultural competence services, and ongoing improvement efforts.

Of significance, inadequacies in health system infrastructure may limit access and contribute to poor quality of care and outcomes, particularly among vulnerable population groups that include racial and ethnic minority groups and people residing in areas with health professional shortages.

This chapter presents data to understand the strength of the U.S. health system infrastructure and how this infrastructure may influence quality of care. This chapter is divided into three sections, health information technology, workforce distribution, and care management processes, each addressing a unique aspect of the health care system. The chapter begins with data to describe the adoption and use of health information technology (IT). Use of health IT can be an effective way to manage health care costs and improve the quality of care.

Since the publication of the IOM report Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare,i which emphasized the need for standardized collection and reporting of racial and ethnic data, the need for more granular detail on racial and ethnic subgroups has become apparent. This is an area where the adoption and use of health IT can be beneficial.

Another area of patient care that could be improved with the adoption and use of health IT is care coordination. A Commonwealth Fund study found that health IT can facilitate care coordination within a practice, but a lack of interoperability makes exchange of information between health care facilities difficult (Shih, et al., 2008).

Evidence has also shown that the adoption and effective use of health IT can help reduce medical errors and adverse events, enable better documentation and file organization, provide patients with information that assists their adherence to medication regimens and scheduled appointments, and assist doctors in tracking their treatment protocols (IOM, 2010).

Following presentation of measures of the use of health IT, data on health care workforce diversity are presented. An adequate supply of health care providers is an important indicator of health care quality. Aside from a provider-to-population ratio that effectively meets demand for care, it is important that the workforce be appropriately distributed.

In previous quality and disparities reports, data have been presented on diversity in the physician, nursing, dental, and pharmacy workforce. This year, the NHQR and NHDR present data on the geographic and racial/ethnic distribution of allied health professionals that include occupational and physical therapists, as well as speech-language pathologists.

The distribution and availability of a culturally competent health care workforce has significant repercussions for access to care, particularly among the Nation's most vulnerable populations—racial or ethnic minorities, low-income populations, and uninsured or underinsured people. People who cannot access health care services, either because of financial considerations or inadequacy in the local health care infrastructure, often rely on safety net providers for essential health care services. The final section presents measures related to the performance of safety net providers, including people served, characteristics of selected safety net providers, and patient outcomes.

Measures

The IOM acknowledges that health system infrastructure measures such as adoption and effective use of health IT are likely to be in the developmental stage, and evidence of the impact on quality improvement has not yet been strongly established. The IOM highlighted three infrastructure capabilities that should be further evaluated for reporting. These capabilities include adoption and use of health IT, workforce distribution and its relevance to minority and other underserved populations, and care management processes.

Findings

Health Information Technology: Focus on Electronic Health Records

According to the Office of the National Coordinator for Health IT, an electronic health record (EHR) is a real-time patient health record with access to evidence-based decision support tools that can be used to aid clinicians in decisionmaking. The EHR can automate and streamline a clinician's workflow, ensuring that all clinical information is communicated. The EHR can also support the collection of data for uses other than clinical care, such as billing, quality management, outcome reporting, and public health disease surveillance and reporting.

The IOM report Future Directions for the National Healthcare Quality and Disparities Reports (IOM, 2010) highlights the adoption and use of health IT as a tool to manage cost and improve the quality of care delivered (IOM, 2010). Meaningful use of an EHR, for instance, is increasingly viewed as essential to improving both the efficiency of service delivery and health care quality (Resnick & Alwan, 2010). The potential benefits of EHRs are not limited to hospitals and ambulatory care settings but are also valuable tools in hospice and home health agencies.

As the proportion of the population represented by older adults continues to increase, so does the need for home health and hospice care. These organizations can improve their service delivery by implementing EHRs. One area in which these benefits are evident is in the home setting, where EHRs can improve accuracy and timeliness of care documentation and facilitate preventive interventions (Resnick & Alwan, 2010).

Health providers using EHRs have reported improvement in clinical decisionmaking and communication with other providers and patients, as well as faster and more accurate access to medical records and avoidance of medical errors (Romano & Stafford, 2011). Components of EHRs, such as computerized provider order entry (CPOE) and clinical decision support (CDS), have been found to be associated with significant reductions in medication errors (Devine, et al., 2010).

CPOE systems are computer applications that allow direct electronic entry of orders for medications, laboratory, radiology, referral, and procedures. CDS encompasses a wide range of computerized tools directed at improving patient care, including computerized reminders and advice regarding drug selection, dosage, interactions, allergies, and need for subsequent orders (Kaushal, et al., 2003).

New! Electronic Health Records in Hospitals

EHRs can improve the quality and safety of care in all types of hospitals and in departments within hospitals. In emergency departments, for instance, electronic clinical documentation and decision support can help mitigate problems of treating new patients with complicated medical histories and gaps in their medical records. EHRs can also provide effective decision support and clinical reminders to facilitate a seamless transition of care by reducing communication breakdown between different providers.

The 2010 NHDR reported on medication management in hospitals, but this report tracks overall EHR use in hospitals. Overall EHR use is presented by hospital ownership because many not-for-profit hospitals serve large populations who experience health care disparities, including racial and ethnic minorities and Medicaid recipients. The Government Accountability Office found that government and not-for-profit hospitals accounted for a larger percentage of total uncompensated cost compared with for-profit hospital groups.

 

Figure 8.1. Electronic medical record use in hospitals, by hospital control and hospital type, 2009

Figure 8.1. Electronic medical record use in hospitals, by hospital control and hospital type, 2009. For details, go to [D] Text Description below.     Figure 8.1. Electronic medical record use in hospitals, by hospital control and hospital type, 2009. For details, go to [D] Text Description below.

[D] Select for Text Description.

Key: CPOE=computerized provider order entry.
Source: American Hospital Association, 2009 Information Technology Supplement.

  • Electronic Clinical Documentation:
    • Hospitals run by the Federal Government also had a much higher percentage (78%) of electronic systems that support clinical documentation than non-Federal (10%), not-for-profit (11%), and investor-owned hospitals (7%) (Figure 8.1).
    • More than 28% of children's general hospitals, 12% of psychiatric, and 12% of general medical and surgical hospitals had an electronic system that supports clinical documentation.
    • Between 6% and 9% of rehabilitation and acute long-term care hospitals had an electronic system that supports clinical documentation.
  • Decision Support:
    • A higher percentage of hospitals run by the Federal Government (70%) had fully implemented electronic decision support systems compared with non-Federal (11%), not-for-profit (18%), and investor-owned hospitals (12%).
    • More than 24% of children's general hospitals and 18% of general medical and surgical hospitals had a fully implemented electronic decision support system.
    • Between 5% and 9% of psychiatric, rehabilitation, and acute long-term care hospitals had a fully implemented electronic decision support system.
  • Computerized Provider Order Entry:
    • Hospitals run by the Federal Government had a much higher percentage (83%) of full implementation of CPOE systems compared with non-Federal (11%), not-for-profit (18%), and investor-owned hospitals (8%).
    • More than 53% of children's general hospitals, 16% of general medical and surgical hospitals, and 14% of rehabilitation hospitals had a fully implemented CPOE system. More than 13% of psychiatric hospitals and 11% of acute long-term care hospitals had full implementation of CPOE systems.
  • Results Viewing:
    • Hospitals run by the Federal Government had a much higher percentage (81%) of full implementation of results viewing systems compared with non-Federal (23%), not-for-profit (43%), and investor-owned hospitals (22%).
    • Nearly 40% of general medical and surgical (39%), 41% of children's general, 17% of acute long-term care, 14% of rehabilitation, and 7% of psychiatric hospitals had a fully implemented results viewing system.

Also, in the NHQR:

  • Hospitals with 400 beds or more had a higher percentage of electronic systems that support clinical documentation (18%) compared with hospitals with 100-399 beds (14%) and hospitals with fewer than 100 beds (9%).
  • The largest difference in implementation of decision support was observed between large and small hospitals. About 30% of hospitals with 400 beds or more had a fully implemented electronic system for decision support, but only 10% of hospitals with fewer than 100 beds had a fully implemented system. Approximately 21% of hospitals with 100-399 beds had a fully implemented electronic system for decision support.
  • The Northeast had the highest percentage of hospitals with a fully implemented CPOE system (25%). The West had 17%, the Midwest had 16%, and the South had 14%.
New! Electronic Medical Records in Home Health and Hospice Agencies

One of the challenges of providing home health and hospice care is that patients are often located in a wide geographic area and require services that have to be coordinated among several different providers. EHRs can be beneficial to home health and hospice agencies by improving the agency's ability to effectively coordinate care between multiple providers from different health disciplines.

EHRs can provide home health and hospice staff with consistent and thorough documentation, leading to improved outcomes for patients due to awareness of potential risks noted in the documentation. EHR adoption holds tremendous promise for improving health care quality and increasing patient safety, as well as reducing the costs of providing home health and hospice care. This is the first time EHR data for home health and hospice agencies are included in the reports.

 

Figure 8.2. Electronic medical record use in home health and hospice agencies, by geographic location and ownership, 2009

Figure 8.2. Electronic medical record use in home health and hospice agencies, by geographic location and ownership, 2009. For details, go to [D] Text Description below.     Figure 8.2. Electronic medical record use in home health and hospice agencies, by geographic location and ownership, 2009. For details, go to [D] Text Description below.
[D] Select for Text Description.

Key: CPOE = computerized provider order entry.
Source: Centers for Disease Control and Prevention, National Center for Health Statistics, National Home Health and Hospice Care Survey, 2009.
Note: Government agencies include city, county, State, Department of Veterans Affairs, and other Federal agencies. Data were statistically unreliable for clinical decision support systems that were located in the West and agencies that were government owned as well as for CPOE used by for-profit agencies, government-owned agencies, and agencies located in the Northeast and the West.

  • Overall Computerized System Adoption:
    • In 2007, agencies in the Midwest had a significantly higher overall percentage of providers of home health or hospice care with EHRs than agencies in the South and the West (Figure 8.2).
    • In 2007, for-profit providers of home health or hospice care had a significantly lower overall percentage of EHRs than private, not-for-profit and government providers.
  • Patient Demographics:
    • In 2007, of those organizations with an EHR system, nearly all providers of home health or hospice care in each region had EHRs that used a component for patient demographics.
    • All government providers of home health or hospice care had an EHR system with a patient demographics component. Nearly all agencies that were private, not for profit and agencies that were for profit had EHRs with a component for patient demographics.
  • Clinical Notes:
    • In 2007, of those agencies that had an EHR system, 97% of agencies in the Midwest, 82% of agencies in the West, 80% of agencies in the South, and 64% of agencies in the Northeast had an EHR system with a component for clinical notes.
    • More than 95% of agencies that are private, not for profit, 80% of agencies that are government owned, and 70% of agencies that are for profit had EHRs with a component for clinical notes.
  • Clinical Decision Support System:
    • In 2007, of those agencies that had an EHR system, 60% of agencies in the Midwest, 59% of agencies in the South, and 49% of agencies in the Northeast had EHRs with a component for clinical decision support.
    • More than 71% of private, not-for-profit providers and 40% of for-profit providers had EHRs with a component for clinical decision support.
  • Computerized Provider Order Entry:
    • In 2007, of those agencies that had an EHR system, 51% in the Midwest and 42% in the South had EHRs with a CPOE component. Nearly 46% of providers of home health or hospice care that are private, not for profit had EHRs with a CPOE component.

Also, in the NHQR:

  • In 2007, among agencies with an EHR, those with101-150 current patients had the lowest percentage of providers of home health or hospice care whose EHRs included patient demographics (96%). Of the agencies that had an EHR system, 99% of agencies with 151 or more current patients, 99.2% of agencies with 50 or fewer current patients, and 99.7% of agencies with 51-100 current patients had providers with EHR systems that had a component for patient demographics.
  • Three-quarters of agencies with 151 or more current patients, 67% of agencies with 51-100 current patients, and only 31% of agencies with 50 or fewer current patients had EHRs with a CDS component.
  • Nearly 63% of organizations that had an EHR system and 51-100 current patients, 53% of organizations with 151 or more current patients, and 38% of organizations with 50 or fewer current patients had EHRs with a component for CPOE

Workforce Diversity

According to the U.S. Census Bureau (2011), adults age 65 and over accounted for 13% (40.3 million) of the U.S. population in 2010 (Howden & Meyer, 2011). By 2050, that number will more than double to 88.5 million (20%). In 2010, the number of people age 100 and over reached 71,991, and this population is projected to grow to 601,000 by 2050 (U.S. Census Bureau, 2011).

Older adults are at increased risk of accidental falls, which are associated with reduced levels of independence, poorer quality of life, and high levels of anxiety (Hanley, et al., 2011). In 2009, 2.2 million nonfatal falls among older adults were treated in emergency departments and more than 520,000 of these patients were hospitalized (Centers for Disease Control and Prevention [CDC], 2011). Occupational and physical therapy can help patients recover from injury and can prevent falls.

Occupational therapists provide treatment to help individuals recover from injuries and regain physical function that might be lost due to injury. They also explore factors that contributed to the injury and create prevention plans tailored to each patient. Physical therapists' expertise includes screening high-risk populations such as older adults, assessing physical functions such as balance, gait, and strength, and implementing risk reduction strategies. These strategies can include development of exercise programs, selection and training in the use of assistive devices, patient education, and identification of potential risks and barriers in the patient's home.

According to CDC, three-quarters of strokes occur in people age 65 and over. Between 15% and 30% of stroke survivors are permanently disabled and suffer from paralysis and movement difficulties, sensory disturbances, language problems, thinking and memory problems, and emotional disturbances. The primary objective of speech and language pathologists is to improve quality of life by optimizing individuals' ability to communicate and swallow. Speech and language pathologists address typical and atypical areas of communication and swallowing, such as speech sound production, cognition, feeding and swallowing, and oral-motor functions. The work of speech-language pathologists is essential in helping temporarily disabled and older patients have a better quality of life.

This year, the NHDR presents the racial/ethnic distribution of occupational therapists, physical therapists, and speech-language pathologists to examine access to these vital health care services. In previous years, the percentage of each racial group represented in each workforce area was calculated and compared with the percentage of the population each racial group represented. In this year's report, the rate per 100,000 population of each racial group in each workforce area is calculated.

 

Figure 8.3. U.S. occupational therapy, physical therapy, and speech-language pathology professionals, by race and ethnicity, 2005-2009

Figure 8.3. U.S. occupational therapy, physical therapy, and speech-language pathology professionals, by race and ethnicity, 2005-2009 . For details, go to [D] Text Description below. Figure 8.3. U.S. occupational therapy, physical therapy, and speech-language pathology professionals, by race and ethnicity, 2005-2009 . For details, go to [D] Text Description below.  Figure 8.3. U.S. occupational therapy, physical therapy, and speech-language pathology professionals, by race and ethnicity, 2005-2009 . For details, go to [D] Text Description below.  Figure 8.3. U.S. occupational therapy, physical therapy, and speech-language pathology professionals, by race and ethnicity, 2005-2009 . For details, go to [D] Text Description below.  Figure 8.3. U.S. occupational therapy, physical therapy, and speech-language pathology professionals, by race and ethnicity, 2005-2009 . For details, go to [D] Text Description below.  Figure 8.3. U.S. occupational therapy, physical therapy, and speech-language pathology professionals, by race and ethnicity, 2005-2009 . For details, go to [D] Text Description below.

[D] Select for Text Description.

Key: AI/AN: American Indian or Alaska Native; NHOPI: Native Hawaiian or Other Pacific Islander.
Source: U.S. Census, American Community Survey.

  • From 2005 to 2009, non-Hispanic Whites had significantly higher rates of occupational therapists than Hispanics (Figure 8.3). Whites had significantly higher rates than all other racial groups except Asians.
  • During this period, Whites had significantly higher rates of physical therapists than Blacks, AI/ANs, and people of other and multiple races. Asians, however, had a higher rate of physical therapists than Whites in all years. Non-Hispanic Whites had significantly higher rates than Hispanics in all years.
  • Also from 2005 to 2009, Whites had significantly higher rates of speech-language pathologists than all other racial groups.

Also, in the NHQR:

  • From 2005 to 2009, the Northeast had a higher rate of occupational therapists than the South and the West in all years.
  • The Northeast also had a significantly higher rate of physical therapists than all other regions in all years.

Care Management Processes: Focus on the Health Care Safety Net

Concern about growing physician and health workforce shortages has increased over the past decade. According to the Health Resources and Services Administration, by 2020, the United States will experience a shortage of about 100,000 physicians and 1 million nurses.ii In his seminal work on health care quality, Donabedian (1980) describes a robust health care "structure"—the setting or infrastructure supporting the delivery of care (e.g., hospitals, providers)—as necessary to ensure that processes of care contribute to good outcomes. Structural deficiencies in the United States health care delivery system resulting from shortages of providers, growing demand, and a high rate of uninsurance and underinsurance have contributed to unmet need and could result in increased morbidity and health care costs.

Safety net providers play an integral role in relieving unmet need. As defined in a report sponsored by HRSA, the U.S. health care safety net is composed of "[t]hose providers that organize and deliver a significant level of health care and other health-related services to the uninsured, Medicaid, and other vulnerable populations" (IOM, 2010). Safety net providers act as a default system, or providers "of last resort," by ensuring access to care for millions of Americans lacking medical coverage or provider access, regardless of education, social status, language competency, or ability to pay.

The safety net includes many different types of providers, including public health departments, hospitals, and federally funded health centers (FFHCs). For the 50 million uninsured people and individuals with low income, safety net providers serve an essential function, eliminating financial barriers to care and enhancing access to services.

This section includes measures that show how well the health care safety net is meeting the needs of the Nation's vulnerable populations, particularly low-income populations and racial/ethnic subgroups. This section focuses on two types of safety net providers: FFHCs and hospitals.

New! Patients Using Federally Funded Health Centers

FFHCs include health care organizations that receive a grant under Section 330 of the Public Health Service Act, including community health centers, migrant health centers, Health Care for the Homeless programs, and Public Housing Primary Care programs. These organizations typically render services to low-income populations, uninsured people, people with limited English proficiency, migrant and seasonal farm workers, individuals and families experiencing homelessness, and public housing residents.

To obtain Federal grant funding, these public and nonprofit organizations agree to provide a minimum set of services, including primary and preventive care, mental health, and dental services. Access to care is available to all persons, regardless of ability to pay. Charges for services rendered are based on a sliding scale, which is linked to patients' family income. More than 19 million people visited an FFHC in 2010.

 

Figure 8.4. Race, ethnicity, and income of patients receiving care in an FFHC, United States, 2010

Figure 8.4. Race, ethnicity, and income of patients receiving care in an FFHC, United States, 2010. For details, go to [D] Text Description below.

[D] Select for Text Description.

Source: Health Resources and Services Administration, Bureau of Primary Health Care, Uniform Data System, 2010.
Note: Racial groups shown are non-Hispanic. Data were obtained from 1,124 Section 330g grantee recipients. Patients with hypertension include those ages 18-85. Hypertension is determined to be controlled if the patient's last blood pressure reading was less than 140/90. Patients with diabetes include those ages 18-75. Diabetes is determined to be controlled if the patient's most recent HbA1c was 7% or less.

  • In 2010, approximately 64 percent of patients seen at an FFHC were White (Hispanics and non-Hispanics), and one-quarter were Black (Figure 8.4).
  • In 2010, more than one-third of FFHC patients were Hispanic and about one-quarter of patients were determined by the FFHC to be best served in a language other than English.
  • Almost three-quarters of patients seen in an FFHC in 2010 had income at or below the Federal poverty level.

Also, in the NHQR:

  • Nearly 40% of patients seen at an FFHC were uninsured and another 40% had Medicaid.
New! Control of Hypertension and Diabetes in FFHC Patients

Nearly 2.4 million adults treated at an FFHC in 2010 had a hypertension diagnosis and almost 1.3 million had either Type I or Type II diabetes. The population with hypertension and diabetes may overlap, so the two numbers should not be added together. Control of hypertension and diabetes can help indicate quality of care at FFHCs since people with these conditions require frequent monitoring.

 

Figure 8.5. FFHC patients with hypertension or diabetes whose symptoms are controlled, by race, 2010

Figure 8.5. FFHC patients with hypertension or diabetes whose symptoms are controlled, by race, 2010. For details, go to [D] Text Description below.

[D] Select for Text Description.

Source: Health Resources and Services Administration, Bureau of Primary Health Care, Uniform Data System, 2010.
Note: Racial groups shown are non-Hispanic. Data were obtained from 1,124 Section 330g grantee recipients. Patients with hypertension include those ages 18-85. Hypertension is determined to be controlled if the patient's last blood pressure reading was less than 140/90 mm Hg. Patients with diabetes include those ages 18-75. Diabetes is determined to be controlled if the patient's most recent hemoglobin A1c level was 7% or less.

  • More than two-thirds of White patients had their hypertension under control. Groups of patients with the lowest percentage of controlled hypertension were Native Hawaiians, Pacific Islanders, and AI/ANs; only about one-half of patients in these racial groups had their blood pressure under control (Figure 8.5).
  • Control of diabetes was found to be worse among Pacific Islanders (21%) and Native Hawaiians (25%) and best among Asians (45%).
  • Among Hispanic FFHC patients with hypertension, two-thirds had controlled blood pressure; one-third of Hispanics with diabetes had their hemoglobin A1c under control (data not shown).

Also, in the NHQR:

  • In 2010, about 63% of all FFHC patients with hypertension had controlled blood pressure at the time of their last reading.
  • Almost 40% had their diabetes under control.
New! Hospital Admissions of Vulnerable Populations

Hospitals continue to play a major role in the health care safety net and, increasingly, safety net hospitals are defined by their low-income population as opposed to control or governance (e.g., public hospitals).iii This section includes one measure suggestive of hospitals' willingness or ability to provide care to low-income populations: hospital inpatient discharges and aggregate cost accounted for by Medicaid and uninsured patients. This measure offers insight into hospitals' contribution to the health care safety net, by selected hospital characteristics. These measures were estimated as follows:

  1. (Number of Medicaid and uninsured discharges ÷ total number of discharges) × 100
  2. (Total Medicaid and uninsured costs ÷ total costs across all payers) × 100

On average, Medicaid recipients and medically uninsured people accounted for about one in four discharges from acute care hospitals in 2009 (data not shown). As indicated in Table 8.1, the proportion of inpatient days and discharges provided to these vulnerable groups varied by hospital characteristics.

 

Table 8.1. Medicaid and uninsured discharges and aggregate hospital costs, by facility characteristics, U.S. short-term acute hospitals, 2009

 Discharges % (Standard Error)Aggregate Costs % (Standard Error)
All Hospitals26.4 (0.8)20.3 (0.8)
Bed Sizea
Small22.5 (1.6)16.8 (1.5)
Medium 27.7 (1.4)22.0 (1.7
Large26.6 (1.1)20.3 (1.0)
Control
Government39.6 (3.3)32.6 (3.7)
Private nonprofit23.3 (0.7)17.9 (0.7)
Private, investor owned29.3 (1.6)20.7 (1.4)
Teaching Facility
Yes29.7 (1.6)23.7 (1.5)
No23.5 (0.6)16.3 (0.5)
Region
Northeast26.2 (2.5)20.8 (2.2)
Midwest21.0 (1.0)15.7 (1.0)
South27.7 (1.2)20.7 (1.4)
West30.5 (2.0)23.7 (1.7)
Location
Metropolitan26.5 (0.9)20.5 (0.9)
Nonmetropolitan25.8 (0.6)17.4 (0.4)

a. Bed size categories used in HCUPnet are based on hospital beds and are specific to the hospital's location and teaching status. The definitions of small, medium, and large vary by region:

RegionLocation and Teaching StatusHospital Bed Size
SmallMediumLarge
NortheastRural1-4950-99100+
Urban, nonteaching1-124125-199200+
Urban, teaching1-249250-424425+
MidwestRural1-2930-4950+
Urban, nonteaching1-7475-174175+
Urban, teaching1-249250-374375+
SouthRural1-3940-7475+
Urban, nonteaching1-99100-199200+
Urban, teaching1-249250-449450+
WestRural1-2425-4445+
Urban, nonteaching1-99100-174175+
Urban, teaching1-199200-324325+

Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, HCUPnet, 2009. Available at http://hcupnet.ahrq.gov/.

  • Discharge percentage:
    • The percentage of Medicaid and uninsured patients discharged from government hospitals was significantly higher than from private hospitals. Compared with private nonprofit hospitals, a greater percentage of patients discharged from investor-owned hospitals was covered by Medicaid or uninsured.
    • Nearly 30 percent of patients discharged from teaching hospitals were uninsured or covered by Medicaid, compared with about 24 percent of patients in nonteaching facilities.
    • Although the difference in percentage of Medicaid and uninsured discharges was statistically significant between metropolitan and nonmetropolitan hospitals, regional differences were noted. Hospitals in western States discharged a greater proportion of Medicaid and uninsured patients (31%), while hospitals in the Midwest discharged the lowest percentage of patients (21%).
  • Aggregate costs:
    • Nearly one-third of government hospitals' patient care costs were associated with the Medicaid and uninsured population; about one-fifth of costs for private nonprofit hospitals was associated with this population.
    • Among hospitals in the West, Medicaid and uninsured patients accounted for about 24 percent of inpatient costs compared with 16 percent among hospitals in the Midwest.

References

Centers for Disease Control and Prevention. WISQARS [Web-based Injury Statistics Query and Reporting System] nonfatal injury death reports. Available at: http://webappa.cdc.gov/sasweb/ncipc/nfirates2001.html. 2011.

Devine EB, Hansen RN, Wilson-Norton JL. The impact of computerized provider order entry on medication errors in a multispecialty group practice. J Am Inform Assoc 2010;17:78-84.

Donabedian A. The definition of quality and approaches to its assessment. Chicago: Health Administration Press; 1980.

Facts for Features. Older Americans Month: May 2011. Suitland, MD: U.S. Census Bureau; March 23, 2011. Publication No. CB11-FF.08. Available at: http://www.census.gov/newsroom/releases/archives/facts_for_features_special_editions/cb11-ff08.html.

Hanley A, Silke C, Murphy J. Community-based health efforts for the prevention of falls in the elderly. Clin Interv Aging 2011;6:19-25. Epub 2010 Dec 20.

Howden LM, Meyer JA. Age and sex composition: 2010. 2010 Census Briefs. Suitland, MD: U.S. Census Bureau; May 2011. Publication No. C2010BR-03. Available at: http://www.census.gov/prod/cen2010/briefs/c2010br-03.pdf [Plugin Software Help]. Accessed August 16, 2011.

Institute of Medicine, Board of Health Care Services. Future directions for the National Healthcare Quality and Disparities Reports. Washington, DC: National Academies Press; 2010.

Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch Intern Med 2003;163(12):1409-16.

Resnick HE, Alwan M. Use of health information technology in home health and hospice agencies: United States, 2007. J Am Med Inform Assoc 2010;17:389-95.

Romano MJ, Stafford RS. Electronic health records and clinical decision support systems: impact on national ambulatory care quality. Arch Intern Med 2011;171(10):897-903.

Shih A, Davis K, Schoenbaum S, et al. Organizing the U.S. health care delivery system for high performance, 2008. New York, NY: The Commonwealth Fund Commission on a High Performance Health System. Available at: http://www.commonwealthfund.org/usr_doc/Shih_organizingushltcaredeliverysys_1155.pdf [Plugin Software Help].


i. Available at the National Academies Press Web site at http://www.nap.edu/openbook.php?isbn=030908265X .
ii. National Center for Health Workforce Analysis, http://bhpr.hrsa.gov/healthworkforce/index.html. Accessed August 15, 2011.
iii. Concerned with the impact of hospital closures on the health care safety net, the HHS Office for Civil Rights (OCR) has expanded its enforcement efforts to prevent ethnic and racial minority communities from suffering race or national origin discrimination when local hospital facilities close or are relocated. Recently, OCR entered into a voluntary compliance agreement with the University of Pittsburgh Medical Center (UPMC), which agreed to provide additional support for primary and urgent care services in the borough of Braddock, Pennsylvania. UPMC entered into the voluntary agreement with OCR to resolve a complaint alleging that it had violated provisions of Title VI of the Civil Rights Act of 1964, 42 U.S.C. 2000d et seq., when UPMC decided to close Braddock Hospital. Public response to the closure of Braddock Hospital focused on the closure's impact on access to health care for African Americans due to residents' widespread dependence on public transportation. Accordingly, the agreement required UPMC to provide door-to-door transportation services from Braddock to new outpatient facilities and the more distant UPMC McKeesport Hospital, as well as health screening, wellness, and community outreach programs.



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Current as of April 2012
Internet Citation: Chapter 8. Health System Infrastructure: National Healthcare Disparities Report, 2011. April 2012. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/research/findings/nhqrdr/nhdr11/chap8.html