Literature Review on Effective Sex- and Gender-Based Systems/Models of Care

January 30, 2007

Research Question 3: Systems Approach and Insurance/Cost Trends

3. What are the trends in demographics, service delivery, costs, or other sectors that could be addressed via a systems approach? To what extent are patients reimbursed for care for specific services (i.e., prevention, mental health, etc.)? Are there gender or sex differences in out-of-pocket patient costs?

The third research question focuses on large trends in the healthcare system that could be addressed via a systems approach, with a particular emphasis on cost data. Our analysis begins with a discussion of what some of the current problems are in the healthcare system, and then continues with a discussion of which of these issues a systems approach could address. We then discuss various large-scale movements to enact systems-level change, all of which are potential models or allies for a movement toward gender-based medicine. Next, we look at trends in health insurance coverage, with an emphasis on coverage differences between males and females. Finally, the section concludes with a discussion of cost data, including trends in out-of-pocket costs, as well as whether men or women bear a disproportionate burden of these costs.

The U.S. healthcare system is fragmented, decentralized, and needlessly complex. There is almost universal consensus that the system has problems, but limited consensus as to what to do about these problems. Some of these problems are briefly discussed in this section of the report. These problems include high costs, inefficiency, disparities, and reduced quality of care.

The U.S. healthcare system is costly; we spend a greater percentage of our gross domestic product on healthcare than other industrialized nations (Gauthier & Serber, 2005). Unfortunately, this high cost is not justified by the quality of care received. Consider the following four findings:

• The U.S. system is inefficient: "The need for fundamental transformation of the U.S. health care system has become increasingly apparent. Research reveals a fragmented system fraught with waste and inefficiency. Among industrialized nations, the United States spends well over twice the per capita average [on care]. High spending, however, has not translated into better health" (Gauthier & Serber, 2005).
• The U.S. system is expensive: "As a share of total health expenditures, U.S. insurance administrative costs were more than three times the rates of countries with the most integrated insurance systems. The U.S. lags well behind other nations in use of electronic medical records: 17 percent of U.S. doctors compared with 80 percent in the top three countries" (Commonwealth Fund, 2006b).
• U.S. performance lags behind other countries: "Overall, the performance of the U.S. health care system falls far below the level it can and should achieve. On many dimensions of performance—from timely access to needed services to the deployment of health information technology—we lag behind other industrialized nations" (Commonwealth Fund, 2006a).
• The U.S. system is full of missed opportunities: "We fall far short of what is achievable on all major dimensions of health system performance. The overwhelming picture that emerges is one of missed opportunities—at every level of the system—to make American health care truly the best that money can buy. ... If we closed just those gaps that are described in the Scorecard—we could save at least $50 billion to $100 billion per year in health care spending and prevent 100,000 to 150,000 deaths. Moreover, the nation would gain from improved productivity. The Institute of Medicine, for example, estimates national economic gains of up to $130 billion per year from insuring the uninsured" (Commonwealth Fund, 2006b).

In addition to being costly and inefficient, our current system of care produces numerous disparities. The Agency for Healthcare Research and Quality (2004) reports that "disparities are observed in almost all aspects of health care":

• "Across all dimensions of quality of health care including effectiveness, patient safety, timeliness, and patient centeredness."
• "Across all dimensions of access to care including getting into the health care system, getting care within the health care system, patient perceptions of care, and health care utilization."
• "Across many levels and types of care including preventive care, acute care, and chronic care."
• "Across many clinical conditions including cancer, diabetes, end stage renal disease, heart disease, and respiratory diseases."
• "Across many care settings including primary care, dental care, mental health care, substance abuse treatment, emergency rooms, hospitals, and nursing homes."
• "Within many subpopulations including women, children, elderly, persons with disabilities, residents of rural areas, and individuals with special health care needs."

Finally, the current U.S. healthcare system produces suboptimal quality of care. A detailed study of the quality of care received by U.S. residents in 12 communities found that "participants received 54.9 percent of recommended care" (Asch et al., 2006). While there were some differences in scores between subgroups (e.g., women and those with higher incomes received a better quality-of-care score), "the differences among sociodemographic subgroups in the observed quality of health care are small in comparison with the gap for each subgroup between observed and desirable quality of health care" (Asch et al., 2006). In other words, while disparities in care are important, they need to be viewed against a larger backdrop of overall failures in the healthcare system to deliver quality care. Another study found that U.S. adults receive only a little more than half of the recommended care for most medical conditions, although the percentage of care received varied by condition (Gauthier & Serber, 2005).

As these examples show, the U.S. system is far from realizing its potential. The Commonwealth Fund (2006a) identified several barriers that will have to be overcome to see progress in this area. Key sources of failure with the current system include the following:

• General support within the healthcare sector for maintaining the status quo, despite acknowledgment that some level of change is necessary.
• Misaligned payment incentives.
• Inadequate information systems.
• A system of regulatory oversight that is duplicative and costly.
• An inappropriate balance between autonomy and accountability.

Assuming these barriers can be overcome, changes at the systems level could lead to dramatic improvements in our current healthcare system.

Large-scale systems-level changes could include changes in insurance coverage, changes in records or reporting requirements, changes in reimbursement or payment structures, improved or more frequent preventive services, or many other factors. Such changes could improve quality of care, reduce disparities, reduce fragmentation, and improve access or improve incentives, in addition to offering potential cost savings.

One of the primary reasons to consider systems-level changes to the healthcare system is to improve overall quality of care. Quality improvements can be realized with systems-level changes. For example, the Veterans Affairs (VA) health system utilizes "one of the country's most mature electronic medical-record systems, decision-support tools at the point of care, automated order entry, routine measurement of and reporting on quality, and financial incentives for performance" (Asch et al., 2006). The VA is "is the largest health care system to have implemented an electronic medical record, routine performance monitoring, and other quality-related system changes" (Asch et al., 2004).

The VA has not only been an early and successful adopter of large scale systems changes, but the adoption of such systems also facilitated marked improvements in the quality of care provided there. Less than 20 years ago, the VA was not known for providing outstanding quality care; now, comparative studies show that the VA provides better than average care. For example, in the VA system participants receive a higher percentage of recommended care than the general population (67 percent vs. 55 percent), and these wide-scale changes are commonly attributed as being part of the reason for this success (Asch et al., 2006). Another study comparing care at the VA to that of the Medicare fee-for-service plan found that the VA performed better on 12 of 13 care indicators, suggesting that "the quality-improvement initiatives adopted by the VA in the mid-1990s were effective" (Jha, Perlin, Kizer, & Dudley, 2003).

Thus, the VA example lends substantial support to the notion that improvements in care can be realized via increased structure, coordination, data collection and evaluation, and other oversight and incentives.

A large-scale reorganization of the healthcare system also could improve the ability of the system to treat chronic illness, thus improving quality. While the current system works well for acute treatment of disease, it is "not always conducive to preventive care" (Cabana & Kim, 2003). Currently, there are "five system barriers to high-quality chronic illness care, which include organization of care around the acute care visit, reliance on the physician, lack of access to medical and nonmedical expertise, inadequate information, and lack of incentives to provide better care for chronically ill patients" (Cabana & Kim, 2003). A modified system might include more emphasis on "allied health professionals to counsel and educate patients or reinforce educational messages," or could create a system with additional "registries, reminder systems, and nontraditional follow-up visits" to improve adherence to treatment guidelines and prevention strategies (Cabana & Kim, 2003).

Sophisticated data collection systems (such as those employed by the VA) also can provide information to improve care. For example, large managed-care systems use "administrative databases that make it possible to measure clinical performance and compare it to nationally accepted best practices. This allows physicians to compare their approaches to the latest scientific literature on diabetes, congestive health failure, heart attacks, breast cancer screenings, immunizations, and asthma" (Ignagni, 2001).

Finally, quality of care could also be improved through better timed care interventions. For example, one trigger for additional care in the current U.S. system is pregnancy. Thus, when pregnant, many low income women may become eligible for additional health services. However, this additional attention is in many cases too late to provide optimal care. Indeed, organizations such as the Centers for Disease Control and Prevention (2007) are encouraging a focus on "Preconception Care" as a better way to improve maternal health outcomes. A systems approach to care might be better equipped to provide such services.

Another primary goal of any systems-level change would be to reduce disparities in access to coverage and quality of care. Universal coverage, with adequate funding to ensure appropriate wait times, would attenuate most inequities in healthcare (Lasser, Himmelstein, & Woolhandler, 2006). However, to eliminate all health disparities, change would also need to "address inferior systems of care in institutions serving the poor and nonfinancial access barriers such as cultural and language barriers" (Lasser et al., 2006).

In our current healthcare system, continuity of care has been "systematically disrupted," "owing to increasing specialization among medical professions and disruption of long-term patient-primary care provider relationships" (Misra & Grason, 2006). Systems-level changes to the healthcare system could reduce this fragmentation, thus improving care.

A systems-level approach to change can also lead to the reduction or elimination of redundant utilization, which results from patients receiving care in different systems. For example, many young women who lack pharmaceutical coverage may seek care at Planned Parenthood or another similar setting, which can result in duplicate exams and Pap smears. Similarly, many VA patients may have duplicate coverage. Even privately insured patients and those on Medicare who need specialty care often receive duplicate services. Such patterns reflect over-utilization by those with better access to care and increase the costs of care nationally.

Another way in which a systems-level approach could improve the healthcare system would be to simplify and standardize access to the system. Such a change could apply to processes such as applying for insurance, end-of-life decision making, and medication instructions. All patients would "benefit from a reduction of paperwork, plain and simple communication, and standardized processes" (Paasche-Orlow, Schillinger, Greene, & Wagner, 2006). Moreover, the authors found that satisfaction, comprehension, and retention of information also were improved by materials presented in accessible language.

A systems-level approach to care also could reorganize the incentive structure of the current system, making it cost-effective to offer certain services that are infrequently offered now. For example, healthcare has been becoming increasingly specialized. Specialized care approaches are financially lucrative for those involved in them, but "threaten to strip services and reduce quality in neighboring general hospitals, with potentially serious implications for their bottom line" (Stevens, 2005). A reorganized health system could create "a renewed market for primary care," which "would prompt more medical students to become residents in family medicine, internal medicine, and pediatrics" (Stevens, 2005). Such a response is not "economically rational" in the current system, but a change in the incentive structure could correct that (Stevens, 2005).

Another similar example relates to colorectal cancer screening (colon cancer is a leading cause of death in both men and women):

The technologies for [colorectal cancer] screening (sigmoidoscopy and colonoscopy) are not new, but at least in the United States, public awareness of their availability for screening is growing. ... At the same time, studies evaluating the effectiveness of these technologies for screening are maturing and showing clear evidence of benefit. ... The main barrier to achieving the potential benefits of these screening technologies is a manpower issue: there are not enough trained endoscopists (Carlson, 2001).

Changes in the incentive system could correct this type of deficit. Changes in the incentive system also could create an impetus for movements toward patient-centered care (Davis, Schoenbaum, & Audet, 2005), or other quality structures that could improve overall quality of care. In addition, changes in incentives may be able to reduce gender-based or other disparities in screening. For example, returning to the example of colorectal screening discussed above, white men are most likely to receive a colonoscopy screening than either women or African American men (McMahon et al., 1999), and men remain more likely to receive screenings for colon cancer (Meissner, Breen, Klabunde, & Vernon, 2006). Changes in the incentive system could correct some of these deficits.

Any effort to create large-scale change in the healthcare system to implement gender-based care would be well-served by learning from and aligning with other large-scale movements in the healthcare system. This sort of alignment would take advantage of natural synergies and avoid the potentially negative consequences of "competing" with other movements. In this section, we describe some other movements that are attempting to promote large-scale change, and we highlight possible synergies or lessons learned as they relate to gender-based care. These efforts to enact systems-level change include patient-centered approaches, family-centered care, consumer-driven care, and pay-for-performance.

There has been a movement in medicine in recent years toward adopting approaches that focus on the delivery of patient-centered care (patient-centered care was discussed previously in research question 2). Here, we list institutional factors that must be addressed to implement such care (Silow-Carroll et al., 2006). Some of these same factors may need to be addressed to implement gender-based approaches to care:

• "Feedback and measurement: seek and respond to suggestions and complaints from patients and families; develop, collect and evaluate data on measures of patient-centered care, and feed back the results into further improvements; incorporate accountability for addressing deficiencies and continually improving indicators."
• "Patient/family involvement: include patients and family members in the planning, design, and ongoing functioning of the organization; consider the patient a member of his/her care team."
• "Workforce development: employ, train, and support a workforce that reflects, appreciates, and celebrates the diversity of the communities and cultures that the organization serves; reward and recognize staff exhibiting patient centeredness principles; develop communication skills among all levels of staff; empower staff to be part of patient-centered teams."
• "Leadership: top management, Board, and department heads make a clear, explicit commitment to patient centeredness and act as role models."
• "Involvement in collaboratives, pilots: seek out and join pilot research projects and collaborative relationships with other organizations that attempt to 'push the envelope' in developing new methods to operationalize patient-centered principles."
• "Technology and structural support: use electronic systems/user-friendly software programs that promote patient/family education and compliance, and minimize medical errors; structure the physical environment to optimize patient flow and safety."
• "Integration into institution: tie patient-centered care to other priorities such as patient safety, quality improvement, etc., and incorporate patient-centered practices into daily operations and culture."

To implement a patient-centered care model, the authors found that change needs to occur

simultaneously at four levels: 1. Organizational level, e.g., structures, processes, leadership, funding, information technology; 2. Patient level, e.g., navigation, translation, convenient access, education; 3. Provider level, e.g., training, interdisciplinary teams, diversity, cultural competence; and 4. Community level, e.g., outreach, recruitment, partnerships (Silow-Carroll et al., 2006).

A comprehensive framework such as this to implement a patient-centered approach provides a useful model for thinking about how to implement gender-based medicine; in fact, a gender-based approach might best be implemented concurrently with such a comprehensive approach to take advantage of synergy and momentum for change. Thus, this detailed description provides a fairly comprehensive outline of some of the factors that might need to be addressed at the institutional level to adopt gender-based medical practices.

The family-centered care movement is based on the core values of dignity and respect, information sharing, participation, and collaboration (Conway et al., 2006). Efforts to enhance family-centered care have resulted in both improved quality and efficiencies. For example, the MGC Health System in Georgia adopted a family-centered approach throughout the entire organization, including a commitment on the part of senior leadership. This approach has resulted in increased patient satisfaction scores, reduced medical stays, reduced medical errors, and reduced nursing shortages (Conway et al., 2006).

Lessons learned from this field regarding partnership-development include (Conway et al., 2006):

• Having senior leaders who are knowledgeable about and committed to collaboration with patients and families.
• Designating a staff member, with patient- and family-centered knowledge and skills to serve as a liaison for collaborative endeavors.
• Creating a variety of ways for patients and families to serve as advisors within an organization and ensuring that they can contribute meaningfully to decision-making— that their presence is not merely tokenism.
• Recruiting patients and families continually for various terms of service to support sustainability and ensuring that these individuals represent the diversity of the community served.
• Investing in orientation and training in patient- and family-centered care and in strategies for effective collaboration for patients, families, staff, and physicians.
• Investing in educational and planning activities for patients, families, physicians, and staff to engage in together in order to develop trusting relationships and understanding of shared and differing perspectives.
• Supporting the development of patient and family leaders.
• Providing staff and physicians with ongoing support and mentoring to address challenges related to collaborating with patients and families as they arise.
• Understanding that patient- and family-centered care is cost-effective—that initial investments in training are modest and will be quickly repaid in terms of increased family and patient satisfaction, improved staff satisfaction and retention rates, and greater market share.
• Ensuring that everyone involved realize that moving toward patient- and family-centered care is a process and that they trust this process and one another.
• Measuring outcomes.
• Celebrating accomplishments and rewarding efforts.

As with other approaches described in this section, a movement toward large-scale change to create gender-based medical care may benefit from attention to some of these same issues.

Another potential model to consider regarding a large-scale systems change is the movement toward consumer-driven healthcare. This movement, at its core, involves an effort to get consumers more involved in the financial and other implications of their own care decisions.

The most common use of the term "consumer-driven healthcare" has referred to benefit plans with "a personal care account; insurance coverage designed to create a 'gap' between the dollars in the account and the level at which a deductible is reached; and various Internet support tools intended to facilitate more extensive, better-informed consumer involvement in health care decisions" (Christianson, Parente, & Feldman, 2004). The idea behind this movement is that giving consumers greater personal control over their use of the health system will reduce unnecessary medical visits and encourage the use of lower-cost options. One possible drawback of this model, however, is that underutilization of services may be a greater problem than overutilization, and "even clear instances of overutilization are often the result of provider decisions and may not be responsive to consumer incentives" (Davis, 2004).

Four main conclusions have been drawn to date about this consumer-driven healthcare movement: 1) voluntary enrollment is relatively limited; 2) enrollees tend to be higher-income and healthier; 3) enrollees tend to reduce their use of services; and 4) enrollees tend to be satisfied (Davis, 2004). Thus, the movement has been successful in some areas but likely does not hold great promise as a universal solution to healthcare problems.

However, as a movement, the consumer-driven healthcare trend may have important lessons for gender-based care.

A final potential model to consider related to gender-based systems-level change is the pay-for-performance model. Pay-for-performance systems are an attempt to bridge the gap between healthcare quality and price, and they have shown some initial successes (Thrall, 2004). These programs reward or penalize hospitals and physicians based on their performance, with the most common model being "a straight bonus system that rewards providers with additional payments for achieving stipulated performance targets" (Thrall, 2004). Many payers are adopting such an approach, including the Centers for Medicare and Medicaid Services, which is embarking on demonstration projects with hospitals (Thrall, 2004).

These plans frequently rely on pre-existing measures (collected initially for other purposes) to reward or penalize performers. For example,

many pay-for-performance plans use quality criteria originally developed for other purposes like the Health Plan Employer Data and Information Set (HEDIS) program of the National Committee for Quality Assurance. The quality criteria defined in the HEDIS program have been used in the managed care industry for many years as measures of health plan and provider performance. The major categories in HEDIS are effectiveness of care, access to and availability of care, satisfaction with the experience of care, health plan stability, use of services, and health plan descriptive information. Within these broad categories, there are several dozen specific quality measures (Thrall, 2004).

Another set of issues related to measurement of pay-for-performance is how to control for year-to-year variations based on statistical fluctuations in cases, a particular problem for smaller practice settings (Thrall, 2004).

Pay-for-performance systems are of interest to gender-based care because they involve an attempt to improve quality while also controlling cost and working within an existing health structure.

Insurance coverage is a critical part of the U.S. healthcare system, and coverage patterns and rates can vary considerably according to gender, race, ethnicity, sexual orientation, and geography. In this section, we outline overall coverage patterns (including sex- and gender-based patterns) as well as factors that are associated with health insurance coverage. We then examine trends among the uninsured and discuss the implications of lack of insurance on overall health. We conclude our analysis of insurance coverage with an examination of trends for other specific populations groups (i.e., minorities, gays and lesbians, and rural residents).

Most people in the United States have some form of health insurance coverage, with the most common form being managed care, which serves approximately 170 million Americans (Ignagni, 2001). However, a significant minority are without coverage, and lapses in coverage are common for a substantial minority. Based on a recent review of available data, The Commonwealth Fund (2006a) reports the following:

• "Fifty-nine percent of the U.S. population is covered by private health insurance, with nearly 92 percent of this coverage linked to employment."
• "Twenty-seven percent of the population receives health insurance coverage from the government—through the Federal Medicare program, military health care, the state-Federal Medicaid program, and the State Children's Health Insurance Program (SCHIP)."
• "Sixteen percent of the population is uninsured. Millions more endure a period without insurance during the year: almost one of three civilian, non-institutionalized citizens under the age of 65 was uninsured for a period of at least one month in 2003."

Coverage patterns are similar between men and women. More women have Medicaid as a source of insurance (9 percent vs. 6 percent), while men are somewhat more likely to be uninsured (22 percent vs. 19 percent) (Salganicoff, 2004). The same proportion of men and women (64 percent) have job-based insurance; however, a greater proportion of women than men have job-based insurance as a dependent (25 percent vs. 13 percent), while men are more likely than women to hold job-based insurance in their own names (51 percent vs. 39 percent) (Salganicoff, 2004). Women may be less likely to participate in employers' health plans because "they are more likely to work part-time, have lower incomes, and rely on spousal coverage" (Henry J. Kaiser Family Foundation, 2006b). As a result, "the take-up rate for job-based coverage among workers is 80% for women and 89% for men" (Henry J. Kaiser Family Foundation, 2006b).

Khoury and Weisman (2002) summarized the literature on sex- and gender-based differences in insurance coverage as follows:

More men than women are uninsured at any given point in time, largely because Medicaid targets poor pregnant women and parents of young children. In general, women are more dependent than men on publicly financed health insurance (Medicaid and Medicare) and have fewer financial resources with which to pay for care. ... Privately insured women rely more than men on dependent coverage and less on private insurance through their own jobs. Dependent coverage may become more difficult to obtain as premiums increase and employers seek ways to reduce health insurance costs.

Another issue to consider is the content of coverage. Zimmerman and Hill (2000) have argued that "ideally, because of differences in health care requirements, insurance should work somewhat differently for women and men," although current coverage patterns tend to serve men better. Their argument is based on life span and illness differences between men and women:

Men and women have different life spans and illness patterns, making their health care needs substantially different and requiring accessibility to different types of health care services. Men tend to have more acute conditions that can result in hospitalization, whereas women more often suffer from chronic problems that require ambulatory or home health care. The Medicare reimbursement structure is geared to hospital care, so among older people women bear a greater financial burden, which may impede their access to care. Inadequacies also exist for younger women. For example, 9 percent of privately insured women have policies that exclude maternity coverage, and 27 to 36 percent of insurance plans do not cover induced abortion. All but 16 percent of HMOs cover oral contraceptives, but only 31 to 60 percent of other plans provide such coverage. Another study that included a range of health plans found that 85 percent covered medication and services related to impotency, whereas only 59 percent covered oral contraception and only 7 percent covered infertility. ... Because women live longer than men, they are more likely to require nursing home services. And associated with living longer, older women have chronic illnesses and disability and are therefore more likely than men to require adaptive aids, home health, community-based services, and outpatient prescriptions (Zimmerman & Hill, 2000).

In summary, U.S. men are slightly less likely to have access to coverage than their female counterparts. However, men are more likely to have health insurance in their own names, and men's care needs may be better addressed by the types of coverage offered.

The primary predictors of insurance coverage are income and employment status.

Low-income families (families who earn less than 200% of the poverty level) "run the highest risk of being uninsured" and "over a third of the poor and 30% of the near-poor (100-199% of poverty level) lack health coverage" (Henry J. Kaiser Family Foundation, 2006a). Additionally, "reliance on public coverage increases dramatically as income declines. When comparing older widowed or divorced women to their married or single counterparts, dramatic differences in public coverage emerge. ... Widowed or divorced women are at least twice as likely to have public coverage compared to married or single women (18.6 percent vs. 7.9 percent)" (McCloskey & Klein, 2001).

Employment status is related to insurance because of the "predominance of employment-based coverage in the United States" (Merzel, 2000). Employment-based coverage generally favors men, who are more likely to hold a policy in their own names (Dewar, 2000). In addition, women "may find themselves without coverage if they do not work continuously or full time because of childbearing and family responsibilities" (Kasper, 2004). Moreover, "women are more likely than men to change jobs for family reasons, including childbearing. This makes them vulnerable to becoming ineligible for private insurance or to paying higher premiums because of medical conditions that have developed during interruptions in private insurance coverage and adversely affects their eligibility for pension-based insurance" (Miles & Parker, 1997).

While one study found that "in general, the determinants of health insurance coverage were quite similar for men and women" (Merzel, 2000), there is some disagreement as to whether women or men are more likely to work in jobs that offer coverage. Dewar (2000) and Kasper (2004) both report that women have more limited access to insurance because of lower wage jobs with more limited fringe benefits. However, Merzel (2000) found that "single women who work full time are slightly more likely than men to be covered through their jobs, primarily as a result of differences in the types of jobs held by single men and women."

It does appear that "women are more vulnerable to losing their insurance should they become divorced or widowed, because they are more likely than men to be covered as dependents. Women are also at greater risk of losing coverage if their spouse loses his job or his employer drops family coverage or increases premium and out-of-pocket costs to unaffordable levels" (Henry J. Kaiser Family Foundation, 2006b). Additionally, widowed or divorced older women may "face problems gaining access to the health insurance market" (McCloskey & Klein, 2001).

Other barriers to acquiring health insurance include being foreign-born (perhaps because of language barriers and cultural differences) (Freeman & Lethbridge-Cejku, 2006), and having less than a high school education (Freeman & Lethbridge-Cejku, 2006).

Numerous factors affect access to health insurance, and these differences are reflected in insurance rates across varies categories (e.g., sex, age, race/ethnicity, income, and education):

The percentage of females without insurance (14.4 percent) is slightly lower than the percentage of males (16.8 percent). However, non-White women are more likely than White women to lack coverage: 10.4 percent of non-Hispanic White females (of all ages) were uninsured, compared to 17.8 percent of Black females, 18.5 percent of Asian females, and 29.6 percent of Hispanic females. The percentage of people without health insurance also varies greatly by age. Young adults of both sexes are the most likely to be uninsured: 34.5 percent of 21 to 24 year-olds lack health insurance, as do 26.6 percent of 25 to 34 year-olds. In contrast, because of the Medicare program, fewer than 1 percent of women aged 65 years and older are uninsured. Rates of uninsurance decrease steadily as household income increases, ranging from a high of 24.2 percent for those with incomes below $25,000 to a low of 8.2 percent for those with incomes of $75,000 or more (Health Resources and Services Administration, 2005b).

Health insurance stability is higher "for those who have higher levels of welfare receipt, have more work hours, have fewer job changes, have higher education levels, are African American or Hispanic, and who live outside central cities" (Anderson & Eamon, 2005). A longitudinal study found that point-in-time estimates tend to dramatically overestimate coverage, because coverage lapses are quite common; in this case, 24 percent of respondents lacked coverage in a 1998 interview, but 49 percent lacked coverage at some point during the three-year study period (Anderson & Eamon, 2005). Such coverage lapses result in disruptions in access to care, quality of care, and compliance with treatment.

Estimates of the number of Americans who are uninsured increase every year (Henry J. Kaiser Family Foundation, 2006a). Based on 2004 census data, almost 46 million Americans are uninsured (Gauthier & Serber, 2005), and many millions more are underinsured (Kasper, 2004). Altogether, "61 million adults, a third of those under 65, are uninsured or underinsured" (Gauthier & Serber, 2005). In 2003, 44 percent of the uninsured were men, 36 percent were women, and 20 percent were children (Salganicoff, 2004).

Because of their more frequent status as healthcare dependents, older women may be especially at risk of losing health coverage:

• "One in four women between ages 50 and 70 was uninsured when her older husband retired" (Kasper, 2004).
• "The patchwork of different private sector and publicly-funded programs in the U.S. leaves nearly one in every five nonelderly women uninsured" (Henry J. Kaiser Family Foundation, 2006b).
• "Although the majority of widowed or divorced women aged 55 to 64 have insurance, nearly one in five is uninsured and may have difficulty finding quality, affordable health coverage. Widowed and divorced older women with low incomes are most likely to be uninsured or to face problems gaining access to health insurance. Older widowed or divorced women face many barriers in the private insurance market. Insurers may refuse to sell them a policy—especially if they have a history of health problems or a chronic or disabling condition. When a policy is available, it is likely to be expensive and may be unaffordable for those most in need of coverage" (McCloskey & Klein, 2001).

Growth in the uninsured population is occurring primarily among adults and those with low incomes (Henry J. Kaiser Family Foundation, 2006a). Additionally, "women who are Latinas, low-income, single, and young are particularly at risk for being uninsured" (Salganicoff et al., 2005). Another group with limited to no coverage is men recently released from prison, fewer than 10 percent of whom have any coverage (Jarrett, Adeyemi, & Huggins, 2006).

Numerous studies have found that being uninsured is related to negative health outcomes. The most significant of these is the increased mortality rate among the uninsured: "Uninsured persons are more likely to be in poor health and to die earlier, even when analyses controlled for other sociodemographic factors" (Freeman & Lethbridge-Cejku, 2006). The Henry J. Kaiser Family Foundation (2006a) offers a more detailed explanation of this increased mortality rate:

The uninsured are less likely to receive preventive care than those with insurance and more likely to be hospitalized for conditions that could have been avoided. For example, people with insurance are significantly more likely to have had recent mammograms, and other types of cancer screenings than the uninsured. Consequently, uninsured cancer patients are diagnosed later and die earlier than those with insurance. Researchers estimate that a reduction in mortality of 5% to 15% could be achieved if the uninsured were to gain continuous health coverage. The Institute of Medicine estimates that at least 18,000 Americans die prematurely each year because they lack health coverage. Charitable care and the safety net of community clinics and public hospitals do not fully substitute for health insurance. Lack of health coverage matters for millions of uninsured Americans, affecting their access to care, health status, job decisions, and financial security, as well as exacting an indirect toll on society in terms of more disability, lower productivity, and increased burden on the health care system.

Lack of insurance also costs the United States financially. The Institute of Medicine estimates these costs at $65 billion to $130 billion annually (Gauthier & Serber, 2005). Lack of insurance or inadequate insurance can have a larger personal financial impact, putting individuals and families at substantial financial risk if a family member becomes critically ill: "Over a third of the uninsured have a serious problem paying medical bills, and nearly a quarter are contacted by collection agencies for medical bills" (Henry J. Kaiser Family Foundation, 2006a).

In addition to an increased mortality rate and significant financial costs, lack of insurance also is associated with greater barriers to care, reduced access to care, fewer preventive visits, and the forgoing of needed medical services (such as prescriptions). Findings in this area include the following:

• "Uninsured persons use less preventive health care than do those with insurance" (Reid et al., 1999).
• "People who are uninsured are less likely than those with insurance to seek preventive care, which can result in poor health outcomes and higher health care costs" (Health Resources and Services Administration, 2005b).
• "Lack of health insurance coverage is associated with reduced access to health care and poorer medical outcomes. Several studies show that uninsured persons are less likely to have a regular source of care, less likely to receive preventive and primary care, less likely to receive required preventive services, and more likely to delay needed medical care than insured persons" (Freeman & Lethbridge-Cejku, 2006).
• Sixty-one percent of the uninsured had an access problem (e.g., not filling prescriptions, not seeing a specialist) during the past year (Gauthier & Serber, 2005).

Uninsured women face a similar set of issues, in addition to problems that are unique to women. Findings specific to women include the following:

• "Uninsured women are the least likely to have had a provider visit in the past year (67%), compared to women with either private (90%) or public insurance-Medicaid (88%) and Medicare (93%)" (Salganicoff et al., 2005).
• "When women are uninsured, they are more likely to postpone care and to forgo filling prescriptions than their insured counterparts and often delay or go without important preventive care such as mammograms and Pap tests" (Henry J. Kaiser Family Foundation, 2006b).
• "Women without insurance consistently report lower use of preventive services, more difficulty paying for care and medicines, and greater barriers to obtaining services" (Salganicoff et al., 2005).
• "Women without insurance consistently fare worse on multiple measures of access to care, including contact with providers, obtaining timely care, access to specialists, and utilization of important screening tests" (Salganicoff et al., 2005).
• "Studies have shown that uninsured women have difficulty accessing care; go without needed care; are less likely to fill a recommended prescription; do not receive preventive care services such as clinical breast exam, mammogram, or Pap test; do not have a regular source of care; and are more likely to rely on episodic emergency room or clinic care" (Kasper, 2004).
• "Uninsured women faced larger access barriers and utilized fewer services, particularly preventive care services, than women with either public or private coverage" (Almeida, Dubay, & Ko, 2001).
• "Uninsured women face significant barriers to care not met by the current safety net system, especially medical, surgical, and dental services" (Almeida et al., 2001).

It is important to note that while not having insurance is associated with poor quality of care, access alone does not guarantee quality:

Although having insurance increases the ease of access to the health care system, it is not sufficient to ensure appropriate use of services or content of care. Indeed, within systems where access to care is more equitable, disparities in quality due to race or ethnic group or to other characteristics are often reduced or even reversed, but substantial gaps between observed and optimal quality remain (Asch et al., 2006).

Minority populations in the United States are less likely to be insured than the majority white population, and this is true for both men and women.

The percentage of women who are uninsured varies by race and ethnicity. White women are least likely to be uninsured (14%), followed by Asian/Pacific women (22%), American Indian/Aleutian Eskimo women (34%), and Latina women (38%) (Salganicoff, 2004). Minority women also are more likely to rely on public coverage such as Medicaid (Wyn et al., 2004), and are more likely to experience gaps in their coverage (Wyn et al., 2004). Insurance rates for Hispanic women also vary by country of origin: "Among both the currently employed and unemployed Hispanic or Latino women, Mexican and Central or South American women were more likely to be uninsured than Puerto Rican, Cuban, and other Hispanic women" (Freeman & Lethbridge-Cejku, 2006).

Among men, "Hispanic, Black, and AI/AN [American Indian/Alaska native] men are less likely than their White counterparts to be insured all year" (Ro et al., 2004). Latino men are particularly at risk, as "nearly half of the non-elderly Latino male population is uninsured" (Rich & Ro, 2002). Another at-risk group among men is young men of color, who "because of their socioeconomic position, are less likely to qualify for public sources of insurance such as Medicaid" (Rich & Ro, 2002).

Gay and lesbian patients may experience additional barriers to coverage:

Coverage is often unaffordable or unavailable to the gay and lesbian patient, compared with heterosexuals. Domestic partnership coverage is still rare, although some progress has been made. ... The lack of insurance coverage contributes to overall poorer health maintenance behaviors among gays and lesbians. Both gay men and lesbians in committed relationships are at a disadvantage compared to married straight couples because many insurance companies and employers continue to deny spousal benefits to unmarried partners (Bonvicini & Perlin, 2003).

Moreover, many individuals may still not feel comfortable revealing their sexual orientation at work in order to request domestic partner coverage, which further limits access.

Rural residents also experience problems obtaining health insurance:

Health insurance coverage for rural Americans [compared with urban residents] may be even more troubling. Rural residents have lower incomes, tend to be in poorer health, and have fewer preventive services than their urban counterparts. Twenty-five percent of people who live in rural areas are uninsured; and they tend to be uninsured for longer periods of time than those in urban centers (Kasper, 2004).

In general, costs are a greater barrier to care for women than they are for men. Women have lower incomes than men, and

women's financial resources have to go farther than men's because women are more likely to become single parents and to become caretakers to their elderly relatives. ... Women experience higher rates of economic hardship than men, especially in their later years when they are more likely to have outlived a spouse and less likely to have a pension to help support them in retirement (Bird & Rieker, 1999).

Perhaps as a result of these economic differences, more women than men do not receive care because of costs (5.8% vs. 5.0%), and delay care because of cost (8.3% vs. 7.0%) (Adams & Barnes, 2004).

Salganicoff, Ranji et al. (2005) provide a comprehensive summary of cost trends as they affect women:

Health care costs are increasingly acting as a barrier to health care for many women. One-quarter of women delay or don't get needed medical care because they cannot afford it. Furthermore, cost-related problems appear to have worsened since 2001. Many women also cannot afford prescription drugs. They do not fill prescriptions or resort to skipping doses and splitting medicines. These problems do not just affect uninsured women, but are also reported by some women with private health coverage. Over one-quarter of non-elderly women (27%) say they delayed or went without medical care they believe they needed due to costs, a significantly larger share than in 2001 (24%). Women (56%) are more likely than men (42%) to use a prescription medicine on a regular basis, and are also more likely to report difficulties affording their medications. In the past year, one in five women (20%) report that they did not fill a prescription because of the cost, compared to 14% of men. While the problem is greatest for uninsured women (41%), one in six women (17%) with private coverage and nearly one in five women with Medicaid (19%) also say they faced the same barrier. One in seven (14%) women also report that they skipped or took smaller doses of their medicines in the past year to make them last longer. Nearly one in 10 women say they have spent less on basic family needs to pay for their medicines.

In this section, we examine trends in costs, including out-of-pocket costs. As noted, these trends show that out-of-pocket costs are a greater burden for women than men, and that healthcare for women may be more expensive than healthcare for men.

Out-of-pocket costs for "copayments, deductibles, coinsurance, and payments for services not covered by insurance" are 12.6 percent of total U.S. health expenditures, or $236 billion annually, based on data from 2004 (Commonwealth Fund, 2006a). U.S. out-of-pocket costs per capita were $737 in 2002, higher than in other countries even after adjustments for cost of living (Gauthier & Serber, 2005). Out-of-pocket costs place a greater burden on those with lower incomes, with 11 percent of all households paying more than 5 percent of income in out-of-pocket costs; this percentage rises to 29 percent for households earning less than $20,000 per year, and to 23 percent for households earning between $20,000 and $34,999 (Gauthier & Serber, 2005).

Drug costs are a significant component of out-of-pocket expenditures, and such costs are substantially higher for those without prescription drug coverage. For example, Blustein (2000) found that such costs were twice as high per tablet for Medicare beneficiaries without drug coverage, and "out-of-pocket expenditures are very high" for Medicare recipients who are unable to afford a Medigap policy to cover prescriptions (Rice, 2000).

While out-of-pocket costs have been rising, this rise has occurred simultaneously with an overall rise in costs. Consumers are reacting to this rise because they have "historically been sheltered from much of the bite of rising health costs by a continuous decline in the out-of-pocket share of spending" (Borger et al., 2006). Out-of-pocket costs are predicted to rise with overall costs; however, as a share of total personal healthcare spending, out-of-pocket costs are "projected to decline from 15.1 percent in 2004 to 12.6 percent by 2015" (Borger et al., 2006).

Out-of-pocket costs have been found to have a greater impact on care than was previously suspected. For example, the threshold at which increased co-pays affect patient compliance with medication usage is surprisingly low. A $10 increase in co-payment for medication for angiotensin-converting enzyme (ACE) inhibitors resulted in a "2.6% decrease in the medication possession ratio ... but a predicted 6.1% increase in the risk of hospitalization for CHF [congestive heart failure]" (Cole, Norman, Weatherby, & Walker, 2006). Another study of antihypertensive medications found that "co-payment level is a strong and independent predictor of medication compliance after adjusting for other model explanatory variables" (Taira, Wong, Frech-Tamas, & Chung, 2006). Such findings make the setting of pharmaceutical prices an important issue for healthcare quality.

Like other lower-income groups, women pay a greater proportion of their total income in out-of-pocket medical costs and also have higher costs overall than men. Partly this is because women are more frequent users of the healthcare system: "Ninety percent of females had at least one health care expenditure in 2002, compared to 80 percent of males" (Health Resources and Services Administration, 2005b). Women also may make more visits to the doctor than men (Bertakis, Azari, Helms, Callahan, & Robbins, 2000), as well as use more prescriptions (Correa-de-Araujo, Miller, Banthin, & Trinh, 2005).

Women on Medicare "spend a greater share of their incomes on health care than men, and the most vulnerable, those who are sicker, pay significantly more. Women use 22% of their total income for out of pocket healthcare expenses, compared with 17% for men" (Rice, 2000). Women also pay more than men out-of-pocket for prescriptions:

While 15% of women report they paid no out-of-pocket costs for their medicines in the past month, over one-third (36%) say they paid up to $50 and an additional 20% paid from $50 to $99 of their own money. However, one in four women (24%) face significant out-of-pocket expenses for prescription medicines, paying $100 or more in the past month, including 10% who paid at least $200 in the past month for their medicines (Salganicoff et al., 2005).

Costs are even higher for uninsured women: "Nearly four in 10 uninsured women (38%) say they spent $100 or more in the past month, including 19% that spent $200 or more. Given that most uninsured women are disproportionately low-income, these costs place a great strain on their already very tight budgets" (Salganicoff et al., 2005).

Variations in women's out-of-pocket costs also occur according to race, ethnicity, age, and insurance status. Taylor, Larson, et al. (2006) report the following differences:

• "Variation in out-of-pocket expenses for health care as a percent of family income was also related to insurance status. Among women under age 65, the uninsured, and those with public insurance only were more likely than the privately insured to have high levels of out-of-pocket expenses relative to income. A different distribution of out-of-pocket spending in relation to income was observed for women age 65 and older in 2000. Those with Medicare only and Medicare plus other public coverage were more likely to have had relatively high levels of out-of-pocket expenses relative to income than those with Medicare plus private insurance."
• "The highest out of pocket expenses as a percent of family income were incurred by women age 75 or over; almost one quarter in this group (21-23%) spent 10% or more of their income on health care in 2000. In the general population only 6% on average had out-of-pocket expenses at this level."
• "Poor, near poor, and low-income women, widows, women who lived in rural areas, those in fair or poor health, and those women with less than a high school education were also more likely to have spent 10% or more of their incomes out of pocket for health care."
• "Another important socio-demographic difference may be found in a comparison among white, black, and Hispanic women. Proportionately fewer Hispanic women than white women spent 10% or more of family income out of pocket for medical care."

Women's greater burden in out-of-pocket expenses is exacerbated among older adults (typically defined as age 65 and older): "Older women bear a disproportionate burden of out-of-pocket health care costs; these costs consume 20% of the income of an older women, as compared to 17% of the income of an older man" (Blustein, 2000). This discrepancy may be because of women's lower incomes combined with potentially worse drug coverage: "Women are less likely to have employer-based ('retiree') plans, which include particularly good drug benefits. Therefore, older women may face higher out-of-pocket costs when they purchase medications" (Blustein, 2000).

A more detailed description of trends for prescription drug use among older adults follows. The study results are based on interviews with individual adults over the age of 65 about their own use of prescription medications:

Women accounted for a somewhat larger portion of prescription drug use and expenditures in this population. Women accounted for 56.3% of the average annual total of 237.4 million prescriptions and 54.6% of the average annual total of $12.7 billion in drug expenditures by the privately insured older adults. Examination of per capita use and expenditures shows that the disproportionate share of drug expenditures by women resulted from higher rates of use. Women were more likely than men to purchase at least one prescription during the year (91.9% vs. 87.5%). Further, among persons with use, women purchased more prescriptions, on average, than men (24.7 vs. 20.7). Men, however, purchased drugs with a somewhat higher average prescription price than women ($55.68 vs. $51.84). Overall, women had total expenditures averaging $1178 per year for drugs, about 17% more than the $1009 in average expenditures by men (Correa-de-Araujo et al., 2005).

The new Medicare Part D drug coverage (effective January 1, 2006) will certainly impact these trends, but data on the effects of this coverage change are still being collected. The Centers for Medicare and Medicaid Services reports that more than 31 million seniors had enrolled in the plan as of May 2006 (Bach & McClellan, 2006). The standard benefit of the coverage entails a "$250 annual deductible, followed by 75 percent coverage for the next $2,000 in drug costs, then by a 'doughnut hole' in which patients pay the next $2,850 in drug costs, and finally by catastrophic coverage for 95 percent of any further prescription-drug costs in a given year" (Bach & McClellan, 2006). This "doughnut hole" may be more likely to negatively impact women than men because of women's lower incomes, but studies on this question are still pending.

In addition to higher out-of-pocket expenses, women appear to have higher healthcare expenditures than men. While this is true in general, there are exceptions for certain procedures and kinds of care:

• "Among those who had at least one health care expense in 2002, the average per-person expenditure was higher for females ($3,461) than for males ($3,116). However, men's expenditures exceeded women's for hospital inpatient services ($14,221 compared to $10,371), home health services, and hospital outpatient services, while women's expenditures exceeded men's in the categories of office-based medical services and prescription drugs" (Health Resources and Services Administration, 2005b).
• "Women ... had significantly lower self-reported health status and lower mean education and income than men. Women had significantly higher mean number of visits to their primary care clinic and diagnostic services than men. Mean charges for primary care, specialty care, emergency treatment, and annual total charges were all significantly higher for women than men; however, there were no differences for mean hospitalization or hospital charges. This confirms the notion that women have higher medical care service utilization and higher associated charges than men" (Bertakis et al., 2000).

Costs also may be driven by age as well as gender:

• "Medicare spending in the last year of life is strongly associated with age, rather than gender. Our age-specific analyses showed that total Medicare expenditures were 70% higher for the youngest decedents, those who were age 65 to 69 than for the oldest, who were age 85 and above. Indeed, overall Medicare expenditures did not differ by gender. However, Medicare expenditures for SNF [skilled nursing facilities] and home health care in the last year of life were higher for women than men and expenditures for inpatient and outpatient care were higher for men" (Bird, Shugarman, & Lynn, 2002).

The U.S. healthcare system is a patchwork overlay of a number of distinct systems of care and a variety of programs intended to serve as safety nets. Consequently the resulting system is imbalanced in many ways that complicate access to care and fail to maximize overall quality of care. Thus, despite spending more money per capita on healthcare than other industrialized nations, the quality of care in the United States remains poor by comparison. Several estimates project that U.S. patients receive a little over half of the care they should receive. This performance is better in other nations, as well as in systems such as the Department of Veterans Affairs' that are more structured and take advantage of technological advances to coordinate and improve quality of care for their beneficiaries. Thus, systems-level changes to the U.S. healthcare system likely would result in substantial improvements to quality of care, as well as reducing disparities and potentially reducing overall costs. Several movements to enact systems-level change (e.g., the movement toward patient-centered care), may provide useful models or partners in a movement toward gender-based medicine.

Nearly a fifth of the U.S. population lacks health insurance coverage. More women than men have health insurance coverage; one contributing factor is that women are more likely to get public assistance through Medicaid because of pregnancy. Men are more likely to hold health insurance policies in their own names, while women are more likely to be covered as dependents, making them vulnerable to disruptions in care due to death and divorce (or because a husband is older and retires before his wife is eligible for Medicare). Income is highly associated with private health insurance status, with higher-income people having more coverage. Minorities, and recent immigrants in particular, are less likely to have health insurance. Lack of health insurance is associated with worse health outcomes across the board, included increased mortality rates and the receipt of fewer preventive services.

Women are financially disadvantaged compared with men and also have greater family responsibilities. This makes healthcare costs, including out-of-pocket costs, a greater burden for women than for men. Women pay a larger percentage of their income out-of-pocket for prescription drug coverage and also are more likely than men to skip needed doses of medications because of cost limitations. Because of their lower incomes, women also may be more sensitive to differences in co-pay amounts, thus contributing to poorer quality of care and reduced care outcomes.

Current as of March 2007