Global Diversity of Health System Financing and Delivery

49CHAPTER 7

privately structured GP-based primary care is more efficient and effective than various clinic-based forms of primary care services. Recent

movement in Northern and Central Europe toward more private GPs,

along with continued private office–based primary care in much of

Canada, the United States, and economically developed countries in

Asia, raises complex policy issues for international organizations like

the World Health Organization (WHO), as well as national policymakers. In the hospital sector, existing levels of clinical quality and patient

responsiveness in publicly operated command-and-control institutions

will increasingly have to compete with those of semi-autonomous public hospitals, as well as various types of private, sometimes very innovative providers. In the financing arena, continued pressure on publicly

raised health system revenues is likely to erode longtime commitments

in some tax-funded health systems to minimal patient copayments and

low out-of-pocket funding.

An additional set of challenges will arise from recent commitments

by international organizations like WHO to restructure health systems

in developed countries to better address the social determinants of

health. This new, incomplete strategy calls for a dramatic expansion of

health sector responsibility to include a wide range of existing institutional arrangements in housing, education, work-life, and social and

political decision-making. The influential 2010 Strategic Review of

Health Inequalities in England entitled “Fair Society, Healthy Lives,”

led by Sir Michael Marmot, a British epidemiologist, called for the

elimination of all “inequities in power, money, and resources.” Separate

from the political dimensions of this proposed new paradigm, how

such fundamental societal change will be funded and implemented has

yet to be addressed.

Looking forward, among the most essential challenges to national

decision-makers in the coming period will be four specific health system imperatives:

1. Finding a more sustainable balance between ethics and funding.

Policymakers in publicly funded health systems face a growing

gap between patient expectations of high-quality clinical care, staff

expectations of better compensation, and the economic imperative

of no new taxes. Recent research has suggested that SHI-funded

health systems, faced with increasing aging and thus proportionally

fewer employed, face a similar gap. While the present solidaristic

foundation for raising collective revenues is insufficient, available

nonsolidaristic tools (copayments, supplemental insurance, private

pay) inevitably contribute to overall inequality. But what then are the

realistic policy alternatives? The minimalist new policy goal necessarily will have to become one of raising new revenues while doing

the least economic and social harm.

2. Developing better strategies to steer provider diversity.

Health systems in developed countries are becoming more diverse

with more and different types of public owners: hospital trusts, state

enterprises, and mixed public-private hospital owners/managers.

There also are more and different types of private providers: not-forprofit community groups, foundations, and cooperatives, as well as

for-profit small local entrepreneurs, large international companies,

and risk capital funds (venture capital). Furthermore, new innovative delivery models are reorganizing traditional service boundaries:

not-for-profit private nursing homes in the Netherlands also provide

outpatient primary care to neighborhood elderly patients, as well

as hospice care; Israeli technology companies combine high-tech

home-based patient monitoring with standard medical and custodial home care services. Public pressure from citizens for more

choice and better outcomes will pressure policymakers toward new,

more accommodative health system arrangements. A 2019 national

government report in Sweden on the hospital sector recommended

a new emphasis on better access to out-of-office hours and out-ofhospital acute care by private as well as public providers.

3. Ensuring better coordination between social and health services.

Tax-funded and SHI-funded systems alike are under intense policy

pressure to develop better strategies to integrate services for the

chronically ill elderly, as a way to improve the quality of services

that these patients receive and to keep them at home healthier and

longer, reducing expensive acute visits to hospitals and emergency

departments. The clear delivery system goal will increasingly be to

keep the elderly out of nursing homes and acute care facilities for as

long as possible.

4. Building labor unions into provider innovation.

In many developed countries, health sector staff, including hospital

physicians, are members of labor unions. Effective policymaking

will require finding mechanisms to build these personnel unions

into accelerated health system restructuring processes. This process

will necessarily involve integrating unions into more innovative,

flexible, fiscally sustainable organizational arrangements with contracts that reward active participation in organizational change,

contracts that pay incentives to more productive employees, quicker

reassignment and redundancy procedures (firing health sector

workers can take a year or longer in some European health systems),

and establishing profit-sharing payments to teams/unions, also in

public sector organizations.

While the structure and complexity of resolving these specific organizational challenges will vary depending on a country’s cultural and

institutional context, the commonality of these problems suggests that

health systems in the developed world require a new, broader range of

targeted policy strategies and solutions.

■ FINANCING AND PROVIDING HEALTH SERVICES

IN DEVELOPING COUNTRIES (See also Chap. 474)

Health systems in developing countries reflect a complex combination

of the same core elements found in developed country systems (hospitals, primary care facilities, medical staff, pharmaceuticals) adapted to

different, widely varying organizational, social, political, and economic

contexts and conditions. System structure and provider institutions

typically vary by differing national characteristics including historical

relationships (Anglophone/Francophone/Hispanic/Soviet Semashko/

American institutional and educational links); GDP and per capita

annual national income (low- or middle-income developing countries);

political norms and values; and ethnic and/or cultural mix. Predominantly public sector funding, particularly in lower-income countries,

typically generates substantially lower levels of resources per capita

than in developed countries and tends to be less reliable, particularly

in countries where the economy is dependent on commodity exports.

Service delivery arrangements in developing countries, in turn,

typically have higher provider-to-population ratios as well as, in

public sector institutions, more mixed quality of care. In a number of

middle-income developing countries, migration of trained medical

staff to practice in higher-paying developed country health systems

(often going to countries with historical relationships and/or where

they received advanced training) further depletes available medical

resources. In nearly all developing countries, private sector providers play an important supplemental role, with some middle-income

developing countries like China currently encouraging their further

development.

Most middle- and lower-income developing countries struggle to

fund high-quality individual health services. Recent emphasis on universal health coverage has intensified that struggle. In middle-income

developing countries (Table 7-3), World Bank data from 2016 show

TABLE 7-3 Middle-Income Developing Countries: Total Health

Expenditure (% of gross domestic product)

Middle-Income Developing Countries

Kazakhstan 3.53%

Thailand 3.71%

Malaysia 3.80%

Turkey 4.31%

China 4.98%

Botswana 5.46%

Mexico 5.47%

Colombia 5.91%

50PART 1 The Profession of Medicine

TABLE 7-4 Low-Income Developing Countries: Total Health

Expenditure (% of gross domestic product)

Low-Income Developing Countries

Nigeria 3.65%

India 3.66%

Ethiopia 3.97%

Nepal 6.29%

Honduras 8.40%

TABLE 7-5 Middle-Income Developing Countries: Per Capita Health

Expenditures

Middle-Income Developing Countries

Thailand $221

Kazakhstan $262

Colombia $340

Malaysia $361

Botswana $379

China $398

Mexico $461

Turkey $468

TABLE 7-6 Low-Income Developing Countries: Per Capital Health

Expenditures

Low-Income Developing Countries

Ethiopia $27

Nepal $45

India $62

Nigeria $79

Honduras $199

a range of health expenditure rates as a percentage of GDP, including

Kazakhstan at 3.53% of GDP, Thailand at 3.71%, Malaysia at 3.80%,

Turkey at 4.31%, China at 4.98%, Botswana at 5.46%, Mexico at 5.47%,

and Colombia at 5.91%. Total health spending in low-income developing countries (Table 7-4) ranges from 3.65% of GDP for Nigeria, 3.66%

for India, 3.97% for Ethiopia, 6.29% for Nepal, to 8.40% for Honduras.

Given lower aggregate GDP levels, per capita annual expenditures

are considerably less than those found in developed countries. In

middle-income developing countries (Table 7-5), Thailand spent (2016

data in adjusted USD) $221 annually per person, Kazakhstan spent

$262, Colombia spent $340, Malaysia spent $361, Botswana spent $379,

China spent $398, Mexico spent $461, and Turkey spent $468. Among

low-income developing countries (Table 7-6), Ethiopia spent $27 per

person annually, Nepal spent $45, India spent $62, and Nigeria spent

$79, whereas Honduras spent $199.

China provides an interesting example of financing and service

delivery development in middle-income developing countries. Financing reforms replaced fully publicly funded services with three new

arrangements tied to work status and residence: (1) Urban Employee

Basic Medical Insurance in 1998 (incorporating privately funded medical savings accounts—a concept pioneered in Singapore); (2) Urban

Resident Basic Medical Insurance in 2007; and (3) New Rural Cooperative Medical Scheme in 2007. The urban employee program is an

SHI model reflecting the rapid rate of economic growth and increasing

incomes for urban workers. Starting in 2013, the Chinese government

increasingly emphasized the development of new private hospitals and

promotion of private insurance in urban areas. These and other health

sector reforms became possible as continued strong economic growth

over 30 years raised an estimated 300 million Chinese into the middle

class, generating the requisite private as well as public revenues to

underpin major structural health sector change.

Service delivery in developing countries varies widely in access,

quality, and outcomes across and also within many developing countries. Medical services and tertiary institutions in urban areas of China,

for example, operate at a substantially higher standard of service than

those typically available in poorer rural regions. Similar disparities

exist in wealthier parts of India such as Rajasthan, whereas in poorer

states such as Bihar, primary care is mostly delivered by community

“volunteers” with basic medical training, supervised by a GP.

Two critical challenges for all developing country health systems

are contingent on generating adequate future funding flows. First, the

current push from United Nations agencies to achieve universal health

coverage will require additional public and private sector funding to

pay for the necessary new providers and services. Second, available

funding will need to be more effectively targeted on needed and appropriate services, with minimized managerial inefficiencies and substantially less political corruption.

Both forms of expanded funding will be dependent on strong

national and global economic growth, which in turn will require continued country-level economic and political reforms. Achieving both

funding-related objectives will require considerable international as

well as national effort.

■ FURTHER READING

Barber SL et al: Price Setting and Price Regulation in Health Care:

Lessons for Advancing Universal Health Coverage. Geneva, World

Health Organization, Organization for Economic Co-operation

and Development, 2019. https://apps.who.int/iris/bitstream/han

dle/10665/325547/9789241515924-eng.pdf.

Figueras J, McKee M (eds): Health Systems, Health, Wealth, and

Societal Well-Being: Assessing the Case for Investing in Health Systems.

Maidenhead, Open University Press/McGraw-Hill Education, 2011.

www.euro.who.int/__data/assets/pdf_file/0007/164383/e96159.pdf.

Haseltine W: Affordable Excellence: The Singapore Health Story.

Washington, Brookings Institution Press, 2013. www.brookings.edu/

wp-www.brookings.edu/wp-content/uploads/2016/07/AffordableExcellencePDF.pdf.

Kuhlmann E et al (eds): The Palgrave International Handbook on

Healthcare Policy and Governance. London, Palgrave MacMillan,

2015.

Rice T et al: United States of America: Health System Review. Health in

Transition (HiT) Series 15 (3). Brussels, European Observatory on

Health Systems and Policies, 2013. www.euro.who.int/__data/assets/

pdf_file/0019/215155/HiT-United-States-of-America.pdf.

Safety and quality are two of the central dimensions of health care. In

recent years, it has become easier to measure safety and quality, and

it is increasingly clear that performance in both dimensions could be

much better. The public is—with good justification—demanding measurement and accountability, and payment for services will increasingly

be based on performance in these areas. Thus, physicians must learn

about these two domains, how they can be improved, and the relative

strengths and limitations of the current ability to measure them.

Safety and quality are closely related but do not completely overlap.

The Institute of Medicine has suggested in a seminal series of reports

that safety is the first part of quality and that the health care system

must first and foremost guarantee that it will deliver safe care, although

quality is also pivotal. In the end, it is likely that more net clinical

8 The Safety and Quality of

Health Care

David W. Bates

The Safety and Quality of Health Care

51CHAPTER 8

action when one is interrupted partway through it by a page, for example. Approaches that may be helpful in this area include minimizing

interruptions and setting up tools that help define the urgency of an

interruption.

Complexity represents a key issue that contributes to errors. Providers are confronted by streams of data (e.g., laboratory tests and vital

signs), many of which provide little useful information but some of

which are important and require action or suggest a specific diagnosis.

Tools that emphasize specific abnormalities or combinations of abnormalities may be helpful in this area.

Transitions between providers and settings are also common in

health care, especially with the advent of the 80-h workweek, and generally represent points of vulnerability. Tools that provide structure in

exchanging information—for example, when transferring care between

providers—may be helpful.

The Frequency of Adverse Events in Health Care Most large

studies focusing on the frequency and consequences of adverse events

have been performed in the inpatient setting; some data are available

for nursing homes, but much less information is available about the

outpatient setting. The Harvard Medical Practice Study, one of the

largest studies to address this issue, was performed with hospitalized

patients in New York. The primary outcome was the adverse event:

an injury caused by medical management rather than by the patient’s

underlying disease. In this study, an event either resulted in death or

disability at discharge or prolonged the length of hospital stay by at

least 2 days. Key findings were that the adverse event rate was 3.7% and

that 58% of the adverse events were considered preventable. Although

New York is not representative of the United States as a whole, the

study was replicated later in Colorado and Utah, where the rates were

essentially similar. Since then, other studies using analogous methodologies have been performed in various developed nations, and the

rates of adverse events in these countries appear to be ~10%. Rates of

safety issues appear to be even higher in developing and transitional

countries; thus, this is clearly an issue of global proportions.

In the Harvard Medical Practice Study, adverse drug events (ADEs)

were most common, accounting for 19% of all adverse events, and were

followed in frequency by wound infections (14%) and technical complications (13%). Almost half of adverse events were associated with a

surgical procedure. Among nonoperative events, 37% were ADEs, 15%

were diagnostic mishaps, 14% were therapeutic mishaps, 13% were

procedure-related mishaps, and 5% were falls.

ADEs have been studied more than any other error category. Studies

focusing specifically on ADEs have found that they appear to be much

more common than was suggested by the Harvard Medical Practice

Study, although most other studies use more inclusive criteria. Detection approaches in the research setting include chart review and the

use of a computerized ADE monitor, a tool that explores the database

and identifies signals that suggest an ADE may have occurred. Studies

that use multiple approaches find more ADEs than does any individual

approach, and this discrepancy suggests that the true underlying rate in

the population is higher than would be identified by a single approach.

About 6–10% of patients admitted to U.S. hospitals experience an ADE.

Injuries caused by drugs are also common in the outpatient setting.

One study found a rate of 21 ADEs per every 100 patients per year

when patients were called to assess whether they had had a problem

with one of their medications. The severity level was lower than in

the inpatient setting, but approximately one-third of these ADEs were

preventable.

The period immediately after a patient is discharged from the hospital appears to be very risky. A recent study of patients hospitalized on a

medical service found an adverse event rate of 19%; about one-third of

those events were preventable, and another one-third were ameliorable

(i.e., they could have been made less severe). ADEs were the single

leading error category.

Prevention Strategies Most work on strategies to prevent adverse

events has targeted specific types of events in the inpatient setting, with

nosocomial infections and ADEs having received the most attention.

Nosocomial infection rates have been reduced greatly in intensive care

Successive layers of defenses, barriers, and safeguards

Other holes due to

latent conditions

(resident “pathogens”)

Some holes due

to active failures

Hazards

Losses

FIGURE 8-1 “Swiss cheese” diagram. Reason argues that most accidents occur

when a series of “latent failures” are present in a system and happen to line up in

a given instance, resulting in an accident. Examples of latent failures in the case

of a fall might be that the unit is unusually busy and the floor happens to be wet.

(Adapted from J Reason: BMJ 320:768, 2000.)

benefit will be derived from improving quality than from improving

safety, though both are important and safety is in many ways more tangible to the public. The first section of this chapter will address issues

relating to the safety of care and the second will cover quality of care.

■ SAFETY IN HEALTH CARE

Safety Theory and Systems Theory Safety theory clearly points

out that individuals make errors all the time. Think of driving home

from the hospital: you intend to stop and pick up a quart of milk on the

way home but find yourself entering your driveway without realizing

how you got there. Everybody uses low-level, semiautomatic behavior

for many activities in daily life; this kind of error is called a slip. Slips

occur often during care delivery—e.g., when people intend to write

an order but forget because they must complete another action first.

Mistakes, by contrast, are errors of a higher level; they occur in new or

nonstereotypic situations in which conscious decisions are being made.

An example would be dosing of a medication with which a physician

is not familiar. The strategies used to prevent slips and mistakes are

often different.

Systems theory suggests that most accidents occur as the result of a

series of small failures that happen to line up in an individual instance

so that an accident can occur (Fig. 8-1). It also suggests that most

individuals in an industry such as health care are trying to do the right

thing (e.g., deliver safe care) and that most accidents thus result from

defects in systems. Systems should be designed both to make errors less

likely and to identify those that do inevitably occur.

Factors That Increase the Likelihood of Errors Many factors

ubiquitous in health care systems can increase the likelihood of errors,

including fatigue, stress, interruptions, complexity, and transitions. The

effects of fatigue in other industries are clear, but its effects in health

care have been more controversial until recently. For example, the accident rate among truck drivers increases dramatically if they work over

a certain number of hours in a week, especially with prolonged shifts.

A recent study of house officers in the intensive care unit demonstrated that they were about one-third more likely to make errors

when they were on a 24-h shift than when they were on a schedule that

allowed them to sleep 8 h the previous night. The American College of

Graduate Medical Education has moved to address this issue by putting

in place the 80-h workweek. Although this stipulation is a step forward,

it does not address the most important cause of fatigue-related errors:

extended-duty shifts. High levels of stress and heavy workloads also

can increase error rates. Thus, in extremely high-pressure situations,

such as cardiac arrests, errors are more likely to occur. Strategies such

as using protocols in these settings can be helpful, as can simple recognition that the situation is stressful.

Interruptions also increase the likelihood of error and occur frequently in health care delivery. It is common to forget to complete an

52PART 1 The Profession of Medicine

settings, especially by using checklists. For ADEs, several strategies

have been found to reduce the medication error rate, although it has

been harder to demonstrate that they reduce the ADE rate overall, and

no studies with adequate power to show a clinically meaningful reduction have been published.

Implementation of checklists to ensure that specific actions are carried out has had a major impact on rates of catheter-associated bloodstream infection and ventilator-associated pneumonia, two of the most

serious complications occurring in intensive care units. The checklist

concept is based on the premise that several specific actions can reduce

the frequency of these issues; when these actions are all taken for every

patient, the result has been an extreme reduction in the frequency of

the associated complication. These practices have been disseminated

across wide areas in the state of Michigan.

Computerized physician order entry (CPOE) linked with clinical

decision support reduces the rate of serious medication errors, defined

as those that harm someone or have the potential to do so. In one

study, CPOE, even with limited decision support, decreased the serious

medication error rate by 55%. CPOE can prevent medication errors by

suggesting a default dose, ensuring that all orders are complete (e.g.,

that they include dose, route, and frequency), and checking orders for

allergies, drug–drug interactions, and drug–laboratory issues. In addition, clinical decision support can suggest the right dose for a patient,

tailoring it to the level of renal function and age. In one study, patients

with renal insufficiency received the appropriate dose only one-third

of the time without decision support, whereas that fraction increased

to approximately two-thirds with decision support; moreover, with

such support, patients with renal insufficiency were discharged from

the hospital half a day earlier. As of 2019, over 95% of U.S. hospitals

had implemented CPOE, although the decision support often is still

limited.

Another technology that can improve medication safety is bar

coding linked with an electronic medication administration record.

Bar coding can help ensure that the right patient gets the right medication at the right time. Electronic medication administration records

can make it much easier to determine what medications a patient has

received. Studies to assess the impact of bar coding on medication

safety are under way, and the early results are promising. Another technology to improve medication safety is “smart pumps.” These pumps

can be set according to which medication is being given and at what

dose; the health care professional will receive a warning if too high a

dose is about to be administered.

The National Safety Picture Several organizations, including

the National Quality Forum and The Joint Commission, have made

recommendations for improving safety. The National Quality Forum

has released recommendations to U.S. hospitals about what practices

will most improve the safety of care, and all hospitals are expected

to implement these recommendations. Many of these practices arise

frequently in routine care. One example is “readback,” the practice

of recording all verbal orders and immediately reading them back to

the physician to verify the accuracy of what was heard. Another is the

consistent use of standard abbreviations and dose designations; some

abbreviations and dose designations are particularly prone to error

(e.g., 7U may be read as 70).

Measurement of Safety Measuring the safety of care is difficult

and expensive, since adverse events are, fortunately, rare. Most hospitals rely on spontaneous reporting to identify errors and adverse

events, but the sensitivity of this approach is very low, with only ~1 in

20 ADEs reported. Promising research techniques involve searching

the electronic record for signals suggesting that an adverse event has

occurred. These methods are not yet in wide use but will probably be

used routinely in the future. Claims data have been used to identify

the frequency of adverse events; this approach works much better for

surgical care than for medical care and requires additional validation.

The net result is that, except for a few specific types of events (e.g., falls

and nosocomial infections), hospitals have little idea about the true

frequency of safety issues.

Nonetheless, all providers have the responsibility to report problems with safety as they are identified. All hospitals have spontaneous

reporting systems, and if providers report events as they occur, those

events can serve as lessons for subsequent improvement.

Conclusions about Safety It is abundantly clear that the safety of

health care can be improved substantially. As more areas are studied

closely, more problems are identified. Much more is known about

the epidemiology of safety in the inpatient setting than in outpatient

settings. A number of effective strategies for improving inpatient safety

have been identified and are increasingly being applied. Some effective strategies are also available for the outpatient setting. Transitions

appear to be especially risky. The solutions to improving care often

entail the consistent use of systematic techniques such as checklists

and often involve leveraging of information technology. Nevertheless,

solutions will also include many other domains, such human factors

techniques, team training, and a culture of safety.

■ QUALITY IN HEALTH CARE

Assessment of quality of care has remained somewhat elusive, although

the tools for this purpose have increasingly improved. Selection of

health care and measurement of its quality are components of a complex process.

Quality Theory Donabedian has suggested that quality of care can

be categorized by type of measurement into structure, process, and outcome. Structure refers to whether a particular characteristic is applicable in a particular setting—e.g., whether a hospital has a catheterization

laboratory or whether a clinic uses an electronic health record. Process

refers to the way care is delivered; examples of process measures are

whether a Pap smear was performed at the recommended interval or

whether an aspirin was given to a patient with a suspected myocardial

infarction. Outcome refers to what happens—e.g., the mortality rate in

myocardial infarction. It is important to note that good structure and

process do not always result in a good outcome. For instance, a patient

may present with a suspected myocardial infarction to an institution

with a catheterization laboratory and receive recommended care,

including aspirin, but still die because of the infarction.

Quality theory also suggests that overall quality will be improved

more in the aggregate if the performance level of all providers is raised

rather than if a few poor performers are identified and punished. This

view suggests that systems changes are especially likely to be helpful in

improving quality, since large numbers of providers may be affected

simultaneously.

The theory of continuous quality improvement suggests that organizations should be evaluating the care they deliver on an ongoing basis

and continually making small changes to improve their individual

processes. This approach can be very powerful if embraced over time.

Several specific tools have been developed to help improve process

performance. One of the most important is the Plan-Do-Check-Act

cycle (Fig. 8-2). This approach can be used for “rapid cycle” improvement of a process—e.g., the time that elapses between a diagnosis of

pneumonia and administration of antibiotics to the patient. Some

statistical tools, such as control charts, are often used in conjunction

to determine whether progress is being made. Because most medical

care includes one or many processes, this tool is especially important

for improvement.

Factors Relating to Quality Many factors can decrease the level

of quality, including stress to providers, high or low levels of production pressure, and poor systems. Stress can have an adverse effect on

quality because it can lead providers to omit important steps, as can a

high level of production pressure. Low levels of production pressure

sometimes can result in worse quality, as providers may be bored or

have little experience with a specific problem. Poor systems can have a

tremendous impact on quality, and even extremely dedicated providers

typically cannot achieve high levels of performance if they are operating within a poor system.

Data about the Current State of Quality A study published by

the RAND Corporation in 2006 provided the most complete picture of