Mortality and mobidity indicators

Junior residentDr Priyamadhaba Behera

Mortality and Morbidity indicators

Outline

• Rate,ratio,proportion

• Measures of mortality

• Measures of morbidity

• Aggregates measures of mortality

• Aggregates measures of morbidity and mortality

12 Properties of Proportionsp takes on values between 0 and 1 (p is a fraction)p has no units

p may be multiplied by a constant kWhere k is a number such as 100, 1,000, or 100,000

Types of Mortality Rates/Ratio• annual death rate• crude death rates• infant mortality rates (ratio)• neonatal mortality rates• postneonatal mortality rates• perinatal mortality rates• fetal death rates• fetal death ratios• abortion rates• maternal mortality rates• adjusted mortality rates• standardized mortality ratio• specific death rates• proportionate mortality rate- case fatality rate• mortality crossover – mortality time trends

Your Assignment: familiarize yourself with the definitions

of these terms

Three Levels of Rates

• Crude rates

• Specific rates/ratios

• Adjusted rates

Crude Death Rates• Does NOT account for differences of

age, sex, etc. in any aspect of death

• Info needed: total deaths total population a given period of time

Crude Death Rates(cont’d)

Cause Specific Mortality Rate

Case Fatality Rate

Specific Death Rates• For example: Early life mortality measures

Specific Death Rates

• For example: infant mortality


• Neonatal mortality rate

(cont’d)

• Postneonatal mortality rate


• Perinatal mortality rates

(cont’d)


• Fetal death rate

(cont’d)

More Convenient:

Summarize an entire situation with a single number calculated for each subpopulation, a number that adjusts for difference in composition

Two Ways:

1. Direct method of standardization

2. Indirect method of standardization

Direct Method of Standardization:

Step 1: Select the standard population.

Step 2: compute the expected events that would result

if ,instead of having different age distributions, all populations were to have same standard age structure

Step 3:Compute the adjusted rate as total expected events in the

group divided by the total standard population

Adjusted Death RatesAge Adjusted Rates

• Direct Method

What data available for you for direct method?


• Direct Method(cont’d)

Indirect Method of Standardization:

Step 1: use a set of standard age-specific rates along with the actual age composition of each population

Step 2: compute the number of events that would have occurred in the two groups if each took on the age specific rates of the standard population while retaining its own age distribution

Step 3: compute standardized event ratio as observed/expected events for each group

The indirect method often concludes with this ratio.

Step 4: actual age adjusted rates for each group= event rate in the standard population x standardized event ratio of the group


• Indirect Method Standard Mortality Ratio

(cont’d)

Standardized Mortality Ratio (SMR)

• Must know when to use an adjusted rate rather than crude rate

• If no confounders: the crude rate is adequate

• If confounders present: subgroup specific rates are sufficient

• Adjusted rates should be considered if they are meaningful

• If distribution of standard population is radically different than the populations being compared, standardization is inappropriate

• Also, when direct standardization is applied, subgroup specific rates should have same general trends in all the groups being compared as well as in the standard population

•Direct method of standardization is used more frequently than indirect method

• Direct method requires subgroup specific rates for all popns.

• Application of either method should lead to same conclusion

Life Expectancy

• Summary of all age-specific mortality rates

• Estimates hypothetical length of life of a cohort born in a particular year

This assumes that current mortality rates will continue

Measures of Morbidity

Sources of Morbidity Statistics• Clinical and hospital• Managed care• Registries• Vital statistics• Surveys• Disease reporting• Insurance and pre-paid med. care plans• Absenteeism records

Terms Related to Morbidity• Morbidity

The extent of illness, injury or disability in a defined population

• Incidence of a disease (Incidence rate)The number of new cases of a disease that

occur during a specified time period (numerator) in a population at risk for developing the disease (denominator)

• Prevalence of a disease (Prevalence rate)The number of total cases of disease present

at a particular time (numerator) in a specific population (denominator)

• RiskThe likelihood that an individual will contract a

disease

Characteristics

RISK PREVALENCE INCIDENCE RATE

Probability of disease

% of pop. with the disease

Rapidity of disease

occurrence

No units No units Cases per person-time

Newly diagnosed

Existing Newly diagnosed

“Cumulative incidence”

“Incidence density”

1. “Do you currently have asthma?” Point prevalence

2. “Have you had asthma during the last 1 years?” Period prevalence

3. “Have you ever had asthma?” Cumulative incidence

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Other Measures of morbidity

1. Notification rate

2. Attendance rates at OPD, health centers

3. Admission, readmission, and discharge rates

4. Duration of stay in the hospital

5. Spells of sickness or absence from work or school

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Problems with Numerators• Who has the disease?

• Who to include in numerator?

• Interview errors

Problems with Denominator

• Selective undercounting

• Everyone in denominator must have potential to enter numerator group

Problems with Hospital Data

• Selective (many reasons)

• Data may be unavailable, etc

IncidenceThe two forms of incidence are:

• Cumulative incidence• "risk of disease“• measures the proportion of persons who develop a disease in a

known span of time• Incidence rate

• "rate of disease“• measures the rate of new disease

occurrence over time

Cumulative incidence

• Cumulative Incidence =

Number of people who get a disease during a specified period * 1000

Number of people free of the disease in the population at risk at the beginning of a study period

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Incidence Rate

• Measures the rapidity with which newly diagnosed cases of the disease of interest develop observe a population count # of new cases measure net time

• individuals in population at risk of developing disease

• person-time person-years patient-days

Incidence rate per 1,000

• Number of new cases of a disease occurring in the population during a specified period of time * 1000

Number of persons who are at risk of developing the disease during that period of time

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Incidence density

• if people at risk are observed for different periods of time

• The denominator consists of the sum of the units of time that each individual was at risk and was observed.

• This is called person-time and is often expressed in terms of person-months or person-years of observation.

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Person time

• 1 person at risk who is observed for one year = 1 person-year.

• 1 person at risk observed for 5 years = 5 person-years.

• 5 people at risk, each of whom is observed for only 1 year = 5 person-years.

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Incidence Rate (Attack Rate) (cont.)

• Can be used for specific exposures

• Also used for multiple exposures

• Other terms:primary casesecondary attack

• secondary cases

Attack rates

Incidence and Attack Rates

• Primary Attack rates

Incidence and Attack rates(cont’d)

• Secondary Attack rates

Prevalence• Measure of the number (or proportion) of

cases in a given population• What is the difference between prevalence

and incidence?Prevalence a slice thru a population at a

given point in time that determines who has the disease and who does not, while Incidence only looks at new cases

• In steady state situation (no change in rate or net population)Prevalence = Incidence X Duration of disease

Prevalence

• Point prevalence- point in time

• Period prevalence- during a defined range of time

Prevalence Rates

Prevalence Rates

• Point

• Period

(cont’d)

2. Aggregate Measures:Mortality-Based

Indicators

Life expectancy

Expected years of life lost

Potential years of life lost

Expectancies and Gaps

• From a typical survival curve, we can either consider the life expectancy (“E”), or the gap (“G”) between current life expectancy and some ideal.

• Expectancies are generic; gaps can be disease-specific (e.g., life yrs lost due to cancer)

G

0%

20%

40%

60%

80%

100%

0 10 20 30 40 50 60 70 80 90 100

E

Classifying Health Gaps

• Gaps: Compare population health to some target. = Difference between time lived in health states less than ideal health, and the specified target

• The implied norm or target can be arbitrary, but must be explicit and the same for all populations being compared. The precise value does not matter

Gaps: Expected Years of Life Lost

• Uses population life expectancy at the individual’s age of death

Problems: different countries may have different life expectancies. It’s overall mortality, so cannot identify impact of a disease.

• Standard Expected Years of Life Lost

Reference is to an “ideal” life expectancy

• E.g., Japan (82 years for women)

• Area between survivorship curve and the chosen norm

Potential Years of Life Lost (PYLL)

• PYLL = ( “normal age at death” – actual age at death). Doesn’t much matter what age is chosen as reference; typically 75

• Attempts to represent impact of a disease on the population: death at a young age is a greater loss than death of an elderly person

• Focuses attention on conditions that kill younger people (accidents; cancers)

• All-causes or cause-specific

3. Aggregate Measures that Combine Mortality &

Morbidity

Health expectancies

Health gaps

Composite Measures

• Aim to represent overall health of a population

• Composite measures combine morbidity and mortality into a health index. (An index is a numerical summary of several indicators of health)

• Mortality data typically derived from life tables; morbidity indicators from health surveys, e.g.

• Self-rated health

• Disability or activity limitations

• A generic health index

Different Types of Morbidity Scales for Use in Composite Measures

• Generic instruments cover a wide range of health topics, e.g. reflecting the WHO definition. These can be health profiles (e.g., Sickness Impact Profile, SF-36) or “health indexes” (e.g., Health Utilities Index, EuroQol)

• Specific instrumentsDisease-specific (e.g., Arthritis Impact

Measurement Scale)Age-specific (e.g., Child Behavior Checklist)Gender-specific (e.g., Women’s Health

Questionnaire)

Survivorship Functions for Health States

G

0%

20%

40%

60%

80%

100%

0 10 20 30 40 50 60 70 80 90 100

H

Survivors

Age

This diagram extends the earlier one by recognizing that not all survivors are perfectly healthy.

The lower area ‘H’ shows the proportion of people in good health (however defined); it shows healthy life expectancy. The top curve shows deaths; intermediate area represents levels of disability.

Area ‘G’ again represents the health gap. The question arises whether the people with a disability ought to be counted with H or with G.

Deaths

Health expectancies

• Generic term: any expectation of life in various states of health. Includes other, more specific terms, such as Disability Free Life Expectancy

• Two main classes:Dichotomous rating: two health statesHealth state valuations for a range of

levels

I. Dichotomous expectancies

• Here full health is rated 1, and any state of poor health (mild, moderate, severe disability) is rated 0.

• This leads to Disability-free life expectancy (DFLE): weight of 1 for “no disability” and 0 for all other states.

• = Expectation of life with no disability, or Healthy Life Expectancy (HLE)

• Very sensitive to threshold of disability chosen

Sullivan(1971)

II. Polytomous states and valuations (Wilkins and Adams-1983)

• These incorporate many levels of disability into life expectancy estimates and count time spent with each level of disability.

• Polytomous model (three or more health states defined: weights assigned to each; generally 0 to 1.0. These may be added together and compared across diseases)

• = Health-adjusted life expectancy (HALE)

• First calculated for Canada by Wilkins. Four levels of severity & arbitrary weights.

• Recent work uses utility weights. E.g. from Health Utilities Index, Quality of Well-Being Scale, EUROQoL, etc.

Polytomous Curves Showing Quality of Survival

G

0%

20%

40%

60%

80%

100%

0 10 20 30 40 50 60 70 80 90 100

H

Survivors

Age(years)

This diagram illustrates several classes of disability, each having a separate severity weighting.

The area ‘H’ again includes healthy people, but the definition may have changed. The top curve shows deaths; intermediate curves represent various levels of disability.

Deaths

Relationship between Life Expectancy, Health Expectancy and Health-Adjusted

Life Expectancy

Health-AdjustedLife Expectancy

LifeExpectancy

HealthyLifeExpectancy

By down-weighting the various levels of disability,the HALE falls between LE and HLE

Gap Measures: QALYs & DALYs

• Gap measures can also use a weighting for intermediate health states. This is necessary to combine time lost due to ill health with time lost due to premature mortality

• Quality Adjusted Life Years (QALYs) lostCommon outcome measurement in clinical trials,

program evaluation

Record extra years of life provided by therapy and quality of that life

Typically use utility scale running from 0 to 1

• DALYS (disability-adjusted life years) lost

Complementarity of Health Expectancies and Health Gaps

SLE

LE

HALE

HLE

LE SEYLL SURVIVAL

HALE HALYPOLYTOMOUS

HLE ?DICHOTOMOUS

Birth

LE = Life Expectancy; SLE = Standard LE; HALE = Health-Adjusted LE; HLE = Healthy LE; SEYLL = Standard Expected Years of Life Lost

HALY = Health-Adjusted Life Years Lost

Gaps

Expectancies

Age

Disability Adjusted Life Years

Possibilities and Problems

What are DALYs?

• DALYs = Disability Adjusted Life Years

• A common measurement unit for morbidity and mortality

• Facilitates comparisons of all types of health outcomes

Possible use of DALYs

• Quantitative analysis of the burden of disease

• Analysis of cost-effectiveness of alternative interventions

• Selection of a package or list of interventions deliverable within the available budget

JL Bobadilla, WHO: 1996

What is the Global Burden of Disease study?

• Backed by the WHO and the World Bank

• A quantitative overview of the burden of disease world-wide

• Combines information about loss of quality of life with traditional epidemiological information on mortality

• All health outcomes are expressed in DALYs

Possible use of the Global Burden of Disease Study

• Epidemiological surveillance of trends across borders and over time

• Projections for future burden of disease

• Basis of information for decision-making on priorities in health research and health policy

CLICK TO ENLARGE

How are DALYs constructed?

• A DALY is a health outcome measure with two main componentsQuality of life reduced due to a

disabilityLifetime lost due to premature

mortality.

DALYs due to living with disability (Red area measures DALYs. Red + white is a “normal”

life)

82,5 YEARS

NO DISABILITY

DALYs due to early death(Red area measures DALYs. Red + white is a standard

life)

NO DISABILITY

82,5 YEARS

DALYs due to disability and premature death combined.

NO DISABILITY

82,5 YEARS

Calculation of DALYs (age-weighting and discounting are

omitted for didactic reasons)

• The calculation of DALYs of a woman who has been deaf since she was 5 and dies when she is 50: ( Disability weight of deafness is set at 0.33) :

• Number of healthy life years × the disability weight of full health (0) + life years with disability (50) × disabilty weight for deafness (0,33) + life years lost (30) × the weighting of death (1)

• 5 × 0+ 45 × 0,33 + 30 × 1 = 47.35 DALYs

DALYs and QALYs

• DALY is a modification of QALY (Quality Adjusted Life Years).

• Both concepts combine information about length of life and quality of life.

• A DALY is a negative QALY.

Relation between QALYs and DALYsDALYs = healthy years lost

QALYs = healthy years gained

NO DISABILITY

82,5 YEARS

How are disability adjustments made?

The methods used to assign a disability weightings to life years is a critical part of the DALY approach.– Diagnostic groups must be chosen and

defined.– Descriptions of those diagnostic groups are

developed.– The health states are assigned a disability

weight to indicate the relative severity of each health state.

Current method used for weighting disability

• Disability weights are obtained by posing two different Person Trade-Off (PTO) questions to expert panels

• PTO1 compares life extensions for disabled and healthy people

• PTO2 compares cures for illness with extension of life

Other choices behind DALY

• In addition to adjusting the value of life years with disability weights, and chosing a particular life expectancy, the value of a life year is modified by

• Discounting – the value of a life year now is set higher

than the value of future life years

• Age weighting– life years of children and old people are

counted less

Age-weights

The effect of age-weighs and discounting

Calculating DALY score,with age weighting and discounting.

• Girl, 5 years old, with below-knee amputation who lives until she is 82,5:

• DALYs= life years lived with disease (77,5) × disability weight (0,3) × age- weight (a1)× discounting factor (d2)

• 77.5 × 0.3 × a1 × d2 = 10.5 DALYs

PROBLEMS of the DALY approach

• Is it true? Questions of the validity of the

results

• Is it just? Questions of the distribution

between groups

General problems of validity

• What is “Quality of Life” or “Disability weighting of life years”?

• Can quality of life be measured in a single and precise number?

• Does the same health problem have equal impact on different persons or groups?

• Is there a general agreement to underlying value choices: discounting, age weighting and choice of life expectancy

Validity problems of the current PTO protocol

• Lack of simplicity, difficult to understand

• Forced consistency between two questions that are essentially different

• Impossible to answer that all individuals are equally valuable

• The expert panel may not represent the values of other people

Validity problems of epidemiological estimates

• Epidemiological data for Africa, Latin America and Asia are crude estimates.

• The uncertainty of the figures of prevalence, may be hidden in the seemingly mathematical rigor of the results.

• Lack of uniform diagnostic criteria. I.e. what do we mean by “depression”?

Justice

• The DALY approach has been criticised for discriminating– the young– the elderly– future generations (future health

benefits)– the disabled– women

The young

• The 5-year-old girl in the example above yielded 10,5 DALYs.

• However, the DALY score without age-weight and discounting would be

• 77.5 × 0.3 = 23,3 DALYs • This result is twice as high, and would

give her a higher priority.

The elderly

• In the literature on justice in health care, many agree that given a choice, it is more important to save young adults than the very old.

• This view is captured by the DALY (as a time based measure) itself.

Future generations

• The practice of discounting future benefits is also controversial.

• From society’s viewpoint, why should a life year now be of more value than a life year twenty years ahead?

• The implications for preventive services versus curative services are significant. Preventive interventions are given less weight.

The disabled

• The DALY approach opens for including chronic illnesses and disabilities in cost-utility calculation. This is an improvement.

• On the other hand, the current person trade-off protocol explicitly assumes that lives of disabled people have less value and

• implies that disabled people are less entitled to health resources to extend their lives

Example of results• In the protocol behind the present Global Burden of

Disease, a life year for 1000 healthy people has been set as equally valuable as one life year for– 9524 people with quadriplegia– 2660 blind people– 1686 people with Down's syndrome without

cardiac malformation– 1499 deaf people– 1236 infertile people

• WHO has announced a change in approach.

Women

• Underlying value choice: Standard expectation of life at birth is 82.5 years for women, 80 years for men

• The ‘true’ gender gap is greater• Gender gap is adjusted to correspond

to ‘biological differences in survival potential’

• Critique: Might underestimate burden of disease for females relative to males

Anand S, Hanson K. Disability-adjusted life years: a critical

review. Journal of Health Economics 1997;16:658-702.

Arnesen T, Nord E. The value of DALY life: problems with

ethics and validity of disability adjusted life years. BMJ

1999; 319:1423-1425.

Bobadilla J-L, Cowley P, Musgrove P, Saxenian. Design,content and financing of an essential national package ofhealth services. Bulletin of the World Health Organization1994;72:653-662.

REFERENCE LIST

Murray CJ, Lopez AD. Global mortality,disability, and the contribution of risk factors:Global Burden of Disease Study. Lancet1997b;349(9063):1436-42.Murray CJ, Lopez AD. Mortality by cause foreight regions of the world: Global Burden ofDisease Study. Lancet 1997c;349(9061):1269-76.Murray CJ, Lopez AD. Regional patterns ofdisability-free life expectancy and disability-adjusted life expectancy: global Burden ofDisease Study. Lancet 1997d;349(9062):1347-52.

Mortality and mobidity indicators

Health & Medicine

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