AGL 22 – BASICS OF HEALTH RISK APPRAISAL FOR HEALTH ...
MANUAL FOR PARTICIPATS
Item Page Number
1. INTRODUCTION 2
2. Part A: STUDY: THEORY AND PRACTICE 7
3. Part B: STUDY: TECHNIQUE 12
4. Part C: STUDY: RISK ESTIMATION AND
HRA EFFECTIVENESS 19
5. Part D: STUDY: NEW METHODOLOGIES 24
6. EXERCISE: (to follow) -
7. SIMPLIFIED GLOSSARY 27
8. REGISTRATION AND FEEDBACK 40
9. QUIZ ANSWER SHEETS 42
10. SUMMARY LECTURE 51
Copyright 1981/5 R.G.A. Boland, M.D., M.P.H.
A.A. Lisiewicz, M.Sc., Ph.D.
M.E.M.Young, M.D., M.P.H.
1.0 INTRODUCTION
1.1. PROGRAM OBJECTIVES
a. To use the language and concepts of the Robbins Technique of Health Hazard Appraisal (HHA)
b. To develop skills in making HHA computations of Risk Score and Health Appraisal Age with Personal Data Sheets, Galler-Gesner Tables and Computation Charts.
c. To determine Interventions and calculate new Risk Score and Compliance Age.
d. To evaluate existing and future HHA methodologies and their appropriateness to individuals, groups and organizations.
e. To motivate further study in the future.
2. MATERIALS
a. Retained by Participants:
1) Text – Prospective Medicine (Hall and Zwemer) including Geller-Gesner Tables by age, sex and race, Risk Factors, protocols, Weight Analysis Tables and Health Appraisal Age Charts, etc.
2) Manual – including lecture notes, learning points, simplified glossary, program learning, articles, references, worksheets, etc. (Abbreviation given in Exhibit A)
3) Learning Recall Tape – cassette for future study summarizing each step in the learning process.
b. Not retained by Participants:
1) Work Pack – case studies, questions on the cases, case solutions, learning patterns, quizzes, exercises, etc.
1.0 INTRODUCTION
3. AGL METHOD
a. The AGL (Autonomous Group Learning Method) was developed in 1969 for international management training programs. It is a way of learning in groups without formal instruction. Participants use the materials and group resources to develop answers to all the cases and questions arising from the learning experience.
b. The work will be done in various modes: IND – individually, PAIRS – in pairs, SG – in small groups, CSG – in combined small groups, and MG – in main group.
c. Groups will be changed to enable participants to work with a variety of course members.
d. The Group Organizer assists the participants and groups to solve all the problems and thus achieve rapid individual learning in the limited time available.
e. Work quickly to cover all the materials in the time allowed. Use the SG’s to help you clarify difficult points and questions. Use your notebook to continually record key learning points. Use the Glossary for new technical word definitions.
f. After the program use the LRT (Learning recall Tape) for about one hour weekly for a month. This should improve the quality of your learning and convert short term into long-term learning.
4. ACKNOWLEDGEMENTS
a. Acknowledgement is made to the following persons who have assisted us in preparing this course on the Health Hazard Appraisal: Charles Althafer and Richard Lasco of CDC, Lynn Hawkins and Paul Melia of the Canadian Department of Health and Welfare, Robert Spasof, Ian McDowell and many others.
b. We are very grateful for the encouragement and support offered us by Dr. L. Robbins.
NOTE: Now complete the Program Registration Form, briefly read the Prospective Medicine Pamphlet, and then complete the Personal Data Sheet for yourself (the first step in HHA) (Exhibit B)
EXHIBIT A
ABBREVIATIONS
AGL Autonomous Group Learning
ASHD Arteriosclerotic Heart Disease
BF Black Female
BM Black Male
BP Blood Pressure
CRF Composite Risk Factor
HA Health Appraisal
HHA Health Hazard Appraisal
IND Individual
PDS Personal Data Sheet
RF Risk Factor
SG Small Group
WF White Female
WM White Male
EXHIBIT A
ABBREVIATIONS
AGL Autonomous Group Learning
ASHD Arteriosclerotic Heart Disease
BF Black Female
BM Black Male
BP Blood Pressure
CRF Composite Risk Factor
HA Health Appraisal
HHA Health Hazard Appraisal
IND Individual
PDS Personal Data Sheet
RF Risk Factor
SG Small Group
WF White Female
WM White Male
[pic]
[pic]
2.0 PART A - STUDY: THEORY AND PRACTICE
(Time 30 minutes)
1. METHOD OF STUDY
a. In MG (main group) - follow the lecture notes
b. In SG (small group) - read the lecture together as follows (A,B,C,D):
1. A reads the first section to the SG
2. B summarizes what A has said and reads the second section
3. C summarizes what B has said and reads the third section
4. The process is repeated by D, and the cycle is continued until the lecture is covered completely.
c. In SG - Summarize the key points of the lecture on one sheet of the flip chart.
d. Work quickly to complete all the work in the time allowed. Key points will be repeated many times during the program.
2. DEFINITION OF HHA
a. Objectives:
- Assess the risks that affect the quality of life of an individual
- Quantify impact on the individual of the risk of death
- Determine Interventions to reduce risk
- Change behavior towards Compliance
b. Quantification enables;
- Comparison between individuals
- Identification of significant risks
- Measurement of Intervention effectiveness
c. Four types of information are needed for HHA:
- Personal and family history : for certain conditions or diseases
- Physical assessment: of weight, height, blood pressure, cholesterol
- Health style behaviors : smoking, drinking exercising, dangerous practices (arrests, weapons, etc.)
- High risk groups : such as hypertensives, diabetics, cancer of the breast/cervix/colon, etc.
2.0 PART A - STUDY: THEORY AND PRACTICE
(Time 30 minutes)
2.3 HISTORICAL REVIEW
a. HHA was conceived by Robbins in 1968 at the Methodist Hospital of Indiana
b. Geller-Gesner Tables for average probability of death per 100,000 population by age, sex and race, were established in 1970. Deaths are expressed as expected deaths over the next ten years for a unit population of 100,000. Limited U.S. population only.
c. Proliferation of HHA instruments with the concept of “Prospective Medicine” including extensive studies by the Canadian Department of Health and welfare and the CDC (USA).
d. The Robbins method of HHA as modified by the CDC has been the most widely used and adopted to date (1981). This is the method described in this program.
2.4 PROBLEM AREAS
a. Data Base - needs continuous updating of risk assessment
- difficult to get at
- is based on mortality data
b. Risk Factors –
1. Originally related to cardio-vascular disease and cancer in the 1960’s.
2. Forecast morbidity but uses mortality data
3. Ranks the relative risks of the individual
4. Tends to sort individuals into risk groups rather than to predict specific outcomes
c. System –
1. Cannot stand alone as a health motivator
2. Is only the first step in a chain of events to change beliefs, motivate people, build skills in affecting lifestyle behaviors, changing social environments
3. Effectiveness not yet scientifically proven
NOTE: (a) Robbins model of HHA based upon limited U.S. population studies.
b) The Framingham Studies;
- were limited to a white middle class population
- showed the usefulness of long-term prospective (forward looking) community study
(c) The American Cancer Society studies:
- were less useful for HHA because it involved volunteers and was most useful for risk of lung cancer from smoking risk factors of ASHD association of health status and risk factor estimates
- called mainly on older population
(d) HHA needs broad prospective studies for total population
2.0 PART A - STUDY: THEORY AND PRACTICE
(Time 30 minutes)
5. HHA AS A HEALTH PROMOTER
a. Improves screening with risk assessment
b. Provides the basis for personal and quantitative prescriptions for health.
c. Makes decision-making for risk reduction more understandable in terms of health.
d. Shows the relationship between individual lifestyle and the risk of death.
e. Focuses responsibility for health onto the individual.
2.6 METHOD
a. HHA involves four stages:
1. Data base development (Text)
2. Personal Data Sheet (exhibit A)
3. Computation Chart (Exhibit B)
4. Intervention and Compliance planning
b. Data base development:
1. Health Appraisal Age Tables to compute the HA Age from the individual Risk Score (Text 42-5)
2. Geller_Gesner Tables (Text 87-293) show, for each age group, race and sex, and for each of the ten major Disease/Injuries the number of expected deaths/100,000 population corrected for prognostic Characteristics and Risk Factors.
3. Weight / Height Tables (Text 30-2) for computation of percentage excess weight
4. Protocols for assessing Risk Factors (Text 75-86) classifying lifestyle factors (exercise, smoking and drinking behaviors) in standard categories.
c. On Personal Data Sheet (Exhibit A) is recorded the baseline data from the individual. Critical data MUST be checked (e.g. possible uncontrolled Diabetes).
d. Computation Chart (Exhibit C):
1. Individual name, age, race, sex.
2. For relevant Disease/Injuries: Average Risk (death/100,000), Prognostic Characteristics, etc. (Geller-Gesner Tables)
3. Relevant Risk Factors (high or low) for each Prognostic Characteristic
4. Composite Risk Factor and Present Risk Score computed for each relevant Disease/Injury
5. Total (Present ) Risk Score and Health Appraisal Age
6. Intervention and Compliance (Achievable) Age computations.
2.0 PART A – STUDY: THEORY AND PRACTICE
(Time 30 minutes)
7. QUESTIONS
1. The main objective of Health Hazard Appraisal (HHA) is to:
a. reduce risk
b. compute risk
c. change behavior
d. use mathematics to compute health status
2. HHA risk analysis is based upon:
a. total population
b. limited U. S. population only
c. multiple international sources
d. astrology
3. A prognostic characteristic is a:
a. relevant disease/injury
b. risk indicator
c. evidence of bad character
d. a CRF
4. In the Framingham Study, the population sampled was:
a. white, middle-class men and women
b. a randomly selected population
c. predominantly blank blue-color workers
d. farmers from New Hampshire
5. The American Cancer Society study is relevant to HHA for all of the following except:
a. smoking as a risk for lung cancer
b. risk of cancer in a younger age group
c. establishing risk factors for arteriosclerotic heart disease (ASHD)
d. association of health status and risk factor estimates
HEALTH HAZARD APPRAISAL CHART
Quality control: Evaluate performance of a predetermined goal.
(Goal: “Get this patient safely through the next ten years.”)
|AVERAGE TO INDIVIDUAL RISK |
|POPULATION AVERAGE |INDIVIDUAL PROGNOSIS |
|10 YEAR DEATUS PER 100.000 |RISK APPRAISAL |
|Disease/Injury |Average |Prognostic | |Risk Factor| |Composite |Present |
| |Risk |Characteristics | | | |Risk Factor |Risk |
|From Manual |From |Listed in Manual | |From Manual |See Instruction |(2) x (5) |
| |Manual |Physician Select | | | | |
| | | | |X |+ | | |
|(1) |(2) |(3) | |(4) |(5) |(6) |
|Heart Attack |1355 |Blood Pressure |180 |1.0 |1.7 | | |
| | | |94 |1.0 |0.2 | | |
| | |Cholesterol |220 |0.7 | | | |
| | |Diabetes |Neg |1.0 | | | |
| | |Exercise |Walk 1ml |1.0 | | | |
| | |Family History |Neg |0.5 | | | |
| | |Smoking |1pkcig |1.0 |0.5 | | |
| | |Weight |15% + |0.9 | |2.7 |3659 |
|Cancer |317 |Smoking |1pk/day |1.0 |0.9 |1.9 |602 |
|Cirrhosis Liver |274 |Alcohol |18dr/wk |1.0 |1.0 |2.0 |548 |
|Accid Mot Veh. |255 |Alcohol |18dr/wk |1.0 |1.0 | | |
| | |Mileage |1500 yr |1.0 |0.5 | | |
| | |Seat Belts |80% |0.7 | |2.2 |561 |
|Suicide |250 |Depression |No |1.0 | | | |
| | |Family History |No |1.0 | |1.0 |250 |
|Stroke |142 |Blood Pressure |180/94 |1.0 |1.6 | | |
| | |Cholesterol |220 |1.0 | | | |
| | |Smoking |1 pk day |1.0 |0.2 |2.8 |398 |
|Homicide |112 |Arrest |No |1.0 | | | |
| | |Weapons |No |1.0 | |1.0 |112 |
|Cancer Col Rec |78 |Polyp |No |1.0 | | | |
| | |Rectal Bleeding |Yes |1.0 |2.0 | | |
| | |Ulcerative Col. |No |1.0 | | | |
| | |Stool exam bl. |No | | |3.0 |234 |
|Pneumonia |61 |Alcohol |18dr/wk |1.0 |2.0 | | |
| | |Hist. Bact. Pn. |No |1.0 | | | |
| | |Emphysema |No |1.0 | | | |
| | |Smoking |1pk/day |1.0 |0.3 |3.3 |201 |
|Alcoholism |54 |Alcohol |18dr/wk |1.0 | |1.0 |54 |
| | | | | | | | |
|Other Causes |1525 | | | | | |1525 |
|Total |4423 | | | | | |8144 |
Health Appraisal Age 47
* Reappraise on assumption that physician’s prescription is complied with.
Columns (7) through (10) same as columns (3) through (6) except where the physician’s prescription changed prognostic characteristics.
** Divide figures in column (11) by total of column (6)
Name John Doe Patient No. XXX Birthdate 12/15/35
Street Blank Apartments Race, Sex. Age WM 41
City Middletown State______Zip______ Date 12/17 19 76
|RISK REDUCTION FOR INDIVIDUAL |
|PROGNOSIS AFTER INTERVENTION |SURVIVAL |
|RISK REAPPRAISAL |ADVANTAGE |
|Prognostic |Risk Factor |Composite |New Risk |Amount |Per Cent |
|Characteristics | |Risk Factor | |Reduction |Reduction |
|After Physician’s |From Manual |See |(2) x (9) |(6) – (10) |.. |
|Prescription | |Instructions | | | |
| |x |+ | | | | |
|(7) |(8) |(9) |(10) |(11) |(12) |
|Reduce b.p. to 140.88 |1.0 |0.7 | | | | |
| |0.7 | | | | | |
| |1.0 | | | | | |
|Prescribed exercise |0.9 | | | | | |
| |0.5 | | | | | |
|Stop smoking |0.9 | | | | | |
|Reduce to ave |0.8 | |0.9 |1220 |2439 |30.0 |
|Stop smoking |1.0 |0.7 |1.7 |539 |63 |0.8 |
|Reduce to 3-6 d/wk |1.0 | |1.0 |274 |274 |3.4 |
|Reduce to 3-6 d/wk |1.0 | | | | | |
| |1.0 |0.5 | | | | |
|Wear seat belts 100% |0.6 | |1.1 |281 |280 |3.4 |
| |1.0 | | | | | |
| |1.0 | |1.0 |250 |0 |0.0 |
|Reduce b.p. to 140/88 |1.0 |0.5 | | | | |
| |1.0 | | | | | |
| |1.0 | | | | | |
|Stop smoking |1.0 | |1.5 |213 |185 |2.3 |
| |1.0 | | | | | |
| |1.0 | |1.0 |112 |0 |0.0 |
| |1.0 | | | | | |
| |1.0 | | | | | |
| |1.0 | | | | | |
|Stool exam (3x/yr) |0.3 | |0.3 |23 |211 |2.6 |
|Reduce to 306d/wk |1.0 | | | | | |
| |1.0 | | | | | |
| |1.0 | | | | | |
|Stop smoking |1.0 | |1.0 |61 |140 |1.7 |
| |1.0 | |1.0 |54 |0 |0.0 |
| | | | | | | |
| | | | | | | |
| | | | |1525 | | |
| | | | |4552 |3592 |44.1% |
Achievable Age 41 Appraiser_______________
(SIGNATURE)
Physician____________________________________________________________________
3.0 PART B – STUDY: TECHNIQUE
(Time 30 minutes)
1. SOURCE DATA
a. Data base –
- health Appraisal Age Tables (Text 42-5)
- Geller-Gesner Tables (Text 87-293)
- Weight/Height Tables (Text 30-2)
- Protocols (Text 75-86)
b. Personal Data Sheet
c. Computation Chart
2. METHOD
a. Personal Data Sheet gives age, sex, race, and life style data for the individual.
b. Computation Chart completed for the individual (Exhibit D) showing
1. Relevant disease/injuries and Average Risk of Death/100,000 population
2. Prognostic Characteristics for each Disease/Injury
3. Risk Factors for each Prognostic Characteristic
4. Composite Risk Factor and Risk Score for each Disease/Injury
5. Total Risk Score and Health Appraisal Age
6. Intervention and Compliance Age Computations
3.0 PART B – STUDY: TECHNIQUE
(Time 30 minutes)
3. RELEVANT DISEASE /INJURIES
a. For a 41 WM (41 year old white male) the Geller-Gesner Tables (Text 103-6) show the following ten major Disease/Injuries and Average Risk of death/100,000 population:
Rank Disease/Injury Deaths
1. Heart Attack (ASHD) 1355
2. Cancer of the Lung 317
3. Cirrhosis 274 274
4. Motor Vehical Accidents 256
5. Suicide 250
6. Vascular Lesions – CNS 142
7. Homicide 112
8. Cancer of the Large Intestine 78
9. Pneumonia 61
10. Alcoholism 54
Other (not specified) 1524
Total Average Risk Score 4423
(deaths/100,000). Population)
b. The average 41 WM has a Risk Score of 4423 (Age Specific Death Rate 4423/100,000). (Exhibit C)
4. PROGNOSTIC CHARACTERISTICS
a. For a 41WM the Geller-Gesner Tables (Text 103-6) List for ASHD (heart attack) the following eight (8) Prognostic Characteristics:
Blood pressure – systolic
Blood pressure – diastolic
Cholesterol
Diabetes
Exercise
Family History
Smoking
Weight
b. This data is also recorded on the Computation Chart (Exhibit C).
3.0 PART B – STUDY: TECHNIQUE
(Time 30 minutes)
5. RISK FACTORS
a. For each Prognostic Characteristic a Risk Factor is determined from the Personal Data Sheet, Geller-Gesner Tables (Text 103-6) and the protocols (Text 75-86).
b. Low Risk Factors (1.0 or less) are recorded on the Computation Chart column 4 (left) and are multiplied together.
c. High Risk Factors (Over 1.0) are recorded on the Computation Chart as follows:
Column 4 (left) – 1.0 (average risk)
Column 4 (right) – the excess over 1.0 (the excess above Average Risk)
Risk factors are combined together as follows:
Column 4 (left) – multiplied together
Column 4 (right) – added together
d. Exhibit D computes the Composite Risk Factor for Heart Attack (ASHD) as follows:
|Prognostic |Risk Factors |Personal |
|Characteristics |Colmn 4 |Data |
| |left |Right | |
| |(low) |(high) | |
|Blood pressure – systolic |1.0 |1.7 |BP 180/94 (RF 2.7) |
|Blood pressure – diastolic |1.0 |0.2 |(RF 1.2) |
|Cholesterol | .7 | |Cholesterol 220 |
|Diabetes |1.0 | |No diabetes |
|Exercise |1.0 | |Occasional activity |
|Family History | .5 | |Parents both alive after 70 |
|Smoking |1.0 |0.5 |20 cigarettes daily (RF 1.5) |
|Weight | .9 | |15% overweight |
|Product of column 4 (left) |0.3 |
|(1.0 x 1.0 x .7 x 1.0 x 1.0 x .5 x 1.0 x .9) | |
|Sum of column 4 (right) |2.4 |
|(1.7 plus .2 plus .5) | |
|Composite Risk Factor (See Exhibit D) |2.7 | |
e. For an average 41 WM, all RF’s would be 1.0 (column 4-left), and thus the CRF would be 1.0 and the Present Risk score would be Average Risk.
3.0 PART B – STUDY: TECHNIQUE
(Time 30 minutes)
3.6 RISK SCORE
a. A CRF (Composite Risk Factor)is calculated for each relevant Disease/Injury
b. For each Disease/Injure the Present Risk Score is computed as: Average Risk (deaths/100,000) times CRF
c. For ASHD the Present Risk Score is computed: Average Risk 1355 times CRF 2.7 equals Risk Score 3659.
d. The Total Present Risk Score is the sum of the Present Risk Scores of the ten (10) relevant Disease/Injuries plus a given Risk Score for “Other Causes” from the relevant Geller-Gesner Table (Text 103-6) for a 41WM
e. Exhibit D shows a Total Risk Score of 8144 for the 41 WM computed as follows:
Disease/Injury Risk Score
Heart Attack(ASHD) 3659
Vascular Lesions – CNS 398
Cancer of the Lung 602
Pneumonia 201
Cirrhosis of the liver 548
Suicide 250
Homicide 112
alcoholism 54
Accidents 561
Other 1525
TOTAL RISK SCORE 8144
3.7 HEALTH APPRAISAL AGE
a. The Health Appraisal Age Table (Text 42-5) convert the Risk Score by race, age, sex into Health Appraisal Age.
b. The last digit of the individual’s age together with the Risk Score identifies the Heath Appraisal Age pm the relevant table, e.g., 41 WM with Risk Score of Appraisal 8144 gives an HA of 47 Years.
3.0 PART B – STUDY: TECHNIQUE
(Time 30 minutes)
3.8 COMMENT ON THE METHOD
a. Low Risk Factors (1.0 or lower) are multiplied together because they should not cumulatively increase the Risk Score.
b. High Risk Factors (over 1.0) added together after deducting 1.0 (average risk) because they do cumulatively increase the risk of death.
c. The CRF reflects the individual’s disposition to acquire risk and die from teh relevant Disease/Injury. CRF is derived from the Prognostic Characteristics described in the personal Data Sheet.
d. The average risk for each Prognostic Characteristic is assumed to be 1.0.
e. CRF’s exceeding 1.0 indicate above average risk, and CRF’s below 1.0 indicate less than average risk.
3.9 INTERVENTION AND COMPLIANCE
a. CRF’s exceeding 1.0 indicate potential for Intervention.
b. The Significance of any Intervention for a particular Disease/Injury depends more on the Average Risk than the size of the CRF (i.d. In Exhibit D a change in the CRF of Heart Attack Cancer of the Colon (Average Risk only 78).
c. Interventions and the new Risk Score and compliance (Achievable) Age are computed on the right side of the Computation Chart using the same technique.
3.0 PART B – STUDY; TECHNIQUE
3.10 QUESTIONS
1. For and average 41 WM the least risk is:
a. stroke
b. alcoholism
c. cancer of colon/rectum
d. pneumonia
2. In the HHA model alcohol relates to all relevant disease/injuries risks except:
a. accidents
b. ASHD]
c. pneumonia
d. cirrhosis
3. In computing the CRF (Composite Risk Factor) RF’s above average 1.0 are :
a. added before deducting 1.0
b. added after deducting 1.0
c. multiplied twice
d. multiplied and then added
4. The Risk Score for each disease/injury is computed:
a. average risk times RF
b. median risk times CRF
c. average risk times CRF
d. to one decimal place
5. An average 40 WM has a risk score of:
a. same as 40 BM
b. more than a 40 BM
c. less than a 40 BF
d. under 8000
HEALTH HAZARD APPRAISAL CHART
Quality control: Evaluate performance of a predetermined goal.
(Goal: “Get this patient safely through the next ten years.”)
|AVERAGE TO INDIVIDUAL RISK |
| POPULATION AVERAGE INDIVIDUAL PROGNDSIS |
|10 YEAR DETAILS PER 100,000 RISK APPRAISAL |
|Disease/Injury |Average |Prognostic | |Risk Factor |Composite |Present Risk |
| |Risk |Characteristics | | |Factor | |
|From Manual |From Manual |Listed in Manual | |From manual |See Instructions |(2) x (5) |
| | |Physician Select | | | | |
| | | | |x |+ | |
|Heart |1355 |Blood Pressure |180 |1.0 |1.7 | | |
|Attack | | | | | | | |
| | | |94 |1.0 |0.2 | | |
| | |Cholesterol |220 |0.7 | | | |
| | |Diabetes |Neg |1.0 | | | |
| | |Exercise |Walk 1mt |1.0 | | | |
| | |Family History |Neg |0.5 | | | |
| | |Smoking |1PK/cig |1.0 |0.5 | | |
| | |Weight |15%+ |0.9 | |2.7 |3659 |
|Cancer Lungs |317 |Smoking |1pk/day |1.0 |0.9 |1.9 |602 |
|Cirrhosis Liver |274 |Alcohol |18dr/wk |1.0 |1. |2.0 |548 |
| | | | | |0 | | |
|Accid:Mot.Veh |255 |Alcohol |18dr/wk |1.0 |1.0 | | |
| | |Mileage |15000yr |1.0 |0.5 | | |
| | |Seat Belts |80% |0.7 | |2.2 |561 |
|Suicide |250 |Depression |No |1.0 | | | |
| | |Family History |No |1.0 | |1.0 |250 |
|Stroke |142 |Blood Pressure |180 94 |1.0 |1.6 | | |
| | |Cholesterol |220 |1.0 | | | |
| | |Diabetes |Neg |1.0 | | | |
| | |Smokint |1pk/day |1.0 |0.2 |2.8 |398 |
|Homicide |112 |Arrest |No |1.0 | | | |
| | |Weapons |No |1.0 | |1.0 |112 |
|Cancer col-rec |78 |Polyp |No |1.0 | | | |
| | |Rectal Bleeding |Yes |1.0 |2.0 | | |
| | |Ulcerative Col. |No |1.2 | | | |
| | |Stool exam bl |No | | | | |
|Pneumonia |61 |Alcohol |18dr/wk |1.0 |2.0 | | |
| | |Hist.Bact.Pn |No |1.0 | | | |
| | |Emphysema |No |1.0 | | | |
| | |Smoking |1pk/day |1.0 |0.3 |3.3 |201 |
|Alcoholism |54 |Alcohol |18dr/wk |1.0 | |1.0 |54 |
| | | | | | | | |
|Others Causes |1525 | | | | | |1525 |
|Total |4423 | | | | | |8144 |
Health Appraisal Age 47
* Reappraise on assumption that physician’s prescription is complied with.
Columns (7) through (10) same as columns (3) through (6) except where the physician’s prescription changed prognostic characteristics.
** Divide figures in column (11) by total of column (6).
|RISK REDUCTION FOR INDIVIDUAL |
|PROGNOSIS AFTER INTERVENTION |SURVIVAL |
|RISK REAPPRAISAL |ADVANTAGE |
|Prognostic Characteristics |Risk Factor |Composite |New Risk |Amount Reduction |Percent Reduction |
| | |Risk Factor | | | |
|After Physician’s |From Manual |See Instructions |(2)x(9) |(6)-(10) |** |
| |x + | | | | |
|(7) |(8) |(9) |(10) |(11) |(12) |
|Reduceb.p.to140 88 |1.0 |0.7 | | | | |
| |0.7 | | | | | |
| |1.0 | | | | | |
|Prescribed exercise |0.9 | | | | | |
| |0.5 | | | | | |
|Stop smoking |0.9 | | | | | |
|Reduce to av |0.8 | |0.9 |1220 |2439 |30.0 |
|Stop Smoking |1.0 |0.7 |1.7 |539 |63 |0.8 |
|Reduce to 3-6 d/wk |1.0 | |1.0 |274 |274 |3.4 |
|Reduce to 3-6d/wk |1.0 | | | | | |
| |1.0 |0.5 | | | | |
|Wear Seat belts 100% |0.6 | |1.1 |281 |280 |3.4 |
| |1.0 | | | | | |
| |1.0 | |1.0 |250 |0 |0.0 |
|Reduceb.p.to 140/88 |1.0 |0.5 | | | | |
| |1.0 | | | | | |
| |1.0 | | | | | |
|Stop smoking |1.0 | |1.5 |213 |185 |2.3 |
| |1.0 | | | | | |
| |1.0 | |1.0 |112 |0 |0.0 |
| |1.0 | | | | | |
| |1.0 | | | | | |
| |1.0 | | | | | |
|Stool exam(3x/yr) |0.3 | |0.3 |23 |211 |2.6 |
|Reduce to 3-6d/wk |1.0 | | | | | |
| |1.0 | | | | | |
| |1.0 | | | | | |
|Stop smoking |1.0 | |1.0 |61 |140 |1.7 |
| |1.0 | |1.0 |54 |0 |0.0 |
| | | | | | | |
| | | | | | | |
| | | | |1525 | | |
| | | | |4552 |3592 |44.1% |
Achievable Age 41 Appraiser_______________
(SIGNATURE)
Physician____________________________________________________________________
4.0 PART C – STUDY: RISK ESTIMATION AND HRA EFFECTIVENESS
(Time 30 minutes)
4.1 CHOICE OF PROGNOSTIC CHARACTERISTICS
a. A Prognostic Characteristics is a risk indicator
b. The choice of risk indicators is limited by availability of well-defined studies (see note on Framingham and American Cancer Society studies in lecture 3.3)
c. Criteria for selection of indictors include:
1. Strength of association between risk and disease.
2. Duration/dose response between risk and disease outcome
3. Biological support and experimental evidence of association between risk and Disease/Injury.
4. Evidence that risk removal reduces the probability of Disease/Injury outcome
d. The more information available, the more predictable (Bayes rule).
4.2 QUANTIFYING THE RISK
a. The HHA model in this program used the Robbins “Actuarial Model” which avoids inflating composite risks.
b. Risk factors are treated differently:
• high risk (greater than 1.0) – promoters of death
• low risk – protectors from death
c. The model works well with a limited number of Risk Factors
d. The model tends to overestimate risk (with highly correlated prognostic characteristics) and to underestimate risk with prognostic characteristics that are mutually independent and have large values.
4.3 METHODOLOGICAL ISSUES
a. Should HHA be appropriate for individuals with early disease onset? Can a successfully treated cancer patient be considered “healthy” compared with a successfully treated hypertensive?
b. How can HHA be adapted to individuals with special occupational or ethnic or environmental risks?
c. Since HHA is for “healthy” people, should the underlying data base be for average mortality? What about the high mortality for chronically ill individuals?
The overall risk must be elevated by the chronically sick:
Technical example: If 90%of the population have a mortality or M and the remainder 2M, then the total mortality:
Mt = .9M + .1 (2M) = 1.10 M (overestimate of 10%)
4.0 PART C - STUDY: RISK ESTIMATION AND HRA EFFECTIVENESS
(Time 30 minutes)
4 RISK TAKING AND THE HEALTH PARTICIPANT
a. The “healthy” worker will tend to take a more risky occupation thus the probability of injury is higher in the younger population.
b. Older workers tend to have supervisory and less risky positions
c. Thus, the age distribution of the population influences the average probability of death.
4 COMPOSITE RISK FACTOR COMPUTATION
a. The Actuarial (“Debit/Credit”) method is arbitrary and makes no provision for total disease interaction (High “debits” are added but low “credits” are effected by multiplication).
b. Is multiplication of low risk factors as if they were “Relative Risks” really justified (Spas off and McDowell,1976)
c. Competing risks are ignored thus overestimating the risk.
d. Corrections are needed for all of the above only if they are high risk factors (Chang, 1970).
e. There is a need to do sensitivity analysis to determine whether any specific assumption significantly affects the resulting Risk Score.
4.6 PROBLEM OF THE YOUNG MALE RISK COMPUTATIONS
a. The assumption that increasing age increases risk of death is not true for young males.
b. The average risk from accidents is higher at age twenty and forty years than it is for thirty years. Thus, there are two ages with equivalent probabilities. This can be corrected by:
1. Regression, or
2. Calculations which ignore traumatic causes of death (this leaves a linear relationship between age and death but lowers young males to unrealistic risk levels).
c. Thus, in computations of HHA for young males:
1. Users of computerized HHA should be wary of what is measured
2. Users should know what models and assumptions are being used and what corrections have been made.
3. Users should be able to adjust programs to compensate for unrealistic results.
4.0 PART C - STUDY: RISK ESTIMATION AND HRA EFFECTIVENESS
(Time 30 minutes)
4.7 HHA EFFECTIVENESS
a. Change of lifestyle is difficult due to: beliefs, motivation, social, cultural and economic environments.
b. Beliefs may be based on objective or subjective data but “belief change” is complex and on must in any case be “relatively pleasant” for acceptance (Roberts 1975).
c. Motivation related to complex factors including:
1. Intention to achieve desired goals
2. Intention to move away from disliked situations
3. Pressures against harmful habits
4. Gratification or release of fear (Jarvis 1967, Kas1 1975, Leventhal 1971, 1973).
d. The social, cultural and economic environment affects:
1. Values of life, health, sickness and death
2. Peer pressures
3. Social engineering
4. prestige of healthy life styles in the social hierarchy.
e. Planning for Intervention must therefore involve a complex mix of motivational factors.
4.8 PROSPECTIVE MEDICINE
a. Prospective Medicine involves four stages:
1. HHA to determine ten year survival chances
2. Planned reduction of risk and plotting a survival course
3. Health management program with family members and social organizations
4. Choice of the right time to act on Interventions.
b. Thus, HHA is a vital part of a total scheme of prospective Medicine which is a new approach to patient care that begins before illness strikes.
c. The key to prospective Medicine is its Epidemiological Approach.
4.0 PART C - STUDY: RISK ESTIMATION AND HRA EFFECTIVENESS
(Time 30 minutes)
4.9 QUESTIONS
1. For an average 45-year-old white male the major HHA risk factor is:
a. Jogging downtown at night ]
b. Stroke
c. cardiac disease]
d. diabetes and hypertension
2. If the CRF if 2.00 and the average probability of death from ischemic heart disease is 1405/100,000, the risk score is about:
a. 700
b. 1400
c. 2800
d. 4200
3. In the Robbins HHA model the risk factor for cancer of the lung for a 50 year old woman smoker is the same as for a 50 year old man.
a. true
b. not true because of ERA
c. true for BF’s
d. not true
4. How is the Risk Score for each relevant disease/injury calculated?
a. CRF’s are added together
b. CRF’s are multiplied together
c. CRF is each multiplied by the average projected mortality
d. none of the above
5. In HHA the (“credit/debit”) approach for risk assessment:
a. accounts for protective risk factors
b. all risk factors are either added or subtracted to calculate the composite risk
c. all risk factors are multiplied together
d. high risk factors have values greater than one, and are added together after one is subtracted from each
5.0 PART D - STUDY: NEW METHODOLIGIES
(Time 30 minutes)
5.1 TRENDS FOR THE EIGHTIES:
a) Questions on the future of HHA
– How accurate should it be?
– Is too much should it being placed on prediction of results?
– How closely is prospective Medicine being turned into predictive medicine?
b) HHA Potential:
– Adopted country-wide in Canada
– Sponsored by CDC in the U.S.A
– Microcomputers will facilitate updating data bases and computing results.
c) HHA methodology:
– Specificity of data bases will be improved]
– Will be adjusted to fit special cases
– New models will be added when the debit-credit system of analysis breaks down (ethnic, cured cancer patient, controlled hypertensive).
– New methodology might be developed by the 1990;s.
5.0 PART D – STUDY: NEW METHODOLOGIES
(Time 30 minutes)
5.2 ALTERNATIVE MODELS FOR HHA ANALYSIS
a) Most popular methods:
- Debit-credit (Actuarial Method which does not use logarthmic rule factors)
- Log-linear
- Logistic
- Branching method
b) Log-linear model
- Permits direct estimation of conditional probabilities of outcome events.
- Allows for interaction.
- Permits the analysis to incorporate new risk indicators.
- Rejects old low associated ones.
- Does not deal with continuous variables.
Technical note:
Condition probabilities given by: p(D/jik), where i, j, k, are three risk factors, D is death from disease, S is survival from disease; then p(D/ijk) = p(Dijk)/p(Dijk)+p(Sijk)
The log linear equation is given by:
Ln p(Dijk) = Uo+Ui+Uj+Uk
+ Uij+........
+ Uijk..
c) The logistic model:
- Accommodates continuous variables.
- More powerful than present methods.
- Will take time to incorporate into common usage.
- Cannot be hand tabulated.
- Requires computer facilities for operation.
Technical note: Logistic model can be written as follows:
P (D/ijk) = 1/(1+e-bx) , where x is a dummy variable vector for the intercept and values for risk indicators at levels i,j,k; b is a vector consisting of intercept and regression weight.
d) The “Branching” model:
- Based on the epidemiological concepts of screening.
- Both sensitivity and specificity measures are involved.
- IR (or intermediate risk) will be determined by the number of screenings performed (Exhibit F)
- Probabilities worked out are based on Bayes’ Rule
- Tests are sequenced form the simple to complex, from the cheap to expensive.
- Most advanced methodology.
5.0 PART D – STUDY: NEW METHODOLOGIES
(Time 30 minutes)
2. ALTERNATIVE MODELS FOR HHA ANALYSIS (cont’d.)
- Model could rely on physical measurement (lab, anthropomorphic, radiology, etc.)
- Risk estimates would be individually assessed.
Technical note: Bayes Rule can be summarized by saying the more information is available, the more predictable the probability measure.
3. WHAT ARE THE QUALITATIVE ISSUES
a) Ethical Issues:
- What information should be presented to the participant?
- Should the report be in two parts, one for health professional, other to the client?
- Should damaging information be released?
- What happens if the risk is racially biased?
b) Formatting:
- Should non-reducible risks be included in the analysis?
- How should the client’s report be written?
- How long is the permissible period for writing?
- Does an interactive model justify the expense?
c) Role of HHA:
- An educational tool only.
- Should it be more predictive?
- Who is the best person to do the HHA?
- Should HHA be incorporated with hypertensive screening?
d) Motivation:
- Do certain results motivate people to change?
- When is “the teachable moment”?
- What should the presentation be to create optimum motivation?
e) Methodology:
- Should the orientation change towards risk assessment?
- How can the instrument be changed for young and old?
- What sort of measures should be used to measure “wellness” in the elderly? (Katz Scale is not enough in HHA)
- What alternative is there for achievable age in the young?
- HHA should be scientific and accurate.
- HHA is not a cult or a pseudoscience; data used must be epidemiologically based.
- Scientific rigor must be maintained.
- A dichotomy must be established between research and application.
- HHA should routinely be used in Health Promotion activities.
5.0 PART D – STUDY: NEW METHODOLOGIES
(Time 30 minutes)
[pic]
5.0 PART D – STUDY: NEW METHODOLOGIES
(Time 30 minutes)
4. QUESTIONS
1. A deficiency of the Geller-Gesner Tables is the:
a. actual method
b. absence of special additional risk factors for the same previously diagnosed illness
c. absence of probabilities for blacks
d. too many tables
2. Which of the following HHA model is used in this program?
a. Log-linear model
b. Branching model
c. Robbins model
d. Log stic model
3. The logarithm of the risk factor is used in the Robbin’s model of HHA is:
a. to make the extrapolation linear
b. to take into account variability of estimate
c. to make it easier for computerization
d. No. Robbins does not use logs
4. HHA computation takes how many minutes to complete:
a. 8
b. 20
c. 40
d. 60
5. If a 42-year-old BM smokes 15 cigaretts per day (RF=1.5), is 50 lbs. overweight (RF=1.5) and has no family history of ischemic heart disease (RF=0.9), what is his composite risk factor?
a. 3.9
b. 1.9
c. 2.2
d. 3.0
7.0 SIMPLIFIED GLOSSARY
Age – present Chronological age - - the age calculated from the birth date.
Age – Achievable The age that an individual can achieve is the lifestyle changes are adopted and risk score reduced. Computed from health Appraisal Age Tables (Text 42.5).
Age - Health Appraisal The appraised age as reflected by the risks reported and the lifestyle recorded. The sum of all the risks and their effects on specific causes of death in an age-risk group which shares the individual’s appraised probability of death. Calculated on the Computation chart.
Appraised probability of Dying This is the Composite Risk Factor (see below)multiplied by the average risk of death.
Average Probability of Death This is the average mortality rate based on 12 causes of death.
Bayes Rule P (D/S) = P(S/D) P(D) which the probabilities
P(S)
of an event occurring is dependent on the amount of information that is available. The more information available, the more predictable the probability measure.
7.0 SIMPLIFIED GLOSSARY
Blood Pressure The force of blood on the sides of the arterial vessel as it passes through the circulation. This is subdivided into Systole – the maximum pressure attained when the heart is contracting and Diastole- the minimum pressure when the heart is relaxing. Prognostic characteristic affecting several disease/injuries. Geller-Gesner Tables require two R.T. ‘s for serious hypertensive individuals.
Cause A Shorthand notation for cause of death, cause of cause of illness or birth. It refers to outcome events rather than precursors.
Cholesterol Levels The amount of cholesterol, a fatty deposit or sterol found in all animal tissues, measured in the blood. Prognostic characteristic for heart disease, stroke and diseases of the arteries.
Cohort A population that is selected because of certain characteristics and followed over time.
Composite Risk Factor (CRF) The value for risks accumulated by calculating individual risks ( precursors of death ) and combining them together using a mathematical formula to get the total value. Each precursor is assigned a numerical weight known as a risk factor. Low R.F. ‘s are multiplied and high R.F.’ s are added ( after deducting 1.0). The sum of low and high R.F. ‘s is the CRF.
Conditional Probability Applies to the situation where the change of a particular event’s occurrence depends on the outcome of some other event.
Crisis Medicine Medicine that responds to problelms at hand and tries to solve them immediately.
Death – Average Probability This is the chance of death of whole population based on the number of deaths occuued irrespective of other variables.
Environmental Risk Those precursors of death (or risk factor) that are found in the environment.
Formula
- Odds Ratio is the ratio that describes the odds in favor of having the disease with the risk present over odds of having the disease with the factor absent.
- Odds Ratio Standard Error gauges the precision of the estimated odds ratio.
Frequency Table The number of people with a certain attribute with a population – percentage distribution.
Geller-Gesner Tables Thsi is an example of a frequency distribution within a population of a hundred thousand. Tables by age, sex and race do indicae: ten simplified disease/injuries with average risk, prognostic characteristics, risk factors and risk score.
Health Hazard Appraisal See HHA
HHA – Age This is equivalent to the appraised age (see above).
HHA – Definition Health Hazard Appraisal is an instrument to establish the probability of an individual dying in the next ten years. Part of Prospective Medicine.Enables qualification of potential interventions to achieve improved health states.
HHA – History Intorduced by L.Robbins in 1960’s as a health screening device for family physicians.
HHA – Intervention The prescription for change in lifestyle for achieving an optimum probability of death is the intervention.
HHA – Manual/computerized HHA can be done by hand (manually) or the analysis can be made via a suitable programmed computer system.
HHA – Tables Geller-Gesner Tables are actuarial tables that give the survival probabilities. Health Appraisal Age Tables connect Risk Scores into HA Ages by sex and race.
Health Risk – American Cancer The establishment of health risks using
Society Sample the American Cancer Society population sample as the population at risk; mainly an older middle class sample, not representative of the U.S. population.
Health Risk – Framingham Sample Framingham population sample as the first major large scale prospective community study. Needed to study cardiovascular risk; middle class rural population and representative of the U.S. population.
Independence The occurrence of two events in which the occurrence of one does not affect the occurrence or non-occurrence of the other.
Intervention See HHA – Intervention.
Level A risk indicator may be continuous or assume two (absent/present) or more levels. (e.g., number of drinks drunk/day may classify an individual at different levels).
Multiplier The quantitative weitht attached to a risk indicator to describe the amount by which risk increases or decreases.
Morbidity A measure of the amount of illness.
Mortality A measure of death rates.
Logarithmic Coefficients If a number “a” is expressed as a power of another number “b”, i.s. a = bn, where the “n” is the logarithm to the base “b”.
Methodology – Current The methodology as practiced at present.
New Risk See Risk
Odds Ratio See Formula “Odds Ratio”.
“Other Causes of Death” Others deaths not due to the ten major disease/ injuries in the Geller-Gesner Tables.
Overall Appraised Probability of Death The sum of appraised probabilities of death.
Probable Risk Is the average mortality rate multiplied by the composite risk factors.
Probability – Single One single probability of survival.
Probability – Composite The sum of many probabilities.
Probability - Conditional See Conditional Probability.
Predictive - Medicine The basis of signs and symptoms predicts the survival of the individual.
Prospective Categories Those categories that have a probabilistic influence on survival.
Prognostic Characteristics Those characteristics that classify individuals into prognostic categories. (e.g. blood pressure, cholesterol level, exercise, smoking, alcohol, family history, etc.).
Prognostic Risk Factors Risk factors that affect change of survival.
Rate The frequency of a disease or characteristic expressed per unit of size of the population or group to which it is observed.
Relative Risk The ratio of the rate of the disease (usually incidence or mortality) among those exposed to the rate among those not exposed.
Risk The chance of dying within 10 years is dependent on the magnitude of the risk.
Risk Components The different parts that make up a total risk:
By Credit/Debit method
All risks that are beneficial are multiplied together and added to the sum of the amounts of the other risks that are greater than one.
Risk Factor (RF) See Galler-Gasner Tables in Text Probability of a Prognostic Characteristic. How risk factors (under 1.0) are protective, average risk factor (1.0) or high risk factor (over 1.0) which are hazardous. See Composite Risk Factor.
Risk Factor Profile A set of risk indicator values or levels, describing and individual.
Risk Indicator Prognostic characteristic, a variable which modified the probability of occurrence of disease or death from that of the general population.
Risk Intervention Activity that changes the value of risk and should reduce the Risk Score. Health Appraisal Age.
Risk Variable – Single/Composite Single risk variable is one that has one component. Composite risk variable has more than one component.
Sensitivity The extent to which patients who truly manifest a characteristic are so classified.
Specitivity The extent to which patients who do not manifest a characteristic are correctly classified.
Standard Error The limits of the accuracy of a prediction.
Standard Error of Odds Ration (See Odds Ratio). The limits of the accuracy of the odds ratio.
Survival Advantage That amount that is less than would be expected if the prescribed lifestyle change had not been undertaken.
8.0 REGISTRATION AND BACKGROUND DATA
COURSE DATE & LOCATION :
PARTICIPANT’S NAME :
TITLE :
ADDRESS :
PREVIOUS PHC EXPERIENCE :
QUIZ RESULTS :
DAY I DAY II DAY II
50 19 50
PERSONAL OBJECTIVES IN TAKING THE COURSE :
NOTE: COMPLETE ONE SHEET OF THE COURSE DIARY FOR EACH DAY INDICATING :
1) Key Points learned
2) Reactions t AGL
3) Questions which are not satisfactorily answered
4) Results of any quizzes given during the day.
8.0 FEED BACK SUMMARY
1. NAME :
TITLE :
ADDRESS :
2. PREVIOUS PHC BACKGROUND :
3. QUIZ SCORES :
DAY I DAY II DAY II
Out of 50 out of 19 out of 50
4. DID THE PROGRAM COMPLETELY SATISFY YOUR PERSONAL OBJECTIVES?
5. WHAT SUGGESTIONS COULD YOU MAKE FOR IMPROVING THE PROGRAM?
6. WHAT OTHER AGL PROGRAMS COULD BE DEVISED WHICH WOULD BE USEFUL?
7. WHAT IS YOUR OVERALL EVALUATION OF THE COURSE IN TERMS OF:
Excellent Good Fair Poor Terrible
1 2 3 4 5
Content
Presentation
Administration
Usefulness
Note : Mark the appropriate item with an X
9.0 QUIZ ANSWER SHEET
1. (a) (b) (c) (d) 26. (a) (b) (c) (d)
2. (a) (b) (c) (d) 27. (a) (b) (c) (d)
3. (a) (b) (c) (d) 28. (a) (b) (c) (d)
4. (a) (b) (c) (d) 29. (a) (b) (c) (d)
5. (a) (b) (c) (d) 30. (a) (b) (c) (d)
6. (a) (b) (c) (d) 31. (a) (b) (c) (d)
7. (a) (b) (c) (d) 32. (a) (b) (c) (d)
8. (a) (b) (c) (d) 33. (a) (b) (c) (d)
9. (a) (b) (c) (d) 34. (a) (b) (c) (d)
10. (a) (b) (c) (d) 35. (a) (b) (c) (d)
11. (a) (b) (c) (d) 36. (a) (b) (c) (d)
12. (a) (b) (c) (d) 37. (a) (b) (c) (d)
13. (a) (b) (c) (d) 38. (a) (b) (c) (d)
14. (a) (b) (c) (d) 39. (a) (b) (c) (d)
15. (a) (b) (c) (d) 40. (a) (b) (c) (d)
16. (a) (b) (c) (d) 41. (a) (b) (c) (d)
17. (a) (b) (c) (d) 42. (a) (b) (c) (d)
18. (a) (b) (c) (d) 43. (a) (b) (c) (d)
19. (a) (b) (c) (d) 44. (a) (b) (c) (d)
20. (a) (b) (c) (d) 45. (a) (b) (c) (d)
21. (a) (b) (c) (d) 46. (a) (b) (c) (d)
22. (a) (b) (c) (d) 47. (a) (b) (c) (d)
23. (a) (b) (c) (d) 48. (a) (b) (c) (d)
24. (a) (b) (c) (d) 49. (a) (b) (c) (d)
25. (a) (b) (c) (d) 50. (a) (b) (c) (d)
10.0 SUMMARY LECTURE
INDEX
Item
1. Introduction
2. What is HRA
3. HRA Computation
4. The Robbins Model
5. Criticism of the Robbins Model
6. HRA in Business
7. Industrial Applications – Alternatives
8. Industrial Applications – Planning
9. Industrial Applications – Criticism
10. Summary
11. Bibliography
12. HRA Computerized Report
1. INRODUCTION
Health Risk Appraisal was used by John Manion at Temple University in 1959 and was developed by Robbins and Hall at the Methodist Hospital in Indiana in the 1960’s. It was associated with Prospective Medicine in the 1970’s with extensive studies summarized under U.S. Government Contract No. 23-78-3008 (Reference No. 1 in Bibliography).
This brief report outlines the basic concepts of HRA and its potential for industrial applications.
2. WHAT IS HAR?
HRA is a technique which uses epidemologiacal data to quantify an individual’s risk of death and health age (compared to calendar age), in order to motivate lifestyle changes to reduce the risks.
HRA may be used as: a screening technique, an educational tool, a personal behavior change agent, a reinforcer of the impact of short and long term behavioral change, etc.
The original HRA model was called Health Hazard Appraisal (not to be confused with the NIOSH meaning of these words). Robbins and Hall, at the Methodist Hospital in Indiana, used the data from the Framingham study and the American Cancer Association study to set up the first Geller-Gesner tables for health risk.
HRA has been used to screen large numbers of the general population since 1974. In the USA over 400 organizations screened more than 1,000 person each in 1980.
3. HRA COMPUTATION
In 1982 there are about 25 HRA models…………., and so the health risk computations will depend upon the model chosen. Models vary from simple one-page questionnaires to long and complex instruments processed by computers. They may be general models for healthy people 16-60 years of age or specialized models dealing with the special risks of cardiovascular disease, stress, fitness, obesity smoking, alcohol, etc. Except for the Robbins model which has been adapted by the Government in Canada and by the CDC in the USA, most of the models have not been substantially tested.
Computation of HRA may be “self-marked”, marked manually by professional staff or processed by computer in batch or “in line” systems. The cost of HRA varies from $2 p.c. (Canadian Government) to $600 p.c. (Control Data) depending upon the counseling and preventive medicine follow-up provided.
4. THE ROBBINS MODEL
The Robbins Model, as adapted by the CDC, can be used manually or by computer. It involves the following steps:
a. Personal Data Sheet:- giving baseline data on medical history, blood pressure, lifestyle, etc.
b. Geller – Gesner Tables – for each age group, by race and sex, giving the average probability of death within 10 years for the appropriate ten leading Disease/Injuries. The Tables also give the relevant prognostic characteristics for each Disease Injury, and rules for computing compsite Risk Factors.
c. Computation Chart
1) Using the individual Personal Data sheet and the Geller-Gesner Tables, the Computation Chart is used to calculate the individual’s Health Age.
2) Risk Factors for each prognostic characteristic are combined into a Composite Rick factor (CRF) for each of the ten leading Disease/Injuries.
3) The CRF is multiplied by the average risk of death/100,000 population to give a Risk Score for that Disease/Injury.
4) The total Risk Score allows computation of the individual’s Health Age from the Health Tables.
5) Interventions are the selected according to significant Disease/Injuries and Composite Risk Factors (exceeding 1.0 average risk) so as to compute a revised Achievable Risk Score and Achievable Health Age.
d. Example for a 41 year old white male follows:
Average risk score for a 41 WM 4423 (Exhibit C)
Individual risk score 8144 (Exhibit D)
Individual Health Age 47 yrs (Exhibit E)
Proposed intervention – BP, smoking, alcohol (Exhibit D)
Achievable life style, risk score (Exhibit D)
Achievable health age 41 (Exhibit E)
5. CEITICISM OF THE ROBBINS MODEL
All HRA models have been criticized and the following are typical objections to the Robbins Model:
a. Input – the Model is based on the old studies at Framingham and the American Cancer Society which are not representative of the general U.S. population. It deals with mortality rather than morbidity. The data base is being updated by CDC, but the results will not be available until 1982.
There is no provision for the special risks or for increased risk due to occupational exposure or previous history of disease. The model is essential appropriate to healthy people and not for those who suffer from chronic disease or are at the extremes of age.
There is no opportunity to introduce laboratory or other medical/health information and no “branching” for special study for persons of high risk.
The method of combining of low and high risk factors is simplistic and does not clearly adjust for the additive effect of certain types of risks without more sophisticated computer based models, but the latter have not yet been subjected to the same degree of research study as the Robbins model.
b. Process – the Model is sometimes accepted by only 50% of the individuals tested, for a variety of reasons including: lack of interest, fear, confidentiality, low socio-economic status, etc. Thus it may be necessary to adapt the technique to encourage special groups to participate.
c. Output – HRA provides the individual with knowledge which is not necessarily an effective motivation to change to a healthier life style. It is extremely difficult to devise the “mix” of motivations to ensure compliance to interventions.
d. Outcome – Compliance with interventions is presumed to reduce risk, improve health and prolong life, but no studies are available to substantiate this claim. In any case such outcome cannot be easily associated solely with the HRA since health depends upon so many different factors.
Overall, despite criticism of the Robbins Model, if it succeeds in motivating individuals towards life styles that reduce risk, then it could be achieving its objectives. Thus the success of the HRA may not depend purely on the development of increasingly scientifically valid models (the objective of the current research), but rather on the motivational problems.
6. HRA IN BUSINESS
Reports of applications in three companies are given
These are not objective scientific studies but they do indicate some degree of corporate satisfaction with the quantitative and non-quantitative results of HRA.
7. INDUSTRIAL APPLICATIONS – ALTERNATIVES
Alternative uses of HRA include the following:
a. Screening for health risks – HRA is quick, low cost ($ 10 or less), and non-invasive screening without the need for physical examinations or laboratory tests. It provides the individual with useful data on his health status. The data can be presented with or without counseling and “follow-up”. Health facilities do not have to be provided by the company since extensive public facilities (programs for : smoking reduction, diet control, alcohol, exercise, etc.) are usefully available.
b. Management data – HRA can provide a health profile for the work force by department; this data may justify changes in the work conditions, fringe benefits, health plans, exercise at work programs, and the general personnel policies. Such summary data can be provided without loss of the personal health confidentiality.
c. Preventive medicine – HRA data may be a useful entry point and motivator for preventive medicine for the individual or the organization. Repeated annual HRA’s may be a cost effective substitute for annual physical examinations with a more effective health education effect.
d. Cost reduction – data on health and health risks may facilitate marked reduction in the costs of health care by reason of improved health status. There may also be some improvement in absenteeism and productivity, but these are complex matters not related purely to the HRA activity. No objective data or justification is presently available.
e. Personal relations – the offer of HRA as a fringe benefit may improve the company image with Trade Unions as regards continuous concern for the employee health status.
8. INDUSTRIAL APPLICATIONS – PLANNING
Application of HRA in an industrial organization may required some months of negotiation and planning to include the following steps:
a. Objectives: clear definition of what is to be achieved by HRA including: individuals to be assessed, counseling, preventive medicine activity, management information, cost saving, etc. for defined groups of employees.
b. Method: selection of the HRA model which involves decision as to the level of sophistication (questionnaire, laboratory tests, physical examinations, etc.); decisions as to use of consultants or training of company staff for HRA administration, counseling, etc. It may be better to start with a relatively simple system and limited follow-up, until the relevant cost becomes apparent, ie., the cost of employee time as well as the HRA “out of pocket” expenses.
c. Coordination: discussion with employee associations and development of appropriate information sheets and meeting arrangements to explain the program.
d. HRA staff: recruitment of HRA supervisor and counsellors (possibly an RN or Social Worker or personnel staff), training and development of routines and protocols.
e. Testing: Choice of a small department or executive group to test the procedures and HRA processing (must be rapid feedback) before working with large numbers.
f. General application: using established routines and protocols on a scheduled program to an increasing number of employees including: introductory talks to small groups, completion and audit of personal data sheets, computation chart calculations, feedback counseling, follow-up and preventive medicine activities.
g. Control: monthly and quarterly reviews of progress in relation to objectives and appropriate change in relation to cost/benefits.
9. INDUSTRIAL APPLICATION – CRITICISM
The general criticisms of the Robbins Model of HRA (section 5) are appropriate except to the extent that more sophisticated models are used. The general lack of occupational risk data and additive risk due to occupation may be questioned, although even a limited HRA model may still be motivational in changing life styles, especially for executives and office workers. It may be less effective with lower socio-economic class, but good data is not yet available.
The direct cost of HRA may vary from $2 to $600 per capita, depending upon the level of counseling and preventive medicine benefits made available. To this must be added the opportunity cost of employee time during HRA activities. Furthermore, if HRA produces savings in reduced executive absenteeism and increased executive productive time, the opportunity cost of such time may be a better justification for HRA than preventive medicine activities. Thus HRA application may be more cost/effective to executives than to lowered paid staff.
HRA may be interpreted by employees as an attempt by the company to “off-load responsibility” for work-related disease/injury by putting the responsibility of employee health on to the individual. Again the choice of HRA method and extent to which it changes the traditional occupational medicine department routines may result in some conflict.
However, overall with appropriate management and coordination with employee organizations, the above criticisms can be handled and HRA can form part of preventive medicine routine for most industrial organizations. This can be done either by selecting “appropriate” employee groups or by selecting “appropriate” services. There is a wide flexibility in using HRA.
10. SUMMARY
From this brief review of the basis of HRA and its potential for industrial application, the following key points are emphasized:
1. HRA can be a low-cost rapid screening technique to quantify individual health risk and provide and entry for preventive medicine activities.
2. HRA can be useful to management by providing data on the overall health risk status of company employees, which is relevant for setting personnel policies on working conditions, health services, improvement of morale and productivity, etc.
3. The four stages of HRA (input, process, output and outcome) although already applied extensively in Canada and the USA are not yet scientifically validated.
4. CDC is actively engaged in providing an improved general data base. However, the existing and proposed data bases do not yet include occupational risk or increased risk from occupational exposure, although a whole series of new models to deal with this problem are being developed.
5. The cost of HRA varies from $2 to $600 per capita depending on the extent of the counseling and preventive medicine activities. New versions of HRA which include laboratory data and medical history information are coming with sophisticated computer processing.
6. Planned HRA application should enable it to become a routine in most organizations in the future.
7. Occupational Medicine training should include some background in HRA.
11. BIBLIOGRAPHY
1. Description, Analysis, and Assessment of Health Hazard/Risk Appraisal Programs: A Final Report. Prepared under contract No. 23-79-3008 for the National Center for Health Services Research; Office of Health Policy, Research and Statistics; U. S. Department of Health and Human Services.
2. Hall, Jack H. and Zwemer, Jack D. Prospective Medicine. Indianapolis, IN: Methodist Hospital of Indiana, 1979.
3. Proceeding of the Annual Meeting of the Society of Prospective Medicine 1974-1979.
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5. Farquhar, John W. The American Way of Life Need Not Be Hazardous to your Health. New York: W. W. Norton, 1978
6. Sorochan, Walter D. Personal Health Appraisal. New York: John Wiley & Sons, Inc., 1976.
7. Vickery, Donald M. Life Plan for your Health. Reading, MA: Addison-Wesley publishing Company, 179.
8. Bauer, C. “Improving the Chances for Health.” Report to the Robert Wood Johnson Foundation (December 1978). Published and distributed by the National Center for Health Education, 211 Sutter St., 4th Floor, San Francisco, CA 94104.
9. Faber, M., ed. “Risk Reduction for Health promotion and Maintenance.” Family and Community Health 3 (May 1980): 1-113
10. Goetz, A.; Duff, J.; and Bernstein, J. “Health Risk Appraisal:
The Estimation of Risk.” Public Health Reports 95 (March-April 1980): 119-126.
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12. “Special Report: Health Hazard Appraisal in the Workplace.” Employment Health & Fitness 2 (February 1980): 21-26.
10.0 SUMMARY LECTURE
SHARE EMPLOYEE PROGRAM
|YOUR HEALTH RISK DATA BEEN ANALYZED AND THE RESULTS ARE SUMMARIZED BELOW |
|AS THEY RELATE TO THE 12 MOST FREQUENT CAUSES OF DEATH FOR WHITE FEMALES AGED 44. |
|? |? |? |CHANCES OF DYING PER 100, 000 WITHIN THE NEXT 10 YEARS |? |
| |? |? | |? |
|? |
|? |
|*AVERAGE CHANCES OF DYING ARE BASED ON 1975-1977 U. S. MORTALITY DATA. (CDC VERSION 1.1) |
|*APPRAISED AGE (DR “HEALTH AGE”) IS AN ESTIMATE OF HOWHEALTHY YOU ARE COMPARED TO OTHERS OF YOUR RACE AND SEX. |
|*ACHIEVABLE AGE IS AN ESTIMATE OF HOW HEALTHY YOU COULD BE BY MAKING THE FOLLOWING CHANGES IN YOUR CONDITION/LIFEESTYLE: |
|SMOKING |FROM |STILL SMOKES 40 | |TO: |STOPPED SMOKING |
|BP: SYST |FROM |250 MM. |TO: | |140 MM. |
|BP: DIAS |FROM |120 MM. |TO: | |88 MM |
|ALCOHOL |FROM |41 DR MORE/WEEK |TO: | |STOPPED |
|FH/BREST |FROM |NO FAMILY HIST. |TO: |NO FH SELF-EXAM |
|PAPSMEAR |FROM |NOT HAD/NOT SURE |TO: |AS RECOMMENDED |
|WEIGHT |FROM |450 LBS |TO: |220 LBS. |
|S-SCALE |FROM |ABOVE AVERAGE RISK |TO | |
|****= = = = ***************************************************= = = =**** |
NOTE—SUICIDE RISK IS PRTLY BASED ON ANSWERS TO QUESTIONS ABOUT PHYSICAL HEALTH, LIFE SATISEACTION, SOCIAL TIES, HOURS OF SLEEP, RECENT LOSS MISFORTUNE AND MARITAL STATUS.
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Learning to Live without Cigarettes. New York, Dolphin, 1973.
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[pic]
The use of mortality data in setting priorities for disease prevention
H. N. Colburn, M. D.* and P. M. Baker, Ottawa, Ont.
Summary: The examination of specific disease mortality by five-year age groups helps identify health problems as problems of people and how they live. Traditional methods of examining data in broad classifications tend to obscure etiological factors and the importance of behavior. Violence, a major cause of death in young adults, gives way to so-called diseases of indulgence in middle age, especially among men who have a much higher death rate than women. Male life expectancy at age 40 has increased only marginally in the past 40 years. Health-related human behaviour must be considered within an ecological framework since social, cultural and physical environmental differences as well as personal factors influence life-style. The responsibility for prevention rests more with the individual and society at large than with health workers. Probability tables, Health Hazard Appraisal (a system of personal risk assessment) and personal counseling can reinforce healthful life-styles and help correct hazardous ones.
Resume: Les donnees de mortalite et leur valeur pour etablir les priorites en matiere de prevention de la morbidite
Letude de la mortalite par maladies specifiques et dans des statistiques portent sur des groupes d’age de cinq en cinq ans, permet de reconnaitre les problemes de sante comme des problemes individuals et d’identifier le mode de vie de ces indivudus. Les methods classiques d’evaluation des donnees en des categories larges ont pour effet d’obscurcir les facteurs etiologiques et l’importance du comportement individual. Si la violence est une cause importante de mort chez les jeunes adultes, chez les gens d’age mur cest surtout labus des bonnes choses qui les rend malades, en particulier les homes
Non-Medical use of Drugs Directorate. Health Protection Branch. Health and Welfare Canada
Statistics Canada: formerly Health and Welfare Canada
Reprint requests to: Dr. H. N. Colburn, 9th Floor, the Journal Building. 365 Laurier Avenue W., Ottawa, Ont, KIA 1B6
don’t is mortalite est deja tres superieure a ceile des femmes. Depuis les 40 demieres annees l’esperance de vie des homes de 40 ans n’a guere augmente. II faut envisager le comportement de l’homme a l’egard de sa sante d’une maniere globale, dans un cadre ecologique complet, car on sait que les differences de milieu, au point de vue social, culturel et physique, et des facteurs strictement personnels influencent le mode de vie. La responsabilite de la prevention repose donc bien plus sur l’individu et la societe en general que sur les specialists de la sante. Les tables de probabilite, le “Health Hazard Appraisal” ou Reieve des risques personnels (systeme d’estimation des risques personnels de maladie) et les conseils personnels peuvent modifier les modes d e vie dans un sens favorable et contribuer a corriger ou a eliminer les facteurs dangereux.
The examination of rates of mortality due to specific diseases by rank within five-year age groups, as described by Robbins and Hall, helps to put in perspective for each stage of life the most important potential health problems. Health problems can thereby be more clearly seen as problems of people and how they live. This knowledge can then offer guidance in determining the means of improving an individual’s chances not only of long life, but also of enjoying healthful and disease-free living.
The traditional methods of examining data in broad classifications such as heart disease, cancer, accidents, etc. Omitting reference to small age groupings, tend to obscure etiological factors. The importance of behaviour and the potential for its alteration with attendant lowering of the risk disease and early death – the true role of preventive medicine – are all too often overlooked.
A glance at the 12 leading causes of death for the next 10 years for Canadian men and women now at age 20 (Table 1)** shows the role of violence in the deaths of young people, tragedies of particular concern because of the loss of human potential.
Jumping to the 45-year age group (Table II). One sees a change to what
might be considered diseases of indulgence. Heart attacks, lung cancer, cirrhosis of the liver and stroke join motor vehicle accidents and suicide to reduce the chances of individuals reaching and enjoying retirement. Two of the major smoking-related diseases, heart attack and lung cancer, are now first and second causes of male deaths and remain so between 45 and 64. The other leading diseases influenced by smoking, chronic bronchitis and emphysema, move quickly up the ranks after age 45 and join heart attacks and lung cancer among the top five causes of death for men aged 55 to 70. For women aged 45, breast cancer, heart attack and stroke are the three leading causes of mortality with suicide, lung cancer, cirrhosis of the liver and motor vehicle accidents in 6th, 7th, 8th and 9th places respectively. Lung cancer may be expected to assume more importance among female deaths as women’s exposure to cigarette smoking increases.
By age 65 (Table III) heart attack, stroke, lung cancer and chronic bronchitis and emphysema are the leading causes of death for men. The impact of diseases attributable mainly or in part to cigarette smoking is striking. For women at age 65 the order is heart attack, stroke, cancer of the intestine includingrectum, and breast cancer.
The tables show the marked excess of mortality in men over that in women. Much of the difference is attributable to the greater risks men assume in the way they live. It is noteworthy that, despite improvements in medical care and social conditions, male life expectancy at age 40 increased by only one year between 1930-32 and 1965-67 while that of women increased by five years.
Reliable and complete data on morbidity are not available. For this reason
One is compelled to use data as indicators of potential health problems. The mortality data are only the disability and the destruction of the quality as well as the quantity of life.
The leading causes of death in south and middle age – motor vehicle accidents and heart attack, respectively – are associated with specific types of human behaviour, as are lung cancer, cirrhosis of the liver and chronic bronchitis and emphysema. Human behaviour must be considered within an ecological framework rather than in isolation. There are social, cultural and physical environmental difference as well as personal factors that help determine whether individuals eat and drink too much, smoke or physically inactive. Ultimately, however, it is the human response to feelings and environment that determines the outcome. Truly, we so often do not die – we kill ourselves, and the responsibility for prevention rests more with the individual and society at large than with the health worker.
The importance of behaviour and environment is emphasized in the four primary divisions (human biology environment, life-style and health care organization) of the health field concept developed by the long-range health planning branch of the Department of National
Health and Welfare. In describing the health field concept, Laframboise said, “It is humbling to realize that all the technological advances of clinical medicine, the prepayment and organization of health services and the removal of health pollutants, have little effect on the decision of an obese person to reach for another place of strawberry shortcake”.
Modern disease prevention is not confined to doing things for an to people, for example, ensuring for them safe food and water and immunning them against infectious diseases. Increasingly, doctors and other Health workers can use knowledge about personal health risks to advise individuals and society how they can alter environments and change attitudes and acorns to ensure healthful living. For example, physical activity requires places to walk, run, and cycle and so forth, as well as personal motivation. Similarly a child may not be able to resist smoking in an environment that does not support nonsmoking behaviors.
McKeown, who has written intensively in this v vein, has concluded that “Past improvement has been mainly due to modification of behaviour and changes in the environment and this to these same influences that we just look particularly for further advantage.”
It is suggested that programs of
Table 1-Causes and probability of death within the next 10 years (from 1971)
|Men, age 20 |
|Rank Cause of death |
|Probability |
|1 |Motor vehicle accidents |661 |
|2 |Suicide and self-inflicted injury |225 |
|3 |Accidental drowning and submersion |106 |
|4 |Accidental poisoning |47 |
|5 |Homicide |46 |
|6 |Tambours of lymphatic and hemtopoietic |33 |
| |tissue excluding leukemia | |
|7 |Accidental falls |25 |
|8 |Cerebrovascular disease |20 |
|9 |Air and space transport accidents |20 |
|10 |Accident caused by fire |19 |
|11 |Ischemic heart disease |17 |
|12 |Accidents caused by firearm missiles |16 |
| |causes | |
| |All other causes |387 |
| |All causes of death |1622 |
|Women, age 20 |
|Rank Cause of death |
|Probability |
|1 |Motor vehicle accidents |170 |
|2 |Suicide and self-inflicted injury |57 |
|3 |Cerebrovascular disease |23 |
|4 |Accidental poisoning |23 |
|5 |Homicide |18 |
|6 |Pneumonia |15 |
|7 |Leukemia |14 |
|8 |Tambours of lymphatic and hematopoietic |14 |
| |tissue excluding leukemia | |
|9 |Breast cancer |13 |
|10 |Chronic rheumatic heart disease |11 |
|11 |Congenital anomalies of the heart and |9 |
| |circulatory system | |
|12 |Accidental drowning and submersion |8 |
| |All other causes |227 |
| |All causes of death |602 |
*Per 100,000
Table II-Causes and probability of death within the next 10 years (from 1971)
|Men, age 45 |
|Rank Causes of death |
|Probability |
|1 |Ischemic heart disease |2653 |
|2 |Lung cancer |477 |
|3 |Motor vehicle accidents |322 |
|4 |Cirrhosis of liver |316 |
|5 |Cerebrovascular disease |309 |
|6 |Suicide and self-inflicted injury |302 |
|7 |Intestinal cancer including rectum |180 |
|8 |Other forms of heart disease |131 |
|9 |Stomach cancer |121 |
|10 |Tumours of lymphatic and hematopoietic |111 |
| |tissue excluding leukemia | |
|11 |Chronic bronchitis and emphysema |106 |
|12 |Pneumonia |104 |
| |All other causes |2132 |
| |All causes of death |7264 |
|Women, age 45 |
|Rank Causes of death |
|Probability |
|1 |Breast cancer |516 |
|2 |Ischemic heart disease |496 |
|3 |Cerebrovascular disease |266 |
|4 |Intestinal cancer including rectum |196 |
|5 |Cancer of ovary, fallopian tube or broad |151 |
| |ligament | |
|6 |Suicide and self-inflicted injury |145 |
|7 |Lung cancer |122 |
|8 |Cirrhosis of liver |122 |
|9 |Motor vehicle accidents |117 |
|10 |Cancer of the cervix |116 |
|11 |Chronic rheumatic heart disease |97 |
|12 |Tumours of lymphatic and hematopoietic |70 |
| |tissue excluding leukemia | |
| |All other causes |1357 |
| |All causes of death |3771 |
*Per 100,000
health promotion and disease prevention might give more attention to helping people under 65 reach retirement safely and enjoyable. Such programs may be developed around mortality tables for five-year age groups and concentrate on helping young and middle-aged individuals to understand their own risk-taking forms of behaviour and their relationships to potential health problems in the immediate and more distant future. For example, a 25-year-old man can see his risks for the next 10 years, as well as his risks at 45 if he continues his current life-t\style. This review can reinforce healthful life-styles as well as draw attention to hazardous ones. The higher level of risk-taking behaviour among men indicates where priorities lie.
The physician in his role as personal counselor can influence the individual’s response. The this end the system of personal risk assessment termed Health Hazard Appraisal, developed by Drs. Lweis Robbins and Jack Hall at the Methodist Hospital of Indiana, Indianapolis, is particularly relevant.. The experimental use of Health Hazard Appraisal in Canada ha been described in recent articles.
Physicians or other health workers wishing to have a set of tables showing chances jof dying in the next 10 years for each five-year age group or further
Table III-Causes and probabilityj of death within the next 10 years (from 1971)
|Men, age 65 |
|Rank Cause of death |
|Probability |
|1 |Ischemic heart disease |13623 |
|2 |Cerebrovascular disease |3160 |
|3 |Lung cancer |2724 |
|4 |Chronic bronchitis and emphysema |1522 |
|5 |Intestinal cancer including rectum |1220 |
|6 |Diseases of arteries, arterioies and |1048 |
| |capillaries | |
|7 |Stomach cancer |872 |
|8 |Cancer of prostate |827 |
|9 |Pneumonia |765 |
|10 |Other forms of heart disease |645 |
|11 |Diabetes mellitus |630 |
|12 |Cancer of pancreas |527 |
| |All other causes |7791 |
| |All causes of death |35354 |
|Women, age 65 |
|Rank Cause of death Probability |
|1 |Ischemic heart disease |6966 |
|2 |Cerebrovascular disease |2502 |
|3 |Intestinal cancer including rectum |1025 |
|4 |Breast cancer |913 |
|5 |Diabetes mellitus |840 |
|6 |Diesease of arteries, Arterioles and |518 |
| |capillaries | |
|7 |Other forms of heart disease |447 |
|8 |Stomach cancer |392 |
|9 |Pneumonia |362 |
|10 |Cancer of pancreas |331 |
|11 |Cancer of ovary, fallopian tube or broad |326 |
| |ligament | |
|12 |Lung cancer |319 |
| |All other causes |5555 |
| |All causes of death |20496 |
information a bout Health Hazard Appraisal may write to: Smoking and Health, Non-Medical Use of Drugs Directorate, Health Protection Branch, Health and Welfare Canada, Ottawa. Those wishing more detailed information about Canadian mortality probabilities by age group should write to Dr. W. H. Cherry, Associate Professor of Statistics, University of Waterloo, and Waterloo, Ontario.
The assistance of Dr. W. H. Chery, Dr. Gaston Coquette, Miss L Craig, Mr. R. Lauzon, Dr. A. B. Morrison and Mr. B Sawka, is gratefully acknowledged.
Reference
1. Robbins L Hall J: How to practice Prospective Medicine. Methodist Hospital of Indiana. 1970
2. Laframbose Hl. Health policy: breaking the problem down into more manageable segments. Can MED ASSOC j 108: 388. 1973
3. mCkFOWN t. A historical appraisal of the medical task, in Medical history and medical care published for the Nuffield provincial hospitals trust by oxford university press, 1971
4. CHOOUETTE G: Evaluation des risques personnels. Med que 8: 38, 1973
5. Idem: Popullations exposees et ennemis a combattre Ibid jp 42
6. Idem: Role des media dinformation et des centres de medicine prenvention Ibid p 34
7. COLBURN HN: Health Hazard Appraisal: a possible tool in healthj protection and promation. Can Jj Public Health 64. 490. 1973
8. CHERRY WH. COLBURN HN: Tabulations of the chancej of dying from 52 selected causes for Canadian residents. Department of statistics, Universityj of Waterloo, Waterloo. Ont 1973
Prospective medicine–
improving the patient’s survival odds
One way for an AMN editor to explore prospective medicine for a story assignment is to put himself through the examination. That’s what Associate Editor Bill McCulloch did.
Here is his report.
Your average 32-year-old newspaper reporter has every reason to feel confident-and maybe even a little bit smug-about his chances of making it through the next 10 years.
The so-called Geller Mortality Tables indicate that for every 100,000 white males in their early 30’s, 97, 780, will live to see their early 40’s. Only 2,20 of us will fall by the wayside, or one man in 45.
Now those are pretty good odds.
According to Nancy Gilbert, though, my odds aren’t quite that good. She’s the registered nurse who gave me my Health Hazard Appraisal at Methodist Hospital in Indianapolis. And what she found, basically, was this.
If we could find 100,000 white males in their early 30’s who smoke and drink as much as Bill McCulloch does, we’d probably lose about 4,450 of them over the next 10 years.
FOR A HORSEPLAYER, those are still pretty attractive odds: only one chance in 22 to come a cropper. Trouble is, horseplayers gamble with their money, not their lives. The plain simple truth of it is that Bill McCulloch’s risk of dying within 10 years is – statistically speaking – about double the average in his peer group.
Now here’s the real topper. Let’s s ay Bill McCulloch has a bad chest cold and goes to see a doctor. The doctor probably will tell him to get plenty of rest, take aspirin, and drink lots of fruit juice. Oh yes, and call again if that cough gets any worse.
Here’s a patient whose habits make him five times more likely than average to die in an auto accident. His risk of dying of cirrhosis is more than 12 times the average; of pneumonia, three times average; of lung cancer, nearly two times. In other words, this guy has health risks that make his chest cold look like nothing.
And some doctor is going to tell him to get plenty of rest, take aspirin, and drink fruit juice. What is going on?
“We’re sitting around waiting for people to get sick when we should be trying to identify the things that make them sick,” says Kenneth F. Kessel, M.D., director of the Family Practice Center at McNeal Memorial Hospital in west-suburban Chicago. “Really, it is amazing to see the fantastic resources medicine can draw on in order to get someone through a crisis. But there are no similar resources invested in trying to prevent the crisis.”
THIS CONCERN in shared by Lewis C. Robbins, M.D., former director of the Health Hazard Appraisal project at Methodist Hospital, Indianapolis. “Our situation
in medicine today,” he says, “reminds me of a few baseball games I’ve seen. Right now, we’re relying almost completely on spectacular, game-saving catches by the outfielders.
“I’d rather see us get a new pitcher in there, some fellow who can keep the batters from getting such good wood on the ball in the first place. We ought to be making things easier for those outfielders.”
The fellow that Dr. Robbins wants to bring in from the bullpen is a physician whose “out pitch” is something called prospective medicine, the science of solving problems before they become crises.
Prospective medicine first began to take shape as a clinical discipline about 15 years ago. It was initiated in the U.S. Public Health Service and was viewed-at the time anyway-as a weapon in the war on cancer. Dr. Robbins, then chief of cancer control for the Public Health Service, was instrumental in developing the prospective-system.
PROSPECTIVE MEDICINE has since outgrown its original categorical emphasis; nowadays it is multidisciplinary. Its advocates say it has been adopted by hundreds of primary care physicians throughout the U.S. and Canada. In addition, the prospective approach to medicine is being taught in several family practices training programs, among them the residency program headed by Dr. Kessel and MacNeal Memorial outside Chicago.
Judged by prevailing standards, prospective medicine is not particularly dramatic or exciting. It is doubtful, for example, that prospective medicine will ever serve as the basis for a popular TV series. Television’s doctor dramas usually offer at least one tense medical crisis per week.
And that is exactly what prospective medicine aims to avoid, which may be one of the reasons why some doctors resist the prospective approach. “Our activities during the clinical phase of training clearly reinforce management of the dramatic,” says Jack H. Hall, M.D., director of Medical education at Methodist Hospital in Indianapolis. “We enter practice expecting minute-to-minute excitement.”
AS DRS. ROBBINS AND HALL explains in their 1970 manual How to Practice Prospective Medicine, the prospective system differs from orthodox medicine in three respects. It is continuous instead of episodic. It is comprehensive, not fragmented by specialties. And as its name clearly implies, it is initiated before, not after, the onset of disease.
Prospective medicine has at least two familiar aliases – predictive medicine and preventive medicine. Neither name is 100% accurate, though, for the same reason that it would be misleading to refer to orthodox practice as curative medicine.
No physician can guarantee to cure his patients of disease. He can only promise to apply his knowledge in a way that will secure the greatest possible healing advantage for a given patient. This is essentially the same promise made by prospective medicine. It cannot predict disease; it
cannot prevent disease. It merely seeks to establish what Dr. Robbins calls a “survival advantage.” It does this by offering each patient a plan for the management of his “disease precursor,” meaning his harbingers of trouble.
According to Dr. Robbins, there are about 22 significant precursors. The average “well” person, he says, carries three of them, and they boost disease risks just as surely as contaminated water used to increase the risk of typhoid fever. Typhoid fever, notes Dr. Robbins, was not brought under control by better disease treatment, but by improved water and sewage (precursor) treatment. The parallel is relevant to prospective medicine.
MANY PHYSICIANS say experience has trained them to be on the lookout for important disease precursors in their patients. They say they react automatically. And to this extent, they claim, they’ve been practicing prospective medicine for years.
But Dr. Robbins wants to go beyond that. He doesn’t discount the importance of physician intuition, or savvy, or whatever. But he does believe that prospective medicine needs as organized format, a system. And this is where the Health Hazard Appraisal comes in. Used properly, explains Dr. Robbins, the Health Hazard Appraisal can help the physician map out an effective 10-year survival plan for any patient. Here’s how the appraisal works:
• It identifies average risks.
Average health risks are based on mortality statistics. According to the Geller Mortality Tables, for example, traffic accidents are the No. 1 killer of white males in their 30’s. The tables tell us that in a group of 100,000 white males, age 30-34, we can expect 376 auto accident fatalities over the next 10 years. The number 376 expresses the average risk for this particular cause of death.
For atherosclerotic heart disease, the No 2 cause of death, the average risk is 310. And so on down the list. When all causes are lumped together, the average 10-year death risk in this age/race/sex group is a composite 2,220.
The appraisal quantifies the patient’s risks.
The patient’s risks are expressed as deviations above below the average risk. These deviations are noting more than numerical extrapolations of personal health characteristics, or to put it another way, precursors translated into numbers.
People who drink a lot, for example, are believed more likely to die in auto accidents than are teetotalers. But how much more likely? Five times more, according to the precursor tables that is used in conjunction with the Health Hazard Appraisal. So the 32-year-old heavy drinker would g et a factor of 5.0 on his No 1 risk. And his 10-year risk of dying in an auto accident would be expressed as five times the average risk of 376, or 1, 880.
By totaling the patient’s various risk figures, another composite is determined, one that can be compared to the average. American Medical News Associate Editor Bill McCulloch has a composite 10-year death risk of 4,450-as mentioned earlier-about twice the average.
*The appraisal establishes unmistakable goals.
“Like most human beings,” observes Methodist Hospital’s Dr. Hall, “We doctors are reluctant to establish goals. We don’t want everybody to know what the target is, because then they can tell if we’re missing.”
But the Health Hazard Appraisal doesn’t leave much room for hedging. Once the patient’s risks are spelled out, the physician makes his commitment: “Get this patient safely through the next 10 years.” That’s the goal; and it is printed at the top of every appraisal form.
In reaching for that goal, the physician sets priorities and does what he can to improve the patient’s survival odds. He does his best to find the necessary survival advantage.
* The appraisal offers a plan for survival.
If there is to be any improvement in the patient’s 10-year survival chances, the physician must look for appropriate ways to reduce the patient’s risks. This is perhaps the most difficult part of the Health Hazard Appraisal.
Obviously, the risk of ling cancer subsides if a cigarette smoker quits smoking. The risk of dying in an auto accident is reduced if the driver always buckles his safety harness. The risks of cirrhosis declines if a problem drinker goes on the wagon. The risk of arteriosclerosis drops off it the patient controls what he eats and gets regular exercise.
But these survival advantages may depend on the modification of behaviour patterns that have been established over years or even lifetimes. And as most physicians are aware, you can lecture patients all you want without having the slightest impact on behaviour. “No, the parental approach just doesn’t work,” observes MacNeal Memorial’s Dr. Kessel. “And you can’t use scare tactics either or you’ll just push the patient into a denial thing.
“About the best you can do,” he says, “is give the patient as much information as possible about his problems and hope that he’s motivated to do something about them.
And maybe 25% follow through. That’s not a lot. But it’s better than zero percent.”
Dr. Robbins believes strongly in the effect of positive reinforcement. “I have good news!” is his usual opening remark to an appraisal subject. “As of right now, this year,” he’ll say, “you can importantly reduce your risks of disease.”
The diminutive Indianapolis physician than outlines a plan for reducing the risks. And after that, it’s up to the patient. Dr. Robbins is never preachy. But the information he presents does convey a sense of urgency. The patient may fell fine, not a complaint in the world. And yet, it suddenly seems important to reduce the risks that Dr. Robbins is t talking about.
THE HEALTH HAZARD Appraisal helps to illustrate the tasks at hand with its catalog of death causes and risk figures. The appraisal also provides incentives for behaviour modification by showing the patient a sort of “before and after” picture of himself.
Bill McCulloch’s appraisal lists a composite patient risk figure of 4450. Also listed, however, is a hypothetical risk figure-it’s the carrot at the end of the stick. It says, in effect, that if McCulloch will give up smoking, cut way back on his drinking, and get a little more exercise, his composite risk figure would drop below 2,000.
The Health Hazard Appraisal also presents an “appraisal age” and a “compliance age.” McCulloch, for example, is said to be facing the same 10-year probabilities of death that are faced by a 40-year- old man. But if he
cleans up his act and starts living right, McCulloch’s compliance age would be somewhere in the low 20’s.
And that’s pretty nice to think about.
SURE, THE AGE FIGURES are a numbers game, a clever way of dramatizing an objective. That’s all. But the people ho administer Health Hazard Appraisals say it’s often the one thing that will really make a patient sit up and take notice. It is a concept to which everyone can relate.
So that’s how the health Hazard Appraisal works. It is by no means a perfect instrument, and it is not universally accepted. “We get shot at by some of the purists in preventive medicine,” admits Dr. Kessel. “They say the appraisal relies on a lot of things that aren’t proven; they wonder if it’s applicable to inner-city populations; they raise questions about what the risk factors mean. And so on.
“But really, the Health Hazard Appraisal is just and attempt to objectify. It forces us into a discipline we didn’t have before.
“If you use the appraisal,” says Dr. Kessel, “there’s no way you can ignore the leading causes of death in a particular patient’s cohort group…. Also, the appraisal makes you look for prescriptions that don’t come out of bottles-physical therapy, counseling, diet, that sort of thing.
“AND THE APPRAISAL is one hell of a good teaching device.”
Drs. Robbins and hall also concede the Health Hazard Appraisal’s imperfections. There is still a great deal to be learned about precursors, they say, and some of the risk factors should be taken with a grain of salt. Alcohol has not yet been included as a precursor to heart disease, for example, despite what some experts claim is mounting evidence that it should be. In addition, the health Hazard Appraisal does not yet list alcohol as a precursor to suicide, even though alcoholics commit suicide at rates four to five time higher than the general population.
Both Dr. Robbins and Dr. Hall predict that the data underlying the Health Hazard Appraisal will improve with time. To that end, Dr. Robbins now works full time coordinating the development and refinement of disease precursor data. In the meantime, he says, physicians need not be reluctant to make use of the appraisal system.
Dr. Kessel agrees. “It’s choice between using what we have or doing nothing,” he says.
PERHAPS BECAUSE of its imperfections, though, the Health Hazard Appraisal loses much of its usefulness when applied in a mass screening situation. The appraisal does not make allowance to the possibility, say, that the 32-year-old problem drinker may not even own an automobile; the guy still gets a risk factor of 5.0 under fatal auto accidents.
“The subjective observations and little findings made by the family physician are important in a Health Hazard Appraisal,” notes Dr. Kessel. “Based on what he knows about his patient, he can make adjustments here and there in the appraisal.
“Plus which, the family physician is the guy who can help the patient deal with his problems. I don’t see any of these specialized preventive medicine clinics really getting involved in patient management or patient car. They’re just advisory,” Dr. Kessel says.
When the average family practitioner hears about prospective medicine, though, one of his first reactions is likely to be, Yes, but will it pay the rent? “We believe it could be remunerative, but we’re not really sure,” concedes Dr. Hall. “ Our biggest problem, as I see it, is convincing the average guy in practice out there that he can charge money for promoting health. He’s been conditioned to think he can only charge for treating sickness. Do you see what I mean? He hasn’t yet learned to act as the patients advocate.”
OBSERVES DR. KESSEL: “This is why episodic medicine is ‘where it’s at’ with the general practitioner. You get fast turnover, and you make a good back. Because of your tanning, you think you have to do something to a patient…you can’t charge him if you just talk to him.”
“And yet counseling should be a major function of the family physician. Our curriculum here includes a tremendous amount of behavioral science…”
According to Dr. Kessel, any physician who does comprehensive prospective studies on his patients is bound to uncover a variety of chronic condition’s “And those ought to pay the rent,” he adds.
It is interesting to speculate about the potential impact of prospective medicine. If it really does work, for example, if we really could keep Bill McCulloch from dying in an auto accident over the next 10 years, maybe we’d merely be sparing him for a worse fate. He might die of lymphatic cancer sometime during the next ten-year cycle. Or he might have heart failure during the 10-years cycle after that. Death is inevitable, whether it comes now or later.
And that, according to Dr. Robbins, is just the point. Too many deaths come now instead of later. He claims that 70-75% of all deaths recorded in this country every year are premature.
Dr. Robbins wants to extend life-but not live on is hospital bed with tubes running out of every orifice. The part of a lifetime that concerns Dr. Robbins is the useful, productive period. That’s what he wants to extend, and that’s where he thinks medicine should begin its battle against disease.
PROGRAM MANAUAL
(used and retained by participants)
Copyright 1981 / 2 R.G.A Boland and A.A Lisiewicz
Content – Manual
Item Page
1. Program Schedule 2
2. Program Objective 3
3. AGL Method 4
4. Acknowledgements 5
5. Syllabus, readings, faculty 6-18
6. Discussion I- Theory and practice of HHA 9-12
7. Discussion II- Methodology 13-15
8. Discussion III – Risk Estimation 16-18
9. Discussion IV – New Methodologies 19-22
10. Bill Brown Cases 23-25
11. Excercise HHA and Cardiovascular Risk 26-28
Appendices
12. Simplified Glossary 30-36
13. Articles and Technical Notes 37
14. HHA Forms and Pre-Program Exercise (Separate package)
15. Tape for Learning Reinforcement
1. Program Schedule
Time Activity Mode
9:00 Registration and Pre-Program Exercise IND
9:15 Quiz IND
9:45 Discussion I- Theory and practice of HHA SG
10:15 Break
10.30 Case Study I - The Polish Sausage maker SG
11:00 Discussion II - Methodology SG
11:30 Case Study II – The Little Prince SG
12:15 Bill Brown Cases SG (new)
1:00 Lunch
1:45 Discussion III – Risk Estimation SG
2:15 Case Study III – great expectations SG
2:45 HHA and cardiovascular Risk CSG
3:00 Case Study IV – The Crunch Pairs
3:45 Discussion IV – New Methodologies SG
4:15 Quiz and Review Pairs
5:00 End
2. Program Objectives
1. The major emphasis of the program is to improve the practical competence of health professionals in completing and using the HHA instrument (as developed by Robbins Hall and adapted by CDC).
2. Specifics learning objectives include:
a. to recognize the language and concepts of Health Hazard Appraisal
b. to develop skills in using the HHA Form B, HHA Chart and Geller-Gesner Tables in computing HHA Present risk (risk score),Health Appraisal Age, New risk Score, and Compliance Age
c. to evaluate the appropriateness of HHA for Varying individual groups, populations and organizations
d. to criticize the existing and future methodology of HHA
e. to motive further study in the future
3. AGL Method
1. The AGL (Autonomous Group Learning Method) was developed min 1969 for management programs as a way of learning in groups without formal instruction. Participants use the materials to develop answer to all the problems and question arising from the learning experience.
2. The materials include:
a. Program Manual – Which is used and retained by participants and includes: discussion notes, simplified glossary, HHA forms, articles and references for future study
b. Text Book – which is used and retained by participants and includes: Gellner- Gesner Tables, by age, sex and race, risk factors, definitions, weight analysis data and health age, etc.
c. Work Pack – which is used but NOT retained by participants and includes: case studies, questions to aid the analysis of the cases, exercises, quizzes, case solutions, learning patterns, etc.
3. The work will be done: IND – individually; PAIR – in pairs; SG – small group; CSG – combined small groups; MG – main group
Groupings will be changed so as to give participants the opportunity to work with different course members.
4. The Group Organizer is provided to assist the groups in solving the problems and to answer
Questions, and thus achieve rapid individual learning in the limited time available.
5. Separate notes are provided to who how the AGL method is applied to the ues of Discussion Notes and Case Studies.
4. Acknowledgements
We are extremely grateful to Charlie Althafer, Richard Lasco of CDC for all the help and encouragement they have given us.
Lynn Hawkins and Paul Melia from Health and Welfare, Canada, has provided us with all and information that was available of the work being done in Canada. Robert Spasoff and Ian McDowell spent time with us discussing their studies. To all these people and others in the
“ Prospective Medicine”.
Community, too numerous to mention, we offer our sincerest thanks. Any errors or omissions, however, we must take full responsibility. We would like to hear from you as to how to improve this presentation.
Robert Boland
Adam Lisiewicz
5.0 SYLLABUS OF THE INSTITUTE
GOALS
The major emphasis of the Institute is to improve the competence of health professionals to use the HHA instrument.
The specific goals would be to:
- teach the participants the mechanics of the Robbins & Hall method for HHA.
- help them understand the scientific basis of risk estimation.
- make them aware of the controversies surrounding the way HHA risks have been
assessed .
- Introduce them to the latest methodological advancement in appraising risk.
- Re-orient those people using the HHA instrument towards research on the effectiveness of the instrument in motivating people to change their life styles.
OBJECTIVES
A. Cognitive objectives
At the end of the Institute, the participant will be able to:
- use frequency tables to answer to answer questions about probabilities.
- apply Bayes’ Rule to the solution of simple diagnostic problems.
- define the odds ratio.
- know the difference between prospective and retrospective studies.
- critically appraise the odds ratio concept.
- understand the importance of independence for estimating risk.
- describe the American Cancer Society and Framingham Studies.
- use the formulas that quantify a single risk variable.
- combine the quantitative effects of multiple risk factors for a single cause into a composite risk factor.
- manipulate given information to calculate the probability of dying from a given cause in a specified cohort.
- Covert probabilities to represent death per 100,00.
B. Affective Objectives
At the end of the Institute, the participant will be:
- more critical in examining HHA instruments.
- Appreciative of the subtle controversies regarding risk assessment.
- More oriented towards research of the effectiveness of the HHA instrument as motivators of life style change.
- More selective in the utilization of an HHA instrument.
C. Psychomotor Objectives
At the end of the Institute, the participants will be able to:
- use the HHA tables found in the “ Prospective Medicine” textbook.
- calculate the estimated risk from given information.
- utilize the Geller-Gesner risk from given information.
- estimate health appraisal age using standard or current methodologies.
CONTENT OF THE COURSE
1. The evolution of the HHA concept is historically linked with the Robbins and Hall work in Prospective Medicine.
2. The Mechanics of calculating HHA’s based on laws of probability, odds ratio concept risk assessment extrapolation is practiced used the case study and AGL methodology.
3. Issues in methodology and organization is described
4. Cardiovascular Update and its application to the HHA is presented.
5. New methodologies for measurement of HHA are described.
FACULTY ON THE COURSE:
R. E. Boland, M.D, M.P.H.
D. Caralis, M.D ., M.P.H.
A. Lisiewicz,M.Sc., Ph.D.
6. Discussion I – Theory and Practice of HHA
Preliminary notes on AGL method of using the materials:
6.1 (SG Individually (IND) – briefly scan the discussion notes
6.2 In small groups (SG) (A, B, C, D)
- A reads the first section to the SG
- B summarized briefly what A has said and then reads the seconds section to the SG
- C summarized what B has said and reads the next section to the SG, etc.
6.3 Individually – re-read the discussion material
6.4 Small group – discuss questions arising using the flip chart to improve communication
Note:
a. Work quickly to cover all the material in the short time allowed. The data will be repeated again and again during the program so that points not fully understood initially will become clear in subsequent discussions
b. Use your notebook to record key points and questions for which the small group cannot develop satisfactory answer. Raise the questions later in the program.
c. Use the glossary for new technical words.
HEALTH RISK APPRAISAL – ONE DAY PROGRAM
1. OBJECTIVES OF THE PROGRAM
a. To use the language and concepts of HRA starting with the Robbins technique and progressing to more advanced models using computers.
b. To develop skills in making HRA computations using Personal Data sheets, Geller-Gesner Tables and Computation Charts.
c. To determine relevant lifestyle interventions and compute new risk Score and Health Compliance Age.
d. To evaluate the existing and future HRA methodologies and their appropriateness to individuals, groups and organization.
e. To motivate further study in the future.
2. TIME & LOCATION – date one day 8:30 am to 5:00 pm
3. PARTICIPANTS
The program is designed for both Health Professionals (physicians, nurses, health educators, etc) and for non-health professionals (personnel officers, managers, administrative staff, etc.).
4. CONTENT
The syllabus covers the following topic: definitions of HRA, historical review of HRA, data base problems and research, risk factors, HRA systems, personal data sheet, computations charts, relevant disease/injuries, prognostic characteristics, risk score computation, health appraisal age computation, intervention and compliance strategies, choice of prognostic characteristics, quantification of risk, risk and the healthy participant, risk and the young male, HRA effectiveness, HRA trends for the 1980’s, debit/credit methods, log linear methods, logistic methods, traveling methods, ethical issues, formatting, motivation and overall methodology for HRA implementation.
5. METHOD
The program will use the AGL (Autonomous Group Learning) method which was developed in 1969 for international management training program. It is a way of learning I groups without formal instruction. Participants use the materials and group resources to develop answers to all cases and question arising from the learning experience.
6. MATERIALS
The materials include: participants manual (lectures, question, exercises, cases, glossary, references, and articles for future study), text book and a learning recall tape (LRT). The tape is used for one hour weekly for three weeks following the program to improve the quality of learning and to convert short term learning to long term learning.
Johnson & Johnson employees and member companies. The institute personal were confident that if such a program was judged to be effective it could be made cost-effective through automation and the involvement of large numbers of people. Program personnel stated that one can screen people cheaply and although they don’t know the exact costs they are certain that such a program might be done for less than $140.00 per employee per year for a three year program in a fairly large company.
V. Data and Data Processing
In-house computer processing was considered but a bid from CISI group was considered more cost-effective. The CISI group provides computer services for those phases of the program which involve a production mode. Research Triangle Institute in North Carolina did the original programming for the health profile. There is also an employee participation system data set which is collected in-house and then is sent to RTI for analysis. There is also an employee cost system which is attempting to obtain and analyze data on health care costs. Since Johnson & Johnson is a self-insured Corporation they are able to collect information on numbers of dollars spent, numbers of claims, and numbers of dollars per claim.
VI. General Assessment
The representatives of Johnson & Johnson feel that the philosophy of the Live for Life Institute and the model which they have chosen to follow is consistent with the current state of the art in risk estimation and risk reduction. They are convinced that the “classical” HHA/HRA method because of its rather heavy-handed approach to motivation and its failure to focus on positive aspects of health behavior is inferior to the Live for the Life Institute model, at least for Johnson& Johnson employees. The Live for Life Institute is investing considerable resources in order to demonstrate that the Live for Life model is proper, cost-effective, and beneficial. However, even given this the data may not support their hypotheses. If such is the case a decision will be made as to whether the subsequent step will involve further program development and refinement or cessation of the program. The Live for Life Institute is a part of a profit-making concern and therefore, the representatives of the program were cautions in sharing their information and data with us. We understand and support this reluctance. It should be noted that the reluctance did not affect their willingness to talk frankly about the program.
Summary Resume – Dr. R.G.A. Boland
1. Personal
Address- c/o Bridgeport Hospital, Conn.06602 (203-384-3000 or 3644) Nationality – English with U.S residence visa
Languages – English, Spanish, French
2. General Education
Nottingham University (B.A. hons 1957)
Harvard University (I.T.P. 1962)
Stellenbosch University (PhD psychology 1973)
3. Medical Education
Phd-MD program of Juarez Medical School – MD due in June 1978
4. Medical Experience
Director of Cape Regional Hospital Management Training Program (1966/70)
Juarez General Hospital and Juarez Social Security Hospital – clinical experience (1976/77)
Fair field Hills Hospital (Conn) – external (psychiatric) (1977)
Bridgeport Hospital (Conn) – extern (OBGY, surgery, pediatrics) (1977/78)
St. Mary’s Hospital (Conn) – extern (medicine) (1978)
5. Other Professional Experience
Tenured full professor (University of Cape Town) (1965/76)
Professor of educational technology (INSEAD, Paris) (1965/76)
Consultant in training and management to various organizations in U.S.A.,
Europe and Africa (chitin Accountant (u.k). C.P.J (U.S.A)
About forty publications in learning systems used in thirty countries and seven languages.
6. References
Professor Dean Berry, yale University, New Have, Conn.
Dr. Douglas Thomas (DME) Fairfield Hills Hospital, Conn.
Dr. Norman Canter, Bridgeport Hospital, Conn.
Dr. Mariano C.Allen (former Director of PhD-KD Program), Hotel Dieu Hospital, El Paso, Texas
Various international references in educational technology field used to obtain 3rd preference visa for U.S. residence
SKILLS BUILDING SESSION
POSITIVE SELF-STATEMENTS:
Our thoughts and beliefs can make even the most nonthreatening situation stressful. Self-defeating beliefs can be changes.
MEDITATION:
Meditation is the ancient method of relaxation that ha been practiced the world over, especially in the EAST, that Western science has now discovered as very helpful in relieving stress. The ancient philosophy behind it is complex , but unnecessary to the modern user of the method. Once the method has been learned, it takes no more than about 20 minutes a day to receive full benefit. This skill session will talk about its benefits: way to use it in a busy schedule, and a twenty minute practice will be utilized.
JACOBSON’S METHOD O FPROGRESSIVE MUSCLE RELAXATION:
This is the mos popular and one of the most effective methods of whole body muscle relaxation. Participants will be given some theoretical background and instruction in the method. Participants will also experience the complete method in the session so that they can begin to develop the skills involved.
COMMUNICATION TECHNIQUES:
Interested in brushing up on skills in listening and giving feedback? In this elective, concepts of active listening and communicating with empathy wil be introduced, and you will have an opportunity to try out and practice these communication skills. (P.S. This may be a little elementary for those who have taken the Westinghouse Communications Workshop).
FLEXIBILITY EXERCISE AND PULSE MONITORING:
Participants will be introduced to and briefly engage in a simple routine of bending, stretching, twisting exercises. Use of this routine for 3-5 minutes per day can improve and maintain flexibility. Also, for those interested in a program of vigorous exercise or aerobics opportunity will be provided to learn to check one’s own pulse and to determine the pulse range which is both sufficient and safe. This technique can be used to monitor an exercise program to assure that one does enough but not too much of any strenuous exercise.
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