Use of epidemiological data as the basis for developing a medical curriculum.

INTRODUCTION

Recent reports have identified overall challenges and the need for innovations in the structure and process of medical education at all levels. These documents suggest that doctors need to be prepared for a more demanding society, and be ready to cope with the explosion of scientific knowledge and technology. Doctors would need to have an aptitude for lifelong learning and be prepared to be part of a working team. 1 , 2 , 3 , 4

It is interesting to note that active learning principles would need to be considered as early as possible during medical school in order to provide the benefits of teamwork in areas like primary care. 5 Nonetheless, a systematic review has suggested that active learning, like the problem-based learning approach, does not have an impact on knowledge acquisition in undergraduate medical education, even though appropriate outcome measurements need to be considered. 6 A generalist education that could provide skills, knowledge and attitudes that make it possible to understand patients’ expectations, address wellness rather than illness alone, assimilate concepts of clinical epidemiology, develop interpersonal communication and strive to control costs would require shifts in attitude and behavior throughout the academic medical community. 7 In Brazil, despite the large number of medical schools, just a few adopt active learning principles, and yet some reports also suggest that the traditional curriculum leaves students poorly educated about the underlying principles of the national health system. 8 , 9

General medical education guidelines usually have clear statements about content and skills, but there are no priorities defining central themes. The core curriculum with special study modules was considered to be a reliable response to content overload, but there is still no suggestion about how to choose a central theme. 10

OBJECTIVE

The aim of this paper was to present a methodological proposal that could help curriculum managers to address this challenge, taking local and regional morbidity and mortality into consideration. We constructed an epidemiological score that can be used by specialists to develop learning objectives or even international requirements. 11

METHODS

Data relating to mortality (OBT) and morbidity (MRB) were taken respectively from summaries of deaths and the Disability-Adjusted Life Year (DALY) measurement of the World Health Organization (WHO) for the year of 2004. 12 These data were chosen to present an international perspective for educational taxonomy directed by mathematical treatment.

The reported numbers of registered deaths and diseases were distributed into columns and rows according to the list provided in the WHO database. No ages or genders were identified. The probabilities were reached by means of R syntax, to reach a cumulative distribution function (CDF) for any value x . R is a language and an environment for statistical computing and graphics that is available as free software under the terms of the Free Software Foundation’s GNU General Public License, in source code form (http://www.r-project.org/).

The final score took into account the square root for the product of morbidity P(MRB) and mortality P(OBT) probabilities. Briefly, the frequencies were tested using the Shapiro-Wilk normality test or after Log10 transformation for both morbidity and mortality. Then, the Z numbers for both morbidity Z(MRB) and mortality Z(OBT) were obtained in order to use the definite integral, from which the results are the probability for each of the diseases from the WHO DALY and death summary lists (see Appendix for equations). In order to obtain a normal distribution, it is advisable to use a large database.

The 75 th percentile (quartile) from the score was used to indicate the subjects to be considered for educational taxonomy.

RESULTS

Three countries were selected for comparison: United Kingdom (UK), Brazil (BR) and Rwanda (RW). They were representative of higher to lower-accuracy database registering, according to the WHO DALY methodology. There were 71 conditions for UK, 82 for Brazil and 87 for Rwanda that reached a score higher than zero ( Table 1 ).

The score allowed separation of the results into quartiles. The highest quartile showed 24 health conditions for the UK, 27 for Brazil and 26 for Rwanda. Among the highest 10 health conditions for the UK, five also appeared in the Brazilian list but only one for Rwanda. On the other hand, among the 10 Brazilian health conditions, three were present in the Rwandan list ( Table 2 ).

DISCUSSION

This investigation used statistical data on morbidity and mortality collected by official government agencies to list and rank themes to be adopted by an undergraduate curriculum. This framework was proposed in order to manage educational taxonomic levels such as knowledge, skills and attitudes, for those in the highest quartile as well as to ensure knowledge for those in the lowest quartile.

An undergraduate curriculum should be based on and related to the needs of learners and society. 13 However, it is not an easy task to define what a need is. Needs have a social origin and they may correspond to habits that are gradually created and also legitimized by references to ideals. 14 Careful analysis could point out and identify needs for individuals, groups, institutions and societies. This investigation used statistical frequencies of registered health conditions as a way to identify conditions that might constitute such needs in medical education.

The taxonomy of objectives in education is a framework used to classify statements of what students are expected to learn. The domains of learning are considered to be related to cognitive, affective/attitude and psychomotor/skills. The revised Bloom taxonomy presents six major categories that differ in their complexity, such that the basic level “ remember ” is considered to be less complex than “ understand ”. From this point on, higher levels are supposed to be reached: apply, analyze, evaluate and create . 15 Many educators have proposed that the educational process should proceed from the lowest levels to the highest levels, and also that the main goal should be the highest levels. Although the taxonomy does not propose any priority regarding the three domains (cognition, skills and attitudes), it is useful for developing educational objectives. However, one difficulty educators may have is making decisions to identify objectives between adjacent categories. Educators ought to carefully reflect on their objectives. In this regard, the taxonomies are valuable tools for defining such objectives. 16

Table 1. List of conditions and scores derived from World Health Organization Disability-Adjusted Life Year (WHO DALY) database. Scores are divided by 10 5 order UK Score Brazil Score Rwanda Score 1 Ischaemic heart disease 4.456 Ischaemic heart disease 2.432 Lower respiratory infections 16.410 2 Cerebrovascular disease 2.415 Cerebrovascular disease 2.205 Diarrhoeal diseases 12.090 3 Chronic obstructive pulmonary disease 1.586 Violence 2.048 HIV/AIDS 11.711 4 Trachea, bronchus, lung cancers 1.504 Lower respiratory infections 1.729 Malaria 4.742 5 Alzheimer and other dementias 1.357 Road traffic accidents 1.219 Neonatal infections and other conditions 4.694 6 Lower respiratory infections 1.119 Diabetes mellitus 1.125 Maternal conditions 3.914 7 Colon and rectum cancers 867 Chronic obstructive pulmonary disease 1.087 Tuberculosis 3.852 8 Breast cancer 783 Diarrhoeal diseases 952 Birth asphyxia and birth trauma 3.790 9 Diabetes mellitus 524 Prematurity and low birth weight 700 Prematurity and low birth weight 2.796 10 Cirrhosis of the liver 498 Hypertensive heart disease 682 Protein-energy malnutrition 1.898 11 Prostate cancer 459 Other unintentional injuries 599 Road traffic accidents 1.825 12 Lymphomas, multiple myeloma 397 Cirrhosis of the liver 549 Cerebrovascular disease 1.755 13 Oesophagus cancer 374 Endocrine disorders 546 Violence 1.544 14 Self-inflicted injuries 363 Alcohol use disorders 516 Other unintentional injuries 1.396 15 Other unintentional injuries 336 HIV/AIDS 491 Ischaemic heart disease 1.272 16 Road traffic accidents 335 Neonatal infections and other conditions 488 Meningitis 1.267 17 Pancreas cancer 317 Inflammatory heart diseases 461 Congenital anomalies 1.128 18 Alcohol use disorders 317 Breast cancer 413 Drownings 822 19 Stomach cancer 290 Protein-energy malnutrition 412 Iron-deficiency anaemia 707 20 Endocrine disorders 277 Trachea, bronchus, lung cancers 383 Diabetes mellitus 666 21 Falls 265 Congenital anomalies 378 Endocrine disorders 581 22 Asthma 253 Stomach cancer 340 Asthma 546 23 Parkinson disease 244 Tuberculosis 319 Vitamin A deficiency 488 24 Leukaemia* 239 Prostate cancer 312 Chronic obstructive pulmonary disease 483 25 Bladder cancer 233 Nephritis and nephrosis 295 Nephritis and nephrosis 445 26 Congenital anomalies 229 Falls 283 Fires* 430 27 Ovary cancer 227 Asthma* 280 Liver cancer 421 28 Drug use disorders 211 Alzheimer and other dementias 270 Syphilis 396 29 Peptic ulcer disease 190 Maternal conditions 269 Epilepsy 391 30 Inflammatory heart diseases 170 Colon and rectum cancers 269 Self-inflicted injuries 386 31 Nephritis and nephrosis 167 Self-inflicted injuries 264 War 359 32 Prematurity and low birth weight 149 Birth asphyxia and birth trauma 250 Inflammatory heart diseases 310 33 Other neoplasms 146 Drownings 220 Schistosomiasis 307 34 Hypertensive heart disease 142 Chagas disease 203 Tetanus 306 35 Melanoma and other skin cancers 136 Cervix uteri cancer 188 Hypertensive heart disease 277 36 Rheumatoid arthritis 128 Lymphomas, multiple myeloma 186 Stomach cancer 247 37 Liver cancer 127 Leukaemia 183 Cervix uteri cancer 239 38 Mouth and oropharynx cancers 122 Iron-deficiency anaemia 163 Pertussis 223 39 Epilepsy 114 Mouth and oropharynx cancers 160 Iodine deficiency 206 40 Violence 105 Meningitis 145 Measles 203 41 Cervix uteri cancer 96 Epilepsy 140 Falls 193 42 Poisonings 94 Oesophagus cancer 128 Upper respiratory infections 192 43 Skin diseases 92 Skin diseases 105 Hepatitis B 160 44 Diarrhoeal diseases 90 Pancreas cancer 97 Cirrhosis of the liver 158 45 Multiple sclerosis 90 Peptic ulcer disease 85 Peptic ulcer disease 150 46 Corpus uteri cancer 90 Ovary cancer 79 Skin diseases 149 47 Rheumatic heart disease 59 Bladder cancer 76 Lymphomas, multiple myeloma 148 48 Unipolar depressive disorders 0.2 Liver cancer 68 Trypanosomiasis 133 49 Osteoarthritis 0.1 Rheumatic heart disease 67 Alzheimer and other dementias 110 50 Birth asphyxia and birth trauma 0.05 Parkinson disease 44 Oesophagus cancer 100 51 Iron-deficiency anaemia 0.05 Other neoplasms 44 Other neoplasms 94 52 Neonatal infections and other conditions 0.05 Melanoma and other skin cancers 41 Mouth and oropharynx cancers 78 53 Schizophrenia 0.04 Unipolar depressive disorders 0.1 Rheumatic heart disease 73 54 HIV/AIDS 0.03 Drug use disorders 0.1 Hepatitis C 72 55 Fires 0.03 Schizophrenia 0.1 Poisonings 71 56 Benign prostatic hypertrophy 0.03 Rheumatoid arthritis 0.1 Colon and rectum cancers 62 57 Tuberculosis 0.03 Benign prostatic hypertrophy 0.04 Breast cancer 61 58 Meningitis 0.03 Fires 0.04 Leukaemia 58 59 Macular degeneration and other 0.02 Osteoarthritis 0.04 Pancreas cancer 49 60 Maternal conditions 0.02 Malaria 0.04 Ovary cancer 49 61 Bipolar disorder 0.02 Hepatitis C 0.04 Bladder cancer 45 62 Drownings 0.02 Schistosomiasis 0.03 Prostate cancer 38 63 Appendicitis 0.01 Corpus uteri cancer 0.03 Melanoma and other skin cancers 37 64 Hepatitis C 0.01 Hepatitis B 0.02 Trachea, bronchus, lung cancers 35 65 Upper respiratory infections 0.01 Multiple sclerosis 0.02 Schizophrenia 0.1 66 Otitis media 0.01 Bipolar disorder 0.02 Alcohol use disorders 0.1 67 War 0.005 Leishmaniasis 0.02 Osteoarthritis 0.1 68 Hepatitis B 0.004 Macular degeneration and other 0.02 Unipolar depressive disorders 0.1 69 Glaucoma 0.003 Appendicitis 0.02 Otitis media 0.04 70 Pertussis 0.002 Otitis media 0.02 Leishmaniasis 0.04 71 Periodontal disease 0.001 Upper respiratory infections 0.01 Macular degeneration and other 0.03 72 Dengue 0.01 Rheumatoid arthritis 0.03 73 Syphilis 0.01 Benign prostatic hypertrophy 0.02 74 Poisonings 0.01 Parkinson disease 0.02 75 Leprosy 0.01 Appendicitis 0.02 76 Pertussis 0.01 Gonorrhoea 0.02 77 Tetanus 0.01 Ascariasis 0.01 78 Chlamydia 0.004 Bipolar disorder 0.01 79 Ascariasis 0.003 Multiple sclerosis 0.01 80 Glaucoma 0.002 Chlamydia 0.01 81 Iodine deficiency 0.002 Diphtheria 0.01 82 Periodontal disease 0.001 Post-traumatic stress disorder 0.01 83 Drug use disorders 0.01 84 Corpus uteri cancer 0.01 85 Dental caries 0.004 86 Leprosy 0.004 87 Periodontal disease 0.003 *Lower limit of highest quartile for the country’s score.

Table 2. List of 10 highest scores derived from World Health Organization Disability-Adjusted Life Year (WHO DALY) database UK Brazil Rwanda Order Ischaemic heart disease Ischaemic heart disease Lower respiratory infections 1 Cerebrovascular disease Cerebrovascular disease Diarrhoeal diseases 2 Chronic obstructive pulmonary disease Violence HIV/AIDS 3 Trachea, bronchus, lung cancers Lower respiratory infections Malaria 4 Alzheimer and other dementias Road traffic accidents Neonatal infections and other conditions 5 Lower respiratory infections Diabetes mellitus Maternal conditions 6 Colon and rectum cancers Chronic obstructive pulmonary disease Tuberculosis 7 Breast cancer Diarrhoeal diseases Birth asphyxia and birth trauma 8 Diabetes mellitus Prematurity and low birth weight Prematurity and low birth weight 9 Cirrhosis of the liver Hypertensive heart disease Protein-energy malnutrition 10 Underline: conditions present in both Brazil and Rwanda. Italics: conditions present in UK, Brazil and Rwanda.

In the medical educational field, there are curriculum proposals spanning from single themes to entire competencies. 10 , 17 , 18 Such discussions have also been reviewed from the point of view of whether to consider that healthcare providers should have an expanded role relating to entire communities or whether the tradition of one patient’s doctor should be maintained, with regard to arranging educational priorities. 19 However, discussion addressing the priorities for the composition of knowledge topics and skills in studying health-related issues seems to be new.

The method proposed in this study identified health conditions that could be used for construction of a medical curriculum, no matter what approach is chosen, i.e. involving either medical care providers or individual doctors, as well as in relation to any instructional design. These results established the morbidity and mortality data as reasonable sources of information for defining curriculum priorities.

Ranking of diseases according to their locally defined morbidity and mortality may suggest that some topics could be classified as presenting lower complexity in the educational taxonomy. However, this action does not eliminate the theme; rather, it instructs the learner that such knowledge could be worth remembering rather than studied up to the creative level, as would be the case for designing research proposals (higher educational taxonomic level). A recent survey of some medical schools in the United States found out that the curricula were compressed, with a large quantity of subjects, and there was no emphasis on any core competencies. 20 The present method developed here could direct the efforts of medical educators towards how to prioritize such subjects, since there would be information to feed their reflections on the objectives.

An initiative in the United States, Undergraduate Medical Education for the 21 st Century (UME-21), has sponsored curricular changes focusing on core primary care clinical clerkships and outpatient settings, with an emphasis on learning objectives and competencies that would supposedly be at the center of the future healthcare system. 21 However, the content was not taken into consideration. On the other hand, a recent study describing the process used for curriculum development stated that the disciplines chosen to run through the course were retrieved from associations of medical specialists. 22 The results presented in this work give prominence to an epidemiological database, ensure that educational expertise from medical societies remains relevant and have the capacity to reveal the reality of local conditions.

This study has some limitations. The score was constructed using a database made available from a WHO inventory (DALY), taken from compulsory notification of diseases. Given that the data originated from government officials and agencies, some diseases with high incidence that would be considered to be public health priorities, but with low lethality and low hospital admission rates, would not be totally represented by the proposed score if they were not in the morbidity database. Proper measurement would rely more on systematic sources derived from outpatient and primary care services. Such reports would capture the spontaneous needs for healthcare, in order to constitute the proposed score. The National Ambulatory Medical Care Surveys (NAMCS) and National Hospital Ambulatory Medical Care Surveys (NHAMCS) produce annual estimates of outpatient care in the United States that show these primary diagnoses. 23 The issue of why it would not simply be better to use prevalence to choose which diseases should be taught in undergraduate medical courses would imply accepting unreal equivalence between morbidity and mortality data. This proposed method respects both types of data, but does not emphasize either of them and allows the related database to point out their relative importance in time.

CONCLUSIONS

In conclusion, the registered health conditions, their statistical treatment and careful analysis made it possible to identify themes that may constitute needs in medical education that have to be mastered. They also suggested that there are limits between topics that should be considered in depth at higher levels of knowledge, skills and attitudes, among those that should be worked on at lower levels of taxonomic educational complexity.

Universidade Cidade de São Paulo (Unicid), São Paulo, Brazil

Sources of funding: None

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