19 Guset_Lecture_EPI_Podiatrics_Sessions 1-4_2022.pdf

Epidemiological Perspectives for Health Care Management and Descriptive Measurements Session 1. Overview Jun Dai, MD, MSc, PhD Professor Department of Public Health  Topics in the Lecture Session 1. Overview of epidemiology (EPI) and...

Epidemiological Perspectives for Health Care Management and Descriptive Measurements Session 1. Overview Jun Dai, MD, MSc, PhD Professor Department of Public Health  Topics in the Lecture Session 1. Overview of epidemiology (EPI) and health care management Session 2. Measures in Epidemiology and Frequency Measures Session 3. Descriptive Epidemiology and Applications of Frequency Measures Session 4. Observational Epidemiology Studies, 2 by 2 Tables, and Measures of Associations Last JM, editor. Dictionary of epidemiology. 4th ed. New York: Oxford University Press; 2001.  WHAT IS EPIDEMIOLOGY? Epidemiology is the study of the distribution and determinants of health‐ related states or events in specified populations, and the application of this study to the control of health problems. Last JM, editor. Dictionary of epidemiology. 4th ed. New York: Oxford University Press; 2001.  WHAT IS EPIDEMIOLOGY? Epidemiology is the study of patterns of disease in human populations: who has disease, how much disease they have, and why they have it. The primary goal of epidemiology is to identify causes of disease and injury and explore ways to control and prevent them. (Adapted from: Epidemiology for Journalists. by Dr. Daniel Wartenberg) Epidemiology and Health Care Management Can epidemiologic approaches be used to manage health care organizations more effectively at an operational level? ‐‐‐Yes. Epidemiology provides evidence‐based, effective management. The approaches are based on well‐tested methods of investigating health problems: well‐established information systems for surveillance of outcomes rigorous processes of data inference continuous reassessment of knowledge. Epidemiology and Health Care Management – Health care management needs research or information on the effectiveness of health care organization and finance, patterns of service use, quality of care, health outcomes, and costs of care – Health care service can be made to be responsive to the prevailing population conditions, such as birth rate, fertility, diseases and deaths from certain conditions, increases in the minority and elderly subgroups, and the infection control. – Aim to apply epidemiological methods to the improvement of the health status  Marshalltown Hospital to Close It Birthing Unit ‐ News in 2019 from “Des Moines Register” https://www.desmoinesregister.com/story/news/health/2019/08/05/marshalltowns‐ hospital‐close‐birthing‐center‐33rd‐since‐2000/1924525001/ Epidemiological Perspectives for Health Care Management and Descriptive Measurements Session 2. Measures in Epidemiology and Frequency Measures Jun Dai, MD, MSc, PhD Professor Department of Public Health  Measures in Epidemiology Count: e.g. the number of newborn babies Frequency measures: (numerator/denominator) x 10n – Ratio: a number that is obtained by dividing one number by another. The numerator can be unrelated to the denominator. Odds ratio (OR) Risk ratio (relative risk) (RR) – Proportion: A type of ratios that relates a part to a whole. Prevalence (prevalence rate) – Rate: A type of ratios in which the denominator also takes into account another dimension, usually time. Incidence rate Morbidity Mortality: e.g., cardiovascular disease mortality rate Birth rate https://sphweb.bumc.bu.edu/otlt/mph‐ modules/ep/ep713_diseasefrequency/ep713_diseasefrequency_print.html https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section1.html  Prevalence The frequency of existing cases in a designated population at some designated time. Provide an indication of the extent of a health problem Provide an implication for the scope of health services needed in the community Need to define a designated population Need to define a designated time Numerator: number of existing cases for the designated time, including pre‐existing and new cases Denominator: unit size of the designated population at the designated time period.  Prevalence Calculation 6,265 people had a heart attack in county T in year of 2008. The population in county T was 100,000 as of July 1, 2008. What is the prevalence of heart attack in county T in 2008? Prevalence = ?/? =?  Prevalence Calculation 6,265 people had a heart attack in county T in year of 2008. The population in county T was 100,000 as of July 1, 2008. What is the prevalence of heart attack in county T in 2008? Prevalence = (6,265/100,000) x 102 = 6.3% The prevalence of heart attack in county T in 2008 is 6.3%.  Prevalence of Coronary Heart Disease (CHD) in the U.S., 2006 ‐ 2010 http://www.aacc.org/publications/cln/2011/December/Pages/CHDPrevalence.aspx#  Incidence Rate (Cumulative Incidence) The rate of development of a disease in a group over a certain time period. Need to define a time period Numerator: number of NEW cases over a specified time period Denominator: population at risk during the same time period  Incidence Rate (Cumulative Incidence) Incidence rate = (Number of new cases/total population size at risk) x 10n  Scenario: The British Regional Heart Study studied first myocardial infarction (MI) incidence over 25 years from 1978 in a cohort of 7,735 men aged 40 to 59 years when recruited. During the first 5 year of follow‐up, there were 240 new cases who died from first MI. Questions: 1. What is the incidence rate of the first MI over the first 5 years of follow‐up in this population expressed in per 1,000 population? 2. What is the incidence rate annually over the first 5 years of follow‐up ? Adapted from Hardoon et al, Circulation 2008  British Regional Heart Study Group Activity (You can discuss with your classmates anytime) What is the specified time period? What is the population at risk? What is the size of the population at risk? What is the number of new cases over the specific time period?  Applications of Incidence Data Help in research on the etiology/causality of disease. Used to estimate – the risk of developing a disease. – the effects of exposure to a hypothesized factor of interest. Interrelationship Between Prevalence and Incidence Interrelationship Between Prevalence and Incidence (cont’d) If duration of disease is short and incidence is high, prevalence becomes similar to incidence. Short duration‐‐cases recover rapidly or are fatal. Example: common cold Interrelationship Between Prevalence and Incidence (cont’d) If duration of disease is long and incidence is low, prevalence increases greatly relative to incidence. Example: many chronic diseases  Crude versus Adjusted Rate Crude rate: actual number of cases/events in a population over a given time period. – they do not permit comparison of populations that vary in composition Adjusted rate: a rate after controlling for differences in the distribution of a factor in a population. – e.g. age‐adjusted rate  Figure 1. Crude and age‐adjusted death rates: United States, 1960‐2005 1,400 Rate per 100,000 population 1,200 Age‐adjusted 1,000 Crude 800 600 0 1960 1970 1980 1990 2000 2005 NOTE: Crude death rates on an annual basis per 100,000 population; age‐adjusted rates per 100,000 U.S. standard population; see “Technical Notes.”  Specific Rate – Cause‐specific mortality rate. e.g., CHD mortality rate, breast cancer rate – Other: e.g., infant mortality rate  Summary – Session 2 Crude rate – Prevalence – Incidence rate Adjusted rate – Age‐adjusted rate Epidemiological Perspectives for Health Care Management and Descriptive Measurements Session 3. Descriptive Epidemiology and Application of Frequency Measures Jun Dai, MD, MSc, PhD Professor Department of Public Health  Descriptive and Analytic Epidemiology Descriptive epidemiology is the first stage of epidemiologic investigation. It focuses on describing disease distribution relating to time, place, and person. Analytic epidemiology is the second stage in an epidemiologic study, in which hypotheses generated in the descriptive phase are tested. http://medical‐dictionary.thefreedictionary.com/descriptive+epidemiology  Descriptive Epidemiological Measures in Health Care Management Descriptive measures, namely proportions, rates, and ratios, useful in planning and evaluating health care services, policies, and programs. The specific type of epidemiological measure used depends on the objective of the assessment, the nature of the health problem being evaluated, and the type of data available. Oleske D.M. (2002) Descriptive Epidemiological Measures. In: Oleske D.M. (eds) Epidemiology and the Delivery of Health Care Services. Springer, Boston, MA  Descriptive and Analytic Epidemiology Descriptive epidemiology provides information on what, who, when, where, how many, and generates hypothesis – What (case definition) – Who /Whom (person) – When (Time) – Where (Place) – How big/many (measures of severity of problem) Application: Patterns of Disease  Descriptive and Analytic Epidemiology Analytical epidemiology attempts to provide the information about why and how, and tests the hypothesis. The key feature of analytic epidemiology is a comparison group. – Why (Causes) – How (Causes)  Descriptive Epidemiology Objective: – Evaluation of trends in health and disease and comparisons among countries and subgroups within countries; monitoring of known diseases and the identification of emerging problems  Descriptive Epidemiology Objective: – Providing information for planning, provision, and evaluation of health services – Generating hypotheses to be studied by analytic methods and to suggest areas that may be fruitful for investigation.  Descriptive Epidemiology Who (Person) – Age – Gender (sex) – Race & Ethnicity – Socioeconomic Status – Marital Status – Migration – Religion – …. …. Annual rate of first heart attacks by age, sex, and race (Atherosclerosis Risk in Communities Surveillance: 1987–2004) Circulation 2012;125:e2-e220 Copyright © American Heart Association  Socioeconomic Status Figure 2. Prevalence of hypertension by age and income, New Jersey adults, 2005 www.nj.gov/health/chs/monthlyfactsheets/hypertension06.pdf accessed Aug 2016  Descriptive Epidemiology When (Time) – Outbreak time, most popular births month – Secular time trends Secular Trend of Ventilator‐Associated Pneumonia (VAP) and Implementing healthcare bundles Ding et al. Chest. 2013;144(5):1461‐8.  Descriptive Epidemiology Where (Place) – Geographic variations Within‐country Between‐country (International) Urban/rural differences – Localized occurrence of disease  US maps corresponding to state death rates from CHD (including the District of Columbia). IA Circulation 2012;125:e2-e220 Copyright © American Heart Association  Summary‐ Session 3 Concept – Epidemiology Descriptive epidemiology Analytic epidemiology – Component of descriptive epidemiology 4 W s and how What the case is, Who are at the high risk for a health‐ related event, When, Where, and How the events occur.  Epidemiological Perspectives for Health Care Management and Descriptive Measurements Session 4. Observational Epidemiology Studies, 2 by 2 Tables, and Measures of Associations Jun Dai, MD, MSc, PhD Professor Department of Public Health  Common Observational Epidemiological Studies Observational: to observe the exposure and disease status of each study participant – Cross‐sectional study: to sample persons from a population and then to measure exposures and health outcomes simultaneously. can assess the prevalence of the health outcome at that point of time without regard to the disease duration can be used for descriptive epidemiology  Common Observational Epidemiological Studies ‐ Case‐control study: to sample a group of people with disease (case group) and a group of people without disease (control groups). disease status of each study participant is known aim to investigate the exposure by collecting data on the exposure It is a retrospective study. ‐ Cohort study: to records whether each study participant is exposed or not, and then tracks the participants to see if they develop the disease of interest. It is prospective.  The 2 X 2 Table —The Epidemiologists’ Dream Tool!! Condition/Disease Condition/Disease Present Absent Exposure Present or b a Screening Test Positive Exposure Absent or c d Screening Test Negative N = a + b + c +d  Effect Measure for Case‐Control Studies Odds Ratio Outcome Cases Controls Exposure (Yes) (No) Exposed (Yes) A B Not Exposed (No) C D Odds of exposure for cases A/C A *D = = =Odds Ratio (OR) Odds of exposure for controls B/D B *C 45  Association between osteoprotegerin G1181C and T245G polymorphisms and diabetic Charcot neuroarthropathy: a case‐control study What is the outcome of this study? What is exposure in this study? Adapted from Pitocco et al. Diabetes Care, 2009. doi: 10.2337/dc09‐0243.  Association between osteoprotegerin G1181C and T245G polymorphisms and diabetic Charcot neuroarthropathy: a case‐control study Abstract –Research Design: We performed a case‐control study with 59 subjects with diabetic Charcot neuroarthropathy (Ch group), 41 with diabetic neuropathy without Charcot neuroarthropathy (ND group), and 103 healthy control subjects (H group) to evaluate the impact of two single nucleotide polymorphisms (SNPs) of the osteoprotegerin gene (G1181C and T245G) on the risk of Charcot neuroarthropathy. Adapted from Pitocco et al. Diabetes Care, 2009. doi: 10.2337/dc09‐0243.  Association between osteoprotegerin G1181C and T245G polymorphisms and diabetic Charcot neuroarthropathy: a case‐control study What is the outcome in this study? Answer: diabetic Charcot neuroarthropathy What is exposure in this study? Answer: 1. G1181C polymorphisms 2. T245G polymorphisms Adapted from Pitocco et al. Diabetes Care, 2009. doi: 10.2337/dc09‐0243.  Table. Frequencies of G1181C and T245G genotypes ND group Ch group H group G1181C CC 15 (36.5) 6 (10.1) 34 (33) GC 19 (46.3) 34 (57.6) 50 (48.5) GG 7 (17.2) 19 (32.3) 19 (18.5) T245G GG 0 (0) 7 (11.9) 2 (1.9) GT 4 (9.75) 16 (27.1) 14 (13.6) TT 37 (90.25) 36 (61) 87 (84.5) Adopted from Pitocco et al. Diabetes Care, 2009. doi: 10.2337/dc09‐0243.  Gene G1181C and Charcot Neuroarthropathy (CN) A Case‐Control Study in the Publication CN G allele Exposure= G1181C – Diabetic Case Healthy Controls in Ch group In H group (Yes) (No) Yes (GG) 19 19 No (GC+CC) 6+34=40 34+50=84 Odds of exposure for cases A/C A*D 19 *84 OR= = = = = 2.10 Odds of exposure for controls B / D B*C 19 *40 Adapted from Pitocco et al. Diabetes Care, 2009. doi: 10.2337/dc09‐0243.  Interpretation of an Odds Ratio (OR) OR = 1 implies no association. Assuming statistical significance: – OR1 suggests the exposure as a risk factor. Interpretation: – Cases were OR times as likely as controls to be exposed to the exposure. – Those with the disease are OR times as likely to have had the exposure as those without the disease. NOTE: Need to specify the disease and the exposure Need to specify “those”  Interpretation of an Odds Ratio (OR) Interpretation: –Patients with diabetic Charcot neuroarthropathy were 2.10 times as likely as healthy controls to have the GG genotype at gene G1181C. –Those with the diabetic Charcot neuroarthropathy are 2.10 times as likely to have the GG genotype at gene G1181C as the healthy controls.  Quiz Study: Associations between mask‐wearing all the time during contact of asymptomatic cases and risk of COVID‐ 19 infection in public: a case‐control study in Thailand Design: Cases were asymptomatic contacts of COVID‐19 patients identified between 1 and 31 March 2020 who were diagnosed with COVID‐19 by 21 April 2020; controls were asymptomatic contacts who were not diagnosed with COVID‐19. Mask‐wearing all the time during contact was compared with not wearing masks Doung‐ngern et al. https://www.medrxiv.org/content/10.1101/2020.06.11.20128900v4  Quiz Study: Associations between mask‐wearing all the time during contact of asymptomatic cases compared with not wearing masks and risk of COVID‐19 infection in public: a case‐control study in Thailand Results: OR = 0.16 How to interpret this OR? Doung‐ngern et al. https://www.medrxiv.org/content/10.1101/2020.06.11.20128900v4  Free online calculator for odds ratio (OR) https://select‐ statistics.co.uk/calculators/confidence‐interval‐ calculator‐odds‐ratio/ Use the 2 by 2 table Can estimate OR and its confidence interval (CI)  Cohort Studies: Measures of Association Relative risk provides a direct measure of association between exposure and outcome. Relative risk is the ratio of the incidence of disease in the exposed group to the incidence in the non‐exposed group.  Relative Risk (RR) Relative risk = Incidence rate in the exposed Incidence rate in the non‐exposed  Effect Measure for Cohort Studies Relative Risk Disease Status Incidence Exposure Yes No Totals Rate Status Yes A B A+B A/(A+B) No C D C+D C/(C+D) Relative Risk = [A/(A+B)]/[C/(C+D)] = [A*(C+D)]/[C*(A+B)]  Peripheral Arterial Disease (PAD) and Charcot Neuroarthropathy (CN) in Diabetic Patients A Hypothetical Cohort Study Disease Status CN Incidence Yes No Totals Rate Yes 34 73 107 A/(A+B)=34/107 PAD No 51 53 106 C/(C+D)=51/106 Relative Risk = [A/A+B]/[C/C+D]=[34/107]/[51/106] =(34*106/51*107) =0.66  Interpretation of Relative Risk (RR) RR = 1: No Association RR>1 exposure is a risk factor for the outcome RR0.05). If OR/RR is less than 1 and the 95% CI does not include 1, exposure is statistically significantly associated with the reduced risk for the outcome at a significant level of 0.05 (i.e., p