Absolute and derived values

Use of absolute and derived values in assessing Population health and the activities of healthcare Submitted by Riya Patil & Rutuja Sonar, to Moldoev Murzali Ilyazovich Osh state University ABSTRACT In contrast, derived values involve the use of statistical techniques to calculate indirect indicators from absolute values. These include metrics like disability-adjusted life years (DALYs), quality-adjusted life years (QALYs), and health-adjusted life expectancy (HALE). Derived values are instrumental in understanding the broader context of population health, as they often combine both mortality and morbidity data to reflect the overall burden of disease. In healthcare institutions, these values are integral in guiding resource allocation, evaluating the effectiveness of interventions, and shaping policies aimed at improving health outcomes. While absolute values provide essential raw data, derived values offer nuanced insights into the quality and long-term impact of healthcare services. Together, they form a comprehensive approach to measuring and improving population health, helping healthcare institutions prioritize actions and allocate resources more effectively. This paper explores the role of absolute and derived values in assessing population health and their relevance to healthcare institutions, examining how both types of values support decision-making and influence health policy. Keywords: Population health, absolute values, derived values, healthcare institutions, mortality rates, morbidity, Disability-Adjusted Life Years (DALYs), Quality-Adjusted Life Years (QALYs), Health-Adjusted Life Expectancy (HALE), health policy, healthcare interventions. INTRODUCTION Use of Absolute and Derived Values in Assessing Population Health and the Activities of Healthcare Institutions** Population health is a key focus of public health systems and healthcare institutions worldwide. Assessing the health of a population requires robust metrics to understand the current state of health, identify risks, and track trends over time. One of the essential tools in evaluating population health is the use of **absolute values** and **derived values**. These metrics offer complementary insights into both the health status of individuals within a population and the effectiveness of healthcare interventions. **Absolute values** are straightforward measures that provide direct data points, such as the total number of people suffering from a specific disease, the number of hospital admissions, or the total expenditure on healthcare services. These values are critical for understanding the scale of health issues and resource needs within a community. **Derived values**, on the other hand, are ratios or indices calculated from absolute values. They allow for more meaningful comparisons across populations, time periods, or geographical areas. Examples include rates such as morbidity or mortality rates, life expectancy, and disease prevalence, which are essential for assessing public health outcomes and guiding healthcare policy and decision-making. By integrating both absolute and derived values, healthcare institutions can gain a comprehensive picture of population health, identify areas for improvement, allocate resources more efficiently, and track the effectiveness of healthcare initiatives. This approach helps ensure that healthcare systems are responsive to the needs of the population and can adapt to emerging health challenges. METHODOLOGY Method and analysis which is performed by the google worksheet and google forms Absolute Values in Assessing Population Health: Absolute values refer to raw, unadjusted data points that provide a direct measure of a population's health status. These values are fundamental for initial assessments, as they provide baseline data for various health indicators. Definition and Examples Absolute values refer to concrete figures that represent the total counts or occurrences of specific health events or conditions. For example: Total Mortality Rate: The number of deaths in a population over a specific time period (e.g., deaths per 100,000 people). Prevalence Rates: The proportion of individuals in a population diagnosed with a specific condition at a particular time (e.g., diabetes prevalence). Incidence Rates: The number of new or newly diagnosed cases of a disease over a given period (e.g., cancer incidence). Life Expectancy: The average number of years a person is expected to live based on current mortality rates. Use in Population Health Health Monitoring: Absolute values allow public health authorities to monitor trends in population health, such as increases in mortality or the spread of disease. Resource Allocation: These values help in determining the burden of disease in different populations, aiding in the efficient distribution of healthcare resources. Derived Values in Assessing Population Health Derived values involve the use of mathematical formulas or statistical techniques to adjust or combine absolute values to create composite indices or ratios that provide deeper insights into health outcomes and healthcare activities. Definition Derived values are statistical measures that offer context to absolute by relating them to population characteristics. Common examples include: Age-Standardized Mortality Rate: Adjusts the mortality rate for differences in the age structure of different populations, allowing comparisons between populations with different age distributions. Disability-Adjusted Life Years (DALY): A composite measure that combines years of life lost due to premature death and years lived with disability. DALY provides a more comprehensive understanding of the burden of disease. Quality-Adjusted Life Years (QALY): A measure used to evaluate the effectiveness of healthcare interventions by combining quantity and quality of life. Health Inequality Index: Derived by comparing health disparities between different subgroups within a population. Use in Population Health Risk Assessment: Derived values like DALYs or QALYs enable healthcare providers and policymakers to assess the relative impact of different diseases or health conditions on the population’s overall health. Health Outcomes Comparison: Derived values facilitate comparisons across different populations or regions, adjusting for factors like age, gender, or socioeconomic status. Policy and Program Evaluation: Derived values are used to evaluate the effectiveness of public health interventions or healthcare programs, such as whether a vaccination program reduces disease burden over time. Significance Contextualizing Health Trends: Absolute values alone may not offer a clear picture. For instance, while an increase in the number of cancer cases might be alarming, derived values like the cancer incidence rate allow us to understand if the increase is due to an actual rise in cases or simply a result of population growth. Comparative Analysis: Derived values are essential when comparing different populations or regions. For example, comparing the infant mortality rate in different countries provides insights into healthcare system performance, whereas absolute numbers may mislead without considering population size differences. Evaluating Healthcare Efficiency: Derived values such as cost-effectiveness or patient outcomes per healthcare dollar provide insights into the efficiency of healthcare institutions. This helps identify areas of improvement in resource allocation and delivery of services. Policy and Planning: Derived values play a crucial role in informing public health policies and healthcare strategies. For example, the quality-adjusted life year (QALY), derived from health outcome measures, is commonly used in health economics to assess the effectiveness of medical treatments and interventions. Conclusion Both absolute and derived values are integral to assessing population health and healthcare institution activities. Absolute values provide raw data, while derived values allow for deeper analysis, trends, and comparisons, giving a more comprehensive picture of health outcomes and healthcare performance. REFERENCE 1.Kindig D, Stoddart G (March 2003). "What is population health?". American Journal of Public Health. 93 (3): 380–3. doi:10.2105/ajph.93.3.380. PMC 1447747. PMID 12604476. 2. McGinnis JM, Williams-Russo P, Knickman JR (2002). "The case for more active policy attention to health promotion". Health Aff (Millwood). 21 (2): 78–93. doi:10.1377/hlthaff.21.2.78. PMID 11900188.. See also National Academies Press free publication: The Future of Public Health in the 21st Century. 3. World Health Organization. 2006. Constitution of the World Health Organization – Basic Documents, Forty-fifth edition, Supplement, October 2006. 4. Jeffery RW. 2001. Public health strategies for obesity treatment and prevention. American Journal of Health Behavior 25:252–259. 5. Buunk BP, Verhoeven K. 1991. Companionship and support at work: a microanalysis of the stress-reducing features of social interactions. Basic and Applied Social Psychology 12:243–258. 6. CDC. 2001. a. CDC FactBook 2000/2001: Profile of the Nation's Health. Atlanta, GA: CDC. 7. What is the WHO definition of health? from the Preamble to the Constitution of WHO as adopted by the International Health Conference, New York, 19 June – 22 July 1946; signed on 22 July 1946 by the representatives of 61 States (Official Records of WHO, no. 2, p. 100) and entered into force on 7 April 1948. The definition has not been amended since 1948. 8. Perdiguero E (1 July 2001). "Anthropology in public health. Bridging differences in culture and society". Jou rnal of Epidemiology & Community Health. 55 (7): 528b–528. doi:10.1136/jech.55.7.528b. ISSN 0143-005X.# 人口健康评估与医疗保健机构运作中绝对数值与派生数值的应用 由里亚·帕蒂尔（Riya Patil）与鲁图贾·索纳尔（Rutuja Sonar）提交至穆尔多耶夫·穆扎利·伊利亚佐维奇奥什国立大学 ## 摘要 与之相对，派生数值指通过统计方法从绝对数值中推导间接指标的做法，涵盖伤残调整寿命年（disability-adjusted life years, DALYs）、质量调整寿命年（quality-adjusted life years, QALYs）与健康调整预期寿命（health-adjusted life expectancy, HALE）等指标。派生数值有助于理解人口健康的整体语境，因其通常结合死亡数据与发病数据，以反映疾病的整体负担。 在医疗保健机构中，这两类数值均为指导资源分配、评估干预措施有效性以及制定旨在改善健康结局的政策的核心依据。绝对数值可提供必要的原始数据，而派生数值则能为医疗服务的质量与长期影响提供精细化的洞察。二者结合可形成一套全面的人口健康测量与改善路径，助力医疗保健机构优化行动优先级并更高效地分配资源。 本论文探讨了绝对数值与派生数值在人口健康评估中的作用，以及二者与医疗保健机构的关联，分析了两类数值如何支撑决策制定并影响卫生政策。 ## 关键词：人口健康，绝对数值，派生数值，医疗保健机构，死亡率，发病情况，伤残调整寿命年（DALYs），质量调整寿命年（QALYs），健康调整预期寿命（HALE），卫生政策，医疗保健干预措施 ## 引言 ### 人口健康评估与医疗保健机构运作中绝对数值与派生数值的应用 人口健康是全球公共卫生体系与医疗保健机构的核心关注方向。评估人群健康状况需要可靠的指标，以掌握当前健康状态、识别风险因素并追踪长期趋势。评估人口健康的核心工具之一便是**绝对数值**与**派生数值**的应用，这两类指标可互为补充，为人群内个体的健康状态以及医疗保健干预措施的有效性提供洞察。 **绝对数值**是可直接提供数据点的简易测量指标，例如某一特定疾病的患者总人数、住院人次总数或医疗服务总支出。这类数值对于理解社区内健康问题的规模与资源需求至关重要。 **派生数值**则是从绝对数值中计算得出的比率或指数，可实现不同人群、时间段或地理区域间更具意义的比较。例如发病率、死亡率、预期寿命与疾病患病率等指标，均为评估公共卫生结局、指导医疗保健政策与决策制定的核心依据。 通过整合绝对数值与派生数值，医疗保健机构可全面掌握人口健康状况，明确待改进领域，更高效地分配资源，并追踪医疗保健举措的实施效果。该方法有助于确保医疗体系贴合人群需求，能够应对新发健康挑战。 ## 研究方法 本研究采用谷歌表格（Google Worksheet）与谷歌表单（Google Forms）开展方法学研究与数据分析。 ### 人口健康评估中的绝对数值 绝对数值指可直接反映人群健康状态的原始、未调整数据点。这类数值是初始评估的基础，可为各类健康指标提供基线数据。 #### 定义与示例 绝对数值指代表特定健康事件或状况总计数或发生次数的具体数据。示例如下： - 总死亡率：特定时间段内某人群的死亡人数（例如每10万人中的死亡数） - 患病率：某一特定时间点人群中被诊断患有某一特定疾病的个体比例（例如糖尿病患病率） - 发病率：特定时间段内某疾病的新增或新诊断病例数（例如癌症发病率） - 预期寿命：基于当前死亡率计算的个体预期平均剩余寿命 #### 在人口健康评估中的应用 - 健康监测：绝对数值可帮助公共卫生部门监测人口健康趋势，例如死亡率上升或疾病传播情况。 - 资源分配：这类数值可用于明确不同人群的疾病负担，助力医疗资源的高效配置。 ### 人口健康评估中的派生数值 派生数值指通过数学公式或统计方法对绝对数值进行调整或整合，以构建复合指数或比率，从而更深入地洞察健康结局与医疗保健活动。 #### 定义 派生数值是将绝对数值与人群特征相结合，为其赋予语境的统计指标。常见示例包括： - 年龄标准化死亡率（Age-Standardized Mortality Rate）：针对不同人群的年龄结构差异对死亡率进行调整，以便在年龄分布不同的人群间进行比较 - 伤残调整寿命年（disability-adjusted life years, DALYs）：整合因过早死亡损失的寿命与伤残生存年限的复合指标，可更全面地反映疾病负担 - 质量调整寿命年（quality-adjusted life years, QALYs）：通过结合生命数量与生命质量，用于评估医疗保健干预措施有效性的指标 - 健康不平等指数：通过比较人群内不同亚组间的健康差异推导得出的指标 #### 在人口健康评估中的应用 - 风险评估：伤残调整寿命年（DALYs）与质量调整寿命年（QALYs）等派生数值可帮助医疗服务提供者与政策制定者评估不同疾病或健康状况对人群整体健康的相对影响。 - 健康结局比较：派生数值可在调整年龄、性别或社会经济地位等因素后，实现不同人群或地区间的健康结局比较。 - 政策与项目评估：派生数值可用于评估公共卫生干预措施或医疗保健项目的有效性，例如疫苗接种项目是否可随时间推移降低疾病负担。 #### 应用意义 - 健康趋势语境化：仅依靠绝对数值往往无法清晰呈现健康趋势。例如，癌症病例数增加或许令人警觉，但通过癌症发病率这类派生数值，我们可判断该增长是源于实际病例数上升，还是仅由人口增长所致。 - 比较分析：在比较不同人群或地区的健康状况时，派生数值是必不可少的工具。例如，比较不同国家的婴儿死亡率可反映医疗体系的运行效能，而若不考虑人口规模差异，绝对人数可能会误导判断。 - 医疗效率评估：成本效益比、每医疗美元投入对应的患者结局等派生数值，可帮助洞察医疗保健机构的运行效率，有助于明确资源分配与服务交付领域的改进方向。 - 政策制定与规划：派生数值可为公共卫生政策与医疗保健策略制定提供关键依据。例如，从健康结局指标中推导得出的质量调整寿命年（QALYs），常被应用于卫生经济学领域，以评估医疗治疗与干预措施的有效性。 ## 结论 绝对数值与派生数值均为人口健康评估与医疗保健机构运作评估的核心组成部分。绝对数值可提供原始数据，而派生数值则支持更深入的分析、趋势研判与比较研究，从而更全面地呈现健康结局与医疗服务绩效。 ## 参考文献 1. Kindig D, Stoddart G (2003年3月). "What is population health?". *American Journal of Public Health*, 93(3): 380–383. DOI:10.2105/ajph.93.3.380. PMC 1447747. PMID 12604476. 2. McGinnis JM, Williams-Russo P, Knickman JR (2002). "The case for more active policy attention to health promotion". *Health Aff (Millwood)*, 21(2):78–93. DOI:10.1377/hlthaff.21.2.78. PMID 11900188. 另可参考美国国家科学院出版社免费出版物：《The Future of Public Health in the 21st Century》。 3. World Health Organization. 2006. *Constitution of the World Health Organization – Basic Documents*, Forty-fifth edition, Supplement, October 2006. 4. Jeffery RW. 2001. Public health strategies for obesity treatment and prevention. *American Journal of Health Behavior*, 25:252–259. 5. Buunk BP, Verhoeven K. 1991. Companionship and support at work: a microanalysis of the stress-reducing features of social interactions. *Basic and Applied Social Psychology*, 12:243–258. 6. CDC. 2001. a. CDC FactBook 2000/2001: Profile of the Nation's Health. Atlanta, GA: CDC. 7. What is the WHO definition of health? from the Preamble to the Constitution of WHO as adopted by the International Health Conference, New York, 19 June – 22 July 1946; signed on 22 July 1946 by the representatives of 61 States (Official Records of WHO, no. 2, p. 100) and entered into force on 7 April 1948. The definition has not been amended since 1948. 8. Perdiguero E (2001年7月1日). "Anthropology in public health. Bridging differences in culture and society". *Journal of Epidemiology & Community Health*, 55(7):528b–528. DOI:10.1136/jech.55.7.528b. ISSN 0143-005X.