Consumer Cost-Sharing in Primary Care: Unintended Health and Economic Outcomes

在许多国家，即使是参保的个人也必须支付费用(通常是患者分担费用)才能看他们的家庭医生。这项收费的理论目的之一是控制成本：限制过度就诊，尽管它也可以在为医疗体系提供资金方面发挥作用。这类费用的一个意想不到的后果是，它们可能会阻止个人在必要的医疗条件下去看家庭医生。因此，个人的健康可能会恶化，未来他们可能需要更昂贵的医疗治疗(例如住院治疗)，这将违背费用本应达到的控制成本的目的。随着非传染性疾病(NCDs)的迅速增加，这一意外后果的重要性可能会增加，这些疾病需要通过初级保健服务及时诊断和管理。对于许多非传染性疾病来说，推迟就诊比较容易，因为它们在发病初期并不痛苦(例如糖尿病)，但如果不及时诊断和适当处理，将导致未来更昂贵的医疗程序。去看家庭医生可能有助于及时诊断病情，并对这种病情保持适当的管理。因此，病人费用可能倾向于使用医院而不是初级保健服务，这是效率低下的，因为医院服务要昂贵得多。这种低效率削弱了卫生系统，并限制了卫生系统在其他方面(覆盖范围、质量改进)的改善程度。尽管文献对这一主题感兴趣，但大多数先前的研究报告了关联，这可能是虚假的。最近的一些论文能够估计患者费用对健康的影响，但它们无法评估医疗保健使用模式或总体治疗成本的变化。这些都是了解病人费用如何影响卫生系统(初级和二级保健资源分配)及其效率的关键问题。为了促进这场辩论，我们将测试初级保健费用的增加是否(以及增加了多少)在短期和长期(长达7年)内增加了未诊断的慢性疾病、不利的健康结果、死亡率、医院服务的使用和治疗成本。为了进行这项工作，我们将使用2011至2018年的卫生管理数据，覆盖97%的哥伦比亚人口，并包含哥伦比亚卫生系统提供的所有卫生保健服务的患者记录，包括使用的服务日期和类型(门诊、医院等)、处方、治疗费用、ICD-10、个人的社会人口学特征(包括收入或财富得分)和死亡率。个人识别符在七年中保持一致，提供了一个独特的丰富和详细的纵向管理数据库。此外，它的巨大规模使我们能够估计利息对特定兴趣亚群的影响(例如，社会经济地位较差的个人，或慢性病患者)。然而，数据不足以为兴趣问题提供强有力的答案。我们还需要一种方法来确保我们不会报告数据中的虚假关联。实验通常用于这一目的，但它们不太可能为我们提供长期影响，因为我们将估计这些影响，而且样本也不够大。我们足够幸运的是，哥伦比亚的患者费用分担制度起到了“突然跳跃”的作用，也就是说，费用分担在一些连续变量的预先指定的阈值下突然跳跃。这是应用一种名为回归不连续(RD)的准实验方法的理想环境，众所周知，该方法在非常弱的假设下提供没有虚假相关性的因果估计。请注意，你不能随时随地使用RD，条件必须存在，但我们幸运的是，哥伦比亚确实存在这种情况。

In many countries, even insured individuals must pay a fee (usually patient cost-sharing) to see their family doctor. The theoretical purpose of that fee is one of cost-containment: to limit the overuse of doctor visits, although it can also play a role in the funding the health system.An unintended consequence of such fees is that they might prevent individuals from visiting their family doctor for necessary medical conditions. Hence, individuals' health might deteriorate, and in the future they might need much more expensive medical treatments (e.g. hospitalizations), which would defeat the cost containment purpose that the fee was supposed to serve. The importance of this unintended consequence might be growing with the rapid increase in Non-Communicable Diseases (NCDs), which require timely diagnosis and management through primary care services. For many NCDs, it is easier to postpone doctor visits because they are not painful in their initial stages (e.g. diabetes), but if they are not diagnosed timely and appropriately managed, they will lead to more expensive medical procedures in the future. Visiting the family doctor might help to diagnose the conditions timely, as well as to keep an adequate management of such conditions.Hence, patient fees might be favoring use of hospitals instead of primary care services, which is inefficient because hospital services are much costlier. This inefficiency weakens the health system and limits how much the health system can improve in other dimensions (coverage, quality improvement).Although the literature has been interested in this topic, most previous research has reported associations, which might be spurious. Some recent papers have been able to estimate the effect of patient fees on health, but they have not been able to assess how health care use patterns or overall treatment costs change. These are key issues to understand how patient fees affect the health system (split of resources between primary and secondary care), and its efficiency. To contribute to this debate, we will be testing whether (and by how much) increased patient fees in primary care increase undiagnosed chronic conditions, adverse health outcomes, mortality, use of hospital services, and treatment costs both in the short and long term (up to 7 years).To conduct this work, we will be using health administrative data for the years 2011 to 2018, covering 97% of the Colombian population and containing patients records of all health care services provided in the Colombian Health System, including date and type of service used (outpatient, hospital, etc), prescriptions, treatment costs, ICD-10, sociodemographic characteristics of individuals (including income or wealth scores) and mortality. The person identifier is consistent across the seven years, providing a uniquely rich and detailed longitudinal administrative database. Moreover, its huge size allows us to estimate the effects of interest for particular subpopulations of interest (e.g. individuals with poor socio-economic status, or chronic patients).However, data is not enough to provide a robust answer to the question of interest. We also need a method to be sure that we will not be reporting spurious associations in the data. Experiments are usually used for that purpose but they are unlikely to provide us with long term effects as the ones that we will be estimating, nor the samples be large enough.We are fortunate enough that the patient cost-sharing system in Colombia works "in abrupt jumps," that is, cost-sharing jumps abruptly at pre-specified thresholds of some continuous variables. This is the ideal setting to apply a quasi-experimental method called Regression Discontinuity (RD), which is known to provide causal estimates, free of spurious correlations, under very weak assumptions. Note that you cannot use RD whenever you want, the conditions must be there, but we are fortunate that they do hold in Colombia.