What is the effect of Long-Term Care (LTC) benefits on healthcare use?

Helena Hernández-Pizarro ’12 is part of a research team that uses administrative data to estimate quality of life and health.

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Photo by Matthias Zomer on Pexels.com

This post is based on the article Ayudas a la dependencia y uso de los servicios sanitarios, ¿qué nos dicen los datos administrativos? (Nada Es Gratis, April 2021) by Helena Hernández-PizarroGuillem López CasasnovasCatia Nicodemo, and Manuel Serrano Alarcón.

Since the 2007 implementation of the “Dependency Act”, people with functional limitations in Spain can request Long-Term Care (LTC) benefits. The Act’s main objective is to improve the care and quality of life of people who have lost their autonomy. Fourteen years later, evidence on the impact of the Dependency Act in Spain on its beneficiaries remains scarce. This is partly because we need data on the quality of life of this population in order to fully evaluate its impact and we still don’t gather a suitable indicator. However, we can assess the impact of benefits by utilising data on the use of healthcare services as a proxy to estimate quality of life and health, and that is the approach we have taken in our research.

The relationship between LTC benefits and healthcare use

The effect of LTC benefits on healthcare use is not trivial and may have implications not just for the quality of life of recipients, but also for the management of healthcare services.

If access to LTC improves the health status of dependent people (for example through better treatment management, better nutrition or avoiding domestic accidents), investments in the LTC system could save healthcare providers money in the future. On the other hand, LTC benefits might increase the demand for healthcare, for example through greater health-monitoring by caregivers.

Using data on the type of healthcare service, type of admission and diagnoses, we can better understand the relationship between benefits and healthcare use, and therefore increase the efficiency in the allocation of social care and healthcare resources to design a better integrated care system.

The data

To study the effects of LTC benefits on healthcare use, we needed to gain access to data from social services and healthcare providers and then link it. As others have shown, this was not easy, but fortunately, the interest of the institutions involved in this research —CatSalut, AQuAS, the Departament de Treball, Afers socials i Famílies de la Generalitat de Catalunya (DTASF) (Labour, Family and Social services department) and CRES (UPF) — helped to facilitate this process.

Even with access to the data, measuring the effect of LTC benefits on the health system is not straightforward. Those who qualify for benefits will by definition have worse health and, regardless of the new policy, will probably make greater use of the healthcare system than those who don’t qualify for benefits. Therefore, simply comparing those applicants who receive LTC benefits with those who don’t would not help us to identify the effects of the Dependency Act.

To deal with this, we use an instrumental variable technique based on the “leniency” of the evaluators. The idea is as follows. When there is an evaluation guided by objective criteria such as when grading an exam, imposing a judicial sentence or assigning the severity of a medical case, there is always a degree of subjectivity from the person performing the assessment. It is common in research literature to consider this as a source of exogenous variation, because there is no predictable basis by which assessors should differ. This allows us to use traditional statistical methods that can identify any consequences associated with new policies. In our context, despite the fact that the assessment is based on the Dependency Assessment Scale, each examiner has a small margin of subjective interpretation. Thus, there are examiners who, on average, tend to provide slightly higher scores, so that their applicants qualify for greater LTC benefits. Since the applicant cannot choose his/her examiner, being assessed by one examiner or another affects the probability of receiving a benefit which is exogenous to the assessment process.

The results

In the two graphs below, we summarize the most important results from our research.

Figure 1 shows that access to LTC benefits decreases by 7 percentage points the probability of a group of hospitalizations considered by the medical literature as avoidable with continuous care for the elderly (such as hospitalizations for injuries, ulcers and nutritional deficiencies). This represents a 60% reduction in this type of hospitalization.

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Figure 1. Effect of LTC benefits on the probability of avoidable hospitalizations

Figure 2 shows that unscheduled visits to primary care decrease by almost 10 visits two years after receiving LTC benefits, a 50% reduction with respect to the mean. Our analysis by diagnosis indicates that this reduction is explained by a sharp drop in visits caused by the economic and family situation of the individual.

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Figure 2. Effect of LTC benefits on visits to primary care. Scheduled vs Unscheduled

Conclusions

Our results show that LTC benefits can mitigate the use of healthcare services, in line with the conclusions of previous research. Additionally, our data allows us to go one step further, identifying in detail the types of services which are the most affected.

Particularly interesting are the results relating to primary care, where LTC benefits strongly reduce visits not strictly related to health causes. It seems that reinforcing the LTC system will not only improve the quality of life of dependents and caregivers, but may also reduce the pressure on the healthcare system.

Undoubtedly, these results are important given the chronic under-financing of the LTC system, especially in a context where COVID-19 has highlighted a need for real integration between social and health care. This is just one example of how access to, and analysis of administrative data can contribute to the evaluation of public policies, facilitating better informed decision making. 

Connect with Barcelona GSE Alumni

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Helena Hernández-Pizarro (ECON ’11, HEP ’12, GPEFM ’17) is a Research Fellow at the Centre for Research in Health and Economics (CRES-UPF).

6 Real Policy Solutions to the U.S. Mental Health Crisis

Article by Patricia Paskov ’18 (Economics) on Medium

image: piranka / Getty Images

In a post on Medium’s Elemental, Patricia Paskov outlines six mental health policy recommendations for the United States during Covid-19 and beyond:

  • Destigmatize mental health
  • Widen accessibility of mental health care
  • Break down barriers to telehealth care
  • Strengthen labor policies for low-skilled workers
  • Build a body of rigorous data and research
  • Harness artificial intelligence and predictive analytics

Connect with the author

Patricia Paskov ’18 is an Impact Evaluation Analyst at The World Bank. She is an alum of the Barcelona GSE Master’s in Economics.

Band-Aids to Major Surgery: Making Healthcare Work in the U.S.

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Editor’s Note: The following post comes from Sergio Gutiérrez. Sergio is a Chicago-based designer and strategist working at the intersection of people, business, and technology. He graduated from BGSE’s MSc Economics of Science and Innovation in 2011.


 

So, as it seems, healthcare in the U.S. seems to be in of trouble and, all the voices say, design can do a lot to solve the problem. For this reason, many design and innovation consulting firms are making healthcare a strong focus area. For any designer —or any person trained to solve problems for that matter— this type of problem, because of its complexity, potential impact, and evident “higher purpose” is also very attractive.

However, regardless all the hype around this topic, thinking of design as the main driver for structural change may prove a bit unrealistic — as much as I would like to think that design can save the world. In reality, given the magnitude of the problem in the U.S., this needs to be attacked from different angles, with various strategies and tools and, probably, the most critical ones will have to come from outside the design field.

The system that is supposed to take care of us is very sick.

To help you gauge the magnitude of the U.S. healthcare problem, let me start with some background info — it won’t hurt, I promise: This is what we pay for our healthcare in the U.S…

  • The U.S. 2010 healthcare expenditure was 18% of the GDP, up to $2.6 trillion. That is roughly double the OECD average and this figure is projected to grow up to 26% of GDP by 2037 (scary).
  • The U.S. has the highest healthcare administration costs in the World at triple the OECD average.
  • Cost of healthcare per capita is above $8,200. That is more than double the OECD average of $3,200. Second, but not even close, is Switzerland with $5,200.

This is what we get…

  • There are fewer physicians and hospital beds per person than in most other OECD countries.
  • Life expectancy has increased over the last few decades but less than compared to other economies. Between 1960 and 2010, 9 years compared in the U.S. to 11 years on average on OECD countries.
  • 33% Americans were obese as of 2009 compared to an average 16% in the OECD countries.
  • The cost of certain procedures is much higher in the U.S. and the industry seems to favor more expensive diagnosis procedures.
  • In 2012, 46% of the U.S. population were underinsured or uninsured at some point, if not all year.
  • The system is terribly complex, especially for users: a new study to be released in September shows how only 14% of all insured Americans “can explain all four key health insurance concepts: deductible, co-pay, co-insurance, out-of-pocket maximum”. Can you?
  • And finally, healthcare bills is the number one reason for family bankruptcy in the U.S.

 A vicious circle

Continue reading “Band-Aids to Major Surgery: Making Healthcare Work in the U.S.”

Healthcare: Are we demanding bad goods?

Details is a trendy American style magazine showcasing movie stars and the latest in everything fashionable and chic. So when they name a health economist as one of the 50 most influential men under 45 it should raise a well-groomed eyebrow (or two).

Submitted by Scott Robertson, Master Program in Health Economics and Policy

Details is a trendy American style magazine showcasing movie stars and the latest in everything fashionable and chic.  So when they name a health economist as one of the 50 most influential men under 45 it should raise a well-groomed eyebrow (or two).

As if that doesn’t give him enough credibility, David Cutler is one of the most-cited minds in modern health economics with a persistent focus on driving the discussion of quality.  Modern Healthcare recently said he is one of the 30 people likely to have a significant impact on the future of healthcare.  Plus he’s a professor at MIT and was an advisor to U.S. Presidents Clinton and Obama.

In short: Cutler is a big deal.  If the UPF, and ostensibly the Barcelona GSE want to prove the profile of their economics program, attracting this star to inaugurate the academic year could be an indicator of success.  The auditorium filled to standing-room only shows the opportunity was not lost on students either.

UPF Economics Department
David Cutler delivers the UPF Economics Department opening lecture in October 2012. Photo credit: UPF

Continue reading “Healthcare: Are we demanding bad goods?”