How can Analytics benefit the increasingly demanded Home Care Services
Jésica de Armas, Master of Science in Management professor
A software to optimize the planning of shared car routes to provide home care to the elderly. This is the proposal of Ingentus Decision Support, an Austrian company dedicated for years to the application of the most sophisticated optimization methods in the field of logistics in production and retailing companies and industries: originally Ingentus was dedicated to the transport of pellets. Now it is an example of how technology can be used in health and social field to provide benefits for society. And this is an upward trend. You only need to look at the data on the aging of the population.
The combination of increasing life spans and low birth rates is accelerating the pace at which the share of elder people in the population worldwide is rising. As a result, the population as a whole is getting older. In Spain, the ageing process has been particularly rapid, accentuated by the country’s low birth rate over the past few decades. The projections by the Spanish Statistics Office (INE) suggest the over-65s will make up more than 25% of the population by 2033, i.e., almost 12 million people, of whom near 4 million will be over-80s. Additionally, according to another study conducted by INE, more than 2 million people over the age of 65 live alone in Spain. As people age their autonomy tends to decrease, leading to the need for support of others to perform their daily living activities. Therefore, specialized home social care services and home health care services providers are a good answer to this need while keeping elders’ quality of life and allowing them to continue living in their homes.
These home health and social care services are gaining popularity in Spain during the last decade, which has been reinforced due to the covid-19 pandemic and what dramatically happened in nursing homes. However, the reality is that the cost associated to home care services is high and is growing, but resources are limited. Therefore, it is clear the need of optimizing them.
It is clear that a better use of limited resources can guarantee the quality of life of elderly people, allowing to extend the benefits of these home cares to an increasing ageing population. This will help decision makers, policymakers, and care managers to make better decisions leading to a positive impact on the society in terms of health, social benefit (quality of life, increasing satisfaction of patients and caregivers), and cost efficiency.
The 3 types of Data Analytics to improve Home Care
The goal of any Data Analytics is to provide the organization with actionable insights for smarter decisions and better outcomes. Different types of analytics, however, provide different types of insights. Therefore, it is important to understand what each analytics type delivers and to match analytics functions to the organization’s operational capabilities. Analytics solutions are of three main kinds: Descriptive Analytics to understand what has happened in the past; Predictive Analytics to know what could happen in the future; and Prescriptive Analytics to react and know what to do, as well as advise on possible outcomes.
The first two kinds of analytics make an important contribution to knowledge, and some companies (e.g. Kantime, AlayaCare) offer these approaches to improve home care. However, if we want to go a step further it is necessary not only to analyse, but to react to the present and future situations. Accordingly, the third kind of analytics constitutes a relevant inflection point for any organization. However, they are the least known analytics, and few researchers focus their efforts on it when dealing with data. Some American and English companies such as TotalMobile, Kirona, Skedulo, or ServicePower are including incipient prescriptive analytics in this field, but there is still way ahead.
Why is Integrated Home Care important and how can Analytics help?
The current home care services provided to elderly people in Spain are mainly provided by two independent entities: health system and social services organizations. A potential new combined model consists of a joint reorganization and coordination of home health and social care systems for elderly people, improving interactions, solving conflicts, and integrating both parts.
Integrated home care can be defined as a model of care where different professionals from health and social care act jointly, sharing information and goals and taking joint or coordinated decisions to guarantee Integrated Care at home. Some studies show that the coordination and integration of both home social care and health care involve a positive effect in terms of service access, utilization, costs, care provision, quality, health status and client/caregiver satisfaction. Actually, the influence of social care on health care utilization is a growing policy concern. Adequate supply of social care has even the potential to reduce demand on health services.
But, how to construct an integrated home care? There are many levels of action, from policy initiatives and standards, to strategic and managerial concepts. Some of them are being widely discussed in the last years. However, quantitative methods, such as Data Analytics, are not being considered enough yet despite their potential. Particularly, innovative quantitative methods applied to supply chain and logistics problems in the area can improve the home care services for elderly people. This will be accomplished by analyzing data, developing mathematical models, algorithms and systems, based on Analytics successfully applied to several industries.
This way decision makers, policymakers and care managers can make better decisions leading to a positive impact on the society in terms of health, social benefit (quality of life, increasing satisfaction of patients and caregivers), and cost efficiency.
What other social and health fields can benefit from these methods?
There are many other close fields that may benefit from these methods. Some potential options that have been showing good results include vaccine distribution and administration, assistive technology distribution, hospital logistics, humanitarian logistics, and school or hospital location in developing countries. They are applications of the general supply chain and logistics field, which has been addressed by the scientific community on production or retailing industries. Yet, the mathematical models and algorithms developed over the years cannot be easily and immediately applied in this kind of field. They need to be tailored to meet the requests of its singular aspects, particularly due to the human factor involved. Nevertheless, the benefit is clear, and this is worth the effort.