Heavy user

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Heavy user (in German: frequent users, intensive users, high users) is an inconsistently used term for a population group or subgroup of people who increasingly use or inquire about a service or product. Compared to normal users (Engl. Ordinary user ) they usually represent a minority. The terminology is mainly in the economic and health sciences and here in the marketing or e-commerce and in the psychiatry needed.

The German-language interpretation in relation to health care often has a negative connotation. Although the term has existed for decades (1960s, 1970s) and various research papers have existed, there are also legitimate doubts about this concept.

Heavy user in business administration

Heavy users are customers who, in contrast to "light users", ask for a product particularly often and therefore represent the main target group of marketing. In a simplified way, buyers are divided according to their consumption intensity, for example into weak, medium, and high consumption.

Heavy user in health sciences

The earliest works dealing with the heavy user concept date from the 1960s and 1970s.

In very simplified terms, the following is often formulated: People who make heavy use of medical services are referred to as so-called "heavy users".

Definition of terms and synonyms

Roik (2002) speaks of a “Babylonian language confusion” in the Heavy User environment, which turns every literary work on the subject into a “Sisyphean work”. Basically, the following terms are optionally used synonymously in English-speaking countries: high user, intensive user, frequent user, high utilizer, high attender, heavy service user, frequent caller, frequent repeater, frequent user, high cost case, high-cost user, high end user, and much more. Analogous formulations in German-speaking countries are: frequent users, high users, maximum users, intensive users. In a more negative connotation: called high-cost case, problem patient, revolving door patient or difficult patient. Efforts are being made to describe the possible problem more neutrally, in particular as strong, intensive or above-average use. Occasionally the suspected subgroup is also referred to as the treatment-intensive population.

An overview of the conceptual history and conceptualization can be found in Frick & Frick (2008).

Because of this multitude of different terms and due to the fact that some arguments speak against the existence of heavy users, Roick describes heavy user research as "mysterious research".

Problem

Inpatient care in particular is very cost-intensive. It is therefore likely that “heavy use” is a problem for the cost bearers or the treating staff, and much less a problem for the patient. It is unclear whether such high users experience additional suffering. The health care research tries to identify the causes of intensive use by patient groups and determining appropriate alternative therapies and interventions.

Operationalization

Often individual or combined indicators are used to identify high levels of utilization. For example, the number of services, the number of contacts, days in hospital or the costs incurred. For each criteria, questions arise about cut-off values ​​(2 or 3 years, 2 or 3 hospital stays).

Identification and prediction

In order to identify the small proportion of patients who account for a large proportion of health expenditure, attempts have been made to develop prediction models. The aim should be to find controllable high users at an early stage and to derive decision support for the choice of a treatment method. There are generally two approaches to identification: on the one hand, patient characteristics are in the foreground (age, gender, diagnosis) and on the other hand, the costs (of therapy and services).

At least with regard to the diagnostic spectrum, there would be a relatively constant picture, addictions (alcohol, mostly men) and affective disorders (mostly women). There is still no uniform information on gender. Otherwise, heavy users are often middle-aged, tend to live alone, but rarely in private homes, are rarely married, have an average level of education, do not have any gainful employment and the increase in hospital stays often leads to a loss of independence in the area of ​​living. A study by Spießl et al. (2002) identified 10 significant predictors for a long treatment duration: among others, schizophrenia, personality disorders and a low general level of functioning.

discussion

From an economic perspective, the heavy user group is also called heavy consumer or heavy buyer . The economy assumes that people are free in their consumption decisions. So buying behavior reflects a decision based on preferences and opportunities. This is a great area of ​​tension and a possible misunderstanding of the use of the term in health care. Because here “heavy users” cannot “choose” to need more products and services.

If the health care payers were to identify people as heavy users with the aim of excluding them from certain services or not accepting them at all, there would be strong ethical problems. In particular, the statutory health insurance is particularly affected by the risk of adverse selection, because it is not allowed here by government regulations to require risikoabgestufte posts or reject persons (see. Risk selection ).

Individual evidence

  1. ↑ Meffert, H. (Ed.). (2013). Marketing today and tomorrow: trends in theory and practice. Springer publishing house. P. 94.
  2. ^ Frick, U., & Frick, H. (2008). Basic data of inpatient psychiatric treatments: In-depth study "Heavy User". P. 7.
  3. ↑ a b c Roick, C. (2002). Heavy User: Mysterious Research. Psychiatric Practice, 29 (07), 331–333. P. 331.
  4. ^ Frick, U., & Frick, H. (2008). Basic data of inpatient psychiatric treatments: In-depth study "Heavy User".
  5. ↑ Schauer, S., Krauth, C., & Amelung, V. (2012) Methods to predict high users: a systematic literature review Methods to predict high users: a systematic literature review.
  6. ↑ Schöny, W. (2017). Social psychiatry - theoretical basics and practical insights. Chapter 9.3. P. 264.
  7. ↑ Spießl, H., Hübner-Liebermann, B., Binder, H., & Cording, C. (2002). Heavy users in a psychiatric clinic - a cohort study with 1811 patients over five years. Psychiatric Practice, 29 (07), 350–354.

literature

  • Roick, C. (2002). Heavy User: Mysterious Research. Psychiatric Practice, 29 (07), 331–333.
  • Frick, U., & Frick, H. (2008). Basic data of inpatient psychiatric treatments: In-depth study "Heavy User".
  • Frick, U., & Frick, H. (2010). Heavy use in inpatient psychiatry in Switzerland ?: Results from the medical statistics of hospitals. Swiss Health Observatory.
  • Schauer, S., Krauth, C., & Amelung, V. (2012) Methods to predict high users: a systematic literature review Methods to predict high users: a systematic literature review.
  • Kumar, GS, & Klein, R. (2013). Effectiveness of case management strategies in reducing emergency department visits in frequent user patient populations: a systematic review. The Journal of emergency medicine, 44 (3), 717-729.
  • Schöny, W. (2017). Social psychiatry - theoretical basics and practical insights. Chapter 9.3.