Modelling home care organisations from an operations management perspective

Abstract

Home Care (HC) service consists of providing care to patients in their homes. During the last decade, the HC service industry experienced significant growth in many European countries. This growth stems from several factors, such as governmental pressure to reduce healthcare costs, demographic changes related to population ageing, social changes, an increase in the number of patients that suffer from chronic illnesses, and the development of new home-based services and technologies. This study proposes a framework that will enable HC service providers to better understand HC operations and their management. The study identifies the main processes and decisions that relate to the field of HC operations management. Hence, an IDEF0 (Integrated Definition for Function Modelling) activity-based model describes the most relevant clinical, logistical and organisational processes associated with HC operations. A hierarchical framework for operations management decisions is also proposed. This analysis is derived from data that was collected by nine HC service providers, which are located in France and Italy, and focuses on the manner in which operations are run, as well as associated constraints, inputs and outputs. The most challenging research areas in the field of HC operations management are also discussed.

A Bayesian framework for describing and predicting the stochastic demand of home care patients

“…Moreover, the human resource organization and the patient classification adopted by this provider can be considered general and common to several other HC providers as underlined by Matta et al [1], so that it is representative of a general class of providers. The provider is divided into three divisions, and the analysis refers to the largest one.…”

“…In Home Care (HC) services, where patients are assisted for a usually longer period than in other facilities and additional planning choices related to service delivery in the territory are required, the impact of random demands is relevant. In particular, when continuity of care is pursued, the assignment of nurses to patients has an impact for a long period (see [1]), and accurate estimations of future patients' demands are fundamental for taking robust nurse-to-patient assignment decisions.…”

“…Appropriate resource planning is thus fundamental for avoiding process inefficiencies, delays, and overloaded operators. In addition, many random events may affect the service delivery and mine the feasibility of plans; see [1,2,3,4]. As mentioned above, the most relevant randomness sources are patients' health conditions, which may determine a different demand for visits than the planned one, as reported in [5].…”

“…Here NB(z, q) denotes the Negative Binomial distribution with probability of "success" q and "number of successes" z, and its expectation is 1 + r(1 − q)/q. The q i,j s are modelled through a logit regression of the form logit(q i,1 ) = log q i, 1 1…”

Evaluation of trip and car sharing concepts for home health care services

“…As a result, home health care (HHC) providers face increased organisational efforts, whilst being additionally exposed to various risks affecting service quality as well as client and employee satisfaction (Rest et al 2012). An overview of various operations managementrelated decisions of HHC providers is provided in Matta et al (2012). On an operational level, in particular, routing and scheduling of nurses is complex.…”