# Data in ambulatory care logistics: What modelers need and what practice can offer

## TL;DR

This paper explores how data can improve decision-making in outpatient healthcare settings by identifying what data is needed and how it can be used.

## Contribution

The paper systematically reviews data requirements for operations research in ambulatory care and discusses practical barriers to model implementation.

## Key findings

- Ambulatory care facilities can collect demand and supply-related data to support decision-making.
- Missing data can significantly affect the quality of planning and control decisions.
- Real-world appointment datasets vary in usefulness for modeling and planning purposes.

## Abstract

Ambulatory care facilities play a critical role in many healthcare systems worldwide. To ensure efficient care provision, we must match care demand with care supply. To support provider decision-making, this article reviews Operations Research planning problems, the corresponding planning and control decisions that must be made when opening up or running an ambulatory care facility, and their data requirements. We give an overview of demand and supply-related data that an ambulatory care facility can collect and comment on the consequences for decision-making if some of that data is missing. We briefly discuss three healthcare systems and their influence on data collection and decision-making. We also take a closer look at several real-world appointment data sets and their usefulness for planning decisions. In addition, we discuss model implementation barriers and give recommendations for modelers and practitioners to bridge the gap between theory and practice. Finally, we present future research directions for Operations Research in ambulatory care.