How to extend value-based healthcare to population-based healthcare systems? Defining an outcome-based segmentation model for health authority.

OBJECTIVES: Value-based healthcare (VBHC) is considered the most promising guiding principle for a new generation of health service production. Many countries have attempted to apply VBHC to managerial and clinical decision-making. However, implementation remains in its infancy and varies between countries. The objective of the study is to help health systems implement a value-based approach by building an outcome-based population segmentation model for health authorities (HAs). DESIGN: First, we define the principles according to which segmentation models in healthcare could be developed. Second, we merge the theoretical characteristics of outcomes with population segmentation dimensions identified in previous literature and design a flow model that establishes population segments from these combinations. We then estimate the size of the segments based on national register data. RESULTS: The population can be divided into 10 different segments based on relevant outcomes, goals and the outcome measurement logic. These segments consist of healthy, help, increased risk, mild curable without risk, mild curable with risk, severe curable without risk, severe curable with risk, single chronic, multimorbid and terminal. The representatives of Finnish HAs found the segments meaningful for evaluating and managing the healthcare system towards improved population health. CONCLUSIONS: An outcome-based segmentation model for the entire population is needed if an HA wants to steer the healthcare system employing the principles of VBHC. Segmentation should be based on the outcome measurement logic and outcome measurements relevant to each segment and the number of segments has to be limited.

Demonstrating the value of digital health: Guidance on contextual evidence gathering for companies in different stages of maturity.

Application of value-based healthcare policies affects all actors in social and health care field, including the Digital Health Intervention (DHI) providers aiming to enter the industry or expand their market. Apparent lack of fit between evidence and expectations inhibits the growth of DHI companies. The companies need efficient and credible methods to access and demonstrate the value of their DHIs. Building on the stage-of-maturity logic presented in World Health Organization's (WHO) guide of monitoring and evaluating digital health interventions and Context-Intervention-Mechanism-Outcome (CIMO) logic, we provide a potential approach for DHI companies to assess the evidence needed in their current situation. The proposed approach takes into account the company's future development goals and the business environment, reflecting for every stage of technology maturity according to the WHO guidelines and through the CIMO lens. The focus is on specific intervention and its fit for different organizational and national contexts. The solution guides the research process of the company to understand which evidence-gathering topics should be addressed. This evidence can be beneficial for companies to enter into, occupy, expand or sustain in the domestic or international market.

Demand and supply-based operating modes--a framework for analyzing health care service production.

CONTEXT: The structure of organizations that provide services should reflect the possibilities of and constraints on production that arise from the market segments they serve. Organizational segmentation in health care is based on urgency and severity as well as disease type, bodily function, principal method, or population subgroup. The result is conflicting priorities, goals, and performance metrics. A managerial perspective is needed to identify activities with similar requirements for integration, coordination, and control. METHODS: The arguments in this article apply new reasoning to the previous literature. FINDINGS: The method used in this article to classify health care provision distinguishes different types of health problems that share generic constraints of production. CONCLUSIONS: The analysis leads to seven different demand-supply combinations, each with its own operational logic. These are labeled demand and supply-based operating modes (DSO modes), and constitute the managerial building blocks of health care organizations. The modes are Prevention, Emergency, One visit, Project, Elective, Cure, and Care. As analytical categories the DSO modes can be used to understand current problems. Several operating modes in one unit create managerial problems of conflicting priorities, goals, and performance metrics. The DSO modes are constructed as managerially homogeneous categories or care platforms responding to general types of demand, and supply constraints. The DSO modes bring methods of industrial management to bear on efforts to improve health care.

Time-based management of patient processes.

PURPOSE: The purpose of this paper is to present a conceptual framework that would enable the effective application of time based competition (TBC) and work in process (WIP) concepts in the design and management of effective and efficient patient processes. DESIGN/METHODOLOGY/APPROACH: This paper discusses the applicability of time-based competition and work-in-progress concepts to the design and management of healthcare service production processes. A conceptual framework is derived from the analysis of both existing research and empirical case studies. FINDINGS: The paper finds that a patient episode is analogous to a customer order-to-delivery chain in industry. The effective application of TBC and WIP can be achieved by focusing on through put time of a patient episode by reducing the non-value adding time components and by minimizing time categories that are main cost drivers for all stakeholders involved in the patient episode. RESEARCH LIMITATIONS/IMPLICATIONS: The paper shows that an application of TBC in managing patient processes can be limited if there is no consensus about optimal care episode in the medical community. PRACTICAL IMPLICATIONS: In the paper it is shown that managing patient processes based on time and cost analysis enables one to allocate the optimal amount of resources, which would allow a healthcare system to minimize the total cost of specific episodes of illness. Analysing the total cost of patient episodes can provide useful information in the allocation of limited resources among multiple patient processes. ORIGINALITY/VALUE: This paper introduces a framework for health care managers and researchers to analyze the effect of reducing through put time to the total cost of patient episodes.