Diagnostic Analysis of Healthcare Facility Performance – Part II: A Multidimensional Model, Algorithm, and Diagnostic Maps

Introduction

Effective healthcare-facility management requires simultaneous monitoring of internal and external factors, results, resources and relationships. Diagnostic analysis converts fragmented operational data into management information that can reveal deviations, strengths, dependencies and areas for improvement.

Aim

To provide an applicable multidimensional model for diagnostic analysis that supports management decisions through a structured analytical sequence, a system of indicators and diagnostic maps covering the key dimensions of healthcare-facility performance.

Twelve analytical dimensions

The model balances 12 dimensions: management, clients, efficiency, clinical perspective, financial perspective, employees, capacity and resources, internal processes, learning and innovation, external microenvironment, external macroenvironment and societal benefits.

Three levels of application

The scope is adapted to the management question:

• operational diagnostic analysis — a short-term horizon of up to one year, focused on management, clients, efficiency, clinical and financial perspectives, employees, and capacity/resources;
• comprehensive diagnostic analysis — a one-year or longer perspective adding internal processes, learning and innovation, and the external microenvironment;
• strategic diagnostic analysis — the broadest scope, incorporating societal benefits and the external macroenvironment to support long-term strategic management.

This tiered design prevents organisations from applying the same analytical burden to every decision while preserving a common conceptual framework.

Three-stage algorithm

The algorithm consists of a preparatory stage (plan, team, questions, indicators, data sources and collection methods), an analytical stage (measurement, data collection and analysis), and a final stage (analytical report, expert interpretation and recommendations).

Diagnostic matrix: six linked elements

The diagnostic matrix structures each analytical task through six linked elements: analytical dimension; main questions; supplementary questions; indicators; data sources; and data-collection methods. Every management conclusion should therefore be traceable to an explicit question, measure, source and method.

Indicator selection and target levels

Indicators should be specific, quantitatively measurable, reliable, valid, comparable across healthcare organisations and practically obtainable. They should characterise the relevant dimension and have real decision-making value.

Key indicators are assigned a target level representing the desired performance state. Targets may be derived from historical and statistical data, benchmarking, professional standards, contractual requirements or expert judgement, allowing interpretation to move beyond simple description toward assessment of deviation from desired performance.

Data sources and data quality

Information support requires explicit selection of data sources and collection methods, followed by checks for completeness, reliability, logical consistency and comparability. The analytical output can be no more reliable than the data on which it is based.

Twelve diagnostic maps

The 12 diagnostic maps transform the conceptual model into a practical management instrument. They create a repeatable path from management questions to indicators, interpretation and recommendations and can be applied in strategic analyses, business plans, annual reports, internal assessments and organisational-improvement initiatives.

Information systems, ERP and Business Intelligence

Information support is presented as an evolution from basic applications toward integrated information systems, Enterprise Resource Planning (ERP) and Business Intelligence (BI). ERP supports coordinated planning and control of material, human, financial and time resources.

BI transforms accumulated data into information and management knowledge. The architecture described includes a Data Warehouse and analytical layers such as Queries & Reports, OLAP and Data Mining. The objective is not automation for its own sake but evidence-based management capable of detecting patterns, trends and emerging deviations.

Main contributions

• a balanced 12-dimensional model;
• operational, comprehensive and strategic levels of analysis;
• a three-stage implementation algorithm;
• a diagnostic matrix linking questions, indicators, sources and methods;
• 12 practical diagnostic maps;
• integration of target levels, benchmarking, ERP and Business Intelligence into the analytical framework.

Conclusions

Diagnostic analysis is a management process rather than a one-off calculation of indicators. Its value comes from systematically connecting objectives, questions, measures, data, interpretation and managerial action.

The multidimensional approach reduces the risk of judging a healthcare organisation only through financial or clinical results. It enables simultaneous assessment of organisational capacity, processes, people, environment, efficiency and societal value and provides a structured basis for evidence-based improvement.

Scientific Key Terms