A Model for Diagnostic Analysis of Hospital Performance to Optimize Its Management

Introduction

Modern hospital management requires reliable information about organisational condition, deviations, causes and the relationships among outcomes, resources, processes and environment. Diagnostic analysis connects measurement with management action and replaces intuition-only decision-making with structured use of data, indicators and evidence.

Aim

To develop a conceptual multidimensional model for balanced diagnostic analysis of modern hospital performance, integrating the critical organisational and environmental parameters required for effective management.

Four research tasks

1. characterise diagnostic analysis in Bulgarian hospitals;
2. define the theoretical, regulatory and practical basis for model development;
3. develop a methodology covering sequence, analytical dimensions and indicators;
4. construct the model, scheme and implementation algorithm.

Methods and national empirical base

The empirical material covered 155 inpatient healthcare facilities out of 251, representing 62% of all Bulgarian inpatient facilities at the time of the study. Structured interviews were conducted with 412 hospital-management specialists. Interview responses were compared with activity reports from the same hospitals. Methods included literature review, structured interview, content analysis, comparative analysis, statistical methods and graphical analysis.

Two perspectives on hospital analysis

A core methodological feature is the comparison between what management teams report analysing and what is actually documented in formal performance analyses and reports. This separates managerial intention from observable analytical practice.

Multidimensional principle

Hospital performance cannot be assessed adequately through financial or clinical indicators alone. Balanced diagnosis requires simultaneous consideration of organisational, clinical, financial, resource, process, workforce and environmental dimensions and their interactions. The key dimensions function as strategic questions that management must monitor systematically.

Three levels of diagnostic analysis

• Operational diagnostic analysis — a short-term perspective of up to 1 year, prioritising management, clients, effectiveness, clinical perspective, financial perspective, employees and capacity/resources.
• Comprehensive diagnostic analysis — covers 1 year or more and adds internal processes, learning and innovation, and the external microenvironment.
• Strategic diagnostic analysis — extends the comprehensive level with societal benefits and the external macroenvironment to support long-term strategic management.

Diagnostic-analysis algorithm

The implementation algorithm is organised into three main stages:

1. Preparatory stage — planning the analysis and team; defining objectives, scope, time frame and responsibilities; selecting the methodological apparatus; formulating key and supplementary questions; choosing indicators, data sources and data-collection methods.
2. Analytical stage — conducting measurements, collecting data, identifying general changes and estimating the quantitative influence of relevant factors.
3. Final stage — preparing an analytical report containing methodology, results, limitations, expert interpretation, conclusions and recommendations for improvement.

Two team roles are distinguished: a strategic role responsible for guidance and quality control and an operational role responsible for data collection, analysis and reporting.

Structure of each diagnostic map

Each of the 12 diagnostic maps follows the same four-part structure:

1. Key questions — the management questions to be answered in the selected area;
2. Indicators for analysis — measures used to assess status, trends and goal attainment;
3. Data-collection methods — interviews, surveys, document review, observation, information searches and other suitable methods;
4. Information sources — people, documents, information systems, official registers, reports, media, internet sources and other relevant sources.

This standardised structure improves transparency, traceability and comparability across analytical domains.

Twelve diagnostic maps and their analytical scope

1. Management — vision, mission, objectives, strategy, strategic portfolio, plan implementation and control, management competence and experience, organisational structure, responsible governance, innovative management methods, achievements/failures and their causes, and management style.
2. Clients — targeting, monitoring, results, relationships and interactions; satisfaction, loyalty, future value and intensity of customer relationships.
3. Effectiveness — relevance, productivity, adequacy, efficacy, medical effectiveness and economic efficiency; the degree to which organisational goals and stakeholder outcomes are achieved.
4. Clinical perspective — volume and variety of medical activity, utilisation of capacity and intensity of activity, including bed use, equipment use, operating-theatre activity, staff utilisation, bed turnover, average length of stay and emergency admissions.
5. Financial perspective — financial planning, accounting and financial reporting; funding sources, cash flows, expenditure, investment and financial viability.
6. Employees — workforce planning, staffing, qualification and development, appraisal, motivation, employee relations and satisfaction.
7. Capacity and resources — physical facilities, medical technologies, infrastructure, transport and the medical information system; adequacy, utilisation, safety, economy, maintenance and modernisation.
8. Internal processes — organisation, quality management, internal control and risk management; compliance with procedures, deadlines and rules and appropriate use of organisational resources.
9. Learning and innovation — staff learning and development and innovation management; organisational capacity to learn, adopt new solutions and adapt.
10. External microenvironment — competitors, suppliers, labour market and social partners; positioning, power, significance and relationships with key external actors.
11. External macroenvironment — health-demographic, socioeconomic, political, technological, cultural and environmental factors and health risk factors; opportunities and threats affecting future development.
12. Societal benefits — stakeholder identification, characterisation and mapping; needs assessment; measurement and analysis of satisfaction; social value and corporate social responsibility.

The maps can be used together for strategic or comprehensive analysis or separately for focused thematic analysis.

Balancing analytical dimensions and stakeholder interests

The model includes a mechanism for checking whether priority stakeholder needs are adequately represented across the analytical dimensions. This supports a balanced focus on patients, staff, funders, partners and other key groups rather than over-emphasising a single perspective.

Measurement and data-quality requirements

Useful measures should be objective, statistically reliable, comparable and sufficiently informative. Indicator choice should be linked to a specific management question, an appropriate target level and feasible data collection. The quality of diagnosis depends on data reliability and validity and on distinguishing general trends from the quantitative effect of specific factors.

Information systems and Business Intelligence

Information support is treated as a critical prerequisite for sustainable diagnostic analysis. The technological pathway progresses from basic systems to integrated information systems, ERP and Business Intelligence. ERP supports analysis, planning, execution and control across organisational units, while BI transforms stored data into decision-support information. The analytical environment may include Data Warehousing, Queries & Reports, OLAP and Data Mining.

Practical application

The framework is applicable to strategic analyses, business plans, annual performance reports, internal assessments, benchmarking and management decisions. Its purpose is to transform routinely available reporting and operational data into information for diagnosis, prioritisation, comparison and improvement.

Main contributions

• national empirical coverage of 155 hospitals, 62% of inpatient facilities;
• participation of 412 hospital managers and management specialists;
• comparison of declared analytical practice with actual reporting;
• integration of theoretical, regulatory, strategic and practical foundations;
• a multidimensional balanced hospital-analysis framework;
• an implementation algorithm and 12 diagnostic maps;
• orientation toward evidence-based managerial action.

Conclusions

High-quality diagnostic analysis requires more than reporting and indicator calculation. It needs a system that connects data with management questions, causes, deviations and corrective action. The multidimensional model provides a basis for balanced, evidence-based hospital management and turns reporting information into actionable organisational knowledge.

Scientific Key Terms