Organising and running a Hospital Under DRG Financing: Efficiency, Safety, Co-Governance, and the Quintuple Aim

Introduction

Organizing and running a hospital under Diagnosis-Related Group (DRG) financing requires an intricate balance of clinical excellence, streamlined operational logistics, financial sustainability, and patient-centric governance. Successfully steering a medical facility under these conditions demands blending top-tier patient care with complex legal and administrative frameworks to maintain patient safety, regulatory compliance, and a resilient workforce.

Diagnosis-Related Group (DRG) financing changes the managerial problem of the acute hospital. Instead of being reimbursed primarily for every input consumed, the hospital is paid, wholly or partly, according to case-mix groups that are intended to reflect clinically meaningful and resource-homogeneous episodes of care. In principle, this improves transparency, allows comparison of hospital activity, and creates incentives to reduce unnecessary length of stay, avoid inefficient resource use, and improve throughput (Busse et al., 2013; Busse et al., 2011; Tan et al., 2014). In practice, however, DRG incentives can also produce unintended effects: premature discharge, under-treatment, cost shifting to post-acute providers, selection of more profitable patients, coding inflation, and pressure on professional work environments (Zou et al., 2020). The organisational challenge is therefore not merely to “perform well financially” under DRGs, but to construct a clinical operating system in which cost discipline is bounded by safety, outcomes, patient experience, workforce well-being, and equity.

In this essay I want to argue that the most robust model for an acute hospital under DRG financing is a co-governed, service-line-based, data-driven organisation. Physicians and nurses should share formal authority with management over clinical pathways, workforce design, patient safety, resource allocation, and outcome monitoring (co-governance). The hospital should use DRG information not as a blunt rationing instrument, but as a case-mix-adjusted management language: a way to understand variation in cost, length of stay (LOS), complications, readmissions, and outcomes. This model aligns DRG efficiency with the Quintuple Aim: better patient experience, better population and clinical outcomes, lower per-capita costs, improved clinician well-being, and health equity (Berwick et al., 2008; Bodenheimer & Sinsky, 2014; Nundy et al., 2022).

Note: Operating a hospital under Diagnosis-Related Group (DRG) criteria in a traditional Fee-For-Service (FFS) model creates a fundamental conflict in financial incentives. These two reimbursement structures are practically incompatible because they pull hospital administration and clinical teams in completely opposite directions. Diagnosis-Related Groups (DRG) shifts the risk to the hospital, while Fee-For-Service (FFS) shifts the risk to the payer (insurance or government).

DRG Financing as a Design Constraint, Not the Hospital’s Purpose

A hospital should begin by recognising that DRG financing is a constraint and an information system, not a sufficient definition of value. DRGs can help hospitals compare case complexity, resource use, and productivity, but they do not automatically measure whether care was necessary, safe, person-centred, equitable, or clinically effective (Busse et al., 2013; Tan et al., 2014). Moreover, European DRG systems vary in important ways: some countries use DRGs mainly for activity-based hospital payment, others combine DRG tariffs with global budgets, quality controls, negotiated budgets, teaching adjustments, or separate treatment of selected cost components such as nursing or capital costs (Busse et al., 2011; Tan et al., 2014). A hospital board should therefore avoid copying a generic “DRG playbook” and should instead build its operating model around the specific national grouper, tariff rules, quality penalties, capital rules, nursing-financing arrangements, and regional planning requirements.

The core DRG risk is that payment encourages a narrow focus on average cost per case and length of stay. This is useful when it exposes waste, unwarranted variation, duplicative testing, avoidable complications, and inefficient discharge processes. It becomes dangerous when it encourages avoidable compression of care, insufficient staffing, or discharge before the patient has adequate functional, social, and post-acute support. Systematic evidence on DRG-like payment suggests that such systems may improve efficiency indicators such as length of stay (LOS), but effects on quality and equity are context-dependent and require active monitoring (Zou et al., 2020). Therefore, cost containment should be treated as “bounded optimisation”: the hospital may pursue lower cost per case only within explicit clinical, safety, workforce, and equity constraints.

The appropriate financial objective is value, not volume. Porter (2010) defines value in health care as outcomes achieved relative to costs. In a DRG-financed acute hospital, this means that the relevant unit of management is not the isolated hospital day, but the full episode of care: admission, diagnosis, treatment, recovery, discharge, post-acute transition, readmission risk, complications, and patient-reported recovery. A hospital that reduces length of stay (LOS) but increases (preventable) readmissions, emergency attendances, caregiver burden, or inequitable access has not improved value; it has shifted cost and risk elsewhere (externalization of costs).

Note: Externalization of healthcare costs occurs when a healthcare organization shifts the true financial, or social costs of their economic activity onto society. Because these "hidden costs" are omitted from the price of their care process, they result in a negative externality, meaning the private cost of healthcare production is artificially lower than its actual cost to society.

A Co-Governed Service-Line Operating Model

The first organisational requirement is a governance architecture that gives physicians and nurses real decision rights. Co-governance should not be limited to consultation committees with no authority. It should be embedded in the formal operating structure of the hospital. At board and executive levels, the hospital should maintain an integrated quality, finance, workforce, and equity committee. Below this, each major service line - such as cardiology, oncology, orthopaedics, emergency medicine, intensive care, internal medicine, or surgery - should be led by a clinical dyad or triad: a physician leader, a nurse leader, and an operations or finance manager. This structure ensures that clinical judgment, bedside workflow knowledge, and resource stewardship are present in the same decision forum.

The service-line leadership team should be accountable for a balanced set of indicators: observed-to-expected mortality, complications, readmissions, patient experience (PREM), patient-reported outcomes (PROM) where available, length of stay (LOS), cost per case, coding quality, staff turnover, sickness absence, burnout indicators, agency staff reliance, and equity-stratified outcomes. No service line should be rewarded purely for lower cost or shorter length of stay. Likewise, no service line should be allowed to defend inefficient variation without reference to outcomes, safety, or patient need. Co-governance is therefore the mechanism through which professional autonomy and organisational accountability are reconciled.

Nursing shared governance is especially important because nurses control and observe many of the processes that determine safety, flow, and patient experience: medication administration, deterioration detection, falls prevention, infection prevention, discharge education, family communication, mobilisation, nutrition, and coordination with community services. Shared governance gives nurses structured authority over practice standards, staffing models, competency development, quality improvement priorities, and work environment design (Kutney-Lee et al., 2016). Evidence from nursing work-environment research shows that better professional environments and adequate nurse staffing are associated with better outcomes and lower burnout (Aiken et al., 2014; Kelly et al., 2011). The practical conclusion is clear: under DRG pressure, nursing leadership must not be treated as a cost centre to be compressed, but as a core safety and flow capability.

Physician engagement is equally necessary. Physicians influence admission thresholds, diagnostic intensity, operative choices, pharmaceutical use, device selection, complication management, and discharge decisions. If DRG targets are imposed externally by finance departments, clinicians may resist them as rationing. If physicians participate in designing care pathways, reviewing variation, and interpreting case-mix-adjusted outcomes, financial discipline becomes a clinical improvement exercise rather than an accounting mandate. Co-governance should therefore include transparent service-line budgets, clinical variation reviews, morbidity and mortality learning, pathway ownership, and professional agreement on what constitutes appropriate resource use.

Clinical Pathways, Flow, and Length-of-Stay (LOS) Management

The second requirement is standardisation where evidence supports it, with room for justified clinical exception. Evidence-based clinical pathways can reduce complications and length of stay, although effects vary across settings and outcomes (Rotter et al., 2025). Under DRG financing, pathways should be designed for common high-volume and high-cost conditions: hip fracture, stroke, heart failure, pneumonia, chronic obstructive pulmonary disease exacerbation, sepsis, colorectal surgery, joint replacement, acute coronary syndrome, and common oncological procedures. These pathways should specify diagnostic steps, treatment milestones, mobilisation goals, medication reconciliation, escalation criteria, patient education, discharge criteria, and post-discharge follow-up.

A pathway-based hospital does not mean a rigid hospital. Rather, it means that variation must be visible, explainable, and clinically justified. For example, a frail older patient with heart failure, renal impairment, delirium risk, and poor home support should not be forced into the same length-of-stay expectation as a younger patient with an uncomplicated admission. The correct metric is not raw length of stay alone, but observed-to-expected length of stay adjusted for case-mix, frailty, social complexity, and complications.

Discharge planning should begin at admission. Cochrane evidence suggests that structured, individualised discharge planning probably produces small reductions in length of stay and readmissions, and may improve patient satisfaction (Gonçalves-Bradley et al., 2022). In organisational terms, this means that every acute ward should operate daily multidisciplinary board rounds involving physicians, nurses, case managers, pharmacists, therapists, and, where relevant, social workers. Each patient should have an expected date of discharge, a clinical criterion for discharge, a medication plan, a functional plan, and an identified post-acute destination. Delayed discharge should be classified by cause: diagnostic delay, procedure delay, therapy delay, medication issue, family or caregiver barrier, nursing home placement, home-care gap, transport delay, or administrative delay. This classification allows the hospital to distinguish clinical need from system friction.

The emergency department and intensive care unit (ICU) require special attention. DRG efficiency cannot be achieved if the hospital lacks real-time bed management, step-down capacity, weekend diagnostics, senior decision-making at the front door, and rapid access to community alternatives. Acute hospitals should therefore operate command-centre-style flow management, but governed by safety rules: no transfer without clinical stability, no discharge without medication reconciliation and patient understanding, and no bed target that overrides escalation criteria.

Note: Hospital step-down capacity refers to the number of beds dedicated to intermediate care for patients who are too sick for a standard medical-surgical ward but do not require the intensive, round-the-clock monitoring of an Intensive Care Unit (ICU). Also known as Step-Down Units (SDUs), Intermediate Care Units (IMCs), or High Dependency Units (HDUs), this capacity bridges the gap in acuity, optimizing resource allocation and improving patient flow.

Clinical Documentation Integrity and Coding Accuracy

The third requirement is a mature clinical documentation integrity system. DRG reimbursement depends on coded diagnoses, procedures, complications, co-morbidities, and, in some systems, severity or complexity modifiers. Poor documentation can understate case complexity, distort outcome benchmarking, misallocate resources, and produce unfair comparisons between services. Conversely, aggressive coding that lacks clinical truth undermines trust and may expose the hospital to audit risk.

Clinical documentation integrity should therefore be framed as clinical accuracy rather than revenue maximisation. Coders, clinical documentation specialists, physicians, and nurses should work concurrently during the admission, especially in high-risk services such as intensive care, oncology, cardiology, geriatrics, and complex surgery. Queries (questions) to clinicians should be compliant, educational, and clinically grounded. The hospital should audit not only financial yield but also coding validity, present-on-admission (POA) indicators, complication coding, denied claims (external audits), mortality risk adjustment, and documentation of frailty, functional status, and social complexity (SDoH) where nationally permitted.

Accurate case-mix capture also protects clinical services. A ward treating older, frailer, multi-morbid patients will appear inefficient if severity is poorly documented. Similarly, outcome indicators such as mortality, readmission, and length of stay require credible risk adjustment if they are to be used fairly. Documentation should therefore be part of the quality infrastructure: it is the language through which clinical reality becomes visible to payment systems, regulators, researchers, and hospital boards (Xiang et al., 2022).

Patient Safety as a Non-Negotiable Constraint

The fourth requirement is a patient safety system strong enough to resist unsafe financial pressure. Patient safety culture is a core quality strategy, involving leadership commitment, psychological safety, incident reporting, learning systems, teamwork, and systematic risk reduction (Wagner et al., 2019). Under DRG financing, preventable harm has a double significance: it injures patients and consumes scarce resources. Hospital-acquired infections, medication errors, pressure injuries, falls, venous thromboembolism (VTE), surgical complications, missed deterioration, and avoidable intensive care transfers increase suffering, length of stay, staff workload, and cost per case.

The hospital should therefore operate a safety management system with five elements:

1. First, it should maintain visible executive accountability for safety through board-level quality review. 
2. Second, it should support a just culture in which staff can report incidents, near misses, and unsafe conditions without fear of punitive response, while still maintaining accountability for reckless conduct. 
3. Third, it should implement evidence-based safety bundles for high-risk processes, including central lines, urinary catheters, surgical safety, sepsis, medication reconciliation, anticoagulation, falls, pressure injuries, and deterioration. 
4. Fourth, it should use ward-level safety huddles to identify risks in real time. 
5. Fifth, it should link safety data to pathway redesign rather than treating adverse events as isolated failures.

Safety indicators should be reviewed together with financial indicators. If a service line reduces cost per case while complications, mortality, staff turnover, or readmissions worsen, the apparent efficiency gain should be rejected. This is a central principle of DRG governance: financial performance is legitimate only when achieved through safer, smoother, less wasteful care.

Note: Ward-level safety huddles are brief, multidisciplinary, daily clinical meetings - typically lasting 5 to 15 minutes - designed to proactively identify patient safety risks, share critical information, and foster a collaborative safety culture at the frontline of care. Rather than focusing on solving complex clinical issues or conducting a traditional ward round, their primary goal is to establish situational awareness and anticipate issues before they lead to patient harm.

Workforce Well-Being and Professional Capacity

The fifth requirement is explicit protection of clinician well-being. The Quadruple Aim added the work life of health professionals to the earlier Triple Aim because exhausted clinicians cannot reliably deliver safe, compassionate, efficient care (Bodenheimer & Sinsky, 2014). The Quintuple Aim then incorporated health equity as a further imperative (Nundy et al., 2022). Burnout is not merely an individual resilience problem; it is an organisational signal that workload, staffing, documentation burden, moral distress, leadership, or professional control may be misaligned.

Systematic reviews associate physician burnout with lower quality of care, reduced professional engagement, and higher career disengagement (Hodkinson et al., 2022). Nurse burnout is also associated with poorer safety climate, adverse events, missed care, lower quality ratings, and lower patient satisfaction (Li et al., 2024). In a DRG-financed hospital, the temptation may be to reduce staffing to improve short-term margins. This is a false economy when it increases complications, turnover, agency costs, sickness absence, readmissions, or failure to rescue.

Workforce strategy should therefore include minimum safe staffing principles, workload-adjusted staffing, protected time for governance participation, investment in team training, reduction of low-value documentation, digital tools designed with clinical users, and administrative support for high-burden specialties. Nurse and physician leaders should jointly review staffing, acuity, overtime, missed breaks, sickness absence, turnover, and safety events. Cost containment should be achieved by eliminating waste, not by depleting the professional capacity required to deliver safe care.

Health Equity and Social Determinants of Health (SDoH)

The sixth requirement is to incorporate equity into the acute hospital’s core operating model. The Quintuple Aim makes equity a central objective, not an optional community programme (Nundy et al., 2022). Social determinants of health (SDoH) - such as housing, food security, income, transport, education, language, discrimination, and social support - shape both admission risk and recovery after discharge (World Health Organization, n.d.). A DRG system that ignores these factors may penalise hospitals serving more deprived populations or encourage premature discharge of patients whose social circumstances make recovery fragile (lemon dropping, cherry picking).

Hospitals should therefore screen patients, particularly high-risk admitted patients, for health-related social needs such as housing instability, food insecurity, transport barriers, utility needs, interpersonal safety, social isolation, and inability to obtain medicines. The Accountable Health Communities screening model provides one example of a structured approach to identifying social needs and connecting patients with navigation and community resources (Billioux et al., 2017; Centers for Medicare & Medicaid Services, n.d.). In Europe, the precise screening tool and referral network should be adapted to national welfare systems, primary care structures, municipal services, and community organisations.

Equity must also be measured. The hospital should stratify key indicators by age, sex, socioeconomic status (SES), migrant status where legally and ethically permissible, disability, language need, geography, and other locally relevant variables. These indicators should include readmissions, emergency reattendance, delayed discharge, complications, mortality, patient experience, complaints, missed appointments, and access to elective procedures. Predictive analytics should be audited for bias, since models trained on historical utilisation may reproduce inequitable patterns of care.

Note: A person's address often dictates their health outcomes more than genetics (zip code effect). Often called the Social Determinants of Health (SDoH), your location heavily influences your access to nutritious food (food swamps, food deserts), quality healthcare (healthcare (or medical) desert), green spaces (environmental exposure), and safe housing (built environment), creating massive disparities in overall (healthy) life expectancy (e.g. wealthy suburbs and pauperized inner cities).

Note: In healthcare economics and policy, cherry picking and lemon dropping describe the two sides of adverse patient selection driven by financial or performance incentives. Cherry Picking occurs when healthcare providers and/or insurers intentionally select healthier, lower-risk, or wealthier patients who are less complex and cheaper to treat. This maximizes profit margins and improves public quality ratings. Lemon Dropping is the reciprocal practice of refusing care, dismissing, or transferring high-risk, medically complex, or non-compliant patients ("lemons") to avoid costly complications and financial penalties.

Data Analytics, Balanced Scorecards, and Learning Systems

The seventh requirement is an analytics infrastructure that supports learning rather than blame. DRG systems generate large quantities of administrative data, but administrative data alone are insufficient. A well-organised hospital should combine DRG data with electronic health record (EHR) data, staffing data, incident reports, patient-reported outcomes, patient experience data, cost-accounting data, and community-care transition data.

Each service line should maintain a clinically relevant balanced scorecard. The financial domain should include cost per case, tariff-to-cost variance, contribution margin, theatre utilisation, implant and drug cost, diagnostic cost, and avoidable bed-days. The clinical domain should include mortality, complications, escalation to intensive care, infection rates, readmissions, reoperations, and evidence-based process adherence. The patient domain should include experience, complaints, communication, shared decision-making, and patient-reported recovery where available. The workforce domain should include staffing adequacy, turnover, burnout, sickness absence, overtime, and participation in governance. The equity domain should stratify outcomes and access indicators across relevant demographic and social groups (Jaber et al., 2022).

Predictive analytics can help identify patients at risk of prolonged length of stay, readmission, deterioration, or complex discharge, but such tools should augment multidisciplinary judgment rather than replace it. Many readmission prediction models have historically shown limited performance across settings, so local validation, recalibration, and fairness auditing are essential. Analytics should therefore be embedded in clinical workflows: daily ward dashboards, discharge-risk flags, pharmacy alerts, deterioration risk scores, and service-line review meetings. Data should trigger inquiry: Why is this DRG group more costly? Why are readmissions higher for this population? Why does this ward have more falls? Why are nurses reporting missed care? The purpose of measurement is organisational learning.

Note: A clinically relevant Balanced Scorecard (BSC) adapts the traditional corporate strategic framework to place patient health outcomes and safety at the pinnacle of organizational success. While a standard business scorecard centers primarily on maximizing financial returns, a clinical BSC flips the hierarchy, ensuring that all financial, operational, and educational objectives directly support delivering high-quality, evidence-based care.

Integrating Cost Containment With Co-Governance

The central tension in DRG-financed hospitals is that cost pressure is real, but unsafe or inequitable cost cutting is unacceptable. Co-governance resolves this tension by requiring that financial decisions pass through clinical and nursing judgment. A practical operating compact can be stated as follows: the hospital will reduce waste, unwarranted variation, avoidable harm, unnecessary waiting, duplicative testing, and preventable bed-days; it will not reduce necessary staffing, discharge patients unsafely, deny clinically indicated care, or hide social complexity to meet financial targets.

This compact should be operationalised through service-line agreements (SLA). Each service line should agree annually on pathway priorities, quality targets, clinical documentation priorities, workforce risks, equity goals, and financial improvement plans. For example, an orthopaedic service may reduce implant variation and improve theatre start times while protecting infection prevention, rehabilitation access, and discharge education. A cardiology service may standardise heart-failure pathways and medication optimisation while improving post-discharge follow-up. A geriatric medicine service may reduce delayed transfers by strengthening early functional assessment and community coordination, while explicitly documenting frailty and social need.

Incentives should be carefully designed. Performance bonuses or internal investment decisions should not be based solely on financial surplus. They should require achievement of safety, patient experience, workforce, and equity thresholds. Similarly, internal benchmarking should compare like with like: case-mix, frailty, deprivation, emergency status, teaching responsibilities, and referral complexity must be considered. Fairness in measurement is essential for professional legitimacy.

Conclusion

An acute hospital can succeed under DRG financing only if it refuses to reduce hospital management to tariff management. DRGs provide a useful language for case-mix, resource use, cost variation, and productivity, but they are incomplete measures of value. The organising principle should be a co-governed clinical operating system: physicians, nurses, and managers jointly designing pathways, managing resources, improving documentation, protecting safety, supporting staff, coordinating transitions, and measuring equity.

The most effective hospital under DRG financing is therefore not the hospital with the shortest length of stay or the highest coding yield. It is the hospital that uses case-mix-adjusted data to deliver necessary care reliably, safely, efficiently, and equitably; that reduces avoidable variation without suppressing clinical judgment; that treats workforce well-being as a safety requirement; and that views discharge not as the end of the hospital’s responsibility, but as a critical transition in the patient’s full episode of care. In this model, cost containment and the Quintuple Aim are not opposing agendas. They are reconciled through co-governance, transparency, disciplined pathway management, and a commitment to value rather than volume.

References

Aiken, L. H., Sloane, D. M., Bruyneel, L., Van den Heede, K., Griffiths, P., Busse, R., Diomidous, M., Kinnunen, J., Kózka, M., Lesaffre, E., McHugh, M. D., Moreno-Casbas, M. T., Rafferty, A. M., Schwendimann, R., Scott, P. A., Tishelman, C., van Achterberg, T., & Sermeus, W. (2014). Nurse staffing and education and hospital mortality in nine European countries: A retrospective observational study. The Lancet, 383(9931), 1824–1830.

Bernstein, D. N., Reitblat, C., van de Graaf, V. A., O’Donnell, E., Philpotts, L. L., Terwee, C. B., & Poolman, R. W. (2021). Is there an association between bundled payments and “cherry picking” and “lemon dropping” in orthopaedic surgery? A systematic review. Clinical Orthopaedics and Related Research®, 479(11), 2430-2443.

Berwick, D. M., Nolan, T. W., & Whittington, J. (2008). The Triple Aim: Care, health, and cost. Health Affairs, 27(3), 759–769.

Billioux, A., Verlander, K., Anthony, S., & Alley, D. (2017). Standardized screening for health-related social needs in clinical settings: The Accountable Health Communities Screening Tool. NAM Perspectives. National Academy of Medicine.

Bodenheimer, T., & Sinsky, C. (2014). From Triple to Quadruple Aim: Care of the patient requires care of the provider. Annals of Family Medicine, 12(6), 573–576.

Busse, R., Geissler, A., Quentin, W., & Wiley, M. (Eds.). (2011). Diagnosis-related groups in Europe: Moving towards transparency, efficiency and quality in hospitals. Open University Press.

Busse, R., Schreyögg, J., & Smith, P. C. (2013). Diagnosis related groups in Europe: Moving towards transparency, efficiency, and quality in hospitals? BMJ, 346, f3197.

Centers for Medicare & Medicaid Services. (n.d.). Accountable Health Communities Model. Retrieved June 19, 2026.

Gonçalves-Bradley, D. C., Lannin, N. A., Clemson, L. M., Cameron, I. D., & Shepperd, S. (2022). Discharge planning from hospital. Cochrane Database of Systematic Reviews, 2022(2), CD000313.

Hodkinson, A., Zhou, A., Johnson, J., Geraghty, K., Riley, R., Panagopoulou, E., Chew-Graham, C. A., Peters, D., Esmail, A., & Panagioti, M. (2022). Associations of physician burnout with career engagement and quality of patient care: Systematic review and meta-analysis. BMJ, 378, e070442. 

Humbyrd, C. J. (2018). The ethics of bundled payments in total joint replacement:“cherry picking” and “lemon dropping”. The Journal of clinical ethics, 29(1), 62-68.

Jaber, A. A. A., Nashwan, A. J., & AbuJaber, A. (2022). Balanced scorecard-based hospital performance measurement framework: a performance construct development approach. Cureus, 14(5).

Kelly, L. A., McHugh, M. D., & Aiken, L. H. (2011). Nurse outcomes in Magnet and non-Magnet hospitals. Journal of Nursing Administration, 41(10), 428–433.

Kutney-Lee, A., Germack, H., Hatfield, L., Kelly, S., Maguire, P., Dierkes, A., Del Guidice, M., & Aiken, L. H. (2016). Nurse engagement in shared governance and patient and nurse outcomes. Journal of Nursing Administration, 46(11), 605–612.

Li, L. Z., Yang, P., Singer, S. J., Pfeffer, J., Mathur, M. B., & Shanafelt, T. (2024). Nurse burnout and patient safety, satisfaction, and quality of care: A systematic review and meta-analysis. JAMA Network Open, 7(11), e2443059.

Nundy, S., Cooper, L. A., & Mate, K. S. (2022). The Quintuple Aim for health care improvement: A new imperative to advance health equity. JAMA, 327(6), 521–522. 

Porter, M. E. (2010). What is value in health care? New England Journal of Medicine, 363(26), 2477–2481.

Rotter, T., Kinsman, L. D., Alsius, A., Scott, S. D., Lawal, A., Ronellenfitsch, U., Plishka, C., Groot, G., Woods, P., Coulson, C., Bakel, L. A., Sears, K., Ross-White, A., Machotta, A., & Schultz, T. J. (2025). Clinical pathways for secondary care and the effects on professional practice, patient outcomes, length of stay and hospital costs. Cochrane Database of Systematic Reviews, 2025(5), CD006632. 

Tan, S. S., Geissler, A., Serdén, L., Heurgren, M., van Ineveld, B. M., Redekop, W. K., & Hakkaart-van Roijen, L. (2014). DRG systems in Europe: Variations in cost accounting systems among 12 countries. European Journal of Public Health, 24(6), 1023–1028. 

Wagner, C., Kristensen, S., Sousa, P., & Panteli, D. (2019). Patient safety culture as a quality strategy. Improving Healthcare Quality in Europe: Characteristics, Effectiveness and Implementation of Different Strategies; Busse, R., Klazinga, N., Panteli, D., Quentin, W., Eds, 287-308.

World Health Organization. (n.d.). Social determinants of health. Retrieved June 19, 2026.

Xiang, J., et al. (2022). Measuring case severity: A novel tool for benchmarking and clinical documentation improvement. BMC Health Services Research, 22, Article 849. 

Zou, K., Li, H.-Y., Zhou, D., & Liao, Z.-J. (2020). The effects of diagnosis-related groups payment on hospital healthcare in China: A systematic review. BMC Health Services Research, 20, Article 112.

Peter Van Osta. An essay concerning a new healthcare (the origin of parts of this text).