Hospital Care

Six problem-based group scenarios focusing on hospital capacity planning, quality of care, healthcare financing, and hospital organization within the Bulgarian healthcare system.
Hospital care
Social medicine
Public health
Assignment
Author

Kostadin Kostadinov

Published

March 20, 2026

Instructions:

This document contains six problem-based group scenarios designed for interactive work in social medicine and public health workshops. Each group will analyze a specific case study focusing on hospital capacity planning, quality of care, healthcare financing, and hospital organization within the Bulgarian healthcare system.

Reference Material

This assignment is based on the reading material: Hospital Care in Bulgaria: Functions, Structure, Hospitalization, and Quality. All problem solving, indicator calculations, and organizational structures must align with the concepts established in this text.

General Instructions for Students

Each group will independently solve a distinct hospital-care problem. Your task is to:

  1. Work through the Scenario: Read your assigned scenario carefully.
  2. Perform the Required Tasks: Complete the calculations or answer the specific regulatory/organizational questions in sequence. Show all working for calculations.
  3. Prepare the Discussion Question: Prepare a brief answer (3–5 sentences) for the final discussion question attached to your scenario, which you will present to the class.
  4. Synthesis Task: At the end of the class, all groups will jointly complete the final synthesis task based on insights drawn from all six scenarios.

Scenario 1 — The Struggling Municipal Hospital

Capacity Planning and Efficiency at MHAT “Dr. Petar Bonev,” Vidin

The scenario. MHAT “Dr. Petar Bonev” is a municipal multiprofile hospital for active treatment in Vidin, a town in north-western Bulgaria with a rapidly ageing and shrinking population. The municipality’s population has declined from 63,000 in 2015 to 48,500 in 2025. The hospital operates 280 beds across six departments: internal medicine (70 beds), surgery (55 beds), obstetrics-gynaecology (30 beds), paediatrics (25 beds), neurology (50 beds), and an intensive care unit (20 beds with continuous monitoring). In 2025, the hospital recorded 8,960 admissions and 128,100 occupied bed-days. The internal medicine department alone recorded 2,870 admissions and 40,180 bed-days, while the obstetrics-gynaecology department recorded 640 admissions and 5,760 bed-days. The hospital also recorded 395 inpatient deaths, of which 52 occurred within the first 24 hours of admission. Following discharge, 312 patients were readmitted to the hospital within 30 days.

Task 1.1. Calculate the overall bed provision rate for Vidin municipality (beds per 1,000 population). Classify it as low, medium, high, or very high.

Bed provision rate = 280 / 48,500 × 1,000 = 5.77 beds per 1,000 population.

This falls in the medium category (4–7 per 1,000). However, given the ageing population and declining denominator, the rate has been rising mechanically without any increase in actual beds, which creates an illusion of adequate supply.

Task 1.2. Calculate the overall bed occupancy rate, the average length of stay, and the bed turnover for the hospital as a whole.

Bed occupancy rate = 128,100 / (280 × 365) × 100 = 128,100 / 102,200 × 100 = 125.3%.

This figure exceeds 100%, which is technically possible when temporary (extra) beds or corridor beds are used, or when patient-days are counted beyond nominal bed capacity. It signals severe overcrowding.

Average length of stay = 128,100 / 8,960 = 14.3 days.

Bed turnover = 8,960 / 280 = 32 patients per bed per year.

Compared to the national average of 4.9 days ALOS and 45 patients per bed turnover (2024), this hospital has substantially longer stays and lower turnover, suggesting inefficiency or a case mix dominated by chronic and complex patients.

Task 1.3. Calculate the same three indicators for the internal medicine department and the obstetrics-gynaecology department separately. Compare the two departments.

Internal medicine: occupancy = 40,180 / (70 × 365) × 100 = 40,180 / 25,550 × 100 = 157.3%; ALOS = 40,180 / 2,870 = 14.0 days; turnover = 2,870 / 70 = 41.0 patients/bed.

Obstetrics-gynaecology: occupancy = 5,760 / (30 × 365) × 100 = 5,760 / 10,950 × 100 = 52.6%; ALOS = 5,760 / 640 = 9.0 days; turnover = 640 / 30 = 21.3 patients/bed.

Internal medicine is catastrophically overcrowded (>150% occupancy) while obstetrics-gynaecology is substantially underutilised (<53%). This reflects the ageing population driving medical admissions upward while the declining birth rate reduces obstetric demand. The ALOS in obstetrics-gynaecology (9.0 days) is also notably high — the national average for maternity-related pathways is considerably shorter.

Task 1.4. Calculate the overall inpatient mortality rate and the 24-hour mortality rate as a percentage of all deaths.

Inpatient mortality rate = 395 / 8,960 × 100 = 4.4%.

24-hour mortality as a proportion of all deaths = 52 / 395 × 100 = 13.2%.

The overall mortality rate (4.4%) is substantially above the national average and may reflect the hospital’s case mix (ageing population, late presentations, limited referral options in north-western Bulgaria) or delayed access to care. The 24-hour mortality proportion (13.2%) may indicate patients arriving in very advanced disease states or with delayed emergency care.

Task 1.5. Calculate the 30-day readmission rate.

Readmission rate = 312 / (8,960 − 395) × 100 = 312 / 8,565 × 100 = 3.6%.

The denominator uses total discharges (admissions minus deaths). A 3.6% readmission rate is relatively low, but interpretation requires caution: in a region with limited healthcare access, patients who should be readmitted may not return to the hospital due to distance, transport barriers, or resignation.

Discussion question. The hospital director proposes closing the obstetrics-gynaecology department and reallocating its 30 beds to internal medicine to address overcrowding. As a public health adviser, what factors would you consider before supporting or opposing this proposal?

Factors to consider include: (a) whether closing obstetrics-gynaecology would force pregnant women to travel to the nearest alternative hospital and what distance/risk this entails; (b) the minimum clinical pathway requirements for obstetric care in the region under the National Health Map; (c) the demographic projections — if birth numbers will continue declining, maintaining 30 beds is unsustainable, but eliminating obstetric services entirely creates a coverage gap; (d) whether a compromise such as reducing obstetric beds (e.g., from 30 to 12) and reallocating the remainder could maintain essential maternity care while relieving internal medicine pressure; (e) implications for university hospital designation and specialist training; (f) the social dimension — for a rural municipality, closing maternity services carries significant symbolic and practical consequences for young families considering whether to remain.

Scenario 2 — The Emergency Boarding Crisis

Analysing Emergency Department Dysfunction at UMHAT “St. Marina,” Varna

The scenario. Dr. Elena Stoyanova is a newly appointed quality manager at UMHAT “St. Marina,” a large university multiprofile hospital in Varna. Over the past year, the emergency department has experienced growing boarding times — patients admitted from the emergency department wait for inpatient beds while remaining physically in the emergency department. During October 2025, the emergency department registered 4,250 visits. Of these, 680 resulted in a decision to hospitalise. Among hospitalised patients, 238 waited more than 4 hours for an inpatient bed, and 41 waited more than 24 hours. The hospital has 620 active treatment beds, of which on average 558 were occupied on any given day during October. Only 38 beds were designated for emergency admissions (against the regulatory minimum of 10%). During the same month, 14 patients left the emergency department without being seen (LWBS) and 6 filed formal complaints about waiting times.

Task 2.1. Calculate the hospitalisation rate from emergency department visits in October.

Hospitalisation rate = 680 / 4,250 × 100 = 16.0%.

This is somewhat above the international average of approximately 10.6% for emergency department visits resulting in hospitalisation. The higher rate may reflect the hospital’s role as a tertiary referral centre receiving more complex cases, or potentially excessive admission thresholds for lower-acuity conditions.

Task 2.2. What percentage of admitted patients experienced boarding of more than 4 hours? More than 24 hours?

Boarding > 4 hours: 238 / 680 × 100 = 35.0%.

Boarding > 24 hours: 41 / 680 × 100 = 6.0%.

Both figures indicate serious capacity strain. For comparison, national US data showed that by 2024 approximately 25% of admitted patients boarded for over 4 hours during non-peak months and nearly 5% for over 24 hours. This hospital’s rates exceed even those benchmarks.

Task 2.3. Calculate the overall bed occupancy rate for October. Does the hospital meet the 10% emergency bed reservation requirement?

Bed occupancy = (558 × 31) / (620 × 31) × 100 = 558 / 620 × 100 = 90.0%.

Emergency bed reservation: 10% of 620 = 62 beds required. Only 38 beds are designated, which is 61.3% of the legal requirement. The hospital is in regulatory non-compliance.

A 90% occupancy rate is at the upper boundary of the optimal range (80–90%). Combined with insufficient emergency bed reserves, this creates the boarding problem: when occupancy exceeds 85–90%, the probability of finding a bed for an incoming emergency admission drops sharply.

Task 2.4. The hospital’s average length of stay in October was 6.2 days. If discharge planning improvements could reduce ALOS by 1 day, how many additional bed-days would be freed monthly, and how many additional patients could theoretically be admitted?

Current total admissions in October are not fully specified, but using the 680 emergency admissions plus planned admissions — let us approximate from the occupancy data. Total occupied bed-days = 558 × 31 = 17,298. At ALOS = 6.2 days, total admissions ≈ 17,298 / 6.2 = 2,790 admissions.

If ALOS decreases by 1 day to 5.2 days: freed bed-days = 2,790 × 1 = 2,790 bed-days per month.

Additional patients at new ALOS of 5.2 days: 2,790 / 5.2 ≈ 536 additional patients per month.

This demonstrates the powerful efficiency gains from even modest reductions in length of stay. A 1-day reduction could potentially eliminate the boarding problem entirely by creating sufficient bed availability.

Discussion question. Dr. Stoyanova must present an action plan to the hospital board. What combination of short-term and long-term measures would you recommend to address the boarding crisis?

Short-term measures: (a) immediately increase emergency-designated beds to at least 62 to meet the 10% regulatory requirement; (b) implement daily bed management huddles to identify discharge-ready patients early; (c) introduce a discharge planning protocol starting at admission rather than the day before discharge; (d) establish clear criteria for “discharge by noon” for suitable patients. Long-term measures: (e) introduce a structured discharge planning framework such as IDEAL; (f) develop ambulatory care pathways for conditions currently requiring admission (e.g., short-stay observation units for chest pain, cellulitis); (g) negotiate with the regional health inspectorate to establish post-acute care capacity (community nursing, home care) to enable earlier safe discharge; (h) implement real-time bed tracking visible to ED staff. The quality manager should also conduct root-cause analysis of the 41 patients who boarded >24 hours to determine whether specific specialties or bed types are bottlenecks.

Scenario 3 — The Social Admission Dilemma

Hospitalization Indications and Patient Rights at MHAT “Dr. Atanas Dafovski,” Kardzhali

The scenario. Dr. Nikolay Dimitrov is a young internist at a municipal hospital in Kardzhali, a town in the eastern Rhodope mountains with a significant elderly population living in remote villages. He faces three patients in one morning, each presenting a different combination of medical and social indications for hospitalisation.

Patient A: Mrs. Fatme Mehmedova, 78, lives alone in a village 35 km from Kardzhali, without public transport connections. She presents with community-acquired pneumonia (temperature 38.9°C, respiratory rate 24/min, oxygen saturation 93% on room air). Her CURB-65 score is 2 (confusion absent, urea elevated, respiratory rate elevated, blood pressure normal, age ≥65). She has no family in Bulgaria; her children emigrated to Germany five years ago. She cannot afford the antibiotics prescribed for outpatient treatment and has no means to reach a pharmacy or return for follow-up. She wants to be hospitalised.

Patient B: Mr. Georgi Kolev, 55, a self-employed carpenter, presents with a stable, uncomplicated lower back pain episode. His pain is moderate (VAS 5/10), neurological examination is normal, and outpatient management with analgesics and physiotherapy would be clinically appropriate. However, Mr. Kolev insists on hospitalisation because he believes hospital care is “more serious” and he has heard that workers who are hospitalised receive higher sick leave benefits. He refuses to leave the emergency department. His health insurance is current.

Patient C: Ms. Radka Petrova, 42, presents after a domestic violence incident. She has facial bruising, a suspected nasal fracture, and acute anxiety. The nasal fracture, if confirmed, requires only outpatient management (reduction under local anaesthesia). However, she states that she is afraid to return home and has nowhere else to go. She does not know about social services and has no family support.

Task 3.1. For each patient, classify the hospitalisation indication as medical, social, or medico-social. Justify each classification in 2–3 sentences.

Patient A — Medico-social (mixed): the pneumonia with a CURB-65 score of 2 represents a borderline medical indication for hospitalisation (some guidelines recommend hospitalisation at CURB-65 ≥ 2). However, the decisive factors are inseparably intertwined: even if her pneumonia could technically be managed at home, the absence of a caregiver, inability to afford medications, lack of transport, and remote location make outpatient treatment impossible. The medical and social factors cannot be meaningfully separated.

Patient B — Neither medical nor social: uncomplicated lower back pain with normal neurological examination has no medical indication for hospitalisation. The patient’s desire for hospitalisation is based on incorrect beliefs about sick leave benefits and a cultural preference for hospital care, neither of which constitutes a legitimate social indication (social indications require that the patient’s condition makes home care impossible, not merely that the patient prefers hospitalisation). The physician should explain this clearly.

Patient C — Social indication (with minor medical needs): the suspected nasal fracture does not require hospitalisation for medical management. However, the domestic violence context, fear of returning home, lack of social support, and acute psychological distress constitute a genuine social indication. The hospital’s social function includes identifying social determinants contributing to illness and connecting patients with social services.

Task 3.2. For Patient A, Dr. Dimitrov decides to admit her under Clinical Pathway X for community-acquired pneumonia. The pathway requires a minimum stay of 48 hours. What documentation must accompany the admission, and what happens when Mrs. Mehmedova is ready for discharge but still has no family support?

Documentation: a hospitalization referral (valid for 30 days) from the admitting physician or the consultative-diagnostic block; an outpatient examination record documenting medical history, objective findings, diagnostic activities, and justification that therapeutic goals cannot be achieved in outpatient care; laboratory tests performed within the previous 7 days; any relevant imaging within 30 days.

At discharge: the hospital must issue a discharge epicrisis in three copies (patient, outpatient provider, hospital archive) containing passport data, admission date, final ICD diagnosis, clinical pathway number, therapeutic scheme, medications, and follow-up recommendations. Mrs. Mehmedova is entitled to two free follow-up examinations within 30 days.

If family support is absent: under Bulgarian law, when a hospitalized patient requires accompaniment for discharge and family members are unavailable or unwilling, the hospital must inform the Social Assistance Directorate to arrange appropriate social service placement. Dr. Dimitrov must initiate this referral before discharge.

Task 3.3. For Patient B, what are the patient’s rights regarding refusal of the physician’s recommendation for outpatient treatment? What documentation is required if the patient insists on refusing to leave?

Patient B has the right to accept or reject proposed treatment. However, the right to reject treatment does not automatically create a right to demand hospitalisation when medical indications are absent. Under the clinical pathway system, hospitalisation can only occur when clinical presentations satisfy defined pathway indications with specific ICD codes and severity thresholds.

If Mr. Kolev refuses the recommended outpatient plan and demands hospitalisation, Dr. Dimitrov should: (a) explain that no medical indication exists; (b) document the patient’s refusal of the recommended outpatient treatment in the medical records, with the patient’s signature; (c) if the patient is actively negative and refuses to leave, involve the senior on-duty physician; (d) avoid admitting the patient solely to avoid conflict, as this would constitute inappropriate utilisation of NHIF resources and could trigger sanctions during audit.

Discussion question. Patient C’s situation involves domestic violence. Beyond the immediate medical treatment of the nasal fracture, what obligations does the hospital have, and what services should Dr. Dimitrov activate?

The hospital’s social function requires identifying social determinants contributing to illness and supporting psychosocial adaptation. For Patient C, Dr. Dimitrov should: (a) provide immediate medical treatment for the nasal fracture and document all injuries meticulously as potential forensic evidence; (b) offer access to psychological support (psychotherapist services are a patient right during hospitalisation); (c) inform the Social Assistance Directorate, which can connect Ms. Petrova with crisis centres for domestic violence victims and temporary shelter; (d) inform her about her right to file a police complaint and seek a protection order under the Protection Against Domestic Violence Act; (e) if a short-term admission is justified for observation and safety while social services are mobilised, this constitutes a legitimate social indication. The case illustrates how hospital social functions extend beyond purely medical care into coordinating community responses to social determinants of health.

Scenario 4 — The Quality Audit

Performance Indicators and Discharge Planning at a Private Hospital in Sofia

The scenario. “Vita” Private Hospital in Sofia is a specialised hospital for active treatment in orthopaedic surgery. The hospital has 85 beds and contracts with the NHIF for 12 clinical pathways covering joint replacement, fracture fixation, arthroscopic procedures, and spinal surgery. In 2025, the hospital reported the following data: 5,100 admissions, 19,380 occupied bed-days, 15 inpatient deaths, 204 postoperative complications (78 wound infections, 56 deep vein thromboses, 42 reoperations, 28 other), and 382 unplanned readmissions within 30 days. The hospital offers physician choice at €200 and team choice at €400. During an inspection, the Executive Agency “Medical Supervision” found that 23 patients had been charged €350 for physician choice and that the hospital’s price list did not display the regulatory maximum limits.

Task 4.1. Calculate the average length of stay, bed occupancy rate, and bed turnover for the hospital.

ALOS = 19,380 / 5,100 = 3.8 days.

Bed occupancy = 19,380 / (85 × 365) × 100 = 19,380 / 31,025 × 100 = 62.5%.

Bed turnover = 5,100 / 85 = 60.0 patients per bed per year.

The ALOS of 3.8 days is below the national average (4.9 days), consistent with the focused surgical profile and contemporary enhanced recovery after surgery (ERAS) protocols. Bed turnover of 60 is well above the national average (45) — reflecting the high throughput of a specialised surgical unit. However, bed occupancy of 62.5% is below the optimal 80–90% range, suggesting the hospital may have excess bed capacity relative to its current patient volume.

Task 4.2. Calculate the overall postoperative complication rate, the hospital-acquired infection rate (wound infections only), and the reoperation rate.

Postoperative complication rate = 204 / 5,100 × 100 = 4.0%.

Wound infection rate = 78 / 5,100 × 100 = 1.5%.

Reoperation rate = 42 / 5,100 × 100 = 0.8%.

The overall complication rate (4.0%) is substantially above the national average (0.5%), but direct comparison is misleading: the national figure includes all hospital types, while this is a pure surgical facility where every patient undergoes an operative procedure. Orthopaedic surgery, particularly joint replacement, carries inherent complication risks. However, the wound infection rate of 1.5% warrants attention — benchmark rates for primary joint replacement surgical site infections are typically 1–2%, placing this hospital at the upper boundary. The DVT rate (56/5,100 = 1.1%) also suggests potential for improvement in thromboprophylaxis protocols.

Task 4.3. Calculate the 30-day readmission rate. What are three possible explanations for the figure you obtain?

Readmission rate = 382 / (5,100 − 15) × 100 = 382 / 5,085 × 100 = 7.5%.

Possible explanations: (a) premature discharge — with an ALOS of 3.8 days and financial incentives to minimise length of stay, some patients may be discharged before achieving adequate stability for home management; (b) inadequate discharge planning — insufficient patient education about wound care, medication management (especially anticoagulants for DVT prophylaxis), warning signs requiring medical attention, and activity restrictions; (c) complications manifesting after discharge — wound infections and DVTs may develop days to weeks after surgery and generate readmissions that were not preventable through longer initial stays but may have been mitigated through better follow-up arrangements. Approximately 27% of 30-day readmissions are potentially preventable through improved discharge processes.

Task 4.4. Regarding the physician choice fee violations: what specific regulations has the hospital breached, and what are the correct regulatory maximums in EUR?

The hospital has breached two regulations: (a) charging €350 for physician choice exceeds the legal maximum of €256 (500 BGN); (b) failing to display the regulatory maximum limits on the price list violates transparency requirements. Under Bulgarian law, the hospital’s price list must clearly state the maximum regulatory caps. Additionally, differential pricing based on procedure complexity or physician characteristics (rank, academic degree, experience) is prohibited — prices must be uniform regardless of these variables. The 23 patients who were overcharged are entitled to refunds of the excess amount (€350 − €256 = €94 each). The Executive Agency “Medical Supervision” may impose administrative penalties and issue mandatory prescriptions for corrective action.

Discussion question. The hospital’s readmission rate (7.5%) is considerably higher than the municipal hospital in Scenario 1 (3.6%). Does this necessarily mean the private hospital provides worse quality care? What contextual factors should be considered before drawing conclusions?

Direct comparison is inappropriate without adjusting for case mix, specialty profile, and measurement differences. The private hospital is a specialised surgical facility where all patients undergo operative procedures carrying inherent complication and readmission risks, while the municipal hospital treats a broader mix including many medical (non-surgical) patients with lower readmission profiles. Additionally, the private hospital’s very short ALOS (3.8 vs. 14.3 days) may shift complications from the inpatient to the post-discharge period, making them visible as readmissions rather than being managed during the initial stay. Geographic access also matters: patients discharged from a hospital in Sofia have ready access to emergency care for re-presentation, whereas patients in Vidin may not return due to distance. Finally, the private hospital may have more complete data capture (documenting all returns), while the municipal hospital may undercount readmissions if patients present elsewhere. Valid quality comparison requires risk-adjusted metrics accounting for surgical volume, procedure complexity, patient comorbidities, and age.

Scenario 5 — The True Cost of “Free” Healthcare

Hospital Funding, Clinical Pathways, and Out-of-Pocket Payments

The scenario. Mr. Ivan Petrov, 45, is admitted to UMHAT “St. Ivan Rilski” in Sofia for a planned orthopaedic surgery (joint replacement). He is fully insured under the National Health Insurance Fund (NHIF). The NHIF reimburses the hospital prospectively for this specific clinical pathway. Mr. Petrov’s inpatient stay lasts 7 days. During the admission process, the patient voluntarily requests the following additional non-medical services: to be operated on by a specific, highly requested surgical team, and a private room with enhanced amenities, priced by the hospital at €20 per day. Additionally, the implantable medical device required for the surgery costs €1,200, which is not covered by the standard NHIF benefits package.

Task 5.1. Calculate the statutory daily user fee for Mr. Petrov’s 7-day hospital stay according to Bulgarian regulations. What is the annual limit?

The daily user fee for hospital treatment in Bulgaria is €0.51. For a 7-day stay, the fee is 7 × €0.51 = €3.57.

The annual limit for user fees is capped at 10 days per calendar year. Therefore, even if Mr. Petrov requires another hospitalization later this year, he will only pay for up to 3 more days.

Task 5.2. Assuming the hospital charges the legal maximum for the choice of medical team, what is this fee in EUR?

The legal maximum allowed for the choice of an entire medical team during hospitalization is €460.

(Note: The maximum for a single physician choice is €256, but since he chose a team, the €460 limit applies).

Task 5.3. Calculate the total Out-of-Pocket (OOP) payment for Mr. Petrov, assuming all his requests are met and the hospital charges the legal maximum for the team choice.

Total Out-of-Pocket (OOP) calculation: 1. Statutory user fee: €3.57 2. Choice of team (legal maximum): €460.00 3. Private room (7 days × €20/day): €140.00 4. Implantable medical device (not covered by NHIF): €1,200.00

Total OOP = €3.57 + €460.00 + €140.00 + €1,200.00 = €1,803.57.

Discussion question. Discuss the equity of the Bulgarian healthcare financing model based on this scenario. While the NHIF officially covers the clinical pathway (the algorithm, staff work, and basic medications), the patient’s out-of-pocket expenses are substantial. How do the legal caps on physician and team choice protect patients from financial exploitation, and what are the implications of expensive medical devices falling outside the pathway reimbursement?

This scenario highlights the mixed financing nature of the Bulgarian system and the heavy reliance on out-of-pocket payments, which can be catastrophic for lower-income patients. While the clinical work is “free” at the point of care (covered by social insurance), the full pathway cannot be executed without the expensive medical device, essentially creating a financial barrier to essential care. The legal caps on team choice (€460) and physician choice (€256) were introduced explicitly to regulate informal payments (“under-the-table” money) and prevent hospitals from financially exploiting vulnerable patients with exorbitant fees based on the prestige of the surgeon. However, these caps do not solve the equity problem created when basic health insurance is insufficient to cover the physical materials required for treatment.

Scenario 6 — Building a New Hospital

Hospital Organization, Structural Blocks, and Regulatory Approval

The scenario. A private healthcare investment group, “MedInvest,” wishes to open a new Specialized Hospital for Oncology in Burgas. They recognize a regional deficit in comprehensive cancer care and have secured private funding to construct a state-of-the-art facility. Their business model relies on immediately establishing an inpatient block with 100 active treatment beds, advanced radiotherapy bunkers, and a large outpatient clinic. To ensure financial sustainability, they plan to contract with the National Health Insurance Fund (NHIF) from day one. They have appointed an experienced oncologist as the planned hospital director, though she lacks formal management qualifications.

Task 6.1. According to the Medical Establishments Act, every hospital must be organized into three mandatory functional structural blocks. Identify these three blocks and provide one example of a unit within each block that would be appropriate for this planned oncology hospital.

1. Consultative-diagnostic block: The primary patient interface. Examples include the outpatient registration area, consultative oncology cabinets, medical-diagnostic laboratories, or the imaging department (CT/PET-CT). 2. Inpatient block: The core operational area for hospitalized patients. Examples include the medical oncology clinic with the 100 active treatment beds, the surgical oncology department, or an intensive care unit. 3. Administrative-economic block: The supporting infrastructure. Examples include the hospital pharmacy (critical for handling oncology medications), central sterilization, laundry, food services, or hospital administration.

Task 6.2. Evaluate the planned appointment of the hospital director. Does the proposed candidate meet the legal requirements to lead the institution?

The proposed candidate does not meet the full legal requirements. While she holds a medical degree (as an experienced oncologist), the law explicitly requires the director of a hospital to also hold a formal qualification in health management (or to hold a master’s degree in economics and management combined with health management training). She must acquire this qualification before formally assuming the director role.

Task 6.3. Outline the legal and organizational steps the hospital must take before it can officially open the 100 beds and receive funding from the NHIF.

The hospital cannot simply construct the building and begin billing the NHIF. It must undergo a rigorous regulatory process: 1. Obtain approval from the Council of Ministers, based on a detailed assessment by the Executive Agency “Medical Supervision.” 2. Acquire an operating permit from the Ministry of Health detailing the specific medical specialties and competence levels it may practice. 3. To receive NHIF funding, the new beds and specific clinical pathways must align with the regional needs and capacity limits outlined in the National Health Map. If the Health Map indicates that Burgas region already has sufficient active treatment beds, the NHIF can legally refuse to sign a contract for the new beds.

Discussion question. Why does the state heavily regulate the opening of new hospital beds and NHIF contracting through instruments like the National Health Map? Discuss how an unregulated over-supply of hospital beds might lead to inefficiencies, and conversely, the risks of artificial under-supply.

State regulation through the National Health Map is designed to ensure equitable geographic distribution of healthcare resources and to control public expenditure. Unregulated over-supply of hospital beds often leads to “supplier-induced demand,” where hospitals lower admission thresholds to fill empty beds and generate NHIF revenue, draining public funds on unnecessary hospitalizations instead of cheaper outpatient care. Conversely, artificial under-supply (too few beds relative to population need) results in long waiting lists, delayed interventions, worsened clinical outcomes, and the very boarding crises observed in Scenario 2. The Health Map attempts to balance these extremes by linking public funding to objectively measured regional demographic and epidemiological needs.

Synthesis Task — Cross-Group Discussion

After all groups have presented their scenarios, discuss as a class:

1. Across all six scenarios, which performance indicator proved most useful for identifying quality problems, and which was most misleading when interpreted without context?

2. How do the regulatory mechanisms (clinical pathways, prospective payment, National Health Map) create incentives that can either improve or undermine hospital care quality and efficiency? Use specific examples from the scenarios.

3. The hospitals in these scenarios serve different populations, have different ownership structures (municipal, state university, private), and operate at different scales. How should a national health system account for these differences when setting performance benchmarks and allocating resources?