Towards reliable forecasting of healthcare capacity needs: A scoping review and evidence mapping.

BACKGROUND: The COVID-19 pandemic has highlighted the critical importance of robust healthcare capacity planning and preparedness for emerging crises. However, healthcare systems must also adapt to more gradual temporal changes in disease prevalence and demographic composition over time. To support proactive healthcare planning, statistical capacity forecasting models can provide valuable information to healthcare planners. This systematic literature review and evidence mapping aims to identify and describe studies that have used statistical forecasting models to estimate healthcare capacity needs within hospital settings. METHOD: Studies were identified in the databases MEDLINE and Embase and screened for relevance before items were defined and extracted within the following categories: forecast methodology, measure of capacity, forecast horizon, healthcare setting, target diagnosis, validation methods, and implementation. RESULTS: 84 studies were selected, all focusing on various capacity outcomes, including number of hospital beds/ patients, staffing, and length of stay. The selected studies employed different analytical models grouped in six items; discrete event simulation (N = 13, 15 %), generalized linear models (N = 21, 25 %), rate multiplication (N = 15, 18 %), compartmental models (N = 14, 17 %), time series analysis (N = 22, 26 %), and machine learning not otherwise categorizable (N = 12, 14 %). The review further provides insights into disease areas with infectious diseases (N = 24, 29 %) and cancer (N = 12, 14 %) being predominant, though several studies forecasted healthcare capacity needs in general (N = 24, 29 %). Only about half of the models were validated using either temporal validation (N = 39, 46 %), cross-validation (N = 2, 2 %) or/and geographical validation (N = 4, 5 %). CONCLUSION: The forecasting models' applicability can serve as a resource for healthcare stakeholders involved in designing future healthcare capacity estimation. The lack of routine performance validation of the used algorithms is concerning. There is very little information on implementation and follow-up validation of capacity planning models.

Radiation dose to heart and cardiac substructures and risk of coronary artery disease in early breast cancer patients: A DBCG study based on modern radiation therapy techniques.

BACKGROUND: Coronary artery disease (CAD) has been reported as a late effect following radiation therapy (RT) of early breast cancer (BC). This study aims to report individual RT doses to the heart and cardiac substructures in patients treated with CT-based RT and to investigate if a dose-response relationship between RT dose and CAD exists using modern radiation therapy techniques. METHODS: Patients registered in the Danish Breast Cancer Group database from 2005 to 2016 with CT-based RT were eligible. Among 15,765 patients, the study included 204 with CAD after irradiation (cases) and 408 matched controls. Individual planning CTs were retrieved, the heart and cardiac substructures were delineated and dose-volume parameters were extracted. RESULTS: The median follow-up time was 7.3 years (IQR: 4.6-10.0). Among cases, the median mean heart dose was 1.6 Gy (IQR 0.2-6.1) and 0.8 Gy (0.1-2.9) for left-sided and right-sided patients, respectively (p < 0.001). The highest RT doses were observed in the left ventricle and left anterior descending coronary artery for left-sided RT and in the right atrium and the right coronary artery after right-sided RT. The highest left-minus-right dose-difference was located in the distal part of the left anterior descending coronary artery where also the highest left-versus-right ratio of events was observed. However, no significant difference in the distribution of CAD was observed by laterality. Furthermore, no significant differences in the dose-volume parameters were observed for cases versus controls. CONCLUSIONS: CAD tended to occur in the part of the heart with the highest left-minus- right dose difference, however, no significant risk of CAD was observed at 7 years' median follow-up.

Non-Persistence with Medication as a Mediator for the Social Inequality in Risk of Major Adverse Cardiovascular Events in Patients with Incident Acute Coronary Syndrome: A Nationwide Cohort Study.

AIM: Low socioeconomic status is associated with higher risk of major adverse cardiovascular events (MACE) among patients with incident acute coronary syndrome (ACS). We examined whether non-persistence with antiplatelet and statin therapy mediated the income- and educational-related inequality in risk of MACE. METHODS: Using national registers, all Danish patients diagnosed with incident ACS from 2010 to 2017 were identified. The primary outcome (MACE) comprised all-cause death, cardiac death and cardiac readmission. Risk of MACE was handled by discrete time analyses using inverse probability of treatment weights. The mediator variable comprised non-persistence to a combined 2-dimensional measure of statin and antiplatelet treatment. The mediation analysis was evaluated by population average effects. RESULTS: The study population was 45,874 patients, of whom 16,958 (37.0%) were non-persistent with medication and 16,365 (35.7%) suffered MACE during the median follow-up of 3.5 years. Compared to patients with low income, the adjusted hazard ratio of MACE was lowered by 33% (HR: 0.67, 95% CI: 0.61-0.72) in men and by 34% (HR: 0.66, 95% CI: 0.61-0.72) in women with high income, respectively. Similar results were observed according to level of education. A socioeconomic difference in risk of non-persistence was found in men but not women and only in relation to income. The lower risk of non-persistence observed in high-income men mediated the lower risk of MACE by 12.6% (95% CI: 11.1-14.1%) compared with low-income men. CONCLUSION: Non-persistence with medication mediated some of the income-related inequality in risk of MACE in men, but not women, with incident ACS.

Patients experience more support, information and involvement after first-time hospital accreditation: a before and after study in the Faroe Islands.

BACKGROUND: The impact of hospital accreditation on the experiences of patients remains a weak point in quality improvement research. This is surprising given the time and cost of accreditation and the fact that patient experiences influence outcomes. We investigated the impact of first-time hospital accreditation on patients' experience of support from health-care professionals, information and involvement in decisions. OBJECTIVE: We aimed to examine the association between first-time hospital accreditation and patient experiences. METHODS: We conducted a longitudinal study in the three Faroese hospitals that, unlike hospitals on the Danish mainland and elsewhere internationally, had no prior exposure to systematic quality improvement. The hospitals were accredited in 2017 according to a modified second version of the Danish Healthcare Quality program. Study participants were 18 years or older and hospitalized for at least 24 h in 2016 before or 2018 after accreditation. We administered the National Danish Survey of Patient Experiences for acute and scheduled hospitalization. Patients rated their experiences of support, information and involvement in decision-making on a 5-point Likert scale. We calculated individual and grouped mean item scores, the percentages of scores ≥4, the mean score difference, the relative risk (RR) for high/very high scores (≥4) using Poisson regression and the risk difference. Patient experience ratings were compared using mixed effects linear regression. RESULTS: In total, 400 patients before and 400 after accreditation completed the survey. After accreditation patients reported increased support from health professionals; adjusted mean score difference (adj. mean diff.) = 1.99 (95% confidence interval (CI): 1.89, 2.10), feeling better informed before and during the hospitalization; adj. mean diff. = 1.14 (95% CI: 1.07; 1.20) and more involved in decision-making; adj. mean diff. = 1.79 (95% CI: 1.76; 1.82). Additionally, the RR for a high/very high score (≥4) was significantly greater on 15 of the 16 questionnaire items. The greatest RR for a high/very high score (≥4) after accreditation, was found for the item 'Have you had a dialogue with the staff about the advantages and disadvantages of the examination/treatment options available?'; RR= 5.73 (95% CI: 4.51, 7.27). CONCLUSION: Hospitalized patients experienced significantly more support from health professionals, information and involvement in decision-making after accreditation. Future research on accreditation should include the patients' perspective.