Background: Bipolar disorder if untreated, has severe consequences: severe role impairment, higher health care costs, mortality and morbidity. Although effective treatment is available, the delay in diagnosis might be as long as 10-15 years. In this study, we aim at documenting the length of the diagnostic delay in Hungary and identifying factors associated with it. Methods: Kaplan-Meier survival analysis and Cox proportional hazards model was employed to examine factors associated with the time to diagnosis of bipolar disorder measured from the date of the first presentation to any specialist mental healthcare institution. We investigated three types of factors associated with delays to diagnosis: demographic characteristics, clinical predictors and patient pathways (temporal sequence of key clinical milestones). Administrative data were retrieved from specialist care; the population-based cohort includes 8935 patients from Hungary. Results: In the sample, diagnostic delay was 6.46 years on average. The mean age of patients at the time of the first bipolar diagnosis was 43.59 years. 11.85% of patients were diagnosed with bipolar disorder without any delay, and slightly more than one-third of the patients (35.10%) were never hospitalized with mental health problems. 88.80% of the patients contacted psychiatric care for the first time in outpatient settings, while 11% in inpatient care. Diagnostic delay was shorter, if patients were diagnosed with bipolar disorder by non-specialist mental health professionals before. In contrast, diagnoses of many psychiatric disorders received after the first contact were coupled with a delayed bipolar diagnosis. We found empirical evidence that in both outpatient and inpatient care prior diagnoses of schizophrenia, unipolar depression without psychotic symptoms, and several disorders of adult personality were associated with increased diagnostic delay. Patient pathways played an important role as well: the hazard of delayed diagnosis increased if patients consulted mental healthcare specialists in outpatient care first or they were hospitalized. Conclusions: We systematically described and analysed the diagnosis of bipolar patients in Hungary controlling for possible confounders. Our focus was more on clinical variables as opposed to factors controllable by policy-makers. To formulate policy-relevant recommendations, a more detailed analysis of care pathways and continuity is needed.

Overall drug expenditure may be reduced by lowering patient care fragmentation through channelling a GP's patients to a small number of SPs.

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Improved patient care coordination is critical for achieving better health outcome measures at reduced cost. Better integration of primary and secondary care in chronic illness care and utilizing the advantages of better collaboration between general practitioners and specialists may support these conflicting goals. Assessing patient care coordination at system level is, however, as challenging as achieving it. Based on prescription data from a private data vendor company, we develop a provider-level care coordination measure to assess the function of primary care at system level. We aim to provide empirical evidence for the possible impact of patient care coordination in chronic illness care-we investigate whether the type of collaborative relationship general practitioners have built up with specialists is associated with prescription drug costs. To our knowledge, no large-scale quantitative study has ever investigated this association. We find that prescription drug costs for patients treated by general practitioners who build up strong collaborative relationships with specialists are significantly lower than for patients treated by general practitioners characterized by fragmented collaborative structures. If future system-level studies in other settings confirm that total healthcare costs are indeed lower for patients treated in strong collaborative structures, then healthcare strategists need to advocate a healthcare system with lower care fragmentation on the interface of primary and secondary care. Regulating access to secondary care might result in significant cost savings through improved care coordination. JEL codes: C12, H51, I18

This article studies the determinants of pharmaceutical innovation diffusion among specialists. To this end, it investigates the infl uences of six categories of factors—social embeddedness, socio-demography, scientifi c orientation, prescribing patterns, practice characteristics, and patient panel composition—on the use of 11 new drugs for the treatment of type 2 diabetes mellitus in Hungary. The Cox proportional hazards model identifi es three determinants—social contagion (in the social embeddedness category) and prescribing portfolio and insulin prescribing ratio (in the prescribing pattern category). First, social contagion has a positive effect among geographically close colleagues—the higher the adoption ratio, the higher the likelihood of early adoption—but no infl uence among former classmates and scientifi c collaborators. Second, the wider the prescribing portfolio, the earlier the new drug uptake. Third, the lower the insulin prescribing ratio, the earlier the new drug uptake—physicians’ therapeutic convictions and patients’ socioeconomic statuses act as underlying infl uencers. However, this fi nding does not extend to opinion-leading physicians such as scientifi c leaders and hospital department and outpatient center managers. This article concludes by arguing that healthcare policy strategists and pharmaceutical companies may rely exclusively on practice location and prescription data to perfect interventions and optimize budgets.