How do individuals with alcohol problems use social and healthcare services in Finland? Comparison of service use patterns between two high-need patient groups.

Aims: Alcohol use disorders (AUDs) are associated with high risk of comorbidities and excess use of social and healthcare services. We examined health service use (HSU) frequencies of patients with AUD in comparison to those with type 2 diabetes mellitus (T2DM). Design: A random sample of individuals with AUD (n = 396) were identified based on ICD-10 codes and HSU patterns, morbidity and mortality were compared with age- and gender-matched T2DM controls (n = 792) using logistic regression analysis. Six years (2011-2016) of electronic health record (EHR) data from the North Karelia district in Finland were used. Results: Similarities in comorbidity patterns existed, although mental health comorbidity (odds ratio [OR] 1.86) was more prevalent in the AUD group. The average annual HSU varied according to the groups: T2DM patients had more continuous contact with public health nurses in primary care, whereas AUD patients were more likely to experience somatic specialised care hospitalisations (OR 11.30) and have frequent somatic primary healthcare doctor visits (OR 3.30) and frequent emergency room doctor visits in specialised care (OR 8.89). Furthermore, patients with AUD had a 7.5 times higher risk of death compared with T2DM patients. Conclusions: This study identified rather similar comorbidity status for the AUD and T2DM patients, but their HSU patterns differed noticeably. AUD patients had higher frequencies of hospitalisation periods and emergency service use and were at a higher risk of death compared with T2DM patients, indicating greater challenges in the organisation of care for AUD patients compared with those having T2DM.

Comparison of data sources on alcohol problems: An exploratory exercise using surveys vs. national healthcare registers.

Aims: Both survey and healthcare register data struggle as data sources to capture the phenomenon of alcohol problems. We study a large group of people for whom survey data and two types of register data are available, and examine the overlaps of similar or related measures in the different data sources to learn about potential weaknesses in each. We also examine how register-based data on the prevalence of alcohol problems change depending on which register data are used. Design: We use data from the Regional Health and Wellbeing Study (ATH) of the adult Finnish population collected in 2013 and 2014 (n = 69,441), individually linked with data on two national healthcare registers (Care Register for Health Care; Register of Primary Health Care visits) for the survey year and previous year. Results: The prevalence of substance-abuse-related healthcare was almost two-fold if data on outpatient primary care visits were included in addition to hospitalisations. Forty-six per cent of the survey respondents self-reporting substance-abuse-related healthcare service use were identified in the registers, and 22% of all respondents with such service use according to registers reported this in the survey. Records of substance-abuse-related healthcare service use, controlled for self-reported alcohol use and self-reported substance-abuse-related service use, were found more often for men, the middle-aged, people with basic education only, and the non-employed. Conclusions: The results are suggestive of underreporting in both data sources. There is an evident need to develop recording practices in the healthcare registers regarding substance use disorders.

Factors Associated with 5-Year Costs of Care among a Cohort of Alcohol Use Disorder Patients: A Bayesian Network Model.

OBJECTIVES: To examine the direct effects of risk factors associated with the 5-year costs of care in persons with alcohol use disorder (AUD) and to examine whether remission decreases the costs of care. METHODS: Based on Electronic Health Record data collected in the North Karelia region in Finland from 2012 to 2016, we built a non-causal augmented naïve Bayesian (ANB) network model to examine the directional relationship between 16 risk factors and the costs of care for a random cohort of 363 AUD patients. Jouffe's proprietary likelihood matching algorithm and van der Weele's disjunctive confounder criteria (DCC) were used to calculate the direct effects of the variables, and sensitivity analysis with tornado diagrams and analysis maximizing/minimizing the total cost of care were conducted. RESULTS: The highest direct effect on the total cost of care was observed for a number of chronic conditions, indicating on average more than a €26,000 increase in the 5-year mean cost for individuals with multiple ICD-10 diagnoses compared to individuals with less than two chronic conditions. Remission had a decreasing effect on the total cost accumulation during the 5-year follow-up period; the percentage of the lowest cost quartile (42.9% vs. 23.9%) increased among remitters, and that of the highest cost quartile (10.71% vs. 26.27%) decreased compared with current drinkers. CONCLUSIONS: The ANB model with application of DCC identified that remission has a favorable causal effect on the total cost accumulation. A high number of chronic conditions was the main contributor to excess cost of care, indicating that comorbidity is an essential mediator of cost accumulation in AUD patients.

Do the Costs of AUD-Related Health and Social Care Services Vary Across Patient Profiles?

OBJECTIVE: Alcohol use disorders (AUDs) are associated with high social and health care costs. We compare the direct social and health care costs of patients with AUDs, according to four service use profiles: (a) AUD treatment, (b) mental health (MH) treatment, (c) AUD + MH treatment, (d) no treatment. A separate analysis of the costliest 10% is included. Furthermore, the association between the service user profile and the risk of death is examined. METHOD: Direct unit service costs were retrieved from the electronic health record system and supplemented with patient grouping-based costs for primary and secondary care services, to examine the yearly mean cost per patient in the AUD cohort (N = 5,136; 71.1% male). We used data collected in the North Karelia region of Finland between 2014 and 2018. RESULTS: Total costs of care for the cohort during the 5-year follow-up were 126 million Euros, and the percentage of the costliest 10% (n = 521) was 51.7% (65 million Euros). Total costs were 12,778 Euros lower if the person received AUD treatment only, compared with those not in treatment. For those receiving MH treatment only, the total costs were 1,819 Euros higher, and costs were 1,523 Euros higher for those receiving AUD + MH treatment. Receiving any treatment was associated with a diminished risk of death (AUD: odds ratio [OR] = 0.56; MH: OR = 0.63; AUD + MH: OR = 0.41). CONCLUSIONS: Receiving only AUD treatment was associated with the lowest cost of care. Our results support the early identification of AUDs and provision of treatment in specialized addiction services to lower the costs of care and improve care outcomes.

Care outcomes and alcohol-related treatment utilisation profiles of patients with alcohol-use disorder: A prospective cohort study using electronic health records.

BACKGROUND: We examined the probabilities of longitudinal care outcomes of working-aged patients with alcohol-use disorder (AUD) and their alcohol-related treatment utilisation patterns across the healthcare services, by using linked electronic health records. METHODS: A random sample (n = 396) of patients with alcohol-related visits to healthcare services in 2011-2012 was collected retrospectively from the electronic health record data in the North Karelia region of Finland and followed prospectively in time until the end of 2016. Data on care outcomes and alcohol-related healthcare use were gathered from the electronic health records. Three outcome groups were identified: (1) dead, (2) present AUD, and (3) remission. Group differences in alcohol-related health service use were compared. RESULTS: At the end of the follow-up period, an increased mortality rate of 22.9% was observed, and 18.4% had achieved stable remission, while for the majority (56%), the AUD remained. Most of those in remission had contact with either specialised AUD services or mental health services. Conversely, the majority of those who had died had no contact with specialised AUD services during the follow-up period. CONCLUSIONS: The electronic-health-record-based register analysis captured mainly individuals with advanced forms of AUD. An excess mortality rate and other negative health consequences were observed. Training providers to identify and treat earlier the less severe forms of AUD could have major benefit to patients and also reduce health system costs.

A review of the organization, regulation, and financing practices of postgraduate education in clinical nursing in 12 European countries.

AIM: The aim of this study was to generate information of postgraduate education in clinical nursing in the EU member states. METHODS: Data were collected via a structured electronic questionnaire and the questionnaire was sent to the government chief nurses in 26 EU countries in May 2013. Response rate was 46% (n=12). FINDINGS: In total, 42 domains of specialization were identified. The most common domains were intensive care, mental health, operating room, emergency care, and pediatrics. Specialization programs were organized by university in two of the respondent countries, as residency program in one country, and as a mix of them in four countries. Regulation practices varied remarkably between the countries: scope of practice, subjects, entry requirements, length of education, description of the minimum competence requirements, and education standards related to the specialization programs were most often regulated by act, decree or other regulation. In some of the countries, no registration was required beyond the initial registration, whereas in some others, registration practices varied depending on the specialization program. New information was gathered on the regulation practices of postgraduate education in clinical nursing in the European Region concerning title provision, entry requirements, and financing practices. The awarded title on specialization programs depended on the level of postgraduate education, and the title might vary between the domains. General clinical experience was included in the entry requirements in seven countries. The government was mainly responsible for financing the postgraduate education in four countries, employer in three countries, and in the rest of the countries, there was a combination of different financiers. CONCLUSIONS: The importance of knowledge exchange on postgraduate education across the European countries needs to be acknowledged. Information provided by this study on international regulation practices provides useful information for the policy-makers regarding the organization of the postgraduate education in clinical nursing.