The Norrtaelje model: a unique model for integrated health and social care in Sweden

Bäck, Monica Andersson; Calltorp, J

doi:10.5334/ijic.2244

Cited by 42 publications

(93 citation statements)

References 3 publications

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“…Regarding its impact at community level, multimorbidity shows positive correlations with number of outpatient visits [7], polypharmacy [8] and with patients' frailty [9]. The latter being a strong modulator of the need for both homecare and social support services [10,11].…”

Section: Introductionmentioning

confidence: 99%

Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population

et al. 2020

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Background: Multimorbidity is highly relevant for both service commissioning and clinical decision-making. Optimization of variables assessing multimorbidity in order to enhance chronic care management is an unmet need. To this end, we have explored the contribution of multimorbidity to predict use of healthcare resources at community level by comparing the predictive power of four different multimorbidity measures. Methods: A population health study including all citizens ≥18 years (n = 6,102,595) living in Catalonia (ES) on 31 December 2014 was done using registry data. Primary care service utilization during 2015 was evaluated through four outcome variables: A) Frequent attendants, B) Home care users, C) Social worker users, and, D) Polypharmacy. Prediction of the four outcome variables (A to D) was carried out with and without multimorbidity assessment. We compared the contributions to model fitting of the following multimorbidity measures: i) Charlson index; ii) Number of chronic diseases; iii) Clinical Risk Groups (CRG); and iv) Adjusted Morbidity Groups (GMA). Results: The discrimination of the models (AUC) increased by including multimorbidity as covariate into the models, namely: A) Frequent attendants (0.771 vs 0.853), B) Home care users (0.862 vs 0.890), C) Social worker users (0.809 vs 0.872), and, D) Polypharmacy (0.835 vs 0.912). GMA showed the highest predictive power for all outcomes except for polypharmacy where it was slightly below than CRG. Conclusions: We confirmed that multimorbidity assessment enhanced prediction of use of healthcare resources at community level. The Catalan population-based risk assessment tool based on GMA presented the best combination of predictive power and applicability.

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Section: Introductionmentioning

confidence: 99%

Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population

et al. 2020

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“…People who consider themselves in need of seeing a medical doctor seem to seek care at the emergency departments rather than primary care clinics where, depending on their health problems, they may be seen by a nurse. Local initiatives have, however, shown that developing and implementing integrated care between hospitals, primary care and social care reduces the number of hospital admissions and readmissions [6869]. For example, at a primary care clinic in Borgholm, a municipality in the south of Sweden with the oldest population in the country, dramatic changes have been made to improve access to healthcare.…”

Section: Discussionmentioning

confidence: 99%

Impact of Integrated Care on Patient-Related Outcomes Among Older People – A Systematic Review

Liljas¹,

Brattström²,

Burström³

et al. 2019

International Journal of Integrated Care

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Introduction: The growing number of older adults with multiple needs increases the pressure to reform existing healthcare systems. Integrated care may be part of such reforms. The aim of this systematic review was to identify important patient-related outcomes of integrated care provided to older adults. Methods: A systematic search of 5 databases to identify studies comprising older adults assessing hospital admission, length of hospital stay, hospital readmission, patient satisfaction and mortality in integrated care settings. Retrieved literature was analysed employing a narrative synthesis. Results: Twelve studies were included (2 randomised controlled trials, 7 quasi-experimental design, 2 comparison studies, 1 survey evaluation). Five studies investigated patient satisfaction, 9 hospital admission, 7 length of stay, 3 readmission and 5 mortality. Findings show that integrated care tends to have a positive impact on hospital admission rates, some positive impact on length of stay and possibly also on readmission and patient satisfaction but not on mortality. Conclusions: Integrated care may reduce hospital admission rates and lengths of hospital stay. However due to lack of robust findings, the effectiveness of integrated care on patient-related outcomes in later life remain largely unknown. Further research is needed to establish the effect of integrated care on these patient-related outcomes. Prospero registration number: CRD42018110491.

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“…Other high bed number countries include Austria (intercept 1350) and Germany (1320), hence while the average for developed countries is a helpful benchmark it is important to realize that countries with high levels of integrated care such as Sweden (intercept 800), Singapore and New Zealand (790) operate with around 40% fewer beds that the developed countries average (Figure ). However, such levels of bed provision are only achieved after many years of effort enabled by government policy . Australia is generally not considered to have a highly integrated health care service, and hence bed provision lies near to the International average for developed countries.…”

Section: Discussionmentioning

confidence: 99%

A pragmatic method to compare hospital bed provision between countries and regions: Beds in the States of Australia

Jones

2019

Health Planning & Management

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Summary A simple method is presented to evaluate bed numbers between countries using a logarithmic relationship between beds per 1000 deaths and deaths per 1000 population, both of which are readily available. The method relies on the importance of the nearness to death effect. This method was tested using data from Australian States. Beds per 1000 deaths varied considerably between States. This variation reduced after adjusting for the ratio of deaths per 1000 population which is a measure of population age structure. After this adjustment, most Australian States roughly approximate to the international average for developed countries while Tasmania was shown to have a chronic bed shortage, as has been recognized for many years. The Northern Territory and the Australian Capital Territory, both of which have the youngest populations, have more beds relative to the other States. The nearness to death effect must be incorporated into capacity planning models in order to give robust estimates of future bed demand and to evaluate differences between countries and health care systems.

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The Norrtaelje model: a unique model for integrated health and social care in Sweden

Cited by 42 publications

References 3 publications

Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population

Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population

Impact of Integrated Care on Patient-Related Outcomes Among Older People – A Systematic Review

A pragmatic method to compare hospital bed provision between countries and regions: Beds in the States of Australia

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