Evidence map›Paper›PMID 31409343›Full record

Trial reportBMC public health2019

Step-wise approach to prevention of chronic diseases in the Danish primary care sector with the use of a personal digital health profile and targeted follow-up - an assessment of attendance.

Lars Bruun Larsen, Jens Sondergaard, Janus Laust Thomsen, Anders Halling, Anders Larrabee Sønderlund, Jeanette Reffstrup Christensen, Trine Thilsing

Open access · goldAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.7field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 34 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Lars Bruun LarsenDepartment of Public Health, Research Unit of General Practice, University of Southern Denmark, J.B. Winsløws Vej 9A, 5000, Odense, Denmark. lblarsen@health.sdu.dk.ORCID http://orcid.org/0000-0001-9120-4751
Jens SondergaardDepartment of Public Health, Research Unit of General Practice, University of Southern Denmark, J.B. Winsløws Vej 9A, 5000, Odense, Denmark.
Janus Laust ThomsenDepartment of Clinical Medicine, Research Unit for General Practice, Aalborg University, Aalborg, Denmark.
Anders HallingDepartment of Clinical Sciences in Malmö, Centre for Primary Health Care Research, Lund University, Lund, Sweden.
Anders Larrabee SønderlundDepartment of Public Health, Research Unit of General Practice, University of Southern Denmark, J.B. Winsløws Vej 9A, 5000, Odense, Denmark.
Jeanette Reffstrup ChristensenDepartment of Public Health, Research Unit of General Practice, University of Southern Denmark, J.B. Winsløws Vej 9A, 5000, Odense, Denmark.
Trine ThilsingDepartment of Public Health, Research Unit of General Practice, University of Southern Denmark, J.B. Winsløws Vej 9A, 5000, Odense, Denmark.
University of Southern Denmark · DKAalborg University · DKLund University · SE

Funding

Ministeriet Sundhed Forebyggelse 1-1010-116/26/KADRegion Syddanmark -
6 · The paper itself

Abstract

backgroundCurrent evidence on chronic disease prevention suggests that interventions targeted at high-risk individuals represents the best way forward. We implemented a step-wise approach in the Danish primary care sector, designed for the systematic and targeted prevention of chronic disease. The intervention centered on a personal digital health profile for all participants, followed by targeted preventive programs for high-risk patients. The present paper examines individual characteristics and health-care usage of patients who took up the targeted preventive programs in response to their personal digital health profile.

methodsA sample of patients born between 1957 and 1986 was randomly selected from the patient-list system of participating general practitioners in two Danish municipalities. The selected patients received a digital invitation to participate. Consenting patients received a second digital invitation for a personal digital health profile based on questionnaire and electronic patient record data. The personal digital health profile contained individualized information on risk profile and personalized recommendations on further actions. If at-risk or presenting with health-risk behaviour a patient would be advised to contact either their general practitioner or municipal health centre for targeted preventive programs. Attendance at the targeted preventive programs was examined using Poisson regression and chi-squared automatic interaction detection methods.

resultsA total of 9400 patients were invited. Of those who participated (30%), 22% were advised to get a health check at their general practitioner. Of these, 19% did so. Another 23% were advised to schedule an appointment for behaviour-change counselling at their municipal health centre. A total of 21% took the advice. Patients who had fair or poor self-rated health, a body mass index above 30, low self-efficacy, were female, non-smokers, or lead a sedentary lifestyle, were most likely to attend the targeted preventive programs.

conclusionsA personal digital health profile shows some promise in a step-wise approach to prevention in the Danish primary care sector and seems to motivate people with low self-efficacy to attend targeted preventive programs.

trial registrationRegistered at Clinical Trial Gov (Unique Protocol ID: TOFpilot2016 ). Prospectively registered on the 29th of April 2016.

Indexed as

Primary Health CareAdultChronic DiseaseCross-Sectional StudiesDenmarkElectronic Health RecordsFemaleFollow-Up StudiesHumansMaleMiddle AgedPatient CompliancePreventive Health ServicesHealth promotionIndicated preventionIntegrated prevention

Identifiers

PMID31409343
PMCPMC6693260
OpenAlexW2967449609

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.