Evidence map›Paper›PMID 35619095›Full record

ArticleBMC primary care2022

Development and validation of a risk score to predict the frequent emergency house calls among older people who receive regular home visits.

Yu Sun, Masao Iwagami, Nobuo Sakata, Tomoko Ito, Ryota Inokuchi, Kazuaki Uda, Shota Hamada, Miho Ishimaru, Jun Komiyama, Naoaki Kuroda and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC primary care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

3 citing papers in PubMed, 9 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

14 authors at 3 institutions in 1 country.

Yu SunGraduate School of Comprehensive Human Sciences, University of Tsukuba, Ibaraki, Japan.
Masao IwagamiDepartment of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan. iwagami-tky@umin.ac.jp.
Nobuo SakataDepartment of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
Tomoko ItoHealth Services Research and Development Center, University of Tsukuba, Ibaraki, Japan.
Ryota InokuchiDepartment of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
Kazuaki UdaDepartment of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
Shota HamadaDepartment of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
Miho IshimaruDepartment of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
Jun KomiyamaGraduate School of Comprehensive Human Sciences, University of Tsukuba, Ibaraki, Japan.
Naoaki KurodaHealth Services Research and Development Center, University of Tsukuba, Ibaraki, Japan.
Satoru YoshieHealth Services Research and Development Center, University of Tsukuba, Ibaraki, Japan.
Tatsuro IshizakiDepartment of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
Katsuya IijimaInstitute of Gerontology, University of Tokyo, Tokyo, Japan.
Nanako TamiyaDepartment of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
University of Tsukuba · JPThe University of Tokyo · JPTokyo Medical and Dental University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe demand for home healthcare is increasing in Japan, and a 24-hour on-call system could be a burden for primary care physicians. Identifying high-risk patients who need frequent emergency house calls could help physicians prepare and allocate medical resources. The aim of the present study was to develop a risk score to predict the frequent emergency house calls in patients who receive regular home visits.

methodsWe conducted a retrospective cohort study with linked medical and long-term care claims data from two Japanese cities. Participants were ≥ 65 years of age and had newly started regular home visits between July 2014 and March 2018 in Tsukuba city and between July 2012 and March 2017 in Kashiwa city. We followed up with patients a year after they began the regular home visits or until the month following the end of the regular home visits if this was completed within 1 year. We calculated the average number of emergency house calls per month by dividing the total number of emergency house calls by the number of months that each person received regular home visits (1-13 months). The primary outcome was the "frequent" emergency house calls, defined as its use once per month or more, on average, during the observation period. We used the least absolute shrinkage and selection operator (LASSO) logistic regression with 10-fold cross-validation to build the model from 19 candidate variables. The predictive performance was assessed with the area under the curve (AUC).

resultsAmong 4888 eligible patients, frequent emergency house calls were observed in 13.0% of participants (634/4888). The risk score included three variables with the following point assignments: home oxygen therapy (3 points); long-term care need level 4-5 (1 point); cancer (4 points). While the AUC of a model that included all candidate variables was 0.734, the AUC of the 3-risk score model was 0.707, suggesting good discrimination.

conclusionsThis easy-to-use risk score would be useful for assessing high-risk patients and would allow the burden on primary care physicians to be reduced through measures such as clustering high-risk patients in well-equipped medical facilities.

Indexed as

Home Care ServicesMedicineAgedHouse CallsHumansRetrospective StudiesRisk FactorsEmergency house callsHigh-risk patientsHome healthcare servicesRisk score

Identifiers

PMID35619095
PMCPMC9137049
OpenAlexW4281559047

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.