Evidence map›Paper›PMID 37158867›Full record

ArticleBMC health services research2023

Patient-level predictors of temporal regularity of primary care visits.

Adam J Rose, Wiessam Abu Ahmad, Faige Spolter, Maram Khazen, Avivit Golan-Cohen, Shlomo Vinker, Ilan Green, Ariel Israel, Eugene Merzon

Abstract read
In one paragraph

Article in BMC health services research, 2023. 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
–field-weighted citation impact
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.

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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

9 authors.

Adam J RoseBraun School of Public Health and Community Medicine, Faculty of Medicine, Hebrew University of Jerusalem, Ein Kerem Campus, Jerusalem, Israel. adam.rose@mail.huji.ac.il.
Wiessam Abu AhmadBraun School of Public Health and Community Medicine, Faculty of Medicine, Hebrew University of Jerusalem, Ein Kerem Campus, Jerusalem, Israel.
Faige SpolterBraun School of Public Health and Community Medicine, Faculty of Medicine, Hebrew University of Jerusalem, Ein Kerem Campus, Jerusalem, Israel.
Maram KhazenBraun School of Public Health and Community Medicine, Faculty of Medicine, Hebrew University of Jerusalem, Ein Kerem Campus, Jerusalem, Israel.
Avivit Golan-CohenLeumit Health Services, Research Institute, Tel Aviv, Israel.
Shlomo VinkerLeumit Health Services, Research Institute, Tel Aviv, Israel.
Ilan GreenLeumit Health Services, Research Institute, Tel Aviv, Israel.
Ariel IsraelLeumit Health Services, Research Institute, Tel Aviv, Israel.
Eugene MerzonLeumit Health Services, Research Institute, Tel Aviv, Israel.

Funding

Israel Science Foundation 764/21
6 · The paper itself

Abstract

backgroundPatients with chronic diseases should meet with their primary care doctor regularly to facilitate proactive care. Little is known about what factors are associated with more regular follow-up.

methodsWe studied 70,095 patients age 40 + with one of three chronic conditions (diabetes mellitus, heart failure, chronic obstructive pulmonary disease), cared for by Leumit Health Services, an Israeli health maintenance organization. Patients were divided into the quintile with the least temporally regular care (i.e., the most irregular intervals between visits) vs. the other four quintiles. We examined patient-level predictors of being in the least-temporally-regular quintile. We calculated the risk-adjusted regularity of care at 239 LHS clinics with at least 30 patients. For each clinic, compared the number of patients with the least temporally regular care with the number predicted to be in this group based on patient characteristics.

resultsCompared to older patients, younger patients (age 40-49), were more likely to be in the least-temporally-regular group. For example, age 70-79 had an adjusted odds ratio (AOR) of 0.82 compared to age 40-49 (p < 0.001 for all findings discussed here). Males were more likely to be in the least-regular group (AOR 1.18). Patients with previous myocardial infarction (AOR 1.07), atrial fibrillation (AOR 1.08), and current smokers (AOR 1.12) were more likely to have an irregular pattern of care. In contrast, patients with diabetes (AOR 0.79) or osteoporosis (AOR 0.86) were less likely to have an irregular pattern of care. Clinic-level number of patients with irregular care, compared with the predicted number, ranged from 0.36 (fewer patients with temporally irregular care) to 1.71 (more patients).

conclusionsSome patient characteristics are associated with more or less temporally regular patterns of primary care visits. Clinics vary widely on the number of patients with a temporally irregular pattern of care, after adjusting for patient characteristics. Health systems can use the patient-level model to identify patients at high risk for temporally irregular patterns of primary care. The next step is to examine which strategies are employed by clinics that achieve the most temporally regular care, since these strategies may be possible to emulate elsewhere.

Indexed as

Atrial FibrillationHeart FailureAdultAgedAmbulatory Care FacilitiesHealth Maintenance OrganizationsHumansMaleMiddle AgedPrimary Health CareCase mix adjustmentPrimary careQuality of health careTemporal regularity of primary care

Identifiers

PMID37158867
PMCPMC10169340

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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.