Evidence map›Paper›PMID 30675742›Full record

ArticleBritish journal of clinical pharmacology2019

Ensuring continuity of patient care across the healthcare interface: Telephone follow-up post-hospitalization.

Mohanad Odeh, Claire Scullin, Glenda Fleming, Michael G Scott, Robert Horne, James C McElnay

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Article in British journal of clinical pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
–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

34 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

6 authors.

Mohanad OdehClinical and Practice Research Group, School of Pharmacy, Queen's University Belfast, Belfast, BT9 7BL, UK.ORCID 0000-0002-6060-8283
Claire ScullinMedicines Optimisation Innovation Centre (MOIC), Antrim, UK.
Glenda FlemingMedicines Optimisation Innovation Centre (MOIC), Antrim, UK.
Michael G ScottMedicines Optimisation Innovation Centre (MOIC), Antrim, UK.
Robert HorneSchool of Pharmacy, University College London, London, WC1N 1AX, UK.
James C McElnayClinical and Practice Research Group, School of Pharmacy, Queen's University Belfast, Belfast, BT9 7BL, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTo implement pharmacist-led, postdischarge telephone follow-up (TFU) intervention and to evaluate its impact on rehospitalization parameters in polypharmacy patients, via comparison with a well-matched control group.

methodPragmatic, prospective, quasi-experimental study. Intervention patients were matched by propensity score techniques with a control group. Guided by results from a pilot study, clinical pharmacists implemented TFU intervention, added to routine integrated medicines management service.

resultsUsing an intention to treat approach, reductions in 30- and 90-day readmission rates for intervention patients compared with controls were 9.9% [odds ratio = 0.57; 95% confidence interval (CI): 0.36-0.90; P < 0.001] and 15.2% (odds ratio = 0.53; 95% CI: 0.36-0.79; P = 0.021) respectively. Marginal mean time to readmission was 70.9 days (95% CI: 66.9-74.9) for intervention group compared with 60.1 days (95% CI: 55.4-64.7) for controls. Mean length of hospital stay compared with control was (8.3 days vs. 6.7 days; P < 0.001). Benefit: cost ratio for 30-day readmissions was 29.62, and 23.58 for 90-day interval. Per protocol analyses gave more marked improvements. In intervention patients, mean concern scale score, using Beliefs about Medicine Questionnaire, was reduced 3.2 (95% CI: -4.22 to -2.27; P < 0.001). Mean difference in Medication Adherence Report Scale was 1.4 (22.7 vs. 24.1; P < 0.001). Most patients (83.8%) reported having better control of their medicines after the intervention.

conclusionsPharmacist-led postdischarge structured TFU intervention can reduce 30- and 90-day readmission rates. Positive impacts were noted on time to readmission, length of hospital stay upon readmission, healthcare costs, patient beliefs about medicines, patient self-reported adherence and satisfaction.

Indexed as

AdultAftercareAgedContinuity of Patient CareDrug MonitoringFemaleFollow-Up StudiesHealth Plan ImplementationHumansMaleMiddle AgedPatient DischargePatient ReadmissionPharmacistsPharmacy Service, HospitalPolypharmacyclinical pharmacistspostdischarge follow-upreadmission raterehospitalization

Identifiers

PMID30675742
PMCPMC6379220

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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.