Evidence map›Paper›PMID 33724372›Full record

ArticleHealth policy and planning2021

Phone-based monitoring to evaluate health policy and program implementation in Kenya.

Paul G Ashigbie, Peter C Rockers, Richard O Laing, Howard J Cabral, Monica A Onyango, John Mboya, Daniella Arends, Veronika J Wirtz

Open access · hybridAbstract read
In one paragraph

Article in Health policy and planning, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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

8 authors at 3 institutions in 4 countries.

Paul G AshigbieDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, USA.ORCID 0000-0001-8221-6785
Peter C RockersDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, USA.
Richard O LaingDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, USA.
Howard J CabralDepartment of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, USA.
Monica A OnyangoDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, USA.
John MboyaInnovations for Poverty Action, Sandalwood Lane, Westlands, Nairobi, Kenya.
Daniella ArendsFaculty of Sciences, Department of Pharmaceutical Sciences and School of Pharmacy, Utrecht University, Universiteitsweg 99, 3584 CG Utrecht, The Netherlands.
Veronika J WirtzDepartment of Global Health, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, USA.
Boston University · USPractical Action · KEUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring and evaluating policies and programs in low- and middle-income countries are often difficult because of the lack of routine data. High mobile phone ownership in these countries presents an opportunity for efficient data collection through telephone interviews. This study examined the feasibility of collecting data on medicines through telephone interviews in Kenya. Data on the availability and prices of medicines at 137 health facilities and 639 patients were collected in September 2016 via in-person interviews. Between December 2016 and December 2017, monthly telephone interviews were conducted with health facilities and patients. An unannounced in-person interview was conducted with respondents to validate the telephone interview within 24 h. A bottom-up itemization costing approach was used to estimate the costs of telephone and in-person data collection. In-depth interviews were conducted with data collectors and respondents to explore their perceptions on both modes of data collection. The level of agreement between data on medicines availability collected through phone and in-person interviews was strong at the health facility level [kappa = 0.90; confidence interval (CI) 0.88-0.92] and moderate at the household level (kappa = 0.50, CI 0.39-0.60). Price data from telephone and in-person interviews showed strong intra-class correlation at health facilities [intra-class correlation coefficient (ICC) = 0.96] and moderate intra-class correlation at households (ICC = 0.47). The cost per phone interview at health facilities and households were $19.73 and $16.86, respectively, compared to $186.20 for a baseline in-person interview. Participants considered telephone interviews to be more convenient. In countries with high cell phone penetration, telephone data collection should be considered in monitoring and evaluating public health programs especially at health facilities. Additional strategies may be needed to optimize this mode of data collection at the household level. Variations in cell phone ownership, telecommunication network and data collection costs across different settings may limit the generalizability of the findings from this study.

Indexed as

Cell PhoneData CollectionHealth PolicyHumansKenyaOwnershipavailabilityhealth facilityhouseholdin-person interviewspriceTelephone interviews

Identifiers

PMID33724372
PMCPMC8128015
OpenAlexW3137083341

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.