Evidence map›Paper›PMID 19272165›Full record

Trial reportBMC medical informatics and decision making2009

Impact of two interventions on timeliness and data quality of an electronic disease surveillance system in a resource limited setting (Peru): a prospective evaluation.

Moises A Huaman, Roger V Araujo-Castillo, Giselle Soto, Joan M Neyra, Jose A Quispe, Miguel F Fernandez, Carmen C Mundaca, David L Blazes

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC medical informatics and decision making, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 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

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Observational
  16. Observational
  17. Article
  18. Article
  19. Tuberculosis Notification by Private Sector' Physicians in Tehran.International journal of preventive medicine · 2015
    Article
  20. 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.

Moises A HuamanUS Naval Medical Research Center Detachment, Lima, Peru. mhuaman1@hfhs.org
Roger V Araujo-Castillo
Giselle Soto
Joan M Neyra
Jose A Quispe
Miguel F Fernandez
Carmen C Mundaca
David L Blazes

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA timely detection of outbreaks through surveillance is needed in order to prevent future pandemics. However, current surveillance systems may not be prepared to accomplish this goal, especially in resource limited settings. As data quality and timeliness are attributes that improve outbreak detection capacity, we assessed the effect of two interventions on such attributes in Alerta, an electronic disease surveillance system in the Peruvian Navy.

methods40 Alerta reporting units (18 clinics and 22 ships) were included in a 12-week prospective evaluation project. After a short refresher course on the notification process, units were randomly assigned to either a phone, visit or control group. Phone group sites were called three hours before the biweekly reporting deadline if they had not sent their report. Visit group sites received supervision visits on weeks 4 & 8, but no phone calls. The control group sites were not contacted by phone or visited. Timeliness and data quality were assessed by calculating the percentage of reports sent on time and percentage of errors per total number of reports, respectively.

resultsTimeliness improved in the phone group from 64.6% to 84% in clinics (+19.4 [95% CI, +10.3 to +28.6]; p < 0.001) and from 46.9% to 77.3% on ships (+30.4 [95% CI, +16.9 to +43.8]; p < 0.001). Visit and control groups did not show significant changes in timeliness. Error rates decreased in the visit group from 7.1% to 2% in clinics (-5.1 [95% CI, -8.7 to -1.4]; p = 0.007), but only from 7.3% to 6.7% on ships (-0.6 [95% CI, -2.4 to +1.1]; p = 0.445). Phone and control groups did not show significant improvement in data quality.

conclusionRegular phone reminders significantly improved timeliness of reports in clinics and ships, whereas supervision visits led to improved data quality only among clinics. Further investigations are needed to establish the cost-effectiveness and optimal use of each of these strategies.

Indexed as

Reminder SystemsAmbulatory Care FacilitiesData CollectionDisease NotificationDisease OutbreaksHumansPeruPopulation SurveillanceProspective StudiesShipsTelephoneTime Factors

Identifiers

PMID19272165
PMCPMC2667397

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.