Evidence map›Paper›PMID 30395496›Full record

Observational studyHealth affairs (Project Hope)2018

Accurate Measurement In California's Safety-Net Health Systems Has Gaps And Barriers.

Elaine C Khoong, Roy Cherian, Natalie A Rivadeneira, Gato Gourley, Jinoos Yazdany, Ashrith Amarnath, Dean Schillinger, Urmimala Sarkar

Erratum issuedAbstract readObservational Study
In one paragraph

Observational study in Health affairs (Project Hope), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Elaine C KhoongElaine C. Khoong ( elaine.khoong@ucsf.edu ) is a primary care research fellow in the Division of General Internal Medicine, University of California San Francisco (UCSF), and the Zuckerberg San Francisco General Hospital and Trauma Center.
Roy CherianRoy Cherian is a research data analyst at the Center for Vulnerable Populations, UCSF, and the Zuckerberg San Francisco General Hospital and Trauma Center.
Natalie A RivadeneiraNatalie A. Rivadeneira is a research data analyst at the Center for Vulnerable Populations, UCSF, and the Zuckerberg San Francisco General Hospital and Trauma Center.
Gato GourleyGato Gourley is a project coordinator at the Center for Vulnerable Populations, UCSF, and the Zuckerberg San Francisco General Hospital and Trauma Center.
Jinoos YazdanyJinoos Yazdany is an associate professor of medicine in the Division of Rheumatology, UCSF.
Ashrith AmarnathAshrith Amarnath is a patient safety officer at the Sutter Medical Foundation and a former patient safety officer in the Office of the Medical Director, Department of Health Care Services, both in Sacramento, California.
Dean SchillingerDean Schillinger is a professor of medicine at UCSF and chief of the Division of General Internal Medicine at Zuckerberg San Francisco General Hospital and Trauma Center.
Urmimala SarkarUrmimala Sarkar is an associate professor of medicine in the Division of General Internal Medicine, UCSF, and a primary care physician at Zuckerberg San Francisco General Hospital's Richard H. Fine People's Clinic.

Funding

Translational Research Core - Health Engagement & Action Translational (HEAT)P30DK092924 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI Alyce Sophia Adams, HILARY Kessler SELIGMAN · 2011 to 2026
$9.2M
Investigating Failures of Notification and Monitoring in Outpatient Care: the Safety Promotion Action Research and Knowledge (SPARK) NetworkR01HS024426 · AHRQ · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SARKAR, URMIMALA · 2015 to 2017
$1.4M
ASPIRE: Advancing Safety Process Innovation in RheumatologyR01HS024412 · AHRQ · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI YAZDANY, JINOOS · 2015 to 2017
$1.4M
Improving Survivorship Care for Diverse Cancer Patients Cared for in Safety-net SettingsK24CA212294 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SARKAR, URMIMALA · 2017 to 2021
$831k
AHRQ HHS R01 HS024412AHRQ HHS R01 HS024426NCI NIH HHS K24 CA212294NIDDK NIH HHS P30 DK092924
6 · The paper itself

Abstract

Patient safety in ambulatory care has not been routinely measured. California implemented a pay-for-performance program in safety-net hospitals that incentivized measurement and improvement in key areas of ambulatory safety: referral completion, medication safety, and test follow-up. We present two years of program data (collected during July 2015-June 2017) and show both suboptimal performance in aspects of ambulatory safety and questionable reliability in data reporting. Performance was better in areas that required limited coordination or patient engagement-for example, annual medication monitoring versus follow-up after high-risk mammograms. Health care systems that lack seamlessly integrated electronic health records and patient registries encountered barriers to reporting reliable ambulatory safety data, particularly for measures that integrated multiple data elements. These data challenges precluded accurate performance measurement in many areas. Policy makers and safety advocates need to support the development of information systems and measures that facilitate the accurate ascertainment of the health systems, patients, and clinical tasks at greatest risk for ambulatory safety failures.

Indexed as

Patient SafetyReimbursement, IncentiveAmbulatory CareCaliforniaDelivery of Health CareElectronic Health RecordsGovernment ProgramsHumansMedication ErrorsQuality Indicators, Health CareReferral and ConsultationReproducibility of ResultsResearch DesignSafety-net ProvidersAmbulatory CarePatient SafetyPerformance MeasurementQuality Of CareSafety-Net Systems

Identifiers

PMID30395496
PMCPMC7491428

What OpenQuestion holds

Textmetadata
LicenceTDM
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.