Literature DB >> 17545349

Patients use an internet technology to report when things go wrong.

John H Wasson1, Todd A MacKenzie, Michael Hall.   

Abstract

BACKGROUND: As patients directly experience harm from adverse events, investigators have proposed patient-report to complement professional reporting of adverse events.
OBJECTIVE: To investigate how an automated health assessment system can be used to identify adverse events. DESIGN AND
SETTING: Internet survey responses from April 2003 to April 2005 involving communities and clinical practices across the USA. PATIENTS: 44,860 adults aged 19-69 years. OUTCOME: Patient perceptions of adverse events experienced during the previous year. Independent legal review was also used to estimate how many patient-reports were serious enough to be potentially compensable.
RESULTS: Although patient reports of possible adverse events was low (1.4%), the percentage of adverse events was eight times higher for patients with the greatest burden of illness than for those with the least (3.4% vs 0.4%). Two expert malpractice attorneys agreed that 9% of the adverse events seemed to be serious.
CONCLUSIONS: PATIENTS will use internet technology to report their perceptions of health-related adverse events. Some of the patient-reported events reported will be serious.

Entities:  

Mesh:

Year:  2007        PMID: 17545349      PMCID: PMC2465004          DOI: 10.1136/qshc.2006.019810

Source DB:  PubMed          Journal:  Qual Saf Health Care        ISSN: 1475-3898


  17 in total

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4.  What can hospitalized patients tell us about adverse events? Learning from patient-reported incidents.

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6.  Patient reports of undesirable events during hospitalization.

Authors:  Thomas Agoritsas; Patrick A Bovier; Thomas V Perneger
Journal:  J Gen Intern Med       Date:  2005-10       Impact factor: 5.128

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Authors:  Tim A Ahles; John H Wasson; Janette L Seville; Deborah J Johnson; Bernard F Cole; Brett Hanscom; Therese A Stukel; Elizabeth McKinstry
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9.  Patient reports of preventable problems and harms in primary health care.

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10.  Comparison of three methods for estimating rates of adverse events and rates of preventable adverse events in acute care hospitals.

Authors:  Philippe Michel; Jean Luc Quenon; Anne Marie de Sarasqueta; Olivier Scemama
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3.  Baseline characteristics and patient reported outcome data of patients prescribed etanercept: web-based and telephone evaluation.

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Authors:  Susan J Stocks; Ailsa Donnelly; Aneez Esmail; Joanne Beresford; Carolyn Gamble; Sarah Luty; Richard Deacon; Avril Danczak; Nicola Mann; David Townsend; James Ashley; Paul Bowie; Stephen M Campbell
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Review 7.  Patients' views of adverse events in primary and ambulatory care: a systematic review to assess methods and the content of what patients consider to be adverse events.

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8.  Frequency and nature of potentially harmful preventable problems in primary care from the patient's perspective with clinician review: a population-level survey in Great Britain.

Authors:  Susan Jill Stocks; Ailsa Donnelly; Aneez Esmail; Joanne Beresford; Sarah Luty; Richard Deacon; Avril Danczak; Nicola Mann; David Townsend; James Ashley; Carolyn Gamble; Paul Bowie; Stephen M Campbell
Journal:  BMJ Open       Date:  2018-06-13       Impact factor: 2.692

9.  Monitoring adverse social and medical events in public health trials: assessing predictors and interpretation against a proposed model of adverse event reporting.

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  10 in total

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