Mitigation of patient harm from testing errors in family medicine offices: a report from the American Academy of Family Physicians National Research Network.
Qual Saf Health Care. 2008 Jun;17(3):201-8
Authors: Graham DG, Harris DM, Elder NC, Emsermann CB, Brandt E, Staton EW, Hickner J
OBJECTIVES: Little research has focused on preventing harm from errors that occur in primary care. We studied mitigation of patient harm by analysing error reports from family physicians’ offices. METHODS: The data for this analysis come from reports of testing process errors identified by family physicians and their office staff in eight practices in the American Academy of Family Physicians National Research Network. We determined how often reported error events were mitigated, described factors related to mitigation and assessed the effect of mitigation on the outcome of error events. RESULTS: We identified mitigation in 123 (21%) of 597 testing process event reports. Of the identified mitigators, 79% were persons from inside the practice, and 7% were patients or patient’s family. Older age was the only patient demographic attribute associated with increased likelihood of mitigation occurring (unadjusted OR 18-44 years compared with 65 years of age or older = 0.27; p = 0.007). Events that included testing implementation errors (11% of the events) had lower odds of mitigation (unadjusted OR = 0.40; p = 0.001), and events containing reporting errors (26% of the events) had higher odds of mitigation (unadjusted OR = 1.63; p = 0.021). As the number of errors reported in an event increased, the odds of that event being mitigated decreased (unadjusted OR = 0.58; p = 0.001). Multivariate logistic regression showed that an event had higher odds of being mitigated if it included an ordering error or if the patient was 65 years of age or older, and lower odds of being mitigated if the patient was between age 18 and 44, or if the event included an implementation error or involved more than one error. Mitigated events had lower odds of patient harm (unadjusted OR = 0.16; p<0.0001) and negative consequences (unadjusted OR = 0.28; p<0.0001). Mitigated events resulted in less severe and fewer detrimental outcomes compared with non-mitigated events. CONCLUSION: Nearly a quarter of testing process errors reported by family physicians and their staff had evidence of mitigation, and mitigated errors resulted in less frequent and less serious harm to patients. Vigilance throughout the testing process is likely to detect and correct errors, thereby preventing or reducing harm.
PMID: 18519627 [PubMed - in process]
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Screening and diagnosing depression in women visiting GPs’ drop in clinic in primary health care.
BMC Fam Pract. 2008 Jun 13;9(1):34
Authors: Stromberg R, Wernering E, Aberg-Wistedt A, Furhoff AK, Johansson SE, Backlund LG
ABSTRACT: BACKGROUND: Only half of all depressions are diagnosed in Primary Health Care (PHC). Depression can remain undetected for a long time and entail high costs for care and low quality of life for the individuals. Drop in clinic is a common form of organizing health care; however the visits are short and focus on solving the most urgent problems. The aim of this study was to investigate the prevalence and severity of depression among women visiting the GPsa drop in clinic and to identify possible clues for depression among women. METHODS: The two-stage screening method with ahigh risk feedbacka was used. Beckas Depression Inventory (BDI) was used to screen 155 women visiting two GPs drop in clinic. Women who screened positive (BDI score i;310) were invited by the GP to a repeat visit. Major depression (MDD) was diagnosed according to DSM-IV criteria and the severity was assessed with Montgomery-Asberg Depression Rating Scale (MADRS). Women with BDI score <10 constituted a control group. Demographic characteristics were obtained by questionnaire. Chart notations were examined with regard to symptoms mentioned at the index visit and were categorized as somatic or mental. RESULTS: The two-stage method worked well with a low rate of withdrawals in the second step, when the GP invited the women to a repeat visit.The prevalence of depression was 22.4% (95% CI 15.6-29.2). The severity was mild in 43%, moderate in 53% and severe in 3%. The depressed women mentioned mental symptoms significantly more often (69%) than the controls (15%) and were to a higher extent sick-listed for a longer period than 14 days. Nearly oen third of the depressed women did not mention mental symptoms.The majority of the women who screened as false positive for depression had crisis reactions and needed further care from health professionals in PHC. Referrals to a psychiatrist were few and revealed often psychiatric co-morbidity. CONCLUSION: The prevalence of previously undiagnosed depression among women visiting GPsa drop in clinic was high. Clues for depression were identified in the depressed womenas symptom presentation; they often mention mental symptoms when they have come to the GP for somatic reasons e.g. respiratory infections. We suggest that GPs do selective screening for depression when women mention mental symptoms and offer to schedule a repeat visit for follow-up rather than just recommending that the patient return if the mental symptoms do not disappear.
PMID: 18554388 [PubMed - as supplied by publisher]
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Chronic disease management in primary care: from evidence to policy.
Med J Aust. 2008 Apr 21;188(8 Suppl):S53-6
Authors: Dennis SM, Zwar N, Griffiths R, Roland M, Hasan I, Powell Davies G, Harris M
OBJECTIVES: To review the effectiveness of chronic disease management interventions for physical health problems in the primary care setting, and to identify policy options for implementing successful interventions in Australian primary care. METHODS: We conducted a systematic review with qualitative data synthesis, using the Chronic Care Model as a framework for analysis between January 1990 and February 2006. Interventions were classified according to which elements were addressed: community resources, health care organisation, self-management support, delivery system design, decision support and/or clinical information systems. Our major findings were discussed with policymakers and key stakeholders in relation to current and emerging health policy in Australia. RESULTS: The interventions most likely to be effective in the context of Australian primary care were engaging primary care in self-management support through education and training for general practitioners and practice nurses, and including self-management support in care plans linked to multidisciplinary team support. The current Practice Incentives Payment and Service Incentives Payment programs could be improved and simplified to encourage guideline-based chronic disease management, integrating incentives so that individual patients are not managed as if they had a series of separate chronic diseases. The use of chronic disease registers should be extended across a range of chronic illnesses and used to facilitate audit for quality improvement. Training should focus on clear roles and responsibilities of the team members. CONCLUSION: The Chronic Care Model provides a useful framework for understanding the impact of chronic disease management interventions and highlights the gaps in evidence. Consultation with stakeholders and policymakers is valuable in shaping policy options to support the implementation of the National Chronic Disease Strategy in primary care.
PMID: 18429737 [PubMed - in process]
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