Detection of events of public health importance under the international health regulations: a toolkit to improve reporting of unusual events by frontline healthcare workers

<p>Abstract</p> <p>Background</p> <p>The International Health Regulations (IHR (2005)) require countries to notify WHO of any event which may constitute a public health emergency of international concern. This notification relies on reports of events occurring at the local level reaching the national public health authorities. By June 2012 WHO member states are expected to have implemented the capacity to "detect events involving disease or death above expected levels for the particular time and place" on the local level and report essential information to the appropriate level of public health authority. Our objective was to develop tools to assist European countries improve the reporting of unusual events of public health significance from frontline healthcare workers to public health authorities.</p> <p>Methods</p> <p>We investigated obstacles and incentives to event reporting through a systematic literature review and expert consultations with national public health officials from various European countries. Multi-day expert meetings and qualitative interviews were used to gather experiences and examples of public health event reporting. Feedback on specific components of the toolkit was collected from healthcare workers and public health officials throughout the design process.</p> <p>Results</p> <p>Evidence from 79 scientific publications, two multi-day expert meetings and seven qualitative interviews stressed the need to clarify concepts and expectations around event reporting in European countries between the frontline and public health authorities. An analytical framework based on three priority areas for improved event reporting (professional engagement, communication and infrastructure) was developed and guided the development of the various tools. We developed a toolkit adaptable to country-specific needs that includes a guidance document for IHR National Focal Points and nine tool templates targeted at clinicians and laboratory staff: five awareness campaign tools, three education and training tools, and an implementation plan. The toolkit emphasizes what to report, the reporting process and the need for follow-up, supported by real examples.</p> <p>Conclusion</p> <p>This toolkit addresses the importance of mutual exchange of information between frontline healthcare workers and public health authorities. It may potentially increase frontline healthcare workers' awareness of their role in the detection of events of public health concern, improve communication channels and contribute to creating an enabling environment for event reporting. However, the effectiveness of the toolkit will depend on the national body responsible for dissemination and training.</p

An appraisal: How notifiable infectious diseases are reported by Hungarian family physicians

L

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

<p>Abstract</p> <p>Background</p> <p>A 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.</p> <p>Methods</p> <p>40 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.</p> <p>Results</p> <p>Timeliness 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.</p> <p>Conclusion</p> <p>Regular 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.</p

Physician privacy concerns when disclosing patient data for public health purposes during a pandemic influenza outbreak

Background: Privacy concerns by providers have been a barrier to disclosing patient information for public health\ud purposes. This is the case even for mandated notifiable disease reporting. In the context of a pandemic it has been\ud argued that the public good should supersede an individual’s right to privacy. The precise nature of these provider\ud privacy concerns, and whether they are diluted in the context of a pandemic are not known. Our objective was to\ud understand the privacy barriers which could potentially influence family physicians’ reporting of patient-level\ud surveillance data to public health agencies during the Fall 2009 pandemic H1N1 influenza outbreak.\ud Methods: Thirty seven family doctors participated in a series of five focus groups between October 29-31 2009.\ud They also completed a survey about the data they were willing to disclose to public health units. Descriptive\ud statistics were used to summarize the amount of patient detail the participants were willing to disclose, factors that\ud would facilitate data disclosure, and the consensus on those factors. The analysis of the qualitative data was based\ud on grounded theory.\ud Results: The family doctors were reluctant to disclose patient data to public health units. This was due to concerns\ud about the extent to which public health agencies are dependable to protect health information (trusting beliefs),\ud and the possibility of loss due to disclosing health information (risk beliefs). We identified six specific actions that\ud public health units can take which would affect these beliefs, and potentially increase the willingness to disclose\ud patient information for public health purposes.\ud Conclusions: The uncertainty surrounding a pandemic of a new strain of influenza has not changed the privacy\ud concerns of physicians about disclosing patient data. It is important to address these concerns to ensure reliable\ud reporting during future outbreaks.University of Ottawa Open Access Author Fun

The highest risk for hypoglycemia after treatment for hyperkalemia is in the emergency department

Background and Objectives: Hypoglycemia is one of the most complications of treatment for hyperkalemia with insulin and glucose. The objective of this analysis was to test if rates of hypoglycemia following hyperkalemia treatment differ between the ED and inpatient units. Methods: We performed a retrospective observational study across 4 hospitals that were inclusive of consecutive ED and hospitalized adults that received insulin and 25 grams of glucose for the management of hyperkalemia over a 12-month period. We excluded patients treated in the setting of cardiac arrest. The primary outcome was hypoglycemia (glucose \u3c 70 mg/dL) following treatment. We performed chi-square and ANOVA comparisons between the ED, general practice units (GPU) and intensive care units (ICU). We then performed multivariate logistic regression to adjust for confounding variables in assessing the primary outcome. Results: The study included 1,291 patients, of whom 539 (41.2%) were female, 416 (31.9%) were on dialysis, and the mean age was 62.2 ±15.3 years. The cohort included 502 patients treated in the ED, 353 in the GPU, and 436 in the ICU. The mean pre-treatment potassium in ED patients (6.4 ±0.9 mEq/L) was higher (p\u3c0.001) compared to the GPU (5.9 ±0.5 mEq/L) and ICU patients (6.0 ±0.6 mEq/L). Pre-treatment glucose in ED patients (133 ±64 mg/dL) was lower (p\u3c0.001) than in the GPU (154 ±73 mg/dL) and ICU patients (158 ±78 mg/dL). There were 238 (18.4%) hypoglycemic events: 117 (23.3%) in the ED, 65 (18.4%) in the GPU, and 56 (12.8%) in the ICU (p\u3c0.001). After adjusting for gender, diabetes, dialysis, weight, age, creatinine, insulin dose, and pretreatment glucose, the odds of hypoglycemia complicating treatment of hyperkalemia in the ED was 1.9 (95% CI 1.3 - 2.8) compared to treatment in the ICU. Compared to the GPU, the higher OR was 1.3 (95% CI 0.9 - 1.9). Conclusion: In this study, patients treated for hyperkalemia in the ED had the highest adjusted odds of hypoglycemia compared to patients treated in the hospital

Improving the Safety of Insulin Treatment for Hyperkalemia

Study Objectives: This study’s objective was to determine key clinical predictors of hypoglycemia following insulin therapy for the emergent management of hyperkalemia and derive a safe insulin treatment strategy. Methods: We performed a retrospective observational study across 4 hospitals that was inclusive of consecutive ED and hospitalized adults that received insulin for the management of hyperkalemia over a 12-month period. We excluded patients treated in the setting of cardiac arrest. The primary outcome was hypoglycemia (glucose \u3c 70 mg/dL) following treatment. We performed multivariate logistic regression to determine clinical predictors of hypoglycemia. We then tested the pre-treatment glucose-insulin ratio (glucose divided by planned weight-based insulin dose) and tested its ability to alert clinicians to the risk of treatment related hypoglycemia. Results: The study included 1,307 patients, of whom 507 were in the ED and 800 were inpatient. The mean pre-treatment K was 6.1 (SD 0.76). Hypoglycemic events occurred 238 times (18.4%). Patients in the ED had the highest rate of hypoglycemic events (23.3%) compared to hospitalized patients (15.3%, p\u3c0.001). Patient’s with a pre-treatment glucose \u3c 100 mg/dl had 31.0% the rate of hypoglycemia compared to those with higher glucose levels (13.7%, p\u3c0.001). Adjusting for multiple clinical covariates, male sex (OR 1.4, 95% CI 1.1 - 2.0), insulin dosing \u3e 0.1 units/kg (OR 1.5, 95% CI 1.1 - 2.1), and pre-treatment glucose \u3c 100 mg/dl (OR 2.4, 95% CI 1.8 - 3.2) were significant predictors of hypoglycemia. The median glucose-insulin ratio was 1310 [IQR 915, 2025]. A ratio \u3c 1310 identified 71.9% of hypoglycemic events (OR 3.0, 95% CI 2.2 - 4.1). Conclusion: Male sex, insulin dose, and pre-treatment glucose are predictors of hypoglycemia in the treatment of hyperkalemia. Attention to the simple ratio of the pre-treatment glucose to weight-based insulin dose identifies most patients at risk of hypoglycemia and can alert clinicians to adjust glucose and insulin administration proactively

18 Improving the Safety of Insulin Treatment for Hyperkalemia

Study Objectives: This study’s objective was to determine key clinical predictors of hypoglycemia following insulin therapy for the emergent management of hyperkalemia and derive a safe insulin treatment strategy. Methods: We performed a retrospective observational study across 4 hospitals that was inclusive of consecutive ED and hospitalized adults that received insulin for the management of hyperkalemia over a 12-month period. We excluded patients treated in the setting of cardiac arrest. The primary outcome was hypoglycemia (glucose \u3c 70 mg/dL) following treatment. We performed multivariate logistic regression to determine clinical predictors of hypoglycemia. We then tested the pre-treatment glucose-insulin ratio (glucose divided by planned weight-based insulin dose) and tested its ability to alert clinicians to the risk of treatment related hypoglycemia. Results: The study included 1,307 patients, of whom 507 were in the ED and 800 were inpatient. The mean pre-treatment K was 6.1 (SD 0.76). Hypoglycemic events occurred 238 times (18.4%). Patients in the ED had the highest rate of hypoglycemic events (23.3%) compared to hospitalized patients (15.3%, p\u3c0.001). Patient’s with a pre-treatment glucose \u3c 100 mg/dl had 31.0% the rate of hypoglycemia compared to those with higher glucose levels (13.7%, p\u3c0.001). Adjusting for multiple clinical covariates, male sex (OR 1.4, 95% CI 1.1 - 2.0), insulin dosing \u3e 0.1 units/kg (OR 1.5, 95% CI 1.1 - 2.1), and pre-treatment glucose \u3c 100 mg/dl (OR 2.4, 95% CI 1.8 - 3.2) were significant predictors of hypoglycemia. The median glucose-insulin ratio was 1310 [IQR 915, 2025]. A ratio \u3c 1310 identified 71.9% of hypoglycemic events (OR 3.0, 95% CI 2.2 - 4.1). Conclusion: Male sex, insulin dose, and pre-treatment glucose are predictors of hypoglycemia in the treatment of hyperkalemia. Attention to the simple ratio of the pre-treatment glucose to weight-based insulin dose identifies most patients at risk of hypoglycemia and can alert clinicians to adjust glucose and insulin administration proactively