What is the real impact of acute kidney injury?

Background: Acute kidney injury (AKI) is a common clinical problem. Studies have documented the incidence of AKI in a variety of populations but to date we do not believe the real incidence of AKI has been accurately documented in a district general hospital setting. The aim here was to describe the detected incidence of AKI in a typical general hospital setting in an unselected population, and describe associated short and long-term outcomes. Methods: A retrospective observational database study from secondary care in East Kent (adult catchment population of 582,300). All adult patients (18 years or over) admitted between 1st February 2009 and 31st July 2009, were included. Patients receiving chronic renal replacement therapy (RRT), maternity and day case admissions were excluded. AKI was defined by the acute kidney injury network (AKIN) criteria. A time dependent risk analysis with logistic regression and Cox regression was used for the analysis of in-hospital mortality and survival. Results: The incidence of AKI in the 6 month period was 15,325 pmp/yr (adults) (69% AKIN1, 18% AKIN2 and 13% AKIN3). In-hospital mortality, length of stay and ITU utilisation all increased with severity of AKI. Patients with AKI had an increase in care on discharge and an increase in hospital readmission within 30 days. Conclusions: This data comes closer to the real incidence and outcomes of AKI managed in-hospital than any study published in the literature to date. Fifteen percent of all admissions sustained an episode of AKI with increased subsequent short and long term morbidity and mortality, even in those with AKIN1. This confers an increased burden and cost to the healthcare economy, which can now be quantified. These results will furnish a baseline for quality improvement projects aimed at early identification, improved management, and where possible prevention, of AKI

Identifying patient preferences for communicating risk estimates: A descriptive pilot study

BACKGROUND: Patients increasingly seek more active involvement in health care decisions, but little is known about how to communicate complex risk information to patients. The objective of this study was to elicit patient preferences for the presentation and framing of complex risk information. METHOD: To accomplish this, eight focus group discussions and 15 one-on-one interviews were conducted, where women were presented with risk data in a variety of different graphical formats, metrics, and time horizons. Risk data were based on a hypothetical woman's risk for coronary heart disease, hip fracture, and breast cancer, with and without hormone replacement therapy. Participants' preferences were assessed using likert scales, ranking, and abstractions of focus group discussions. RESULTS: Forty peri- and postmenopausal women were recruited through hospital fliers (n = 25) and a community health fair (n = 15). Mean age was 51 years, 50% were non-Caucasian, and all had completed high school. Bar graphs were preferred by 83% of participants over line graphs, thermometer graphs, 100 representative faces, and survival curves. Lifetime risk estimates were preferred over 10 or 20-year horizons, and absolute risks were preferred over relative risks and number needed to treat. CONCLUSION: Although there are many different formats for presenting and framing risk information, simple bar charts depicting absolute lifetime risk were rated and ranked highest overall for patient preferences for format

Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>Electronic medical records contain valuable clinical information not readily available elsewhere. Accordingly, they hold important potential for contributing to and enhancing chronic disease registries with the goal of improving chronic disease management; however a standard for diagnoses of conditions such as diabetes remains to be developed. The purpose of this study was to establish a validated electronic medical record definition for diabetes.</p> <p>Methods</p> <p>We constructed a retrospective cohort using health administrative data from the Institute for Clinical Evaluative Sciences Ontario Diabetes Database linked with electronic medical records from the Deliver Primary Healthcare Information Project using data from 1 April 2006 - 31 March 2008 (N = 19,443). We systematically examined eight definitions for diabetes diagnosis, both established and proposed.</p> <p>Results</p> <p>The definition that identified the highest number of patients with diabetes (N = 2,180) while limiting to those with the highest probability of having diabetes was: individuals with ≥2 abnormal plasma glucose tests, or diabetes on the problem list, or insulin prescription, or ≥2 oral anti-diabetic agents, or HbA1c ≥6.5%. Compared to the Ontario Diabetes Database, this definition identified 13% more patients while maintaining good sensitivity (75%) and specificity (98%).</p> <p>Conclusions</p> <p>This study establishes the feasibility of developing an electronic medical record standard definition of diabetes and validates an algorithm for use in this context. While the algorithm may need to be tailored to fit available data in different electronic medical records, it contributes to the establishment of validated disease registries with the goal of enhancing research, and enabling quality improvement in clinical care and patient self-management.</p

An algorithm to identify patients with treated type 2 diabetes using medico-administrative data

<p>Abstract</p> <p>Background</p> <p>National authorities have to follow the evolution of diabetes to implement public health policies. An algorithm was developed to identify patients with treated type 2 diabetes and estimate its annual prevalence in Luxembourg using health insurance claims when no diagnosis code is available.</p> <p>Methods</p> <p>The DIABECOLUX algorithm was based on patients' age as well as type and number of hypoglycemic agents reimbursed between 1995 and 2006. Algorithm validation was performed using the results of a national study based on medical data. Sensitivity, specificity and predictive values were estimated.</p> <p>Results</p> <p>The sensitivity of the DIABECOLUX algorithm was found superior to 98.2%. Between 2000 and 2006, 22,178 patients were treated for diabetes in Luxembourg, among whom 21,068 for type 2 diabetes (95%). The prevalence was estimated at 3.79% in 2006 and followed an increasing linear trend during the period. In 2005, the prevalence was low for young age classes and increased rapidly from 40 to 70 for male and 80 for female, reaching a peak of, respectively 17.0% and 14.3% before decreasing.</p> <p>Conclusions</p> <p>The DIABECOLUX algorithm is relevant to identify treated type 2 diabetes patients. It is reproducible and should be transferable to every country using medico-administrative databases not including diagnosis codes. Although undiagnosed patients and others with lifestyle recommendations only were not considered in this study, this algorithm is a cheap and easy-to-use tool to inform health authorities. Further studies will use this tool with the aim of improving the quality of health care dedicated to diabetic patients in Luxembourg.</p

Health services research in the public healthcare system in Hong Kong: An analysis of over 1 million antihypertensive prescriptions between 2004-2007 as an example of the potential and pitfalls of using routinely collected electronic patient data

&lt;b&gt;Objectives&lt;/b&gt; Increasing use is being made of routinely collected electronic patient data in health services research. The aim of the present study was to evaluate the potential usefulness of a comprehensive database used routinely in the public healthcare system in Hong Kong, using antihypertensive drug prescriptions in primary care as an example.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Methods&lt;/b&gt; Data on antihypertensive drug prescriptions were retrieved from the electronic Clinical Management System (e-CMS) of all primary care clinics run by the Health Authority (HA) in the New Territory East (NTE) cluster of Hong Kong between January 2004 and June 2007. Information was also retrieved on patients’ demographic and socioeconomic characteristics, visit type (new or follow-up), and relevant diseases (International Classification of Primary Care, ICPC codes). &lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; 1,096,282 visit episodes were accessed, representing 93,450 patients. Patients’ demographic and socio-economic details were recorded in all cases. Prescription details for anti-hypertensive drugs were missing in only 18 patients (0.02%). However, ICPC-code was missing for 36,409 patients (39%). Significant independent predictors of whether disease codes were applied included patient age &gt; 70 years (OR 2.18), female gender (OR 1.20), district of residence (range of ORs in more rural districts; 0.32-0.41), type of clinic (OR in Family Medicine Specialist Clinics; 1.45) and type of visit (OR follow-up visit; 2.39). &lt;p&gt;&lt;/p&gt; In the 57,041 patients with an ICPC-code, uncomplicated hypertension (ICPC K86) was recorded in 45,859 patients (82.1%). The characteristics of these patients were very similar to those of the non-coded group, suggesting that most non-coded patients on antihypertensive drugs are likely to have uncomplicated hypertension. &lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusion&lt;/b&gt; The e-CMS database of the HA in Hong Kong varies in quality in terms of recorded information. Potential future health services research using demographic and prescription information is highly feasible but for disease-specific research dependant on ICPC codes some caution is warranted. In the case of uncomplicated hypertension, future research on pharmaco-epidemiology (such as prescription patterns) and clinical issues (such as side-effects of medications on metabolic parameters) seems feasible given the large size of the data set and the comparability of coded and non-coded patients

Optimal strategy to identify incidence of diagnostic of diabetes using administrative data

<p>Abstract</p> <p>Background</p> <p>Accurate estimates of incidence and prevalence of the disease is a vital step toward appropriate interventions for chronic disease like diabetes. A growing body of scientific literature is now available on producing accurate information from administrative data. Advantages of use of administrative data to determine disease incidence include feasibility, accessibility and low cost, but straightforward use of administrative data can produce biased information on incident cases of chronic disease like diabetes. The present study aimed to compare criteria for the selection of diabetes incident cases in a medical administrative database.</p> <p>Methods</p> <p>An exhaustive retrospective cohort of diabetes cases was constructed for 2002 using the Canadian National Diabetes Surveillance System case definition (one hospitalization or two physician claims with a diagnosis of diabetes over a 2-year period) with the Quebec health service database. To identify previous occurrence of diabetes in the database, a five-year observation period was evaluated using retrograde survival function and kappa agreement. The use of NDSS case definition to identify incident cases was compared to a single occurrence of an ICD-9 code 250 in the records using the McNemar test.</p> <p>Results</p> <p>Retrograde survival function showed that the probability of being a true incident case after a 5-year diabetes-free observation period was almost constant and near 0.14. Agreement between 10 years (maximum period) and 5 years and more diabetes-free observation periods were excellent (kappa > 0.9). Respectively 41,261 and 37,473 incident cases were identified using a 5-year diabetes-free observation period with NDSS definition and using a single ICD-9 code 250.</p> <p>Conclusion</p> <p>A 5-year diabetes-free observation period was a conservative time to identify incident cases in an administrative database using one ICD-9 code 250 record.</p

Can postponement of an adverse outcome be used to present risk reductions to a lay audience? A population survey

BACKGROUND: For shared decision making doctors need to communicate the effectiveness of therapies such that patients can understand it and discriminate between small and large effects. Previous research indicates that patients have difficulties in understanding risk measures. This study aimed to test the hypothesis that lay people may be able to discriminate between therapies when their effectiveness is expressed in terms of postponement of an adverse disease event. METHODS: In 2004 a random sample of 1,367 non-institutionalized Danes aged 40+ was interviewed in person. The participants were asked for demographic information and asked to consider a hypothetical preventive drug treatment. The respondents were randomized to the magnitude of treatment effectiveness (heart attack postponement of 1 month, 6 months, 12 months, 2 years, 4 years and 8 years) and subsequently asked whether they would take such a therapy. They were also asked whether they had hypercholesterolemia or had experienced a heart attack. RESULTS: In total 58% of the respondents consented to the hypothetical treatment. The proportions accepting treatment were 39%, 52%, 56%, 64%, 67% and 73% when postponement was 1 month, 6 months, 12 months, 2 years, 4 years and 8 years respectively. Participants who thought that the effectiveness information was difficult to understand, were less likely to consent to therapy (p = 0.004). CONCLUSION: Lay people can discriminate between levels of treatment effectiveness when they are presented in terms of postponement of an adverse event. The results indicate that such postponement is a comprehensible measure of effectiveness

Treatment decision-making and the form of risk communication: results of a factorial survey

BACKGROUND: Prospective users of preventive therapies often must evaluate complex information about therapeutic risks and benefits. The purpose of this study was to evaluate the effect of relative and absolute risk information on patient decision-making in scenarios typical of health information for patients. METHODS: Factorial experiments within a telephone survey of the Michigan adult, non-institutionalized, English-speaking population. Average interview lasted 23 minutes. Subjects and sample design: 952 randomly selected adults within a random-digit dial sample of Michigan households. Completion rate was 54.3%. RESULTS: When presented hypothetical information regarding additional risks of breast cancer from a medication to prevent a bone disease, respondents reduced their willingness to recommend a female friend take the medication compared to the baseline rate (66.8% = yes). The decrease was significantly greater with relative risk information. Additional benefit information regarding preventing heart disease from the medication increased willingness to recommend the medication to a female friend relative to the baseline scenario, but did not differ between absolute and relative risk formats. When information about both increased risk of breast cancer and reduced risk of heart disease were provided, typical respondents appeared to make rational decisions consistent with Expected Utility Theory, but the information presentation format affected choices. Those 11% – 33% making decisions contrary to the medical indications were more likely to be Hispanic, older, more educated, smokers, and to have children in the home. CONCLUSIONS: In scenarios typical of health risk information, relative risk information led respondents to make non-normative decisions that were "corrected" when the frame used absolute risk information. This population sample made generally rational decisions when presented with absolute risk information, even in the context of a telephone interview requiring remembering rates given. The lack of effect of gender and race suggests that a standard strategy of presenting absolute risk information may improve patient decision-making

Chronic disease risk factors associated with health service use in the elderly

<p>Abstract</p> <p>Background</p> <p>To examine the association between number and combination of chronic disease risk factors on health service use.</p> <p>Methods</p> <p>Data from the 1995 Nova Scotia Health Survey (n = 2,653) was linked to provincial health services administrative databases. Multivariate regression models were developed that included important interactions between risk factors and were stratified by sex and at age 50. Negative-binomial regression models were estimated using generalized estimating equations assuming an autoregressive covariance structure.</p> <p>Results</p> <p>As the number of chronic disease risk factors increased so did the number of annual general practitioner visits, specialist visits and days spent in hospital in people aged 50 and older. This was not seen among individuals under age 50. Comparison of smokers, people with high blood pressure and people with high cholesterol showed no significantly different impact on health service use.</p> <p>Conclusion</p> <p>As the number of chronic disease risk factors increased so did health service use among individuals over age 50 but risk factor combination had no impact.</p

Self-reported diabetes is associated with self-management behaviour: a cohort study

<p>Abstract</p> <p>Background</p> <p>The purposes of this cohort study were to establish how frequently people with physician-diagnosed diabetes self-reported the disease, to determine factors associated with self-reporting of diabetes, and to evaluate subsequent differences in self-management behaviour, health care utilisation and clinical outcomes between people who do and do not report their disease.</p> <p>Methods</p> <p>We used a registry of physician-diagnosed diabetes as a reference standard. We studied respondents to a 2000/01 population-based health survey who were in the registry (n = 1,812), and we determined the proportion who reported having diabetes during the survey. Baseline factors associated with self-report and subsequent behavioural, utilisation and clinical differences between those who did and did not self-report were defined from the survey responses and from linkage with administrative data sources.</p> <p>Results</p> <p>Only 75% of people with physician-diagnosed diabetes reported having the disease. People who did self-report were more likely to be male, to live in rural areas, to have longer disease duration and to have received specialist physician care. People who did not report having diabetes in the survey were markedly less likely to perform capillary blood glucose monitoring in the subsequent two years (OR 0.05, 95% CI 0.02 to 0.08). They were also less likely to receive specialist physician care (OR 0.55, 95% CI 0.37 to 0.86), and were less likely to require hospital care for hypo- or hyperglycaemia (OR 0.09, 95% CI 0.01 to 0.28).</p> <p>Conclusion</p> <p>Many people with physician-diagnosed diabetes do not report having the disease, but most demographic and clinical features do not distinguish these individuals. These individuals are much less likely to perform capillary glucose monitoring, suggesting that their diabetes self-management is inadequate. Clinicians may be able to use the absence of glucose monitoring as a screening tool to identify people needing a detailed evaluation of their disease knowledge.</p