Informatics in Primary Care (BCS, The Chartered Institute for IT)
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Accuracy of online health information about controlling childhood fever during the H1N1 influenza pandemic
Get PDFAdoption of information technology in primary care physician offices in New Zealand and Denmark, part 5: final comparisons
Get PDFThis is the last in a series of five papers about the use of computing technology in general practitioner (GP) practices in Denmark and New Zealand. This paper introduces a unique comparison instrument developed for this study using the best evidence available namely data was pulled from centralised databases and was indisputable (e.g. percentage of primary care physicians who send medication prescriptions electronically to pharmacies). Where the data was simply not available, estimates were made. Since the reliability of the data on the use of computers by primary care physicians is so variable and in some case simply not available, the authors also introduce the use of a Cochrane-like confidence factor (CF) to each comparison measure. The paper draws particular attention to the fact that both countries have a highly visible central unifying body or what might be called a Health System Integrator; though Denmark s Medcom is a pseudo government agency New Zealand's HealthLink is a private company, both play critical roles in the success story of these two countries
Clinical informatics to improve quality of care: a population-based system for patients with diabetes mellitus
Get PDFBackground The prevalence of diabetes mellitus is increasing in the USA. However, control of intermediate outcome measures remains substandard. Recently, significant emphasis has been placed on the value of electronic medical records and informatics systems to improve the delivery of health care.
Objective To determine whether a clinical informatics system improves care of patients with diabetes mellitus.
Methods In this quality improvement pilot initiative, we identified 48 patients with diabetes mellitus who were due for their annual haemoglobin A1c (HbA1c), low-density lipoprotein (LDL) and microalbumin tests. Through our newly developed clinical informatics initiative, patients were reminded to schedule tests and a physician appointment. Seventy-five patients without reminders served as controls.
Results A significant improvement in LDL control was achieved in the intervention group (35.4% vs 13.3%; P=0.004). The intervention group had a greater percentage of patients who underwent the three tests, and members of this group also showed greater control of haemoglobin A1c, but these differences were not statistically significant.
Conclusions A clinical informatics system, used to deliver proactive, co-ordinated care to a population of patients with diabetes mellitus, can improve process and also quality outcome measures. Larger studies are needed to confirm these early findings
The impact of a physician-directed health information technology system on diabetes outcomes in primary care: a pre- and post-implementation study
Get PDFPurpose To determine the impact of a physiciandirected, multifaceted health information technology (HIT) system on diabetes outcomes.
Methods A pre/post-interventional study.
Setting and participants The setting was Providence Primary Care Research Network in Oregon, with approximately 71 physicians caring for 117 369 patients in 13 clinic locations. The study covered Network patients with diabetes age 18 years and older.
Intervention The study intervention included implementation of the CareManagerTM HIT system which augments an electronic medical record (EMR) by automating physician driven quality improvement interventions, including point-of-care decision support and care reminders, diabetes registry with care prompts, performance feedback with benchmarking and access to published evidence and patient educational materials.
Measures The primary clinical measures included the change in mean value for low density lipoprotein (LDL) target <100 mg/dL or 2.6 mmol/l, blood pressure (BP) target <130/80 mmHg and glycated haemoglobin (HbA1c) target <7%, and the proportion of patients meeting guideline-recommended targets for those measures. All measures were analysed using closed and open cohort approaches.
Results A total of 6072 patients were identified at baseline, 70% of whom were continuously enrolled during the 24-month study. Significant improvements were observed in all diabetes related outcomes except mean HbA1c. LDL goal attainment improved from 32% to 56% (P=0.002), while mean LDL decreased by 13 mg/dL (0.33 mmol/l, P=0.002). BP goal attainment increased significantly from 30% to 52%, with significant decreases in both mean systolic and diastolic BP. The proportion of patients with an HbA1c below 7% was higher at the end of the study (P=0.008). Mean patient satisfaction remained high, with no significant difference between baseline and follow-up. Total Relative Value Units per patient per year significantly increased as a result of an increase in the number of visits in year one and the coding complexity throughout.
Conclusion Implementation of a physician-directed, multifaceted HIT system in primary care was associated with significantly improved diabetes process and outcome measures
Effectiveness of an HbA1c tracking tool on primary care management of diabetes mellitus: glycaemic control, clinical practice and usability
Get PDFObjective To determine if a laboratory data report (the HbA1c Tracking Tool) could be used as an effective intervention to improve diabetes management.
Design A longitudinal quasi-experimental cohort design was used to test the effectiveness of an HbA1c summary report sent to primary care physicians for all patients having HbA1c levels greater than 7%. Setting Moncton, New Brunswick, Canada.
Sample selection Administrative data from all adult patients with diabetes who had had at least two HbA1c measurements within the year prior to the initiation of the HbA1c Tracking Tool, and who had had five years of HbA1c measurements (2002-2007) overall was included.
Interventions In March 2006 all primary care physicians began receiving HbA1c summary reports (through the HbA1c Tracking Tool) as a means to improving the management of diabetes.
Main outcome measures (a) patient glycaemic control as indicated by HbA1c levels, (b) physician adherence to practice guidelines as indicated by measuring the mean number of HbA1c tests ordered per patient per year, and (c) physician usage rates of the HbA1c Tracking Tool in clinical practice.
Results The sample (n=955)was divided into three subgroups based on flagged HbA1c level (7_9%). The strongest effect of the intervention was found in the two groups with the poorest glycaemic control. The effect was stronger in the >9% group (from 10.1 to 9.3%), than in the 8_9% group (a drop of 8.5 to 8.3%). Longitudinal analyses over a five-year period indicated the same findings. Patients were also found to receive more tests across time (from 2.45 tests per year to 3.0 across five years). In terms of usage, 92.1% of the physicians surveyed used the tool in their practice.
Conclusion Routinely collected hospital laboratory data can be used both as the basis for an information- based intervention and as a tool to monitor quality of diabetes care
Many family physicians will not manually update PDA software: an observational study
Get PDFBackground In a prospective study to explore connections between clinical information delivery and information retrieval, 41 Canadian family physicians searched an electronic knowledge resource (EKR) as needed for practice. Research software, called the Information Assessment Method (IAM), prompted family physicians to report on the situational relevance, perceived cognitive impact and application of their retrieved information hits. Both the IAM and the EKR needed periodic updating to properly address our research questions.
Objective To determine the frequency of software updating when manual or semi-automatic approaches are used by family physicians.
Methods Each family physician received a handheld computer (PDA) that ran the Windows Mobile 6 operating system. For technical reasons, both the IAM and the EKR were accessed offline on PDA. To update the EKR and the IAM, family physicians were asked to synchronise their PDA to their PC. Updating the IAM was a manual process, whereas updating the EKR was semi-automatic.
Results We found: (1) about 25% of family physicians never or rarely updated PDA software on their own, (2) a large number of software updates were never installed and (3) the semi-automatic method was associated with a small increase in the proportion of installed software updates (58.9% versus 48.6% for the manual method).
Conclusions When a wireless internet connection is not used to update PDA software, sociotechnical issues complicate mobile data collection and data transfer
Electronic patient record evaluation in community mental health
Get PDFBackground Deployment of electronic patient records (EPRs) is one of the primary goals of national NHS information technology (IT) initiatives. However, many systems come into disrepute through poor planning or design flaws, and media scrutiny focuses on these problems rather than the potential gains.
Objective To evaluate the deployment of an EPR in a community mental health setting.
Method A validated user questionnaire was issued to all clinically qualified staff working in community mental health teams followed by interview and validation phases. The study encompassed both quantitative and qualitative mechanisms to establish the efficacy and usability of the system.
Results The questionnaire had a response rate of 49.3%. Overall, the response was positive, with almost no extreme negative responses. Of respondents, 88.5% were satisfied with system accuracy, while 91.7% of responses indicated that data was made available in a timely manner. Of those surveyed, 88.7% agreed the system was 'worth the time and effort required to use it'. Additionally, electronic notes are used more frequently than paper-based equivalents.
Conclusion The research concludes that the implemented system appears to offer a robust EPR that gives its users a high degree of satisfaction and provides tangible benefits to clinical staff
Attitudes and practices of recording diabetic patient information within an Australian general practice setting: an exploratory study
Get PDFBackground An accurate diabetes register enables a general practice to effectively monitor and manage the services for their patients with diabetes. This pilot project builds on the National Primary Care Collaboratives Program (a quality improvement programme for general practice) as the first change principle for managing chronic diseases.
Objectives The main aim of the project was to improve the systems management of electronic registers of people with diabetes in the general practice setting. The pilot project assessed the uptake, awareness and confidence levels amongst practice staff in improving the diabetes register.
Method This was completed by conducting a survey of general practitioners and practice nurses within one general practice in Perth, Western Australia. In addition, focus groups per and post intervention were facilitated to obtain practice staff 's views upon the issues around maintaining an efficient and updated patient register within a busy practice setting.
Results By the end of the project the general practice had an established diabetes register with defined and agreed practice systems
Using surrogate markers in primary electronic patient record systems to confirm or refute the diagnosis of diabetes
Get PDFBackground UK primary care records are computerised and these records are used for both research and quality improvement. However, there is disparity in the prevalence of diabetes found in epidemiological studies compared with that reported through the UK's national quality improvement scheme.
Objective To investigate how non-diagnostic computer data could be used to identify, confirm or refute prevalent cases of people with diabetes.
Method We carried out a literature review to identify the most accurate non-diagnostic markers. For each type of diabetes we focused on four broad areas; demographic details, biochemical markers, clinical features and therapeutic strategies. Sample markers were tested by calculating their positive predictive value (PPV) and sensitivity (Sn) and their ability to differentiate between types of diabetes.
Results Biochemical markers were useful in identifying cases of diabetes but not in differentiating between types of diabetes as the same plasma glucose criterion is used to diagnose Type 1, Type 2, and 'other' types of diabetes; the lack of a 'fasting' qualifier blunts the use of this marker.
Auto-immune markerswere the most accurate in identifying Type 1 diabetes but are not recorded frequently in primary care.
Clinical features of diabetes and therapeutic strategies were of some use - however, without time sequence data are difficult to interpret.
Raised plasma glucose (PG), and glycated haemoglobin (HbA1c), had useful PPV but low Sn. When PG was more than 7.0 and less than 11.1 mmol/l, PPV equalled 77.8% and Sn 48%; and when PG was 11.1, PPV equalled 92% and Sn 17%. For an HbA1c of more than 6.5%, PPV was 89% and Sn 73.3%, and for anHbA1c of more than 8, PPV was 92% and Sn 26%.
A person with a combination of aged under 30 years and prescribed insulin has an 84% PPV of Type 1 diabetes; if they also have a BMI 30 kg/m2 has a 5.3% PPV of Type 2 diabetes; if they are also hypertensive the PPV is 30%; Asian ethnicity increases PPV to 44%.
Conclusion Non-diagnostic data has the potential to confirm or refute the diagnosis of diabetes and identify its type