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PCS Clinical Audit Tool

PCS Clinical Audit Tool. “Using Data Wisely” Improving clinical data quality & identifying business opportunity. Factors limiting General Practice eHealth uptake. Lack of national Standards Patchy incentives for enhancement of information technology Limited investment in change management

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PCS Clinical Audit Tool

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  1. PCS Clinical Audit Tool “Using Data Wisely” Improving clinical data quality & identifying business opportunity

  2. Factors limiting General Practice eHealth uptake • Lack of national Standards • Patchy incentives for enhancement of information technology • Limited investment in change management • Limited focus on practice systems quality • No time to consider and review • Limited and variable support

  3. And the Outcome • Limited and patchy adoption of IS at the practice • Poor quality and lack of consistency in data • Lack of resources • Lack of integration into work practice

  4. Clinical Audit can assist here… • Simplify the assessment of data quality by the GP • Devolve some of the data quality issues to other practice staff • Support financial opportunities around data quality • Identify target population risk groups easily • Monitor data quality improvement

  5. An extract from an article in Australian Doctor

  6. Real Life Results

  7. Demonstration“CAT in (the) Practice”

  8. Screen shots from the PCS Clinical Audit Tool • For further information please contact: • John Johnston BSc DipSci AIMM • john.johnston@pencs.com.au • Mobile: 0408 276 742

  9. The Opening Screen of the PCS Clinical Audit System showing its 3 panes. At the left, the population snapshots from the Clinical Desktop System The General, Disease State and Medication Filters to the right and the Graphical Report Section to the Lower Right

  10. The Extracts area is a library of data snapshots taken from the GP desktop system over time so that changes in practice performance can be reviewed over time. • The Help Button exposes a training manual. • The Collect Button starts the preparation of an extract from the underlying GP data • The Hide Extracts button removes this pane after a specific snapshot has been selected for review

  11. The second pane containing the Filters of the data. Under general there are some broad patient selection criteria based on Age, Gender, Ethnicity, presentation regularity etc

  12. The Conditions Filter allows the operator to drill down through the clinical data by broad (and more specific) chronic disease classifications

  13. And the Medications Filter allows further investigation to identify patients that have been prescribed (or not prescribed) a chronic disease medication type All 3 Filters can be used in combination to assist the GP or practice staff member to generate more complex queries

  14. The 3rd Pane is the Reporting Pane where patient information is presented in a graphical way to highlight issues of interest.

  15. Here is a useful example of the Age and Gender Distribution of the Practice Population. Which age groups are not presenting at the practice? Are they at risk?

  16. In Australia there is a growing focus on improving GP clinical data quality. There are incentives to GPs if they can lift their Allergy recording to greater than 90% We have to get these patients here to less than 10% to qualify.

  17. So we can identify them by selecting the appropriate slice of the Pie Chart. In all examples in this presentation the patient identification information has been hidden as this is real data from a real practice

  18. And because Smoking is such an important contributor to chronic disease there are incentives for improving patient smoking status information as well…in this example 583 of the 1539 regular patients at this clinic have no smoking status recorded in the computer system

  19. Here is an example of using an Age Range Filter and a Body Mass Index Report to show the BMI status of a population

  20. And this is a Disease Prevalence Report for a practice population. Note that there are “undefined diabetics” here. They are patients with diabetic conditions for which no diagnosis of diabetes has been recorded. We can fix this by identifying the patients and correcting their records

  21. And the same Disease Prevalence Report can be represented in patient number terms… so you can see that there are 203 patients with Hypertension in a selected population of 1214 patients.

  22. So which of our practice patients have Heart Failure? Easy, Click on the Heart Failure Column and the system will display the patients.

  23. And for Women’s Health Checks which are normally scheduled for every 2 years there are incentive payments for GPs to focus on those women that are more than 4 years overdue. Note that nearly half of the eligible women have no Pap Smear Status recorded for them in the Clinical computer system.

  24. Some more examples around Lipids

  25. In this example we have selected the Diabetics and we are looking at HBA1c levels and BP status to assess levels of recording and of patient control. Continued next page…

  26. …And the BP results for the Diabetic population (remember – in this example we filtered the search to look at the Diabetic population only)

  27. Here is an example how the tool can really help manage quality. We have selected Diabetics and filtered those to determine which are not taking an Ace Inhibitor 1 2 3

  28. There are incentives to GPs to ensure that Diabetics receive the “best practice” cycle of care. This slide identifies the outstanding work that needs to be recorded for the Diabetics in this practice. We have selected patients overdue for Eye Exams and identified them.

  29. And this is a standard report produced by the system that presents patient coverage and health status metrics for patients with Diabetes and Coronary Heart Disease

  30. And using a well documented Cardiac Risk tool based on the Framingham studies we can identify patients “assumed to be healthy” who are at risk of heart attack. The red ones have 20% risk of an incident in the next 10 years

  31. But if there is not enough data in the system for the Risk Calculator to be useful this report advises the practice about the level of missing data. If the patients highlighted below have a record added for Smoking and BP they will comply with the risk calculator.

  32. Australia is also interested in identifying patients that are at risk of misadventure because of the number of medications they are taking. They offer substantial incentives to general practice to work with pharmacists to consider medication reviews for those taking 5 drugs or more.

  33. So which patients have records that show that they have more than 8 medications recorded in their current medication history?

  34. For further information John Johnston BSc DipSci AIMM john.johnston@pencs.com.au Mobile: 0408 276 742

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