Structured reports and feedback can improve general practice data quality

A Sydney study has shown that the use of structured data quality reports (SDQR) along with feedback sessions can improve the quality of routinely collected data in general practice electronic health records, although the improvements didn't quite meet targets set by the RACGP.

The study, conducted by Jane Taggart, Siaw-Teng Liaw and Hairong Yu of the Centre for Primary Health Care & Equity at the University of NSW, looked at four general practices in south-western Sydney over a 12-month period, with feedback sessions conducted at four, eight and 12 months with practice principals and practice managers.

The practices all participate in the university's electronic Practice Based Research Network (ePBRN), with data regularly extracted from their clinical information systems using the GRHANITE extraction and linkage software and examined for completeness, correctness, consistency and duplication of records.

In this study, the researchers looked at whether structured reports could improve EHR data quality for demographic information and clinical measurements such as date of birth, gender, height, weight, waist circumference, BMI, Aboriginal or Torres Strait Islander status, smoking, alcohol consumption, blood pressure, country of birth and allergies.

The SDQRs emphasised data quality metrics for each practice, compared with the previous reports and aggregate of all four practices, and benchmarked against the RACGP standards for data collection.

The patients were all “RACGP-active”, or those who had three or more visits in the two years prior to the data extraction.

The research found that while the quality of all of the variables measured improved significantly over the 12 months, particularly for recording allergies, only on two measures did they meet RACGP targets of “working towards” or “routinely recording” certain data, as set out in its Standards for General Practice 4th edition.

For example, at the start of the study, there were high rates of completeness of information recorded for gender (99 per cent) and date of birth (100 per cent) and relatively high rates for smoking (68 per cent).

However, the researchers report that recording of Aboriginal and Torres Strait Islander status (44 per cent), alcohol consumption (eight per cent), height (32 per cent), weight (37 per cent), waist circumference (five per cent) and BMI (17 per cent) were low. Allergies (84 per cent) had a relatively high rate while the recording of country of birth (two per cent) was low.

Apart from date of birth, all of these variables were below the RACGP targets.

Over the 12 month study, the recording of date of birth remained perfect and gender near perfect (99.99 per cent) and there were also significant positive changes in all other study variables.

“However, only date of birth and allergies (95 per cent) met the RACGP targets for all practices at the end of the 12 months,” they write. Smoking was almost at target (73 per cent), but the recording of alcohol assessment and consumption were well below.

“Most practices were working on improving their recording of height (37 per cent), weight (43 per cent) and BMI (21 per cent).”

Feedback from GPs explained a lot of this. “I think it is all about time constraints ...” one said.

“Computerisation ... does help but it takes the focus off why the patient is here and to get that balance I am still struggling with it and I will still struggle until I finish working as a general practitioner,” said another.

Others said things like measuring waist circumference in obese patients was uncomfortable, and alcohol assessment is difficult when patients are often not forthcoming on their drinking habits.

The researchers found that GPs and practice managers were proactive about implementing change in response to the reports and feedback, with some talking about ways to improve and achieve goals such as the RACGP standards for completeness of records.

“Benchmarking against their peers was a motivator for quality improvement, especially when their performance was lower than the average for the ePBRN,” they write.

The inability to reach the RACGP targets might mean that the targets are a bit unrealistic, the authors say. “The RACGP could consider including specific targets that are more useful and measurable so that practices have a clearer understanding of what they should be aiming to achieve in order to provide quality care.

“Taken together, these findings suggest that a multi-pronged and ecological approach across the data production cycle is required to improve the quality of data in EHRs.”

However, they say that the lack of a control group in the study makes it difficult to suggest a causal relationship or exclude other causal factors.

'Structured data quality reports to improve EHR data quality' is published in the International Journal of Medical Informatics.

Posted in Australian eHealth

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