Poor data and systems hamper health service delivery

Disjointed and outdated systems, poor data quality and project failures are hampering health initiatives in New Zealand.

Efforts to boost collaboration across regional health authorities in New Zealand have been stymied by a lack of robust data and poor information technology, the Auditor-General has found.

A new audit report (pdf) has found a “widespread awareness” of issues of data quality in the sector leading to a lack of confidence in the data available.

A lack of robust data leads to imprecision and inaccuracy, the report says. This, in turn, can lead to false assumptions, followed by poor decision-making.

“Some District Health Boards (DHBs) are using old and outdated patient management systems. Some DHBs have been unable to access information systems in their regions. The uneven progress has resulted in disjointed systems that contribute to poor-quality data and information.”

The audit report noted an earlier sector review had found the health sector has a history of poor execution of information technology projects. Because of this, many information systems are incomplete and inconsistent.

“This limits their usefulness to support clinical workstreams,” the report says.

It has also led to a lack of connectedness between state funded District Health Boards and the primary and private health sectors.

“Although we did not carry out a system-wide review of data, we found problems where we did look,” the report says. “Based on our limited testing, we share the concerns raised with us by people in the health and disability sector. These concerns were mostly about completeness of data, information technology systems, coding errors, and timeliness.”

The aggregation of patient and service data supports improvement in performance, service delivery, and planning, the report says.

“As funding and accountability systems become more complicated, the demand for good quality information – based on valid and reliable data – increases. Good quality data and information provides users and decision-makers with assurances about effectiveness, efficiency, and economy.”

A lack of confidence in the data available meant staff had to rely more on their experience than the available data in some instances.

Staff also face difficulties collecting data manually because it was too difficult to get data from the offcial computer systems.

In one instance, up to 20% of records could have incomplete data, with one or two incomplete fields in about 15% of cases and wrong data in about 5%. This was attributed to busy staff being under pressure.

In particular, the audit tested new Health Ministry Faster Cancer Treatment (FCT) indicators, important new measures for tracking how quickly cancer patients get treatment.

The guidance on FCT indicators was diffcult to understand, with complicated and ambiguous definitions. Each of the four DHBs whose patient records were audited had interpreted the definitions differently, the report says.

“We found various ‘teething issues’ with reliability. Information about cancer treatment timeliness was not comparable, because individual DHBs ‘started and stopped the clock’ at different points. There were many copies of guidance in circulation, between and within DHBs. We found discrepancies in, and missing, data.

“Some DHBs had to access many separate in-house information systems to extract data, but did not always have access to the electronic and paper information systems that they needed to verify dates.”

Progress towards effective implementation of IT is happening, the report finds, especially in the shift from local to regional systems.

“Before regional services planning was introduced, each DHB invested in its own information technology systems. This uncoordinated investment was sometimes not enough. Now, investing in regional information technology systems means that the quality of data available is improving.”

Good information technology systems can also help identify and avoid human failures in data entry, the report says.

“Human action – or inaction – caused many of the factors affecting data quality that we identified. However, a good information technology system can ensure that some of these errors are prevented, by ensuring that expected entries are well defined and that reporting happens quickly on what appear to be outliers.”