More Than Just Reporting

The Primary Mental Health Care Minimum Data Set (PMHC MDS) is not simply a reporting obligation. For Primary Health Networks (PHNs), it is the backbone of how performance is measured and how success is demonstrated to the Department of Health. Through the PHN Performance and Quality Framework (PQF), the government uses this data to assess whether PHNs are delivering on key priorities like improving access, coordinating care, and ensuring services are high quality.

In other words, your PHN’s outcomes are judged through the lens of this dataset. The Department expects that PMHC MDS records are submitted within 31 days of service activity. This is not just a technical rule.

Timely and accurate reporting shows strong governance, helps inform planning, and keeps PHNs aligned with national expectations.

Why Delayed Reporting Hurts Performance

Too many PHNs still think of the PMHC MDS as something to complete when the submission is due. That approach means you only discover issues months after they have occurred. If outcome measures are not being collected properly, or if a provider is falling behind on referrals, the problem has already impacted client care by the time you notice.

This is where the PQF performance criteria matter. For example, one key indicator requires PHNs to ensure that outcome measures are completed at least 70 percent of the time. If you only check this at the six-month mark, you may find yourself scrambling to explain gaps. But if you monitor it monthly, you can see early whether you are trending below target and take action.

The difference is simple. Waiting for submissions leaves you in a reactive position. Embedding PQF targets into everyday reporting keeps you in control.

Turning Performance Criteria Into Live Indicators

The PQF is designed to provide a clear view of performance across all PHNs. The mental health indicators it includes are drawn directly from PMHC MDS fields. That makes them perfect candidates for real-time dashboards.

Here is what that might look like in practice:

• Outcome measure completion: Instead of aiming to scrape past 70 percent at reporting time, set an internal goal of 80 percent by month three. If rates drop below 60 percent midway through the quarter, that is your signal to investigate and support providers.
• Service volume and reach: If a program is supposed to engage 100 clients in a quarter, check halfway through whether you are at least at 50. Falling behind early gives you time to adjust referral pathways or outreach strategies.
• Data completeness: Make sure all mandatory fields are filled in weekly. Missing data is much easier to fix at the source than to clean up during a last-minute submission rush.
• Timeliness of reporting: Track whether each provider is entering data within the 31-day requirement. If someone is consistently backlogging, you can intervene before it becomes a systemic issue.
• Benchmarking: Compare your outcomes with national or regional averages. If your dropout rate is significantly higher than peers, that is a chance to look deeper and improve quality.

By treating these criteria as live indicators rather than submission requirements, PHNs can keep their finger on the pulse of service delivery.

Using Technology to Stay Ahead

Modern technology makes this work much easier. You do not need a massive IT team to set up meaningful monitoring. Many PHNs already use tools like Power BI to pull data into dashboards. Murray PHN, for example, shares live dashboards with both staff and providers. This allows everyone to see how services are performing and quickly fix problems before they grow.

North Western Melbourne PHN went even further, building a national digital platform for intake and referral that provides real-time reporting. What used to take days of work can now be done in minutes. The benefit is not just efficiency but confidence that the data is always current.

Other PHNs are experimenting with cloud-based platforms like Microsoft Fabric, which can automate the flow of data from different sources into a central view. Whether you use a big solution or a simple dashboard, the principle is the same: bring PQF criteria into day-to-day monitoring so there are no surprises at submission time.

Building a Culture Around Data

The tools are only one part of the story. Leadership has to create a culture where data is reviewed regularly and acted upon. That means including data in program management discussions, holding monthly reviews of dashboards, and agreeing in advance on what actions will be taken if performance slips.

It is also important to involve providers. Sharing performance dashboards creates transparency and encourages them to keep data accurate and timely. When people know their results are being looked at in real time, quality improves naturally.

A National Expectation

Every PHN across Australia is measured under the same framework. Communities and governments want to know not only how much service is being delivered, but how effective that service is. Using PMHC MDS data to track PQF indicators positions your PHN to answer those questions with confidence. It also allows you to showcase successes, highlight areas for improvement, and strengthen your credibility as a leader.

On the other hand, if issues only become visible when the Department reviews your six-monthly submission, it can undermine confidence in your oversight. In today’s environment, staying on top of data is not optional. It is an expectation.

From Reporting to Leadership

The PMHC MDS and the PHN Performance and Quality Framework are powerful tools when used together. They give leaders the chance to shift from reactive compliance to proactive management. By setting internal targets that align with PQF criteria, embedding them in real-time dashboards, and fostering a culture of regular review, PHNs can avoid surprises, strengthen accountability, and improve outcomes for their communities.

The question for PHN leaders is simple: Do you know, right now, whether you are meeting your PQF targets? If the answer is no, it is time to change how you use your data. The technology is there, the framework is clear, and the responsibility is yours.

Written By: Bernard Herrok, proofed by AI.