Step-by-step guide to creating a logic model for your health program

A logic model is a visual map of how a health program is intended to work. It links resources, actions, deliverables, and changes in health or behaviour, making the underlying theory of change easier to discuss. It supports planning, coordination, funder reporting, and evaluation, but it is not by itself proof that the program caused a change.

The method is most useful when a team starts with a decision it needs to make: whether to launch, expand, redesign, or continue a program. The steps below move from scope to cause-and-effect, then test the result with stakeholders. This approach can be adapted for a council initiative, a not-for-profit service, or a program commissioned through an Australian Primary Health Network.

Set the program boundaries

Begin by defining what the program includes: its target population, location, delivery period, and responsible organisation. For example, a Brisbane program might combine dietitian referrals with community cooking sessions for adults at risk of type 2 diabetes. Recording these boundaries prevents teams from crediting the model with unrelated activities.

Write the aim as one sentence: the program will achieve a specified change for a defined group within a stated period. Then record the owner, delivery partners, and decision-maker. In Australia, Commonwealth, state and territory, local council, and primary health responsibilities can overlap, while Medicare funds many general practice services. A model should show who controls each part rather than blur those responsibilities.

Map resources and activities

Identify inputs as resources the team controls or can influence: staff hours, funding, facilities, information systems, partnerships, cultural expertise, and evidence. Do not list participants as an input; they are the people expected to benefit or contribute. Quantify resources where possible, including the staff time required to maintain referral pathways and collect outcome data.

Next, describe activities in the order they occur, using direct verbs such as co-design, train, refer, deliver, follow up, and review. Each activity needs a clear audience, owner, and delivery method. A council-funded walking program might train community facilitators, promote walking routes, organise peer groups, and monitor attendance rather than claiming vaguely to promote wellbeing.

A one-page first draft is often enough to expose gaps. Before the team workshop, participants can review professional learning resources to refresh related study and professional-development practices, then bring a rough sequence to colleagues for testing.

Link outputs to outcomes

Outputs are the products delivered, so they should be countable and observable. Examples include 30 peer leaders trained, 12 community events completed, 800 households receiving screening information, and a referral protocol operating in three clinics. Record quality standards and timing as well as volume; a workshop is not the same as 30 workers gaining a usable skill.

Outcomes describe changes in knowledge, behaviour, service use, or wellbeing. Separate immediate or short-term outcomes from intermediate and longer-term outcomes, then continue to the intended impact on population health. For a tobacco-control program, the sequence might move from increased knowledge of nicotine harms to more quit attempts, lower smoking prevalence, and reduced cardiovascular disease.

Keep the causal language proportionate. A program may contribute to a population outcome, but other policies, economic conditions, and services also shape it. Record plausible alternative explanations and evidence supporting the proposed pathway. This is where logic modelling becomes disciplined contribution analysis rather than a promotional diagram.

Make assumptions and indicators visible

Every model rests on assumptions and is affected by external factors. An assumption might be that primary care staff will refer eligible patients; an external factor might be a change in state screening policy, workforce shortages, digital access, or transport conditions. Australian teams should consider the different policy settings across states and territories, along with the effect of extreme weather on access and participation.

Attach indicators to every stage of the pathway. For each one, specify the measure, baseline, target, data source, collection frequency, and responsible person. Process indicators show whether activities ran; outcome indicators show whether intended changes occurred. Keep outcome measures feasible and sensitive enough to detect meaningful change within the program’s timeframe.

For cross-jurisdictional perspectives, the Lower New York State Public Health Training Center offers course and resource material that can inform team discussion about logic modelling and evaluation. Australian teams can adapt that discipline while aligning their work with the Australasian Evaluation Guidelines and relevant privacy obligations, including the Privacy Act 1988 where applicable.

Stress-test the model together

Bring people who know the work into the review: frontline staff, managers, finance partners, data specialists, participants, and community representatives. In a Sydney service, an Aboriginal and Torres Strait Islander community-controlled organisation may require a different governance process from a mainstream provider. Cultural authority, local language, and community ownership should appear in the model rather than remain outside it.

Use the comparison as a practical review: can another team see the resources, actions, products, and expected changes without relying on spoken explanation? In Australia’s competitive grant and procurement market, a well-structured logic model helps assess feasibility, value for money, and equity. It still requires credible evidence and realistic assumptions, so weak links should be revised rather than concealed.

Turn the model into action

Transfer the approved model into a spreadsheet or diagram that the team can maintain. Assign an owner to every indicator, set reporting dates, and define review triggers such as low referral completion or delayed data. Connect the logic model to the evaluation plan by testing which activities plausibly contributed to each observed change. Record decisions and revisions so it remains a record of the program’s current theory.

Create a one-page draft this week, bring it to one frontline colleague and one partner, and revise the causal pathway together. Share the final version with managers, participants, and funders so each person can connect their work to the intended health improvement. A maintained logic model gives the program a common direction, exposes delivery problems early, and makes future evaluation more credible.