LEAD 6523 Module 2 Logic Model Example

From Five Paramedics to Fewer Night Calls: A Logic Model for a Rural Community Paramedicine Program, With the Assumptions Each Arrow Depends On

Student Name

American College of Education

LEAD6523: Planning, Evaluation, and Accountability

Module 2 Assignment

Instructor Name

October 19, 2026

Introduction

Module 1 found that 72 frequent callers account for about a fifth of the ambulance calls in the rural Oklahoma county where I manage emergency medical services, and that their most pressing unmet needs are chronic disease management, follow-up after hospital discharge and medication support. This paper sets out the logic of a community paramedicine program designed for those needs. Drawing the program's logic, from what it spends to what it hopes to change, forces its hidden bets into the open.

Why a Logic Model

McLaughlin and Jordan (1999) described logic models as a way for managers to tell their program's performance story: a plausible, sensible account of how resources and activities lead to outputs and to short-, intermediate- and long-term outcomes for the people served, along with the external influences that can help or hinder them. Public health's standard evaluation framework puts the same task near the start of any evaluation: before measuring a program, describe how it is meant to work (Centers for Disease Control and Prevention, 1999). Funnell and Rogers (2011) add that the most useful program theories spell out not only the chain of results but the assumptions that hold each step together. For a new program with a thin evidence base, the model's most useful feature is that it shows which links are proven and which are hopes.

How the Model Was Built

The model was drafted in two sessions with the people who would run the program: three paramedics, the hospital discharge planner, the clinic's nurse practitioner and a family member of a frequent caller. Each session started from the right side of the model, the outcomes the group hoped for, and worked backward to the activities and resources needed to produce them, a practice that keeps a model from becoming a list of things the organization already wanted to do. The family member's contribution changed the model: she pointed out that her father's calls came at night, when no clinic was open, and the group added an activity, a paramedic phone line until midnight for enrolled patients, that the professionals had not thought of.

Inputs

The program's inputs are five paramedics with 120 hours of additional training in chronic disease, medication review and home safety, each working the program part-time; one dedicated response vehicle; standing orders and weekly case review from the clinic's nurse practitioner; referrals from the hospital's discharge planner; a shared electronic record view arranged with the clinic; and a two-year grant of about $310,000 from a regional health foundation, which covers training, the vehicle and staff time.

Activities and Outputs

Activities fall into four groups. A paramedic calls at the home of each enrolled heart failure or lung disease patient no more than three days after the hospital sends them home; they conduct scheduled visits every one to two weeks to check weight, vital signs, symptoms and medications; they review medications with a pharmacist by phone and set up pill organizers; and they assess home fall risks and connect patients with meal, volunteer driver and home health services. Outputs, the direct products, are counted as patients enrolled, visits completed, medication reviews done, referrals made and calls from enrolled patients answered by a community paramedic rather than an ambulance. The planning target is 45 enrolled patients in the first year with an average of 30 visits a week.

Outcomes

Short-term outcomes, within three to six months, are changes in knowledge and behavior: patients can describe their medication plan, weigh themselves daily and know whom to call when symptoms worsen, and a larger share of patients see a primary care clinician in the two weeks after leaving hospital. Intermediate outcomes, within a year, are changes in health care use: fewer 911 calls and emergency department visits by enrolled patients and fewer heart failure readmissions within 30 days. Long-term outcomes, over two to three years, are better quality of life and health for enrolled patients and more ambulance capacity for emergencies in the county. Every arrow from left to right is a claim, and the program is only as strong as its weakest one.

The Assumptions Behind the Arrows

Writing out the assumptions behind each link shows where the program is vulnerable. From inputs to activities: that paramedics trained in emergency care can learn and sustain a slower, relationship-based role, and that the clinic will keep its commitment to weekly case review. From activities to short-term outcomes: that patients will accept home visits, and that monitoring and teaching in the home change behavior. From short-term to intermediate outcomes: that better self-management and timely follow-up reduce crises severe enough to prompt 911 calls and readmissions. From intermediate to long-term outcomes: that fewer calls by enrolled patients translate into more ambulances available for emergencies, rather than simply into fewer billed transports. The research reviewed in Module 1 offers some support for the second and third assumptions in other settings and almost none for the first and fourth.

External Factors

Several factors outside the program could help or break the chain. The clinic's capacity is the most important: if new patients still wait five weeks, post-discharge visits will catch problems but cannot arrange timely primary care. Medicaid and insurer payment rules affect whether visits can be billed after the grant ends. Weather and distance limit how many homes a paramedic can reach in a day. And the hospital's own readmission efforts may change outcomes regardless of the program, which matters for evaluation. Staff turnover is a factor too: losing even one of the five trained paramedics would cut visit capacity by a fifth, so the model treats retention of the program's staff as a condition of success.

Who Might Be Left Out

A logic model can also show who the program might miss. Enrollment depends on hospital referral, so frequent callers who rarely reach the hospital, including people who decline transport, could be overlooked; the model therefore adds a second referral route from crews who meet such patients in the field. Patients who distrust government services may refuse visits from an agency vehicle, and the program will offer the option of an unmarked car. Spanish-speaking residents, a growing share of the county, will need visits in their language, which the current staff cannot provide without an interpreter line.

Links the Evaluation Must Test

The model points the evaluation in Module 3 toward three links. The first is participation: whether enough frequent callers enroll and stay, since outcomes cannot follow without it. The second is the step from visits to fewer calls and readmissions, the program's central claim. The third is the step from fewer calls by enrolled patients to more available ambulance capacity, which the county commission will care about most and which is least certain. Short-term knowledge outcomes are worth measuring but are not the program's justification.

Conclusion

The logic model turns a promising idea into a set of testable claims. It shows the resources the program needs, what paramedics will do and the chain of changes the program expects, and it makes visible the assumptions that most proposals leave implicit. Those assumptions, particularly about the paramedics' new role and about ambulance capacity, are where the evaluation must focus.

References

Centers for Disease Control and Prevention. (1999). Framework for program evaluation in public health. MMWR Recommendations and Reports, 48(RR-11), 1-40. https://www.cdc.gov/mmwr/preview/mmwrhtml/rr4811a1.htm

Funnell, S. C., & Rogers, P. J. (2011). Purposeful program theory: Effective use of theories of change and logic models. Jossey-Bass.

McLaughlin, J. A., & Jordan, G. B. (1999). Logic models: A tool for telling your program's performance story. Evaluation and Program Planning, 22(1), 65-72. https://doi.org/10.1016/S0149-7189(98)00042-1