OUTCOME MEASUREMENT PLAN TEMPLATE

OUTCOME MEASUREMENT PLAN TEMPLATE

Part 1 (20 points total) (Do not enter anything into the gray areas)

Delete this message and the example content on page 2 before adding this to an appendix.

Outcome Objectives

 

1 point each

Outcome Domain and Indicators

1 point  each

Data Metric

How will the indicators be measured? Ie what formula or calculation will be used?

1 point each

Instrument or Tool

1 point each

Data Source
Where will the data come from? (ie practice or hospital database, distributed instrument, etc)

1 point each

Process Objective

Ex. To measure the number of staff able to be concordant with the new policy…

Domain 1 _
Patient Function
__________

 

 

 

 

[Indicator 1]

 

Change in systolic/diastolic BP

Pre/post BP readings comparison

Automated BP monitor readings, EHR BP logs

[Indicator 2]

 

% of patients achieving BP <140/90 Numerator = # patients with BP <140/90 / Denominator = total patients assessed   Outcome Objective To measure the impact of [intervention 1] on [your first outcome of interest]   Domain 2 _ Satisfaction __________         [Indicator 1] :   % of patients reporting satisfaction >80%

Numerator = # patients reporting satisfaction /

Satisfaction survey, interview notes

[Indicator 2]

Positive feedback count

 

Denominator = total survey respondents Counting number of positive comments from patients

 

Points:       /2                                        /6                                     /4                                               /4                                                    /4

Total Points Earned:     /20

Appendix A: Outcome Measurement Plan Table

Objective (Process or Outcome)

Outcome Domain

Indicators

Metrics (How Measured)

Instrument or Tool

Data Source

To measure the number of patients who received follow-up motivational interviewing and mobile reminders.

Patient Engagement

1. % of enrolled patients receiving follow-up sessions

2. % of patients receiving mobile reminders

1. Number of follow-up sessions completed / Total enrolled

2. Number receiving reminders / Total enrolled

Follow-up log, mHealth usage log

Clinic records, app backend

To measure the impact of culturally tailored interventions on medication adherence.

Quality

1. Change in MMAS-8 adherence scores

2. % of prescription refills completed

1. Mean pre/post MMAS-8 score

2. Number of refills / Total expected refills

MMAS-8 survey, Pharmacy refill tracker

Self-reported surveys, EHR, pharmacy data

To measure the impact of interventions on blood pressure control.

Patient Function

1. Change in average systolic/diastolic BP

2. % of patients achieving BP <140/90 1. Mean BP pre/post intervention 2. Number achieving target BP / Total evaluated Automated BP monitor readings, EHR BP logs Clinic BP records, EHR system To assess satisfaction with the culturally tailored interventions. Satisfaction 1. % of patients reporting satisfaction >80%

2. Positive feedback count

1. Number satisfied / Total respondents

2. Number of positive comments

Satisfaction survey (customized)

Patient surveys, interview notes

 

Data Collection

New data will be collected to assess the impact that the interventions have on medication adherence, blood pressure control and satisfaction of the patient. The data in this will be gathered using patient self-reports, Electronic Health Records (EHR) data extraction, and Mobile Health (mHealth) application use data (Reeves et al., 2021). More specifically, MMAS-8 adherence survey will be used to measure patient adherence, and we will record in clinic BP readings, as well as pharmacy refill logs, to track blood pressure levels. We will be evaluating satisfaction with the interventions using custom satisfaction surveys the post intervention.

Data collection methods will consist in structured surveys, real time mHealth tracking, and EHR reviews. For instance, they choose these tools to capture a range of data that will facilitate direct assessment of clinical and patient reported outcomes (Tian, 2024). I will select 60 of African American patients diagnosed with hypertension from the community clinic; for sample. To obtain a purposive sample in line with these criteria, the sample will be chosen based on current antihypertensive prescriptions and a history of nonadherence to medication regimens. This is to ensure that the sample is representative of the target population that can be benefited from interventions. In order to implement the full scale of the study, data collection instruments (MMAS-8 and the satisfaction surveys) will be piloted on a small subset of patients (approximately 10 participants). Thus, it is ensured that the instruments are culturally appropriate and understandable, and that they are measuring what was intended to be measured. Some adjustments will be made to enhance their reliability and validity.

Regular audits will be done and new data compared with baseline measures so that the quality and utility of the existing data can be determined. I will cross check self-report against EHR data to ensure accuracy where there are inconsistencies. Reliable data will be collected from patients, their EHRs, their pharmacy logs, and mHealth app platforms, but will cover both direct measures of clinical activity and their patient experiences (Tian, 2024). The data will be anonymized and stored in secure HIPAA complient password protected systems in order to protect it. Only authorized research personnel will have access, and confidentiality of patient information and integrity of the data will be protected.

 

Data Analysis and Interpretation

The interventions evaluated in the data analysis will be on medication adherence, blood pressure control and patient satisfaction. The indicators of success are highlighted as: a ≥ 25% improvement in medication adherence, a ≥ 10 mmHg reduction of systolic blood pressure, and a ≥ 80% patient satisfaction. Set on the basis of previous literature and clinical goals of the intervention, these standards have been set. The level to which these expectations will be met will be the measure of success. For example, a medication adherence will be taken as successful if MMAS-8 scores improved by at least 25% over baseline, and a blood pressure control is taken as successful if at least 80% of patients had a BP reading of < 140 / 90 mm Hg. Success of patient satisfaction will be dependent on if 80% of patients report high satisfaction with the interventions. It will have two steps regarding data analysis, one will be quantitative and other will be qualitative. The changes in medication adherence and blood pressure will be summarized using descriptive statistics and changes pre and post intervention will be compared using paired t tests (Taherdoost, 2022). We will perform chi square tests to evaluate the relationship between patient engagement and certain health outcomes, e.g. patient medication refill and blood pressure control (Masiero et al., 2023). Qualitative feedback from satisfaction surveys will be subject to thematic analysis to reveal key themes within the themes of the impact of the intervention on patients. The data interpretation and justification of the conclusions will be done by the evaluation team with key stakeholders. They will include primary care providers, community health workers, and project leads all of whom will bring the clinical and community perspective to the findings. The meeting will be on regular basis among these stakeholders, and participate with inputs from their expertise. The result is truly a data-driven conclusion that is also culture and applied patient care driven. Communication and Reporting Results Based on the findings from this evaluation, the data will be disseminated in multiple ways to ensure that it is used to improve the intervention and also to inform future practices. Results will be shared first with clinic staff by in person meetings and report. The findings will be emphasized by these communications and solicitation for continuing interest in the project because of such improvements in medication adherence and patient satisfaction (Reith‐Hall & Montgomery, 2023). The positive impacts of the interventions will be shared with the wider community through presentations and community workshops as a result of which community partners and stakeholders will also be informed about their. Evaluation findings will be used to refine and extend the intervention to other clinics or community settings if successful in terms of decision making. Additionally, the results will be used to advocate for additional funding or resources to sustain and scale the intervention. These findings will be implemented, by the clinic leadership and project stakeholders, to ensure that the program will remain evolving and adapting, accordingly. However, during the evaluation, we will carry out frequent communications with stakeholders. For example, this includes regular communication with clinic staff, patients, as well as funders and community organizations. The communication methods will be of emails, written reports, and presentation that suits their needs. Clinic staff will use in-person meetings to facilitate detailed conversations and emails and reports will be suitable for funders and additional community partners. These methods make sure that the outcomes are accessible to all concerned, then the outcomes can be used to drive further improvements in patient care and intervention effectiveness. Timeline (1 page) Please insert the detailed timeline into an appendix as previously provided, using the following structure. Activity Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Staff training on MI & mHealth tools ✔️ Patient recruitment & baseline data ✔️ ✔️ Intervention implementation (CHW + mHealth + MI) ✔️ ✔️ ✔️ ✔️ Midpoint data collection & evaluation ✔️ Final data collection ✔️ Data analysis & reporting ✔️ Summary and Conclusion (1/2 page) This PIP aims to improve hypertension management among African Americans by addressing medication adherence through culturally sensitive interventions. With targeted strategies like mHealth tools, community health workers, and motivational interviewing, the project seeks to engage patients in their care. The comprehensive evaluation plan ensures that interventions are continuously assessed and refined for better outcomes in this underserved population.       References Reeves, L., Robinson, K., McClelland, T., Adedoyin, C. A., Broeseker, A., & Adunlin, G. (2021). Pharmacist interventions in the management of blood pressure control and adherence to antihypertensive medications: a systematic review of randomized controlled trials.  Journal of Pharmacy practice ,  34 (3), 480-492. https://doi.org/10.1177/0897190020903573 Tian, O. G. (2024).  Confirmatory factor analysis of the Malaysia medication adherence assessment tool (MYMAAT) among patients with chronic medications  (Doctoral dissertation). https://eprints.usm.my/61110/1/Ong%20Gaik%20Tian-E.pdf Masiero, M., Spada, G. E., Sanchini, V., Munzone, E., Pietrobon, R., Teixeira, L., … & Pravettoni, G. (2023). A machine learning model to predict patients’ adherence behavior and a decision support system for patients with metastatic breast cancer: protocol for a randomized controlled trial.  JMIR Research Protocols ,  12 (1), e48852. https://www.researchprotocols.org/2023/1/e48852/ Taherdoost, H. (2022). What are different research approaches? Comprehensive review of qualitative, quantitative, and mixed method research, their applications, types, and limitations.  Journal of Management Science & Engineering Research ,  5 (1), 53-63. https://hal.science/hal-03741840/document Reith‐Hall, E., & Montgomery, P. (2023). Communication skills training for improving the communicative abilities of student social workers: A systematic review.  Campbell systematic reviews ,  19 (1), e1309. https://doi.org/10.1002/cl2.1309