CCPP Module 18, Section 1: The Pharmacist’s Role in Population Health Programs
MODULE 18: POPULATION HEALTH AND VALUE-BASED CARE

Section 18.1: The Pharmacist’s Role in Population Health Programs

A foundational look at what population health means in practice. We will explore how pharmacists use data analytics to identify high-risk patients, design targeted interventions, and manage the health of entire patient panels at scale.

SECTION 18.1

The Pharmacist’s Role in Population Health Programs

From Dispensing Transactions to Health Transformations: Managing the Health of an Entire Community.

18.1.1 The “Why”: A Fundamental Shift in the Pharmacy Landscape

For your entire career, the fundamental unit of your work has been the individual prescription for the individual patient standing in front of you. Your focus has been reactive and transactional: a prescription arrives, you verify its safety and appropriateness for that person at that moment, you dispense it, and you counsel on its use. This is the bedrock of pharmacy practice, a critical and life-saving function. However, the healthcare system is undergoing a seismic shift, moving away from a model that rewards the volume of services (fee-for-service) to one that rewards the value of those services (value-based care). This shift fundamentally changes the question from “Did we dispense the medication correctly?” to “Did our care lead to a better health outcome for the patient and a lower overall cost for the system?”

This new question cannot be answered by looking at one patient or one prescription at a time. It requires a new lens: the lens of population health. Instead of focusing solely on the patient in front of you, you are now asked to consider the health of an entire group of patients—a “panel” or “population.” This could be all the patients with diabetes in a primary care clinic, all the employees of a large company, or all the Medicare beneficiaries covered by a specific health plan. Your role is evolving from a dispenser of products to a manager of outcomes for this entire group.

Why is this happening? The traditional fee-for-service model has led to unsustainable cost growth without a proportional improvement in health outcomes. Value-based care models, which we will explore in depth in this module, financially incentivize health systems, clinics, and providers to keep their patient populations healthy and out of the hospital. Medication mismanagement is one of the single largest drivers of poor outcomes and avoidable costs. It is a multi-billion-dollar problem stemming from non-adherence, adverse drug events, and sub-optimal therapy. Health systems have finally recognized a profound truth that pharmacists have known all along: you cannot achieve better outcomes and lower costs without optimizing medication use. Therefore, the pharmacist is no longer a peripheral figure in the clinic; you are a central, indispensable asset in achieving the goals of value-based care.

This section is your introduction to this new mindset. We will demonstrate that the skills you already possess—your deep drug knowledge, your ability to identify problems, your patient counseling skills—are the exact skills needed to succeed in population health. The only change is the scale and the tools. You will learn to trade your spatula and counting tray for dashboards and data analytics, moving from managing a single patient’s profile to managing the medication-related risk of thousands. This is not a departure from pharmacy; it is the ultimate application of it.

Pharmacist Analogy: From Community Pharmacist to Public Health Director

Imagine you are the most respected pharmacist in a small, tight-knit town. In your traditional role, you are excellent at what you do. Mrs. Jones comes in, and you know her blood pressure medication causes a cough, so you call her doctor to switch her to an ARB. Mr. Smith picks up his insulin, and you ensure he has a new glucometer and knows how to use it. You solve problems one by one as they walk through your door. Your perspective is the individual.

Now, imagine the town’s mayor and council come to you with a new proposal. “We’re concerned about the overall health of our town,” they say. “Instead of just paying you for each prescription you fill, we want to pay you to make our whole town healthier. We want to see fewer heart attacks, fewer hospitalizations from asthma, and better diabetes control across all 10,000 residents. You have access to the clinic’s records and our insurance claims data. How would you do it?”

Your job has just shifted from community pharmacist to the town’s de facto public health director. Your mindset must change entirely. You can’t wait for Mrs. Jones to come in with a cough. You need to proactively run a report of everyone in town on an ACE inhibitor and identify who might be at risk. You can’t just help Mr. Smith when he comes to the counter; you need to identify every single person with diabetes in the town who has a high A1c and isn’t on the right medications, then reach out to them. You would analyze the data to find patterns: “Why is adherence to statins so low in the Northside neighborhood? Is it a cost issue? A health literacy issue?”

You would then design targeted programs (your “interventions”). You might launch a town-wide “know your numbers” blood pressure screening campaign. You might hold a diabetes education workshop at the community center. For the highest-risk residents—those with multiple diseases and recent hospital stays—you would schedule one-on-one comprehensive medication reviews. Your focus is no longer on the single transaction but on the health trends of the entire population. You are using the same core pharmacy knowledge, but you are applying it proactively and at scale, using data as your guide. This is the essence of population health pharmacy.

18.1.2 Deconstructing Population Health: A Pharmacist’s Glossary

To operate in this new environment, you must be fluent in its language. These terms are not just jargon; they represent the core concepts and operational frameworks that will define your daily work. Understanding them deeply is the first step to mastering your role.

Core Concept Formal Definition Translation for the Practical Pharmacist
Population Health The health outcomes of a group of individuals, including the distribution of such outcomes within the group. It is an approach that aims to improve the health of an entire human population. This means your responsibility expands beyond the individual patient. You are now accountable for improving specific health metrics (e.g., A1c control, blood pressure control, medication adherence) for a defined group of people, whether they actively seek your care or not.
Patient Panel A group of patients assigned to a specific provider or care team for whom that team is responsible for providing and coordinating care. This is your “roster.” In a primary care clinic, you might be assigned a panel of 5,000 patients. Your job is to manage the medication-related needs of every single person on that list. They are your professional responsibility.
Value-Based Care (VBC) A healthcare delivery framework where providers are paid based on patient health outcomes. It rewards providers for helping patients improve their health, reduce the effects and incidence of chronic disease, and live healthier lives in an evidence-based way. It’s the “why” behind population health. The health system gets paid for quality, not quantity. Your work in improving adherence and optimizing therapy directly generates the quality outcomes that allow the system to get paid. Your salary is justified by the value you create.
Risk Stratification A process for identifying and predicting which patients are at high risk, or are likely to be at high risk, and prioritizing them for interventions. This is how you manage a large panel without being overwhelmed. You use data to sort your entire patient panel into different “risk buckets” (e.g., healthy, rising-risk, high-risk). This allows you to focus your intensive, one-on-one efforts on the small percentage of “high-risk” patients who are driving the majority of poor outcomes and costs.
Gaps in Care The discrepancy between the care a patient should receive based on clinical guidelines and the care they are actually receiving. This is a primary target of your data analysis. You are looking for patients who are missing recommended care. For example, a patient with diabetes who has not had an A1c test in a year or is not on a statin represents a “gap in care” that you need to close.
Data Analytics The science of analyzing raw data to make conclusions about that information. In healthcare, this involves using EMR, claims, and other data to identify trends, predict risks, and measure performance. This is your new primary tool. Instead of just looking at a patient’s profile in the dispensing system, you’ll use a dashboard or software that aggregates data for your entire panel, allowing you to filter, sort, and identify opportunities for intervention at scale.

18.1.3 The Pharmacist as Data Analyst: Your New Core Competency

In traditional pharmacy, your primary data source was the patient profile and the prescription itself. In population health, you become an analyst, synthesizing vast amounts of data from multiple sources to paint a comprehensive picture of your panel’s health. Your ability to interpret this data is what allows you to move from being reactive to being powerfully proactive. Let’s do a deep dive into the data streams you will be working with.

The Three Pillars of Population Health Data

Think of yourself as a detective building a case. You need evidence from multiple sources to see the whole story. Your three main sources of evidence will be pharmacy claims, medical claims, and the Electronic Medical Record (EMR).

Data Source What It Contains What It Tells You (Strengths) What It Doesn’t Tell You (Weaknesses)
Pharmacy Claims Data A record of every prescription dispensed to a patient that was paid for by their insurance. Includes drug name (NDC), quantity, days supply, fill date, pharmacy, and prescriber.
  • The “Truth” of Adherence: This is the gold standard for measuring medication adherence (e.g., calculating PDC). A prescription in the EMR doesn’t mean the patient picked it up. A claim means money changed hands.
  • Full Medication Picture: Reveals medications filled from multiple prescribers (specialists, dentists) and multiple pharmacies, which may not all be captured in a single EMR.
  • Cost Insights: Shows patient copays and total drug costs, helping to identify cost-related barriers to adherence.
  • No Clinical Context: You see the drug, but you don’t see the “why.” There are no lab results, vitals, or diagnoses directly in the claim.
  • Cash Pays & Samples: Doesn’t capture prescriptions paid for with cash, discount cards, or free samples from a doctor’s office.
  • Indication ambiguity: A claim for gabapentin doesn’t tell you if it’s for neuropathy, seizures, or anxiety.
Medical Claims Data A record of every bill submitted to insurance for a medical service. Includes diagnosis codes (ICD-10), procedure codes (CPT), place of service, and provider.
  • Comprehensive Health History: Shows every diagnosis, hospitalization, ER visit, and specialist consultation, regardless of where it happened (as long as it was billed to insurance).
  • Identifies High-Cost Events: The best source for flagging recent hospitalizations or ER visits, which are powerful predictors of high future risk.
  • Validates Diagnoses: Confirms the conditions for which medications are being prescribed.
  • Lacks Clinical Detail: You see a diagnosis code for “diabetes,” but you don’t see the most recent A1c. You see a code for a hospitalization, but not the discharge summary.
  • Lag Time: Medical claims can take weeks or months to be processed and appear in the data, so it’s not “real-time.”
  • “Upcoding” and Errors: The data is for billing purposes, so it can sometimes be inaccurate or reflect “rule-out” diagnoses rather than confirmed conditions.
Electronic Medical Record (EMR) Data The clinical record from a specific doctor’s office or health system. Contains progress notes, problem lists, lab results, vital signs, allergies, and orders.
  • The Source of Clinical Truth: This is where you find the rich, real-time clinical details: the latest A1c, the blood pressure reading from yesterday, the provider’s thought process in the progress note.
  • Real-Time Information: Lab results and vital signs are available almost instantly, allowing for immediate action.
  • Provider Intent: You can see what was ordered, even if the patient didn’t fill it, revealing potential adherence issues at the point of prescribing.
  • Highly Fragmented: The EMR only shows what happened within that specific health system. It’s blind to care the patient received from outside specialists, urgent care clinics, or hospitals across town.
  • “Dirty” Data: Problem lists are often outdated, and medication lists can be cluttered with discontinued drugs, making them unreliable without reconciliation.
  • Access Can Be Limited: You may only have access to the EMR data of the clinic you work for, requiring you to rely on claims for the full picture.
The Synergy of Data: Building the Complete Patient Story

The real power comes not from using any single data source, but from synthesizing all three. Imagine this scenario:

  • EMR Data shows a 68-year-old male patient, Mr. Smith, with a diagnosis of diabetes and an A1c of 9.2%. His medication list includes metformin and glipizide.
  • Pharmacy Claims Data shows that Mr. Smith has only filled his metformin and glipizide twice in the last six months (PDC < 50%). It also reveals he recently filled a 5-day course of prednisone from an urgent care clinic across town.
  • Medical Claims Data shows a new ICD-10 diagnosis code for COPD from that urgent care visit, as well as an ER visit two months ago for “shortness of breath.”

Your Synthesis: A single data source would have given you an incomplete story. The EMR showed uncontrolled diabetes. The pharmacy claims revealed profound non-adherence and a steroid prescription that could worsen his hyperglycemia. The medical claims identified a new, high-risk comorbidity (COPD) and a recent ER visit. By combining them, you have a clear picture: Mr. Smith is a very high-risk patient with uncontrolled diabetes, severe medication non-adherence, and a new diagnosis of COPD who is likely having exacerbations. He needs an immediate, intensive intervention. This is the work of a population health pharmacist.

18.1.4 The Art and Science of Risk Stratification

You have a panel of 5,000 patients. You cannot possibly provide intensive, one-on-one care to all of them. Risk stratification is the essential process of using data to sort this large population into meaningful tiers of risk, allowing you to allocate your time and resources most effectively. The fundamental principle is that a small percentage of the population (typically 5-10%) drives a disproportionately large share (often 50% or more) of the total healthcare costs and poor outcomes. Your primary job is to find that 5-10%.

This process is not arbitrary. It’s a systematic layering of data points to create a risk score for each patient. While the specific algorithms can be complex and proprietary, they are all built on the same foundational elements.

Visualizing the Risk Stratification Pyramid

Think of your patient panel as a pyramid. Your goal is to identify the patients at each level and apply an appropriate level of intervention.

Tier 3: Complex / High-Risk (5%)
1-on-1 CMM, Care Coordination
Tier 2: Rising-Risk (15-20%)
Targeted MTM, Disease State Education
Tier 1: Generally Healthy (75-80%)
Automated Outreach, Health Education, Preventive Care

Masterclass Table: The Building Blocks of a Risk Score

How does a patient get assigned to one of these tiers? It’s based on an aggregation of risk factors. A patient’s “score” increases as they accumulate more of these factors.

Risk Domain Specific Data Points (Examples) Why it Matters & How it’s Used
Demographics
  • Age (e.g., > 65)
  • Gender
 This is the base layer. Advanced age is one of the strongest independent predictors of health risk and cost. It provides initial context.
Clinical Complexity
  • Number of chronic conditions (e.g., Diabetes, CHF, CKD, COPD)
  • Specific high-risk diagnoses (e.g., Cancer, End-Stage Renal Disease)
  • Lab values (e.g., A1c > 9%, eGFR < 30)
 This is the core of clinical risk. The more chronic diseases a patient has, the higher their risk. Specific conditions like ESRD automatically place a patient in the highest risk tier. Lab values provide objective evidence of disease control.
Utilization History
  • Hospitalization within the last 6-12 months
  • Two or more ER visits in the last 6 months
  • Skilled Nursing Facility (SNF) stay
 Past utilization is the single best predictor of future utilization. A recent hospitalization is a massive red flag. It indicates that the patient’s condition was severe enough to require acute care and that they are at extremely high risk for readmission. This is a powerful and heavily weighted factor in any risk model.
Medication-Related Risk
  • Polypharmacy (e.g., > 10-15 unique medications)
  • Use of high-risk medications (e.g., anticoagulants, insulin, opioids)
  • Poor adherence (PDC < 80%) to critical medications
  • Use of inappropriate medications in the elderly (Beers Criteria)
 This is the pharmacist’s domain. Medication complexity is a direct proxy for clinical complexity and risk of adverse events. Non-adherence is a direct predictor of disease exacerbation. Your role is to specifically identify and mitigate this layer of risk.
Social Determinants of Health (SDOH)
  • Zip code (proxy for socioeconomic status)
  • Documented housing or food insecurity
  • Lack of transportation
  • Low health literacy
 This is an increasingly critical layer. A patient can have the perfect drug regimen, but if they can’t afford it, can’t get to the pharmacy to pick it up, or don’t understand how to take it, the regimen will fail. Identifying these non-clinical barriers is essential for creating effective interventions.

Patient Personas: Bringing the Risk Tiers to Life

Let’s move from the abstract to the concrete. Here are examples of patients you would find in each tier.

  • Tier 1 – “Generally Healthy” – Susan: Susan is 45 years old with well-controlled hypothyroidism, for which she takes levothyroxine. Her PDC is 95%. She has no other chronic conditions and hasn’t been to the ER or hospital in years. Your Intervention: Low-touch, automated. Ensure she’s up to date on preventive screenings (e.g., mammogram) and vaccinations via automated reminders. No intensive pharmacist intervention needed.
  • Tier 2 – “Rising-Risk” – David: David is 58 years old with hypertension, hyperlipidemia, and newly diagnosed Type 2 Diabetes. His A1c is 8.1%. He’s on metformin, lisinopril, and atorvastatin. His PDC for his statin is only 65% because he read something online about muscle pains. He has no recent hospitalizations. Your Intervention: Targeted. David’s data profile would flag him for “uncontrolled diabetes” and “statin non-adherence.” He is a perfect candidate for a targeted MTM session to address his statin concerns, provide diabetes education, and discuss the importance of adherence.
  • Tier 3 – “Complex/High-Risk” – Maria: Maria is 72 years old with CHF (EF 30%), COPD, CKD Stage 4 (eGFR 25), and A-Fib. She takes 16 different medications, including furosemide, apixaban, carvedilol, and multiple inhalers. Pharmacy and medical claims show she was hospitalized for a CHF exacerbation two months ago and visited the ER last week for shortness of breath. Her PDC for her anticoagulant is 70%. Your Intervention: High-touch, intensive, and immediate. Maria is a top priority. She requires a comprehensive medication management (CMM) visit to review every medication for appropriateness, safety, and adherence. You need to coordinate with her cardiologist and PCP, provide intensive inhaler technique education, and address her apixaban adherence. You will likely have weekly or bi-weekly follow-up calls with her until she is stable.

18.1.5 From Data to Action: Designing and Implementing Targeted Interventions

Identifying high-risk patients is only half the battle. The true value of a population health pharmacist lies in designing and executing effective, evidence-based interventions to mitigate that risk. This is where your clinical skills, communication abilities, and problem-solving acumen come to the forefront. The intervention must match the risk level and the specific problem identified in the data.

Masterclass Table: Linking Data-Identified Problems to Pharmacist-Led Interventions

This table is your playbook. It translates the abstract findings from your data analysis into concrete, actionable steps you can take to improve the health of your panel.

Data-Identified Problem / Gap in Care Risk Tier Typically Affected Pharmacist-Led Intervention Suite Key Counseling & Action Points
Adherence Gap: PDC < 80% for Chronic Meds (e.g., Statins, RAS inhibitors, DOACs) Tier 2 (Rising-Risk)
  • Targeted MTM session (telephonic or in-person)
  • Medication synchronization enrollment
  • Barrier assessment (cost, side effects, health beliefs)
  • Switch to 90-day supplies
  • “I see from your records you’ve only been able to pick up your cholesterol pill about half the time. Can we talk about what’s making it difficult?”
  • Explore patient-specific barriers. Is it cost? Offer to investigate lower-cost alternatives or patient assistance programs. Is it a side effect? Provide education and offer to discuss alternatives with the prescriber. Is it forgetfulness? Recommend pillboxes and med sync.
Therapeutic Gap: Uncontrolled Diabetes (A1c > 9%) Tier 2 or 3 (Rising/High-Risk)
  • Comprehensive Medication Management (CMM)
  • Review of guideline-directed medical therapy (GLP-1s, SGLT2is)
  • Continuous Glucose Monitor (CGM) data review
  • Collaboration with PCP for therapy intensification
  • Review the full regimen. Is the patient on agents with proven cardiovascular benefits?
  • “Dr. Smith, I just completed a review with our mutual patient, David. His A1c is still 9.1% on metformin and glipizide. Per the ADA guidelines, I’d like to recommend adding an SGLT2 inhibitor like empagliflozin for its proven cardiovascular and renal benefits. Would you be open to me prescribing that per our collaborative practice agreement?”
Safety Gap: High-Risk Medication Use in Elderly (e.g., Beers Criteria meds like glyburide, benzodiazepines) Tier 2 or 3 (Rising/High-Risk)
  • Targeted chart review and deprescribing consultation
  • Patient counseling on risks (falls, confusion)
  • Recommendation of safer alternatives to the prescriber
  • “Mrs. Davis, I wanted to talk about the sleeping pill you’ve been taking. We know that in patients over 65, it can increase the risk of falls and confusion. There might be safer ways to help you get a good night’s rest. Would you be open to me discussing some alternatives with your doctor?”
  • Never recommend abrupt discontinuation. Always propose a gradual taper plan.
Utilization Red Flag: Recent Hospitalization for Chronic Condition (e.g., CHF, COPD) Tier 3 (High-Risk)
  • Post-discharge CMM within 72 hours (Transitions of Care)
  • Thorough medication reconciliation to identify and resolve discrepancies
  • Intensive patient education on new medications
  • Ensure follow-up appointments are scheduled
  • This is your highest priority intervention. The goal is to prevent readmission.
  • Compare the hospital discharge medication list against the patient’s pre-admission list and their pharmacy claims. Discrepancies are almost guaranteed.
  • Confirm the patient understands their new regimen, especially changes in doses or new additions. “Let’s go through each of your pill bottles one by one and make sure we’re on the same page about how you’re taking them now that you’re home.”
Preventive Care Gap: Statin Use in Persons with Diabetes (SUPD) Tier 1 or 2 (Healthy/Rising-Risk)
  • Data query to identify all patients with diabetes aged 40-75 not on a statin
  • Automated EMR message to PCPs for eligible patients
  • Patient outreach and education on cardiovascular risk reduction
  • This is a key HEDIS quality metric. It’s often a “low-hanging fruit” for population health pharmacists.
  • “Dr. Jones, our records indicate your patient, Robert Green, has diabetes but is not currently on a statin. Per guidelines, a moderate-intensity statin is recommended for primary prevention. Please consider initiating therapy at his next visit.”

18.1.6 Operationalizing Your Role: Workflows for Panel Management

Having the knowledge and a playbook is essential, but success in population health requires a structured, efficient, and scalable workflow. You must move from ad-hoc problem solving to a systematic process of identifying, prioritizing, intervening, and documenting your work across your entire panel. This requires leveraging technology and developing standardized processes.

The Population Health Pharmacist’s Weekly Workflow

Your week should have a predictable rhythm designed to balance proactive panel management with reactive consultations.

A Sample Weekly Workflow Template
  • Monday: Triage and Planning
    • Morning: Review the weekend admissions/discharge report. Identify all panel patients discharged from the hospital. Schedule high-priority Transitions of Care (TOC) calls/visits for the week.
    • Afternoon: Review your population health dashboard. Triage new alerts (e.g., new high A1c, ER visit alerts). Create your prioritized task list for the week based on risk stratification. Focus on your Tier 3 patients first.
  • Tuesday: High-Risk Patient Interventions
    • Dedicated “Focus Time”: Block 3-4 hours for proactive outreach and CMM for your highest-risk (Tier 3) patients. This is your core value-add time and should be protected from interruptions.
    • Documentation: Document every intervention in the EMR immediately after it occurs.
  • Wednesday: Rising-Risk and Quality Gaps
    • Focus: Shift focus to your Tier 2 patients. Conduct targeted MTMs for adherence, perform disease state management follow-ups.
    • Quality Metrics: Run reports to identify and close care gaps (e.g., Statin use in diabetes, adherence to hypertension meds). Send batch communications to providers or patients as needed.
  • Thursday: Team Collaboration and Case Conferences
    • Attend interdisciplinary team huddles or case conferences. Present your most complex patients and provide medication-related recommendations to the care team (PCPs, nurses, social workers).
    • Follow up on recommendations made earlier in the week.
  • Friday: Follow-up, Documentation Catch-up, and Planning
    • Complete any outstanding documentation.
    • Conduct follow-up calls with patients you intervened on earlier in the week to assess progress and address new issues.
    • Review your dashboard and pre-plan your priorities for the upcoming week.

The Power of the Collaborative Practice Agreement (CPA)

To be truly effective and efficient in population health, you need the authority to act on your clinical recommendations. A Collaborative Practice Agreement is a formal agreement between a pharmacist and a provider (or group of providers) that allows the pharmacist to perform expanded patient care functions, such as initiating, modifying, and discontinuing medication therapy for specific disease states. Within a population health model, a CPA is a force multiplier.

CPA: Your License to Practice at the Top of Your License

Imagine your workflow for managing uncontrolled diabetes without a CPA. You identify a patient with a high A1c who needs therapy intensification. You perform a chart review, formulate a recommendation, send a message to the PCP, wait for a response, and hope the order gets placed. This creates delays and administrative friction.

Now, imagine the same scenario with a CPA for diabetes. You identify the same patient. You perform your review. You determine that adding an SGLT2 inhibitor is appropriate based on the agreed-upon protocol. You then place the order for the new medication yourself, under your own name, and send a notification to the PCP. You have just saved multiple steps, accelerated the time to optimal therapy, and demonstrated your value as a provider. Advocating for and operating under a well-defined CPA is critical to succeeding in a population health role.

Documenting Your Value: The SOAP Note

If an intervention isn’t documented, it didn’t happen. In value-based care, your documentation is not just a clinical record; it is the evidence of your contribution. The SOAP (Subjective, Objective, Assessment, Plan) note format, used by other clinicians, is the gold standard for documenting your encounters in the EMR.

  • Subjective: What the patient tells you. (“I’ve been forgetting to take my blood pressure pill a few days a week.” “My new inhaler makes me feel shaky.”)
  • Objective: The data. (Home BP readings, PDC from claims data, relevant lab results from the EMR, medication list from reconciliation.)
  • Assessment: Your clinical judgment. This is the most important part. Identify and prioritize the medication therapy problems. (e.g., “1. Hypertension – Non-adherence leading to uncontrolled BP. 2. Asthma – Improper inhaler technique resulting in side effects and suboptimal control.”)
  • Plan: What you are going to do. Each point in the plan should correspond to a problem in your assessment. (e.g., “1. Provided patient with a 7-day pillbox and enrolled in med sync program. Will follow up in 2 weeks. 2. Re-educated on proper MDI technique using teach-back method. Provided a spacer. Will assess response at follow-up.”)