Clinician-friendly, time-saving, and burnout-busting. That’s what effective clinical documentation can deliver for small and medium-sized practices.
The conversation around Clinical Documentation Improvement (CDI) often centers on sprawling hospital systems. But that leaves outpatient clinics and small provider groups wondering if meaningful change is even possible. The truth is, transformative CDI success stories are unfolding every day in practices just like yours.
In this guide, you'll find snapshots of small teams who’ve streamlined their workflows, reduced administrative headaches, and carved out more space for genuine patient care.
We'll walk through clear before-and-after documentation examples, discover practical, time-smart tools, and learn how focused CDI efforts can make both compliance and clinician happiness truly achievable, even with limited resources.
Read the full case study on this practice here.
Blake Thompson, a Family Nurse Practitioner running his own primary care practice in rural Idaho, is one example of modern CDI transforms small practice operations. His practice experienced a dramatic shift by embracing clinical documentation AI with Freed.
Post-Freed, Blake’s workflow dramatically changed for the better. Instead of taking notes or struggling with dictation software, Blake simply records each visit and has natural conversations while the AI captures the clinical and contextual details. He reviews and signs off on his documentation immediately after each encounter. Blake now leaves the office within two minutes of seeing his last patient — a shift he once thought impossible. Blake saves 1.5–2 hours daily, and collectively, his healthcare team has regained dozens of hours each week.
What began as. Blake's own experiment in patient care has grown; it now involves four providers in his practice. Two additional clinics in his region have also adopted Freed's clinical documentation AI.
Understanding the difference between pre-CDI and post-CDI documentation quality is crucial. Here's how Blake's actual patient notes transformed:
Blake's pre-CamDI notes were rushed, incomplete, and generic. Something like this, for example:
CC: Diabetes follow-up
HPI: Patient doing okay, checking sugars at home
PE: Appears well
Labs: A1C pending
A/P: Continue current meds, RTC 3 months
The same type of visit now generates comprehensive, clinically rich notes like the following:
CHIEF COMPLAINT: Type 2 diabetes mellitus follow-up
HISTORY OF PRESENT ILLNESS: 68-year-old male returns for routine diabetes management. Reports good adherence to metformin 1000mg twice daily. Home glucose monitoring shows fasting readings 110-140 mg/dL, post-meal readings typically 150-180 mg/dL. Patient mentions he's been more consistent with evening walks since our last discussion about exercise. Denies symptoms of hyperglycemia or hypoglycemia. No episodes of chest pain, shortness of breath, or visual changes. Reports 8-pound weight loss since implementing portion control strategies we discussed.
PHYSICAL EXAMINATION: General: Alert, cooperative, appears stated age Vital Signs: BP 132/78, HR 76, Weight 187 lbs (down from 195 lbs) HEENT: Pupils equal and reactive, no retinal hemorrhages on fundoscopic exam Cardiovascular: Regular rate and rhythm, no murmurs or gallops Extremities: No lower extremity edema, pulses intact, no diabetic foot changes.
ASSESSMENT AND PLAN: Type 2 Diabetes Mellitus (E11.9) - Improving control - Home glucose logs show good trend, estimated A1C likely 7.2-7.8% - Continue metformin 1000mg BID - Congratulated patient on 8-pound weight loss - Discussed importance of consistent exercise routine - Lab draw today: HbA1c, CMP, lipid panel - Follow-up in 3 months or sooner if concerns - Reinforced when to contact office for glucose readings >300 or <70.
Blake's transformation centered on implementing clinical documentation AI that captures natural conversations and automatically generates structured clinical notes. He completely eliminated the traditional dictation bottleneck that had been consuming hours of his day.
The most impactful CDI strategy for small practices is ambient clinical documentation using AI scribes. Here's how it works in practice:
Traditional workflow
Modern CDI workflow
Effective CDI adapts to your specialty's unique needs. Here are examples of how different practices customize their approach:
Successful clinical documentation improvement often starts with one champion clinician. It can expand organically. A typical timeline for implementation might look like this:
Phase 1: Single clinician pilot (2-4 weeks)
Phase 2: Department expansion (1-2 months) Phase 3: Practice-wide adoption (3-6 months)
Assessment: Back pain
Plan: Follow up in 2 weeks
ASSESSMENT: Acute lumbar strain, likely muscular in origin, exacerbated by prolonged sitting at desk work. No radicular symptoms. Patient reports similar episode 6 months ago that resolved with physical therapy.
PLAN: NSAIDs, ergonomic assessment, physical therapy referral if no improvement in 1 week. Return if symptoms worsen or radicular pain develops.
Ambient clinical documentation captures the full conversation, including clinical reasoning and contextual details that manual note-taking often misses.
Ambient documentation captures the full conversation, including clinical reasoning and contextual details that manual note-taking often misses. Overall, it provides more clinical documentation integrity.
Disjointed notes where subjective complaints don't clearly connect to objective findings or assessment conclusions.
Structured documentation automatically organizes information into logical SOAP format with clear connections between sections.
Modern CDI systems use natural language processing to understand the clinical narrative and automatically create logical connections between what the patient reports, what the clinician observes, and the resulting clinical decisions. Instead of filling out disconnected template fields, clinicians can speak naturally about their clinical reasoning: "His chest pain sounds concerning because it's happening with exercise and his blood pressure is higher than usual, so I'm worried this could be cardiac-related." The AI captures this reasoning and structures it appropriately, to reference both the subjective complaints and objective findings.
Bloated notes filled with irrelevant template text and copy-pasted information from previous visits.
Concise, relevant documentation focused on the actual patient encounter, with smart templates that include only pertinent information.
CDI systems generate fresh documentation for each encounter based on the actual conversation. Instead of clinicians pulling forward irrelevant template text or copying previous visits, the AI captures only what's discussed and examined during the visit.
Smart templates adapt to the visit type; so a diabetes follow-up automatically focuses on glucose control, medication adherence, and diabetic complications rather than generating a comprehensive review of systems that wasn't performed. Notes aren't a recycled version of every previous visit. This approach also helps with regulatory compliance and reduces legal liability, since notes accurately reflect what actually occurred during the patient interaction.
CDI delivers benefits far beyond saved time. Many practices using modern CDI strategies report:
CC: Follow-up
HPI: Doing well
PE: Normal
A/P: Continue current medications
SUBJECTIVE: Patient returns for follow-up of hypertension and type 2 diabetes. Reports excellent adherence to metformin and lisinopril. Home blood glucose readings averaging 110-130 mg/dL. No episodes of hypoglycemia. Blood pressure at home consistently 120-135/75-85. Denies chest pain, shortness of breath, or lower extremity swelling. Reports 10-pound weight loss since last visit through dietary changes and walking 30 minutes daily.
OBJECTIVE:
BP: 128/82, HR: 72, regular rhythm
Weight: 185 lbs (down from 195 lbs)
HEENT: No retinal changes noted on fundoscopic exam
CV: Regular rate and rhythm, no murmurs Extremities: No pedal edema
ASSESSMENT & PLAN:
1. Type 2 Diabetes Mellitus
- Well controlled (estimated HbA1c 7.0-7.5% based on home glucose logs)
- Continue metformin 1000mg BID
- Recheck HbA1c in 3 months
- Congratulated on weight loss efforts
2. Essential Hypertension
- Well controlled
- Continue lisinopril 10mg daily
- Recheck in 3 months with basic metabolic panel
Week 1: Assess and align
Weeks 2–3: Launch your pilot
Weeks 4–6: Validate and refine
Month 2: Expand your advantage
Month 3: Optimize and accelerate growth
Together, these tools facilitate your team doing more of what matters most: patient care.
Interested in setting up a CDI program in your own practice? Start with a free trial of Freed and join thousands of clinicians who've already made the switch to documentation quality improvement.
Clinician-friendly, time-saving, and burnout-busting. That’s what effective clinical documentation can deliver for small and medium-sized practices.
The conversation around Clinical Documentation Improvement (CDI) often centers on sprawling hospital systems. But that leaves outpatient clinics and small provider groups wondering if meaningful change is even possible. The truth is, transformative CDI success stories are unfolding every day in practices just like yours.
In this guide, you'll find snapshots of small teams who’ve streamlined their workflows, reduced administrative headaches, and carved out more space for genuine patient care.
We'll walk through clear before-and-after documentation examples, discover practical, time-smart tools, and learn how focused CDI efforts can make both compliance and clinician happiness truly achievable, even with limited resources.
Read the full case study on this practice here.
Blake Thompson, a Family Nurse Practitioner running his own primary care practice in rural Idaho, is one example of modern CDI transforms small practice operations. His practice experienced a dramatic shift by embracing clinical documentation AI with Freed.
Post-Freed, Blake’s workflow dramatically changed for the better. Instead of taking notes or struggling with dictation software, Blake simply records each visit and has natural conversations while the AI captures the clinical and contextual details. He reviews and signs off on his documentation immediately after each encounter. Blake now leaves the office within two minutes of seeing his last patient — a shift he once thought impossible. Blake saves 1.5–2 hours daily, and collectively, his healthcare team has regained dozens of hours each week.
What began as. Blake's own experiment in patient care has grown; it now involves four providers in his practice. Two additional clinics in his region have also adopted Freed's clinical documentation AI.
Understanding the difference between pre-CDI and post-CDI documentation quality is crucial. Here's how Blake's actual patient notes transformed:
Blake's pre-CamDI notes were rushed, incomplete, and generic. Something like this, for example:
CC: Diabetes follow-up
HPI: Patient doing okay, checking sugars at home
PE: Appears well
Labs: A1C pending
A/P: Continue current meds, RTC 3 months
The same type of visit now generates comprehensive, clinically rich notes like the following:
CHIEF COMPLAINT: Type 2 diabetes mellitus follow-up
HISTORY OF PRESENT ILLNESS: 68-year-old male returns for routine diabetes management. Reports good adherence to metformin 1000mg twice daily. Home glucose monitoring shows fasting readings 110-140 mg/dL, post-meal readings typically 150-180 mg/dL. Patient mentions he's been more consistent with evening walks since our last discussion about exercise. Denies symptoms of hyperglycemia or hypoglycemia. No episodes of chest pain, shortness of breath, or visual changes. Reports 8-pound weight loss since implementing portion control strategies we discussed.
PHYSICAL EXAMINATION: General: Alert, cooperative, appears stated age Vital Signs: BP 132/78, HR 76, Weight 187 lbs (down from 195 lbs) HEENT: Pupils equal and reactive, no retinal hemorrhages on fundoscopic exam Cardiovascular: Regular rate and rhythm, no murmurs or gallops Extremities: No lower extremity edema, pulses intact, no diabetic foot changes.
ASSESSMENT AND PLAN: Type 2 Diabetes Mellitus (E11.9) - Improving control - Home glucose logs show good trend, estimated A1C likely 7.2-7.8% - Continue metformin 1000mg BID - Congratulated patient on 8-pound weight loss - Discussed importance of consistent exercise routine - Lab draw today: HbA1c, CMP, lipid panel - Follow-up in 3 months or sooner if concerns - Reinforced when to contact office for glucose readings >300 or <70.
Blake's transformation centered on implementing clinical documentation AI that captures natural conversations and automatically generates structured clinical notes. He completely eliminated the traditional dictation bottleneck that had been consuming hours of his day.
The most impactful CDI strategy for small practices is ambient clinical documentation using AI scribes. Here's how it works in practice:
Traditional workflow
Modern CDI workflow
Effective CDI adapts to your specialty's unique needs. Here are examples of how different practices customize their approach:
Successful clinical documentation improvement often starts with one champion clinician. It can expand organically. A typical timeline for implementation might look like this:
Phase 1: Single clinician pilot (2-4 weeks)
Phase 2: Department expansion (1-2 months) Phase 3: Practice-wide adoption (3-6 months)
Assessment: Back pain
Plan: Follow up in 2 weeks
ASSESSMENT: Acute lumbar strain, likely muscular in origin, exacerbated by prolonged sitting at desk work. No radicular symptoms. Patient reports similar episode 6 months ago that resolved with physical therapy.
PLAN: NSAIDs, ergonomic assessment, physical therapy referral if no improvement in 1 week. Return if symptoms worsen or radicular pain develops.
Ambient clinical documentation captures the full conversation, including clinical reasoning and contextual details that manual note-taking often misses.
Ambient documentation captures the full conversation, including clinical reasoning and contextual details that manual note-taking often misses. Overall, it provides more clinical documentation integrity.
Disjointed notes where subjective complaints don't clearly connect to objective findings or assessment conclusions.
Structured documentation automatically organizes information into logical SOAP format with clear connections between sections.
Modern CDI systems use natural language processing to understand the clinical narrative and automatically create logical connections between what the patient reports, what the clinician observes, and the resulting clinical decisions. Instead of filling out disconnected template fields, clinicians can speak naturally about their clinical reasoning: "His chest pain sounds concerning because it's happening with exercise and his blood pressure is higher than usual, so I'm worried this could be cardiac-related." The AI captures this reasoning and structures it appropriately, to reference both the subjective complaints and objective findings.
Bloated notes filled with irrelevant template text and copy-pasted information from previous visits.
Concise, relevant documentation focused on the actual patient encounter, with smart templates that include only pertinent information.
CDI systems generate fresh documentation for each encounter based on the actual conversation. Instead of clinicians pulling forward irrelevant template text or copying previous visits, the AI captures only what's discussed and examined during the visit.
Smart templates adapt to the visit type; so a diabetes follow-up automatically focuses on glucose control, medication adherence, and diabetic complications rather than generating a comprehensive review of systems that wasn't performed. Notes aren't a recycled version of every previous visit. This approach also helps with regulatory compliance and reduces legal liability, since notes accurately reflect what actually occurred during the patient interaction.
CDI delivers benefits far beyond saved time. Many practices using modern CDI strategies report:
CC: Follow-up
HPI: Doing well
PE: Normal
A/P: Continue current medications
SUBJECTIVE: Patient returns for follow-up of hypertension and type 2 diabetes. Reports excellent adherence to metformin and lisinopril. Home blood glucose readings averaging 110-130 mg/dL. No episodes of hypoglycemia. Blood pressure at home consistently 120-135/75-85. Denies chest pain, shortness of breath, or lower extremity swelling. Reports 10-pound weight loss since last visit through dietary changes and walking 30 minutes daily.
OBJECTIVE:
BP: 128/82, HR: 72, regular rhythm
Weight: 185 lbs (down from 195 lbs)
HEENT: No retinal changes noted on fundoscopic exam
CV: Regular rate and rhythm, no murmurs Extremities: No pedal edema
ASSESSMENT & PLAN:
1. Type 2 Diabetes Mellitus
- Well controlled (estimated HbA1c 7.0-7.5% based on home glucose logs)
- Continue metformin 1000mg BID
- Recheck HbA1c in 3 months
- Congratulated on weight loss efforts
2. Essential Hypertension
- Well controlled
- Continue lisinopril 10mg daily
- Recheck in 3 months with basic metabolic panel
Week 1: Assess and align
Weeks 2–3: Launch your pilot
Weeks 4–6: Validate and refine
Month 2: Expand your advantage
Month 3: Optimize and accelerate growth
Together, these tools facilitate your team doing more of what matters most: patient care.
Interested in setting up a CDI program in your own practice? Start with a free trial of Freed and join thousands of clinicians who've already made the switch to documentation quality improvement.
Frequently asked questions from clinicians and medical practitioners.