Identifying care gaps

Missed refills

Timely refills ensure patients receive continuous treatment, reducing the risk of complications and preventing unnecessary healthcare utilization such as emergency visits or hospital admissions. However, patients may miss their refills due to various reasons, including forgetfulness, cost barriers, or medication side effects.

Identifying patients with missed refills enables care teams to take proactive steps in addressing these barriers, ensuring continuity of care and improving health outcomes. This process involves analyzing patient medication records to detect gaps between prescribed refill schedules and actual dispensation events.

The query below:

• Identifies the most recent dispensation or fill date for each medication by patient.
• Calculates the number of days since the last refill or dispensation.
• Flags patients with missed refills by comparing the days since their last fill with the expected days of medication supply.

By monitoring missed refills, healthcare organizations can engage patients early, provide support for adherence, and implement targeted interventions to address potential gaps in medication management.

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Sample query available here

High blood pressure

High blood pressure, also known as hypertension, is a critical risk factor for cardiovascular diseases, including heart attacks, strokes, and kidney disease. Identifying patients with elevated blood pressure allows healthcare providers to implement timely interventions, such as lifestyle modifications or medication adjustments, to prevent complications and improve health outcomes. For this reason, CMS maintains an Electronic Clinical Quality Measure (eCQM) related to Controlling Blood Pressure.

This analytic leverages LOINC-coded blood pressure measurements to detect patients with high blood pressure. Blood pressure is typically recorded with two key metrics:

• Systolic Pressure: The pressure in the arteries when the heart beats.
• Diastolic Pressure: The pressure in the arteries when the heart rests between beats.

By tracking blood pressure values over time, providers can target high-risk patients for follow-up and ensure continuous monitoring and care management. The query enables population health managers to align interventions with data-driven insights, ensuring early detection and treatment of hypertension.

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Sample query available here

HbA1c > 9%

An elevated HbA1c level indicates poor blood sugar control, placing patients at greater risk of heart disease, kidney failure, and other complications associated with diabetes. Identifying patients with high HbA1c allows healthcare providers to proactively intervene, offering personalized care plans and adjusting medications to improve glycemic control. For this reason, CMS maintains an eCQM related to identifying and treating patients with elevated HbA1c levels (Diabetes: HbA1c Poor Control (> 9%)).

This query leverages LOINC-coded A1C lab results to detect patients with HbA1c levels above the target threshold, such as greater than or equal to 9%. The query identifies these patients and provides insight into the timing of their measurements, encounter types, and interpretation codes. It also flags whether there is EHR documentation available.

Zus deduplicates encounters by date into an Encounter Lens, which can be queried from the Lens Encounter table. Zus also enriches data by tagging Encounter Lenses with context-appropriate categories, in this case Ambulatory, Inpatient, Emergency, etc.

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Sample query available here

Kidney health evaluation

Monitoring kidney health in patients with diabetes prevents the progression of chronic kidney disease (CKD) and related complications. Diabetes is a leading cause of kidney dysfunction, so healthcare providers aim to regularly evaluate kidney function through key tests, such as urine albumin-to-creatinine ratio (uACR) and estimated glomerular filtration rate (eGFR). These assessments allow for early detection and better management of kidney health, reducing the risk of end-stage renal disease. For this reason, CMS maintains an eCQM related to Kidney Health Evaluation.

This analytic identifies the most relevant kidney health lab results (eGFR or uACR) if available for each diabetic patient. It ensures valid records by filtering out canceled or erroneous observations and only including non-null lab values.

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Sample query available here

Missing colorectal cancer screenings

Colorectal cancer screening can detect cancer early when it is most treatable. Though regular screening for colorectal cancer starting at age 45 for average-risk adults is recommended, many eligible patients fail to receive timely screenings. Identifying patients who are due for colorectal cancer screening allows healthcare providers to better adhere to guidelines. For this reason, CMS maintains an eCQM related to Colorectal Cancer Screening.

This analytic begins by selecting colorectal observations such as FOBT, sDNA FIT Test, and CT Colonography, using relevant LOINC codes. For each observation, it aggregates details such as test results, encounter types, and whether the data likely has associated EHR documentation available. The query also pulls data on procedures like colonoscopy and flexible sigmoidoscopy, using SNOMED, CPT, and HCPCS codes to filter for specific colorectal procedures.

In addition, the query tracks patients who have undergone colectomy surgeries by using specific surgical procedure codes (ICD10 and HCPCS) and identifies patients diagnosed with colorectal cancer by filtering relevant conditions using ICD10 and SNOMED codes.

Finally, the main query pulls together patients with colorectal cancer-related observations and procedures, excluding patients who have a prior cancer diagnosis or have undergone a colectomy. The resulting dataset contains distinct patients who are within the screening-relevant age group (45-75 years old) and are candidates for further colorectal cancer screenings.

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Sample query available here

Connecting care gaps to documentation

Coming soon!