A measurement framework is the backbone of accountable IPV programming. This section provides a comprehensive set of measures organized across six domains, with alignment to existing MCAS touchpoints, DHCS PHM reporting requirements, and CalAIM program expectations. This framework proposes process, outcome, and balancing measures to support MCPs implementing the IPV toolkit.

Measure types and examples:

• Process Measures track the specific steps and activities that drive your goals. They measure how well the interdependent tasks, steps, or interventions in a workflow are performed. MCPs and practices can directly control the levers of these measures
  
  IPV Example: % of Eligible Members Offered IPV Education Annually

• Balancing Measures indicate whether changes in one area cause unintended or negative changes elsewhere. They ensure that trying to fix one problem does not accidentally break another part of the system. Every QI effort needs at least one.
  
  IPV Example: Member Reported Experience of Support Services

• Outcome Measures assess the changes in member health, safety, and care engagement. These measures take longer to move. Track them over 12 to24-month periods.
  
  IPV Example: % of IPV-Positive Members Engaged in Prenatal Care (aligns with PPC: Timeliness of Prenatal Care MCAS measure)

MCPs should establish a measurement framework organized across six domains (Education, Screening, Referral, Linkage, Follow-Up, and Equity) and also includes workforce/training and balancing measures. Here are steps to consider in establishing the measurement framework:

• Baseline first. Document a baseline for each measure before setting targets. Readiness assessment data will calibrate starting points.
• Use the six domains as a QI diagnostic. If screening rates are high but referral rates are low, the gap is in disclosure response, not awareness. The six-domain structure helps locate where to intervene.
• PDSA cycles are small tests of change. Each measure should generate a small, specific test of change, not a comprehensive overhaul. PDSAs build iteratively: Test one change with one provider or team, learn from it, adjust, then spread. Start with the area where the data shows the biggest gap.
• Set your own targets. The scorecard includes sample targets for reference, but MCPs should set their own targets based on their baseline data, population, and community context. Do not treat the sample targets as requirements.
• Equity is not a column, it is a lens. Stratified data should be reviewed at every QI meeting. When equity gaps emerge, they should be the starting point for the next small test of change.

HEDIS/MCAS Measure Alignment

MCAS Measure	IPV Touchpoint	Why It Matters	IPV Metric to Embed
PPC: Timeliness of Prenatal Care	Prenatal visits are the primary window for perinatal IPV screening.	IPV increases risk of preterm birth; early identification is preventive.	% of perinatal members offered IPV education at prenatal visit
PPC: Postpartum Care	Postpartum visit is critical—IPV risk does not end at delivery.	CUES intervention and support prevent postpartum depression and promote safety.	% of postpartum members screened; % with referral if positive
Depression Screening & Follow-Up	IPV is a major driver of depression; co-screening is clinically appropriate.	IPV intersects with behavioral health; depression visits are natural IPV touchpoints.	% of members screened for both depression and IPV in the same encounter
Well-Child Visits (First 30 Months)	Well-child visits capture caregivers and are an opportunity to offer education to parents and guardians.	Visits engage caregivers ; ACEs framing supports trauma-informed care.	% of caregivers offered IPV education at well-child visits
Chlamydia Screening	Reproductive health visits are an opportunity to deliver the CUES intervention.	It aligns with adolescent health special population pathway.	% of members at chlamydia screening who also received the CUES intervention

Sample process, outcome, & balancing measures by domain

Sample Scorecard

Use this scorecard to track MCP-level performance quarterly and annually. Populate with actual data. Status indicators: 🟢 Target Met (within 0pp) | 🟡 Near Target (within 5pp) | 🔴 Needs Attention (>5pp below target).

Domain	Metric	Level	Sample Target2	Result	Status
Universal Education (CUES)	% of members receiving CUES approach	MCP	≥85%	[enter]	[enter]
Screening	% of perinatal members screened (network-wide)	MCP	≥85%	[enter]	[enter]
Referral	% of positive disclosures with documented referral linkage	MCP	≥95%	[enter]	[enter]
Linkage	% referred successfully linked to service	MCP	≥70%*	[enter]	[enter]
Follow-Up	% with follow-up documented within 30 days	MCP	≥80%	[enter]	[enter]
Equity	Screening rate gap by race/ethnicity (pp gap)	MCP	≤5pp	[enter]	[enter]
Privacy	Privacy/EOB incidents (Balancing)	MCP	0	[enter]	[enter]
Workforce	% of network sites with ≥80% staff CUES-trained	MCP	≥80%	[enter]	[enter]

1. California DHCS. MCAS MY2026 Measure List, Reporting Year 2027. Current MCAS measure set used above for the California alignment. DHCS MCAS MY2026 Measure List(opens in new tab) ↩︎
2. Targets shown are illustrative programmatic goals for MCPs to calibrate against their own baseline performance, not literature-derived benchmarks. Published IPV screening/education-rate studies vary widely by setting and intervention maturity — from single-digit to low-20% baselines in general primary care and ED quality-improvement projects (e.g., Sharples L, et al. Fam Med. 2018;50(9):702-705, 22% baseline; DNP QI capstone projects, University of San Francisco, 2026, 4.1% baseline), to 45-65% with EHR clinical-decision-support alerts (Lenert L, et al. JAMA Netw Open. 2024;7(8):e2425070), to as high as 88% in one high-volume labor-and-delivery screening protocol. MCPs should set targets from their own baseline data rather than these illustrative figures. ↩︎