How to read our Washington inspection data — what state averages hide

The Washington inspection dataset on StarlynnCare covers 180 publishable ALFs, 721 inspections spanning May 2023 through May 2026, and 919 deficiencies. All data comes from DSHS Long-Term Care Regulation (LTCR) via the public BHForms portal.

Why 180 and not all WA ALFs.Washington licenses roughly 7,000+ ALF, AFH (Adult Family Home), and ESF (Enhanced Services Facility) beds across thousands of facilities. The vast majority are small AFHs — residential settings with 6 or fewer beds, often not dementia-focused. Our publishable set applies two filters: a memory care signal (explicit name keywords, DSHS Dementia Care contract, memory care certification flag, or dementia specialty self-declaration) and a 48-month freshness gate requiring at least one inspection on record. Facilities that don't pass both are not shown publicly. They remain in our database for future re-evaluation.

Inspection types. DSHS inspects ALFs in two modes: routine surveys (scheduled, approximately annual) and complaint investigations (triggered by a complaint from a resident, family member, or other party). Our dataset tags each inspection as standard or complaint-driven. In the WA dataset, 457 of 721 inspections (63%) are complaint-driven.

The most important structural fact about the WA dataset: complaints are not distributed evenly across facilities. They concentrate sharply in a small tail.

In the 180-facility dataset: the top 10% of facilities by complaint count (18 facilities) absorbed 33% of all complaints. The top 20% (36 facilities) absorbed 54%. The bottom half of the distribution — facilities with zero or one complaint — accounts for a small fraction of total complaint volume.

Normalizing by beds changes the picture further. Small facilities with high complaint counts can appear moderate in raw numbers but extreme when adjusted for capacity. A facility with 47 beds and 10 complaints is generating complaints at 21 per 100 beds — roughly 3× the rate of a 126-bed facility with 9 complaints.

The practical implication: a statewide average complaint rate describes almost no actual facility accurately. The distribution is so skewed that the mean is far above the median. When a state-level summary says “the average WA memory care facility receives X complaints per year,” it is averaging a large quiet majority with a small extremely active tail. We don't publish that average. We rank individual facilities instead.

Quarterly serious citations (IJ + Type A) across all 180 WA facilities:

WA DSHS LTCR uses its own severity classification system for ALF deficiencies, rooted in the Washington Administrative Code (WAC). StarlynnCare maps those classifications to the following tiers:

• Immediate Jeopardy (IJ) — findings where DSHS determines a resident faces an immediate threat to health or safety. IJ findings require an immediate corrective action plan. In our 180-facility WA dataset, IJ findings are rare: 5 deficiencies across 2 facilities.
• Type A— actual or high-probability harm to one or more residents. Serious findings that require a corrective action plan but are not classified as immediate jeopardy. The most common “serious” tier in the WA dataset.
• Type B — potential for harm if not corrected. Lower severity. These appear on facility profiles but are not counted in the serious-citation metric.

On each WA facility profile, the serious-citation count reflects IJ + Type A only. The total deficiency count includes all tiers. Both numbers are shown.

Three things to look at when you open a WA facility profile, in order of signal strength:

1. Recent inspection density and type.How many inspections in the last 36 months? What share were complaint-driven vs. routine? A facility with 8 complaint-driven inspections in 36 months and findings in most of them is a different situation than a facility with 2 routine inspections and no findings. The count alone isn't the signal — the type and outcome combination is.

2. Severity mix. One IJ finding is more significant than ten Type B findings. Look at whether the serious-citation count reflects one bad inspection year or a recurring pattern. Read the description text on each serious deficiency — DSHS inspectors are specific about what was wrong and what residents were affected.

3. Complaint share of inspections. A facility where 80% of inspections are complaint-driven and 70% of those produce findings is in a different situation than a facility where routine surveys dominate and findings are minor. The complaint-driven share is a behavioral signal: it means someone in the facility — a resident, a family member, a staff member — is reaching out to DSHS. That pattern matters independent of whether any individual inspection produced a serious finding.

Several analyses that would be genuinely useful to families are not yet possible with the WA data we have. We name them explicitly rather than omitting them silently.

• Civil money penalties.DSHS can impose fines on facilities with serious violations. The penalty amounts are not consistently populated in our WA dataset. We don't show a “$X in fines” figure because we can't confirm that zero means no fines or means no data.
• Repeat deficiency flags.Whether a citation is a repeat of a previously cited violation — one of the clearest signals of systemic failure — requires matching deficiency text across inspections. Our WA ingest does not yet perform that match reliably. We don't show “repeat citation” labels.
• Residents affected and harm descriptions.DSHS inspection reports describe how many residents were affected and the nature of the harm. Those fields are not yet parsed from source PDFs into structured columns. We show the inspector narrative text where available, but not a structured “X residents affected” figure.
• Operator and ownership chain analysis.The operator and management company fields are null for most WA facilities — DSHS doesn't surface them in the directory sources we ingest. Brand-by-name matching (using facility name keywords) is a weak proxy. We don't publish ownership comparisons for WA until the data improves.