net promoter score
nps_scrDefinition
ISO-11179 Definition
A member loyalty metric calculated from a single survey question asking how likely the member is to recommend their health plan or provider to a friend or family member on a scale of zero to ten, with promoters scoring nine or ten, passives scoring seven or eight, and detractors scoring zero through six. Net Promoter Score is calculated by subtracting the percentage of detractors from the percentage of promoters, producing a score ranging from negative 100 to positive 100. Health plan NPS scores typically range from negative 20 to positive 30 with higher scores indicating stronger member loyalty and advocacy.
NPS is used as a leading indicator of member retention because high scores predict lower voluntary disenrollment rates. Healthcare data teams track nps_scr by plan product, member demographic segment, geographic market, and provider attribution to identify loyalty drivers and at-risk populations, correlate NPS with subsequent retention and disenrollment behavior, and measure the impact of member experience improvement initiatives on loyalty scores across the enrolled population.
Standard Abbreviation
nps_scr
Category
Production DDL — FACT_QUALITY_MEASURE
CREATE OR REPLACE TABLE FACT_QUALITY_MEASURE (
qlty_key INTEGER NOT NULL -- surrogate key,
mbr_key INTEGER NOT NULL -- FK to DIM_MEMBER,
plan_key INTEGER NOT NULL -- FK to DIM_PLAN,
meas_yr SMALLINT -- measurement year,
hedis_meas_cd VARCHAR(20) -- HEDIS measure code,
denom_ind CHAR(1) -- denominator eligible,
numer_ind CHAR(1) -- numerator met,
excl_ind CHAR(1) -- exclusion indicator,
gap_open_ind CHAR(1) -- care gap open,
star_rtg_nbr DECIMAL(3,1) -- star rating,
qlty_scr DECIMAL(5,2) -- quality score,
perf_thrsh_pct DECIMAL(5,2) -- performance threshold,
raf_scr DECIMAL(10,3) -- risk adjustment factor,
outreach_cnt SMALLINT -- outreach attempts,
load_dt TIMESTAMP_NTZ NOT NULL -- load timestamp
);
Standard Snowflake DDL for the canonical quality table. Convert to BigQuery or Databricks →
Why This Term Matters
Quality measure data determines how payers and providers are rated and reimbursed under CMS Stars, HEDIS, and value-based care contracts. Data engineers who understand quality terminology build measure calculation pipelines that correctly attribute patients, apply denominator exclusions, and flag documentation gaps before submission deadlines. Incorrect quality data directly affects star ratings, pay-for-performance bonuses, and Medicare Advantage plan bids.
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