Identifying Workers at Risk for High Health Care Expenditures: A Short Questionnaire

Abstract

The objective of this study was to create and measure the predictive accuracy of a brief questionnaire for screening new workers to identify those at increased risk for generating high health care insurance expenditures during the following year. Such an instrument could help health plans and providers intervene to mitigate the health risks of identified high-risk workers. We mailed a 53-item questionnaire to members of a "derivation cohort" (adult food processing workers, n = 15496) and obtained records of the eligible respondents' health insurance expenditures during the following year. Using multiple linear regression, we identified eight of the questions that predicted future expenditures most accurately, and created a formula to predict total expenditures from answers to these questions. To validate the formula's predictive accuracy, we used the eight-item questionnaire to survey two "validation cohorts" (transportation workers, n = 7445; and their dependents, n = 5562), inserted responses into the scoring formula, classified respondents into high-risk (top 10%) or low-risk (lower 90%) groupings, and then compared health insurance expenditures generated by the high- and low-risk groups during the following year. In the derivation cohort, age, sex, regular use of medications, frequent visits to physicians, and having arthritis, diabetes, cancer, or high cholesterol predicted future health care expenditures. In the worker and dependent validation cohorts, the respondents classified by the formula as high-risk generated insurance expenditures during the following year that were 2.4 and 1.8 times greater than those generated by the members of the low-risk groups (p < 0.001). An eight-item questionnaire and its scoring formula can identify high-risk groups of workers that will generate high health care expenditures during the following year. Healthcare organizations could use this questionnaire to help target new workers for care management and disease management interventions.

Screening tools to identify patients with complex health needs at risk of high use of health care services: A scoping review

“…Seven studies were published between 2010 and 2016,[ 19 , 26 , 38 – 42 ] 16 were published between 2000 and 2009,[ 13 – 16 , 18 , 23 – 25 , 29 , 31 – 37 ] and 7 were published between 1990 and 1999. [ 17 , 20 – 22 , 27 , 28 , 30 ]…”

“…Fourteen studies were from the USA,[ 14 – 18 , 20 – 24 , 34 – 37 ] 5 were from the Netherlands, [ 30 , 32 , 33 , 41 , 42 ] 5 were from Switzerland,[ 13 , 27 – 29 , 31 ] 4 were from Germany,[ 13 , 26 , 38 , 39 ] and 4 other studies were from Spain,[ 19 ] United Kingdom,[ 13 ] Canada,[ 25 ] and Australia,[ 40 ] respectively. One study on a self-administered questionnaire was conducted in three European countries—Germany, United Kingdom, and Switzerland.…”

“…Fourteen articles presented the development of the questionnaire or the screening tool, [ 15 , 16 , 21 – 23 , 26 , 30 , 34 – 37 , 39 , 40 , 42 ] while 16 others were validation studies. [ 13 , 14 , 17 – 20 , 24 , 25 , 27 – 29 , 31 – 33 , 38 , 41 ]…”

Design and validation of a complex case evaluation index

“…Respecto a su aplicabilidad, y a diferencia del resto de instrumentos existentes 35 , el IECC se ha diseñado para ser cumplimentado por las enfermeras a través de la observación directa del paciente y con información contenida en su historia clínica. Esta característica facilita su uso, ya que elimina la carga de la persona evaluada en pacientes con enfermedades neurodegenerativas como las demencias, o en situaciones clínicas que limitan la comunicación del paciente, como pueden ser las situaciones de final de vida 13,15,[17][18][19][20] .…”

The case‐mix of chronic illness hospitalization rates in a managed care population: implications for health management programmes

“…Given the limitations of claims‐based approaches for identification and stratification, a better suited approach is by administering a health risk survey instrument at the population level that has been proven valid and reliable in predicting future hospital admissions or health care costs [11–13]. Historically, the health care industry has shied away from administering paper‐based surveys because of high cost and low response rates.…”