2021 MBHR Measure: Sleep Quality Screening and Sleep Response at 3-months 

QCDR Name: MBHR Mental and Behavioral Health Registry

Measure Title Sleep Quality Screening and Sleep Response at 3-months
NQS Domain Effective Clinical Care
Measure ID MBHR6
Measure Type Patient Reported Outcome (PRO)
High Priority? Yes
Description Percentage of patients 18 years and older who reported sleep quality concerns (e.g., insomnia) with documentation of a standardized tool AND demonstrated a response to treatment at three months (+/- 60 days) after index visit. To see additional details, please view the workflow diagram for this measure: View diagram
Denominator DENOMINATOR (SUBMISSION CRITERIA 1):Patients 18 years and older who reported sleep quality concerns (e.g., insomnia)DENOMINATOR (SUBMISSION CRITERIA 2):Patients 18 years and older who reported sleep quality concerns (e.g., insomnia) and an initial (index) Insomnia Severity Index (ISI) score of 15 or higher.Denominator Exclusions: none
Denominator Exceptions Patient refuses to participate or is unable to complete the questionnaire
Numerator NUMERATOR (SUBMISSION CRITERIA 1):Patients who reported sleep concerns (e.g., insomnia, hypersomnia), with a documented standardized tool to assess sleep quality and a documented care plan (e.g., Pittsburg Sleep Quality Index (PSQI), and the Insomnia Severity Index (ISI).NUMERATOR (SUBMISSION CRITERIA 2):Patients with an Insomnia Severity Index (ISI) that is reduced by 25% or greater from the index Insomnia Severity Index (ISI) score, three months (+/- 60 days) after index date.Numerator Exclusions: None
Data Source Claims, EHR, Paper Medical Record, Registry
Meaningful Measure Area Functional Outcomes
Meaningful Measure Rationale Screening for sleep quality will promote interventions and best practices that are effective at reducing symptoms and improve functional status and quality of life by identifying and addressing appropriate treatment needs. This provides a standardized way to communicate status which will improve both quality of treatment and efficient use of resources.Measuring improved sleep quality response in treatment will promote interventions and best practices, such as psychotherapy, that are effective at reducing symptoms and improve functional status and quality of life.
Inverse Measure? No
Proportional Measure? Yes
Continuous Variable Measure? No
Ratio Measure No
Number of Performance Rates 2
Risk Adjusted No
Preferred Specialty mental and behavioral health
Applicable Specialties Family Medicine, Internal Medicine, Geriatric Medicine, Psychiatry, Behavioral Health


Measure Justification

Sleep problems are common. In fact, large scale epidemiologic and population studies show that sleep deprivation and disorders affect more individuals than previously thought.[1, 2] Insomnia is the most common sleep disorder, with up to a third of adults reporting some difficulty falling or staying asleep in the past year and approximately 10% reporting chronic insomnia.[3] The prevalence of obstructive sleep apnea, characterized with respiratory difficulties during sleep is also high, with estimates of 9-21% in women and 24-31% in men.[4] These rates may be higher among individuals with serious mental illness, such as major depressive disorder, bipolar disorder, and schizophrenia.[5] Sleep problems can lead to other undesired outcomes. For example, sleep problems are associated with accidents and human error, including significant motor vehicle and occupational accidents. [6-8] The direct and indirect costs of disordered sleep are staggering, with some estimates as high as $100 billion attributable to insomnia alone. [9-11] Although causal mechanisms are not well-known, there is also increasing awareness of the association between disordered sleep and health, including general wellbeing, performance, daytime sleepiness, and fatigue. We also know that sleep disorders can contribute to premature mortality, cardiovascular disease, obesity, and many medical and psychological disorders. [12-15] Unfortunately, sleep problems may increase over time due to decreases in sleep duration, increases in chronic illnesses associated with poor sleep quality, and an aging population.[1, 4, 12]

  1. Ivanenko, A. and B.R. Gururaj, Classification and epidemiology of sleep disorders. Child Adolesc Psychiatr Clin N Am, 2009. 18(4): p. 839-48.
  2. Owens, J., Classification and epidemiology of childhood sleep disorders. Prim Care, 2008. 35(3): p. 533-46, vii.
  3. Brown, W. and T. Lee-Chiong, Insomnia: prevalence and daytime consequences, in Sleep: A Comprehensive Handbook. 2006, Wiley and Sons. p. 93-98.
  4. Ferrie, J.E., et al., Sleep epidemiology–a rapidly growing field. Int J Epidemiol, 2011. 40(6): p. 1431-7.
  5. Stubbs, B., et al., The prevalence and predictors of obstructive sleep apnea in major depressive disorder, bipolar disorder and schizophrenia: A systematic review and meta-analysis. J Affect Disord, 2016. 197: p. 259-67.
  6. Garbarino, S., et al., Sleep Apnea, Sleep Debt and Daytime Sleepiness Are Independently Associated with Road Accidents. A Cross-Sectional Study on Truck Drivers. PLoS One, 2016. 11(11): p. e0166262.
  7. Garbarino, S., et al., Risk of Occupational Accidents in Workers with Obstructive Sleep Apnea: Systematic Review and Meta-analysis. Sleep, 2016. 39(6): p. 1211-8.
  8. Hassani, S., et al., Association between Occupational Accidents and Sleep Apnea in Hospital Staff. Tanaffos, 2015. 14(3): p. 201-7.
  9. Botteman, M., Health economics of insomnia therapy: implications for policy. Sleep Med, 2009. 10 Suppl 1: p. S22-5.
  10. Wickwire, E.M., F.T. Shaya, and S.M. Scharf, Health economics of insomnia treatments: The return on investment for a good night’s sleep. Sleep Med Rev, 2016. 30: p. 72-82.
  11. Leger, D., The cost of sleep-related accidents: a report for the National Commission on Sleep Disorders Research. Sleep, 1994. 17(1): p. 84-93.
  12. Carmona, R.H., Frontiers of knowledge in sleep and sleep disorders: opportunities for improving health and quality of life. J Clin Sleep Med, 2005. 1(1): p. 83-9.
  13. Matricciani, L., et al., Rethinking the sleep-health link. Sleep Health, 2018. 4(4): p. 339-348.
  14. Medic, G., M. Wille, and M.E. Hemels, Short- and long-term health consequences of sleep disruption. Nat Sci Sleep, 2017. 9: p. 151-161.
  15. Stone, K.L. and Q. Xiao, Impact of Poor Sleep on Physical and Mental Health in Older Women. Sleep Med Clin, 2018. 13(3): p. 457-465.


MBHR-2021, Mental/Behavioral Health-2021, Psychology-2021