Benchmarking Psychiatric Deinstitutionalization: Development and Testing of a Nonlinear Regression Model

Background/Purpose. Only occasionally over the history of deinstitutionalization have debates about the wisdom of this policy led to efforts to determine optimal levels of inpatient psychiatric care needed. Without such benchmarks, public mental health authorities have had little basis to know whether they are wasting scarce resources on hospitalizing those without sufficient need, or neglecting the clinical needs of acutely mentally ill individuals. This study, thus, aims to develop benchmarks for rates of psychiatric beds needed in various nations. Sporadic efforts, since the 1950s, to estimate such need have generated divergent results, but in recent years these have converged on the 30 to 70 bed per 100,000 population level. These studies have been based on various methodologies ranging from use of existing utilization levels to professional opinion studies. The current study builds on this body of research by developing a predictive model of psychiatric bed needs, based on rates of psychiatric disability, CMH services, and socioeconomic indicators.

Methods. This project employs predictive analytics, specifically non-linear multiple regression, with existing data to identify national benchmarks for needed psychiatric beds. It employs data from the Global Burden of Disease study on rates of psychiatric disability and from WHO’s Assessment Instrument for Mental Health Systems on mental health services, as well as other sources for sociodemographic predictors. Two sets of estimates are generated, one with predictors at measured levels, and one with community mental health levels set at the level of the top 10% of the nations, which presumes an ambitious but attainable level of community mental health services. Results are validated through comparison with those from previous studies that used alternative methodologies.

Results. The final regression model accounts for 42.3% (p<.001) of the variation in psychiatric bed days among the 166 nations with available data. A comparison of the actual hospitalization levels with the projected need indicates that 69.6% of the nations have significantly fewer beds than needed; 18.3% have rates of hospitalization commensurate with need; and 11.8% have an excess of psychiatric beds. The overall projected rate of need, at 45.5 beds per 100,000, has a confidence interval of 36.5 to 54.5 that encompasses most of the recently published estimates. Whereas only European nations provide beds at a level commensurate with need, all other regions (and the U.S.) provide beds at a level significantly less than the need.

Conclusions/Implications. These results enable national mental health authorities to develop operational goals for either increasing, maintaining, or decreasing psychiatric beds, and in some cases, redeploying resources to community mental health services. Both the point estimates and confidence intervals for each nation provide a basis to begin to determine how to ‘right-size’ and balance the segment of a nation’s mental health system involving inpatient services. It also demonstrates the possibilities for similar studies of other service modalities, whether outpatient, day programs, ACT programs, or residential or employment programs. Such benchmarking studies provide a practical basis for balancing alternative service modalities and enhancing the coherence, responsiveness, and effectiveness of a nation’s mental health system.