Regression Analysis — SeekingChartis Corpus

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44.2%

R²

44.0%

Adj R²

4,858

Observations

Features

182.7

F-Statistic

0.1397

RMSE (avg error)

R² = fraction of variance explained (1.0 = perfect, 0 = no signal). RMSE = root mean squared error (average prediction miss in target units). F-statistic tests whether the model explains more than random chance.

Intercept Interpretation

Value: 0.3623

SE: 0.0020

Target Mean: 0.3623

Target Range: 0.0283 — 1.0000

When all features are at their mean values, the predicted net to gross ratio is 0.36

Coefficients (Standardized)

Target: Net To Gross Ratio. Standardized coefficients (-1.0 to +1.0): a one-SD increase in the feature produces this fraction of the strongest effect. *** p<0.001, ** p<0.01, * p<0.05.

Variable	Strength	t	p-value	Sig	95% CI
Medicare Days	+1.000	4.3	0.0000	***	[0.050, 0.132]
Medicare Intensity	-0.947	4.2	0.0000	***	[-0.126, -0.046]
Contractual Allowances	-0.852	28.1	0.0000	***	[-0.083, -0.072]
Beds	+0.852	3.2	0.0015	**	[0.030, 0.125]
Size Quartile	-0.760	18.3	0.0000	***	[-0.077, -0.062]
Payer Diversity	-0.559	18.4	0.0000	***	[-0.056, -0.045]
Net Patient Revenue	+0.547	15.8	0.0000	***	[0.044, 0.056]
Gross Patient Revenue	-0.543	26.8	0.0000	***	[-0.053, -0.046]
Commercial Pct	-0.525	27.1	0.0000	***	[-0.051, -0.044]
Operating Expenses	+0.476	15.9	0.0000	***	[0.038, 0.049]
Medicaid Day Pct	+0.379	14.9	0.0000	***	[0.030, 0.039]
Medicare Day Pct	+0.288	14.7	0.0000	***	[0.023, 0.030]
Total Patient Days	-0.269	1.1	0.2837	ns	[-0.069, 0.020]
Revenue Per Bed	-0.211	2.1	0.0374	*	[-0.037, -0.001]
Bed Days Available	-0.181	1.0	0.3196	ns	[-0.049, 0.016]
Expense Per Bed	+0.159	1.7	0.0909	ns	[-0.002, 0.031]
Net Income	+0.134	4.7	0.0000	***	[0.007, 0.017]
Occupancy Rate	+0.095	2.6	0.0092	**	[0.002, 0.015]
Medicaid Days	-0.075	2.1	0.0399	*	[-0.013, -0.000]
Operating Margin	+0.027	1.0	0.3260	ns	[-0.002, 0.007]
Revenue Per Day	+0.021	0.8	0.4481	ns	[-0.003, 0.007]

Univariate Correlations with Target

Pearson r for each feature vs Net To Gross Ratio. Shows raw linear relationship before controlling for other variables.

Feature	r	Strength
Size Quartile	-0.472	Moderate
Commercial Pct	-0.426	Moderate
Medicare Day Pct	0.358	Weak
Contractual Allowances	-0.346	Weak
Gross Patient Revenue	-0.316	Weak
Bed Days Available	-0.287	Weak
Beds	-0.286	Weak
Medicare Intensity	-0.265	Weak
Total Patient Days	-0.241	Weak
Medicare Days	-0.230	Weak
Net Patient Revenue	-0.183	Weak
Occupancy Rate	-0.175	Weak
Operating Expenses	-0.173	Weak
Medicaid Day Pct	0.107	Weak
Medicaid Days	-0.090	Weak
Operating Margin	-0.074	Weak
Revenue Per Day	0.037	Weak
Net Income	0.025	Weak
Payer Diversity	-0.017	Weak
Revenue Per Bed	-0.008	Weak
Expense Per Bed	0.004	Weak

Hospital Outliers (Residual Analysis)

Hospitals with the largest standardized residuals. >2σ = model underpredicts/overpredicts — investigate for deal opportunities or data quality issues.

Hospital	State	Actual	Predicted	Residual
NYU LANGONE HOSPITALS	NY	0.1747	-0.7075	+6.31σ
LINCOLN REGIONAL CENTER	NE	1.0000	0.3375	+4.74σ
EASTERN STATE HOSPITAL	WA	0.9942	0.3779	+4.41σ
STANFORD HEALTH CARE	CA	0.2000	-0.4156	+4.41σ
SOUTHERN PLAINS MED CTR OF GARVIN C	OK	1.0000	0.3926	+4.35σ
VIBRA HOSPITAL DENVER	CO	0.0924	0.6884	-4.26σ
STATE HOSPITAL SOUTH	ID	0.9550	0.3593	+4.26σ
KINGWOOD EMERGENCY HOSPITAL	TX	0.9988	0.4033	+4.26σ
NEW MEXICO REHABILITATION CENTER	NM	1.0000	0.4094	+4.23σ
MARYLAND GENERAL HOSPITAL	MD	0.8553	0.2778	+4.13σ
ST. JOSEPHS COMM. HOSPT.	WI	0.9263	0.3497	+4.13σ
CEDARS-SINAI MEDICAL CENTER	CA	0.1508	-0.4208	+4.09σ
HOSPITAL MENONITA HUMACAO	PR	0.9413	0.3706	+4.08σ
CORPORACION DEL CENTRO CARDIOVASCUL	PR	0.9152	0.3460	+4.07σ
HENDRICKS BEHAVIORAL HOSPITAL	IN	0.9145	0.3479	+4.05σ

Variance Inflation Factors

VIF > 10 = severe multicollinearity (coefficient estimates unreliable). VIF > 5 = moderate. Consider removing high-VIF features.

Feature	VIF	Status
Net Patient Revenue	999.0	High
Operating Expenses	999.0	High
Medicare Day Pct	999.0	High
Medicaid Day Pct	999.0	High
Net Income	999.0	High
Gross Patient Revenue	999.0	High
Contractual Allowances	999.0	High
Commercial Pct	999.0	High
Beds	148.0	High
Total Patient Days	129.9	High
Medicare Days	110.2	High
Medicare Intensity	105.3	High

Model Fit by State

How well the national model predicts within each state. Low R² states have unique market dynamics not captured by national features — consider state-specific models.

State	n	R²	Mean Residual
HI	18	63.6%	0.0000
NJ	79	61.9%	-0.0000
IA	91	59.2%	0.0000
SD	53	53.0%	-0.0000
CO	103	51.4%	-0.0000
NV	49	50.4%	-0.0000
GA	149	49.7%	-0.0000
NH	27	48.6%	0.0000
MS	89	46.5%	-0.1000
AK	18	45.8%	0.0000
WA	95	45.0%	0.0000
VA	89	44.8%	-0.0000
VT	14	41.9%	-0.0000
FL	192	40.9%	-0.0000
CA	317	38.5%	-0.0000

Top Pairwise Correlations

Variable 1	Variable 2	r
Gross Patient Revenue	Contractual Allowances	0.992
Beds	Bed Days Available	0.984
Net Patient Revenue	Operating Expenses	0.982
Total Patient Days	Bed Days Available	0.976
Beds	Total Patient Days	0.962
Medicare Days	Medicare Intensity	0.955
Revenue Per Bed	Expense Per Bed	0.953
Net Patient Revenue	Gross Patient Revenue	0.912
Total Patient Days	Medicare Days	0.901
Operating Expenses	Gross Patient Revenue	0.891
Beds	Medicare Intensity	0.881
Net Patient Revenue	Total Patient Days	0.879
Medicare Days	Bed Days Available	0.874
Operating Expenses	Total Patient Days	0.869
Total Patient Days	Gross Patient Revenue	0.863

Market Heatmap Analysis Hub Regression JSON API Operating Margin Revenue/Bed Occupancy Net-to-Gross