Regression Analysis — SeekingChartis Corpus

🛡️ Public data only — no PHI permitted on this instance.

63.8%

R²

63.6%

Adj R²

4,858

Observations

Features

405.9

F-Statistic

0.1454

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: 0.5240

SE: 0.0021

Target Mean: 0.5240

Target Range: 0.0066 — 2.3918

When all features are at their mean values, the predicted occupancy rate is 0.52

Coefficients (Standardized)

Target: Occupancy Rate. 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
Bed Days Available	-1.000	34.0	0.0000	***	[-0.556, -0.496]
Medicare Days	+0.713	17.6	0.0000	***	[0.334, 0.417]
Beds	+0.651	13.7	0.0000	***	[0.294, 0.392]
Medicare Intensity	-0.629	15.8	0.0000	***	[-0.372, -0.290]
Total Patient Days	+0.466	10.4	0.0000	***	[0.199, 0.291]
Size Quartile	+0.245	35.7	0.0000	***	[0.122, 0.136]
Revenue Per Bed	+0.138	7.6	0.0000	***	[0.054, 0.091]
Net Patient Revenue	-0.087	13.8	0.0000	***	[-0.052, -0.039]
Revenue Per Day	-0.081	16.9	0.0000	***	[-0.047, -0.038]
Operating Expenses	-0.074	13.7	0.0000	***	[-0.045, -0.034]
Expense Per Bed	-0.055	3.3	0.0011	**	[-0.046, -0.012]
Operating Margin	+0.048	9.7	0.0000	***	[0.020, 0.030]
Medicaid Day Pct	+0.032	6.8	0.0000	***	[0.012, 0.022]
Net Income	-0.028	5.5	0.0000	***	[-0.020, -0.010]
Payer Diversity	-0.022	3.9	0.0001	***	[-0.017, -0.006]
Medicaid Days	-0.022	3.3	0.0009	***	[-0.018, -0.005]
Gross Patient Revenue	-0.019	5.0	0.0000	***	[-0.014, -0.006]
Net To Gross Ratio	+0.014	2.6	0.0092	**	[0.002, 0.013]
Medicare Day Pct	-0.011	3.1	0.0022	**	[-0.009, -0.002]
Commercial Pct	-0.009	2.4	0.0182	*	[-0.009, -0.001]
Contractual Allowances	+0.002	0.3	0.7834	ns	[-0.005, 0.007]

Univariate Correlations with Target

Pearson r for each feature vs Occupancy Rate. Shows raw linear relationship before controlling for other variables.

Feature	r	Strength
Size Quartile	0.539	Moderate
Total Patient Days	0.509	Moderate
Medicare Days	0.488	Moderate
Bed Days Available	0.431	Moderate
Beds	0.427	Moderate
Net Patient Revenue	0.392	Weak
Operating Expenses	0.382	Weak
Gross Patient Revenue	0.380	Weak
Medicare Intensity	0.375	Weak
Contractual Allowances	0.363	Weak
Medicare Day Pct	-0.352	Weak
Medicaid Days	0.342	Weak
Commercial Pct	0.296	Weak
Operating Margin	0.193	Weak
Revenue Per Day	-0.176	Weak
Net To Gross Ratio	-0.175	Weak
Payer Diversity	-0.115	Weak
Net Income	-0.115	Weak
Revenue Per Bed	0.099	Weak
Medicaid Day Pct	0.092	Weak
Expense Per Bed	0.081	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
IZARD REGIONAL HOSPITAL	AR	2.3458	0.2404	+14.48σ
FIRSTHEALTH MONTGOMERY MEMORIAL CAH	NC	2.3918	0.5653	+12.56σ
PARKLAND HLTH CTR - BONNE TERRE	MO	0.0493	-0.9369	+6.78σ
SPECTRUM HEALTH REED CITY	MI	0.0066	-0.9264	+6.41σ
MEMORIAL HERMANN MEMORIAL CITY MEDI	TX	2.2445	1.4439	+5.50σ
BAPTIST HEALTH SYSTEM	TX	0.5249	-0.1885	+4.90σ
NORTH SHORE UNIVERSITY HOSPITAL	NY	1.0026	1.7036	-4.82σ
BRIGHAM AND WOMENS HOSPITAL	MA	1.0133	1.6682	-4.50σ
CHRISTIANA CARE HEALTH SYSTEM	DE	0.8816	1.5128	-4.34σ
RIVERSIDE HOSPITAL OF LOUISIANA	LA	1.0998	0.4720	+4.32σ
ATLANTA MEDICAL CENTER	GA	0.4014	1.0178	-4.24σ
ST. JOSEPHS HOSPITAL	FL	0.5616	-0.0443	+4.17σ
MASSACHUSETTS GENERAL HOSPITAL	MA	0.9262	1.4940	-3.90σ
CLEVELAND CLINIC HOSPITAL	OH	0.7592	0.2042	+3.82σ
HENRICO DOCTORS HOSPITAL	VA	0.4116	-0.1286	+3.71σ

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	142.7	High
Total Patient Days	127.1	High
Medicare Days	103.9	High
Medicare Intensity	100.5	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
CT	31	75.2%	0.0000
IL	191	72.9%	-0.0000
ND	40	71.4%	0.0000
TN	72	71.4%	-0.0000
MN	122	71.3%	-0.0000
CO	103	70.8%	-0.0000
TX	320	70.7%	-0.0000
WA	95	69.7%	0.0000
NH	27	69.4%	0.1000
IA	91	69.2%	-0.1000
NV	49	67.8%	0.0000
GA	149	65.4%	0.0000
PA	174	65.4%	0.0000
MI	137	64.3%	-0.0000
OR	57	64.2%	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