healthcare cost

Why are our healthcare costs so expensive? The United States spends an unproportional amount of spending on healthcare compared to any other country, which in turn is reflected in sky-rocketing out-of-pocket payments and insurance premiums. In 2021, the U.S. spent 17.8 percent of gross domestic product (GDP) on health care, nearly twice as much as the average OECD country (Commonwealth Fund). Despite spending so much on healthcare, the US also has one of the poorest health outcomes compared to countries that spend much less. The U.S. has the lowest life expectancy at birth, the highest death rates for preventable conditions, the highest maternal and infant mortality, and among the highest suicide rates. The long-term trend in national healthcare spending is unsustainable, as spending is anticipated to continue rising. To curb unnesscessary spending, action should be taken toward examining where the money is being allocated and which components of the healthcare system need more or less focus.

NYT article summary of issue here.

More in-depth reading about the factors behind excessive healthcare spending here.

Commonwealth Fund statistics comparing US healthcare spending and outcomes with graphs here.

Datasets

import pandas as pd
df_costs = pd.read_csv('national_spending_on_healthcare_goods_and_services_usafacts.csv')

df_costs.head()

	Years	1960	1961	1962	1963	1964	1965	1966	1967	1968	...	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
0	National spending on healthcare goods and serv...	27122000000	29060000000	31765000000	34558000000	38245000000	41627000000	45752000000	5.118600e+10	5.801500e+10	...	2.676178e+12	2.782804e+12	2.855822e+12	3.001434e+12	3.163647e+12	3.305581e+12	3.446492e+12	3.604511e+12	3.759123e+12	4.124005e+12
1	By expenditure	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	Hospital ($)	8985000000	9777000000	10432000000	11507000000	12501000000	13545000000	15298000000	1.779800e+10	2.053700e+10	...	8.332460e+11	8.779680e+11	9.068040e+11	9.405260e+11	9.889710e+11	1.035398e+12	1.077580e+12	1.122633e+12	1.193716e+12	1.270149e+12
3	Physician and clinical ($)	5551000000	5814000000	6261000000	7074000000	8109000000	8587000000	9309000000	1.044800e+10	1.134400e+10	...	5.357760e+11	5.571220e+11	5.679360e+11	5.976620e+11	6.364330e+11	6.753480e+11	7.094100e+11	7.368760e+11	7.678810e+11	8.094600e+11
4	Dental services ($)	1987000000	2104000000	2225000000	2372000000	2617000000	2819000000	2993000000	3.447000e+09	3.707000e+09	...	1.080220e+11	1.097000e+11	1.113760e+11	1.146940e+11	1.199610e+11	1.261970e+11	1.311290e+11	1.375200e+11	1.432490e+11	1.424050e+11

5 rows × 62 columns

Column: Expenditures	Data Type	Description
Out of pocket	int	expenses for medical care that aren't reimbursed by insurance
Private health insurance	int	coverage provided by a private entity
Medicare	int	health insurance for people 65 or older
Medicaid	int	health coverage to some people with limited income and resources.
Children's health insurance program	int	provide health insurance to low-income children whose family income meets the eligibility requirements for Medicaid in their state.
Department of Defense	int	responsible for providing the military forces needed to deter war and protect the security of our country.
Department of Veterans Affairs	int	provide health, education, disability, funerary, and financial benefits earned by Veterans of the United States Armed Forces
worksite healthcare	int	setting where an employer or union offers one or more medical and wellness services
other private revenues	int	company revenues
indian health services	int	delivers health care to American Indians and Alaska Natives
workers compensation	int	insurance that provides cash benefits and/or medical care for workers who are injured or become ill as a direct result of their job
general assistance	int	economic assistance (cash benefit) programs that help individuals and families
maternal and infant health program	int	to improve access to and quality of care for pregnant and postpartum women and their infants,
vocational rehabilitation	int	helps job seekers with disabilities obtain and maintain a job.
other federal programs	int	etc.
substance abuse and mental health administration	int	agency within the U.S. Department of Health and Human Services that leads public health efforts to advance the behavioral health of the nation
other state and local programs	int	etc.
school health	int	comprehensive efforts of developing, implementing, and evaluating services, both within the school and the community, that provide each and every student with the resources needed to thrive within a healthful environment.
investment	int	general investment into healthcare programs/social welfare

Each feature is an important part of the U.S. healthcare system in which the federal government distributes its resources to. By determining which department produces the most costs over the years, we can delve deeper into whether its spending is excessive or not.

df_issues = pd.read_csv('/Users/mel/Desktop/DS2500/leading_causesof_death.csv')

df_issues.head()

	index	State_FIPS_Code	County_FIPS_Code	CHSI_County_Name	CHSI_State_Name	CHSI_State_Abbr	Strata_ID_Number	A_Wh_Comp	CI_Min_A_Wh_Comp	CI_Max_A_Wh_Comp	...	F_Bl_Cancer	CI_Min_F_Bl_Cancer	CI_Max_F_Bl_Cancer	F_Ot_Cancer	CI_Min_F_Ot_Cancer	CI_Max_F_Ot_Cancer	F_Hi_Cancer	CI_Min_F_Hi_Cancer	CI_Max_F_Hi_Cancer	LCD_Time_Span
0	0	1	1	Autauga	Alabama	AL	29	-1111	-1111	-1111	...	19	14	23	-1111	-1111	-1111	-1111	-1111	-1111	1999-2003
1	1	1	3	Baldwin	Alabama	AL	16	57	39	75	...	20	15	25	-1111	-1111	-1111	-1111	-1111	-1111	2001-2003
2	2	1	5	Barbour	Alabama	AL	51	-1111	-1111	-1111	...	26	22	31	-1111	-1111	-1111	-1111	-1111	-1111	1999-2003
3	3	1	7	Bibb	Alabama	AL	42	-1111	-1111	-1111	...	20	14	25	-1111	-1111	-1111	-1111	-1111	-1111	1994-2003
4	4	1	9	Blount	Alabama	AL	28	34	17	52	...	28	10	46	-1111	-1111	-1111	-1111	-1111	-1111	1999-2003

5 rows × 236 columns

df_dict = pd.read_csv('/Users/mel/Downloads/DATAELEMENTDESCRIPTION.csv')

df_dict

	index	PAGE_NAME	COLUMN_NAME	DATA_TYPE	IS_PERCENT_DATA	DESCRIPTION	REFERENCE
0	0	Demographics	State_FIPS_Code	Text	N	Two-digit state identifier, developed by the N...	Data Sources, Definitions, and Notes, Page 6
1	1	Demographics	County_FIPS_Code	Text	N	Three-digit county identifier, developed by th...	Data Sources, Definitions, and Notes, Page 6
2	2	Demographics	CHSI_County_Name	Text	N	Name of county	NaN
3	3	Demographics	CHSI_State_Name	Text	N	Name of State or District of Columbia	NaN
4	4	Demographics	CHSI_State_Abbr	Text	N	Two-character postal abbreviation for state name	NaN
...	...	...	...	...	...	...	...
573	573	RiskFactorsAndAccessToCare	Disabled_Medicare	Integer	N	County data, medicare beneficiaries, disabled	Data Sources, Definitions, and Notes, Page 29
574	574	RiskFactorsAndAccessToCare	Prim_Care_Phys_Rate	Decimal	N	County data, primary care physicians per 100,0...	Data Sources, Definitions, and Notes, Page 30
575	575	RiskFactorsAndAccessToCare	Dentist_Rate	Decimal	N	County data, dentists per 100,000 pop.	Data Sources, Definitions, and Notes, Page 30
576	576	RiskFactorsAndAccessToCare	Community_Health_Center_Ind	Integer	N	Indicator for any Community/Migrant Health Cen...	Data Sources, Definitions, and Notes, Page 30
577	577	RiskFactorsAndAccessToCare	HPSA_Ind	Integer	N	Indicator for single county designated Health ...	Data Sources, Definitions, and Notes, Page 30

578 rows × 7 columns

Each column type is a health indicator. By studying the nature of these health indicators, we can determine what the leading health issues are in America and redirect healthcare spending on resolving those issues.

Usage of Data

The first dataset will be used to compile the categories that account for the greatest amount of spending above a sustainable spending trend. Then we will compare those categories with the most significant health indicators affecting the U.S. population to redesign healthcare spending allocation.