Health Outcomes for the UK and others

Published: Mon 30 May 2022
Updated: Tue 22 November 2022
By steve

In Markets.

Monday 30, May 2022

International Health Outcomes Index

It’s remarkable how well Japan does, and how badly the US does. We are depressingly low in the table, well below countries like Portugal, which have much lower GDP per capita than the UK. The NHS, while scoring well on access and ‘fairness,’ does a very poor job in keeping us alive. I’m sure it’s good on diversity and inclusivity metrics too.

The only thing we seem to be good at is treating people who have diabetes, but I suspect this is a matter of diagnosis.

Clearly, these tables are less than perfect, because they are easily skewed by early diagnosis. If we diagnose colon cancer at the last moment, survival rates will be poor, but this doesn’t mean that you’ll survive any longer in a country with better diagnosis. In the limit of no effective treatment, the outcomes will be precisely the same.

Rank Life expectancy Breast Cancer Colon Cancer Rectal Cancer Lung Cancer Stomach Cancer Diabetes admission Diabetes amputat. COPD Ischaemic Stroke Haemo. Stroke Acute Myocardial Infarction Treatable Mortality Neonatal Mortality Perinatal Mortality Maternal Mortality
Top JPN USA AUS AUS JPN JPN ITA GBR ITA NLD PRT NLD FRA JPN JPN DNK
2nd ESP AUS BEL CAN CAN BEL ESP FIN PRT DNK SWE CAN AUS SWE FIN IRL
3rd ITA JPN JPN BEL USA AUT NLD IRL FIN FIN FIN PRT JPN FIN PRT NLD
4th SWE SWE CAN NZL AUT DEU PRT SWE SWE CAN NLD DEN SWE ESP ITA AUS
5th AUS CAN USA NLD SWE USA SWE AUS NLD PRT CAN SWE NLD ITA DNK AUT
6th FRA FIN SWE JPN AUS PRT GBR NLD ESP SWE DNK ESP ITA AUT SWE DEU
7th IRL NZL FIN DNK DEU AUS IRL ESP AUT ESP ESP NZL ESP PRT ESP ESP
8th NLD PRT DEU SWE BEL ITA CAN DEU CAN NZL NZL FIN BEL IRL AUT ITA
9th CAN FRA ITA FIN IRE CAN FIN DNK GBR GBR GBR GBR FIN DEU NLD JPN
10th NZL NLD NZL AUT FRA IRE DNK AUT DEU AUT AUS GRC BEL
11th BEL BEL FRA USA NLD ESP BEL BEL CAN GRC IRL SWE
12th FIN DNK AUT GBR DNK FRA AUT DNK DNK BEL CAN GBR
13th AUT ITA ESP DEU ITA FIN DEU AUS NZL NLD USA NZL
14th PRT DEU NLD IRL PRT NZL IRL DEU FRA DEU CAN
15th GRC GBR DNK ITA NZL NLD GBR GBR GBR FRA
16th DNK ESP PRT FRA ESP SWE USA DNK BEL FIN
17th GBR AUT IRE PRT GBR GBR NZL AUS GRC
18th DEU IRL GBR ESP FIN DNK CAN FRA PRT
19th USA USA

from International Health Care Outcomes Index 2022 by Tim Knox, a study produced by Civitas, a UK think tank.

For those curious about how I dug out the data for this post

I dug the tables out of the pdf report with pdf2docx, and formatted them with this simple python script. I know you don’t care, but I did. The nice thing about this script is that you can tell it to dig out (e.g.) just the tables from a pdf.

null = "N/A"

table1 = [["Rank", "Life expectancy ", "Breast Cancer ", "Colon Cancer ", "Rectal Cancer ", "Lung Cancer ", "Stomach Cancer ", "Diabetes admission ", "Diabetes amputat. ", "COPD ", "Ischaemic Stroke ", "Haemo. Stroke ", "Acute Myocardial Infarction ", "Treatable Mortality ", "Neonatal Mortality ", "Perinatal Mortality ", "Maternal Mortality "], ["Top ", "JPN ", "USA ", "AUS ", "AUS ", "JPN ", "JPN ", "ITA ", "GBR", "ITA ", "NLD ", "PRT ", "NLD ", "FRA ", "JPN ", "JPN ", "DNK "], ["2nd ", "ESP ", "AUS ", "BEL ", "CAN ", "CAN ", "BEL ", "ESP ", "FIN ", "PRT ", "DNK ", "SWE ", "CAN ", "AUS ", "SWE ", "FIN ", "IRL "], ["3rd ", "ITA ", "JPN ", "JPN ", "BEL ", "USA ", "AUT ", "NLD ", "IRL ", "FIN ", "FIN ", "FIN ", "PRT ", "JPN ", "FIN ", "PRT ", "NLD "], ["4th ", "SWE ", "SWE ", "CAN ", "NZL ", "AUT ", "DEU ", "PRT ", "SWE ", "SWE ", "CAN ", "NLD ", "DEN ", "SWE ", "ESP ", "ITA ", "AUS "], ["5th ", "AUS ", "CAN ", "USA ", "NLD ", "SWE ", "USA ", "SWE ", "AUS ", "NLD ", "PRT ", "CAN ", "SWE ", "NLD ", "ITA ", "DNK ", "AUT "], ["6th ", "FRA ", "FIN ", "SWE ", "JPN ", "AUS ", "PRT ", "GBR", "NLD ", "ESP ", "SWE ", "DNK ", "ESP ", "ITA ", "AUT ", "SWE ", "DEU "], ["7th ", "IRL ", "NZL ", "FIN ", "DNK ", "DEU ", "AUS ", "IRL ", "ESP ", "AUT ", "ESP ", "ESP ", "NZL ", "ESP ", "PRT ", "ESP ", "ESP "], ["8th ", "NLD ", "PRT ", "DEU ", "SWE ", "BEL ", "ITA ", "CAN ", "DEU ", "CAN ", "NZL ", "NZL ", "FIN ", "BEL ", "IRL ", "AUT ", "ITA "], ["9th ", "CAN ", "FRA ", "ITA ", "FIN ", "IRE ", "CAN ", "FIN ", "DNK ", "GBR", "GBR", "GBR", "GBR", "FIN ", "DEU ", "NLD ", "JPN "], ["10th ", "NZL ", "NLD ", "NZL ", "AUT ", "FRA ", "IRE ", "DNK ", "AUT ", "DEU ", "", "", "", "AUT ", "AUS ", "GRC ", "BEL "], ["11th ", "BEL ", "BEL ", "FRA ", "USA ", "NLD ", "ESP ", "BEL ", "", "BEL ", "", "", "", "CAN ", "GRC ", "IRL ", "SWE "], ["12th ", "FIN ", "DNK ", "AUT ", "GBR", "DNK ", "FRA ", "AUT ", "", "DNK ", "", "", "", "DNK ", "BEL ", "CAN ", "GBR"], ["13th ", "AUT ", "ITA ", "ESP ", "DEU ", "ITA ", "FIN ", "DEU ", "", "AUS ", "", "", "", "NZL ", "NLD ", "USA ", "NZL "], ["14th ", "PRT ", "DEU ", "NLD ", "IRL ", "PRT ", "NZL ", "", "", "IRL ", "", "", "", "DEU ", "FRA ", "DEU ", "CAN "], ["15th ", "GRC ", "GBR", "DNK ", "ITA ", "NZL ", "NLD ", "", "", "", "", "", "", "GBR", "GBR", "GBR", "FRA "], ["16th ", "DNK ", "ESP ", "PRT ", "FRA ", "ESP ", "SWE ", "", "", "", "", "", "", "USA ", "DNK ", "BEL ", "FIN "], ["17th ", "GBR", "AUT ", "IRE ", "PRT ", "GBR", "GBR", "", "", "", "", "", "", "", "NZL ", "AUS ", "GRC "], ["18th ", "DEU ", "IRL ", "GBR", "ESP ", "FIN ", "DNK ", "", "", "", "", "", "", "", "CAN ", "FRA ", "PRT "], ["19th ", "USA ", "", "", "", "", "", "", "", "", "", "", "", "", "USA ", "", ""]]

table2 = [["", "Unmet need for medical examination due to financial, geographic or waiting times reasons, 2018 ", null, "", "Extent of coverage Gov + compulsory insurance spending as % of total health spending, 2019 or earliest year ", null, null, null, null, null, null, "", "Share of households with catastrophic health spending, latest year ", null], ["", "", "", "", "All services ", "", "", "Hospital care ", "Outpatien t care ", "Dental care ", "Pharma-ceuticals ", "", "", ""], ["", "Ranking ", "% of pop. ", "", "Ranking ", "% ", "", "", "", "", "", "", "Ranking ", "% all households "], ["Top ", "NLD ", "0.2 ", "", "SWE ", "85 ", "", "SWE ", "SWE ", "JPN ", "DEU ", "", "IRL ", "1.2 "], ["2nd ", "ESP ", "0.2 ", "", "DEU ", "85 ", "", "DEU ", "DNK ", "DEU ", "FRA ", "", "GBR ", "1.4 "], ["3rd ", "DEU ", "0.2 ", "", "JPN ", "84 ", "", "FRA ", "DEU ", "AUT ", "IRL ", "", "ESP ", "1.6 "], ["4th ", "AUT ", "0.3 ", "", "FRA ", "84 ", "", "ITA ", "GBR ", "GBR ", "JPN ", "", "SWE ", "1.8 "], ["5th ", "FRA ", "1.2 ", "", "DNK ", "83 ", "", "FIN ", "JPN ", "SWE ", "ESP ", "", "FRA ", "2.1 "], ["6th ", "SWE ", "1.4 ", "", "NLD ", "83 ", "", "GBR", "CAN ", "FIN ", "AUT ", "", "DEU ", "2.4 "], ["7th ", "DNK ", "1.8 ", "", "GBR ", "79 ", "", "JPN ", "NLD ", "BEL ", "NLD ", "", "JPN ", "2.6 "], ["8th ", "BEL ", "1.8 ", "", "FIN ", "78 ", "", "NLD ", "FIN ", "DNK ", "BEL ", "", "AUS ", "3.2 "], ["9th ", "IRL ", "2.0 ", "", "BEL ", "77 ", "", "CAN ", "AUS ", "AUS ", "ITA ", "", "AUT ", "3.2 "], ["10th ", "PRT ", "2.1 ", "", "AUT ", "75 ", "", "DNK ", "AUT ", "NLD ", "GBR ", "", "FIN ", "3.8 "], ["11th ", "ITA ", "2.4 ", "", "IRL ", "75 ", "", "AUT ", "FRA ", "CAN ", "FIN ", "", "BEL ", "3.8 "], ["12th ", "GBR ", "4.5 ", "", "ITA ", "74 ", "", "ESP ", "IRL ", "ESP ", "SWE ", "", "USA ", "7.4 "], ["13th ", "FIN ", "4.7 ", "", "ESP ", "71 ", "", "PRT ", "ESP ", "GRC ", "PRT ", "", "GRC ", "8.9 "], ["14th ", "GRC ", "8.1 ", "", "CAN ", "70 ", "", "BEL ", "BEL ", "", "GRC ", "", "ITA ", "9.4 "], ["15th ", "", "", "", "AUS ", "67 ", "", "IRL ", "PRT ", "", "AUS ", "", "PRT ", "10.6 "], ["16th ", "", "", "", "PRT ", "61 ", "", "GRC ", "GRC ", "", "DNK ", "", "", ""], ["17th ", "", "", "", "GRC ", "60 ", "", "AUS ", "ITA ", "", "CAN ", "", "", ""], ["AVERAGE ", null, "2.2 ", "", "", "76 ", "", "", "", "", "", "", "", "4.0 "]]

table3 = [["", "Health Access and Quality Index ", "", "Tuberculosis ", "Diarrhoeal diseases ", "Lower respiratory infections ", "Upper respiratory infections ", "Maternal disorders ", "Neonatal disorders ", "Non-melanoma skin cancer ", "Cervical cancer ", "Uterine cancer ", "Testicular cancer ", "Hodgkin’  lymphoma ", "Leukaemia ", "Rheumatic heart disease ", "Ischaemic heart disease ", "Cerebrovascular disease ", "Hypertensive heart disease ", "Chronic respiratory disease ", "Peptic ulcer disease ", "Appendicitis ", "Inguinal, femoral and abdominal hernia ", "Gallbladder and biliary diseases ", "Epilepsy ", "Diabetes mellitus ", "Chronic Kidney disease ", "Congenital heart anomalies ", "Adverse effects of medical treatment "], ["Top ", "SWE ", "", "AUS ", "GRC ", "AUT ", "SWE ", "ITA ", "JN ", "JPN ", "JPN ", "NLD ", "AUS ", "JPN ", "NLD ", "FIN ", "JPN ", "AUS ", "AUS ", "FIN ", "ESP ", "GRC ", "JPN ", "SWE ", "GRC ", "ESP ", "GBR ", "SWE ", "FIN "], ["2nd ", "AUS ", "", "NLD ", "FIN ", "ITA ", "AUS ", "FIN ", "FIN ", "FIN ", "FIN ", "SWE ", "JPN ", "SWE ", "FIN ", "GRC ", "FRA ", "AUT ", "NLD ", "ITA ", "ITA ", "JPN ", "SWE ", "GRC ", "JPN ", "GRC ", "FIN ", "BEL ", "NZL "], ["3rd ", "FIN ", "", "SWE ", "SWE ", "FIN ", "FIN ", "ESP ", "PRT ", "PRT ", "NLD ", "AUS ", "BEL ", "AUS ", "DNK ", "NLD ", "PRT ", "IRL ", "BEL ", "FRA ", "AUS ", "IRL ", "GRC ", "AUS ", "ESP ", "IRE ", "SWE ", "AUS ", "NLD "], ["4th ", "ESP ", "", "CAN ", "ESP ", "NZL ", "ESP ", "AUT ", "SWE ", "SWE ", "SWE ", "DEU ", "SWE ", "CAN ", "JPN ", "JPN ", "ESP ", "ESP ", "CAN ", "GRC ", "FRA ", "SWE ", "DEU ", "AUT ", "USA ", "JPN ", "FRA ", "AUT ", "SWE "], ["5th ", "NLD ", "", "DEU ", "ITA ", "GRC ", "NLD ", "DNK ", "IRL ", "IRL ", "DEU ", "FIN ", "ESP ", "AUT ", "CAN ", "SWE ", "ITA ", "CAN ", "SWE ", "AUT ", "NLD ", "AUS ", "AUS ", "CAN ", "ITA ", "BEL ", "NLD ", "ESP ", "IRE "], ["6th ", "JPN ", "", "USA ", "DEU ", "AUS ", "JPN ", "SWE ", "FRA ", "FRA ", "ESP ", "DNK ", "IRE ", "FIN ", "USA ", "BEL ", "DNK ", "FRA ", "DNK ", "SWE ", "CAN ", "ITA ", "AUT ", "JPN ", "CAN ", "ITS ", "AUS ", "NLD ", "JPN "], ["7th ", "ITA ", "", "NZL ", "AUS ", "SWE ", "ITA ", "JPN ", "ESP ", "ESP ", "ITA ", "FRA ", "CAN ", "FRA ", "AUS ", "DNK ", "NLD ", "SWE ", "FRA ", "ESP ", "NZL ", "AUT ", "NZL ", "IRL ", "AUT ", "FRA ", "IRL ", "FIN ", "ITA "], ["8th ", "IRL ", "", "DNK ", "NZL ", "ESP ", "IRE ", "IRL ", "GRC ", "GRC ", "AUS ", "CAN ", "GBR ", "DEU ", "IRE ", "IRL ", "AUS ", "ITA ", "ESP ", "DEU ", "AUT ", "BEL ", "ITA ", "FRA ", "PRT ", "GBR ", "BEL ", "DEU ", "CAN "], ["9th ", "AUS ", "", "ITA ", "JPN ", "FRA ", "AUT ", "PRT ", "AUT ", "AUT ", "DNK ", "IRE", "FIN ", "USA ", "DEU ", "AUS ", "BEL ", "GBR ", "IRL ", "NLD ", "USA ", "FIN ", "NLD ", "NZL ", "SWE ", "NLD ", "ESP ", "DNK ", "DNK "], ["10th ", "FRA ", "", "AUT ", "IRE ", "DNK ", "FRA ", "AUS ", "BEL ", "BEL ", "FRA ", "GBR", "ITA ", "NZL ", "SWE ", "AUT ", "GBR", "BEL ", "NZL ", "BEL ", "JPN ", "CAN ", "IRE ", "DEU ", "AUS ", "AUT ", "ITA ", "CAN ", "AUS "], ["11th ", "BEL ", "", "BEL ", "CAN ", "CAN ", "BEL ", "NLD ", "DEU ", "AUS ", "AUT ", "BEL ", "PRT ", "NLD ", "AUT ", "GBR ", "AUT ", "NLD ", "PRT ", "IRL ", "PRT ", "NZL ", "BEL ", "FIN ", "NLD ", "DEU ", "CAN ", "IRL ", "ESP "], ["12th ", "CAN ", "", "GBR", "GBR", "DEU ", "CAN ", "CAN ", "AUS ", "DEU ", "CAN ", "ESP ", "NLD ", "BEL ", "BEL ", "CAN ", "SWE ", "DEU ", "JPN ", "CAN ", "GRC ", "NLD ", "CAN ", "NLD ", "IRE ", "PRT ", "DEU ", "FRA ", "GBR"], ["13th ", "GRC ", "", "FIN ", "AUT ", "NLD ", "DEU ", "DEU ", "ITA ", "ITA ", "GBR", "USA ", "FRA ", "ESP ", "GBR", "DEU ", "IRE ", "NZL ", "GRC ", "DNK ", "BEL ", "FRA ", "FRA ", "BEL ", "NZL ", "AUS ", "DNK ", "ITA ", "BEL "], ["14th ", "DEU ", "", "ESP ", "FRA ", "IRE ", "NZL ", "BEL ", "DNK ", "DNK ", "BEL ", "ITA ", "NZL ", "DNK ", "ESP ", "FRA ", "CAN ", "USA ", "GBR", "JPN ", "IRL ", "DEU ", "USA ", "ITA ", "DNK ", "NZL ", "AUT ", "NZL ", "DEU "], ["15th ", "NZL ", "", "FRA ", "BEL ", "BEL ", "GBR", "GRC ", "NLD ", "NZL ", "USA ", "AUT ", "AUT ", "PRT ", "FRA ", "PRT ", "DEU ", "DNK ", "DEU ", "PRT ", "DEU ", "ESP ", "FNI ", "DNK ", "FIN ", "SWE ", "GRC ", "PRT ", "PRT "], ["16th ", "DNK ", "", "IRE ", "PRT ", "GBR", "GRC ", "FRA ", "NZL ", "NLD ", "GRC ", "NZL ", "USA ", "ITA ", "GRC ", "ITA ", "NZL ", "FIN ", "AUT ", "AUS ", "SWE ", "PRT ", "ESP ", "USA ", "BEL ", "CAN ", "PRT ", "JPN ", "GRC "], ["17th ", "GBR", "", "GRC ", "NZL ", "JPN ", "DNK ", "GBR", "CAN ", "CAN ", "DEU ", "PRT ", "GRC ", "IRE ", "NZL ", "ESP ", "FIN ", "JPN ", "FIN ", "GBR", "FIN ", "GBR", "DNK ", "ESP ", "FRA ", "FIN ", "NZL ", "GBR", "USA "], ["18th ", "PRT ", "", "JPN ", "DNK ", "PRT ", "PRT ", "NZL ", "GBR", "GBR", "SWE ", "GRC ", "DEU ", "GBR", "ITA ", "USA ", "USA ", "GRC ", "ITA ", "NZL ", "GBR", "USA ", "PRT ", "PRT ", "DEU ", "DNK ", "JPN ", "USA ", "AUT "], ["19th ", "USA ", "", "PRT ", "USA ", "USA ", "USA ", "USA ", "USA ", "USA ", "PRT ", "JPN ", "DNK ", "GRC ", "PRT ", "NZL ", "GRC ", "PRT ", "USA ", "USA ", "USA ", "DNK ", "GBR", "GBR", "GBR ", "USA ", "USA ", "GRC ", "FRA "]]

for i in table1:
    print('|', end="")
    for j in i:
        print("{} | ".format(j), end="")
    if i[0] == "Rank":
        print()
        for j in i:
            print("| ---", end='')
        print('|', end = '')
    print()

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