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Development of Computer-assisted Health Policy Decision Making. Jung- Der Wang, MD, ScD ( 王榮德 ) Chao- Hui Lee, PhD ( 李昭輝 ) Dept. of Public Health, College of Medicine National Cheng Kung University. 綱要 (Outlines). 回到醫療照護的核心價值:全民健康 電腦輔助決策對醫療照護的影響 : Lower cost and best quality of care

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development of computer assisted health policy decision making

Development of Computer-assisted Health Policy Decision Making

Jung-Der Wang, MD, ScD (王榮德)

Chao-Hui Lee, PhD (李昭輝)

Dept. of Public Health, College of Medicine

National Cheng Kung University

outlines
綱要(Outlines)
  • 回到醫療照護的核心價值:全民健康
  • 電腦輔助決策對醫療照護的影響:

Lower cost and best quality of care

健康計量基本原理:發生率(少生傷病)、活得長壽、生活品質又好(功能障礙少)

  • 未來的發展方向:藍海策略

醫療資料電子化企機:生活品質與功能評估

跨領域學識之發展與人才的培養

acknowledgement
Acknowledgement:
  • Dr. Hwang JS(黄景祥), Institute of Statistical Science, Academia Sinica (iSQoL software)
  • Dr. Fang CT (方啟泰), Graduate Institute of Epidemiology and Preventive Medicine, National Taiwan University (mathematical proof of our extrapolation of survival)
  • Dr. Liu JT (劉錦添), Department of Economics, National Taiwan University
  • Dr. Yao KP (姚開屏), Department of Psychology National Taiwan University
  • NSC(國科會),NHRI(國衛院),BHP(國民健康局)ssistants
slide4

事件總衝擊量(Impact of event)

重大傷病之發生率及預期損失壽命與健保花費

事件發生率

(國家決策或個人健康風險評估得出之機率)

(Likelihood of event)

事件(疾病)之後果

損失壽命與生活品質、健保及長照之花費(Consequence of event)

X

電腦輔助預防與診療決策系統

(以提高健保服務之成本效果cost-effectiveness)

slide5

Head injury as an example for policy decision

likelihood utility QALY

0.85

0.10

0.05

0.85

0.10

0.05

0.7

0.2

0.1

0.4

0.2

0.4

1

0.5

0

1

0.5

0

1

0.5

0

1

0.5

0

40

32

0

40

32

0

40

30

0

40

20

0

0.8

0.9(utility)

37.2 QALY

0.895(utility)

37.04 QALY

0.15

0.9(utility)

37.2 QALY

0.05

0.8(utility)

34 QALY

0.5(utility)

20 QALY

slide7
為甚麼健康照護應該要以非營利方式經營?
  • 健康照護的核心價值是病患的價值,而不是牟利。(醫學倫理)
  • 以營利為目標會切斷醫病之互信

(趁火打劫?)

  • 增加健康照護花費並無法完全提升健康照護的結果(如: 存活或平均餘命和生活品質)

(Scientific American 2011 July:37)

slide8

大部分工業國在積極提高健康照護成

本,美國的總支出從1980年開始飛漲

且高於在經濟合作與發展組織

(OECD)內的其他國家。

人均健康總支出,以美金為計

美國(紅線)給付每個人的健康

照護費用更高於其他的OECD

國家。英國(藍線)

Scientific American 2011 July:37

slide9

當涉及到健康指標, 如預期壽命,美國表現(紅線)比英國(藍線,約在中位數上)差

出生時預期壽命(年)

Scientific American 2011 July:37

annual figure for 2009 projected by centers for medicare and medicaid services

由Medicare和Medicaid服務中心預計2009年度的分配情形由Medicare和Medicaid服務中心預計2009年度的分配情形

Annual figure for 2009 projected by Centers for Medicare and Medicaid Services

國内生產總值的分配

健康照護

房屋和公

用事業

交通工具

和其他

汽油和其他能源產品

國防

食物

Source: Korn AM, et.al. Health care reform in the United States – one year later. ISOPR connection.

u s health in international perspective shorter lives poorer health
U.S. Health in International Perspective: Shorter Lives, Poorer Health
  • infant mortality and low birth weight
  • injuries and homicides
  • adolescent pregnancy

and sexually transmitted

infections

  • HIV and AIDS
  • drug-related deaths
  • obesity and diabetes
  • heart disease
  • chronic lung disease
  • disability

Institute of Medicine, 2013

slide12

Best Care at Lower Cost :The Path to Continuously Learning Health Care in America(Institute of Medicine, 2012) (IOM, 2010 waste of resources)

  • Unnecessary services 210 billions

(Beyond evidence-established levels)

  • Inefficiently delivered services 130 billions

(Errors and preventable complications)

  • Excess administrative costs 190 billions
  • Prices too high 105 billions

(beyond competitive benchmarks)

  • Misses prevention opportunities 55 billions
  • Fraud – All sources, patients & workers 75 billions
characteristics of computer science
Characteristics of computer science
  • Speedy storage and retrieval of large amount of information
  • Fast arithmetic calculation
  • Ubiquitous

How to apply the technology of information engineering on continuous improvement of cost-effectiveness in healthcare services ?

continuously learning health care system institute of medicine 2012 best care at lower cost
Continuously Learning Health Care system(Institute of Medicine, 2012: Best Care at Lower Cost )
  • Sciences and informatics:

Real time access to knowledge and previous care experiences (即時取得從前照護經驗及知識)

  • Patient-clinician partnership:

Engaged and empower patients and families(鼓勵病人家家屬参與醫療決策)

  • Incentives:

Reward high value care and transparency of costs and outcome(廻饋高價值醫療並讓成本與效果透明)

  • Culture:

Leadership instilled culture of learning, team work, collaboration (培植團隊學習與合作之文化)

united states chemotherapy drug price trends

美國化療藥價的趨勢

United States Chemotherapy Drug Price Trends

癌症藥物

累計百分比增加

癌症治療

健康照護

美國國內生產總值

Source: Korn AM, et.al. 2011, ISOPR connection.

2006 by michael porter and elizabeth teisberg
重新定義健康照護(2006):by Michael Porter and Elizabeth Teisberg
  • 著重於病人價值
  • 花費在提供服務上的每一元美金的健康結果, 稱之為價值。結果是多面向的,不只是包含了存活,更包括了生活品質 …

(New Engl J Med 2009;361:109-12)

slide18
成本效果是讓全民健康保險在有限資源下得以永續成本效果是讓全民健康保險在有限資源下得以永續
  • 什麼是療效最終指標?

活得長壽且健康(生活品質好)

pubmed
PubMed資料庫中的文獻數量

QOL 2012----20224 2011----18468

QOL

生活品質

實證醫學

a common question raised
A common question raised:
  • Is there a common unit to measure our customer’s or patient’s outcome ?
  • Live vs. Dead ---- counting the no. of lives saved
  • More delicate measures:

--Length of survival S(t) or S(ti|xi)存活函數 --Quality of life Qol(ti|xi)生活品質函數

  • Can we measure S(ti|xi) or Qol(ti|xi)?
  • Can we develop a method to combine both?
  • (Can we quantify the cost paid by the NHI? )
slide21

QALY (quality-adjusted life year) –

integrate survival and quality of life

Area under survival curve

=Life expectancy

(with life-year as unit)

slide22

QALE====

(Quality-adjusted life expectancy)

Kernel smoothing, 用cross-sectional方式收集QOL資料,以每個時間點之失能百分比, 取左右鄰近10%,估計其平均值逐步移動

Hwang et al. Stat Med 1996;15:93-102

conceptual developments
Conceptual developments
  • Lifetime survival function from a cohort
  • Plus a second function:

* Quality of life (utility or psychometry)

*Healthcare expenditures

*Salaries (human capital cost)

*Proportions of functional disabilities

*Durations of hospitalization, No. clinic visits

slide24

Validation of method: 7 yrs to predict up to 15 yrs(Chu PC et al. Value in Health 2008; 7:1102-1109)

illustrative examples
ILLUSTRATIVE EXAMPLES:
  • How much utility of health (in QALY) does it cost for a case of liver cancer?

survival curve

quality of life (standard gamble, EQ-5D, etc.)

  • Cancer registry + vital statistics

patients with liver cancer

general population

(Lee et al. Sci Total Environ 2010;408:1271-1275)

slide27

Estimating the quality-adjusted life

expectancy of liver cancer in QALY

quality of life

survival curve

3.1 QALY

quality-adjusted survival

slide28

Comparison of prevention and treatments

Health benefit gained from prevention

17.5 QALY

Treatment(A-B)=

0.5QALY

slide29

Lifetime healthcare costs of lung cancer

Life time cost: US $22,359

(Lee et al Occup Environ Med 2012 doi:10.1136/oemed-2011-100462)

slide30

EXTENSION TO HEALTH PROFILE (SCORES of PATIENTS REPORTED OUTCOME)

Consequence of the event can be replaced by patient report outcome STATES measured by psychometrics

(Hwang JS, Wang JD. Quality of Life Research 2004; 13:1-10)

estimations
Estimations
  • The estimate of expected psychometric score-adjusted survival (PAS) for an index population,
  • is obtained by firstly estimatingand at chosen time points ’s

The estimate of expected psychometric score-adjusted survival (PAS) for an index population,

is obtained by firstly estimatingand at chosen time points ’s

slide32

Comparison of life time psychometric

scores for BMT and chemotherapy (EORTC cancer specific instrument)

(Hsu et al. Qual Life Res 2003;12:503-517)

extension to proportions of functional states determination of needs for long term care

Extension to proportions of functional states: Determination of needs for long term care

estimation of needs of long term care for patients with ischemic stroke under view
Estimation of needs of long term care for patients with ischemic stroke (under view)
  • On average, how long does a stroke patient require a full time caregiver?
  • How many months is he/she disability-free?
  • How many months is he/she partially disabled, and requires partial assistance in daily activities?
slide35

……Survival probability

…… Proportion of no disability(巴氏量表)

……Health-adjusted survival curve

8.4 yrs

6.0 yrs of loss of life expectancy

3.5 yrs living with disability

Lifetime health-adjusted survival for stroke

expected impact
Expected impact:

LIKELIHOOD OF EVENT

(Incidence rate, risk, or probability from epidemiological studies)

X

CONSEQUENCE OF EVENT

(Utility gained or lost in QALY or score-time due to the event, plus cost data into cost/effectiveness)

cumulative incidence rate cir
Cumulative incidence rate(累積發生率,CIR)
  • CIR1(發生密度法)
  • CIR2(生命表法)
  • 當累積時間段(例如20至79歲)之期間相同即可以直接比較,而不僅限於個人風險。
  • 累積發生率的意涵:於特定期間中,該個體未因其他原因死亡,則得該病的機率。
slide41

計算男性20到49歲嚼檳榔得口腔癌的累積發生率計算男性20到49歲嚼檳榔得口腔癌的累積發生率

先分別計算20-29、30-39、40-49歲嚼食檳榔的口腔癌發生率。

假設未嚼檳榔者的發生率是R0,依據文獻,嚼檳榔者的發生率為58.4倍的R0。20-29歲檳榔嚼食盛行率為11.4%、口腔癌發生率為0.001%。求R0=?

20-29歲 58.4 R0*0.114+R0 (1-0.114)=0.0000142

R0(未嚼檳榔口腔癌發生率)=0.0000019

嚼檳榔口腔癌發生率= 0.0000019*58.5

嚼檳榔盛行率

slide42

20-49歲男性嚼檳榔得口腔癌的累積發生率(CIR20-49):20-49歲男性嚼檳榔得口腔癌的累積發生率(CIR20-49):

1- EXP(-(0.00011*10+0.001006*10+

0.002713*10 )=0.037559

20~29 CIR

30~39 CIR

40~49 CIR

如果沒有死於其他疾病,則從20歲嚼檳榔到49歲之男性,得口腔癌的機率有3.76%,如果20到49歲期間都不嚼檳榔,則得口腔癌的機率為0.066%

directions and markets
Directions and markets
  • 目前已有的醫療資訊學之紅海市場
    • 醫療上有用之資料的即時存取與3D建構
    • 有效提升目前醫療運作機制(開檢驗或藥與報帳)
    • 從microarray資料分析新疾病與基因型的關聯
    • 藉由手機的感應資料做疾病的預防 ………..etc.
  • 藍海市場在哪裏?
  • 醫療照護決策:先使用現有資料作發生率、存活函數(預期壽命) 、得病後損失之壽命、終身費用之分析。長期插管呼吸治療病人意識變化。(作成Apps)
  • 讓病人参與決策提昇他本身之生活品質,WHOQOL世界衛生組織生活品質問卷,EQ-5D歐盟五層面問卷,各病發展其問卷與功能評估模組﹔病人直接網路輸入。照護者當面直接廻饋,再把眾多重覆測量資料利用mixed effects model廻歸分析,立即提供照護者與病人商量改善生活品質
roadmap for computer science
Roadmapfor Computer Science
  • 資料電子化 (才能進一步處理)
    • 無論是圖檔或是文字檔
  • 資料格式結構化 (才能快速處理)
    • 統一資料存取模式 (不一定是模式)
  • 資訊技術模組化 (方便利用)
    • 各項指標規律回報(各種趨勢的掌握,及健康政策的實施指標)
  • 各疾病輔助決策機制:一病一模組又可互通共享
    • 與各疾病發生率及療效相結合,引導決策往病人所需要的方向:降發生率(少生傷病)、活得長壽、生活品質又好(功能障礙少)
f or information engineering
For Information engineering
  • Data
    • 可以取得目前所有診療記錄、及各生理量測資料、生活品質並與國家高品質資料庫相聯(如死因資料) ,以計算其存活壽命
  • Process
    • No problem for CS researchers!
  • Output
    • What is the purpose of research?
    • Collaboration of health-related domain knowledge and information engineers

data

Process

output

extrapolation of survival function hwang wang 1999 fang et al 2007
Extrapolation of survival function(Hwang & Wang 1999, Fang et al. 2007)
  • Most available cohorts were followed for a short period of time, or, 5-10 years:

High censored rate (>50%)

  • No parametric method available
  • Development of semi-parametric method for extrapolation by borrowing information from vital statistics (or general population)
is constant excess hazard a plausible assumption
Is constant excess hazard a plausible assumption ?
  • The index population would die of other diseases in the same likelihood as the general population except for the index disease Xi
  • A constant excess proportion of index population would die prematurely because of the index disease Xi
  • Major causes of death: cancer, end stage renal disease, HIV/AIDS, head injuries, stroke, etc. would fulfill
slide52

Logit transformation of the survival ratio W(t) between the survival functions of HIV-positive patients and that of the age- and gender-matched reference population generated by the Monte Carlo method. The solid line is the linear regression line.

  • AIDS group.
  • non-AIDS
  • group.
estimation of long term care needs for patients under maintenance hemodialysis under view
Estimation of long-term care needs for patients under maintenance hemodialysis(under view)
slide56

男性

女性

incidence rate with difference risk factors
Incidence Rate With Difference Risk Factors

Tsai et al., Am J Epidemiology 1996, 142, p974-981

  • No helmet:10.1*10-4
  • Half-face helmet:7.37*10-4
  • Full-face helmet:3.13*10-4
slide59

Likelihood of occurrence of a

hazardous event or exposure

Consequence that can be caused by the event or exposures

consequences under various situations
Consequences under various situations

Lee et al. Am J Public Health2010;100:165-170

Helmet

No Helmet 9.1 years 10.7 QALY

With Helmet 4.3 years 5.8 QALY

Loss of quality-adjusted life expectancy (QALE)

Loss of life expectancy

the risk
The Risk

Following our example of a 45 years old male who will

ride motorcycle to 69 years without helmet:

Severity of Head

Injury without Helmet

Loss of 9.1 person-years or 10.7 QALY

Incidence of Head

Injury during the

Period:0.025

The estimated loss for the person:

0.2275 Person-Years and 0.2675 QALY