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Informatics for Health Policy and Systems Research:! 
Lessons Learned from a Study of Healthcare Financing! 
Cross-subsidi...
Special 
thanks 
to: 
Ø Pha1a 
Kirdruang, 
Ph.D. 
Ø Thaworn 
Sakulpanich, 
M.D. 
Ø Patchanee 
Thamwanna 
Ø Utoomporn 
...
PresentaAon 
Outline 
1. Introducing 
Health 
Policy 
& 
Systems 
Research 
(HPSR) 
– Purposes 
of 
HPSR 
– Overview 
of 
...
“What 
exactly 
is 
HPSR?” 
Pix source: online.wsj.com
New 
Health 
Research 
Mapping? 
Source: Hoffman et al. (2012).
New 
Health 
Research 
Mapping? 
Different 
kinds 
of 
knowledge 
needed 
Source: Hoffman et al. (2012).
“The 
Systems” 
• The WHO Six Building Blocks” of health (services) systems 
Source: WHO )2012); de Savigny & Adam (2009);...
Different 
Levels 
of 
Health 
Systems 
Source: Gilson, editor (2012). Health Policy and Systems Research: A Methodology R...
Health 
Systems 
& 
Health 
Policy 
• Terrain of Health Policy and Systems Research 
Source: Gilson, editor (2012). Health...
What 
Is 
& 
What 
Is 
Not 
HPSR? 
Research “on” health systems 
VS. 
Research “for” Health systems 
Source: Gilson, edito...
Research 
Strategies 
in 
HPSR 
Source: Gilson, editor (2012). Health Policy and Systems Research: A Methodology Reader.
Research 
Strategies 
in 
HPSR 
Source: Gilson, editor (2012). Health Policy and Systems Research: A Methodology Reader.
Example 
of 
HPSR: 
Study 
of 
Healthcare 
Cross-­‐subsidizaAon 
in 
Thai 
Public 
Hospitals 
Pix source: online.wsj.com
Financing 
of 
Thai 
Healthcare 
System 
CSMBS SSS UCS Motor Vehicle 
Victim 
Protection 
Law 
Private Health 
Insurance 
...
Financing 
of 
Thai 
Healthcare 
Systems 
CGD 
(CSMBS), 
NHSO 
(UCS) 
Taxes Payers 
Employer-based 
private health 
insura...
of the out-patient expenditure during the second period showed an upward trend and 
had very rapid growth in the last two ...
Study 
RaAonale 
Ø “Do 
hospitals 
use 
payments 
of 
a 
type 
of 
health 
services 
to 
subsidize/support 
financing 
of...
Literature 
Review 
Ø Concepts 
of 
“cross-­‐subsidiza?on” 
or 
“cost-­‐shi^ing” 
from 
developed 
countries 
such 
as 
t...
Study 
ObjecAves 
1. To 
explore 
mo?va?ons 
and 
exis?ng 
prac?ces 
of 
the 
administrators 
of 
Thai 
public 
hospitals ...
Methodology: 
Research 
Design 
Ø No 
empirical 
study 
of 
cross-­‐subsidiza?on 
in 
the 
contexts 
of 
Thai 
healthcare...
Methodology: 
“Mixed 
Methods” 
Ø Mixed-­‐methods 
research 
with 
concurrent 
embedded 
design, 
which 
quan?ta?ve 
data...
Methodology: 
Source 
of 
Data 
Ø Data 
was 
based 
on 
three 
selected 
public 
hospitals: 
Ø Two 
medical 
centers 
wi...
Methodology: 
Data 
Ø QualitaAve 
data: 
Ø Semi-­‐structure 
interviews 
and 
focus-­‐group 
interviews. 
Ø 30 
key 
in...
Research 
Findings 
Pix source: online.wsj.com
QualitaAve 
Analysis 
Ø Construc?vist 
grounded 
theory 
(Chamaz, 
2005; 
2006) 
Ø Coding 
process 
(Strauss 
& 
Corbin ...
QualitaAve 
Findings 
Ø 13 
sub-­‐themes, 
categorized 
into 
4 
emerging 
themes. 
26 
Sub-­‐themes 
Themes 
Varied 
und...
QuanAtaAve 
Analysis 
Ø Analyze 
the 
cost 
differences 
across 
health 
schemes 
Ø By 
using 
descrip?ve 
sta?s?cs 
and...
QuanAtaAve 
Findings 
#1: 
Cost 
Differences 
across 
Health 
Schemes 
“Total 
Cost 
Across 
Health 
Schemes” 
0 10,000 20...
QuanAtaAve 
Findings 
#2: 
“Profit” 
or 
“Loss” 
across 
Health 
Schemes 
“Total 
Charge, 
Total 
Cost, 
and 
Reimbursemen...
QuanAtaAve 
Findings 
#2: 
“Profit” 
or 
“Loss” 
across 
Health 
Schemes 
“Charge-­‐Cost’ 
vs. 
‘Reimbursement-­‐Cost” 
-2...
QuanAtaAve 
Findings 
#2: 
“Profit” 
or 
“Loss” 
across 
Health 
Schemes 
“Difference 
between 
Reimbursement 
and 
Cost” ...
QuanAtaAve 
Findings 
#2: 
“Profit” 
or 
“Loss” 
across 
Health 
Schemes 
“Difference 
between 
Reimbursement 
and 
Cost” ...
QuanAtaAve 
Findings 
#2: 
“Profit” 
or 
“Loss” 
across 
Health 
Schemes 
“Difference 
between 
Reimbursement 
and 
Cost” ...
QuanAtaAve 
Findings 
#3: 
Evidence 
for 
Cross-­‐SubsidizaAon? 
RelaAonship 
between 
‘Charge-­‐Cost’ 
for 
OOP 
and 
‘Re...
QuanAtaAve 
Findings 
#4: 
LimitaAons 
of 
Available 
Data 
Reimbursement-­‐to-­‐Cost 
RaAo 
0 50 100 150 200 
mean of rei...
QuanAtaAve 
Findings 
#4: 
LimitaAons 
of 
Available 
Data 
Reimbursement-­‐to-­‐Cost 
RaAo 
aeer 
DeleAng 
Outliers 
0 5 ...
• No 
Summary 
of 
Findings 
direct 
evidence 
suggests 
that 
hospitals 
cost-­‐shi^ 
by 
increasing 
prices 
charged 
to...
Mental 
Models 
of 
Hospital 
Administrators 
38
ImplicaAons 
for 
Policy 
and 
PracAce 
Ø To 
policymakers: 
• Demonstrates 
an 
empirical 
evidence 
of 
that 
current 
...
InformaAon 
Systems 
for 
DeterminaAon: 
The 
Case 
of 
Policies 
for 
Healthcare 
Financing 
Pix source: online.wsj.com
Lessons 
Learned 
① HPSR 
is 
an 
emerging 
mul?disciplinary 
field 
of 
study 
that 
aims 
to 
help 
decision-­‐making 
o...
Lessons 
Learned 
② HPSR 
methodology 
depends 
on 
research 
ques?ons. 
– Some 
HPSR 
use 
primary 
data 
collec?on. 
– S...
③ Data 
needed 
for 
future 
research 
on 
healthcare 
financing: 
Ø Micro-­‐data 
(e.g. 
data 
at 
DRG 
level) 
are 
not...
Bibliography 
1. สุพล ลิมวัฒนานท์ และคณะ. (2555) รายงานผลการพัฒนาระบบการจัดเก็บข้อมูลด้านยาเพื่อติดตามประเมินการสั่งใช้ยาแ...
Bibliography 
18. Khiaocharoen, O, Pannarunothai, P., Chairoj Zungsontiporn, A. (2011). Patient-Level Cost for Thai Diagno...
Q 
& 
A 
borwornsom.lee@mahidol.ac.th 
Pix source: online.wsj.com
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Informatics for Health Policy and Systems Research: Lessons Learned from a Study of Healthcare Financing Cross-subsidization in Thai Public Hospitals

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A panel discussion on health information systems at presenting the related issues between health informatics and health systems research.

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Informatics for Health Policy and Systems Research: Lessons Learned from a Study of Healthcare Financing Cross-subsidization in Thai Public Hospitals

  1. 1. Informatics for Health Policy and Systems Research:! Lessons Learned from a Study of Healthcare Financing! Cross-subsidization in Thai Public Hospitals Borwornsom Leerapan, MD PhD! ! JITMM2014 & FBPZ8! Bangkok, Thailand! December 2, 2014 Pix source: workwithbrianandfelicia.com
  2. 2. Special thanks to: Ø Pha1a Kirdruang, Ph.D. Ø Thaworn Sakulpanich, M.D. Ø Patchanee Thamwanna Ø Utoomporn Wongsin Ø NutniAma Changprajuck Ø Health Insurance System Research Office (HISRO) & Health System Research InsAtute (HSRI) 2
  3. 3. PresentaAon Outline 1. Introducing Health Policy & Systems Research (HPSR) – Purposes of HPSR – Overview of HPSR methodology & Data for HPSR 2. Example: Study of Cross-­‐subsidizaAon of Health Services in Thai Public Hospitals – Study objec?ves, methods, results 3. Discussion: InformaAon Systems for “DeterminaAon” – Implica?ons for policy and prac?ces – Informa?cs needed for future HPSR 3
  4. 4. “What exactly is HPSR?” Pix source: online.wsj.com
  5. 5. New Health Research Mapping? Source: Hoffman et al. (2012).
  6. 6. New Health Research Mapping? Different kinds of knowledge needed Source: Hoffman et al. (2012).
  7. 7. “The Systems” • The WHO Six Building Blocks” of health (services) systems Source: WHO )2012); de Savigny & Adam (2009); Scheerens and Bosker (1997); Pix source: humanrevod.wordpress.com
  8. 8. Different Levels of Health Systems Source: Gilson, editor (2012). Health Policy and Systems Research: A Methodology Reader.
  9. 9. Health Systems & Health Policy • Terrain of Health Policy and Systems Research Source: Gilson, editor (2012). Health Policy and Systems Research: A Methodology Reader.
  10. 10. What Is & What Is Not HPSR? Research “on” health systems VS. Research “for” Health systems Source: Gilson, editor (2012). Health Policy and Systems Research: A Methodology Reader.
  11. 11. Research Strategies in HPSR Source: Gilson, editor (2012). Health Policy and Systems Research: A Methodology Reader.
  12. 12. Research Strategies in HPSR Source: Gilson, editor (2012). Health Policy and Systems Research: A Methodology Reader.
  13. 13. Example of HPSR: Study of Healthcare Cross-­‐subsidizaAon in Thai Public Hospitals Pix source: online.wsj.com
  14. 14. Financing of Thai Healthcare System CSMBS SSS UCS Motor Vehicle Victim Protection Law Private Health Insurance Feature State/Employer welfare Compulsory heath insurance with state subsidies State welfare Compulsory heath insurance for vehicle owners Voluntary health insurance Targeted groups of beneficiaries Civil servants, state enterprise employees and dependents Employees in private sector and temporary employees in public sector Thai citizens without the coverage of CSMBS & SSS Victims of vehicle accidents General public Source of financing Govt. budget Tri-party (Employee, employer and govt. budget) Govt. budget Vehicle owners Household Method of payment to health facilities Fee-for-service Capitation and Fee-for-service Capitation and Fee-for-service Fee-for-service Fee-for-service Major problems Rapidly and constantly rising costs Covering while being employed only Inadequate budget Redundant eligibility and slow disbursement Redundant eligibility and slow disbursement Source: Adapted from Wibulpolprasert et al. (2011). Thailand Health Profile 2008-2010.
  15. 15. Financing of Thai Healthcare Systems CGD (CSMBS), NHSO (UCS) Taxes Payers Employer-based private health insurance Individual & Employer’s private health insurance (Voluntary) Hospitals Medical Specialists Generalists & PCPs Social Security Office (SSS) Patients paying out-of-pocket Ambulatory Facilities Payment Mechanisms: Salary, Fee-for-Service, Global Budget, Capitation, DRGs, etc. Providers in Public & Private Sector Commercial Insurance Companies Motor vehicle’s owners (Mandatory by the Motor Vehicle Victim Protection Law)
  16. 16. of the out-patient expenditure during the second period showed an upward trend and had very rapid growth in the last two years, 2006 and 2007 (graph 2.5). With respect to expenditure per patient, this study can merely consider the average in-patient Study RaAonale expenditure, because of data limitations. According to data from the electronic payment system, the average in-patient expenditure in 2003-2006 increased over time as shown in graph 2.6. CSMBS Expenditure in the fiscal years 1996-2007 13,587 15,502 16,440 15,253 17,058 19,181 20,476 22,686 8,761 9,877 10,574 9,048 10,050 11,058 10,967 4,826 5,625 5,866 6,206 7,007 8,123 50,000 45,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Million Baht Figure source: Benjaporn (2007) 46,481 15,649 14 Graph 2.4: CSMBS expenditure during the fiscal years 1996-2007 9,509 26,043 11,350 13,905 37,004 29,380 16,943 21,896 30,833 11,335 12,138 12,437 15,109 Year Out-patient In-patient Total Source: The Comptroller General’s Department and the Government Fiscal Management Information System (GFMIS) Note: 1 Euro = 49.4450 Baht, as of January 8, 2008 Ø Common assump?ons of what causes increasing healthcare expenditures: • Overuse of NED drug? • Overuse of brand-­‐named drugs? • Limited EBM prac?ces? • Corrup?on in healthcare sector? Ø Cross-­‐subsidiza,on can be a missing piece! 16
  17. 17. Study RaAonale Ø “Do hospitals use payments of a type of health services to subsidize/support financing of other services?” • If so, how?, at which level?, at what degree? Figure source: www.be2hand.com; www.imdb.com 17
  18. 18. Literature Review Ø Concepts of “cross-­‐subsidiza?on” or “cost-­‐shi^ing” from developed countries such as the U.S. (Morrisey 1994, Cutler 1998, Dranove 1988, Feldman et al. 1998, Frakt 2010 & 2011). Ø Such theorec?cal concepts might not be applicable in Thailand’s healthcare systems, especially that Thai public hospitals do not have the ability to set prices by themselves. Ø There was no empirical study of cross-­‐subsidiza?on in the contexts of Thai healthcare systems. 18
  19. 19. Study ObjecAves 1. To explore mo?va?ons and exis?ng prac?ces of the administrators of Thai public hospitals that poten?ally can lead to cross-­‐subsidiza?on (“to use payments of a type of health services to support financing of other services”). 2. To develop mental models of the administrators of Thai public hospitals regarding organiza?onal responses to healthcare financing policies. 3. To demonstrate an empirical evidence related to cross-­‐ subsidiza?on at the hospital level, including the cost difference and the difference of excess of revenues over expenses among health schemes. 19
  20. 20. Methodology: Research Design Ø No empirical study of cross-­‐subsidiza?on in the contexts of Thai healthcare system. Ø Concepts from developed countries such as the U.S. might not be applicable in Thailand. Ø Mixed-­‐methods research, with the concurrent embedded research design (Creswell et al., 2004). Ø Qualita,ve study: the mental models. Ø Quan,ta,ve study: an empirical evidence related to cross-­‐subsidiza,on at the hospital level. 20
  21. 21. Methodology: “Mixed Methods” Ø Mixed-­‐methods research with concurrent embedded design, which quan?ta?ve data analysis is used to compliment as the qualita?ve data analysis. Source: Creswell (2009). Research design: Qualitative, quantitative, and mixed methods approaches. 3rrd ed. 21
  22. 22. Methodology: Source of Data Ø Data was based on three selected public hospitals: Ø Two medical centers with 1,000 and 1,134 beds Ø One teaching hospital with 1,378 beds. Ø Hospitals were purposefully selected, based on the accessibility to the hospital administrators and the availability of the datasets of unit cost, claims, and reimbursement. 22
  23. 23. Methodology: Data Ø QualitaAve data: Ø Semi-­‐structure interviews and focus-­‐group interviews. Ø 30 key informants who are responsible for the administra?on of the three hospitals. Ø Verba?m was transcribed and analyzed using ATLAS.? 7. Ø QuanAtaAve data: Ø Secondary data of inpa?ent care, collected at the pa?ent level, from the two medical centers. Ø Unit-­‐cost, charge, reimbursement, pa?ent’s health scheme, DRG codes, and basic demographic characteris?cs. Ø Analysis was conducted using Stata 12. 23
  24. 24. Research Findings Pix source: online.wsj.com
  25. 25. QualitaAve Analysis Ø Construc?vist grounded theory (Chamaz, 2005; 2006) Ø Coding process (Strauss & Corbin 1990) 25
  26. 26. QualitaAve Findings Ø 13 sub-­‐themes, categorized into 4 emerging themes. 26 Sub-­‐themes Themes Varied understanding of cross-­‐subsidiza?on, Unclear financing for non-­‐healthcare missions Different understanding of ajtudes towards cross-­‐subsidiza?on concepts Inadequate reimbursement, Non-­‐performing loan, Unequal nego?a?on power Obstacles facing management due to policies of the payers Conflic?ng roles between quality & equity-­‐ focus and efficiency-­‐focus, Limited informa?on to manage prices and cost Obstacles facing management due to organiza?onal limita?ons To be missions-­‐driven organiza?on, To focus more on efficiency than revenues, To do public funds raising, To control the volume of certain groups of pa?ents when feasible, To advocate changes of the payer’s policies Organiza?onal responses to policies of the payers
  27. 27. QuanAtaAve Analysis Ø Analyze the cost differences across health schemes Ø By using descrip?ve sta?s?cs and a regression analysis. Ø Compare the differences among charge, cost, reimbursement, par?cularly ‘reimbursement-­‐cost’ and ‘reimbursement-­‐to-­‐cost ra?o’: Ø Across health schemes Ø Across MDC groups Ø Across Age groups Ø Inves?gate possibili?es for cross-­‐subsidiza?on Ø By examining the rela?onship between (charge-­‐cost)OOP and (reimbursement-­‐cost)UC. 27
  28. 28. QuanAtaAve Findings #1: Cost Differences across Health Schemes “Total Cost Across Health Schemes” 0 10,000 20,000 30,000 mean of totalcost CSMBS SSS UC Cash Source: Center hospital #1 Ø The average costs per visit vary across health schemes, where CSMBS pa?ents have the highest cost. Ø A^er controlling for age, gender, disease, LOS, the regression analysis confirms that the pa?ent’s health scheme has a significant impact on the unit cost of health services. 28
  29. 29. QuanAtaAve Findings #2: “Profit” or “Loss” across Health Schemes “Total Charge, Total Cost, and Reimbursement” (by Health Scheme) 0 10,000 20,000 30,000 40,000 CSMBS SSS UC Cash mean of totalcharge mean of totalcost mean of reimbursement Source: Center hospital #1 Ø CSMBS pa?ents are the only group whose reimbursement is greater than cost, while reimbursement is lower than costs for UC pa?ents. Ø Total charge is set to be greater than the cost for all health schemes. 29
  30. 30. QuanAtaAve Findings #2: “Profit” or “Loss” across Health Schemes “Charge-­‐Cost’ vs. ‘Reimbursement-­‐Cost” -2,000 0 2,000 4,000 6,000 8,000 CSMBS SSS UC Cash mean of charge_cost_diff mean of reimb_cost_diff Source: Center hospital #1 Ø ‘Reimbursement-­‐Cost’ is the highest for CSMBS, but is nega?ve for other groups. Ø ‘Charge-­‐Cost’ are posi?ve for all groups, but is very small for OOP pa?ents. Ø OOP pa?ents may not be the ‘profitable’ group as suspected. 30
  31. 31. QuanAtaAve Findings #2: “Profit” or “Loss” across Health Schemes “Difference between Reimbursement and Cost” (by Health Scheme) -10,000 -5,000 0 5,000 mean of reimb_cost_diff csmbs sss uc foreign cash Others Source: Center hospital #2 Ø Assume that charge equals reimbursement for foreign, OOP, and ‘others’ groups. Ø Reimbursement (or charge) is much lower than the cost for UC and foreign pa?ents. Ø Insufficient reimbursement Ø Hospital’s burden to take care of pa?ents without health rights (e.g. foreign pts) 31
  32. 32. QuanAtaAve Findings #2: “Profit” or “Loss” across Health Schemes “Difference between Reimbursement and Cost” (by DRG-­‐MDC) 0 10,000 -30,000 -20,000 -10,000 mean of reimb_cost_diff 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 28 Source: Center hospital #1 Ø The hospital receives reimbursement more than the cost for only 5 MDC groups. Ø Some major diagnos?c categories create a large deficit for the hospital. 32 MDC 5 = Diseases & disorders of the circulatory system MDC 22 = Burns
  33. 33. QuanAtaAve Findings #2: “Profit” or “Loss” across Health Schemes “Difference between Reimbursement and Cost” (by Health Scheme and Age group) -5,000 0 5,000 10,000 <20 21-30 31-40 41-50 51-60 61-70 71+ mean of reimb_cost_diff_CS mean of reimb_cost_diff_SS mean of reimb_cost_diff_UC mean of reimb_cost_diff_cash Source: Center hospital #1 Ø ‘Reimbursement-­‐Cost’ is generally posi?ve for CSMBS, and the difference is large for elder pa?ents. Ø This difference is nega?ves for almost all age groups for UC pa?ents. 33
  34. 34. QuanAtaAve Findings #3: Evidence for Cross-­‐SubsidizaAon? RelaAonship between ‘Charge-­‐Cost’ for OOP and ‘Reimbursement-­‐Cost’ for UCS -50000 0 50000 100000 150000 200000 (mean) charge_cost_diff_cash -300000 -200000 -100000 0 100000 200000 (mean) reimb_cost_diff_UC Source: Center hospital #1 Ø If there is cost-­‐shi^ing between UC and OOP pa?ents, we expect to see a nega?ve rela?onship between: (reimbursement-­‐cost)UC and (charge-­‐cost)OOP. Ø No 34 clear evidence of ‘ac?ve’ cross-­‐subsidiza?on.
  35. 35. QuanAtaAve Findings #4: LimitaAons of Available Data Reimbursement-­‐to-­‐Cost RaAo 0 50 100 150 200 mean of reimb_cost_ratio csmbs sss uc foreign cash Others Source: Center hospital #2 Ø The reimbursement-­‐ to-­‐cost ra?o is extremely high for CSMBS, possibly because of the outliers. Ø 26 observa?ons have reimbursement-­‐to-­‐cost ra?o greater than 2000!! 35
  36. 36. QuanAtaAve Findings #4: LimitaAons of Available Data Reimbursement-­‐to-­‐Cost RaAo aeer DeleAng Outliers 0 5 10 15 20 mean of reimb_cost_ratio csmbs sss uc foreign cash Others Source: Center hospital #2 Ø A^er dele?ng the outliers, the reimbursement-­‐to-­‐cost ra?os are s?ll rela?vely high for CSMBS and SSS. Ø This could be due to missing informa?on in terms of recording the cost data. 36
  37. 37. • No Summary of Findings direct evidence suggests that hospitals cost-­‐shi^ by increasing prices charged to out-­‐of-­‐pocket payment pa?ents to compensate for the loss. • Yet, three parerns of decision-­‐making of hospital administrators related to cross-­‐subsidiza?on were found. • Therefore, financing policies of health schemes also impact other pa?ents groups within the hospitals.
  38. 38. Mental Models of Hospital Administrators 38
  39. 39. ImplicaAons for Policy and PracAce Ø To policymakers: • Demonstrates an empirical evidence of that current healthcare financing of hospitals s?ll inappropriate/inadequate. • Suggests that payments from par?cular payers could be used as a “buffer” for hospitals, poten?ally leading to “passive cross-­‐subsidiza?on” and inequity issues of healthcare access. • Suggests how to “harmonize” health funds in a more efficient and equitable fashion. 39
  40. 40. InformaAon Systems for DeterminaAon: The Case of Policies for Healthcare Financing Pix source: online.wsj.com
  41. 41. Lessons Learned ① HPSR is an emerging mul?disciplinary field of study that aims to help decision-­‐making of health policymakers and healthcare administrators. – HPSR is a study “for” health system development. – HPSR is not a study “on” health systems or specific health interven?onal programs. – HPSR usually requires different kinds of data than typical clinical/epidemiological/cost-­‐effec?veness studies.
  42. 42. Lessons Learned ② HPSR methodology depends on research ques?ons. – Some HPSR use primary data collec?on. – Some HPSR use secondary data collec?on. – Some HPSR do require a u?liza?on of administra?ve data of healthcare organiza?ons. (e.g. study for strengthening healthcare financing policy).
  43. 43. ③ Data needed for future research on healthcare financing: Ø Micro-­‐data (e.g. data at DRG level) are not suitable in determining cross-­‐subsidiza?on across health schemes. • Varia?on across pa?ents within the same DRG. • Hospitals unlikely make financial decisions at the micro-­‐level. • Aggregate data at the hospital level are more suitable to study cross-­‐ subsidiza?on. Ø Results are highly sensi?ve to the data accuracy. Ø Data from different sources (e.g. reimbursement and cost) may be inconsistent, and could result in misleading results. Ø Cross-­‐sec?onal data used in this study limits the ability to inves?gate the dynamic of changes in reimbursement and cost over ?me. 43 Lessons Learned #3
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