Using U'lisa'on Data to Es'mate Future Demand of Health Care in Thailand Under The Na'onal Health Security Supasit Pannarunothai, MD, PhD Centre for Health Equity Monitoring Founda<on Phitsanulok, Thailand The Sriwijaya Interna<onal Conference of Public Health (SICPH) 5 October 2017 in Palembang, Indonesia
Scope Universal health coverage in Thailand U<lisa<on data sets Methods of forecast Demand for medical specialists Demand for medical subspecialists Demand for other health professionals Lessons learnt 2
Universal health coverage in Thailand Since 2001 Thailand has reached UHC The Na<onal Health Security Office was set up in 2002 to manage new scheme for 75% pop The Social Security Scheme enacted since 1990, now covering 16% pop (formal workers) The Civil Servant Medical Benefit Scheme as a decree of fringe benefit covering 9% pop Three schemes set their own e-claim systems Inpa<ent payment method by Diagnosis Related Group (DRG) provided good health system data. 3
U'lisa'on data sets Inpa'ent services Outpa'ent services 4
Table 5.3 Utilization of specialized hospital services within the UCS, 2005 2011 2005 2006 2007 2008 2009 2010 2011 Open-heart surgery 4064 4138 5102 5452 5582 6111 6299 Percutaneous transluminal coronary angioplasty (PTCA) Access to thrombolytic agent among STEMI patients (%) Renal replacement therapy 368 2232 3098 4170 4497 5626 7677 0.43 1.64 4.93 9.79 16.96 31.43 35.09 Antiretroviral therapy 74 841 106 798 Cataract 42 191 88 089 106 096 972 10 875 16 509 21 486 Haemophilia 483 718 889 927 1039 1171 Cleft lip & cleft palate 1226 1828 2692 2779 3731 3258 STEMI: ST elevated myocardial infarction. Source: NHSO (2011a). HIT Thailand 2015 5 137 082 116 382 120 824 143 064 124 845 161 319 122 064
Figure 5.2 Utilization rate of open-heart surgery of UCS members by province, 2004 2007 2004 2005 2006 2007 Less than 21.06 21.06-42.12 42.13 and more Source: Srithamrongsawat et al. (2008). HIT Thailand 2015 6
Figure 4: Health system developments, 1965 2005 1,400 1,300 1,200 1,100 1,000 900 800 700 600 500 400 300 200 100 0 Hospitals 1965 1970 1975 1980 1985 1990 1995 2000 2005 120,000 110,000 100,000 90,000 80,000 70,000 60,000 50,000 40,000 30,000 20,000 10,000 0 Doctors and nurses 1965 1970 1975 1980 1985 1990 1995 2000 2005 All District Other public Private Doctors Nurses 1,400 1,300 1,200 1,100 1,000 900 800 700 600 Population per bed 10,000 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 Population per doctor and nurse 500 400 1965 1970 1975 1980 1985 1990 1995 2000 2005 Patcharanarumol et al 2011 in HSRI 2012 1965 1970 1975 1980 1985 1990 1995 2000 2005 Doctor Nurse 7
Supply side in Indonesia & Thailand Indonesia Thailand Hospital beds/10,000 2.5 22 Physicians/100,000 13 37 Nurses/100,000 62 28 Midwives/100,000 20 1 USAID 2009 8
Demand and gap in Indonesia Table 5-2: Current Capacity and Future Demand in I Service Current Demand in ca~acb 2020 (2m5) Hospital beds W~th prevalence rate change - - 52 W~thout prevalence rat 64,100 change Physicians 27,191 World Bank 2009 9
Figure 17: Magnitude of population ageing, Thailand and Southeast Asia Sources: Institute for Population and Social Research, Mahidol University, Population Projections for Thailand, 2005 2025, 2006; and United Nations, Department of Economic and Social Affairs Division, World Population Ageing 1950 2050, Population Division, New York. 2002. 10 HSRI 2012
Methods of forecast Popula<on ra<o Health needs method Health demands method Service target method; adjusted service based Budget driven Workloads; work points Wai<ng list Professional group planning model Needs assessment model Segal et al 2008; Thanawut & Upakdee 2015 11
Demand for medical specialists Specialists Major Diagnostic Category/ Disease Cluster for workload calculation Ophthalmologist MDC02 (Disease and disorder of the Average time for surgical DCs in MDC02 eye) Otolaryngologist MDC03 (Disease and disorder of ear, Average time for surgical DCs in MDC03 nose and throat Orthopaedist MDC08 (Musculoskeletal system) Average time for surgical DCs in MDC08 Neurosurgeon MDC01 (Nervous system) Average time for surgical DCs in MDC01 OG MDC13 (Female reproductive Average time for surgical DCs in MDC13 and 14 system), MDC14 (Childbirth) Surgeon Surgical DRG except all above Average time for all other surgical DCs Anaesthesiologist Surgical cases of all above Half of average time for all surgical DCs Paediatrician Medical DRG except all above, age Average length of stay of DRG for ward round 0-18 Medical internist Medical DRG except all above, age >18 Average length of stay of DRG for ward round Phanthunane, Pannarunothai, Pakaiya 2017 12
Study framework Health needs -Treated pa<ents -Untreated pa<ents -Hospital types -Demographics Doctors in prac'ce -Working hours -Work loads -Work processes -Availability/ Produc<vity of clinical <me -Demographic profile -Geographic distribu<on Entry Cer<fica<on Exit Re<rement -Career choice -Migra<on
Demand for Internal Medicine 2009 and 2021 800 700 600 500 400 300 200 Female 2021 Male 2021 Female 2009 Male 2009 100 0 14 19 24 29 34 39 44 49 54 59 64 69 74 79 80+
Demand for surgeons in Thailand 2021 250 200 Persons 150 100 Male2009 Female2009 Mael2021 Females2021 50 0 4 9 14 19 24 29 34 39 44 49 54 59 64 69 74 79 80+ Age groups Phanthunane & Pannarunothai 2012
Demand for neurosurgeons Thailand 2021 70 60 50 Persons 40 30 20 10 Male2009 Female2009 Mael2021 Females2021 0 4 9 14 19 24 29 34 39 44 49 54 59 64 69 74 79 80+ Age groups Phanthunane & Pannarunothai 2012
Demand for 2021 and expected supply!12,000!!!10,000!!!8,000!!!6,000!!!4,000!! Year!2021! Expected!!2,000!!!"!!!! Ana! ENT! Eye! Med! OG! Ort! Pae! Sur! N!Sur!
Agreed conceptual framework Total Minutes of care Other MDCs of other subspecialists Medical & surgical DRGs (severe cases) Same lists of ICD-10/ICD-9-CM codes Es'mate demand for subspecialists ç ç ê MDC(s) of the Subspecialist Medical DRGs (severe cases) Lists of ICD-10/ ICD-9-CM codes ê ç ç Same MDC(s) of the Subspecialist but Surgical DRGs (severe cases) Same lists of ICD-10/ ICD-9-CM codes Pannarunothai et al 2016
Demand for medical subspecialists Table 1. Allocation of Major Diagnostic Category and disease and procedure codes to subspecialists Subspecialty MDC ICD-10 ICD-9-CM Neurology 01 501 5 Respiratory 04 233 36 Cardiology 05 273 86 Gastroenterology and Hepatology 06, 07 509 41 Rheumatology 08 620 18 Endocrinology 10 139 2 Nephrology 11 222 7 Hematology 16, 17 102 5 Infectious Disease 18, 25 246 19 Oncology Carcinoma as principal diagnosis 327 6 Leelarasamee, Intaragumtornchai, Pannarunothai et al 2017 19
Demand for medical subspecialists Table 3. Time (minutes) needed for subspecialist care and proportion of consultation as responded by the IM subspecialty Associations First visit (min) Subsequent visit (min) Inpatient Referral from peers in surgical subspecialists % of ICD-10 (A1) Neurologist 45 20 By each ICD-10 % of ICD-9-CM (B1) By each ICD-9-CM Cardiologist 30 10 15 By each ICD-9-CM Gastroenterologist and hepatologist Referral from other subspecialists % of ICD-10 (A2) By each ICD-10 % of ICD-9-CM (B2) By each ICD-9-CM 15 By each ICD-9-CM First visit (min) Outpatient Subsequent visit (min) 30 15 50 20 10 30 30 15 5 10 15 80 20 10 40 Endocrinologist 30 15 80 20 80 20 30 15 5 Nephrologist 20 10 10 10 15 10 15 10* 30 Oncologist 30 15 90 90 90 90 25 10 50 Rheumatologist 50 20 8 70 8 70 30 10 30 Hematologist 30 20 90 90 90 90 30 20 90 Pulmonologist 30 15 20 90 20 90 20 10 40 Infectious disease specialist 30 15 90 30 90 30 20 10 40 A1, A2, B1, B2 were the referral or consultation rates as described in Figure 1 * 10 minutes for peritoneal dialysis or hemodialysis case of subsequent visit Leelarasamee, Intaragumtornchai, Pannarunothai et al 2017 % of ICD-10 20
Number needed by assump'ons 1,000 800 500 600 400 400 300 Regional 200 - -200-400 -600-800 Neuro Cardio GI Endocrine Nephro Onco 200 Regional 100 Teaching Excess 0-100 Neuro Cardio GI Endocrin Nephro Onco Different assump<ons give different number of subspecialists needed Teaching Excess -1,000 When compared with the exis<ng number of subspecialists, the exis<ng number of oncologists was only 25 percent of the number needed; while the exis<ng number of cardiologists was 87 percent of the number needed. 21
Demand for den'sts specialists Specialty 2011 2031 Public Private Total Public Private Total General dentists 2,063 1,528 3,591 9,956 4,969 14,925 Oro-Maxillofacial 247 365 611 1,190 1,187 2,376 Oral surgeons 25 191 216 119 621 740 Endodontists 114 96 210 550 311 861 Periodontists 71 146 218 344 476 820 Paediatric dentists 77 37 114 373 121 494 Prosthodontists 357 410 767 1,724 1,332 3,056 Orthodontists 53 3,901 3,954 258 12,683 12,941 Total 3,008 6,673 9,681 14,514 21,700 36,213 Suwatmaykin, Phanthunane, Pannarunothai 2015 22
180,000 160,000 140,000 120,000 100,000 80,000 60,000 40,000 20,000 Demand for hospital pharmacists กรณ ท 1 กรณ ท 2 0 2015 2025 2035 พ.ศ. 2558 พ.ศ. 2568 พ.ศ. 2578 Scenario 1: Time based of all activities Upakdee et al 2015 Scenario 2: Time-based by level of service Scenario 3: P4P adjusted time based of all activities Scenario 4: P4P adjusted time cased by level of service
Discussion All assump<ons must be validated for befer es<ma<ons Not a projec<on % ac<ve subspecialists by age/sex Limita<on on private hospitals & others 24
Lessons learnt This evidence based health policy development with assump<ons for sustainable matching demand and supply of human resource for health was involved with ac<vi<es of pa<ent care All assump<ons must be validated for befer es<ma<ons Limita<on on data from private hospitals & others 25