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Cirm akhil behl_rashtriya_swasthya_bima_yojana_handout

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Cirm akhil behl_rashtriya_swasthya_bima_yojana_handout

  1. 1. Rashtriya Swasthya Bima Yojana Delivering healthcare through Public Private Partnership Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research October 29, 2010 October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  2. 2. Private Public Partnership Model Private Public Partnership Model Healthcare expenditure insured as a risk The insurance market bears the risk Transfer Payments by the government to cover the risk premium For low-income households Market provision; government regulation October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  3. 3. Federal Ownership Framework Federal Ownership - Framework Shared nancing - 25% + 75% Shared origination Shared administration October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  4. 4. Federal Ownership Costs Federal Ownership - Costs Poor states Political will at the State level Lack of technical infrastructure Extra costs of standardization October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  5. 5. Federal Ownership Benets Federal Ownership - Benets Ownership creates initiative Improved administration; closer to home More innovation October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  6. 6. The Business Model: Aligning Interests for Welfare Business Model Government - supply failure, management, competition Insurers - New markets, risk pool, distribution cost Healthcare providers and Intermediaries - more markets October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  7. 7. Suited to the Beneciary Suited to the Beneciary Choice - Public or private healthcare Cashless and paperless for the poor and illiterate Portable across states for the migrating population October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  8. 8. Suited to the Beneciary Using Technology to Scale Automation Digitization Standardization without vendor lock-in Smart Card Real time monitoring October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  9. 9. A rst look at the data - Trends and Hypothesis Conversion Ratio Trends National Average: 44.0% Delhi, Jharkhand and Maharashtra are the worst performers. Haryana, Chandigarh, Nagaland and HP - best States with bad districts - Maharashtra, Punjab, UP, Kerala, Jhark- hand Insurer not correlated with the bad performance of the districts October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  10. 10. A rst look at the data - Trends and Hypothesis Conversion Ratio Hypotheses Low demand of (Govt?) insurance Limited marketing education Ineciency of TPAs October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  11. 11. A rst look at the data - Trends and Hypothesis Incidence Ratio Trends National Average: 1.77% 8 of 15 states show abnormally high/low incidence ratios High IR districts frequently in Gujarat, Kerala Low IR districts frequently in Maharashtra, Punjab, UP Exceptional uctuations at the district level October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  12. 12. A rst look at the data - Trends and Hypothesis Incidence Ratio Trends (2) Observations Delhi Kerala: High incidence even with low conversion HP: Low incidence with high conversion Exceptional uctuations in IR October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  13. 13. A rst look at the data - Trends and Hypothesis Incidence Ratio Hypotheses Questions Observed IR = Natural IR? Accumulated historical risk? Endemic risk? Evolution of health-seeking behavior over time? Fraud? October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  14. 14. A rst look at the data - Trends and Hypothesis Incidence Ratio Curious case of Goa Near zero incidence ratio for Goa. Zero incidence for South Goa! Three empanelled hospitals in Goa. Zero empanelled hospitals in South Goa! Mandate a minimum density of empanelled hospitals? October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  15. 15. A rst look at the data - Trends and Hypothesis Incidence Ratio Fraud? Delhi High incidence ratio All private hospitals Abnormally high female hospitalization rates Fraud? E.g.: Fraudulent hysterectomies, Yashaswini. Bihar and Jharkhand? October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  16. 16. Conclusions Conclusions Assess de-centralization Grievance redressal? Low conversion ratio Highly uctuating incidence ratio Should government price? Quality control and fraud October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  17. 17. Thank You Visit us at http://www.ifmr.ac.in/cirm http://www.ifmr.ac.in/cirm/blog October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  18. 18. October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  19. 19. October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  20. 20. October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research
  21. 21. October 29, 2010 Akhil S. Behl akhil.behl@ifmr.ac.in CIRM, IFMR Research

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