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Reducing Resource Disparity in Healthcare Resource Allocation of Laboratories in Countries with Limited Resources by Empowering Policy-Making and Implementation


Affiliations
1 Centre for Technology Alternatives for Rural Areas
2 Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai 400 076, India
 

In resource constraint settings of developing countries like India, inadequate importance and consideration to resource (re)allocation approach causes resource disparity issues. The Indian public health care system has focused on developing rural primary health centres (PHCs) to reduce rural–urban resource disparity and pressure on urban health care facilities. However, all the resources as recommended in national standards for PHCs’ functioning are not completely available in PHCs. Local-level decision-makers are not provided with a policy framework to (re)allocate resources. This study states that empowering local-level decision makers with the ability to (re)allocate resources to reduce resource disparity is critical. The study proposes a new framework for minimizing resource disparity with resource allocation optimization. The study suggests a strategy to improve implementation of policies like the National Rural Health Mission and the National Health Policy. The 42 PHCs in rural areas of Osmanabad District (India) with 23 laboratory technicians (LTs) as resources are considered as a case study to assess the proposed method. The study optimization model showed that reallocating 6 of 23 LTs to different PHCs would reduce disparity in LT workload (from 57.62% to 30.54%) and LT access (from 116.4% to 49.3%). The disparity reduction highlights the impact of resource reallocation according to the proposed framework.

Keywords

Developing Nations, Healthcare, Optimization, Policy, Resource Disparity, Resource Allocation.
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  • Rao, M., Rao, K. D., Kumar, A. S., Chatterjee, M. and Sundara-raman, T., Human resources for health in India. Lancet, 2011, 377(9765), 587–598.

  • MoHFW, Rural health statistics, New Delhi, 2013.

  • MoUD, Urban and Regional Development Plans Formulation and Implementation (URDPFI) Guidelines 2015, New Delhi, 2015, vol. I.

  • MoHFW, National Rural Health Mission: Framework for Imple-mentation (2005–2012), Ministry of Health and Family Welfare, New Delhi, 2005.

  • Rahman, S. U. and Smith, D. K., Use of location-allocation models in health service development planning in developing nations. Eur. J. Oper. Res., 2000, 123, 437–452.

  • Romero-Conrado, A. R., Castro-Bolaño, L. J., Montoya-Torres, J. R. and Jiménez-Barros, M. Á., Operations research as a decision-making tool in the health sector: a state-of-the-art. DYNA, 2017, 84(201), 129–137.

  • Baltussen, R. and Niessen, L., Priority setting of health interven-tions: The need for multi-criteria decision analysis. Cost Eff. Resour. Alloc., 2006, 4, 1–9.

  • Planning Commission of India. Health and Family Welfare and AYUSH. In: Eleventh Five Year Plan (2007-2012): Social Sectors (Volume II) [Internet]. New Delhi: Oxford University Press, 2008, pp. 57–127; http://planningcommission.nic.in/plans/planrel/fiveyr/index9.html

  • Basu, R., Jana, A. and Bardhan, R., A health care facility allocation model for expanding cities in developing nations: strategizing urban health policy implementation. Appl. Spat. Anal. Policy, 2016, 9(1), 1–16.

  • Rao, K. S., Challenging times for public health towards attaining sustainable development goals. Indian J. Community Med., 2017, 42(2), 65–68.

  • World Health Organization, Alma-Ata Declaration, Geneva, 1978.

  • MoHFW. Indian Public Health Standards (IPHS) for Primary Health Centres Revised Guidelines 2012, New Delhi, 2012.

  • Forsman, R. W., Why is the laboratory an afterthought for managed care organizations? Clin. Chem., 1996, 42(5), 813–816.

  • Devane-Padalkar, A., Deshpande, S. and Yakkundi, D., Laboratory services at primary health centers under the lens: a need for over-haul. Int. J. Trop. Dis. Health, 2016, 13(4), 1–6.

  • Office of Registrar General and Census Commissioner. Census 2011: Population Enumeration Data [Internet]. Ministry of Home Affairs. 2011 [cited 2016 Jan 11]; http://www.censusindia.gov.in/2011census/population_enumeration.html

  • Walshe, K. and Rundall, T. G., Evidence-based management: from theory to practice in health care. Milbank Q., 2001, 79(3), 429–457.


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  • Reducing Resource Disparity in Healthcare Resource Allocation of Laboratories in Countries with Limited Resources by Empowering Policy-Making and Implementation

Abstract Views: 428  |  PDF Views: 131

Authors

Rahi Jain
Centre for Technology Alternatives for Rural Areas
Himank Ajmera
Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai 400 076, India
Bakul Rao
Centre for Technology Alternatives for Rural Areas

Abstract


In resource constraint settings of developing countries like India, inadequate importance and consideration to resource (re)allocation approach causes resource disparity issues. The Indian public health care system has focused on developing rural primary health centres (PHCs) to reduce rural–urban resource disparity and pressure on urban health care facilities. However, all the resources as recommended in national standards for PHCs’ functioning are not completely available in PHCs. Local-level decision-makers are not provided with a policy framework to (re)allocate resources. This study states that empowering local-level decision makers with the ability to (re)allocate resources to reduce resource disparity is critical. The study proposes a new framework for minimizing resource disparity with resource allocation optimization. The study suggests a strategy to improve implementation of policies like the National Rural Health Mission and the National Health Policy. The 42 PHCs in rural areas of Osmanabad District (India) with 23 laboratory technicians (LTs) as resources are considered as a case study to assess the proposed method. The study optimization model showed that reallocating 6 of 23 LTs to different PHCs would reduce disparity in LT workload (from 57.62% to 30.54%) and LT access (from 116.4% to 49.3%). The disparity reduction highlights the impact of resource reallocation according to the proposed framework.

Keywords


Developing Nations, Healthcare, Optimization, Policy, Resource Disparity, Resource Allocation.

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DOI: https://doi.org/10.18520/cs%2Fv115%2Fi6%2F1049-1055