Afraid of flying?
Quality health care is effective, safe, and person-centric. This means services are timely (without long wait times or harmful delays); equitable (regardless of gender, ethnicity, geographic location, and socioeconomic status); integrated (offering the full range of services a person needs throughout their lifetime); and efficient (maximizing the benefit of available resources and avoiding waste).1
Poor quality medical care, on the other hand, means incorrect diagnoses, improper or unnecessary treatments, medication errors, lack of screening and preventative actions, unsafe clinical facilities, and providers without proper training. Every year, between 5.7 and 8.4 million deaths are attributed to poorquality care in low and medium income countries, or up to 15% of deaths in those countries.2
To put in another way, the risk of dying due to medical error during a hospital stay (1 in 300 people, according to the WHO) vastly outweighs the risk of dying in a plane crash (1 in 3 million people).3 And although no country is immune to this problem (some estimates claim that if medical error were included in the official ranking, it would be the third leading cause of death in the US),4,5 lower income countries—which are home to 80% of the world’s population—have the highest rates of death due to “adverse events.”6 In LAC, only 30% of preventable deaths are caused by lack of access to medical attention. The other 70% are the result of poor quality.7
What do quality data have to do with medical care?
“We need to increase the automation of data collection so thar they are of higher quality”.
Also part of healthcare quality is preventing diseases through early detection and guidance, as well as education to promote behavioral changes both within and outside of clinics. A closer look at the probability of dying from a non-communicable disease would likely recalibrate some people’s fear of flying. In the US, 1 in 6 people die of heart disease, and 1 in 7 of cancer8 In 2019 alone, it was estimated that 2.5 million deaths in the Americas—35% of all deaths—were preventable.9 In terms of data, current initiatives to measure quality are fragmented and focus more on inputs than outputs. They are not designed based on the population’s health needs.10 Since decision-makers in the region do not have timely information that provides a snapshot of the health system as a whole, they are flying blind.
The value of DT
The first response to this situation is usually: How and in what areas can DT help? Before answering this question, we need to first consider a more important one: Who does this process benefit? The answer is not just citizens, but also professionals and providers, institutions, and the health system in general. This is what makes DT such an integral part of reaching the “Quintuple Aim” of health care: i) improving the patient experience; ii) improving the population’s health; iii) reducing costs; iv) improving the work life of medical providers and professionals; and v)promoting equity and inclusion.11 The DT helps this ecosystem of stakeholders by giving them timely access to precise information.
Estonia: Key learnings from the digital transformation of its health system
“We have seen that patients are the main beneficiaries”
Beneficios digitales en concreto
The network of DT solutions is vast and will only be effective with a strategy tailored to each country’s needs and resources.
Also, there is mixed evidence on ineffective implementations and uses of IT tools in specific contexts.
The examples and information below are specific cases where introducing technology has facilitated progress toward quality.
Fewer medical errors and better decisions:
Patient empowerment (information, self-care, and access):
At the organizational level:
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Una revisión sistemática de la literatura de 32 artículos encontró que los estudios de sisteams de intercambio de la información clínica (HIE, por sus siglas en inglés) han reportado hallazgos fuertemente positivos para la calidad y la rentabilidad de la atención. Dieciséis estudios (64%) reportaron efectos positivos sobre la mejora de la calidad de la atención al paciente.
References:
1 OMS, “Quality of Care”, Health Topics, https://www.who.int/health-topics/quality-of-care#tab=tab_1.
2 Ibid.
3 Liam Donaldson et al., ed., Textbook of Patient Safety and Clinical Risk Management, (Cham: Springer, 2021), 5.
4 The BMJ, “Medical error—the third leading cause of death in the US”,https://www.bmj.com/content/353/bmj.i2139.full.
5 Estimating the rate of deaths due to medical error is not simple. While rough estimates have been used to justify improvements in the quality of hospital care, they are not free from criticism, as seen in:https://www.mcgill.ca/oss/article/critical-thinking-health/medical-error-not-third-leading-cause-death.
6 3 Dean T Jamison et al., “Global health 2035: A world converging within a generation.” The Lancet, 398, no. 9908. (December 2013): 1898-1955 https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(13)62105-4/fulltext.
7 Ibid. see Health sector framework document, 2021, 17. https://idbdocs.iadb.org/wsdocs/getdocument.aspx?docnum=EZSHARE-1348179246-3.
8 NSC, “Odds of dying”, Preventable deaths, NSC Injury facts, https://injuryfacts.nsc.org/all-injuries/preventable-death-overview/odds-of-dying/.
9 OPS, “Mortalidad prematura potencialmente evitable (MPPE)”, Salud en Las Américas, OPS, https://hia.paho.org/es/mortalidad-evitable.
10 Dean T Jamison et al., “Global Health”.
11 Thomas Bodenheimer y Christine Sinsky, “From triple to quadruple aim: care of the patient requires care of the provider”,Annals of family medicine 12, no. 6 (November 2014): 573-6. https://www.annfammed.org/content/12/6/573.
12 Paolo Campanella et al., “The impact of electronic health records on healthcare quality: a systematic review and meta-analysis”, European Journal of Public Health26, no. 1. (June 2015): 60–64. https://academic.oup.com/eurpub/article/26/1/60/2467302 .
13 Nadia Roumelioti et al., “Effect of Electronic Prescribing Strategies on Medication Error and Harm in Hospital: a Systematic Review and Metaanalysis”, Journal of General Internal Medicine 34 (August 2019): 2210–2223 https://link.springer.com/article/10.1007%2Fs11606-019-05236-8 .
14 Lorenzo Moja et al., “Effectiveness of Computerized Decision Support Systems Linked to Electronic Health Records: A Systematic Review and Meta-analysis”, American Journal of Public Health 104, no. 12 (October 2016): e12–e22 https://ajph.aphapublications.org/doi/10.2105/AJPH.2014.302164 .
15 Roghayeh Ershad Sarabi et al., “The Effectiveness of Mobile Phone Text Messaging in Improving Medication Adherence for Patients with Chronic Diseases: A Systematic Review”, Iranian Red Crescent medical journal 18, no. 5 (April 2016) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4939231/.
16 Thakkar Jay et al., “Mobile Telephone Text Messaging for Medication Adherence in Chronic Disease: A Meta-analysis”, JAMA Intern Med. 176, no. 3 (March 2016): 340–349 https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2484905.
17 Andrea Beratarrechea, “The impact of mobile health interventions on chronic disease outcomes in developing countries: a systematic review”, Telemedicine journal and e-health: the official journal of the American Telemedicine Association, 20. no. 11 (December 2013): 75–82. https://www.liebertpub.com/doi/10.1089/tmj.2012.0328.
18 Ray Widmer et al., “Digital health interventions for the prevention of cardiovascular disease: a systematic review and meta-analysis”, Mayo Clinic proceedings 90, no. 4 (April 2015): 469–480. https://www.mayoclinicproceedings.org/article/S0025-6196(15)00073-7/fulltext.
19 Mihiretu M. Kebede et al., “Effectiveness of Digital Interventions for Improving Glycemic Control in Persons with Poorly Controlled Type 2 Diabetes: A Systematic Review, Meta-analysis, and Meta-regression Analysis”, Diabetes Technology & Therapeutics 20, no.11 (October 2018)https://www.liebertpub.com/doi/abs/10.1089/dia.2018.0216.
20 Farahnaz Sadoughi, et al., “The impact of health information exchange on healthcare quality and costeffectiveness: A systematic literature review”, Computer Methods and Programs in Biomedicine 161 (July de 2018), 209-232,https://www.sciencedirect.com/science/article/abs/pii/S0169260718300907?via%3Dihub.