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 Table of Contents  
Year : 2020  |  Volume : 8  |  Issue : 2  |  Page : 60-63

Applying patient safety principles in public safety in the COVID-19 scenario

1 President, AIIMS, Mangalagiri, Andhra Pradesh, India
2 Department of Community and Family Medicine, All India Institute of Medical Sciences, Mangalagiri, Andhra Pradesh, India
3 Department of Oral and Maxillofacial Surgery (Dentistry), All India Institute of Medical Sciences, Mangalagiri, Andhra Pradesh, India

Date of Submission22-Jul-2020
Date of Decision20-Aug-2020
Date of Acceptance02-Sep-2020
Date of Web Publication21-Dec-2020

Correspondence Address:
Dr. Aravindakshan Rajeev
Additional Professor, Department of Community and Family Medicine, All India Institute of Medical Sciences, Mangalagiri, Pin 522 503, Andhra Pradesh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jpsic.jpsic_20_20

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COVID-19 has overwhelmed the health systems all over the world. Using a methodology for finding excess deaths due to illnesses, we estimated the statistics for the countries which had their first case of coronavirus infection in January 2020. For illustration, the avoidable harm in the USA was 160,988 and that of the UK was 38,857 until the 2nd week of August 2020. Geographic distribution of excess deaths was plotted on GeoDa® shaded map. Spatial error model showed that early and vigorous testing reduced the mortality load. Strategy has to be worked out to contain the pandemic using the appropriate public health tools.

Keywords: COVID-19, mortality, pandemic, patient safety

How to cite this article:
Ravikumar TS, Rajeev A, Yadav S. Applying patient safety principles in public safety in the COVID-19 scenario. J Patient Saf Infect Control 2020;8:60-3

How to cite this URL:
Ravikumar TS, Rajeev A, Yadav S. Applying patient safety principles in public safety in the COVID-19 scenario. J Patient Saf Infect Control [serial online] 2020 [cited 2021 Apr 21];8:60-3. Available from: https://www.jpsiconline.com/text.asp?2020/8/2/60/304214

  Introduction Top

We had performed an interim analysis of outcomes in COVID-19 management, in countries with their first cases in January 2020.[1] We name these countries collectively, the 'January Cohort'. The rationale for this January Cohort analysis is that these 21 countries had their first cases early in the pandemic, and hence, the strategies/tactics/outcomes are fairly mature as compared to other countries with the first case in subsequent months.[2] Herein, further analysis was conducted to discern on-going practices in these countries and apply patient safety principles to public safety.

  Methodology Top

The principles of patient safety are rooted in avoidance and elimination of preventable harm.[3] Harm reduction in patient safety is measured in several domains: hospital mortality, morbidity, excess hospital stay, incremental costs and patient experience of care, to name a few.[4] Risk adjustments are often used to measure death rates (e.g. standardised mortality ratio) or excess death rates per geographic areas.[5] While multi-dimensional analysis will be performed in the future to analyse COVID-19 outcomes, herein, we take initial step to analyse the death rates (deaths per million) as an indicator of relative performance across this cohort.

We also hypothesise that in countries with high testing rates yet with high mortality, the timing of testing (early vs. late) is a critical factor. In most countries with higher death rates, the testing was ramped up later in the course of the pandemic such that they were all in Stage 4 (epidemic in their regions), instead of vigorous early testing in Stage 1 (imported cases only) and 2 (local transmission) or even in Stage 3 (community transmission).

Ordinary least squares regression is inefficient when dealing with aggregate country-wise statistics because of lack of normal distribution in the data. We performed spatial regression using GeoDa® mapping and analysis software for testing whether the death rate as a dependent variable predicated on the categorical (dichotomous) variables of early testing or contact tracing while adjusting for the number of tests done and cases per million of the countries in question.

  Results Top

We applied the principles of avoidable harm in patient safety to public health in the context of COVID-19 pandemic using the median value of deaths of per million of India. Totalling excess deaths (307,308) and deducting the lives saved (12,744) yielded the net value of potentially avoidable harm of 294,564 deaths in this cohort [Table 1]. The excess deaths in countries as the preventable harm in relation to the median death rate amongst the January Cohort are shown in [Figure 1].[5],[6]
Table 1: Statistics per country (as on August 17, 2020)

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Figure 1: Quantile Map of the January cohort as per ratio of deaths/million to cases/million

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[Figure 2] shows the country-specific data. Early testing and contact tracing efforts are indicated by shades and patterns. The aggregate data have reasonable amount of multi-collinearity (number = 4.902) and the errors were significantly away from normal distribution as shown by Jarque–Bera test (P < 0.0001). Robust LM (lag) and Robust LM (error) were significant as per the spatial regression, and based on the Akaike information criterion, the spatial error model was used to find the dependence of death rate on the variables mentioned above. The model derived thus indicated that the deaths corresponded to the number of cases detected (every unit increase in cases corresponded to 0.22 increase in deaths). Early testing as well as the number of tests per million was found to be independently significant. Contact tracing was not found to be significant [Table 2].
Figure 2: COVID-19 data of January cohort (as on August 17, 2020) on the logarithmic scale

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Table 2: Spatial error model for deaths per million

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  Discussion Top

Our model based on the principles of avoidable harm on the January Cohort of countries shows that there were close to 300,000 avoidable deaths among those countries. Other models have looked at delays in the implementation of public health measures such as lockdown on death rates. The office for national statistics estimated an excess of about 55,000 deaths in the UK, and similar counter-factual analysis in the USA found a net loss of 36,000 lives, attributable to delays in lockdown in the preceding months alone.[7],[8] Our analysis is in keeping with this counter-factual model of 91,000 deaths in two countries alone referred to above.

Sweden which followed the unusual model of letting 'herd immunity' develop without lockdown, contact tracing, isolation, etc., experienced a high death rate (573/million). The rest of the Scandinavian countries (e.g. Finland) have performed well with relatively lower death rates than Sweden, by using the public health interventions such as lockdown, quarantine, testing, tracing and isolation. Aggressive testing was pursued by the USA, UK, Italy, Spain, etc., only after getting to stages three or four. Better outcomes are observed in countries where early aggressive testing was combined with isolation as shown in [Figure 2] (early testing/contact tracing axis).[9],[10] Germany, Canada, Singapore, South Korea, Australia and Thailand used early testing strategies along with contact tracing. India, Japan and Sri Lanka though had relatively lower testing rates pursued their country-specific public health strategies vigorously.

  Conclusion Top

We conclude that while the many uncertainties are yet to come, analysis of first 6 months of January Cohort provides valuable lessons. Early testing with a higher coverage seems paramount both in reducing number of cases as a result of community transmission and in decreasing mortality as exemplified by countries such as Japan, Hong Kong, South Korea, Singapore and Malaysia.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Ravikumar TS, Aravindakshan R. A single strand RNA impacts global DNA. Indian J Comm Health 2020;32:313-6.  Back to cited text no. 1
Lai CC, Shih TP, Ko WC, Tang HJ, Hsueh PR. Severe acute respiratory syndrome coronavirus 2 (SARS CoV 2) and coronavirus disease 2019 (COVID 19): The epidemic and the challenges. Int J Antimicrob Agents 2020;55:105924.  Back to cited text no. 2
Bates DW, Singh H. Two decades since to err is human: An assessment of progress and emerging priorities in patient safety. Health Aff (Millwood) 2018;37:1736-43.  Back to cited text no. 3
Agbabiaka TB, Lietz M, Mira JJ, Warner B. A literature-based economic evaluation of healthcare preventable adverse events in Europe. Int. J. Qual Health Care 2017;29:9-18.  Back to cited text no. 4
Anselin L. Maps for Rates or Proportions [Internet]. Available from: https://geodacenter.github.io/workbook/3b_rates/lab3b.html. [Last accessed on 2020 Jun 18].  Back to cited text no. 5
Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB. Bayesian Data Analysis. 3rd ed. Boca Raton, USA: Chapman and Hall; 2014.  Back to cited text no. 6
Giles C. UK Deaths Since Virus Struck Almost 55,000 above Average, Says ONS. Financial Times. Available from: https://www.ft.com/content/f6a11fcd-0445-4643-9d3c-24d5fc0611da. [Last accessed on 2020 Jun 18].  Back to cited text no. 7
Pei S, Kandula S, Shaman J. Differential Effects of Intervention Timing on COVID-19 Spread in the United States. medRxiv: the preprint server for health sciences, 2020.05.15.20103655. https://doi.org/10.1101/2020.05.15.20103655.  Back to cited text no. 8
Oh J, Lee JK, Schwarz D, Ratcliffe HL, Markuns JF, Hirschhorn LR. National response to COVID-19 in the republic of Korea and lessons learned for other countries. Health Syst Reform 2020;6:e1753464.  Back to cited text no. 9
Boccia S, Ricciardi W, Ioannidis JP. What other countries can learn from Italy during the COVID-19 pandemic. JAMA Intern Med 2020;180:927-8.  Back to cited text no. 10


  [Figure 1], [Figure 2]

  [Table 1], [Table 2]


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