OBJECTIVE: The present study intends to monitor variations in deaths and identify the growth phases such as pre-growth, growth, and post-growth phases in Pakistan due to the COVID-19 pandemic.
METHODS: New approaches are needed that display the death patterns and signal an alarming situation so that corrective actions can be taken before the condition worsens. To meet this purpose, secondary data on daily reported deaths due to the COVID-19 pandemic have been considered, and the $c$ and exponentially weighted moving average (EWMA) control charts are used To meet this purpose, secondary data on daily reported deaths in Pakistan due to the COVID-19 pandemic have been considered. The $ c$ and exponentially weighted moving average (EWMA) control charts have been used for monitoring variations.
RESULTS: The chart shows that Pakistan switches from the pre-growth to the growth phase on 31 March 2020. The EWMA chart demonstrates that Pakistan remains in the growth phase from 31 March 2020 to 17 August 2020, with some indications signaling a decrease in deaths. It is found that Pakistan moved to a post-growth phase for a brief period from 27 July 2020 to 28 July 2020. Pakistan switches to re-growth phase with an alarm on 31/7/2020, right after the short-term post-growth phase. The number of deaths starts decreasing in August in that Pakistan may approach the post-growth phase shortly.
CONCLUSION: This amalgamation of control charts illustrates a systematic implementation of the charts for government leaders and forefront medical teams to facilitate the rapid detection of daily reported deaths due to COVID-19. Besides government and public health officials, it is also the public's responsibility to follow the enforced standard operating procedures as a temporary remedy of this pandemic in ensuring public safety while awaiting a suitable vaccine to be discovered.
DESIGN: Cross-sectional survey conducted between April and May 2017.
SETTING: Forty public clinics in Malaysia.
PARTICIPANTS: A total of 956 adult patients with T2D and/or hypertension were interviewed.
MAIN OUTCOME MEASURES: Patient experience on SMS was evaluated using a structured questionnaire of the short version Patient Assessment of Chronic Illness Care instrument, PACIC-M11. Linear regression analysis adjusting for complex survey design was used to determine the association of patient and clinic factors with PACIC-M11 scores.
RESULTS: The overall PACIC-M11 mean was 2.3(SD,0.8) out of maximum of 5. The subscales' mean scores were lowest for patient activation (2.1(SD,1.1)) and highest for delivery system design/decision support (2.9(SD,0.9)). Overall PACIC-M11 score was associated with age, educational level and ethnicity. Higher overall PACIC-M11 ratings was observed with increasing difference between actual and expected consultation duration [β = 0.01; 95% CI (0.001, 0.03)]. Better scores were also observed among patients who would recommend the clinic to friends and family [β = 0.19; 95% CI (0.03, 0.36)], when health providers were able to explain things in ways that were easy to understand [β = 0.34; 95% CI (0.10, 0.59)] and knew about patients' living conditions [β = 0.31; 95% CI (0.15, 0.47)].
CONCLUSIONS: Our findings indicated patients received low levels of SMS. PACIC-M11 ratings were associated with age, ethnicity, educational level, difference between actual and expected consultation length, willingness to recommend the clinic and provider communication skills.