| Literature DB >> 32530396 |
Rashida S Smith1, Robert J Zucker1, Rosemary Frasso2.
Abstract
INTRODUCTION: Natural hazards are elements of the physical environment caused by forces extraneous to human intervention and may be harmful to human beings. Natural hazards, such as weather events, can lead to natural disasters, which are serious societal disruptions that can disrupt dialysis provision, a life-threatening event for dialysis-dependent people. The adverse outcomes associated with missed dialysis sessions are likely exacerbated in island settings, where health care resources and emergency procedures are limited. The effect of natural disasters on dialysis patients living in geographically vulnerable areas such as the Cayman Islands is largely understudied. To inform predisaster interventions, we systematically reviewed studies examining the effects of disasters on dialysis patients and discussed the implications for emergency preparedness in the Cayman Islands.Entities:
Mesh:
Year: 2020 PMID: 32530396 PMCID: PMC7316419 DOI: 10.5888/pcd17.190430
Source DB: PubMed Journal: Prev Chronic Dis ISSN: 1545-1151 Impact factor: 2.830
FigureThe study selection process for a systematic review of natural disasters in the Americas, dialysis patients, and implications for emergency planning. The search was conducted from January 29, 2019, through February 1, 2019.
Results of Studies Reporting on the Effects of Natural Disasters in the Americas on Dialysis Patients, January 2009–January 2019
| Authors | Study Location | Sample Characteristics and Size | Study Design | Study Objectives | Summary of Findings |
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| Bonilla-Félix et al, 2018 ( | San Juan, Puerto Rico | Pediatric patients with chronic renal disease; sample size not reported | Narrative report: personal recollections and experiences of the authors | Describe the authors’ experiences with patients with renal disease in an academic medical center |
Shortage of fuel affected patient transportation services and personnel; peritoneal dialysis patients compensated by doing manual exchanges. Lack of electricity and potable water resulted in 3 cases of bacterial peritonitis; physicians forced to close their practices. Complete loss of the communication system resulted in difficulties sharing messages with patients about where to receive dialysis treatments; challenges communicating with dialysis centers and staff members. Blocked roads created challenges in moving patients. |
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| Malik et al, 2018 ( | New York, New York | Adults aged 65 or older who used the ED post-disaster (N = 9,852 weekly average in the 43 weeks before Sandy; N = 10,073 average 1 week after Sandy) | Temporal and geospatial analysis; retrospective review of an all-payer claims database to analyze demographics, insurance status, geographic distribution and health conditions of older adults post-disaster | Evaluate the effect of Hurricane Sandy on ED use by older adults post-disaster, and characterize the primary and secondary medical needs of these people |
Increase in overall average weekly ED visits for all evacuation zones in New York City in the first week after Hurricane Sandy. Greatest increase in ED use was by older adults in evacuation zone 1 (from 552 to 1,111; Significant increases ( Significant increases ( |
| Lee et al, 2016 ( | New York, New York | Noninstitutionalized adult patients aged ≥18 who visited the ED in 2012 and had a home address in New York City (N = 50,996 one week before the hurricane; N = 46,131 one week after the hurricane) | Retrospective review of emergency claims data for adults visiting the ED in 2012; time-series analysis of frequency of visits for specific conditions and comorbidities | Characterize the geographic distribution of ED use post-Hurricane Sandy, and identify the post-disaster acute medical needs that developed in various geographic regions |
From the day of the hurricane (day 0) through day 5, categories of primary ICD-9 diagnosis codes with significant ( The significant increase in dialysis dependence lasted the longest of the 4 increases: it was significant ( The frequency of ED use significantly ( |
| Gotanda et al, 2015 ( | Lower Manhattan, New York | Patients aged ≥18 who visited the Beth Israel Medical Center ED from May 7, 2012, through April 28, 2013 (n = 1,747 ED visits during the baseline phase; n = 1,766 ED visits during the immediate post-Sandy phase; n = 424 admissions during baseline phase; n = 516 admissions during the immediate post-Sandy phase) | Retrospective observational study using data from ED and hospital databases | Evaluate the impact of Hurricane Sandy on ED and hospital use for the geriatric population compared to adults aged <65 in lower Manhattan and determine the reasons for their ED visits and subsequent hospitalizations |
Dialysis was 1 of the 4 concerns reported in EDs that significantly increased from baseline to the immediate post-Sandy phase (October 29–November 4, 2012) in all 3 age groups (18–64, 65–79, and ≥80; Dialysis was 1 of the 3 chief reasons for hospital admission that significantly increased in all 3 age groups ( |
| Murakami et al, 2015 ( | Lower Manhattan, New York | Patients aged ≥18 receiving dialysis care at 5 of 8 dialysis facilities in lower Manhattan at the time of Hurricane Sandy (n = 357) | Systematic cross-sectional 1-year follow-up survey: dialysis-specific preparedness was assessed by using the 13-item National Kidney Foundation–recommended dialysis-specific disaster preparedness checklist, and general disaster preparedness was assessed using the 15-item checklist proposed by the Department of Homeland Security | Describe the relationship between dialysis-specific and general disaster preparedness with missed dialysis sessions post-Sandy, for patients on hemodialysis |
94 (26.3%) study participants missed dialysis; median number of dialysis sessions missed was 2 (interquartile range, 1–3). 65 (69.1%) participants missed 1 or 2 sessions, and 27 (28.7%) participants missed 3–5 sessions. Transportation (no. of study participants stating reason = 14/94; 14.9%), unit closure (n = 38/94; 40.4%), and both transportation and unit closure (n = 42/94; 44.7%) were cited as reasons for missing dialysis. 221 (61.9%) participants received early dialysis, and 57 (25.8%) of those that received early dialysis still missed dialysis sessions. Although early dialysis did not significantly change the number of participants missing dialysis ( 236 (66.1%) participants received dialysis at nonregular dialysis facilities; 209 (58.5% ) received dialysis at affiliated facilities, and 27 (7.6%) in EDs. Among those receiving dialysis at affiliated facilities or in EDs, 68 (28.8%) received shortened treatments, which led to overt symptoms in 11 participants. Several factors were associated with a significantly lower incidence of missed dialysis sessions after Hurricane Sandy: dialysis-specific preparedness (IRR, 0.91; 95% CI, 0.87–0.98; Two factors were associated with a significantly higher number of missed dialysis sessions after Hurricane Sandy: the requirement for evacuation (IRR, 1.9; 95% CI, 1.1–2.3; |
| Lurie et al, 2015 ( | New York, New York, and state of New Jersey | ESRD Medicare beneficiaries enrolled in Medicare Parts A and B receiving facility-based hemodialysis who had a claim for ≥1 maintenance dialysis treatment (from October 1 to October 28, 2012, in New York City and New Jersey) and were not hospitalized for the week of the storm (N = 13,836) | Retrospective cohort analysis using data from the Centers for Medicare & Medicaid Services Datalink Project | Examine the relationship between early dialysis and adverse outcomes (ie, ED visits, hospitalizations, and 30-day mortality after the storm) among patients with ESRD in the areas most affected by Sandy |
8,256 (60%) study patients received early dialysis. In unadjusted analyses, patients receiving early dialysis had lower odds of ED visits (OR, 0.75; 95% CI, 0.63–0.89; In unadjusted analyses, the odds of 30-day mortality were similar among patients receiving early dialysis and patients not receiving early dialysis (OR, 0.80; 95% CI, 0.58–1.09; |
| Kelman et al, 2015 ( | New York, New York, and State of New Jersey | ESRD Medicare beneficiaries enrolled in Medicare Parts A and B receiving facility-based hemodialysis who had a claim for ≥1 maintenance dialysis treatment between October 1 and October 28, 2012, in New York City and the state of New Jersey (N = 13,264 study group patients) | Retrospective cohort study with 2 comparison groups using claims data from the Centers for Medicare & Medicaid Services Datalink Project. Study group consisted of ESRD patients in Sandy-affected areas. Comparison group 1 consisted of ESRD patients living in states unaffected by Sandy during the same period. Comparison group 2 consisted of ESRD patients living in the Sandy-affected region a year before the hurricane (October 1–October 30, 2011) | Characterize patterns of care and mortality of patients with ESRD in Sandy-affected areas (study group) and compare the results with the 2 comparison groups |
7,791 (58.7%) patients in the study group received early dialysis. The percentage of participants who had ED visits was greater in the study group (4.1%) than in comparison group 1 (2.6%) and comparison group 2 (1.7%), both The percentage of participants who were hospitalized during the week of the storm was greater in the study group than in comparison groups: 4.5% in study group, 3.2% in comparison group 1 ( 23% of study group participants who visited the ED received dialysis, compared with 9.3% in comparison group 1 ( Primary discharge diagnoses for patients visiting the ED or being hospitalized were for dialysis or ESRD. The 30-day mortality rate for patients in the study group (1.83%) was significantly higher than for comparison group 1 (1.47%; |
| Lin et al, 2014 ( | Brooklyn, New York | Dialysis unit nurse managers (n = 15) | Retrospective survey conducted through interviews with a key focus on the influx of hemodialysis patients from closed dialysis centers to hospitals, coping strategies these hospitals used, and difficulties encountered | Determine the extent of surge of transient dialysis patients in hospital dialysis units from closed dialysis facilities during the storm and its aftermath, and explore difficulties encountered by hospitals in Brooklyn, New York in response to the patient surge |
During and after Hurricane Sandy, 13 of 15 Brooklyn hospitals performed 347 hemodialysis sessions for transient hemodialysis patients. Influx of transient hemodialysis patients started before landfall, on October 28, 2012, rapidly increased after landfall, on October 29, 2012, and peaked on October 31, 2012. On peak day, dialysis units dialyzed 50.9% more patients than usual. Factors significantly associated with increased surge capacity were the average number of patients per day during nondisaster operations ( Storm-related challenges prevented the efficient operation of dialysis units; 7 of 14 operating hospital dialysis facilities reported a staff shortage due to transportation issues in getting to the facilities. All 5 affiliated outpatient dialysis centers cited communication challenges with ambulette service providers, which resulted in delays in transferring patients from EDs to outpatient dialysis centers. Closure of free-standing dialysis centers and other organizations presented communication challenges for hospital dialysis facilities. |
| Adalja et al, 2014 ( | New York, New York | Health care professionals in clinical or administrative leadership roles (ie, nurses, EMS/hospital emergency management, administration) in departments likely to be affected by the increase in patient volume (N = 71) | Qualitative interview-based method: semi-structured open-ended questions addressed how the evacuations affected the facilities that received a large proportion of the evacuated patients | Examine the effect of the surge of dialysis patients on hospitals during Hurricane Sandy, describe operational challenges faced by these hospitals, and examine the coordination efforts among hospitals receiving patients |
Communication challenges arose between receiving and evacuating hospitals. EMS teams’ unfamiliarity with the city’s geography and location of some receiving facilities presented challenges. Many hemodialysis patients who visited EDs for dialysis had missed ≥1 dialysis sessions, and some were in crisis. In some EDs, ED staff members corrected electrolyte imbalances until alternative dialysis arrangements could be made. One hospital anticipated the surge in dialysis patients, and as a result, it rapidly triaged dialysis patients. |
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| Kutner et al, 2009 ( | New Orleans, Louisiana | Dialysis patients who were affiliated with clinics in the US Gulf Coast Katrina-affected area and the New Orleans metropolitan area (N = 5,031) | Retrospective cohort study using updated data from the United States Renal Data System Standard Analysis Files released in 2008 | Investigate whether Hurricane Katrina’s landfall resulted in excess mortality among dialysis patients |
Hurricane Katrina was not associated with excess mortality for dialysis patients in Katrina-affected areas (HR, 0.98; 95% CI, 0.86–1.11; Significant predictors of increased mortality were older patient age (HR, 1.03; 95% CI, 1.03–1.04; |
| Anderson et al, 2009 ( | New Orleans, Louisiana | Patients (N = 386) receiving dialysis at 9 New Orleans hemodialysis units | Cross-sectional survey: structured telephone interviews with questions addressing sociodemographic dialysis factors and evacuation characteristics | Estimate the percentage of New Orleans patients who missed hemodialysis sessions after Hurricane Katrina, and identify the factors associated with missed dialysis sessions and increased hospitalizations of hemodialysis patients post-Katrina |
44% missed ≥1 dialysis session, and 16.8% missed ≥3 dialysis sessions post-Katrina. 8.6% of scheduled hemodialysis treatments were missed in the first month after the storm. Odds of missing ≥3 dialysis sessions, compared with missing no sessions, was 2.44 (95% CI, 1.14–5.24) for patients on dialysis for <2 years versus patients on dialysis ≥5 years. Patients who had <37 billed dialysis sessions (OR, 4.97; 95% CI, 1.57–15.8) and 37-38 billed sessions (OR 2.94; 95% CI, 1.11-7.80) were more likely to miss ≥3 dialysis sessions than patients who had ≥39 billing sessions in the 3 months before the storm. Patients who lived alone before the storm were more likely than patients who were cohabitating to miss ≥3 dialysis sessions (OR, 4.37; 95% CI, 1.85–10.3). 23% of participants reported being hospitalized in the first month after Katrina. Patients who missed ≥3 dialysis sessions were more likely to be hospitalized than patients who did not miss any sessions (OR, 2.16; 95% CI, 1.05–4.43). |
| Howard et al, 2012 ( | Louisiana, Mississippi, Alabama | Patients from 103 clinics (outpatient and hospital-based) that had service disruptions during Hurricane Katrina (n = 5,861 hospitalized; n = 2,857 not hospitalized) | Retrospective observational study using data from the United States Renal Data System 2008 Standard Analytical Files | Estimate the impact of Hurricane Katrina on hospitalization rates among dialysis patients |
Renal-related admissions rate for dialysis patients increased as a result of Hurricane Katrina, rising from 3.0 admissions per 100 patient-days in July 2004 to 5.5 admissions per 100 patient-days during September 2005. The rate ratio for renal-related hospitalizations associated with Hurricane Katrina was 2.53 ( The estimated number of excess renal-related hospital admissions attributable to Katrina was 140, roughly 3% of total dialysis patients at affected clinics. |
| Edmonson et al, 2013 ( | New Orleans, Louisiana | Long-term hemodialysis patients receiving dialysis from 9 facilities in the New Orleans area 1 week before the landfall of Hurricane Katrina and were still alive 1 year later (n = 388) | Prospective cohort study | Determine the association of psychiatric symptoms (PTSD and depression), subsequent hospitalization, and mortality in the year after Hurricane Katrina among ESRD patients |
92 (24%) reported symptoms consistent with a diagnosis of PTSD (posttraumatic stress disorder), and 178 (46%) reported symptoms consistent with a diagnosis of depression. 74 (19%) participants reported symptoms consistent with both PTSD and depression. 18 (5%) reported symptoms consistent with PTSD only, and 104 (27%) with depression only. Participants with depression, compared with participants without depression, were at a 33% higher risk of all-cause hospitalization and mortality (HR, 1.33; 95% CI, 1.06–1.66; Participants with PTSD, compared with participants without PTSD, were not at significantly higher risk of all-cause hospitalization or mortality (HR, 1.11; 95% CI, 0.85–1.44; |
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| Dossabhoy et al, 2015 ( | Shreveport-Bossier, Louisiana | Dialysis patients visiting health care facilities in surrounding areas (notably Shreveport and Bossier, Louisiana) not directly affected by the hurricane (sample size not reported) | Narrative report: personal recollections and experiences of the authors | Describe the impact of hurricanes Katrina and Rita on the nephrology community, patients, and health care providers in areas not directly affected by the storm |
Mass evacuation of hundreds of dialysis patients overwhelmed host hemodialysis centers; host hemodialysis centers compensated by providing up to 4 dialysis shifts per day at the time of maximum crisis. Surge of dialysis patients resulted in shortening dialysis treatments, which sometimes led to the development of uremic symptoms and inadequate dialysis. Arriving without knowledge of routine medication resulted in suboptimal treatment of comorbid conditions such as hypertension and diabetes. Closure of 2 of the 3 major transplant centers reduced the availability of cadaveric organs for transplantation and prolonged waiting times for patients on the transplant list. |
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| Abir et al, 2014 ( | District of Columbia, West Virginia, Virginia, and Maryland | Charge nurse or supervisor in each dialysis facility (n = 81 of 90 centers approached) | Cross-sectional survey: semistructured interview guide. Survey questions addressed whether their centers lost power, and if so, duration of power loss, and where their patients received dialysis | Determine how large-scale power outages from the June 29, 2012, mid-Atlantic storms affected operations in a sample of hemodialysis centers in the affected regions |
Of the 36 centers that lost power, 13 lost power for ≤12 hours; 9 lost power for 13–24 hours; 12 lost power for >24 hours, and 2 lost power for an unknown length of time. Of the 36 centers that lost power, 11 referred their patients to other dialysis centers, and 8 accommodated their patients during a later shift or on a different day. The power outage affected the operations of 24 dialysis centers. 8 centers that lost power received patients from other centers after restoration of their power, and 19 centers that were not affected by the power outage received patients from other centers. Some centers cited barriers in contacting patients by telephone to refer them to other centers as a result of the power outage. Respondents reported that despite making arrangements for their patients to receive treatment at alternate sites, some patients asked why they could not go to nearby EDs to receive dialysis, mentioning distance from home to alternate centers and transportation barriers. |
Abbreviations: ED, emergency department; EMS, emergency medical services; ESRD, end-stage renal disease; HR, hazard ratio; ICD, International Classification of Diseases; IRR, incident rate ratio; OR, odds ratio; PTSD, posttraumatic stress disorder.
Emergency Planning Recommendations for Dialysis Patients
| Identified Effects of Natural Hazards | Impact | Recommendations |
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| Loss of electricity | Leads to closure of dialysis facilities and missed dialysis sessions. | Electricity and clean water are critical for dialysis; emergency planners could compensate for the loss of electricity by using generators and lack of clean water by making preparations to have extra storage of potable water; additionally, emergency planners and dialysis providers can make arrangements to transport patients to affiliate sites. |
| Lack of clean water | Leads to closure of dialysis facilities and missed dialysis sessions. Use of unclean water by peritoneal dialysis patients can lead to bacterial peritonitis | |
| Blocked roads and lack of transportation | Creates challenges in transporting dialysis patients and leads to missed dialysis sessions. Problems in the commute of staff members and providers to dialysis facilities can lead to a shortage of dialysis providers. | Emergency planners and dialysis centers should have a contingency plan to transport patients to another center; proactively evacuate dialysis patients living in vulnerable areas or those with limited mobility; make preparations for dialysis staff members and providers to shelter in place at dialysis units. |
| Disrupted communication system | Presents challenges in communicating with patients or staff members about emergency plans. | Develop an action plan of how to communicate with staff members ahead of disasters; provide dialysis patients with pertinent information before a hurricane, such as contact information for alternative dialysis centers, information on an emergency renal diet, copies of their dialysis orders, and a list of their medications and comorbidities. |
| Mass evacuation and disturbed living situation | Interrupts usual source of care for dialysis patients, leading to a strain on other centers as they face an influx of dialysis patients. | Identify dialysis patients from areas likely to experience mass evacuation and proactively admit these patients to the hospital, if possible; consider early dialysis and provide all dialysis patients with contact information for different dialysis centers to overcome surge problems. |
| Surge of dialysis patients at hospitals and dialysis units | Shortens treatment sessions for dialysis patients as dialysis centers grapple with trying to meet the increased demand on units. | Make plans to have dialysis providers readily available in alternate locations; have functioning dialysis centers open for extended hours and offer more treatment sessions to manage the increasing patient load. |
| Missed dialysis sessions | Leads to adverse health outcomes, such as visits to the emergency department, hospitalizations, and mortality. | Create and distribute a dialysis emergency packet, which should contain information for alternate dialysis locations; consider offering early dialysis |
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| Use of emergency department | Increase in emergency department visits for dialysis patients | Dialysis providers should consider offering early dialysis and provide dialysis patients with dialysis-specific preparedness knowledge, such as contact information for alternative sites, information on an emergency renal diet, copies of their dialysis orders, and a list of their medications and comorbidities. |
| Hospitalizations | Increase in hospitalizations for dialysis patients | |
| Mortality | — | |
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| Posttraumatic stress disorder | Onset or exacerbation of posttraumatic stress disorder | In addition to preparing to manage the medical and social needs of dialysis patients after disasters, clinicians should prepare to screen dialysis patients for signs of depression, posttraumatic stress disorder, and other mental health conditions, and develop an action plan to address and treat the mental health needs of dialysis patients, such as referral to counseling and support groups. |
| Depression | Onset or exacerbation of depression | |
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| Dialysis-specific preparedness | Lower the incidence of missed dialysis sessions | Periodically review dialysis-specific preparedness and awareness with dialysis patients, especially during the hurricane season; providers can assess the readiness of dialysis patients by using the disaster preparedness checklist provided by the National Kidney Foundation. |
| Early dialysis | Lower odds of missed dialysis sessions | Emergency planners should consider offering preemptive dialysis to curb adverse outcomes associated with missed dialysis sessions, such as emergency department visits and hospitalizations. |
| Category | Search Terms |
|---|---|
| Problem | Disasters, natural disasters |
| Intervention | Kidney failure, dialysis |
| Outcomes | Delivery of health care, mortality, morbidity, hospitalization, emergency department use, adverse outcomes, health services accessibility, quality of life, patient satisfaction, patient care, patient experiences, patient care management, treatment outcome, mental health, complications, questionnaires and surveys |
| Database | Electronic Search |
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| PubMed | (((((((Disasters OR “Disasters”[Mesh] OR “Natural Disasters” OR “Natural Disasters”[Mesh] OR hurricanes OR Storms))) AND ((Dialysis OR “Dialysis”[Mesh] OR Renal Dialysis OR “Renal Dialysis”[Mesh] OR kidney failure OR “Kidney Failure, Chronic”[Mesh] OR renal failure OR hemodialysis OR peritoneal dialysis))) AND ((“Delivery of Health Care”[Mesh] OR healthcare delivery OR health-care delivery OR health care delivery OR Mortality OR “Mortality”[Mesh] OR “Morbidity”[Mesh] OR Morbidity OR morbidities OR “Hospitalization”[Mesh] OR hospitalization OR “emergency department use” OR “adverse outcomes” OR “Health Services Accessibility”[Mesh] OR “Quality of Life”[Mesh] OR “quality of life” OR “Patient Satisfaction”[Mesh] OR “Patient Care”[Mesh] OR “Patient Health Questionnaire”[Mesh] OR patient experiences OR “Patient Care Management”[Mesh] OR “Treatment Outcome”[Mesh] OR “Surveys and Questionnaires”[Mesh] OR “Health Care Surveys”[Mesh] OR complications OR “Mental Health”[Mesh] OR survey OR surveys OR Questionnaires OR Questionnaire))))) |
| Scopus | ((TITLE-ABS-KEY (disaster*) OR TITLE-ABS-KEY ({natural disasters}) OR TITLE-ABS-KEY (hurricane*) OR TITLE-ABS-KEY (storm*))) AND ((TITLE-ABS-KEY (dialysis) OR TITLE-ABS-KEY ({renal dialysis}) OR TITLE-ABS-KEY ({kidney failure}) OR TITLE-ABS-KEY ({renal failure}) OR TITLE-ABS-KEY (hemodialysis) AND TITLE-ABS-KEY ({peritoneal dialysis}))) AND ((TITLE-ABS-KEY ({delivery of health care}) OR TITLE-ABS-KEY (healthcare W/2 delivery) OR TITLE-ABS-KEY ({health-care delivery}) OR TITLE-ABS-KEY (mortality*) OR TITLE-ABS-KEY (morbidity*) OR TITLE-ABS-KEY (hospitalization*) OR TITLE-ABS-KEY ({emergency department use}) OR TITLE-ABS-KEY ({adverse outcomes}) OR TITLE-ABS-KEY ({health services accessibility}) OR TITLE-ABS-KEY ({quality of life}) OR TITLE-ABS-KEY ({patient satisfaction}) OR TITLE-ABS-KEY ({patient care}) OR TITLE-ABS-KEY ({patient health questionnaire}) OR TITLE-ABS-KEY (patient W/2 experiences) OR TITLE-ABS-KEY ({patient management}) OR TITLE-ABS-KEY ({treatment outcome}) OR TITLE-ABS-KEY (survey*) OR TITLE-ABS-KEY (questionnaires*) OR TITLE-ABS-KEY ({health care surveys}) OR TITLE-ABS-KEY (complications*) OR TITLE-ABS-KEY ({mental health}))) AND (LIMIT-TO (PUBYEAR,2018) OR LIMIT-TO (PUBYEAR,2017) OR LIMIT-TO (PUBYEAR,2016) OR LIMIT-TO (PUBYEAR,2015) OR LIMIT-TO (PUBYEAR,2014) OR LIMIT-TO (PUBYEAR,2013) OR LIMIT-TO (PUBYEAR,2012) OR LIMIT-TO (PUBYEAR,2011) OR LIMIT-TO (PUBYEAR,2010) OR LIMIT-TO (PUBYEAR,2009)) AND (LIMIT-TO (LANGUAGE, “English”) |
| CINAHL | (MH “Disasters+” OR MH “Natural Disasters” OR disasters OR hurricanes OR Storms) AND (MH “Dialysis+” OR MH “Dialysis Patients” OR MH “Renal Replacement Therapy+” OR MH “Hemodialysis+” OR Renal Dialysis OR MH “Peritoneal Dialysis+” OR MH “Renal Insufficiency+” OR kidney failure OR renal failure OR hemodialysis OR dialysis OR peritoneal dialysis) AND (MH “Health Care Delivery+” OR healthcare delivery OR health-care delivery OR health care delivery OR MH “Mortality+” OR mortality OR MH “Morbidity+” OR morbidity OR morbidities OR MH “Hospitalization+” OR hospitalization OR MH “Emergency Care+” OR emergency department use OR adverse outcomes OR MH “Health Services Accessibility+” OR health services accessibility OR MH “Health Services Needs and Demand+” OR MH “Health Services+” OR MH “Treatment Outcomes+” OR MH “Quality of Life+” OR MH “Quality-Adjusted Life Years” OR MH “Quality of Working Life” OR MH “Psychological Well-Being+” OR quality of life OR MH “Patient Satisfaction+” OR patient satisfaction OR MH “Patient Care+” OR MH “Continuity of Patient Care+” OR patient care OR patient health questionnaire OR patient experiences OR patient care management OR MH “Treatment Outcome+” OR treatment outcome OR MH “Surveys+” OR surveys OR MH “Questionnaires+” OR questionnaires OR health care surveys OR complications OR MH “Mental Health” OR mental health) |
| Cochrane Library | A complete description of this search can be requested from the corresponding author. |
Quality Assessment Using the Newcastle–Ottawa Scalea of Cohort Studies
| Study | Selection (Maximum 1 ◆) | Comparab ility (Maximum 2 ◆) | Outcome (Maximum 1 ◆) | Quality | |||||
|---|---|---|---|---|---|---|---|---|---|
| Representativeness of Exposed Cohort | Selection of Nonexposed Cohort | Ascertainment of Exposure | Outcome Not Present at Start of Study | Assessment of Outcome | Length of Follow-Up | Adequacy of Follow-Up of Cohorts | |||
| Malik et al ( | ◆ | ◆ | ◆ | ◆◆ | ◆ | ◆ | Good | ||
| Lee et al ( | ◆ | ◆ | ◆ | ◆◆ | ◆ | ◆ | Good | ||
| Gotanda et al ( | ◆ | ◆ | ◆ | ◆ | ◆ | ◆ | Good | ||
| Lurie et al ( | ◆ | ◆ | ◆ | ◆◆ | ◆ | ◆ | Good | ||
| Kelman et al ( | ◆ | ◆ | ◆ | ◆ | ◆ | Poor | |||
| Kutner et al ( | ◆ | ◆ | ◆ | ◆◆ | ◆ | ◆ | ◆ | Good | |
| Howard et al ( | ◆ | ◆ | ◆ | ◆◆ | ◆ | ◆ | Good | ||
| Edmonson et al ( | ◆ | ◆ | ◆ | ◆◆ | ◆ | ◆ | ◆ | Good | |
a Thresholds for converting the scale into good, fair, and poor quality are as follows: good, 3 or 4 diamonds in selection domain and 1 or 2 diamonds in comparability domain and 2 or 3 diamonds in outcome domain; fair, 2 diamonds in selection domain and 1 or 2 diamonds in comparability domain and 2 or 3 diamonds in outcome domain; poor, 0 or 1 diamond in selection domain or 0 diamonds in comparability domain or 0 or 1 diamonds in outcome domain. Source: Wells et al (20), Borge et al (23), Shurrab et al (24).
Quality Assessment Using the Critical Appraisal Skills Programme Qualitative Checklista
| Criteria | Bonilla-Félix and Suárez-Rivera ( | Dossabhoy et al ( | Adalja et al ( |
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| Was there a clear statement of the aims of the research? | Yes | Yes | Yes |
| Is a qualitative methodology appropriate? | Yes | Yes | Yes |
| Was the research design appropriate to address the aims of the research? | No | No | Can’t tell |
| Was the recruitment strategy appropriate to the aims of the research? | Can’t tell | Can’t tell | Yes |
| Was the data collected in a way that addressed the research issue? | Can’t tell | Yes | Yes |
| Has the relationship between the researcher and participants been adequately considered? | No | No | Can’t tell |
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| Have ethical issues been taken into consideration? | Can’t tell | Can’t tell | Yes |
| Was the data analysis sufficiently rigorous? | No | No | Can’t tell |
| Is there a clear statement of findings? | Yes | Yes | Yes |
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| How valuable is the research? | Somewhat valuable: findings should be reviewed with caution because they may be heavily biased: study is based on personal recollections and experiences of the authors | Somewhat valuable: low-quality evidence; findings should be reviewed with caution because they may be heavily biased: study is based on personal recollections and experiences of the authors | Valuable: although findings should be reviewed with caution because no specific tool was used to group or organize identified themes |
a Options were yes, can’t tell, no. Source: Critical Appraisal Skills Programme (21).
Quality Assessment Using the Joanna Briggs Checklista for Analytical Cross-Sectional Studies
| Criteria | Murakami et al ( | Abir et al ( | Lin et al ( | Anderson et al ( |
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| Were the criteria for inclusion in the sample clearly defined? | Yes | Yes | Yes | Yes |
| Were the study subjects and the setting described in detail? | Yes | Yes | Yes | Yes |
| Was the exposure measured in a valid and reliable way? | Unclear | Yes | Yes | Yes |
| Were objective, standard criteria used for measurement of the condition? | Unclear | Yes | Yes | Yes |
| Were confounding factors identified? | Yes | No | Yes | Yes |
| Were strategies to deal with confounding factors stated? | Yes | Not applicable | Yes | Yes |
| Were the outcomes measured in a valid and reliable way? | Unclear | Yes | Yes | Yes |
| Was appropriate statistical analysis used? | Yes | Not applicable | Yes | Yes |
| Overall appraisal | Include | Include | Include | Include |
a Options were yes, no, unclear, or not applicable. Source: Moola et al (22).