PUBH 9102 Week 11 Execution Write-Up Example

Risk-Based Scheduling and Repeat Critical Violations at Public Pools, Spas and Splash Pads in a Composite County: An Execution Write-Up Reported on the SQUIRE 2.0 Headings

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Walden University

PUBH 9102: Completing Doctoral Capstone II

Instructor Name

Month Day, Year

Risk-Based Scheduling and Repeat Critical Violations at Public Pools, Spas and Splash Pads in a Composite County: An Execution Write-Up Reported on the SQUIRE 2.0 Headings

Introduction

Problem and Available Knowledge

Between 2000 and 2014, U.S. health departments reported 493 outbreaks tied to treated recreational water (Hlavsa et al., 2018), and for most local health departments a scheduled inspection is how they verify that operators maintain disinfectant levels, circulation and safety gear. Inspection workloads have pushed some departments toward risk-based schedules that visit higher-risk facilities more often and lower-risk ones less. Whether such schedules change how often the same facility keeps failing has received little published study.

Rationale and Specific Aim

Between 2022 and 2024, the three districts of Alder County, a fictional jurisdiction, dropped their flat two-visit season calendar in favor of tiered scheduling. The study asked whether repeats, meaning back-to-back routine visits that each found a critical problem, became more or less common within each tier once a district switched, and how inspectors described the scheduling change in practice.

Methods

Context

The county's environmental health division permits pools, spas and splash pads and inspects them during an outdoor season running from May to September. Three districts made the change at different times. When the final season opened, the county also began enforcing a revised pool rule patterned on the newest national model code (Centers for Disease Control and Prevention [CDC], 2024).

The Intervention

The intervention was the tiered schedule itself, and it is described here apart from the study that examined it, as SQUIRE asks (Ogrinc et al., 2016). Each facility was assigned to a higher, middle or lower tier by the division on the basis of venue type, bather load and prior violations. Higher-tier facilities received three routine inspections per season, middle-tier two and lower-tier one, with complaint and follow-up visits unchanged. North District began tier scheduling as an unannounced pilot in August 2022; Central followed in May 2023 and East in May 2024.

Study of the Intervention

The study used an interrupted time series design within each tier, in which each district's own switch date set where its interruption fell, and a qualitative interview strand with inspectors. It ran as planned in the working document except for the departures listed in Table 1.

Table 1

Departures from the working document and their handling

Each departure is dated in the deviation log in the appendix.

Measures

Pairs joined each facility's back-to-back routine visits; a visit within 21 days of a critical citation or closure was treated as a follow-up. A pair became a repeat when each of its two visits carried a critical citation, or, for inspections under the revised rule, at least one closure-level or major violation, using the crosswalk approved by the committee in Week 6.

Analysis

Repeat shares were calculated by tier, season and period. Segmented regression estimated pre-switch level and trend and any change in each at the switch (Wagner et al., 2002). Because each district contributed only two or three seasons on one side of its switch, estimates are reported with their 95% confidence intervals and no claims of effect are made from point estimates alone (Lopez Bernal et al., 2017). Interviews were coded thematically by one coder using a codebook built from the first two transcripts.

Ethics

The records described facilities and contained no personal information on swimmers or operators. The review board judged the records strand not human subjects research and the interview strand exempt; one amendment covered a reworded interview question.

Results

Of 438 facilities with a permit during the window, 319 formed the analytic set, contributing 2,176 pairs: 1,098 before the switch and 1,078 after. Repeats made up 21.4% of higher-tier pairs before the switch (88/412) against 15.9% afterward (79/497). Among middle-tier facilities the shares were 14.8% (55 of 371) and 13.5% (48 of 356); among lower-tier facilities, 9.8% (31 of 315) and 11.1% (25 of 225). Modeled level changes at the switch came to -4.8 points for the higher tier (interval -10.9 to 1.3), -1.0 for the middle tier (-6.7 to 4.7) and 1.6 for the lower tier (-4.2 to 7.4). Excluding the 118 pairs that straddled the code change moved the higher-tier estimate to -4.5 percentage points, with an interval of similar width. Weak disinfectant readings featured in 61.0% of the repeat pairs.

Five transcripts were analyzed. Four inspectors said the tiered schedule gave them more time at higher-tier facilities. Three described reassigning a facility informally after a bad visit, a practice they called "bumping a pool," which did not always reach the tier file. Two said lower-tier operators were harder to reach between visits.

Discussion

Summary

The share of repeat pairs was lower after the switch in the higher tier and similar or slightly higher in the other two, but every confidence interval for a change in level included zero.

Interpretation

The pattern is consistent with what a tiered schedule is meant to do: more frequent visits where risk is greatest. It is also consistent with chance, given how few seasons each district contributed, and with two other explanations. First, informal "bumping" may have moved some troubled facilities into the higher tier without a record, so the tier file the analysis used may lag behind practice. Second, the lower-tier pools left in the analysis were only the ones visited often enough to produce pairs, which may make the lower-tier result unrepresentative of the tier as a whole.

Limitations

Short series on each side of the switch limit what segmented regression can separate from noise. The code change altered the outcome vocabulary in the final season. The interview strand lost long-serving East District inspectors, and the single-coder arrangement rests on a partial audit. Inspection results do not measure illness, and earlier work on food establishments found that inspection scores and outbreaks did not consistently track each other (Jones et al., 2004).

Conclusions

In this composite county, the move to tiered pool inspection was followed by a lower repeat share in the higher tier, an estimate too uncertain to support a claim of effect. The tier file should record informal reassignments, and a longer series under one violation code would allow a firmer answer.

References

Centers for Disease Control and Prevention. (2024). Model aquatic health code (5th ed.). U.S. Department of Health and Human Services. https://www.cdc.gov/model-aquatic-health-code/php/our-work/index.html

Hlavsa, M. C., Cikesh, B. L., Roberts, V. A., Kahler, A. M., Vigar, M., Hilborn, E. D., Wade, T. J., Roellig, D. M., Murphy, J. L., Xiao, L., Yates, K. M., Kunz, J. M., Arduino, M. J., Reddy, S. C., Fullerton, K. E., Cooley, L. A., Beach, M. J., Hill, V. R., & Yoder, J. S. (2018). Outbreaks associated with treated recreational water: United States, 2000-2014. MMWR Morbidity and Mortality Weekly Report, 67(19), 547-551. https://doi.org/10.15585/mmwr.mm6719a3

Jones, T. F., Pavlin, B. I., LaFleur, B. J., Ingram, L. A., & Schaffner, W. (2004). Restaurant inspection scores and foodborne disease. Emerging Infectious Diseases, 10(4), 688-692. https://doi.org/10.3201/eid1004.030343

Lopez Bernal, J., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: A tutorial. International Journal of Epidemiology, 46(1), 348-355. https://doi.org/10.1093/ije/dyw098

Ogrinc, G., Davies, L., Goodman, D., Batalden, P., Davidoff, F., & Stevens, D. (2016). SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence): Revised publication guidelines from a detailed consensus process. BMJ Quality & Safety, 25(12), 986-992. https://doi.org/10.1136/bmjqs-2015-004411

Wagner, A. K., Soumerai, S. B., Zhang, F., & Ross-Degnan, D. (2002). Segmented regression analysis of interrupted time series studies in medication use research. Journal of Clinical Pharmacy and Therapeutics, 27(4), 299-309. https://doi.org/10.1046/j.1365-2710.2002.00430.x