BackgroundPost-discharge surgical site infections (SSI) are a major source of morbidity, expense and anxiety for patients. However, patient perceptions about barriers experienced while seeking care for post-discharge SSI have not been assessed in depth. We explored patient experience of SSI and openness to a mobile health (mHealth) wound monitoring “app” as a novel solution to address this problem.MethodsMixed method design with semi-structured interviews and surveys. Participants were patients who had post-discharge surgical wound complications after undergoing operations with high risk of SSI, including open colorectal or ventral hernia repair surgery. The study was conducted at two affiliated teaching hospitals, including an academic medical center and a level 1 trauma center.ResultsFrom interviews with 13 patients, we identified 3 major challenges that impact patients' ability to manage post-discharge surgical wound complications, including required knowledge for wound monitoring from discharge teaching, self-efficacy for wound monitoring at home, and accessible communication with their providers about wound concerns. Patients found an mHealth wound monitoring application highly acceptable and articulated its potential to provide more frequent, thorough, and convenient follow-up that could reduce post-discharge anxiety compared to the current practice. Major concerns with mHealth wound monitoring were lack of timely response from providers and inaccessibility due to either lack of an appropriate device or usability challenges.ConclusionsOur findings reveal gaps and frustrations with post-discharge care after surgery which could negatively impact clinical outcomes and quality of life. To address these issues, we are developing mPOWEr, a patient-centered mHealth wound monitoring application for patients and providers to collaboratively bridge the care transition between hospital and home.

We have identified critical barriers to integrating PGHD into clinical care and describe design implications to help address these barriers. Our work informs future efforts to ensure the smooth integration of essential PGHD into clinical practice.

Background Surgical site infection (SSI) remains a common, costly and morbid healthcare-associated infection. Early detection may improve outcomes, yet previous risk models consider only baseline risk factors (“BF”), not incorporating a proximate and timely data source: the wound itself. We hypothesize that incorporation of daily wound assessment improves the accuracy of SSI identification compared to traditional BF alone. Methods A prospective cohort of 1,000 post-open abdominal surgery patients at an academic teaching hospital were examined daily for serial features (“SF”), e.g. wound characteristics and vital signs, in addition to standard BF, e.g. wound class. Using supervised machine learning, we trained three Naïve Bayes classifiers (BF, SF, BF+SF) using patient data from 1-5 days before diagnosis to classify SSI on the following day. For comparison, we also created a simplified SF model that used logistic regression. Control patients without SSI were matched on 5 similar consecutive post-operative days to avoid confounding by length of stay. Accuracy, sensitivity/specificity, and AUC were calculated on a training and hold-out testing set. Results Of 851 patients, 19.4% had inpatient SSI. Univariate analysis showed differences in CRP, surgery duration and contamination, but no differences in ASA scores, diabetes or emergency surgery. The BF/SF/BF+SF classifiers had AUC of 0.67/0.76/0.76. The best performing classifier (SF) had optimal sensitivity of 0.80, specificity of 0.64, PPV of 0.35, and NPV of 0.93. Features most associated with subsequent SSI diagnosis were granulation degree, exudate amount, nasogastric tube presence, and heart rate. Conclusions Serial features provided moderate PPV and high NPV for early identification of SSI. Addition of baseline risk factors did not improve identification. Features of evolving wound infection are discernable prior to the day of diagnosis primarily based on visual inspection.

Background Postoperative surgical site infections (SSI) are common and costly. Most occur post-discharge, and may result in potentially preventable readmission and/or unnecessary urgent evaluation. Mobile health approaches incorporating patient-generated wound photos are being implemented in an attempt to optimize triage and management. We assessed how adding wound photos to existing data sources modifies provider decision-making. Study Design Web-based simulation survey using convenience sample of providers with expertise in surgical infections. Participants viewed a range of scenarios including surgical history, physical exam and description of wound appearance. All participants reported SSI diagnosis, diagnostic confidence, and management recommendations (main outcomes), first without, and then with accompanying wound photos. At each step, participants ranked the most important features contributing to their decision. Results Eighty-three participants completed a median of 5 scenarios (IQR 4-7). Most participants were physicians in academic surgical specialties (N=70, 84%). Addition of photos improved overall diagnostic accuracy from 67% to 76% (p<0.001), and increased specificity from 77% to 92% (p<0.001) but did not significantly increase sensitivity (55% to 65%, p=0.16). Photos increased mean confidence in diagnosis from 5.9/10 to 7.4/10 (p<0.001). Overtreatment recommendations decreased from 48% to 16% (p<0.001) while undertreatment did not change (28% to 23%, p=0.20) with addition of photos. Conclusions Addition of wound photos to existing data as available via chart review and telephone consultation with patients significantly improved diagnostic accuracy and confidence, and prevented proposed overtreatment in scenarios without SSI. Post-discharge mobile health technologies have the potential to facilitate patient-centered care, decrease costs, and improve clinical outcomes.

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