Descriptive, Longitudinal Study Results Applied to Statistical Models to Assess the Impact of Early Microbiological Cultures on the Economic Burden of Treatment for Infected Diabetic Foot Ulcers at a Mexican Public Health Facility
Infection plays a critical role in health care and impacts the cost of the treatment of diabetic foot ulcers (DFU). To examine the cost reduction associated with the multidisciplinary treatment of infected DFU (IDFU) by obtaining early (ie, within 48 hours of admission) microbiological culture results, a descriptive, longitudinal study was conducted.
Data were collected prospectively from patient medical charts of a cohort of 67 patients (mean age, 56.14 ± 12.3 years; mean duration of diabetes, 14.95 ± 8 years) with IDFU treated at a Mexican public health facility from January 1 to April 30, 2010. Information included demographic data (age, gender, marital status, time elapsed since first diagnosis of diabetes mellitus type 2 [DM2]), and the following clinical records: Wagner classification, bacterium type, antimicrobial resistance, length of hospital stay, and the antibiotic schedule utilized, as well as number and type of laboratory tests, medications, intravenous therapy, surgical and supportive treatment, type and number of specialists, and clinical outcome. Microcosting was used to calculate the unit cost of each medical treatment element. Using the Monte Carlo and Markov predictive simulation economical models, cost reduction associated with early identification of the specific microorganism through bacterial culture in IDFU was estimated. Based on the statistical results, differences between real and estimated costs when including early microbiological culture were identified and the number and type of most common species of infectious bacteria were detected. The total cost observed in the patient cohort was $502 438.04 USD, mean cost per patient was $7177.69 ± $5043.51 USD, and 72.75% of the total cost was associated with the hospital stay length. The cost of the entire treatment including antibiotics was $359 196.16 USD; based on the simulation of early microbiological culture, the model results showed cost could be reduced by 10% to 25% (in this study, the cost could be as low as $304 624.63 USD). The use of early microbiological cultures on IDFU to determine the appropriate antibiotic can reduce treatment costs by >30% if hospital stay is part of the consideration.
Diabetes mellitus type 2 (DM2) is one of the most common chronic diseases worldwide. North America and the Caribbean Region have the highest diabetes prevalence. According to the International Diabetes Federation (IDF),1 44.3 million persons between the ages of 20 and 79 years have been diagnosed with diabetes. Treatment of DM2 and its long-term complications are associated with high costs and represent a substantial economic burden for health systems in different countries, particularly for third-party payer health institutions. In North America and the Caribbean Region, the total health expenditure related to DM2 treatment was estimated to be $348 to $610 billion USD, solely for 2015; 14% of the total health budget in the region is spent on diabetes treatment and represents 51.7% of the world health care spending associated with diabetes.1,2
In 2015, DM2 affected 383 million persons worldwide. Estimations suggest 592 million individuals will be affected in 2040.1 In Mexico, according to data provided by the National Health and Nutrition Survey3 in 2012, DM2 prevalence was 9%; this is a 1.25-times higher prevalence rate than the estimation for 2030 calculated by Wild.4 Data provided by the IDF1 showed a prevalence in Mexico of 15.8% (age-adjusted) and 14.7% (raw). Specifically in 2012, DM2 prevalence adjusted by age in Mexico was 8.9% for 40- to 49-year-old patients, 19.2% for patients 50 to 59 years old, and 25.3% for 60- to 69-year-old patients. These data are similar to international reports, where the highest prevalence is observed in persons age 40 to 59 years.1 These groups represent the economically active population of the country and exert a profound economic impact.1
Diabetic foot ulcers (DFU) are an important long-term complication in patients with DM2. Epidemiological and economic statistics on infected DFU (IDFU) and amputations have been obtained from real-world data and through the use of theoretical mathematical models1 that describe typical diabetic foot cases with clinical outcomes characterized by different complexity levels ranging from wound healing to transtibial amputation.5 Nearly all data on infected foot ulcers in diabetes are obtained from information of developed countries.5,6 Studies with data deriving from developing countries are scarce.
Symptoms associated with diabetic foot syndrome include loss of sensation and, when a trauma occurs, loss of capacity to feel pain in the lower limbs. This worsening sensation is a consequence of diabetic neuropathy.7–12 According to epidemiological data,13 15% of individuals with diabetes will undergo amputation, and 20% to 25% of these patients will be candidates for a second amputation. Prevention programs have been reported to decrease the need for amputation in 80% to 90% of cases.4
Specific guidelines14 and descriptive studies on microorganisms associated with IDFU15,16 with respect to the management of diabetic foot infections describe treatment for wounds in diabetic foot injuries according to the absence or presence of infection and its severity. Consensus guidelines8 for treatment consider wound depth (involved tissues) and the presence of clinical data on infection (such as edema, erythema, rubor, heat) and vascular compromise to determine the specific treatment. IDFU must be treated with specific antibiotics according to microbiological cultures from the wound, and these must be provided after debridement to optimize microbiological diagnosis and antibiotic selection.14
For the initial treatment, the guidelines suggest empirical selection of an antibiotic that is active against Gram-positive bacteria. For geographic areas with a high prevalence of Gram-negative bacteria, double antibiotic coverage against Gram-positive and Gram-negative bacteria also is considered (extended-spectrum antibiotics drugs). When a microbiological culture is available, treatment must be modified according to culture results and antibiotic susceptibility under a more specific schedule. Because existing guidelines are based on a limited number of patients,14 it is difficult make decisions regarding cost-effective antibiotic therapy.
Some investigators have analyzed the cost-effectiveness of different approaches to IDFU in hypothetical cohorts employing mathematic models (eg, Markov and Monte Carlo tools17,18) that consider the probability of multiple complications and clinical outcomes according to the proposed treatments.19,20 However, the theoretical models have not described the role of microbiological cultures in diminishing the hospital stay and costs.
In view of this gap in the literature, the purpose of this study was to estimate the economic impact (cost reduction) of performing early (within 48 hours of admission) microbiological cultures in the treatment of IDFU by using the Markov and Monte Carlo predictive simulation economical models.
Methods and Procedures
The study was conducted in 2 parts. A prospective, descriptive, longitudinal study was performed to analyze real-world data from a group of patients with diabetes with infected foot ulcers; the known prevalence of microorganisms and registered treatment costs were described. In the second step, a hypothetical cohort with 100 iterations (case simulations) at different treatment stages was constructed through the Monte Carlo simulation, employing the data derived from the patients studied in the first phase (this information was utilized for the mathematical basis of the economical tool). The simulations provided predictions of the economic impact of obtaining early microbiological cultures of infected ulcers in order to make an informed decision about a specific antibiotic treatment.
The study was approved by the CLIEIS No. 1306 (Comité Local de Investigación y Ética en Investigación en Salud: Local Committee of Research and Ethics in Health Research) at the Institute Mexicano del Seguro Social (IMSS) Jalisco. Based on the observational nature of the investigation, the Committee authorized the use of signed informed consent according to the guidelines in the regulation of the General Health Law responsible for health research of studies without risk in Mexico.
In this study, data were obtained from the medical charts of patients with diabetes with IDFU who were seen at the IMSS Emergency Room (ER) of a second-level facility from January 1 to April 30, 2010. The patients were followed during hospital treatment for the IDFU. Patients with a diagnosis of cancer, hepatic cirrhosis, and/or rheumatic-orthopedic diseases that could impact their walking ability and patients with pressure-associated ulcers or DFU that appeared during their hospital stay were excluded.
Cost per patient was calculated based on the identification of the antibiotic schedule, the bacterium, and antimicrobial resistance from the patients’ charts. Length of hospital stay (days); number and type of laboratory tests, medications, and intravenous (IV) fluids; costs for surgical and supportive treatment; specialists (type and number of); and clinical outcomes also were abstracted, as well as demographic information and the patient’s history (age, gender, marital status, and time elapsed since first DM2 diagnosis). The Wagner classification of foot ulcers and microbiological culture also were obtained. The cost of each component of the medical treatment was obtained from the IMSS website IMSS compró21 (an institutional website that displays for public opinion the cost of drugs, medical technology, wound care material, and other supplies purchased by IMSS at each hospital).
Data collection. Data were collected from the patient’s chart by an emergency medicine physician and subsequently entered into an electronic database. To preserve anonymity, patients were identified by means of a code and their social security number.
Statistical analysis. Using the data collected by Gutiérrez et al,3 the sample size of this study was calculated with a 95% confidence interval (95% CI) and 80% potency. For quantitative data, means, standard deviations (SD), medians, ranks, and intervals were calculated. For qualitative data, percentages and proportions were utilized. All data were processed in SPSS version 16 and Excel 2010 statistical software (SPSS Inc, Chicago, IL).
In parallel, a descriptive economic analysis using microcosting was performed to evaluate the partial cost of medical treatment by employing the third-party-payer perspective (ie, the IMSS, for this particular study). The time horizon defined was 30 days. Discount rates were not applied.
Microcosting comprises a cost estimation method that involves the “direct enumeration and costing out of every input consumed in the treatment of a particular patient.”21 It employs the aggregation level, which allows knowing the lower-level estimated cost associated with the various treatment elements for a given level within the patient’s treatment. Indirect costs such as buildings, equipment, and maintenance were not considered. In order to estimate unit costs, the resource pattern utilized was identified according to microorganism type and was registered in the medical record of each patient; a monetary value was assigned later. The unit cost was identified for each resource. For health services (consultation, surgeries, hospitalization), cost information was obtained from the Diario Oficial de la Federación (DOF) website22 and the medication cost was obtained from the IMSS website under IMSS compró.23 The economic expenditure for each resource was calculated as the product of the unit cost multiplied by the number of units used. The monetary value for Mexican pesos was obtained in 2009 and converted into US dollars (USD) with an exchange rate of $12.75 Mexican pesos per $1 USD.
The following cost-related information was calculated: total cost per patient, total cost for the group of patients with diabetes, and mean cost for each patient.
Markov modeling. This mathematical model is employed in decision analysis to evaluate potential outcomes of a disease process, which are defined as specific health states and transitions that are modeled iteratively. In standard-decision tree analysis, a patient moves through states in a Markov process. Some states cannot be left once entered (the so-called “absorbing states” or natural history of the disease), including death.24-26 In IDFU, specific issues were considered with the following elements in the process: DM2 without complications; DM2+DFU; DM2+DFU+infection; DM2+DFU+infection+1st amputation; and DM2+DFU+1st amputation+2nd amputation (see Figure 1 and Tables 1 and 2), to estimate (calculated values) the proportion of persons affected by each condition per specific period (eg, proportion of patients with DM2+DFU in the first period [0.25], which corresponds to 25%; while in the second period, 0.297 corresponds to 29.7%). These proportions are utilized to construct the probabilistic mathematical model.
Monte Carlo modeling. The Monte Carlo method is a nondeterministic statistical method for obtaining a numerical solution for a problem too complicated to be solved analytically. This method solves a problem by generating a set of random or pseudorandom numbers within the domain of the variables under study. The corresponding absolute error decreases as the number of Monte Carlo evaluations increases, using the central limit theorem as a basis.27 The mathematical model allows for containing estimated numeric results through a design of specific clinical sets.28
The Monte Carlo predictive model was used in this study to find the behavior (through extrapolating the data of a specific clinical set) of the phenomenon denoted infected diabetic foot ulcer. Differences between real cost and estimated cost of procedures including early microbiological culture in each patient (eg, surgical procedures, wound healing, culture specimens) were considered based on the statistical results to optimize resources for the patient and for the third-party payer (IMSS) (see Figure 2 and Table 3). The Monte Carlo simulation was employed to estimate the cost reduction associated with early identification of the specific microorganism in the IDFU at the beginning of treatment. Data for the model included species, type of bacterium according to Gram stain, number of infecting microorganisms, and antibiotic sensitivity through bacterial culture.
The information analyzed included the bacterium type identified through microbiological culture; number of microorganisms identified in each microbiological culture and their susceptibility to medications (1–3 different bacteria were identified); unit cost for each medication (purchase of ordinary [eg, public tendering — ie, an administrative procedure where governments select the person or vendor from whom to buy different kind of supplies through public contest; and centralized procurement coordinated through the Acquisitions Department] and extraordinary [eg, items purchased from suppliers without public tendering such as antibiotics) used in the treatment recommended by the physician; length of ER stay (days), mindful of guidelines that have established a maximum time in the ER as 24 hours, while every extra hour generates an increase in financial expenditures per patient; length of hospital stay (days); and cost per day for total hospital stay at a secondary-level hospital.
The structure of the Monte Carlo model involved medications (antimicrobial spectrum: active against Gram-positive bacteria, Gram-negative bacteria, or anaerobic bacteria); specific antibiotic; cost of each antibiotic; cost of each group of antibiotics; and bacteria (specific bacterium identified through microbiological culture, along with bacterial group [Gram-positive, Gram-negative, anaerobic bacteria, fungus]).
As part of the Monte Carlo model, the following factors were considered: days of hospital stay (total or overnight and in the ER); hospital-associated costs; type of bacterium or group of bacteria (see Table 4); specific antibiotic or antibiotic groups, and the cost of each antibiotic in ordinary and extraordinary purchasing (see Table 5). One hundred (100) Monte Carlo iterations (simulations) were performed in order to observe the predictive model behavior. Final treatment cost and total cost with the proposed model were ultimately analyzed.
Data were obtained from the medical charts of 71 patients with IDFU; 4 clinical charts had incomplete data on the microbiological culture and were excluded from pseudorandom iterations, leaving 67 patients (mean age, 56.14 ± 12.3 years; mean time elapsed since initial diagnosis, 14.95 ± 8 years) considered for designing the iterations (simulations) utilized in the Monte Carlo model.
Patients were enrolled between January and April and were followed during 16 months. Infected ulcers in the diabetic foot were found to be more common in patients with 11–20 years of DM2 evolution. Men at the economically productive age (16–65 years old) were more affected than women; the educational level was basic (1–9 academic years). The most common concomitant chronic disease was hypertension (53.6%). Approximately one quarter (24.6%) of the patients with diabetes had undergone a previous lower-limb amputation (see Table 6).
Average ER length-of-stay was 1.4 ± 0.58 days; hospital stay when treated by other specialists (General Surgery, Angiology, Orthopedics, Traumatology, and Internal Medicine) was 14.7 ± 9.7 days.
Microcosting analysis results. Total treatment costs for the sample were $502 438.04 USD, mean cost per patient was $7177.69 ± $5043.51 USD, median cost was $6422.99 USD, 25th percentile was $3502.93 USD, 75th percentile was $9,298.33 USD), and 72.75% ($365 527.45 USD) of the total cost was associated with the hospital stay.
Furthermore, 10.6% ($53 240.86 USD) of expenditure during treatment was directed to wound healing care (eg, debridement procedures, wound healing, lavage), 9.98% ($50 132.94 USD) to surgical procedures, and 1.87% ($9389.27 USD) to antidiabetic drugs and concomitant chronic diseases. With regard to laboratory tests and treatment, 1.79% ($9008.47 USD) was attributed to clinical chemistry tests, 1% each to antibiotics ($5405.98 USD) and imaging studies ($5000.08 USD), 0.66% ($3309.88 USD) to acute phase reactants, 0.19% ($965.65 USD) to microbiological cultures, and the lowest percentage was attributed to IV fluids (see Figure 3).
The costs were determined according to the resource utilization pattern, which comprised the use of medications, wound healing material, hospital stay, and debridement procedures, modified for individual patients. Resource utilization was determined by the multidisciplinary treatment employed (identification, diagnosis, and treatment) according to the Wagner classification.14 Results from analyzed cases were included as Wagner grade 3 (30 cases [43.5%]) and Wagner grade 4 (22 [31.9%]). Patients in both groups required supracondylar amputation (13, 19%) or transmetatarsal amputation (20, 14%) (see Table 7). Microbiological culture was not performed in 2 patients; 1 of the remaining patients had a negative bacterial culture. The bacteria most frequently identified were Escherichia coli (20.4%) and Enterococcus faecalis (19.4%) (see Table 4). The most used antibiotic combination employed was ciprofloxacin/clindamycin.
Bacterial antibiotic susceptibility.
Gram-negative bacteria. In bacterial cultures positive for E. coli, the greatest proportion showed susceptibility to imipenem, amikacin, meropenem, cefotetan, and piperacillin/tazobactam; intermediate susceptibility was demonstrated toward quinolones, and there was resistance to ampicillin/sulbactam and ampicillin. Escherichia faecalis exhibited susceptibility to penicillin, vancomycin, linezolid, and gentamicin, with intermediate susceptibility to ciprofloxacin and resistance to tetracycline and synercid. Proteus mirabilis demonstrated susceptibility to amikacin, cefotetan, and carbapenem and was resistant to quinolones, while Morganella morganii was susceptible to amikacin, gentamicin, and meropenem, and resistant to ciprofloxacin, cefuroxime, cefotetan, moxifloxacin, and piperacillin (see Table 4).
Gram-positive bacteria. Staphylococcus haemolyticus was susceptible to linezolid, synercid, rifampicin, vancomycin, and chloramphenicol and resistant to clindamycin, gentamicin, penicillin, and quinolones. S. epidermidis exhibited susceptibility to linezolid, synercid, vancomycin, and rifampicin and resistance to ciprofloxacin, clindamycin, oxacillin, and amoxicillin. S. aureus displayed susceptibility to cefazolin, imipenem, piperacillin/tazobactam, rifampicin, vancomycin, oxacillin, and amoxicillin and resistance to ampicillin and penicillin. Methicillin-resistant S. aureus was susceptible to tetracycline, linezolid, trimethoprim/sulfamethoxazole, vancomycin, and synercid and resistant to cefazolin, quinolones, penicillin, and amoxicillin (see Table 4).
Monte Carlo modeling results. This study comprised 67 patients. For each patient, the number of days spent in the ER and in their hospital room was reported. According to the data collected, time in the ER ranged from 0 to 3 days, and time in the hospital room ranged from 0 to 15 days. Average costs per day in the ER and the hospital room were $1001.00 USD and $5,684.00 USD, respectively.
To implement the Monte Carlo methodology, the number of days the patient could spend in the ER and in the hospital room was randomly selected. Utilizing the average cost per day, the cost of hospitalization for 1 patient was calculated and then repeated 67 times to calculate the total cost for hospitalization. This procedure was performed 100 times, and the corresponding results are illustrated in Figure 4.
The antibiotic cost analysis showed if the physician takes a secretion sample from the IDFU within the first 48 hours of the patient’s admission to the ER and begins empirical antibiotic treatment but modifies the criteria according to the microbiological results from the culture, costs will be reduced (through antibiotic expenditure) by 9% to 15% (see Figure 4); the cost reduction could be as high as 20% to 32% when associated with a reduced number of hospital days, with a 10% to 25% total reduction in costs related with IDFU receiving multidisciplinary treatment.
IDFU are 1 of the most common late-stage complications of DM229 and inflict a substantial economic burden on society, particularly in developing countries such as Mexico, as well as on worldwide health systems.2,5 This condition places diabetic foot infection as a public health problem in the microbiological, clinical, epidemiological, and economic context; the American Diabetes Association (ADA)30 concluded diabetic foot complications represent 12% to 15% of the health care budget in developed countries and 40% in developing countries. Therefore, it is important to evaluate economic impact with a health care model that includes early microbiological culture in the care process of IDFU.
Treatment for DM2 in late-stage complications such as vision loss or blindness, kidney damage or failure, nerve pain and damage, heart and blood vessel disease, high blood pressure, dental problems, hand problems, and foot problems represents an increase from 50% to 700% in the total medical care cost in developed countries, according to data provided by the ADA.1,28–30 IDFU have a calculated incidence of 7% and are the cause of 80% to 95% of nontraumatic, lower-limb amputations throughout the world. In their descriptive study (N = 80), Gönen et al33 found higher cost associated with lengthy hospital stay and amputation, similar to the situation observed by the current study, in which 24.6% of patients underwent lower-limb amputation.
In a clinical setting, providing appropriate antibiotic treatment requires knowing the sensitivity associated with a specific antibiotic through a microbiological culture with an antibiogram for wound secretions with clinical infection data.14 For public health care systems in medical units of developing countries, it is important to follow the specific clinical guidelines; this situation directly affects hospital length-of-stay and treatment-response time,14,34 subsequently affecting the economic burden in the clinical care of these patients with diabetes. Clinical guidelines could help clinicians make the best cost-effective decisions concerning antibiotic treatment according to the type of bacterium and its antibiotic sensitivity.14,34
Employing guidelines for the diagnosis and treatment of patients with diabetes with DFU is associated with the proper use of economic resources and improved patient outcomes. In their descriptive study, Sotto et al35 demonstrated implementation of guidelines was associated with a savings of $20 046 USD related to a reduced microbiology laboratory workload and of $147 536 USD in a reduction in the prescription of extended-spectrum antibiotic drugs.
Conversely, bias with regard to the diagnosis and treatment guidelines of IDFU could give rise to overdiagnosis or underdiagnosis. This scenario is associated with inadequate use of the antibacterial medication, as well as with potential development of bacterial resistance and presence of adverse events related to medication use and a high amputation rate.29 Each of these situations causes an increase in the length of the hospital stay and the unnecessary waste of financial supplies in developed and developing countries.35
International best practice guidelines for DFU management, cost-effectiveness analysis, and direct cost-descriptive studies28,36,37 report failure of antibiotic treatment associated with a high risk of developing an infection in chronic foot ulcers, as well as a high risk of a nontraumatic amputation, with the associated cost of surgery, prolonged hospital stay, postoperative care, prosthesis use, and orthopedic rehabilitation. These costs are financed by secondary-level hospitals in the Mexican Health-Care System.
In late-stage complications of DM2, an IDFU is associated with a high social cost. The burden is the result of health care costs and work disability associated with amputations during treatment, which reduce productivity for countries and their governments, impacting expenditures related to pensions and early retirement.38 In the current study, 74.6% of patients were <65 years of age (65 years of age is considered the official retirement age, and younger patients were considered economically active), all with a high risk of nontraumatic, lower-limb amputation.
According to 2007 US statistics,30 health care expenditures for the treatment of DM2 were 2.3 times higher than in patients without diabetes. Similarly, expenditure related with absenteeism from work in this type of patient represented $2.6 million USD. DM2-associated disability exerted an influence on unemployment and decreased productivity. In the US, early death was related with a loss of $26.9 million USD, which reflects a loss of $116 million USD for direct costs. Of these, 33% was caused directly by IDFU.30
A group of Swiss and French investigators35 evaluated the economic impact derived from the use of treatment guidelines for the infected diabetic foot. Between 2003 and 2007, these researchers studied the potential effects of bacteriological data (number of microbiologic cultures, number of isolated microorganisms, the frequency of multiresistant bacteria, colonizing flora), costs associated with antibiotic use, and the workload for the microbiology laboratory. The microbiology results and health care costs comprised the most important outcomes in the investigation. The investigators also documented a reduction in the median of bacterial species for each sample (from 4 to 1) was associated with a savings of $20 046 USD derived from a workload reduction for the microbiology laboratory, and $147 536 USD were associated with a reduction in the prescription of unnecessary broad-spectrum antibiotics. Similarly, the current study also found a relationship among use of treatment guidelines at treatment initiation, re-collection of microbiological culture samples, and economic resource savings with an enhanced global quality-of-treatment in IDFU.
Current treatment and its cost-effectiveness have been analyzed in other developing countries. In Turkey, investigators identified an increase in the cost of infected diabetic foot treatments was related to chronic treatments and surgical procedures, especially if the latter were associated with osteomyelitis and subsequent amputation.31 These conditions were associated with therapeutic failure in early microbiological diagnosis and with inefficient use of antibiotics. The investigation also found having an infected diabetic foot was associated with psychosocial trauma and work loss. For third-party payers in Turkey, an increased number of hospital treatments increased total treatment cost. The current study resulted in similar observations: increased percentage of treatment expenditure was associated with prolonged hospital stay.
With regard to the microbiological cultures, it is important to consider the early sampling at hospital admission (ER) before the use of empirical antibiotic treatment. As has been observed through the current Monte Carlo modeling, costs to the health system could be reduced because of less antibiotic use and consequently fewer hospital days would be required. This situation underscores the need for attention to appropriate antibiotic use to enhance the planning of resource utilization.
Observations, disease behavior, or processes are subject to unpredictability. Disease models are often difficult to capture and reproduce, the most important disadvantage being that their probability functions usually cannot be calculated explicitly. Statistical models provide an option to test theories. However, although probabilistic methods such as Monte Carlo modeling attempt to reproduce the disease behavior, in real-life clinic settings, many confounder variables can modify the result. With a specific condition such as an infected ulcer in a diabetic foot, these variable situations usually are related to the human factor in the process of treating a patient. Therefore, model results must be considered carefully.
Infected diabetic foot treatment requires the application of new operational and process-engineering strategies to enhance treatment outcomes and the cost-effective use of resources39; early microbiological culture (within 48 hours of admittance to a health care facility) can be considered an important operational strategy. The multidisciplinary treatment of infected ulcers in the diabetic foot involves the evaluation and establishment of infection severity as a first step to the choice of a specific treatment. Using mathematical models, investigators analyzed the role of microbiological cultures in reducing hospital stay and costs. Early microbiological culture and subsequent antibiotic selection were found to be ancillary factors for reducing hospital stay, antibiotic expenditure, and amputation rates, reducing treatment costs by >30% and enhancing the patient’s outcome. The current study did not consider patient outcomes such as satisfaction or health-related quality of life; these are issues that warrant future study.
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Dr. Balderas-Pena is a titular researcher, Unidad de Investigación Médica en Epidemiología Clínica (UIMEC) of Unidad Médica de Alta Especialidad Hospital de Especialidades Centro Médico Nacional de Occidente (UMAE HE CMNO), Instituto Mexicano del Seguro Social (IMSS), Guadalajara, Jalisco, México. Dr. Sat-Munoz is an associate researcher, UMAE HE CMNO, IMSS; and titular research professor, Departamento de Morfología, Centro Universitario de Ciencias de la Salud, UdG. Ms. Ramírez-Conchas is a research assistant, Unidad de Investigación Social, Epidemiológica y en Servicios de Salud, Delegación Jalisco, IMSS. Mr. Alvarado-Iñiguez is a graduate of and Dr. Garcia de Alba Garcia is Head, Unidad de Investigación Social, Epidemiológica y en Servicios de Salud, Delegación Jalisco, Instituto Mexicano del Seguro Social. Mr. Cruz-Corona is a research fellow, UIMEC, UMAE HE CMNO, IMSS. Mr. Chávez-Hurtadois is Asignature Professor, MBA Program, Centro Universitario de Ciencias Económico Administrativas (CUCEA), UdG. Mr. Chagollán-Ramírez is a titular professor, MBA Program, CUCEA, UdG. Please address correspondence to: Luz-Ma-Adriana Balderas-Peña, MD, PhD, MBA, Research Division, UIMEC, UMAE HE CMNO, IMSS, Belisario Domínguez #1000, Colonia Independencia, Guadalajara, Jalisco CP 44340 Mexico; email: firstname.lastname@example.org.