LEAN LABORATORY PRACTICES DR AYE AYE KHINE CHEMICAL PATHOLOGY NHLS TYGERBERG STELLENBOSCH UNIBERSITY Lab Management workshop 3-6 June 2019

Lean is a process Any change that improves efficiency and patient care Remove waste Standardize Monitor the results (audit) Improve efficiency Harmonize Any change that improves efficiency and patient care (practice the same) Value added services no unnecessary steps, no repeats get better result with same resources Compatible and comparable

Exercise Value added lean practices Give examples Non value added practices (not lean) Who is our customer? What does our customer need?

Waste Required waste or purposeful waste – give example QC/EQA Calibration Health and safety

Identifying waste in complete testing process Pre pre-A Pre-A A Post A Post post- A

Lean process leads to quality Improvement Higher Quality Improved efficiency Reduced TAT Resource Optimisation Space utilization- streamline workflow

How? Workflow analysis Benchmark before you implement Study your processes: Do a survey or audit for a day or week Follow a rack of samples through your lab (choose urgent and routine racks) Benchmark before you implement Run a pilot for a week Understand the impact of the change on the rest of the service Do this before spending money on technology!

Lean process in workflow Replaces processes with more reliable ones Facilitates to make work easier to perform Detects errors when it occurs Eliminates possibility of error (Predicts errors)

From workflow analysis to Data surveys, interviews and audits Discussions with staff can focus on what impacts their day-to-day tasks Charts show real issues Impact of issues on service Use data to Influence decision makers To get attention of staff involved

Spaghetti Maps

Post Lean

Lean Analysis Reveals Opportunities The daily specimen collection run at the hospital began at 6 a.m. The majority of the volume occurred during this hour. This created a bottleneck (Figure 1) that affected all parts of the process.

Value Stream Map of Specimen Collection

Other Areas to be lean to improve workflow LIMS QCQA INVENTORY HR Safety and risk

Basic Lean Rules 1 Do not make changes until you understand the current situation and analyse data Make changes based on data, not emotion! Communicate 360* Include staff in the plan- listen to your staff Facilitate new ideas Work with the suppliers Pilot first and evaluate the change

A Lean Workplace... looks organised and clean Samples flow without bottle necks Results meet TAT Fewer staff needed for the same output Others moved to special bench or sent for workplace skill development Very few rejections No stock outs or expiries Spend less than budgeted  Revenue exceeds expenditure  Staff happy: bonuses and job satisfaction Management happy

Lean process and six sigma

Copy Right- only for training purposes and not permitted for publications

Introduction Just like the “Lean”, Six Sigma is another tool for business process improvement. It was introduced by engineer Bill Smith while working at Motorola in 1986. Jack Welch made it central to his business strategy at General Electric in 1995. Today, it is used in many industrial sectors Sigma in Statistics it is used to measure the variability of a process or a result/product is a dynamic process with the goal being six sigma status TQM can be applied to SS as it makes quality management a more quantitative science

SS calculation needs TAE Total allowable error of many analytes are well published (BV, CLIA, RCPA) To asses the SS of a process the following equation is used: Six Sigma = 𝑻𝒐𝒕𝒂𝒍 𝒂𝒍𝒍𝒐𝒘𝒂𝒃𝒍𝒆 𝒆𝒓𝒓𝒐𝒓 – 𝒃𝒊𝒂𝒔 𝑪𝑽 Which TAE to use? CLIA too loose, BV too tight Do we have any bias?

SS calculation- challenges Example of Cholesterol CLIA defined allowable error= 10% NCEP specification for imprecision- 3% and for bias- 3% (TAE = 7,95 = 8%) Lab’s bias is 2% and CV is 4% SS = 10 –2 4 = 2 SS = ( 8– 2)/4 = 1,5 Bias 4% and CV 2% SS = 10 –4 2 = 3 Lab’s bias is 2% and CV is 2% SS = (10 –2)/2 = 4 SS = (8 –2)/2 = 3

CAP: Q-probe and Q-track to estimate SS Laboratories subscribe to CAP can register for these programs Participate in surveys Analyzed in stats software A summary data from across participating laboratories The defects/errors observed were converted to DPMO for sigma assignment CAP Q-Track another software that looks at longitudinal data collected from serial time points from participating laboratories Areas of survey- qualitative questionnaire response converted to % (Likert scale) Error rates (request form, test names, missing information, errors in logging, delays in logging, missing tubes, leaked tubes, wrong tubes, centrifuge errors, instrument breakdown, IQC errors, reagent errors, dilution errors, reporting errors, discordant critical results, pending tests % etc.)

Conclusion SS can be seen as an important tool for assessing method or process performance, method validation, and in prioritizing resources for analytes that are at risk based on SS